Muon g-2 Estimates. Can One Trust Effective Lagrangians and Global Fits?

International Nuclear Information System (INIS)

Benayoun, M.; DelBuono, L.

2015-07-01

Previous studies have shown that the Hidden Local Symmetry (HLS) Model, supplied with appropriate symmetry breaking mechanisms, provides an Effective Lagrangian (BHLS) which encompasses a large number of processes within a unified framework; a global fit procedure allows for a simultaneous description of the e + e - annihilation into the 6 final states - π + π - , π 0 γ, ηγ, π + π - π 0 , K + K - , K L K S - and includes the dipion spectrum in the τ decay and some more light meson decay partial widths. The contribution to the muon anomalous magnetic moment a th μ of these annihilation channels over the range of validity of the HLS model (up to 1.05 GeV) is found much improved compared to its partner derived from integrating the measured spectra directly. However, most spectra for the process e + e - → π + π - undergo overall scale uncertainties which dominate the other sources, and one may suspect some bias in the dipion contribution to a th μ . However, an iterated fit algorithm, shown to lead to unbiased results by a Monte Carlo study, is defined and applied succesfully to the e + e - → π + π - data samples from CMD2, SND, KLOE (including the latest sample) and BaBar. The iterated fit solution is shown to be further improved and leads to a value for a μ different from aexp above the 4σ level. The contribution of the π + π - intermediate state up to 1.05 GeV to a μ derived from the iterated fit benefits from an uncertainty about 3 times smaller than the corresponding usual estimate. Therefore, global fit techniques are shown to work and lead to improved unbiased results. The main issue raised in this study and the kind of solution proposed may be of concern for other data driven methods when the data samples are dominated by global normalization uncertainties.

Correcting Model Fit Criteria for Small Sample Latent Growth Models with Incomplete Data

Science.gov (United States)

McNeish, Daniel; Harring, Jeffrey R.

2017-01-01

To date, small sample problems with latent growth models (LGMs) have not received the amount of attention in the literature as related mixed-effect models (MEMs). Although many models can be interchangeably framed as a LGM or a MEM, LGMs uniquely provide criteria to assess global data-model fit. However, previous studies have demonstrated poor…

arXiv Updated Global SMEFT Fit to Higgs, Diboson and Electroweak Data

CERN Document Server

Ellis, John; Sanz, Verónica; You, Tevong

The ATLAS and CMS collaborations have recently released significant new data on Higgs and diboson production in LHC Run 2. Measurements of Higgs properties have improved in many channels, while kinematic information for $h \\to \\gamma\\gamma$ and $h \\to ZZ$ can now be more accurately incorporated in fits using the STXS method, and $W^+ W^-$ diboson production at high $p_T$ gives new sensitivity to deviations from the Standard Model. We have performed an updated global fit to precision electroweak data, $W^+W^-$ measurements at LEP, and Higgs and diboson data from Runs 1 and 2 of the LHC in the framework of the Standard Model Effective Field Theory (SMEFT), allowing all coefficients to vary across the combined dataset, and present the results in both the Warsaw and SILH operator bases. We exhibit the improvement in the constraints on operator coefficients provided by the LHC Run 2 data, and discuss the correlations between them. We also explore the constraints our fit results impose on several models of physics ...

A Fast Global Fitting Algorithm for Fluorescence Lifetime Imaging Microscopy Based on Image Segmentation

OpenAIRE

Pelet, S.; Previte, M.J.R.; Laiho, L.H.; So, P.T. C.

2004-01-01

Global fitting algorithms have been shown to improve effectively the accuracy and precision of the analysis of fluorescence lifetime imaging microscopy data. Global analysis performs better than unconstrained data fitting when prior information exists, such as the spatial invariance of the lifetimes of individual fluorescent species. The highly coupled nature of global analysis often results in a significantly slower convergence of the data fitting algorithm as compared with unconstrained ana...

Fitting PAC spectra with stochastic models: PolyPacFit

Energy Technology Data Exchange (ETDEWEB)

Zacate, M. O., E-mail: zacatem1@nku.edu [Northern Kentucky University, Department of Physics and Geology (United States); Evenson, W. E. [Utah Valley University, College of Science and Health (United States); Newhouse, R.; Collins, G. S. [Washington State University, Department of Physics and Astronomy (United States)

2010-04-15

PolyPacFit is an advanced fitting program for time-differential perturbed angular correlation (PAC) spectroscopy. It incorporates stochastic models and provides robust options for customization of fits. Notable features of the program include platform independence and support for (1) fits to stochastic models of hyperfine interactions, (2) user-defined constraints among model parameters, (3) fits to multiple spectra simultaneously, and (4) any spin nuclear probe.

A new approach to a global fit of the CKM matrix

Energy Technology Data Exchange (ETDEWEB)

Hoecker, A.; Lacker, H.; Laplace, S. [Laboratoire de l' Accelerateur Lineaire, 91 - Orsay (France); Le Diberder, F. [Laboratoire de Physique Nucleaire et des Hautes Energies, 75 - Paris (France)

2001-05-01

We report on a new approach to a global CKM matrix analysis taking into account most recent experimental and theoretical results. The statistical framework (Rfit) developed in this paper advocates frequentist statistics. Other approaches, such as Bayesian statistics or the 95% CL scan method are also discussed. We emphasize the distinction of a model testing and a model dependent, metrological phase in which the various parameters of the theory are estimated. Measurements and theoretical parameters entering the global fit are thoroughly discussed, in particular with respect to their theoretical uncertainties. Graphical results for confidence levels are drawn in various one and two-dimensional parameter spaces. Numerical results are provided for all relevant CKM parameterizations, the CKM elements and theoretical input parameters. Predictions for branching ratios of rare K and B meson decays are obtained. A simple, predictive SUSY extension of the Standard Model is discussed. (authors)

Local and Global Function Model of the Liver

Energy Technology Data Exchange (ETDEWEB)

Wang, Hesheng, E-mail: hesheng@umich.edu [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Feng, Mary [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Jackson, Andrew [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York (United States); Ten Haken, Randall K.; Lawrence, Theodore S. [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Cao, Yue [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Department of Radiology, University of Michigan, Ann Arbor, Michigan (United States); Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan (United States)

2016-01-01

Purpose: To develop a local and global function model in the liver based on regional and organ function measurements to support individualized adaptive radiation therapy (RT). Methods and Materials: A local and global model for liver function was developed to include both functional volume and the effect of functional variation of subunits. Adopting the assumption of parallel architecture in the liver, the global function was composed of a sum of local function probabilities of subunits, varying between 0 and 1. The model was fit to 59 datasets of liver regional and organ function measures from 23 patients obtained before, during, and 1 month after RT. The local function probabilities of subunits were modeled by a sigmoid function in relating to MRI-derived portal venous perfusion values. The global function was fitted to a logarithm of an indocyanine green retention rate at 15 minutes (an overall liver function measure). Cross-validation was performed by leave-m-out tests. The model was further evaluated by fitting to the data divided according to whether the patients had hepatocellular carcinoma (HCC) or not. Results: The liver function model showed that (1) a perfusion value of 68.6 mL/(100 g · min) yielded a local function probability of 0.5; (2) the probability reached 0.9 at a perfusion value of 98 mL/(100 g · min); and (3) at a probability of 0.03 [corresponding perfusion of 38 mL/(100 g · min)] or lower, the contribution to global function was lost. Cross-validations showed that the model parameters were stable. The model fitted to the data from the patients with HCC indicated that the same amount of portal venous perfusion was translated into less local function probability than in the patients with non-HCC tumors. Conclusions: The developed liver function model could provide a means to better assess individual and regional dose-responses of hepatic functions, and provide guidance for individualized treatment planning of RT.

Global Fits of the Electroweak Standard Theory: Past, Present and Future

CERN Document Server

Baak, M; Mönig, K

2016-01-01

The last decades have seen tremendous progress in the experimental techniques for measuring key observables of the Standard Theory (ST) as well as in theoretical calculations that has led to highly precise predictions of these observables. Global electroweak fits of the ST compare the precision measurements of electroweak observables from lepton and hadron colliders at CERN and elsewhere with accurate theoretical predictions of the ST calculated at multi-loop level. For a long time, global fits have been used to assess the validity of the ST and to constrain indirectly (by exploiting contributions from quantum loops) the remaining free ST parameters, like the masses of the top quark and Higgs boson before their direct discovery. With the discovery of the Higgs boson at the Large Hadron Collider (LHC), the electroweak sector of the ST is now complete and all fundamental ST parameters are known. Hence the global fits are a powerful tool to probe the internal consistency of the ST, to predict ST parameters with...

A vertically resolved, global, gap-free ozone database for assessing or constraining global climate model simulations

Directory of Open Access Journals (Sweden)

G. E. Bodeker

2013-02-01

Full Text Available High vertical resolution ozone measurements from eight different satellite-based instruments have been merged with data from the global ozonesonde network to calculate monthly mean ozone values in 5° latitude zones. These ''Tier 0'' ozone number densities and ozone mixing ratios are provided on 70 altitude levels (1 to 70 km and on 70 pressure levels spaced ~ 1 km apart (878.4 hPa to 0.046 hPa. The Tier 0 data are sparse and do not cover the entire globe or altitude range. To provide a gap-free database, a least squares regression model is fitted to the Tier 0 data and then evaluated globally. The regression model fit coefficients are expanded in Legendre polynomials to account for latitudinal structure, and in Fourier series to account for seasonality. Regression model fit coefficient patterns, which are two dimensional fields indexed by latitude and month of the year, from the N-th vertical level serve as an initial guess for the fit at the N + 1-th vertical level. The initial guess field for the first fit level (20 km/58.2 hPa was derived by applying the regression model to total column ozone fields. Perturbations away from the initial guess are captured through the Legendre and Fourier expansions. By applying a single fit at each level, and using the approach of allowing the regression fits to change only slightly from one level to the next, the regression is less sensitive to measurement anomalies at individual stations or to individual satellite-based instruments. Particular attention is paid to ensuring that the low ozone abundances in the polar regions are captured. By summing different combinations of contributions from different regression model basis functions, four different ''Tier 1'' databases have been compiled for different intended uses. This database is suitable for assessing ozone fields from chemistry-climate model simulations or for providing the ozone boundary conditions for global climate model simulations that do not

The inert doublet model in the light of Fermi-LAT gamma-ray data: a global fit analysis

Science.gov (United States)

Eiteneuer, Benedikt; Goudelis, Andreas; Heisig, Jan

2017-09-01

We perform a global fit within the inert doublet model taking into account experimental observables from colliders, direct and indirect dark matter searches and theoretical constraints. In particular, we consider recent results from searches for dark matter annihilation-induced gamma-rays in dwarf spheroidal galaxies and relax the assumption that the inert doublet model should account for the entire dark matter in the Universe. We, moreover, study in how far the model is compatible with a possible dark matter explanation of the so-called Galactic center excess. We find two distinct parameter space regions that are consistent with existing constraints and can simultaneously explain the excess: One with dark matter masses near the Higgs resonance and one around 72 GeV where dark matter annihilates predominantly into pairs of virtual electroweak gauge bosons via the four-vertex arising from the inert doublet's kinetic term. We briefly discuss future prospects to probe these scenarios.

The inert doublet model in the light of Fermi-LAT gamma-ray data: a global fit analysis

Energy Technology Data Exchange (ETDEWEB)

Eiteneuer, Benedikt; Heisig, Jan [RWTH Aachen University, Institute for Theoretical Particle Physics and Cosmology, Aachen (Germany); Goudelis, Andreas [UMR 7589 CNRS and UPMC, Laboratoire de Physique Theorique et Hautes Energies (LPTHE), Paris (France)

2017-09-15

We perform a global fit within the inert doublet model taking into account experimental observables from colliders, direct and indirect dark matter searches and theoretical constraints. In particular, we consider recent results from searches for dark matter annihilation-induced gamma-rays in dwarf spheroidal galaxies and relax the assumption that the inert doublet model should account for the entire dark matter in the Universe. We, moreover, study in how far the model is compatible with a possible dark matter explanation of the so-called Galactic center excess. We find two distinct parameter space regions that are consistent with existing constraints and can simultaneously explain the excess: One with dark matter masses near the Higgs resonance and one around 72 GeV where dark matter annihilates predominantly into pairs of virtual electroweak gauge bosons via the four-vertex arising from the inert doublet's kinetic term. We briefly discuss future prospects to probe these scenarios. (orig.)

An Analysis of Yip's Global Strategy Model, Using Coca-Cola ...

African Journals Online (AJOL)

Analysis of the selected business cases suggest a weak fit between the Yip model of a truly Global strategy ... like Coca-Cola in the beverage industry for effective implementation of a global strategy. ... Keywords: Global Strategy, Leadership.

A fast global fitting algorithm for fluorescence lifetime imaging microscopy based on image segmentation.

Science.gov (United States)

Pelet, S; Previte, M J R; Laiho, L H; So, P T C

2004-10-01

Global fitting algorithms have been shown to improve effectively the accuracy and precision of the analysis of fluorescence lifetime imaging microscopy data. Global analysis performs better than unconstrained data fitting when prior information exists, such as the spatial invariance of the lifetimes of individual fluorescent species. The highly coupled nature of global analysis often results in a significantly slower convergence of the data fitting algorithm as compared with unconstrained analysis. Convergence speed can be greatly accelerated by providing appropriate initial guesses. Realizing that the image morphology often correlates with fluorophore distribution, a global fitting algorithm has been developed to assign initial guesses throughout an image based on a segmentation analysis. This algorithm was tested on both simulated data sets and time-domain lifetime measurements. We have successfully measured fluorophore distribution in fibroblasts stained with Hoechst and calcein. This method further allows second harmonic generation from collagen and elastin autofluorescence to be differentiated in fluorescence lifetime imaging microscopy images of ex vivo human skin. On our experimental measurement, this algorithm increased convergence speed by over two orders of magnitude and achieved significantly better fits. Copyright 2004 Biophysical Society

Implicit Active Contours Driven by Local and Global Image Fitting Energy for Image Segmentation and Target Localization

Directory of Open Access Journals (Sweden)

Xiaosheng Yu

2013-01-01

Full Text Available We propose a novel active contour model in a variational level set formulation for image segmentation and target localization. We combine a local image fitting term and a global image fitting term to drive the contour evolution. Our model can efficiently segment the images with intensity inhomogeneity with the contour starting anywhere in the image. In its numerical implementation, an efficient numerical schema is used to ensure sufficient numerical accuracy. We validated its effectiveness in numerous synthetic images and real images, and the promising experimental results show its advantages in terms of accuracy, efficiency, and robustness.

Assessing a moderating effect and the global fit of a PLS model on online trading

Directory of Open Access Journals (Sweden)

Juan J. García-Machado

2017-12-01

Full Text Available This paper proposes a PLS Model for the study of Online Trading. Traditional investing has experienced a revolution due to the rise of e-trading services that enable investors to use Internet conduct secure trading. On the hand, model results show that there is a positive, direct and statistically significant relationship between personal outcome expectations, perceived relative advantage, shared vision and economy-based trust with the quality of knowledge. On the other hand, trading frequency and portfolio performance has also this relationship. After including the investor’s income and financial wealth (IFW as moderating effect, the PLS model was enhanced, and we found that the interaction term is negative and statistically significant, so, higher IFW levels entail a weaker relationship between trading frequency and portfolio performance and vice-versa. Finally, with regard to the goodness of overall model fit measures, they showed that the model is fit for SRMR and dG measures, so it is likely that the model is true.

A Stepwise Fitting Procedure for automated fitting of Ecopath with Ecosim models

Directory of Open Access Journals (Sweden)

Erin Scott

2016-01-01

Full Text Available The Stepwise Fitting Procedure automates testing of alternative hypotheses used for fitting Ecopath with Ecosim (EwE models to observation reference data (Mackinson et al. 2009. The calibration of EwE model predictions to observed data is important to evaluate any model that will be used for ecosystem based management. Thus far, the model fitting procedure in EwE has been carried out manually: a repetitive task involving setting >1000 specific individual searches to find the statistically ‘best fit’ model. The novel fitting procedure automates the manual procedure therefore producing accurate results and lets the modeller concentrate on investigating the ‘best fit’ model for ecological accuracy.

The effect of measurement quality on targeted structural model fit indices: A comment on Lance, Beck, Fan, and Carter (2016).

Science.gov (United States)

McNeish, Daniel; Hancock, Gregory R

2018-03-01

Lance, Beck, Fan, and Carter (2016) recently advanced 6 new fit indices and associated cutoff values for assessing data-model fit in the structural portion of traditional latent variable path models. The authors appropriately argued that, although most researchers' theoretical interest rests with the latent structure, they still rely on indices of global model fit that simultaneously assess both the measurement and structural portions of the model. As such, Lance et al. proposed indices intended to assess the structural portion of the model in isolation of the measurement model. Unfortunately, although these strategies separate the assessment of the structure from the fit of the measurement model, they do not isolate the structure's assessment from the quality of the measurement model. That is, even with a perfectly fitting measurement model, poorer quality (i.e., less reliable) measurements will yield a more favorable verdict regarding structural fit, whereas better quality (i.e., more reliable) measurements will yield a less favorable structural assessment. This phenomenon, referred to by Hancock and Mueller (2011) as the reliability paradox, affects not only traditional global fit indices but also those structural indices proposed by Lance et al. as well. Fortunately, as this comment will clarify, indices proposed by Hancock and Mueller help to mitigate this problem and allow the structural portion of the model to be assessed independently of both the fit of the measurement model as well as the quality of indicator variables contained therein. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The globalization of training in adolescent health and medicine: one size does not fit all.

Science.gov (United States)

Leslie, Karen

2016-08-01

Adolescent medicine across the globe is practiced within a variety of healthcare models, with the shared vision of the promotion of optimal health outcomes for adolescents. In the past decade, there has been a call for transformation in how health professionals are trained, with recommendations that there be adoption of a global outlook, a multiprofessional perspective and a systems approach that considers the connections between education and health systems. Many individuals and groups are now examining how best to accomplish this educational reform. There are tensions between the call for globally accepted standards of education models and practice (a one-size fits all approach) and the need to promote the ability for education practices to be interpreted and transformed to best suit local contexts. This paper discusses some of the key considerations for 'importing' training program models for adolescent health and medicine, including the importance of cultural alignment and the utilization of best evidence and practice in health professions education.

Global fits of the two-loop renormalized Two-Higgs-Doublet model with soft Z 2 breaking

Science.gov (United States)

Chowdhury, Debtosh; Eberhardt, Otto

2015-11-01

We determine the next-to-leading order renormalization group equations for the Two-Higgs-Doublet model with a softly broken Z 2 symmetry and CP conservation in the scalar potential. We use them to identify the parameter regions which are stable up to the Planck scale and find that in this case the quartic couplings of the Higgs potential cannot be larger than 1 in magnitude and that the absolute values of the S-matrix eigenvalues cannot exceed 2 .5 at the electroweak symmetry breaking scale. Interpreting the 125 GeV resonance as the light CP -even Higgs eigenstate, we combine stability constraints, electroweak precision and flavour observables with the latest ATLAS and CMS data on Higgs signal strengths and heavy Higgs searches in global parameter fits to all four types of Z 2 symmetry. We quantify the maximal deviations from the alignment limit and find that in type II and Y the mass of the heavy CP -even ( CP -odd) scalar cannot be smaller than 340 GeV (360 GeV). Also, we pinpoint the physical parameter regions compatible with a stable scalar potential up to the Planck scale. Motivated by the question how natural a Higgs mass of 125 GeV can be in the context of a Two-Higgs-Doublet model, we also address the hierarchy problem and find that the Two-Higgs-Doublet model does not offer a perturbative solution to it beyond 5 TeV.

The universal Higgs fit

DEFF Research Database (Denmark)

Giardino, P. P.; Kannike, K.; Masina, I.

2014-01-01

We perform a state-of-the-art global fit to all Higgs data. We synthesise them into a 'universal' form, which allows to easily test any desired model. We apply the proposed methodology to extract from data the Higgs branching ratios, production cross sections, couplings and to analyse composite...... Higgs models, models with extra Higgs doublets, supersymmetry, extra particles in the loops, anomalous top couplings, and invisible Higgs decays into Dark Matter. Best fit regions lie around the Standard Model predictions and are well approximated by our 'universal' fit. Latest data exclude the dilaton...... as an alternative to the Higgs, and disfavour fits with negative Yukawa couplings. We derive for the first time the SM Higgs boson mass from the measured rates, rather than from the peak positions, obtaining M-h = 124.4 +/- 1.6 GeV....

Fitting the Phenomenological MSSM

CERN Document Server

AbdusSalam, S S; Quevedo, F; Feroz, F; Hobson, M

2010-01-01

We perform a global Bayesian fit of the phenomenological minimal supersymmetric standard model (pMSSM) to current indirect collider and dark matter data. The pMSSM contains the most relevant 25 weak-scale MSSM parameters, which are simultaneously fit using `nested sampling' Monte Carlo techniques in more than 15 years of CPU time. We calculate the Bayesian evidence for the pMSSM and constrain its parameters and observables in the context of two widely different, but reasonable, priors to determine which inferences are robust. We make inferences about sparticle masses, the sign of the $\\mu$ parameter, the amount of fine tuning, dark matter properties and the prospects for direct dark matter detection without assuming a restrictive high-scale supersymmetry breaking model. We find the inferred lightest CP-even Higgs boson mass as an example of an approximately prior independent observable. This analysis constitutes the first statistically convergent pMSSM global fit to all current data.

Error estimation and global fitting in transverse-relaxation dispersion experiments to determine chemical-exchange parameters

International Nuclear Information System (INIS)

Ishima, Rieko; Torchia, Dennis A.

2005-01-01

Off-resonance effects can introduce significant systematic errors in R 2 measurements in constant-time Carr-Purcell-Meiboom-Gill (CPMG) transverse relaxation dispersion experiments. For an off-resonance chemical shift of 500 Hz, 15 N relaxation dispersion profiles obtained from experiment and computer simulation indicated a systematic error of ca. 3%. This error is three- to five-fold larger than the random error in R 2 caused by noise. Good estimates of total R 2 uncertainty are critical in order to obtain accurate estimates in optimized chemical exchange parameters and their uncertainties derived from χ 2 minimization of a target function. Here, we present a simple empirical approach that provides a good estimate of the total error (systematic + random) in 15 N R 2 values measured for the HIV protease. The advantage of this empirical error estimate is that it is applicable even when some of the factors that contribute to the off-resonance error are not known. These errors are incorporated into a χ 2 minimization protocol, in which the Carver-Richards equation is used fit the observed R 2 dispersion profiles, that yields optimized chemical exchange parameters and their confidence limits. Optimized parameters are also derived, using the same protein sample and data-fitting protocol, from 1 H R 2 measurements in which systematic errors are negligible. Although 1 H and 15 N relaxation profiles of individual residues were well fit, the optimized exchange parameters had large uncertainties (confidence limits). In contrast, when a single pair of exchange parameters (the exchange lifetime, τ ex , and the fractional population, p a ), were constrained to globally fit all R 2 profiles for residues in the dimer interface of the protein, confidence limits were less than 8% for all optimized exchange parameters. In addition, F-tests showed that quality of the fits obtained using τ ex , p a as global parameters were not improved when these parameters were free to fit the R

An algorithm to provide UK global radiation for use with models

International Nuclear Information System (INIS)

Hamer, P.J.C.

1999-01-01

Decision support systems which include crop growth models require long-term average values of global radiation to simulate future expected growth. Global radiation is rarely available as there are relatively few meteorological stations with long-term records and so interpolation between sites is difficult. Global radiation data across a good geographical spread throughout the UK were obtained and sub-divided into ‘coastal’ and ‘inland’ sites. Monthly means of global radiation (S) were extracted and analysed in relation to irradiance in the absence of atmosphere (S o ) calculated from site latitude and the time of year. The ratio S/S o was fitted to the month of the year (t) and site latitude using a nonlinear fit function in which 90% of the variance was accounted for. An algorithm is presented which provides long-term daily values of global radiation from information on latitude, time of year and whether the site is inland or close to the coast. (author)

Alternative difference analysis scheme combining R-space EXAFS fit with global optimization XANES fit for X-ray transient absorption spectroscopy.

Science.gov (United States)

Zhan, Fei; Tao, Ye; Zhao, Haifeng

2017-07-01

Time-resolved X-ray absorption spectroscopy (TR-XAS), based on the laser-pump/X-ray-probe method, is powerful in capturing the change of the geometrical and electronic structure of the absorbing atom upon excitation. TR-XAS data analysis is generally performed on the laser-on minus laser-off difference spectrum. Here, a new analysis scheme is presented for the TR-XAS difference fitting in both the extended X-ray absorption fine-structure (EXAFS) and the X-ray absorption near-edge structure (XANES) regions. R-space EXAFS difference fitting could quickly provide the main quantitative structure change of the first shell. The XANES fitting part introduces a global non-derivative optimization algorithm and optimizes the local structure change in a flexible way where both the core XAS calculation package and the search method in the fitting shell are changeable. The scheme was applied to the TR-XAS difference analysis of Fe(phen) 3 spin crossover complex and yielded reliable distance change and excitation population.

Calibration of a simple and a complex model of global marine biogeochemistry

Science.gov (United States)

Kriest, Iris

2017-11-01

The assessment of the ocean biota's role in climate change is often carried out with global biogeochemical ocean models that contain many components and involve a high level of parametric uncertainty. Because many data that relate to tracers included in a model are only sparsely observed, assessment of model skill is often restricted to tracers that can be easily measured and assembled. Examination of the models' fit to climatologies of inorganic tracers, after the models have been spun up to steady state, is a common but computationally expensive procedure to assess model performance and reliability. Using new tools that have become available for global model assessment and calibration in steady state, this paper examines two different model types - a complex seven-component model (MOPS) and a very simple four-component model (RetroMOPS) - for their fit to dissolved quantities. Before comparing the models, a subset of their biogeochemical parameters has been optimised against annual-mean nutrients and oxygen. Both model types fit the observations almost equally well. The simple model contains only two nutrients: oxygen and dissolved organic phosphorus (DOP). Its misfit and large-scale tracer distributions are sensitive to the parameterisation of DOP production and decay. The spatio-temporal decoupling of nitrogen and oxygen, and processes involved in their uptake and release, renders oxygen and nitrate valuable tracers for model calibration. In addition, the non-conservative nature of these tracers (with respect to their upper boundary condition) introduces the global bias (fixed nitrogen and oxygen inventory) as a useful additional constraint on model parameters. Dissolved organic phosphorus at the surface behaves antagonistically to phosphate, and suggests that observations of this tracer - although difficult to measure - may be an important asset for model calibration.

Measured, modeled, and causal conceptions of fitness

Science.gov (United States)

Abrams, Marshall

2012-01-01

This paper proposes partial answers to the following questions: in what senses can fitness differences plausibly be considered causes of evolution?What relationships are there between fitness concepts used in empirical research, modeling, and abstract theoretical proposals? How does the relevance of different fitness concepts depend on research questions and methodological constraints? The paper develops a novel taxonomy of fitness concepts, beginning with type fitness (a property of a genotype or phenotype), token fitness (a property of a particular individual), and purely mathematical fitness. Type fitness includes statistical type fitness, which can be measured from population data, and parametric type fitness, which is an underlying property estimated by statistical type fitnesses. Token fitness includes measurable token fitness, which can be measured on an individual, and tendential token fitness, which is assumed to be an underlying property of the individual in its environmental circumstances. Some of the paper's conclusions can be outlined as follows: claims that fitness differences do not cause evolution are reasonable when fitness is treated as statistical type fitness, measurable token fitness, or purely mathematical fitness. Some of the ways in which statistical methods are used in population genetics suggest that what natural selection involves are differences in parametric type fitnesses. Further, it's reasonable to think that differences in parametric type fitness can cause evolution. Tendential token fitnesses, however, are not themselves sufficient for natural selection. Though parametric type fitnesses are typically not directly measurable, they can be modeled with purely mathematical fitnesses and estimated by statistical type fitnesses, which in turn are defined in terms of measurable token fitnesses. The paper clarifies the ways in which fitnesses depend on pragmatic choices made by researchers. PMID:23112804

Brief communication: human cranial variation fits iterative founder effect model with African origin.

Science.gov (United States)

von Cramon-Taubadel, Noreen; Lycett, Stephen J

2008-05-01

Recent studies comparing craniometric and neutral genetic affinity matrices have concluded that, on average, human cranial variation fits a model of neutral expectation. While human craniometric and genetic data fit a model of isolation by geographic distance, it is not yet clear whether this is due to geographically mediated gene flow or human dispersal events. Recently, human genetic data have been shown to fit an iterative founder effect model of dispersal with an African origin, in line with the out-of-Africa replacement model for modern human origins, and Manica et al. (Nature 448 (2007) 346-349) have demonstrated that human craniometric data also fit this model. However, in contrast with the neutral model of cranial evolution suggested by previous studies, Manica et al. (2007) made the a priori assumption that cranial form has been subject to climatically driven natural selection and therefore correct for climate prior to conducting their analyses. Here we employ a modified theoretical and methodological approach to test whether human cranial variability fits the iterative founder effect model. In contrast with Manica et al. (2007) we employ size-adjusted craniometric variables, since climatic factors such as temperature have been shown to correlate with aspects of cranial size. Despite these differences, we obtain similar results to those of Manica et al. (2007), with up to 26% of global within-population craniometric variation being explained by geographic distance from sub-Saharan Africa. Comparative analyses using non-African origins do not yield significant results. The implications of these results are discussed in the light of the modern human origins debate. (c) 2007 Wiley-Liss, Inc.

Kinetic modeling and fitting software for interconnected reaction schemes: VisKin.

Science.gov (United States)

Zhang, Xuan; Andrews, Jared N; Pedersen, Steen E

2007-02-15

Reaction kinetics for complex, highly interconnected kinetic schemes are modeled using analytical solutions to a system of ordinary differential equations. The algorithm employs standard linear algebra methods that are implemented using MatLab functions in a Visual Basic interface. A graphical user interface for simple entry of reaction schemes facilitates comparison of a variety of reaction schemes. To ensure microscopic balance, graph theory algorithms are used to determine violations of thermodynamic cycle constraints. Analytical solutions based on linear differential equations result in fast comparisons of first order kinetic rates and amplitudes as a function of changing ligand concentrations. For analysis of higher order kinetics, we also implemented a solution using numerical integration. To determine rate constants from experimental data, fitting algorithms that adjust rate constants to fit the model to imported data were implemented using the Levenberg-Marquardt algorithm or using Broyden-Fletcher-Goldfarb-Shanno methods. We have included the ability to carry out global fitting of data sets obtained at varying ligand concentrations. These tools are combined in a single package, which we have dubbed VisKin, to guide and analyze kinetic experiments. The software is available online for use on PCs.

Fitting neuron models to spike trains

Directory of Open Access Journals (Sweden)

Cyrille eRossant

2011-02-01

Full Text Available Computational modeling is increasingly used to understand the function of neural circuitsin systems neuroscience.These studies require models of individual neurons with realisticinput-output properties.Recently, it was found that spiking models can accurately predict theprecisely timed spike trains produced by cortical neurons in response tosomatically injected currents,if properly fitted. This requires fitting techniques that are efficientand flexible enough to easily test different candidate models.We present a generic solution, based on the Brian simulator(a neural network simulator in Python, which allowsthe user to define and fit arbitrary neuron models to electrophysiological recordings.It relies on vectorization and parallel computing techniques toachieve efficiency.We demonstrate its use on neural recordings in the barrel cortex andin the auditory brainstem, and confirm that simple adaptive spiking modelscan accurately predict the response of cortical neurons. Finally, we show how a complexmulticompartmental model can be reduced to a simple effective spiking model.

Induced subgraph searching for geometric model fitting

Science.gov (United States)

Xiao, Fan; Xiao, Guobao; Yan, Yan; Wang, Xing; Wang, Hanzi

2017-11-01

In this paper, we propose a novel model fitting method based on graphs to fit and segment multiple-structure data. In the graph constructed on data, each model instance is represented as an induced subgraph. Following the idea of pursuing the maximum consensus, the multiple geometric model fitting problem is formulated as searching for a set of induced subgraphs including the maximum union set of vertices. After the generation and refinement of the induced subgraphs that represent the model hypotheses, the searching process is conducted on the "qualified" subgraphs. Multiple model instances can be simultaneously estimated by solving a converted problem. Then, we introduce the energy evaluation function to determine the number of model instances in data. The proposed method is able to effectively estimate the number and the parameters of model instances in data severely corrupted by outliers and noises. Experimental results on synthetic data and real images validate the favorable performance of the proposed method compared with several state-of-the-art fitting methods.

Global thermal models of the lithosphere

Science.gov (United States)

Cammarano, F.; Guerri, M.

2017-12-01

Unraveling the thermal structure of the outermost shell of our planet is key for understanding its evolution. We obtain temperatures from interpretation of global shear-velocity (VS) models. Long-wavelength thermal structure is well determined by seismic models and only slightly affected by compositional effects and uncertainties in mineral-physics properties. Absolute temperatures and gradients with depth, however, are not well constrained. Adding constraints from petrology, heat-flow observations and thermal evolution of oceanic lithosphere help to better estimate absolute temperatures in the top part of the lithosphere. We produce global thermal models of the lithosphere at different spatial resolution, up to spherical-harmonics degree 24, and provide estimated standard deviations. We provide purely seismic thermal (TS) model and hybrid models where temperatures are corrected with steady-state conductive geotherms on continents and cooling model temperatures on oceanic regions. All relevant physical properties, with the exception of thermal conductivity, are based on a self-consistent thermodynamical modelling approach. Our global thermal models also include density and compressional-wave velocities (VP) as obtained either assuming no lateral variations in composition or a simple reference 3-D compositional structure, which takes into account a chemically depleted continental lithosphere. We found that seismically-derived temperatures in continental lithosphere fit well, overall, with continental geotherms, but a large variation in radiogenic heat is required to reconcile them with heat flow (long wavelength) observations. Oceanic shallow lithosphere below mid-oceanic ridges and young oceans is colder than expected, confirming the possible presence of a dehydration boundary around 80 km depth already suggested in previous studies. The global thermal models should serve as the basis to move at a smaller spatial scale, where additional thermo-chemical variations

Analytical fitting model for rough-surface BRDF.

Science.gov (United States)

Renhorn, Ingmar G E; Boreman, Glenn D

2008-08-18

A physics-based model is developed for rough surface BRDF, taking into account angles of incidence and scattering, effective index, surface autocovariance, and correlation length. Shadowing is introduced on surface correlation length and reflectance. Separate terms are included for surface scatter, bulk scatter and retroreflection. Using the FindFit function in Mathematica, the functional form is fitted to BRDF measurements over a wide range of incident angles. The model has fourteen fitting parameters; once these are fixed, the model accurately describes scattering data over two orders of magnitude in BRDF without further adjustment. The resulting analytical model is convenient for numerical computations.

Incorporating doubly resonant $W^\\pm$ data in a global fit of SMEFT parameters to lift flat directions

CERN Document Server

Berthier, Laure; Trott, Michael

2016-09-27

We calculate the double pole contribution to two to four fermion scattering through $W^{\\pm}$ currents at tree level in the Standard Model Effective Field Theory (SMEFT). We assume all fermions to be massless, $\\rm U(3)^5$ flavour and $\\rm CP$ symmetry. Using this result, we update the global constraint picture on SMEFT parameters including LEPII data on these charged current processes, and also include modifications to our fit procedure motivated by a companion paper focused on $W^{\\pm}$ mass extractions. The fit reported is now to 177 observables and emphasises the need for a consistent inclusion of theoretical errors, and a consistent treatment of observables. Including charged current data lifts the two-fold degeneracy previously encountered in LEP (and lower energy) data, and allows us to set simultaneous constraints on 20 of 53 Wilson coefficients in the SMEFT, consistent with our assumptions. This allows the model independent inclusion of LEP data in SMEFT studies at LHC, which are projected into the S...

Modeling Evolution on Nearly Neutral Network Fitness Landscapes

Science.gov (United States)

Yakushkina, Tatiana; Saakian, David B.

2017-08-01

To describe virus evolution, it is necessary to define a fitness landscape. In this article, we consider the microscopic models with the advanced version of neutral network fitness landscapes. In this problem setting, we suppose a fitness difference between one-point mutation neighbors to be small. We construct a modification of the Wright-Fisher model, which is related to ordinary infinite population models with nearly neutral network fitness landscape at the large population limit. From the microscopic models in the realistic sequence space, we derive two versions of nearly neutral network models: with sinks and without sinks. We claim that the suggested model describes the evolutionary dynamics of RNA viruses better than the traditional Wright-Fisher model with few sequences.

Fitting Hidden Markov Models to Psychological Data

Directory of Open Access Journals (Sweden)

Ingmar Visser

2002-01-01

Full Text Available Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive statistics for model selection and model assessment are lacking in the psychological literature. We present model selection and model assessment statistics that are particularly useful in applying hidden Markov models in psychology. These statistics are presented and evaluated by simulation studies for a toy example. We compare AIC, BIC and related criteria and introduce a prediction error measure for assessing goodness-of-fit. In a simulation study, two methods of fitting equality constraints are compared. In two illustrative examples with experimental data we apply selection criteria, fit models with constraints and assess goodness-of-fit. First, data from a concept identification task is analyzed. Hidden Markov models provide a flexible approach to analyzing such data when compared to other modeling methods. Second, a novel application of hidden Markov models in implicit learning is presented. Hidden Markov models are used in this context to quantify knowledge that subjects express in an implicit learning task. This method of analyzing implicit learning data provides a comprehensive approach for addressing important theoretical issues in the field.

Statistical topography of fitness landscapes

OpenAIRE

Franke, Jasper

2011-01-01

Fitness landscapes are generalized energy landscapes that play an important conceptual role in evolutionary biology. These landscapes provide a relation between the genetic configuration of an organism and that organism’s adaptive properties. In this work, global topographical features of these fitness landscapes are investigated using theoretical models. The resulting predictions are compared to empirical landscapes. It is shown that these landscapes allow, at least with respe...

Random-growth urban model with geographical fitness

Science.gov (United States)

Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

2012-12-01

This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

Using the Flipchem Photochemistry Model When Fitting Incoherent Scatter Radar Data

Science.gov (United States)

Reimer, A. S.; Varney, R. H.

2017-12-01

The North face Resolute Bay Incoherent Scatter Radar (RISR-N) routinely images the dynamics of the polar ionosphere, providing measurements of the plasma density, electron temperature, ion temperature, and line of sight velocity with seconds to minutes time resolution. RISR-N does not directly measure ionospheric parameters, but backscattered signals, recording them as voltage samples. Using signal processing techniques, radar autocorrelation functions (ACF) are estimated from the voltage samples. A model of the signal ACF is then fitted to the ACF using non-linear least-squares techniques to obtain the best-fit ionospheric parameters. The signal model, and therefore the fitted parameters, depend on the ionospheric ion composition that is used [e.g. Zettergren et. al. (2010), Zou et. al. (2017)].The software used to process RISR-N ACF data includes the "flipchem" model, which is an ion photochemistry model developed by Richards [2011] that was adapted from the Field LineInterhemispheric Plasma (FLIP) model. Flipchem requires neutral densities, neutral temperatures, electron density, ion temperature, electron temperature, solar zenith angle, and F10.7 as inputs to compute ion densities, which are input to the signal model. A description of how the flipchem model is used in RISR-N fitting software will be presented. Additionally, a statistical comparison of the fitted electron density, ion temperature, electron temperature, and velocity obtained using a flipchem ionosphere, a pure O+ ionosphere, and a Chapman O+ ionosphere will be presented. The comparison covers nearly two years of RISR-N data (April 2015 - December 2016). Richards, P. G. (2011), Reexamination of ionospheric photochemistry, J. Geophys. Res., 116, A08307, doi:10.1029/2011JA016613.Zettergren, M., Semeter, J., Burnett, B., Oliver, W., Heinselman, C., Blelly, P.-L., and Diaz, M.: Dynamic variability in F-region ionospheric composition at auroral arc boundaries, Ann. Geophys., 28, 651-664, https

Contrast Gain Control Model Fits Masking Data

Science.gov (United States)

Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)

1994-01-01

We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.

Ensuring dynamic strategic fit of firms that compete globally in alliances and networks: proposing the Global SNA - Strategic Network Analysis - framework

Directory of Open Access Journals (Sweden)

T. Diana L. Van Aduard de Macedo-Soares

2011-02-01

Full Text Available In order to sustain their competitive advantage in the current increasingly globalized and turbulent context, more and more firms are competing globally in alliances and networks that oblige them to adopt new managerial paradigms and tools. However, their strategic analyses rarely take into account the strategic implications of these alliances and networks, considering their global relational characteristics, admittedly because of a lack of adequate tools to do so. This paper contributes to research that seeks to fill this gap by proposing the Global Strategic Network Analysis - SNA - framework. Its purpose is to help firms that compete globally in alliances and networks to carry out their strategic assessments and decision-making with a view to ensuring dynamic strategic fit from both a global and relational perspective.

"Doing for Group Exercise What McDonald's Did for Hamburgers": Les Mills, and the Fitness Professional as Global Traveller

Science.gov (United States)

Andreasson, Jesper; Johansson, Thomas

2016-01-01

This article analyses fitness professionals' perceptions and understanding of their occupational education and pedagogical pursuance, framed within the emergence of a global fitness industry. The empirical material consists of interviews with personal trainers and group fitness instructors, as well as observations in their working environment. In…

Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

DEFF Research Database (Denmark)

Bolker, B.M.; Gardner, B.; Maunder, M.

2013-01-01

Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. R is convenient and (relatively) easy...... to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield...

The structural relationships between organizational commitment, global job satisfaction, developmental experiences, work values, organizational support, and person-organization fit among nursing faculty.

Science.gov (United States)

Gutierrez, Antonio P; Candela, Lori L; Carver, Lara

2012-07-01

GUTIERAIM: The aim of this correlational study was to examine the relations between organizational commitment, perceived organizational support, work values, person-organization fit, developmental experiences, and global job satisfaction among nursing faculty. The global nursing shortage is well documented. At least 57 countries have reported critical shortages. The lack of faculty is finally being recognized as a major issue directly influencing the ability to admit and graduate adequate numbers of nurses. As efforts increase to both recruit and retain faculty, the concept of organizational commitment and what it means to them is important to consider. A cross-sectional correlational design was used. The present study investigated the underlying structure of various organizational factors using structural equation modelling. Data were collected from a stratified random sample of nurse faculty during the academic year 2006-2007. The final model demonstrated that perceived organizational support, developmental experiences, person-organization fit, and global job satisfaction positively predicted nurse faculty's organizational commitment to the academic organization. Cross-validation results indicated that the final full SEM is valid and reliable. Nursing faculty administrators able to use mentoring skills are well equipped to build positive relationships with nursing faculty, which in turn, can lead to increased organizational commitment, productivity, job satisfaction, and perceived organizational support, among others. © 2012 Blackwell Publishing Ltd.

The Electroweak Fit of the Standard Model after the Discovery of a New Boson at the LHC

CERN Document Server

Baak, M.

2012-11-03

In view of the discovery of a new boson by the ATLAS and CMS Collaborations at the LHC, we present an update of the global Standard Model (SM) fit to electroweak precision data. Assuming the new particle to be the SM Higgs boson, all fundamental parameters of the SM are known allowing, for the first time, to overconstrain the SM at the electroweak scale and assert its validity. Including the effects of radiative corrections and the experimental and theoretical uncertainties, the global fit exhibits a p-value of 0.07. The mass measurements by ATLAS and CMS agree within 1.3sigma with the indirect determination M_H=(94 +25 -22) GeV. Within the SM the W boson mass and the effective weak mixing angle can be accurately predicted to be M_W=(80.359 +- 0.011) GeV and sin^2(theta_eff^ell)=(0.23150 +- 0.00010) from the global fit. These results are compatible with, and exceed in precision, the direct measurements. For the indirect determination of the top quark mass we find m_t=(175.8 +2.7 -2.4) GeV, in agreement with t...

The electroweak fit of the standard model after the discovery of a new boson at the LHC

International Nuclear Information System (INIS)

Baak, M.; Hoecker, A.; Schott, M.; Goebel, M.; Kennedy, D.; Moenig, K.; Haller, J.; Kogler, R.; Stelzer, J.

2012-09-01

In view of the discovery of a new boson by the ATLAS and CMS Collaborations at the LHC, we present an update of the global Standard Model (SM) fit to electroweak precision data. Assuming the new particle to be the SM Higgs boson, all fundamental parameters of the SM are known allowing, for the first time, to overconstrain the SM at the electroweak scale and assert its validity. Including the effects of radiative corrections and the experimental and theoretical uncertainties, the global fit exhibits a p-value of 0.07. The mass measurements by ATLAS and CMS agree within 1.3σ with the indirect determination M H =94 +25 -22 GeV. Within the SM the W boson mass and the effective weak mixing angle can be accurately predicted to be M W =80.359±0.011 GeV and sin 2 θ l eff =0.23150±0.00010 from the global fit. These results are compatible with, and exceed in precision, the direct measurements. For the indirect determination of the top quark mass we find m t =175.8 +2.7 -2.4 GeV, in agreement with the kinematic and cross-section based measurements.

Globally COnstrained Local Function Approximation via Hierarchical Modelling, a Framework for System Modelling under Partial Information

DEFF Research Database (Denmark)

Øjelund, Henrik; Sadegh, Payman

2000-01-01

be obtained. This paper presents a new approach for system modelling under partial (global) information (or the so called Gray-box modelling) that seeks to perserve the benefits of the global as well as local methodologies sithin a unified framework. While the proposed technique relies on local approximations......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality....

topicmodels: An R Package for Fitting Topic Models

Directory of Open Access Journals (Sweden)

Bettina Grun

2011-05-01

Full Text Available Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent variables which are referred to as topics. The R package topicmodels provides basic infrastructure for fitting topic models based on data structures from the text mining package tm. The package includes interfaces to two algorithms for fitting topic models: the variational expectation-maximization algorithm provided by David M. Blei and co-authors and an algorithm using Gibbs sampling by Xuan-Hieu Phan and co-authors.

Global parameter estimation for thermodynamic models of transcriptional regulation.

Science.gov (United States)

Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N

2013-07-15

Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.

Five challenges for stochastic epidemic models involving global transmission

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Tom Britton

2015-03-01

Full Text Available The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For example, when will such an epidemic go extinct and with what probability (questions depending on the population being fixed, changing or growing? How can a model be defined explaining the sometimes observed scenario of frequent mid-sized epidemic outbreaks? How can evolution of the infectious agent transmission rates be modelled and fitted to data in a robust way?

Goodness-of-Fit Assessment of Item Response Theory Models

Science.gov (United States)

Maydeu-Olivares, Alberto

2013-01-01

The article provides an overview of goodness-of-fit assessment methods for item response theory (IRT) models. It is now possible to obtain accurate "p"-values of the overall fit of the model if bivariate information statistics are used. Several alternative approaches are described. As the validity of inferences drawn on the fitted model…

GAMBIT: the global and modular beyond-the-standard-model inference tool

Science.gov (United States)

Athron, Peter; Balazs, Csaba; Bringmann, Torsten; Buckley, Andy; Chrząszcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Dickinson, Hugh; Edsjö, Joakim; Farmer, Ben; Gonzalo, Tomás E.; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Lundberg, Johan; McKay, James; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje; Raklev, Are; Ripken, Joachim; Rogan, Christopher; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Seo, Seon-Hee; Serra, Nicola; Weniger, Christoph; White, Martin; Wild, Sebastian

2017-11-01

We describe the open-source global fitting package GAMBIT: the Global And Modular Beyond-the-Standard-Model Inference Tool. GAMBIT combines extensive calculations of observables and likelihoods in particle and astroparticle physics with a hierarchical model database, advanced tools for automatically building analyses of essentially any model, a flexible and powerful system for interfacing to external codes, a suite of different statistical methods and parameter scanning algorithms, and a host of other utilities designed to make scans faster, safer and more easily-extendible than in the past. Here we give a detailed description of the framework, its design and motivation, and the current models and other specific components presently implemented in GAMBIT. Accompanying papers deal with individual modules and present first GAMBIT results. GAMBIT can be downloaded from gambit.hepforge.org.

GAMBIT. The global and modular beyond-the-standard-model inference tool

Energy Technology Data Exchange (ETDEWEB)

Athron, Peter; Balazs, Csaba [Monash University, School of Physics and Astronomy, Melbourne, VIC (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Bringmann, Torsten; Dal, Lars A.; Gonzalo, Tomas E.; Krislock, Abram; Raklev, Are [University of Oslo, Department of Physics, Oslo (Norway); Buckley, Andy [University of Glasgow, SUPA, School of Physics and Astronomy, Glasgow (United Kingdom); Chrzaszcz, Marcin [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Polish Academy of Sciences, H. Niewodniczanski Institute of Nuclear Physics, Krakow (Poland); Conrad, Jan; Edsjoe, Joakim; Farmer, Ben; Lundberg, Johan [AlbaNova University Centre, Oskar Klein Centre for Cosmoparticle Physics, Stockholm (Sweden); Stockholm University, Department of Physics, Stockholm (Sweden); Cornell, Jonathan M. [McGill University, Department of Physics, Montreal, QC (Canada); Dickinson, Hugh [University of Minnesota, Minnesota Institute for Astrophysics, Minneapolis, MN (United States); Jackson, Paul; White, Martin [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); University of Adelaide, Department of Physics, Adelaide, SA (Australia); Kvellestad, Anders; Savage, Christopher [NORDITA, Stockholm (Sweden); McKay, James [Imperial College London, Blackett Laboratory, Department of Physics, London (United Kingdom); Mahmoudi, Farvah [Univ Lyon, Univ Lyon 1, ENS de Lyon, CNRS, Centre de Recherche Astrophysique de Lyon UMR5574, Saint-Genis-Laval (France); CERN, Theoretical Physics Department, Geneva (Switzerland); Martinez, Gregory D. [University of California, Physics and Astronomy Department, Los Angeles, CA (United States); Putze, Antje [LAPTh, Universite de Savoie, CNRS, Annecy-le-Vieux (France); Ripken, Joachim [Max Planck Institute for Solar System Research, Goettingen (Germany); Rogan, Christopher [Harvard University, Department of Physics, Cambridge, MA (United States); Saavedra, Aldo [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); The University of Sydney, Faculty of Engineering and Information Technologies, Centre for Translational Data Science, School of Physics, Sydney, NSW (Australia); Scott, Pat [Imperial College London, Blackett Laboratory, Department of Physics, London (United Kingdom); Seo, Seon-Hee [Seoul National University, Department of Physics and Astronomy, Seoul (Korea, Republic of); Serra, Nicola [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Weniger, Christoph [University of Amsterdam, GRAPPA, Institute of Physics, Amsterdam (Netherlands); Wild, Sebastian [DESY, Hamburg (Germany); Collaboration: The GAMBIT Collaboration

2017-11-15

We describe the open-source global fitting package GAMBIT: the Global And Modular Beyond-the-Standard-Model Inference Tool. GAMBIT combines extensive calculations of observables and likelihoods in particle and astroparticle physics with a hierarchical model database, advanced tools for automatically building analyses of essentially any model, a flexible and powerful system for interfacing to external codes, a suite of different statistical methods and parameter scanning algorithms, and a host of other utilities designed to make scans faster, safer and more easily-extendible than in the past. Here we give a detailed description of the framework, its design and motivation, and the current models and other specific components presently implemented in GAMBIT. Accompanying papers deal with individual modules and present first GAMBIT results. GAMBIT can be downloaded from gambit.hepforge.org. (orig.)

GAMBIT. The global and modular beyond-the-standard-model inference tool

International Nuclear Information System (INIS)

Athron, Peter; Balazs, Csaba; Bringmann, Torsten; Dal, Lars A.; Gonzalo, Tomas E.; Krislock, Abram; Raklev, Are; Buckley, Andy; Chrzaszcz, Marcin; Conrad, Jan; Edsjoe, Joakim; Farmer, Ben; Lundberg, Johan; Cornell, Jonathan M.; Dickinson, Hugh; Jackson, Paul; White, Martin; Kvellestad, Anders; Savage, Christopher; McKay, James; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje; Ripken, Joachim; Rogan, Christopher; Saavedra, Aldo; Scott, Pat; Seo, Seon-Hee; Serra, Nicola; Weniger, Christoph; Wild, Sebastian

2017-01-01

We describe the open-source global fitting package GAMBIT: the Global And Modular Beyond-the-Standard-Model Inference Tool. GAMBIT combines extensive calculations of observables and likelihoods in particle and astroparticle physics with a hierarchical model database, advanced tools for automatically building analyses of essentially any model, a flexible and powerful system for interfacing to external codes, a suite of different statistical methods and parameter scanning algorithms, and a host of other utilities designed to make scans faster, safer and more easily-extendible than in the past. Here we give a detailed description of the framework, its design and motivation, and the current models and other specific components presently implemented in GAMBIT. Accompanying papers deal with individual modules and present first GAMBIT results. GAMBIT can be downloaded from gambit.hepforge.org. (orig.)

Retrieving global aerosol sources from satellites using inverse modeling

Directory of Open Access Journals (Sweden)

O. Dubovik

2008-01-01

Full Text Available Understanding aerosol effects on global climate requires knowing the global distribution of tropospheric aerosols. By accounting for aerosol sources, transports, and removal processes, chemical transport models simulate the global aerosol distribution using archived meteorological fields. We develop an algorithm for retrieving global aerosol sources from satellite observations of aerosol distribution by inverting the GOCART aerosol transport model.

The inversion is based on a generalized, multi-term least-squares-type fitting, allowing flexible selection and refinement of a priori algorithm constraints. For example, limitations can be placed on retrieved quantity partial derivatives, to constrain global aerosol emission space and time variability in the results. Similarities and differences between commonly used inverse modeling and remote sensing techniques are analyzed. To retain the high space and time resolution of long-period, global observational records, the algorithm is expressed using adjoint operators.

Successful global aerosol emission retrievals at 2°×2.5 resolution were obtained by inverting GOCART aerosol transport model output, assuming constant emissions over the diurnal cycle, and neglecting aerosol compositional differences. In addition, fine and coarse mode aerosol emission sources were inverted separately from MODIS fine and coarse mode aerosol optical thickness data, respectively. These assumptions are justified, based on observational coverage and accuracy limitations, producing valuable aerosol source locations and emission strengths. From two weeks of daily MODIS observations during August 2000, the global placement of fine mode aerosol sources agreed with available independent knowledge, even though the inverse method did not use any a priori information about aerosol sources, and was initialized with a "zero aerosol emission" assumption. Retrieving coarse mode aerosol emissions was less successful

Automatic fitting of spiking neuron models to electrophysiological recordings

Directory of Open Access Journals (Sweden)

Cyrille Rossant

2010-03-01

Full Text Available Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains that can run in parallel on graphics processing units (GPUs. The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models.

Modelling stratospheric chemistry in a global three-dimensional chemical transport model

Energy Technology Data Exchange (ETDEWEB)

Rummukainen, M [Finnish Meteorological Inst., Sodankylae (Finland). Sodankylae Observatory

1996-12-31

Numerical modelling of atmospheric chemistry aims to increase the understanding of the characteristics, the behavior and the evolution of atmospheric composition. These topics are of utmost importance in the study of climate change. The multitude of gases and particulates making up the atmosphere and the complicated interactions between them affect radiation transfer, atmospheric dynamics, and the impacts of anthropogenic and natural emissions. Chemical processes are fundamental factors in global warming, ozone depletion and atmospheric pollution problems in general. Much of the prevailing work on modelling stratospheric chemistry has so far been done with 1- and 2-dimensional models. Carrying an extensive chemistry parameterisation in a model with high spatial and temporal resolution is computationally heavy. Today, computers are becoming powerful enough to allow going over to 3-dimensional models. In order to concentrate on the chemistry, many Chemical Transport Models (CTM) are still run off-line, i.e. with precalculated and archived meteorology and radiation. In chemistry simulations, the archived values drive the model forward in time, without interacting with the chemical evolution. This is an approach that has been adopted in stratospheric chemistry modelling studies at the Finnish Meteorological Institute. In collaboration with the University of Oslo, a development project was initiated in 1993 to prepare a stratospheric chemistry parameterisation, fit for global 3-dimensional modelling. This article presents the parameterisation approach. Selected results are shown from basic photochemical simulations

Modelling stratospheric chemistry in a global three-dimensional chemical transport model

Energy Technology Data Exchange (ETDEWEB)

Rummukainen, M. [Finnish Meteorological Inst., Sodankylae (Finland). Sodankylae Observatory

1995-12-31

Numerical modelling of atmospheric chemistry aims to increase the understanding of the characteristics, the behavior and the evolution of atmospheric composition. These topics are of utmost importance in the study of climate change. The multitude of gases and particulates making up the atmosphere and the complicated interactions between them affect radiation transfer, atmospheric dynamics, and the impacts of anthropogenic and natural emissions. Chemical processes are fundamental factors in global warming, ozone depletion and atmospheric pollution problems in general. Much of the prevailing work on modelling stratospheric chemistry has so far been done with 1- and 2-dimensional models. Carrying an extensive chemistry parameterisation in a model with high spatial and temporal resolution is computationally heavy. Today, computers are becoming powerful enough to allow going over to 3-dimensional models. In order to concentrate on the chemistry, many Chemical Transport Models (CTM) are still run off-line, i.e. with precalculated and archived meteorology and radiation. In chemistry simulations, the archived values drive the model forward in time, without interacting with the chemical evolution. This is an approach that has been adopted in stratospheric chemistry modelling studies at the Finnish Meteorological Institute. In collaboration with the University of Oslo, a development project was initiated in 1993 to prepare a stratospheric chemistry parameterisation, fit for global 3-dimensional modelling. This article presents the parameterisation approach. Selected results are shown from basic photochemical simulations

The FITS model office ergonomics program: a model for best practice.

Science.gov (United States)

Chim, Justine M Y

2014-01-01

An effective office ergonomics program can predict positive results in reducing musculoskeletal injury rates, enhancing productivity, and improving staff well-being and job satisfaction. Its objective is to provide a systematic solution to manage the potential risk of musculoskeletal disorders among computer users in an office setting. A FITS Model office ergonomics program is developed. The FITS Model Office Ergonomics Program has been developed which draws on the legislative requirements for promoting the health and safety of workers using computers for extended periods as well as previous research findings. The Model is developed according to the practical industrial knowledge in ergonomics, occupational health and safety management, and human resources management in Hong Kong and overseas. This paper proposes a comprehensive office ergonomics program, the FITS Model, which considers (1) Furniture Evaluation and Selection; (2) Individual Workstation Assessment; (3) Training and Education; (4) Stretching Exercises and Rest Break as elements of an effective program. An experienced ergonomics practitioner should be included in the program design and implementation. Through the FITS Model Office Ergonomics Program, the risk of musculoskeletal disorders among computer users can be eliminated or minimized, and workplace health and safety and employees' wellness enhanced.

Reliability and Model Fit

Science.gov (United States)

Stanley, Leanne M.; Edwards, Michael C.

2016-01-01

The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the…

Updated Status of the Global Electroweak Fit and Constraints on New Physics

CERN Document Server

Baak, M; Haller, J; Hoecker, A; Kennedy, D; Moenig, K; Schott, M; Stelzer, J

2012-01-01

We present an update of the Standard Model fit to electroweak precision data. We include newest experimental results on the top quark mass, the W mass and width, and the Higgs boson mass bounds from LEP, Tevatron and the LHC. We also include a new determination of the electromagnetic coupling strength at the Z pole. We find for the Higgs boson mass (96 +31 -24) GeV and (120 +12 -5) GeV when not including and including the direct Higgs searches, respectively. From the latter fit we indirectly determine the W mass to be (80.362 +- 0.013) GeV. We exploit the data to determine experimental constraints on the oblique vacuum polarisation parameters, and confront these with predictions from the Standard Model (SM) and selected SM extensions. By fitting the oblique parameters to the electroweak data we derive allowed regions in the BSM parameter spaces. We revisit and consistently update these constraints for a fourth fourth fermion generation, two Higgs doublet, inert Higgs and littlest Higgs models, models with lar...

Updated Status of the Global Electroweak Fit and Constraints on New Physics

CERN Document Server

Baak, Max; Haller, Johannes; Hoecker, Andreas; Ludwig, Doerthe; Moenig, Klaus; Schott, Matthias; Stelzer, Joerg

2011-01-01

We present an update of the Standard Model fit to electroweak precision data. We include newest experimental results on the top quark mass, the W mass and width, and the Higgs boson mass bounds from LEP, Tevatron and the cLHC. We also include a new determination of the electromagnetic coupling strength at the Z pole. We find for the Higgs boson mass (96 +31 -24) GeV and (120 +12 -5) GeV when not including and including the direct Higgs searches, respectively. From the latter fit we indirectly determine the W mass to be (80.359 +0.017 -0.010) GeV. We exploit the data to determine experimental constraints on the oblique vacuum polarisation parameters, and confront these with predictions from the Standard Model (SM) and selected SM extensions. By fitting the oblique parameters to the electroweak data we derive allowed regions in the BSM parameter spaces. We revisit and consistently update these constraints for a fourth family, two Higgs doublet, inert Higgs and littlest Higgs models, models with large,...

In search of laterally heterogeneous viscosity models of Glacial Isostatic Adjustment with the ICE-6G_C global ice history model

Science.gov (United States)

Li, Tanghua; Wu, Patrick; Steffen, Holger; Wang, Hansheng

2018-05-01

Most models of Glacial Isostatic Adjustment (GIA) assume that the Earth is laterally homogeneous. However, seismic and geological observations clearly show that the Earth's mantle is laterally heterogeneous. Previous studies of GIA with lateral heterogeneity mostly focused on its effect or sensitivity on GIA predictions, and it is not clear to what extent can lateral heterogeneity solve the misfits between GIA predictions and observations. Our aim is to search for the best 3D viscosity models that can simultaneously fit the global relative sea-level (RSL) data, the peak uplift rates (u-dot from GNSS) and peak gravity-rate-of-change (g-dot from the GRACE satellite mission) in Laurentia and Fennoscandia. However, the search is dependent on the ice and viscosity model inputs - the latter depends on the background viscosity and the seismic tomography models used. In this paper, the ICE-6G_C ice model, with Bunge & Grand's seismic tomography model and background viscosity models close to VM5 will be assumed. A Coupled Laplace-Finite Element Method is used to compute gravitationally self-consistent sea level change with time dependent coastlines and rotational feedback in addition to changes in deformation, gravity and the state of stress. Several laterally heterogeneous models are found to fit the global sea level data better than laterally homogeneous models. Two of these laterally heterogeneous models also fit the ICE-6G_C peak g-dot and u-dot rates observed in Laurentia simultaneously. However, even with the introduction of lateral heterogeneity, no model that is able to fit the present-day g-dot and uplift rate data in Fennoscandia has been found. Therefore, either the ice history of ICE-6G_C in Fennoscandia and Barent Sea needs some modifications, or the sub-lithospheric property/non-thermal effect underneath northern Europe must be different from that underneath Laurentia.

Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

Science.gov (United States)

Bolker, Benjamin M.; Gardner, Beth; Maunder, Mark; Berg, Casper W.; Brooks, Mollie; Comita, Liza; Crone, Elizabeth; Cubaynes, Sarah; Davies, Trevor; de Valpine, Perry; Ford, Jessica; Gimenez, Olivier; Kéry, Marc; Kim, Eun Jung; Lennert-Cody, Cleridy; Magunsson, Arni; Martell, Steve; Nash, John; Nielson, Anders; Regentz, Jim; Skaug, Hans; Zipkin, Elise

2013-01-01

1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.

Are Physical Education Majors Models for Fitness?

Science.gov (United States)

Kamla, James; Snyder, Ben; Tanner, Lori; Wash, Pamela

2012-01-01

The National Association of Sport and Physical Education (NASPE) (2002) has taken a firm stance on the importance of adequate fitness levels of physical education teachers stating that they have the responsibility to model an active lifestyle and to promote fitness behaviors. Since the NASPE declaration, national initiatives like Let's Move…

ITEM LEVEL DIAGNOSTICS AND MODEL - DATA FIT IN ITEM ...

African Journals Online (AJOL)

Global Journal

Item response theory (IRT) is a framework for modeling and analyzing item response ... data. Though, there is an argument that the evaluation of fit in IRT modeling has been ... National Council on Measurement in Education ... model data fit should be based on three types of ... prediction should be assessed through the.

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

Science.gov (United States)

Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

2014-01-01

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

Assessing fit in Bayesian models for spatial processes

KAUST Repository

Jun, M.; Katzfuss, M.; Hu, J.; Johnson, V. E.

2014-01-01

© 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.

Assessing fit in Bayesian models for spatial processes

KAUST Repository

Jun, M.

2014-09-16

© 2014 John Wiley & Sons, Ltd. Gaussian random fields are frequently used to model spatial and spatial-temporal data, particularly in geostatistical settings. As much of the attention of the statistics community has been focused on defining and estimating the mean and covariance functions of these processes, little effort has been devoted to developing goodness-of-fit tests to allow users to assess the models\\' adequacy. We describe a general goodness-of-fit test and related graphical diagnostics for assessing the fit of Bayesian Gaussian process models using pivotal discrepancy measures. Our method is applicable for both regularly and irregularly spaced observation locations on planar and spherical domains. The essential idea behind our method is to evaluate pivotal quantities defined for a realization of a Gaussian random field at parameter values drawn from the posterior distribution. Because the nominal distribution of the resulting pivotal discrepancy measures is known, it is possible to quantitatively assess model fit directly from the output of Markov chain Monte Carlo algorithms used to sample from the posterior distribution on the parameter space. We illustrate our method in a simulation study and in two applications.

Updated status of the global electroweak fit and constraints on new physics

Energy Technology Data Exchange (ETDEWEB)

Baak, M.; Hoecker, A.; Schott, M. [CERN, Geneva (Switzerland); Goebel, M.; Ludwig, D. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Hamburg Univ. (Germany). Inst. fuer Experimentalphysik; Haller, J. [Hamburg Univ. (Germany). Inst. fuer Experimentalphysik; Goettingen Univ. (Germany). II. Physikalisches Inst.; Moenig, K. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Stelzer, J. [Michigan State Univ., East Lansing, MI (United States). Dept. of Physics and Astronomy

2011-07-15

We present an update of the Standard Model fit to electroweak precision data. We include newest experimental results on the top quark mass, the W mass and width, and the Higgs boson mass bounds from LEP, Tevatron and the LHC. We also include a new determination of the electromagnetic coupling strength at the Z pole. We find for the Higgs boson mass 96{sub -24}{sup +31} GeV and 120{sub -5}{sup +12} GeV when not including and including the direct Higgs searches, respectively. From the latter fit we indirectly determine the W mass to be (80.362{+-} 0.013)GeV. We exploit the data to determine experimental constraints on the oblique vacuum polarisation parameters, and confront these with predictions from the Standard Model (SM) and selected SM extensions. By fitting the oblique parameters to the electroweak data we derive allowed regions in the BSM parameter spaces. We revisit and consistently update these constraints for a fourth fermion generation, two Higgs doublet, inert Higgs and littlest Higgs models, models with large, universal or warped extra dimensions and technicolour. In most of the models studied a heavy Higgs boson can be made compatible with the electroweak precision data. (orig.)

The FIT Model - Fuel-cycle Integration and Tradeoffs

International Nuclear Information System (INIS)

Piet, Steven J.; Soelberg, Nick R.; Bays, Samuel E.; Pereira, Candido; Pincock, Layne F.; Shaber, Eric L.; Teague, Melissa C.; Teske, Gregory M.; Vedros, Kurt G.

2010-01-01

All mass streams from fuel separation and fabrication are products that must meet some set of product criteria - fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the 'system losses study' team that developed it (Shropshire2009, Piet2010) are an initial step by the FCR and D program toward a global analysis that accounts for the requirements and capabilities of each component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R and D needs and set longer-term goals. The question originally posed to the 'system losses study' was the cost of separation, fuel fabrication, waste management, etc. versus the separation efficiency. In other words, are the costs associated with marginal reductions in separations losses (or improvements in product recovery) justified by the gains in the performance of other systems? We have learned that that is the wrong question. The right question is: how does one adjust the compositions and quantities of all mass streams, given uncertain product criteria, to balance competing objectives including cost? FIT is a method to analyze different fuel cycles using common bases to determine how chemical performance changes in one part of a fuel cycle (say used fuel cooling times or separation efficiencies) affect other parts of the fuel cycle. FIT estimates impurities in fuel and waste via a rough estimate of physics and mass balance for a set of technologies. If feasibility is an issue for a set, as it is for 'minimum fuel treatment' approaches such as melt refining and AIROX, it can help to make an estimate of how performances would have to change to achieve feasibility.

Automated Model Fit Method for Diesel Engine Control Development

NARCIS (Netherlands)

Seykens, X.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.

2014-01-01

This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

Automated model fit method for diesel engine control development

NARCIS (Netherlands)

Seykens, X.L.J.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.J.H.

2014-01-01

This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

Firm Size Distribution in Fortune Global 500

Science.gov (United States)

Chen, Qinghua; Chen, Liujun; Liu, Kai

By analyzing the data of Fortune Global 500 firms from 1996 to 2008, we found that their ranks and revenues always obey the same distribution, which implies that worldwide firm structure has been stable for a long time. The fitting results show that simple Zipf distribution is not an ideal model for global firms, while SCL, FSS have better fitting goodness, and lognormal fitting is the best. And then, we proposed a simple explanation.

New Region-Scalable Discriminant and Fitting Energy Functional for Driving Geometric Active Contours in Medical Image Segmentation

Directory of Open Access Journals (Sweden)

Xuchu Wang

2014-01-01

that uses region-scalable discriminant and fitting energy functional for handling the intensity inhomogeneity and weak boundary problems in medical image segmentation. The region-scalable discriminant and fitting energy functional is defined to capture the image intensity characteristics in local and global regions for driving the evolution of active contour. The discriminant term in the model aims at separating background and foreground in scalable regions while the fitting term tends to fit the intensity in these regions. This model is then transformed into a variational level set formulation with a level set regularization term for accurate computation. The new model utilizes intensity information in the local and global regions as much as possible; so it not only handles better intensity inhomogeneity, but also allows more robustness to noise and more flexible initialization in comparison to the original global region and regional-scalable based models. Experimental results for synthetic and real medical image segmentation show the advantages of the proposed method in terms of accuracy and robustness.

An R package for fitting age, period and cohort models

Directory of Open Access Journals (Sweden)

Adriano Decarli

2014-11-01

Full Text Available In this paper we present the R implementation of a GLIM macro which fits age-period-cohort model following Osmond and Gardner. In addition to the estimates of the corresponding model, owing to the programming capability of R as an object oriented language, methods for printing, plotting and summarizing the results are provided. Furthermore, the researcher has fully access to the output of the main function (apc which returns all the models fitted within the function. It is so possible to critically evaluate the goodness of fit of the resulting model.

Are Fit Indices Biased in Favor of Bi-Factor Models in Cognitive Ability Research?: A Comparison of Fit in Correlated Factors, Higher-Order, and Bi-Factor Models via Monte Carlo Simulations

Directory of Open Access Journals (Sweden)

Grant B. Morgan

2015-02-01

Full Text Available Bi-factor confirmatory factor models have been influential in research on cognitive abilities because they often better fit the data than correlated factors and higher-order models. They also instantiate a perspective that differs from that offered by other models. Motivated by previous work that hypothesized an inherent statistical bias of fit indices favoring the bi-factor model, we compared the fit of correlated factors, higher-order, and bi-factor models via Monte Carlo methods. When data were sampled from a true bi-factor structure, each of the approximate fit indices was more likely than not to identify the bi-factor solution as the best fitting. When samples were selected from a true multiple correlated factors structure, approximate fit indices were more likely overall to identify the correlated factors solution as the best fitting. In contrast, when samples were generated from a true higher-order structure, approximate fit indices tended to identify the bi-factor solution as best fitting. There was extensive overlap of fit values across the models regardless of true structure. Although one model may fit a given dataset best relative to the other models, each of the models tended to fit the data well in absolute terms. Given this variability, models must also be judged on substantive and conceptual grounds.

Does model fit decrease the uncertainty of the data in comparison with a general non-model least squares fit?

International Nuclear Information System (INIS)

Pronyaev, V.G.

2003-01-01

The information entropy is taken as a measure of knowledge about the object and the reduced univariante variance as a common measure of uncertainty. Covariances in the model versus non-model least square fits are discussed

Efficient occupancy model-fitting for extensive citizen-science data

Science.gov (United States)

Morgan, Byron J. T.; Freeman, Stephen N.; Ridout, Martin S.; Brereton, Tom M.; Fox, Richard; Powney, Gary D.; Roy, David B.

2017-01-01

Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species’ range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen

A Model Fit Statistic for Generalized Partial Credit Model

Science.gov (United States)

Liang, Tie; Wells, Craig S.

2009-01-01

Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…

Unifying distance-based goodness-of-fit indicators for hydrologic model assessment

Science.gov (United States)

Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim

2014-05-01

The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on

Impact of CMS Multi-jets and Missing Energy Search on CMSSM Fits

CERN Document Server

Allanach, B C

2011-01-01

Recent CMS data significantly extend the direct search exclusion for supersymmetry. We examine the impact of such data on global fits of the constrained minimal supersymmetric standard model (CMSSM) to indirect and cosmological data. By simulating supersymmetric signal events at the LHC, we construct a likelihood map for the recent CMS data, validating it against the exclusion region calculated by the experiment itself. A previous CMSSM global fit is then re-weighted by our likelihood map. The CMS results nibble away at the high fit probability density region, transforming probability distributions for the scalar and gluino masses. The CMS search has a with non-trivial effect on tan \\beta due to correlations between the parameters implied by the fits to indirect data.

A global fit of the MSSM with GAMBIT

Science.gov (United States)

Athron, Peter; Balázs, Csaba; Bringmann, Torsten; Buckley, Andy; Chrząszcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje; Raklev, Are; Rogan, Christopher; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Serra, Nicola; Weniger, Christoph; White, Martin

2017-12-01

We study the seven-dimensional Minimal Supersymmetric Standard Model (MSSM7) with the new GAMBIT software framework, with all parameters defined at the weak scale. Our analysis significantly extends previous weak-scale, phenomenological MSSM fits, by adding more and newer experimental analyses, improving the accuracy and detail of theoretical predictions, including dominant uncertainties from the Standard Model, the Galactic dark matter halo and the quark content of the nucleon, and employing novel and highly-efficient statistical sampling methods to scan the parameter space. We find regions of the MSSM7 that exhibit co-annihilation of neutralinos with charginos, stops and sbottoms, as well as models that undergo resonant annihilation via both light and heavy Higgs funnels. We find high-likelihood models with light charginos, stops and sbottoms that have the potential to be within the future reach of the LHC. Large parts of our preferred parameter regions will also be accessible to the next generation of direct and indirect dark matter searches, making prospects for discovery in the near future rather good.

A global fit of the MSSM with GAMBIT

Energy Technology Data Exchange (ETDEWEB)

Athron, Peter; Balazs, Csaba [Monash University, School of Physics and Astronomy, Melbourne, VIC (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Bringmann, Torsten; Dal, Lars A.; Krislock, Abram; Raklev, Are [University of Oslo, Department of Physics, Oslo (Norway); Buckley, Andy [University of Glasgow, SUPA, School of Physics and Astronomy, Glasgow (United Kingdom); Chrzaszcz, Marcin [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Polish Academy of Sciences, H. Niewodniczanski Institute of Nuclear Physics, Krakow (Poland); Conrad, Jan; Edsjoe, Joakim; Farmer, Ben [AlbaNova University Centre, Oskar Klein Centre for Cosmoparticle Physics, Stockholm (Sweden); Stockholm University, Department of Physics, Stockholm (Sweden); Cornell, Jonathan M. [McGill University, Department of Physics, Montreal, QC (Canada); Jackson, Paul; White, Martin [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); University of Adelaide, Department of Physics, Adelaide, SA (Australia); Kvellestad, Anders; Savage, Christopher [NORDITA, Stockholm (Sweden); Mahmoudi, Farvah [Univ Lyon, Univ Lyon 1, ENS de Lyon, CNRS, Centre de Recherche Astrophysique de Lyon UMR5574, Saint-Genis-Laval (France); CERN, Theoretical Physics Department, Geneva (Switzerland); Martinez, Gregory D. [Physics and Astronomy Department, University of California, Los Angeles, CA (United States); Putze, Antje [LAPTh, Universite de Savoie, CNRS, Annecy-le-Vieux (France); Rogan, Christopher [Harvard University, Department of Physics, Cambridge, MA (United States); Saavedra, Aldo [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); School of Physics, The University of Sydney, Centre for Translational Data Science, Faculty of Engineering and Information Technologies, Sydney, NSW (Australia); Scott, Pat [Imperial College London, Department of Physics, Blackett Laboratory, London (United Kingdom); Serra, Nicola [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Weniger, Christoph [University of Amsterdam, GRAPPA, Institute of Physics, Amsterdam (Netherlands); Collaboration: The GAMBIT Collaboration

2017-12-15

We study the seven-dimensional Minimal Supersymmetric Standard Model (MSSM7) with the new GAMBIT software framework, with all parameters defined at the weak scale. Our analysis significantly extends previous weak-scale, phenomenological MSSM fits, by adding more and newer experimental analyses, improving the accuracy and detail of theoretical predictions, including dominant uncertainties from the Standard Model, the Galactic dark matter halo and the quark content of the nucleon, and employing novel and highly-efficient statistical sampling methods to scan the parameter space. We find regions of the MSSM7 that exhibit co-annihilation of neutralinos with charginos, stops and sbottoms, as well as models that undergo resonant annihilation via both light and heavy Higgs funnels. We find high-likelihood models with light charginos, stops and sbottoms that have the potential to be within the future reach of the LHC. Large parts of our preferred parameter regions will also be accessible to the next generation of direct and indirect dark matter searches, making prospects for discovery in the near future rather good. (orig.)

A Comparison of Item Fit Statistics for Mixed IRT Models

Science.gov (United States)

Chon, Kyong Hee; Lee, Won-Chan; Dunbar, Stephen B.

2010-01-01

In this study we examined procedures for assessing model-data fit of item response theory (IRT) models for mixed format data. The model fit indices used in this study include PARSCALE's G[superscript 2], Orlando and Thissen's S-X[superscript 2] and S-G[superscript 2], and Stone's chi[superscript 2*] and G[superscript 2*]. To investigate the…

Sensitivity of Fit Indices to Misspecification in Growth Curve Models

Science.gov (United States)

Wu, Wei; West, Stephen G.

2010-01-01

This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…

Generic global regression models for growth prediction of Salmonella in ground pork and pork cuts

DEFF Research Database (Denmark)

Buschhardt, Tasja; Hansen, Tina Beck; Bahl, Martin Iain

2017-01-01

Introduction and Objectives Models for the prediction of bacterial growth in fresh pork are primarily developed using two-step regression (i.e. primary models followed by secondary models). These models are also generally based on experiments in liquids or ground meat and neglect surface growth....... It has been shown that one-step global regressions can result in more accurate models and that bacterial growth on intact surfaces can substantially differ from growth in liquid culture. Material and Methods We used a global-regression approach to develop predictive models for the growth of Salmonella....... One part of obtained logtransformed cell counts was used for model development and another for model validation. The Ratkowsky square root model and the relative lag time (RLT) model were integrated into the logistic model with delay. Fitted parameter estimates were compared to investigate the effect...

A global fitting code for multichordal neutral beam spectroscopic data

International Nuclear Information System (INIS)

Seraydarian, R.P.; Burrell, K.H.; Groebner, R.J.

1992-05-01

Knowledge of the heat deposition profile is crucial to all transport analysis of beam heated discharges. The heat deposition profile can be inferred from the fast ion birth profile which, in turn, is directly related to the loss of neutral atoms from the beam. This loss can be measured spectroscopically be the decrease in amplitude of spectral emissions from the beam as it penetrates the plasma. The spectra are complicated by the motional Stark effect which produces a manifold of nine bright peaks for each of the three beam energy components. A code has been written to analyze this kind of data. In the first phase of this work, spectra from tokamak shots are fit with a Stark splitting and Doppler shift model that ties together the geometry of several spatial positions when they are fit simultaneously. In the second phase, a relative position-to-position intensity calibration will be applied to these results to obtain the spectral amplitudes from which beam atom loss can be estimated. This paper reports on the computer code for the first phase. Sample fits to real tokamak spectral data are shown

Another method for a global fit of the Cabibbo-Kobayashi-Maskawa matrix

International Nuclear Information System (INIS)

Dita, Petre

2005-01-01

Recently we proposed a novel method for doing global fits on the entries of the Cabibbo-Kobayashi-Maskawa matrix. The new used ingredients were a clear relationship between the entries of the CKM matrix and the experimental data, as well as the use of the necessary and sufficient condition the data have to satisfy in order to find a unitary matrix compatible with them. This condition writes as -1 ≤ cosδ ≤1 where δ is the phase that accounts for CP violation. Numerical results are provided for the CKM matrix entries, the mixing angles between generations and all the angles of the standard unitarity triangle. (author)

The Open Global Glacier Model

Science.gov (United States)

Marzeion, B.; Maussion, F.

2017-12-01

Mountain glaciers are one of the few remaining sub-systems of the global climate system for which no globally applicable, open source, community-driven model exists. Notable examples from the ice sheet community include the Parallel Ice Sheet Model or Elmer/Ice. While the atmospheric modeling community has a long tradition of sharing models (e.g. the Weather Research and Forecasting model) or comparing them (e.g. the Coupled Model Intercomparison Project or CMIP), recent initiatives originating from the glaciological community show a new willingness to better coordinate global research efforts following the CMIP example (e.g. the Glacier Model Intercomparison Project or the Glacier Ice Thickness Estimation Working Group). In the recent past, great advances have been made in the global availability of data and methods relevant for glacier modeling, spanning glacier outlines, automatized glacier centerline identification, bed rock inversion methods, and global topographic data sets. Taken together, these advances now allow the ice dynamics of glaciers to be modeled on a global scale, provided that adequate modeling platforms are available. Here, we present the Open Global Glacier Model (OGGM), developed to provide a global scale, modular, and open source numerical model framework for consistently simulating past and future global scale glacier change. Global not only in the sense of leading to meaningful results for all glaciers combined, but also for any small ensemble of glaciers, e.g. at the headwater catchment scale. Modular to allow combinations of different approaches to the representation of ice flow and surface mass balance, enabling a new kind of model intercomparison. Open source so that the code can be read and used by anyone and so that new modules can be added and discussed by the community, following the principles of open governance. Consistent in order to provide uncertainty measures at all realizable scales.

Standard error propagation in R-matrix model fitting for light elements

International Nuclear Information System (INIS)

Chen Zhenpeng; Zhang Rui; Sun Yeying; Liu Tingjin

2003-01-01

The error propagation features with R-matrix model fitting 7 Li, 11 B and 17 O systems were researched systematically. Some laws of error propagation were revealed, an empirical formula P j = U j c / U j d = K j · S-bar · √m / √N for describing standard error propagation was established, the most likely error ranges for standard cross sections of 6 Li(n,t), 10 B(n,α0) and 10 B(n,α1) were estimated. The problem that the standard error of light nuclei standard cross sections may be too small results mainly from the R-matrix model fitting, which is not perfect. Yet R-matrix model fitting is the most reliable evaluation method for such data. The error propagation features of R-matrix model fitting for compound nucleus system of 7 Li, 11 B and 17 O has been studied systematically, some laws of error propagation are revealed, and these findings are important in solving the problem mentioned above. Furthermore, these conclusions are suitable for similar model fitting in other scientific fields. (author)

Model-fitting approach to kinetic analysis of non-isothermal oxidation of molybdenite

International Nuclear Information System (INIS)

Ebrahimi Kahrizsangi, R.; Abbasi, M. H.; Saidi, A.

2007-01-01

The kinetics of molybdenite oxidation was studied by non-isothermal TGA-DTA with heating rate 5 d eg C .min -1 . The model-fitting kinetic approach applied to TGA data. The Coats-Redfern method used of model fitting. The popular model-fitting gives excellent fit non-isothermal data in chemically controlled regime. The apparent activation energy was determined to be about 34.2 kcalmol -1 With pre-exponential factor about 10 8 sec -1 for extent of reaction less than 0.5

Supersymmetric Fits after the Higgs Discovery and Implications for Model Building

CERN Document Server

Ellis, John

2014-01-01

The data from the first run of the LHC at 7 and 8 TeV, together with the information provided by other experiments such as precision electroweak measurements, flavour measurements, the cosmological density of cold dark matter and the direct search for the scattering of dark matter particles in the LUX experiment, provide important constraints on supersymmetric models. Important information is provided by the ATLAS and CMS measurements of the mass of the Higgs boson, as well as the negative results of searches at the LHC for events with missing transverse energy accompanied by jets, and the LHCb and CMS measurements off BR($B_s \\to \\mu^+ \\mu^-$). Results are presented from frequentist analyses of the parameter spaces of the CMSSM and NUHM1. The global $\\chi^2$ functions for the supersymmetric models vary slowly over most of the parameter spaces allowed by the Higgs mass and the missing transverse energy search, with best-fit values that are comparable to the $\\chi^2$ for the Standard Model. The $95\\%$ CL lower...

Significant uncertainty in global scale hydrological modeling from precipitation data errors

Science.gov (United States)

Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

2015-10-01

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.

When the model fits the frame: the impact of regulatory fit on efficacy appraisal and persuasion in health communication.

Science.gov (United States)

Bosone, Lucia; Martinez, Frédéric; Kalampalikis, Nikos

2015-04-01

In health-promotional campaigns, positive and negative role models can be deployed to illustrate the benefits or costs of certain behaviors. The main purpose of this article is to investigate why, how, and when exposure to role models strengthens the persuasiveness of a message, according to regulatory fit theory. We argue that exposure to a positive versus a negative model activates individuals' goals toward promotion rather than prevention. By means of two experiments, we demonstrate that high levels of persuasion occur when a message advertising healthy dietary habits offers a regulatory fit between its framing and the described role model. Our data also establish that the effects of such internal regulatory fit by vicarious experience depend on individuals' perceptions of response-efficacy and self-efficacy. Our findings constitute a significant theoretical complement to previous research on regulatory fit and contain valuable practical implications for health-promotional campaigns. © 2015 by the Society for Personality and Social Psychology, Inc.

Flexible competing risks regression modeling and goodness-of-fit

DEFF Research Database (Denmark)

Scheike, Thomas; Zhang, Mei-Jie

2008-01-01

In this paper we consider different approaches for estimation and assessment of covariate effects for the cumulative incidence curve in the competing risks model. The classic approach is to model all cause-specific hazards and then estimate the cumulative incidence curve based on these cause...... models that is easy to fit and contains the Fine-Gray model as a special case. One advantage of this approach is that our regression modeling allows for non-proportional hazards. This leads to a new simple goodness-of-fit procedure for the proportional subdistribution hazards assumption that is very easy...... of the flexible regression models to analyze competing risks data when non-proportionality is present in the data....

An NCME Instructional Module on Item-Fit Statistics for Item Response Theory Models

Science.gov (United States)

Ames, Allison J.; Penfield, Randall D.

2015-01-01

Drawing valid inferences from item response theory (IRT) models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. This instructional module provides an overview of methods used for evaluating the fit of IRT models. Upon completing…

Critical elements on fitting the Bayesian multivariate Poisson Lognormal model

Science.gov (United States)

Zamzuri, Zamira Hasanah binti

2015-10-01

Motivated by a problem on fitting multivariate models to traffic accident data, a detailed discussion of the Multivariate Poisson Lognormal (MPL) model is presented. This paper reveals three critical elements on fitting the MPL model: the setting of initial estimates, hyperparameters and tuning parameters. These issues have not been highlighted in the literature. Based on simulation studies conducted, we have shown that to use the Univariate Poisson Model (UPM) estimates as starting values, at least 20,000 iterations are needed to obtain reliable final estimates. We also illustrated the sensitivity of the specific hyperparameter, which if it is not given extra attention, may affect the final estimates. The last issue is regarding the tuning parameters where they depend on the acceptance rate. Finally, a heuristic algorithm to fit the MPL model is presented. This acts as a guide to ensure that the model works satisfactorily given any data set.

Item level diagnostics and model - data fit in item response theory ...

African Journals Online (AJOL)

Item response theory (IRT) is a framework for modeling and analyzing item response data. Item-level modeling gives IRT advantages over classical test theory. The fit of an item score pattern to an item response theory (IRT) models is a necessary condition that must be assessed for further use of item and models that best fit ...

Understanding the Concept of Fit-For-Purpose Land Administration in Support of the Post 2015 Global Agenda

DEFF Research Database (Denmark)

Enemark, Stig

2015-01-01

on top-end technical solutions and high accuracy surveys. Of course, such flexibility allows for land administration systems to be incrementally improved over time. This paper unfolds the Fit-For-Purpose concept by analysing the three core components: • The spatial framework (large scale land parcel......This paper argues that the fit-for-purpose approach to building land administration systems in less developed countries will enable provision of the basic administrative frameworks for managing the people to land relationship that is fundamental for meeting the upcoming post 2015 global agenda....... The term “Fit-For-Purpose Land Administration” indicates that the approach used for building land administration systems in less developed countries should be flexible and focused on serving the purpose of the systems (such as providing security of tenure and control of land use) rather than focusing...

Fitting ARMA Time Series by Structural Equation Models.

Science.gov (United States)

van Buuren, Stef

1997-01-01

This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)

Identifying best-fitting inputs in health-economic model calibration: a Pareto frontier approach.

Science.gov (United States)

Enns, Eva A; Cipriano, Lauren E; Simons, Cyrena T; Kong, Chung Yin

2015-02-01

To identify best-fitting input sets using model calibration, individual calibration target fits are often combined into a single goodness-of-fit (GOF) measure using a set of weights. Decisions in the calibration process, such as which weights to use, influence which sets of model inputs are identified as best-fitting, potentially leading to different health economic conclusions. We present an alternative approach to identifying best-fitting input sets based on the concept of Pareto-optimality. A set of model inputs is on the Pareto frontier if no other input set simultaneously fits all calibration targets as well or better. We demonstrate the Pareto frontier approach in the calibration of 2 models: a simple, illustrative Markov model and a previously published cost-effectiveness model of transcatheter aortic valve replacement (TAVR). For each model, we compare the input sets on the Pareto frontier to an equal number of best-fitting input sets according to 2 possible weighted-sum GOF scoring systems, and we compare the health economic conclusions arising from these different definitions of best-fitting. For the simple model, outcomes evaluated over the best-fitting input sets according to the 2 weighted-sum GOF schemes were virtually nonoverlapping on the cost-effectiveness plane and resulted in very different incremental cost-effectiveness ratios ($79,300 [95% CI 72,500-87,600] v. $139,700 [95% CI 79,900-182,800] per quality-adjusted life-year [QALY] gained). Input sets on the Pareto frontier spanned both regions ($79,000 [95% CI 64,900-156,200] per QALY gained). The TAVR model yielded similar results. Choices in generating a summary GOF score may result in different health economic conclusions. The Pareto frontier approach eliminates the need to make these choices by using an intuitive and transparent notion of optimality as the basis for identifying best-fitting input sets. © The Author(s) 2014.

Mapping the global depth to bedrock for land surface modelling

Science.gov (United States)

Shangguan, W.; Hengl, T.; Yuan, H.; Dai, Y. J.; Zhang, S.

2017-12-01

Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of Depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 130,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surfacee reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forests and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.

SPSS macros to compare any two fitted values from a regression model.

Science.gov (United States)

Weaver, Bruce; Dubois, Sacha

2012-12-01

In regression models with first-order terms only, the coefficient for a given variable is typically interpreted as the change in the fitted value of Y for a one-unit increase in that variable, with all other variables held constant. Therefore, each regression coefficient represents the difference between two fitted values of Y. But the coefficients represent only a fraction of the possible fitted value comparisons that might be of interest to researchers. For many fitted value comparisons that are not captured by any of the regression coefficients, common statistical software packages do not provide the standard errors needed to compute confidence intervals or carry out statistical tests-particularly in more complex models that include interactions, polynomial terms, or regression splines. We describe two SPSS macros that implement a matrix algebra method for comparing any two fitted values from a regression model. The !OLScomp and !MLEcomp macros are for use with models fitted via ordinary least squares and maximum likelihood estimation, respectively. The output from the macros includes the standard error of the difference between the two fitted values, a 95% confidence interval for the difference, and a corresponding statistical test with its p-value.

LEP asymmetries and fits of the standard model

International Nuclear Information System (INIS)

Pietrzyk, B.

1994-01-01

The lepton and quark asymmetries measured at LEP are presented. The results of the Standard Model fits to the electroweak data presented at this conference are given. The top mass obtained from the fit to the LEP data is 172 -14-20 +13+18 GeV; it is 177 -11-19 +11+18 when also the collider, ν and A LR data are included. (author). 10 refs., 3 figs., 2 tabs

BETR global - A geographically-explicit global-scale multimedia contaminant fate model

International Nuclear Information System (INIS)

MacLeod, Matthew; Waldow, Harald von; Tay, Pascal; Armitage, James M.; Woehrnschimmel, Henry; Riley, William J.; McKone, Thomas E.; Hungerbuhler, Konrad

2011-01-01

We present two new software implementations of the BETR Global multimedia contaminant fate model. The model uses steady-state or non-steady-state mass-balance calculations to describe the fate and transport of persistent organic pollutants using a desktop computer. The global environment is described using a database of long-term average monthly conditions on a 15 o x 15 o grid. We demonstrate BETR Global by modeling the global sources, transport, and removal of decamethylcyclopentasiloxane (D5). - Two new software implementations of the Berkeley-Trent Global Contaminant Fate Model are available. The new model software is illustrated using a case study of the global fate of decamethylcyclopentasiloxane (D5).

Validation of individual and aggregate global flood hazard models for two major floods in Africa.

Science.gov (United States)

Trigg, M.; Bernhofen, M.; Whyman, C.

2017-12-01

A recent intercomparison of global flood hazard models undertaken by the Global Flood Partnership shows that there is an urgent requirement to undertake more validation of the models against flood observations. As part of the intercomparison, the aggregated model dataset resulting from the project was provided as open access data. We compare the individual and aggregated flood extent output from the six global models and test these against two major floods in the African Continent within the last decade, namely severe flooding on the Niger River in Nigeria in 2012, and on the Zambezi River in Mozambique in 2007. We test if aggregating different number and combination of models increases model fit to the observations compared with the individual model outputs. We present results that illustrate some of the challenges of comparing imperfect models with imperfect observations and also that of defining the probability of a real event in order to test standard model output probabilities. Finally, we propose a collective set of open access validation flood events, with associated observational data and descriptions that provide a standard set of tests across different climates and hydraulic conditions.

High sensitivity cavity ring down spectroscopy of N_2O near 1.22 µm: (II) "1"4N_2"1"6O line intensity modeling and global fit of "1"4N_2"1"8O line positions

International Nuclear Information System (INIS)

Tashkun, S.A.; Perevalov, V.I.; Karlovets, E.V.; Kassi, S.; Campargue, A.

2016-01-01

In a recent work (Karlovets et al., 2016 [1]), we reported the measurement and rovibrational assignments of more than 3300 transitions belonging to 64 bands of five nitrous oxide isotopologues ("1"4N_2"1"6O, "1"4N"1"5N"1"6O, "1"5N"1"4N"1"6O, "1"4N_2"1"8O and "1"4N_2"1"7O) in the high sensitivity CRDS spectrum recorded in the 7915–8334 cm"−"1 spectral range. The assignments were performed by comparison with predictions of the effective Hamiltonian models developed for each isotopologue. In the present paper, the large amount of measurements from our previous work mentioned above and literature are gathered to refine the modeling of the nitrous oxide spectrum in two ways: (i) improvement of the intensity modeling for the principal isotopologue, "1"4N_2"1"6O, near 8000 cm"−"1 from a new fit of the relevant effective dipole moment parameters, (ii) global modeling of "1"4N_2"1"8O line positions from a new fit of the parameters of the global effective Hamiltonian using an exhaustive input dataset collected in the literature in the 12–8231 cm"−"1 region. The fitted set of 81 parameters allowed reproducing near 5800 measured line positions with an RMS deviation of 0.0016 cm"−"1. The dimensionless weighted standard deviation of the fit is 1.22. As an illustration of the improvement of the predictive capabilities of the obtained effective Hamiltonian, two new "1"4N_2"1"8O bands could be assigned in the CRDS spectrum in the 7915–8334 cm"−"1 spectral range. A line list at 296 K has been generated in the 0–10,700 cm"−"1 range for "1"4N_2"1"8O in natural abundance with a 10"−"3"0 cm/molecule intensity cutoff. - Highlights: • Line parameters of two new "1"4N_2"1"8O bands centered at 7966 cm"−"1 and at 8214 cm"−"1. • Refined sets of the "1"4N_2"1"6O effective dipole moment parameters for ΔP=13,14 series. • Global modeling of "1"4N_2"1"8O line positions and intensities in the 12–8231 cm"−"1 range. • 5800 observed of "1"4N_2"1"8O line positions

Global Delivery Models

DEFF Research Database (Denmark)

Manning, Stephan; Larsen, Marcus M.; Bharati, Pratyush

2013-01-01

This article examines antecedents and performance implications of global delivery models (GDMs) in global business services. GDMs require geographically distributed operations to exploit both proximity to clients and time-zone spread for efficient service delivery. We propose and empirically show...

Checking the Adequacy of Fit of Models from Split-Plot Designs

DEFF Research Database (Denmark)

Almini, A. A.; Kulahci, Murat; Montgomery, D. C.

2009-01-01

models. In this article, we propose the computation of two R-2, R-2-adjusted, prediction error sums of squares (PRESS), and R-2-prediction statistics to measure the adequacy of fit for the WP and the SP submodels in a split-plot design. This is complemented with the graphical analysis of the two types......One of the main features that distinguish split-plot experiments from other experiments is that they involve two types of experimental errors: the whole-plot (WP) error and the subplot (SP) error. Taking this into consideration is very important when computing measures of adequacy of fit for split-plot...... of errors to check for any violation of the underlying assumptions and the adequacy of fit of split-plot models. Using examples, we show how computing two measures of model adequacy of fit for each split-plot design model is appropriate and useful as they reveal whether the correct WP and SP effects have...

Repair models of cell survival and corresponding computer program for survival curve fitting

International Nuclear Information System (INIS)

Shen Xun; Hu Yiwei

1992-01-01

Some basic concepts and formulations of two repair models of survival, the incomplete repair (IR) model and the lethal-potentially lethal (LPL) model, are introduced. An IBM-PC computer program for survival curve fitting with these models was developed and applied to fit the survivals of human melanoma cells HX118 irradiated at different dose rates. Comparison was made between the repair models and two non-repair models, the multitar get-single hit model and the linear-quadratic model, in the fitting and analysis of the survival-dose curves. It was shown that either IR model or LPL model can fit a set of survival curves of different dose rates with same parameters and provide information on the repair capacity of cells. These two mathematical models could be very useful in quantitative study on the radiosensitivity and repair capacity of cells

HDFITS: Porting the FITS data model to HDF5

Science.gov (United States)

Price, D. C.; Barsdell, B. R.; Greenhill, L. J.

2015-09-01

The FITS (Flexible Image Transport System) data format has been the de facto data format for astronomy-related data products since its inception in the late 1970s. While the FITS file format is widely supported, it lacks many of the features of more modern data serialization, such as the Hierarchical Data Format (HDF5). The HDF5 file format offers considerable advantages over FITS, such as improved I/O speed and compression, but has yet to gain widespread adoption within astronomy. One of the major holdbacks is that HDF5 is not well supported by data reduction software packages and image viewers. Here, we present a comparison of FITS and HDF5 as a format for storage of astronomy datasets. We show that the underlying data model of FITS can be ported to HDF5 in a straightforward manner, and that by doing so the advantages of the HDF5 file format can be leveraged immediately. In addition, we present a software tool, fits2hdf, for converting between FITS and a new 'HDFITS' format, where data are stored in HDF5 in a FITS-like manner. We show that HDFITS allows faster reading of data (up to 100x of FITS in some use cases), and improved compression (higher compression ratios and higher throughput). Finally, we show that by only changing the import lines in Python-based FITS utilities, HDFITS formatted data can be presented transparently as an in-memory FITS equivalent.

Modelling 1-minute directional observations of the global irradiance.

Science.gov (United States)

Thejll, Peter; Pagh Nielsen, Kristian; Andersen, Elsa; Furbo, Simon

2016-04-01

Direct and diffuse irradiances from the sky has been collected at 1-minute intervals for about a year from the experimental station at the Technical University of Denmark for the IEA project "Solar Resource Assessment and Forecasting". These data were gathered by pyrheliometers tracking the Sun, as well as with apertured pyranometers gathering 1/8th and 1/16th of the light from the sky in 45 degree azimuthal ranges pointed around the compass. The data are gathered in order to develop detailed models of the potentially available solar energy and its variations at high temporal resolution in order to gain a more detailed understanding of the solar resource. This is important for a better understanding of the sub-grid scale cloud variation that cannot be resolved with climate and weather models. It is also important for optimizing the operation of active solar energy systems such as photovoltaic plants and thermal solar collector arrays, and for passive solar energy and lighting to buildings. We present regression-based modelling of the observed data, and focus, here, on the statistical properties of the model fits. Using models based on the one hand on what is found in the literature and on physical expectations, and on the other hand on purely statistical models, we find solutions that can explain up to 90% of the variance in global radiation. The models leaning on physical insights include terms for the direct solar radiation, a term for the circum-solar radiation, a diffuse term and a term for the horizon brightening/darkening. The purely statistical model is found using data- and formula-validation approaches picking model expressions from a general catalogue of possible formulae. The method allows nesting of expressions, and the results found are dependent on and heavily constrained by the cross-validation carried out on statistically independent testing and training data-sets. Slightly better fits -- in terms of variance explained -- is found using the purely

Modeling of the Earth's gravity field using the New Global Earth Model (NEWGEM)

Science.gov (United States)

Kim, Yeong E.; Braswell, W. Danny

1989-01-01

Traditionally, the global gravity field was described by representations based on the spherical harmonics (SH) expansion of the geopotential. The SH expansion coefficients were determined by fitting the Earth's gravity data as measured by many different methods including the use of artificial satellites. As gravity data have accumulated with increasingly better accuracies, more of the higher order SH expansion coefficients were determined. The SH representation is useful for describing the gravity field exterior to the Earth but is theoretically invalid on the Earth's surface and in the Earth's interior. A new global Earth model (NEWGEM) (KIM, 1987 and 1988a) was recently proposed to provide a unified description of the Earth's gravity field inside, on, and outside the Earth's surface using the Earth's mass density profile as deduced from seismic studies, elevation and bathymetric information, and local and global gravity data. Using NEWGEM, it is possible to determine the constraints on the mass distribution of the Earth imposed by gravity, topography, and seismic data. NEWGEM is useful in investigating a variety of geophysical phenomena. It is currently being utilized to develop a geophysical interpretation of Kaula's rule. The zeroth order NEWGEM is being used to numerically integrate spherical harmonic expansion coefficients and simultaneously determine the contribution of each layer in the model to a given coefficient. The numerically determined SH expansion coefficients are also being used to test the validity of SH expansions at the surface of the Earth by comparing the resulting SH expansion gravity model with exact calculations of the gravity at the Earth's surface.

Global ice sheet modeling

International Nuclear Information System (INIS)

Hughes, T.J.; Fastook, J.L.

1994-05-01

The University of Maine conducted this study for Pacific Northwest Laboratory (PNL) as part of a global climate modeling task for site characterization of the potential nuclear waste respository site at Yucca Mountain, NV. The purpose of the study was to develop a global ice sheet dynamics model that will forecast the three-dimensional configuration of global ice sheets for specific climate change scenarios. The objective of the third (final) year of the work was to produce ice sheet data for glaciation scenarios covering the next 100,000 years. This was accomplished using both the map-plane and flowband solutions of our time-dependent, finite-element gridpoint model. The theory and equations used to develop the ice sheet models are presented. Three future scenarios were simulated by the model and results are discussed

Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

Science.gov (United States)

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.

Modelling population dynamics model formulation, fitting and assessment using state-space methods

CERN Document Server

Newman, K B; Morgan, B J T; King, R; Borchers, D L; Cole, D J; Besbeas, P; Gimenez, O; Thomas, L

2014-01-01

This book gives a unifying framework for estimating the abundance of open populations: populations subject to births, deaths and movement, given imperfect measurements or samples of the populations.  The focus is primarily on populations of vertebrates for which dynamics are typically modelled within the framework of an annual cycle, and for which stochastic variability in the demographic processes is usually modest. Discrete-time models are developed in which animals can be assigned to discrete states such as age class, gender, maturity,  population (within a metapopulation), or species (for multi-species models). The book goes well beyond estimation of abundance, allowing inference on underlying population processes such as birth or recruitment, survival and movement. This requires the formulation and fitting of population dynamics models.  The resulting fitted models yield both estimates of abundance and estimates of parameters characterizing the underlying processes.  

Spatial modeling of agricultural land use change at global scale

Science.gov (United States)

Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

2014-11-01

Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling

Tests of fit of historically-informed models of African American Admixture.

Science.gov (United States)

Gross, Jessica M

2018-02-01

African American populations in the U.S. formed primarily by mating between Africans and Europeans over the last 500 years. To date, studies of admixture have focused on either a one-time admixture event or continuous input into the African American population from Europeans only. Our goal is to gain a better understanding of the admixture process by examining models that take into account (a) assortative mating by ancestry in the African American population, (b) continuous input from both Europeans and Africans, and (c) historically informed variation in the rate of African migration over time. We used a model-based clustering method to generate distributions of African ancestry in three samples comprised of 147 African Americans from two published sources. We used a log-likelihood method to examine the fit of four models to these distributions and used a log-likelihood ratio test to compare the relative fit of each model. The mean ancestry estimates for our datasets of 77% African/23% European to 83% African/17% European ancestry are consistent with previous studies. We find admixture models that incorporate continuous gene flow from Europeans fit significantly better than one-time event models, and that a model involving continuous gene flow from Africans and Europeans fits better than one with continuous gene flow from Europeans only for two samples. Importantly, models that involve continuous input from Africans necessitate a higher level of gene flow from Europeans than previously reported. We demonstrate that models that take into account information about the rate of African migration over the past 500 years fit observed patterns of African ancestry better than alternative models. Our approach will enrich our understanding of the admixture process in extant and past populations. © 2017 Wiley Periodicals, Inc.

[How to fit and interpret multilevel models using SPSS].

Science.gov (United States)

Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael

2007-05-01

Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.

A versatile curve-fit model for linear to deeply concave rank abundance curves

NARCIS (Netherlands)

Neuteboom, J.H.; Struik, P.C.

2005-01-01

A new, flexible curve-fit model for linear to concave rank abundance curves was conceptualized and validated using observational data. The model links the geometric-series model and log-series model and can also fit deeply concave rank abundance curves. The model is based ¿ in an unconventional way

Modelling MIZ dynamics in a global model

Science.gov (United States)

Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto

2016-04-01

Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.

Fitting Equilibrium Search Models to Labour Market Data

DEFF Research Database (Denmark)

Bowlus, Audra J.; Kiefer, Nicholas M.; Neumann, George R.

1996-01-01

Specification and estimation of a Burdett-Mortensen type equilibrium search model is considered. The estimation is nonstandard. An estimation strategy asymptotically equivalent to maximum likelihood is proposed and applied. The results indicate that specifications with a small number of productiv...... of productivity types fit the data well compared to the homogeneous model....

Fast Algorithms for Fitting Active Appearance Models to Unconstrained Images

NARCIS (Netherlands)

Tzimiropoulos, Georgios; Pantic, Maja

2016-01-01

Fitting algorithms for Active Appearance Models (AAMs) are usually considered to be robust but slow or fast but less able to generalize well to unseen variations. In this paper, we look into AAM fitting algorithms and make the following orthogonal contributions: We present a simple “project-out‿

Fast and exact Newton and Bidirectional fitting of Active Appearance Models.

Science.gov (United States)

Kossaifi, Jean; Tzimiropoulos, Yorgos; Pantic, Maja

2016-12-21

Active Appearance Models (AAMs) are generative models of shape and appearance that have proven very attractive for their ability to handle wide changes in illumination, pose and occlusion when trained in the wild, while not requiring large training dataset like regression-based or deep learning methods. The problem of fitting an AAM is usually formulated as a non-linear least squares one and the main way of solving it is a standard Gauss-Newton algorithm. In this paper we extend Active Appearance Models in two ways: we first extend the Gauss-Newton framework by formulating a bidirectional fitting method that deforms both the image and the template to fit a new instance. We then formulate a second order method by deriving an efficient Newton method for AAMs fitting. We derive both methods in a unified framework for two types of Active Appearance Models, holistic and part-based, and additionally show how to exploit the structure in the problem to derive fast yet exact solutions. We perform a thorough evaluation of all algorithms on three challenging and recently annotated inthe- wild datasets, and investigate fitting accuracy, convergence properties and the influence of noise in the initialisation. We compare our proposed methods to other algorithms and show that they yield state-of-the-art results, out-performing other methods while having superior convergence properties.

The Meaning of Goodness-of-Fit Tests: Commentary on "Goodness-of-Fit Assessment of Item Response Theory Models"

Science.gov (United States)

Thissen, David

2013-01-01

In this commentary, David Thissen states that "Goodness-of-fit assessment for IRT models is maturing; it has come a long way from zero." Thissen then references prior works on "goodness of fit" in the index of Lord and Novick's (1968) classic text; Yen (1984); Drasgow, Levine, Tsien, Williams, and Mead (1995); Chen and…

Global Hail Model

Science.gov (United States)

Werner, A.; Sanderson, M.; Hand, W.; Blyth, A.; Groenemeijer, P.; Kunz, M.; Puskeiler, M.; Saville, G.; Michel, G.

2012-04-01

Hail risk models are rare for the insurance industry. This is opposed to the fact that average annual hail losses can be large and hail dominates losses for many motor portfolios worldwide. Insufficient observational data, high spatio-temporal variability and data inhomogenity have hindered creation of credible models so far. In January 2012, a selected group of hail experts met at Willis in London in order to discuss ways to model hail risk at various scales. Discussions aimed at improving our understanding of hail occurrence and severity, and covered recent progress in the understanding of microphysical processes and climatological behaviour and hail vulnerability. The final outcome of the meeting was the formation of a global hail risk model initiative and the launch of a realistic global hail model in order to assess hail loss occurrence and severities for the globe. The following projects will be tackled: Microphysics of Hail and hail severity measures: Understand the physical drivers of hail and hailstone size development in different regions on the globe. Proposed factors include updraft and supercooled liquid water content in the troposphere. What are the thresholds drivers of hail formation around the globe? Hail Climatology: Consider ways to build a realistic global climatological set of hail events based on physical parameters including spatial variations in total availability of moisture, aerosols, among others, and using neural networks. Vulnerability, Exposure, and financial model: Use historical losses and event footprints available in the insurance market to approximate fragility distributions and damage potential for various hail sizes for property, motor, and agricultural business. Propagate uncertainty distributions and consider effects of policy conditions along with aggregating and disaggregating exposure and losses. This presentation provides an overview of ideas and tasks that lead towards a comprehensive global understanding of hail risk for

The l z ( p ) * Person-Fit Statistic in an Unfolding Model Context.

Science.gov (United States)

Tendeiro, Jorge N

2017-01-01

Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded unfolding model is used. Results from a simulation study indicate that the person-fit statistic performed relatively well in detecting midpoint response style patterns and not so well in detecting extreme response style patterns.

arXiv A global fit of the MSSM with GAMBIT

CERN Document Server

Athron, Peter; Bringmann, Torsten; Buckley, Andy; Chrząszcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje; Raklev, Are; Rogan, Christopher; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Serra, Nicola; Weniger, Christoph; White, Martin

2017-12-18

We study the seven-dimensional Minimal Supersymmetric Standard Model (MSSM7) with the new GAMBIT software framework, with all parameters defined at the weak scale. Our analysis significantly extends previous weak-scale, phenomenological MSSM fits, by adding more and newer experimental analyses, improving the accuracy and detail of theoretical predictions, including dominant uncertainties from the Standard Model, the Galactic dark matter halo and the quark content of the nucleon, and employing novel and highly-efficient statistical sampling methods to scan the parameter space. We find regions of the MSSM7 that exhibit co-annihilation of neutralinos with charginos, stops and sbottoms, as well as models that undergo resonant annihilation via both light and heavy Higgs funnels. We find high-likelihood models with light charginos, stops and sbottoms that have the potential to be within the future reach of the LHC. Large parts of our preferred parameter regions will also be accessible to the next generation of dire...

BETR Global - A geographically explicit global-scale multimedia contaminant fate model

Energy Technology Data Exchange (ETDEWEB)

Macleod, M.; Waldow, H. von; Tay, P.; Armitage, J. M.; Wohrnschimmel, H.; Riley, W.; McKone, T. E.; Hungerbuhler, K.

2011-04-01

We present two new software implementations of the BETR Global multimedia contaminant fate model. The model uses steady-state or non-steady-state mass-balance calculations to describe the fate and transport of persistent organic pollutants using a desktop computer. The global environment is described using a database of long-term average monthly conditions on a 15{sup o} x 15{sup o} grid. We demonstrate BETR Global by modeling the global sources, transport, and removal of decamethylcyclopentasiloxane (D5).

Fit Gap Analysis – The Role of Business Process Reference Models

Directory of Open Access Journals (Sweden)

Dejan Pajk

2013-12-01

Full Text Available Enterprise resource planning (ERP systems support solutions for standard business processes such as financial, sales, procurement and warehouse. In order to improve the understandability and efficiency of their implementation, ERP vendors have introduced reference models that describe the processes and underlying structure of an ERP system. To select and successfully implement an ERP system, the capabilities of that system have to be compared with a company’s business needs. Based on a comparison, all of the fits and gaps must be identified and further analysed. This step usually forms part of ERP implementation methodologies and is called fit gap analysis. The paper theoretically overviews methods for applying reference models and describes fit gap analysis processes in detail. The paper’s first contribution is its presentation of a fit gap analysis using standard business process modelling notation. The second contribution is the demonstration of a process-based comparison approach between a supply chain process and an ERP system process reference model. In addition to its theoretical contributions, the results can also be practically applied to projects involving the selection and implementation of ERP systems.

A global fit of the γ-ray galactic center excess within the scalar singlet Higgs portal model

International Nuclear Information System (INIS)

Cuoco, Alessandro; Eiteneuer, Benedikt; Heisig, Jan; Krämer, Michael

2016-01-01

We analyse the excess in the γ-ray emission from the center of our galaxy observed by Fermi-LAT in terms of dark matter annihilation within the scalar Higgs portal model. In particular, we include the astrophysical uncertainties from the dark matter distribution and allow for unspecified additional dark matter components. We demonstrate through a detailed numerical fit that the strength and shape of the γ-ray spectrum can indeed be described by the model in various regions of dark matter masses and couplings. Constraints from invisible Higgs decays, direct dark matter searches, indirect searches in dwarf galaxies and for γ-ray lines, and constraints from the dark matter relic density reduce the parameter space to dark matter masses near the Higgs resonance. We find two viable regions: one where the Higgs-dark matter coupling is of O(10"−"2), and an additional dark matter component beyond the scalar WIMP of our model is preferred, and one region where the Higgs-dark matter coupling may be significantly smaller, but where the scalar WIMP constitutes a significant fraction or even all of dark matter. Both viable regions are hard to probe in future direct detection and collider experiments.

Soil physical properties influencing the fitting parameters in Philip and Kostiakov infiltration models

International Nuclear Information System (INIS)

Mbagwu, J.S.C.

1994-05-01

Among the many models developed for monitoring the infiltration process those of Philip and Kostiakov have been studied in detail because of their simplicity and the ease of estimating their fitting parameters. The important soil physical factors influencing the fitting parameters in these infiltration models are reported in this study. The results of the study show that the single most important soil property affecting the fitting parameters in these models is the effective porosity. 36 refs, 2 figs, 5 tabs

The fitness landscape of HIV-1 gag: advanced modeling approaches and validation of model predictions by in vitro testing.

Directory of Open Access Journals (Sweden)

Jaclyn K Mann

2014-08-01

Full Text Available Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model, generalizing our previous approach (Ising model that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = -0.74, p = 3.6×10-6 are strongly correlated, and this was further strengthened in the regularized Ising model (r = -0.83, p = 3.7×10-12. Performance of the Potts model (r = -0.73, p = 9.7×10-9 was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion

Global nuclear material control model

International Nuclear Information System (INIS)

Dreicer, J.S.; Rutherford, D.A.

1996-01-01

The nuclear danger can be reduced by a system for global management, protection, control, and accounting as part of a disposition program for special nuclear materials. The development of an international fissile material management and control regime requires conceptual research supported by an analytical and modeling tool that treats the nuclear fuel cycle as a complete system. Such a tool must represent the fundamental data, information, and capabilities of the fuel cycle including an assessment of the global distribution of military and civilian fissile material inventories, a representation of the proliferation pertinent physical processes, and a framework supportive of national or international perspective. They have developed a prototype global nuclear material management and control systems analysis capability, the Global Nuclear Material Control (GNMC) model. The GNMC model establishes the framework for evaluating the global production, disposition, and safeguards and security requirements for fissile nuclear material

Supersymmetry with prejudice: Fitting the wrong model to LHC data

Science.gov (United States)

Allanach, B. C.; Dolan, Matthew J.

2012-09-01

We critically examine interpretations of hypothetical supersymmetric LHC signals, fitting to alternative wrong models of supersymmetry breaking. The signals we consider are some of the most constraining on the sparticle spectrum: invariant mass distributions with edges and endpoints from the golden decay chain q˜→qχ20(→l˜±l∓q)→χ10l+l-q. We assume a constrained minimal supersymmetric standard model (CMSSM) point to be the ‘correct’ one, but fit the signals instead with minimal gauge mediated supersymmetry breaking models (mGMSB) with a neutralino quasistable lightest supersymmetric particle, minimal anomaly mediation and large volume string compactification models. Minimal anomaly mediation and large volume scenario can be unambiguously discriminated against the CMSSM for the assumed signal and 1fb-1 of LHC data at s=14TeV. However, mGMSB would not be discriminated on the basis of the kinematic endpoints alone. The best-fit point spectra of mGMSB and CMSSM look remarkably similar, making experimental discrimination at the LHC based on the edges or Higgs properties difficult. However, using rate information for the golden chain should provide the additional separation required.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species.

Science.gov (United States)

Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R

2017-01-04

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

Science.gov (United States)

Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.

A person fit test for IRT models for polytomous items

NARCIS (Netherlands)

Glas, Cornelis A.W.; Dagohoy, A.V.

2007-01-01

A person fit test based on the Lagrange multiplier test is presented for three item response theory models for polytomous items: the generalized partial credit model, the sequential model, and the graded response model. The test can also be used in the framework of multidimensional ability

The lz(p)* Person-Fit Statistic in an Unfolding Model Context

NARCIS (Netherlands)

Tendeiro, Jorge N.

2017-01-01

Although person-fit analysis has a long-standing tradition within item response theory, it has been applied in combination with dominance response models almost exclusively. In this article, a popular log likelihood-based parametric person-fit statistic under the framework of the generalized graded

MSSM fits to the ATLAS 1 lepton excess

Energy Technology Data Exchange (ETDEWEB)

Kowalska, Kamila [TU Dortmund, Fakultaet fuer Physik, Dortmund (Germany); Sessolo, Enrico Maria [National Centre for Nuclear Research, Warsaw (Poland)

2017-02-15

We use the framework of the p19MSSM to perform a fit to the mild excesses over the Standard Model background recently observed in three bins of the ATLAS 1-lepton + (b-)jets + E{sub T}{sup miss} search. We find a few types of spectra that can fit the emerging signal and at the same time are not excluded by other LHC searches. They can be grouped roughly in two categories. The first class is characterized by the presence of one stop or stop and sbottoms with mass in the ballpark of 700-800 GeV and a neutralino LSP of mass around 400 GeV, with or without the additional presence of an intermediate chargino. In the second type of scenarios the stop, lightest chargino, sbottom if present, and the neutralino are about or heavier than ∝ 650 GeV and the signal originates from cascade decays of squarks of the 1st and 2nd generation, which should have a mass of 1.1-1.2 TeV. For the best-fit scenarios, we compare the global chi-squared with several ATLAS and CMS searches with the corresponding chi-squared of the Standard Model expectation, showing that the putative signal is also favored globally with respect to the background-only hypothesis. We point out that if the observed excess persists in the next round of data, it should be accompanied by associated significant excesses in all-hadronic final-state searches. (orig.)

Global corporate workplaces implementing new global workplace standards in a local context

CERN Document Server

Hodulak, Martin

2017-01-01

In recent years, multinational corporations were increasingly engaged in the development of standardized global workplace models. For their implementation and feasibility, it is decisive as how these standards fit the diverse regional workplace cultures. This topic was pursued in the course of a research project, comparing established workplaces in Germany, USA and Japan against global workplace standards of multinational corporations. The analysis confirmed the expected differences among local workplaces and on the other hand a predominant mainstream among global corporate workplace standards. Conspicuous however, are the fundamental differences between local models and corporate standards. For the implementation of global standards in local context, this implies multiple challenges on cultural, organizational and spatial level. The analysis findings provide information for assessing current projects and pinpointing optimization measures. The analysis framework further provides a tool to uncover and assess n...

Global spatiotemporal distribution of soil respiration modeled using a global database

Science.gov (United States)

Hashimoto, S.; Carvalhais, N.; Ito, A.; Migliavacca, M.; Nishina, K.; Reichstein, M.

2015-07-01

The flux of carbon dioxide from the soil to the atmosphere (soil respiration) is one of the major fluxes in the global carbon cycle. At present, the accumulated field observation data cover a wide range of geographical locations and climate conditions. However, there are still large uncertainties in the magnitude and spatiotemporal variation of global soil respiration. Using a global soil respiration data set, we developed a climate-driven model of soil respiration by modifying and updating Raich's model, and the global spatiotemporal distribution of soil respiration was examined using this model. The model was applied at a spatial resolution of 0.5°and a monthly time step. Soil respiration was divided into the heterotrophic and autotrophic components of respiration using an empirical model. The estimated mean annual global soil respiration was 91 Pg C yr-1 (between 1965 and 2012; Monte Carlo 95 % confidence interval: 87-95 Pg C yr-1) and increased at the rate of 0.09 Pg C yr-2. The contribution of soil respiration from boreal regions to the total increase in global soil respiration was on the same order of magnitude as that of tropical and temperate regions, despite a lower absolute magnitude of soil respiration in boreal regions. The estimated annual global heterotrophic respiration and global autotrophic respiration were 51 and 40 Pg C yr-1, respectively. The global soil respiration responded to the increase in air temperature at the rate of 3.3 Pg C yr-1 °C-1, and Q10 = 1.4. Our study scaled up observed soil respiration values from field measurements to estimate global soil respiration and provide a data-oriented estimate of global soil respiration. The estimates are based on a semi-empirical model parameterized with over one thousand data points. Our analysis indicates that the climate controls on soil respiration may translate into an increasing trend in global soil respiration and our analysis emphasizes the relevance of the soil carbon flux from soil to

After the Higgs: status and prospects of the electroweak fit of the SM and beyond -- with Gfitter

CERN Multimedia

CERN. Geneva

2013-01-01

models are also obtained, through an analysis of the so-called oblique parameters. We discuss the impact of the electroweak fit on Higgs coupling studies and vice versa. Future measurements at the Large Hadron Collider and the International Linear Collider promise to improve the experimental precision of key observables used in the fit. We present the prospects of the global electroweak fit in view of these improvements.

FIT ANALYSIS OF INDOSAT DOMPETKU BUSINESS MODEL USING A STRATEGIC DIAGNOSIS APPROACH

Directory of Open Access Journals (Sweden)

Fauzi Ridwansyah

2015-09-01

Full Text Available Mobile payment is an industry's response to global and regional technological-driven, as well as national social-economical driven in less cash society development. The purposes of this study were 1 identifying positioning of PT. Indosat in providing a response to Indonesian mobile payment market, 2 analyzing Indosat’s internal capabilities and business model fit with environment turbulence, and 3 formulating the optimum mobile payment business model development design for Indosat. The method used in this study was a combination of qualitative and quantitative analysis through in-depth interviews with purposive judgment sampling. The analysis tools used in this study were Business Model Canvas (MBC and Ansoff’s Strategic Diagnosis. The interviewees were the representatives of PT. Indosat internal management and mobile payment business value chain stakeholders. Based on BMC mapping which is then analyzed by strategic diagnosis model, a considerable gap (>1 between the current market environment and Indosat strategy of aggressiveness with the expected future of environment turbulence level was obtained. Therefore, changes in the competitive strategy that need to be conducted include 1 developing a new customer segment, 2 shifting the value proposition that leads to the extensification of mobile payment, 3 monetizing effective value proposition, and 4 integrating effective collaboration for harmonizing company’s objective with the government's vision. Keywords: business model canvas, Indosat, mobile payment, less cash society, strategic diagnosis

Experimental Rugged Fitness Landscape in Protein Sequence Space

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-01-01

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12–130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7×104-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18–24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region. PMID:17183728

Experimental rugged fitness landscape in protein sequence space.

Science.gov (United States)

Hayashi, Yuuki; Aita, Takuyo; Toyota, Hitoshi; Husimi, Yuzuru; Urabe, Itaru; Yomo, Tetsuya

2006-12-20

The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4)-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1) the dependence of stationary fitness on library size, which increased gradually, and (2) the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

Experimental rugged fitness landscape in protein sequence space.

Directory of Open Access Journals (Sweden)

Yuuki Hayashi

Full Text Available The fitness landscape in sequence space determines the process of biomolecular evolution. To plot the fitness landscape of protein function, we carried out in vitro molecular evolution beginning with a defective fd phage carrying a random polypeptide of 139 amino acids in place of the g3p minor coat protein D2 domain, which is essential for phage infection. After 20 cycles of random substitution at sites 12-130 of the initial random polypeptide and selection for infectivity, the selected phage showed a 1.7x10(4-fold increase in infectivity, defined as the number of infected cells per ml of phage suspension. Fitness was defined as the logarithm of infectivity, and we analyzed (1 the dependence of stationary fitness on library size, which increased gradually, and (2 the time course of changes in fitness in transitional phases, based on an original theory regarding the evolutionary dynamics in Kauffman's n-k fitness landscape model. In the landscape model, single mutations at single sites among n sites affect the contribution of k other sites to fitness. Based on the results of these analyses, k was estimated to be 18-24. According to the estimated parameters, the landscape was plotted as a smooth surface up to a relative fitness of 0.4 of the global peak, whereas the landscape had a highly rugged surface with many local peaks above this relative fitness value. Based on the landscapes of these two different surfaces, it appears possible for adaptive walks with only random substitutions to climb with relative ease up to the middle region of the fitness landscape from any primordial or random sequence, whereas an enormous range of sequence diversity is required to climb further up the rugged surface above the middle region.

A global central banker competency model

Directory of Open Access Journals (Sweden)

David W. Brits

2014-07-01

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

Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

KAUST Repository

Zhang, Saijuan; Krebs-Smith, Susan M.; Midthune, Douglas; Perez, Adriana; Buckman, Dennis W.; Kipnis, Victor; Freedman, Laurence S.; Dodd, Kevin W.; Carroll, Raymond J

2011-01-01

There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole

Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

KAUST Repository

Zhang, Saijuan

2011-01-06

There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole

Using a Global Climate Model in an On-line Climate Change Course

Science.gov (United States)

Randle, D. E.; Chandler, M. A.; Sohl, L. E.

2012-12-01

Seminars on Science: Climate Change is an on-line, graduate-level teacher professional development course offered by the American Museum of Natural History. It is an intensive 6-week course covering a broad range of global climate topics, from the fundamentals of the climate system, to the causes of climate change, the role of paleoclimate investigations, and a discussion of potential consequences and risks. The instructional method blends essays, videos, textbooks, and linked websites, with required participation in electronic discussion forums that are moderated by an experienced educator and a course scientist. Most weeks include additional assignments. Three of these assignments employ computer models, including two weeks spent working with a full-fledged 3D global climate model (GCM). The global climate modeling environment is supplied through a partnership with Columbia University's Educational Global Climate Modeling Project (EdGCM). The objective is to have participants gain hands-on experience with one of the most important, yet misunderstood, aspects of climate change research. Participants in the course are supplied with a USB drive that includes installers for the software and sample data. The EdGCM software includes a version of NASA's global climate model fitted with a graphical user interface and pre-loaded with several climate change simulations. Step-by-step assignments and video tutorials help walk people through these challenging exercises and the course incorporates a special assignment discussion forum to help with technical problems and questions about the NASA GCM. There are several takeaways from our first year and a half of offering this course, which has become one of the most popular out of the twelve courses offered by the Museum. Participants report a high level of satisfaction in using EdGCM. Some report frustration at the initial steps, but overwhelmingly claim that the assignments are worth the effort. Many of the difficulties that

The Global Tsunami Model (GTM)

Science.gov (United States)

Lorito, S.; Basili, R.; Harbitz, C. B.; Løvholt, F.; Polet, J.; Thio, H. K.

2017-12-01

The tsunamis occurred worldwide in the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but often disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by the United Nations International Strategy for Disaster Reduction (UNISDR) and the World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR). We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models, the use of aleatory variability and epistemic uncertainty, and preliminary results for a probabilistic global hazard assessment, which is an update of the model included in UNISDR GAR15.

Nonlinear models for fitting growth curves of Nellore cows reared in the Amazon Biome

Directory of Open Access Journals (Sweden)

Kedma Nayra da Silva Marinho

2013-09-01

Full Text Available Growth curves of Nellore cows were estimated by comparing six nonlinear models: Brody, Logistic, two alternatives by Gompertz, Richards and Von Bertalanffy. The models were fitted to weight-age data, from birth to 750 days of age of 29,221 cows, born between 1976 and 2006 in the Brazilian states of Acre, Amapá, Amazonas, Pará, Rondônia, Roraima and Tocantins. The models were fitted by the Gauss-Newton method. The goodness of fit of the models was evaluated by using mean square error, adjusted coefficient of determination, prediction error and mean absolute error. Biological interpretation of parameters was accomplished by plotting estimated weights versus the observed weight means, instantaneous growth rate, absolute maturity rate, relative instantaneous growth rate, inflection point and magnitude of the parameters A (asymptotic weight and K (maturing rate. The Brody and Von Bertalanffy models fitted the weight-age data but the other models did not. The average weight (A and growth rate (K were: 384.6±1.63 kg and 0.0022±0.00002 (Brody and 313.40±0.70 kg and 0.0045±0.00002 (Von Bertalanffy. The Brody model provides better goodness of fit than the Von Bertalanffy model.

Analysis of Long-Term Global Solar Radiation, Sunshine Duration and Air Temperature Data of Ankara and Modeling with Curve Fitting Methods

Directory of Open Access Journals (Sweden)

Mehmet YEŞİLBUDAK

2018-03-01

Full Text Available The information about solar parameters is important in the installation of photovoltaic energy systems that are reliable, environmentally friendly and sustainable. In this study, initially, long-term global solar radiation, sunshine duration and air temperature data of Ankara are analyzed on the annual, monthly and daily basis, elaborately. Afterwards, three different empirical methods that are polynomial, Gaussian and Fourier are used for the purpose of modeling long-term monthly total global solar radiation, monthly total sunshine duration and monthly mean air temperature data. The coefficient of determination and the root mean square error are computed as statistical test metrics in order to compare data modeling performance of the mentioned empirical methods. The empirical methods that provide the best results enable to model the solar characteristics of Ankara more accurately and the achieved outcomes constitute the significant resource for other locations with similar climatic conditions.

Three dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling

International Nuclear Information System (INIS)

Liang, Zhong Wei; Wang, Yi Jun; Ye, Bang Yan; Brauwer, Richard Kars

2012-01-01

In inspecting the detailed performance results of surface precision modeling in different external parameter conditions, the integrated chip surfaces should be evaluated and assessed during topographic spatial modeling processes. The application of surface fitting algorithms exerts a considerable influence on topographic mathematical features. The influence mechanisms caused by different surface fitting algorithms on the integrated chip surface facilitate the quantitative analysis of different external parameter conditions. By extracting the coordinate information from the selected physical control points and using a set of precise spatial coordinate measuring apparatus, several typical surface fitting algorithms are used for constructing micro topographic models with the obtained point cloud. In computing for the newly proposed mathematical features on surface models, we construct the fuzzy evaluating data sequence and present a new three dimensional fuzzy quantitative evaluating method. Through this method, the value variation tendencies of topographic features can be clearly quantified. The fuzzy influence discipline among different surface fitting algorithms, topography spatial features, and the external science parameter conditions can be analyzed quantitatively and in detail. In addition, quantitative analysis can provide final conclusions on the inherent influence mechanism and internal mathematical relation in the performance results of different surface fitting algorithms, topographic spatial features, and their scientific parameter conditions in the case of surface micro modeling. The performance inspection of surface precision modeling will be facilitated and optimized as a new research idea for micro-surface reconstruction that will be monitored in a modeling process

Three dimensional fuzzy influence analysis of fitting algorithms on integrated chip topographic modeling

Energy Technology Data Exchange (ETDEWEB)

Liang, Zhong Wei; Wang, Yi Jun [Guangzhou Univ., Guangzhou (China); Ye, Bang Yan [South China Univ. of Technology, Guangzhou (China); Brauwer, Richard Kars [Indian Institute of Technology, Kanpur (India)

2012-10-15

In inspecting the detailed performance results of surface precision modeling in different external parameter conditions, the integrated chip surfaces should be evaluated and assessed during topographic spatial modeling processes. The application of surface fitting algorithms exerts a considerable influence on topographic mathematical features. The influence mechanisms caused by different surface fitting algorithms on the integrated chip surface facilitate the quantitative analysis of different external parameter conditions. By extracting the coordinate information from the selected physical control points and using a set of precise spatial coordinate measuring apparatus, several typical surface fitting algorithms are used for constructing micro topographic models with the obtained point cloud. In computing for the newly proposed mathematical features on surface models, we construct the fuzzy evaluating data sequence and present a new three dimensional fuzzy quantitative evaluating method. Through this method, the value variation tendencies of topographic features can be clearly quantified. The fuzzy influence discipline among different surface fitting algorithms, topography spatial features, and the external science parameter conditions can be analyzed quantitatively and in detail. In addition, quantitative analysis can provide final conclusions on the inherent influence mechanism and internal mathematical relation in the performance results of different surface fitting algorithms, topographic spatial features, and their scientific parameter conditions in the case of surface micro modeling. The performance inspection of surface precision modeling will be facilitated and optimized as a new research idea for micro-surface reconstruction that will be monitored in a modeling process.

Efficient Constrained Local Model Fitting for Non-Rigid Face Alignment.

Science.gov (United States)

Lucey, Simon; Wang, Yang; Cox, Mark; Sridharan, Sridha; Cohn, Jeffery F

2009-11-01

Active appearance models (AAMs) have demonstrated great utility when being employed for non-rigid face alignment/tracking. The "simultaneous" algorithm for fitting an AAM achieves good non-rigid face registration performance, but has poor real time performance (2-3 fps). The "project-out" algorithm for fitting an AAM achieves faster than real time performance (> 200 fps) but suffers from poor generic alignment performance. In this paper we introduce an extension to a discriminative method for non-rigid face registration/tracking referred to as a constrained local model (CLM). Our proposed method is able to achieve superior performance to the "simultaneous" AAM algorithm along with real time fitting speeds (35 fps). We improve upon the canonical CLM formulation, to gain this performance, in a number of ways by employing: (i) linear SVMs as patch-experts, (ii) a simplified optimization criteria, and (iii) a composite rather than additive warp update step. Most notably, our simplified optimization criteria for fitting the CLM divides the problem of finding a single complex registration/warp displacement into that of finding N simple warp displacements. From these N simple warp displacements, a single complex warp displacement is estimated using a weighted least-squares constraint. Another major advantage of this simplified optimization lends from its ability to be parallelized, a step which we also theoretically explore in this paper. We refer to our approach for fitting the CLM as the "exhaustive local search" (ELS) algorithm. Experiments were conducted on the CMU Multi-PIE database.

Global model structures for ∗-modules

DEFF Research Database (Denmark)

Böhme, Benjamin

2018-01-01

We extend Schwede's work on the unstable global homotopy theory of orthogonal spaces and L-spaces to the category of ∗-modules (i.e., unstable S-modules). We prove a theorem which transports model structures and their properties from L-spaces to ∗-modules and show that the resulting global model...... structure for ∗-modules is monoidally Quillen equivalent to that of orthogonal spaces. As a consequence, there are induced Quillen equivalences between the associated model categories of monoids, which identify equivalent models for the global homotopy theory of A∞-spaces....

Multi-binding site model-based curve-fitting program for the computation of RIA data

International Nuclear Information System (INIS)

Malan, P.G.; Ekins, R.P.; Cox, M.G.; Long, E.M.R.

1977-01-01

In this paper, a comparison will be made of model-based and empirical curve-fitting procedures. The implementation of a multiple binding-site curve-fitting model which will successfully fit a wide range of assay data, and which can be run on a mini-computer is described. The latter sophisticated model also provides estimates of binding site concentrations and the values of the respective equilibrium constants present: the latter have been used for refining assay conditions using computer optimisation techniques. (orig./AJ) [de

On the physical interpretation of torsion-rotation parameters in methanol and acetaldehyde: Comparison of global fit and ab initio results

International Nuclear Information System (INIS)

Xu, L.; Lees, R.M.; Hougen, J.T.

1999-01-01

Equilibrium structural constants and certain torsion endash rotation interaction parameters have been determined for methanol and acetaldehyde from ab initio calculations using GAUSSIAN 94. The substantial molecular flexing which occurs in going from the bottom to the top of the torsional potential barrier can be quantitatively related to coefficients of torsion endash rotation terms having a (1-cos ampersand hthinsp;3γ) dependence on torsional angle γ. The barrier height, six equilibrium structural constants characterizing the bottom of the potential well, and six torsion endash rotation constants are all compared to experimental parameters obtained from global fits to large microwave and far-infrared data sets for methanol and acetaldehyde. The rather encouraging agreement between the Gaussian and global fit results for methanol seems both to validate the accuracy of ab initio calculations of these parameters, and to demonstrate that the physical origin of these torsion endash rotation interaction terms in methanol lies primarily in structural relaxation with torsion. The less satisfactory agreement between theory and experiment for acetaldehyde requires further study. copyright 1999 American Institute of Physics

On coupling global biome models with climate models

International Nuclear Information System (INIS)

Claussen, M.

1994-01-01

The BIOME model of Prentice et al. (1992), which predicts global vegetation patterns in equilibrium with climate, is coupled with the ECHAM climate model of the Max-Planck-Institut fuer Meteorologie, Hamburg. It is found that incorporation of the BIOME model into ECHAM, regardless at which frequency, does not enhance the simulated climate variability, expressed in terms of differences between global vegetation patterns. Strongest changes are seen only between the initial biome distribution and the biome distribution computed after the first simulation period, provided that the climate-biome model is started from a biome distribution that resembles the present-day distribution. After the first simulation period, there is no significant shrinking, expanding, or shifting of biomes. Likewise, no trend is seen in global averages of land-surface parameters and climate variables. (orig.)

On coupling global biome models with climate models

OpenAIRE

Claussen, M.

1994-01-01

The BIOME model of Prentice et al. (1992; J. Biogeogr. 19: 117-134), which predicts global vegetation patterns in equilibrium with climate, was coupled with the ECHAM climate model of the Max-Planck-Institut fiir Meteorologie, Hamburg, Germany. It was found that incorporation of the BIOME model into ECHAM, regardless at which frequency, does not enhance the simulated climate variability, expressed in terms of differences between global vegetation patterns. Strongest changes are seen only betw...

Fitting Latent Cluster Models for Networks with latentnet

Directory of Open Access Journals (Sweden)

Pavel N. Krivitsky

2007-12-01

Full Text Available latentnet is a package to fit and evaluate statistical latent position and cluster models for networks. Hoff, Raftery, and Handcock (2002 suggested an approach to modeling networks based on positing the existence of an latent space of characteristics of the actors. Relationships form as a function of distances between these characteristics as well as functions of observed dyadic level covariates. In latentnet social distances are represented in a Euclidean space. It also includes a variant of the extension of the latent position model to allow for clustering of the positions developed in Handcock, Raftery, and Tantrum (2007.The package implements Bayesian inference for the models based on an Markov chain Monte Carlo algorithm. It can also compute maximum likelihood estimates for the latent position model and a two-stage maximum likelihood method for the latent position cluster model. For latent position cluster models, the package provides a Bayesian way of assessing how many groups there are, and thus whether or not there is any clustering (since if the preferred number of groups is 1, there is little evidence for clustering. It also estimates which cluster each actor belongs to. These estimates are probabilistic, and provide the probability of each actor belonging to each cluster. It computes four types of point estimates for the coefficients and positions: maximum likelihood estimate, posterior mean, posterior mode and the estimator which minimizes Kullback-Leibler divergence from the posterior. You can assess the goodness-of-fit of the model via posterior predictive checks. It has a function to simulate networks from a latent position or latent position cluster model.

Adaptive evolutionary walks require neutral intermediates in RNA fitness landscapes.

Science.gov (United States)

Rendel, Mark D

2011-01-01

In RNA fitness landscapes with interconnected networks of neutral mutations, neutral precursor mutations can play an important role in facilitating the accessibility of epistatic adaptive mutant combinations. I use an exhaustively surveyed fitness landscape model based on short sequence RNA genotypes (and their secondary structure phenotypes) to calculate the minimum rate at which mutants initially appearing as neutral are incorporated into an adaptive evolutionary walk. I show first, that incorporating neutral mutations significantly increases the number of point mutations in a given evolutionary walk when compared to estimates from previous adaptive walk models. Second, that incorporating neutral mutants into such a walk significantly increases the final fitness encountered on that walk - indeed evolutionary walks including neutral steps often reach the global optimum in this model. Third, and perhaps most importantly, evolutionary paths of this kind are often extremely winding in their nature and have the potential to undergo multiple mutations at a given sequence position within a single walk; the potential of these winding paths to mislead phylogenetic reconstruction is briefly considered. Copyright © 2010 Elsevier Inc. All rights reserved.

Twitter classification model: the ABC of two million fitness tweets.

Science.gov (United States)

Vickey, Theodore A; Ginis, Kathleen Martin; Dabrowski, Maciej

2013-09-01

The purpose of this project was to design and test data collection and management tools that can be used to study the use of mobile fitness applications and social networking within the context of physical activity. This project was conducted over a 6-month period and involved collecting publically shared Twitter data from five mobile fitness apps (Nike+, RunKeeper, MyFitnessPal, Endomondo, and dailymile). During that time, over 2.8 million tweets were collected, processed, and categorized using an online tweet collection application and a customized JavaScript. Using the grounded theory, a classification model was developed to categorize and understand the types of information being shared by application users. Our data show that by tracking mobile fitness app hashtags, a wealth of information can be gathered to include but not limited to daily use patterns, exercise frequency, location-based workouts, and overall workout sentiment.

Recent results in the development of a global medium-energy nucleon-nucleus optical-model potential

International Nuclear Information System (INIS)

Madland, D.G.

1988-02-01

Initial results are presented for the determination of a global medium-energy nucleon-nucleus phenomenological optical-model potential using a relativistic Schroedinger representation. The starting point for this work is the global phenomenological optical-model potential of Schwandt /ital et al./, which is based on measured elastic scattering cross sections and analyzing power for polarized protons ranging from 80 to 180 MeV. This potential is optimally modified to reproduce experimental proton reaction cross sections as a function of energy, while allowing only minimal deterioration in the fits to the elastic cross sections and analyzing powers. Further modifications in the absorptive potential were found necessary to extrapolate the modified potential to higher energies. The final potential is converted to a neutron-nucleus potential by use of standard Lane model assumptions and by accounting approximately for the Coulomb correction. Comparisons of measured and calculated proton reaction and neutron total cross sections are presented for 27 Al, 56 Fe, and 208 Pb. Medium-energy optical-model potentials for complex projectiles are briefly discussed in an appendix. 7 refs., 20 figs

Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program

Science.gov (United States)

Moore, Berrien, III; Sahagian, Dork

1997-01-01

The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.

Confronting Theoretical Predictions With Experimental Data; Fitting Strategy For Multi-Dimensional Distributions

Directory of Open Access Journals (Sweden)

Tomasz Przedziński

2015-01-01

Full Text Available After developing a Resonance Chiral Lagrangian (RχL model to describe hadronic τ lepton decays [18], the model was confronted with experimental data. This was accomplished using a fitting framework which was developed to take into account the complexity of the model and to ensure the numerical stability for the algorithms used in the fitting. Since the model used in the fit contained 15 parameters and there were only three 1-dimensional distributions available, we could expect multiple local minima or even whole regions of equal potential to appear. Our methods had to thoroughly explore the whole parameter space and ensure, as well as possible, that the result is a global minimum. This paper is focused on the technical aspects of the fitting strategy used. The first approach was based on re-weighting algorithm published in [17] and produced results in around two weeks. Later approach, with improved theoretical model and simple parallelization algorithm based on Inter-Process Communication (IPC methods of UNIX system, reduced computation time down to 2-3 days. Additional approximations were introduced to the model decreasing time to obtain the preliminary results down to 8 hours. This allowed to better validate the results leading to a more robust analysis published in [12].

Reconciling uncertainties in integrated science and policy models: Applications to global climate change

Energy Technology Data Exchange (ETDEWEB)

Kandlikar, Milind [Carnegie Mellon Univ., Pittsburgh, PA (United States)

1994-12-01

In this thesis tools of data reconciliation are used to integrate available information into scientific and policy models of greenhouse gases. The role of uncertainties in scientific and policy models of global climate change is examined, and implications for global change policy are drawn. Methane is the second most important greenhouse gas. Global sources and sinks of methane have significant uncertainties. A chance constrained methodology was developed and used to perform inversions on the global methane cycle. Budgets of methane that are consistent with source fluxes, isotopic and ice core measurements were determined. While it is not possible to come up with a single budget for CH{sub 4}, performing the calculation with a number of sets of assumed priors suggests a convergence in the allowed range for sources. In some cases -- wetlands (70-130 Tg/yr), rice paddies (60-125 Tg/yr) a significant reduction in the uncertainty of the source estimate is achieved. Our results compare favorably with the most recent measurements of flux estimates. For comparison, a similar analysis using bayes monte carlo simulation was performed. The question of the missing sink for carbon remains unresolved. Two analyses that attempt to quantify the missing sink were performed. First, a steady state analysis of the carbon cycle was used to determine the pre-industrial inter-hemispheric carbon concentration gradient. Second, a full blown dynamic inversion of the carbon cycle was performed. An advection diffusion ocean model with surface chemistry, coupled to box models of the atmosphere and the biosphere was inverted to fit available measurements of {sup 12}C and {sup 14}C carbon isotopes using Differential-Algebraic Optimization. The model effectively suggests that the {open_quotes}missing{close_quotes} sink for carbon is hiding in the biosphere. Scenario dependent trace gas indices were calculated for CH{sub 4}, N{sub 2}O, HCFC-22.

New global ICT-based business models

DEFF Research Database (Denmark)

The New Global Business model (NEWGIBM) book describes the background, theory references, case studies, results and learning imparted by the NEWGIBM project, which is supported by ICT, to a research group during the period from 2005-2011. The book is a result of the efforts and the collaborative ...... The NEWGIBM Cases Show? The Strategy Concept in Light of the Increased Importance of Innovative Business Models Successful Implementation of Global BM Innovation Globalisation Of ICT Based Business Models: Today And In 2020......The New Global Business model (NEWGIBM) book describes the background, theory references, case studies, results and learning imparted by the NEWGIBM project, which is supported by ICT, to a research group during the period from 2005-2011. The book is a result of the efforts and the collaborative....... The NEWGIBM book serves as a part of the final evaluation and documentation of the NEWGIBM project and is supported by results from the following projects: M-commerce, Global Innovation, Global Ebusiness & M-commerce, The Blue Ocean project, International Center for Innovation and Women in Business, NEFFICS...

Modeling Global Biogenic Emission of Isoprene: Exploration of Model Drivers

Science.gov (United States)

Alexander, Susan E.; Potter, Christopher S.; Coughlan, Joseph C.; Klooster, Steven A.; Lerdau, Manuel T.; Chatfield, Robert B.; Peterson, David L. (Technical Monitor)

1996-01-01

Vegetation provides the major source of isoprene emission to the atmosphere. We present a modeling approach to estimate global biogenic isoprene emission. The isoprene flux model is linked to a process-based computer simulation model of biogenic trace-gas fluxes that operates on scales that link regional and global data sets and ecosystem nutrient transformations Isoprene emission estimates are determined from estimates of ecosystem specific biomass, emission factors, and algorithms based on light and temperature. Our approach differs from an existing modeling framework by including the process-based global model for terrestrial ecosystem production, satellite derived ecosystem classification, and isoprene emission measurements from a tropical deciduous forest. We explore the sensitivity of model estimates to input parameters. The resulting emission products from the global 1 degree x 1 degree coverage provided by the satellite datasets and the process model allow flux estimations across large spatial scales and enable direct linkage to atmospheric models of trace-gas transport and transformation.

The development and application of the AstroFit program for complementary dark matter studies

International Nuclear Information System (INIS)

Nguyen, Ngoc-Lan Nelly

2013-02-01

This doctoral thesis describes the development and application of the AstroFit program. Many studies have shown the existence of dark matter (DM), a mass component that constitutes over eighty percent of the entire matter in the Universe. From historical astrophysical evidence to latest reconstructions with sophisticated methods, the gravitational effect of DM can be shown, but its nature remains unknown. Many theoretical explanations aim at describing DM, for example as weakly interacting massive particles (WIMPs), within particular frameworks. The majority of these frameworks extend the existing standard model of particle physics (SM), so that new particles are added to the known set of elementary particles. One of these frameworks is the constrained supersymmetric standard model (CMSSM) that naturally introduces a DM candidate in form of the lightest supersymmetric particle(LSP). Searches for DM particles are undertaken in three different ways. First, directly with fixed-target experiments that measure WIMPs coming towards the Earth with nuclei of the target material. Second, indirectly by reconstructing DM signatures in particle spectra of known particles observed with ground-based telescopes, spaceborne satellites or balloon-borne experiments. And third, indirectly via direct production of DM at particle colliders such as the Large Hadron Collider (LHC) and energy reconstructions where missing transverse energy is presumably carried away by the DM particles. Global fit programs used in particle physics, such as Fittino, are designed to fit parameters of theories beyond the SM simultaneously that are in accordance with the experimental and observed data in order to probe models and constrain the parameter space. To explore complementarity in DM research, the AstroFit interface program has been developed to combine all available information from direct and indirect searches for DM as well as collider searches for new physics in such global fits. To demonstrate

The development and application of the AstroFit program for complementary dark matter studies

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Ngoc-Lan Nelly

2013-02-15

This doctoral thesis describes the development and application of the AstroFit program. Many studies have shown the existence of dark matter (DM), a mass component that constitutes over eighty percent of the entire matter in the Universe. From historical astrophysical evidence to latest reconstructions with sophisticated methods, the gravitational effect of DM can be shown, but its nature remains unknown. Many theoretical explanations aim at describing DM, for example as weakly interacting massive particles (WIMPs), within particular frameworks. The majority of these frameworks extend the existing standard model of particle physics (SM), so that new particles are added to the known set of elementary particles. One of these frameworks is the constrained supersymmetric standard model (CMSSM) that naturally introduces a DM candidate in form of the lightest supersymmetric particle(LSP). Searches for DM particles are undertaken in three different ways. First, directly with fixed-target experiments that measure WIMPs coming towards the Earth with nuclei of the target material. Second, indirectly by reconstructing DM signatures in particle spectra of known particles observed with ground-based telescopes, spaceborne satellites or balloon-borne experiments. And third, indirectly via direct production of DM at particle colliders such as the Large Hadron Collider (LHC) and energy reconstructions where missing transverse energy is presumably carried away by the DM particles. Global fit programs used in particle physics, such as Fittino, are designed to fit parameters of theories beyond the SM simultaneously that are in accordance with the experimental and observed data in order to probe models and constrain the parameter space. To explore complementarity in DM research, the AstroFit interface program has been developed to combine all available information from direct and indirect searches for DM as well as collider searches for new physics in such global fits. To demonstrate

The stress peak at the borehole of point-fitted IGU with undercut anchors

Directory of Open Access Journals (Sweden)

Mike Tibolt

2015-05-01

Full Text Available The highest transparency in glass facades is obtained with point fitted glass units. Point fitted insulating glass units minimize thermal bridging and lead to glass facades with better energy efficiency. Though, insufficient knowledge is present to offer a design method for point fittings in insulating glass. Therefore research has been carried out to extend the existing SLG-design-method (Linear superposition of local and global stress components of Beyer for point fitted single and laminated glass to insulation glass units. This paper presents the first results of this research campaign. Load bearing tests on point fittings in single glazing have been conducted. A finite element model of the point fitting is calibrated by strain comparison. A test campaign for the deviation of a material law for silicone, used as secondary sealant in the edge seal system, is presented. The verified FE-model is implemented in a selected insulation glass unit, and the influence of the edge distance of the point fitting, as well as the edge bond stiffness and geometry on the stress peak at the borehole is investigated. In addition, the size of the so called ‘local area’ is adjusted for insulation glass units.

The neural network approach to parton fitting

International Nuclear Information System (INIS)

Rojo, Joan; Latorre, Jose I.; Del Debbio, Luigi; Forte, Stefano; Piccione, Andrea

2005-01-01

We introduce the neural network approach to global fits of parton distribution functions. First we review previous work on unbiased parametrizations of deep-inelastic structure functions with faithful estimation of their uncertainties, and then we summarize the current status of neural network parton distribution fits

Rapid world modeling: Fitting range data to geometric primitives

International Nuclear Information System (INIS)

Feddema, J.; Little, C.

1996-01-01

For the past seven years, Sandia National Laboratories has been active in the development of robotic systems to help remediate DOE's waste sites and decommissioned facilities. Some of these facilities have high levels of radioactivity which prevent manual clean-up. Tele-operated and autonomous robotic systems have been envisioned as the only suitable means of removing the radioactive elements. World modeling is defined as the process of creating a numerical geometric model of a real world environment or workspace. This model is often used in robotics to plan robot motions which perform a task while avoiding obstacles. In many applications where the world model does not exist ahead of time, structured lighting, laser range finders, and even acoustical sensors have been used to create three dimensional maps of the environment. These maps consist of thousands of range points which are difficult to handle and interpret. This paper presents a least squares technique for fitting range data to planar and quadric surfaces, including cylinders and ellipsoids. Once fit to these primitive surfaces, the amount of data associated with a surface is greatly reduced up to three orders of magnitude, thus allowing for more rapid handling and analysis of world data

Kernel-density estimation and approximate Bayesian computation for flexible epidemiological model fitting in Python.

Science.gov (United States)

Irvine, Michael A; Hollingsworth, T Déirdre

2018-05-26

Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a long time to run, and it can be difficult to fully capture the heterogeneity in the data. We develop an adaptive approximate Bayesian computation scheme to fit a variety of epidemiologically relevant data with minimal hyper-parameter tuning by using an adaptive tolerance scheme. We implement a novel kernel density estimation scheme to capture both dispersed and multi-dimensional data, and directly compare this technique to standard Bayesian approaches. We then apply the procedure to a complex individual-based simulation of lymphatic filariasis, a human parasitic disease. The procedure and examples are released alongside this article as an open access library, with examples to aid researchers to rapidly fit models to data. This demonstrates that an adaptive ABC scheme with a general summary and distance metric is capable of performing model fitting for a variety of epidemiological data. It also does not require significant theoretical background to use and can be made accessible to the diverse epidemiological research community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Model-independent partial wave analysis using a massively-parallel fitting framework

Science.gov (United States)

Sun, L.; Aoude, R.; dos Reis, A. C.; Sokoloff, M.

2017-10-01

The functionality of GooFit, a GPU-friendly framework for doing maximum-likelihood fits, has been extended to extract model-independent {\\mathscr{S}}-wave amplitudes in three-body decays such as D + → h + h + h -. A full amplitude analysis is done where the magnitudes and phases of the {\\mathscr{S}}-wave amplitudes are anchored at a finite number of m 2(h + h -) control points, and a cubic spline is used to interpolate between these points. The amplitudes for {\\mathscr{P}}-wave and {\\mathscr{D}}-wave intermediate states are modeled as spin-dependent Breit-Wigner resonances. GooFit uses the Thrust library, with a CUDA backend for NVIDIA GPUs and an OpenMP backend for threads with conventional CPUs. Performance on a variety of platforms is compared. Executing on systems with GPUs is typically a few hundred times faster than executing the same algorithm on a single CPU.

Cuckoo search with Lévy flights for weighted Bayesian energy functional optimization in global-support curve data fitting.

Science.gov (United States)

Gálvez, Akemi; Iglesias, Andrés; Cabellos, Luis

2014-01-01

The problem of data fitting is very important in many theoretical and applied fields. In this paper, we consider the problem of optimizing a weighted Bayesian energy functional for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS) that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way.

Global scale groundwater flow model

Science.gov (United States)

Sutanudjaja, Edwin; de Graaf, Inge; van Beek, Ludovicus; Bierkens, Marc

2013-04-01

As the world's largest accessible source of freshwater, groundwater plays vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and supplies water for agricultural and industrial activities. During times of drought, groundwater sustains water flows in streams, rivers, lakes and wetlands, and thus supports ecosystem habitat and biodiversity, while its large natural storage provides a buffer against water shortages. Yet, the current generation of global scale hydrological models does not include a groundwater flow component that is a crucial part of the hydrological cycle and allows the simulation of groundwater head dynamics. In this study we present a steady-state MODFLOW (McDonald and Harbaugh, 1988) groundwater model on the global scale at 5 arc-minutes resolution. Aquifer schematization and properties of this groundwater model were developed from available global lithological model (e.g. Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moorsdorff, in press). We force the groundwtaer model with the output from the large-scale hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the long term net groundwater recharge and average surface water levels derived from routed channel discharge. We validated calculated groundwater heads and depths with available head observations, from different regions, including the North and South America and Western Europe. Our results show that it is feasible to build a relatively simple global scale groundwater model using existing information, and estimate water table depths within acceptable accuracy in many parts of the world.

Compounding local invariant features and global deformable geometry for medical image registration.

Directory of Open Access Journals (Sweden)

Jianhua Zhang

Full Text Available Using deformable models to register medical images can result in problems of initialization of deformable models and robustness and accuracy of matching of inter-subject anatomical variability. To tackle these problems, a novel model is proposed in this paper by compounding local invariant features and global deformable geometry. This model has four steps. First, a set of highly-repeatable and highly-robust local invariant features, called Key Features Model (KFM, are extracted by an effective matching strategy. Second, local features can be matched more accurately through the KFM for the purpose of initializing a global deformable model. Third, the positional relationship between the KFM and the global deformable model can be used to precisely pinpoint all landmarks after initialization. And fourth, the final pose of the global deformable model is determined by an iterative process with a lower time cost. Through the practical experiments, the paper finds three important conclusions. First, it proves that the KFM can detect the matching feature points well. Second, the precision of landmark locations adjusted by the modeled relationship between KFM and global deformable model is greatly improved. Third, regarding the fitting accuracy and efficiency, by observation from the practical experiments, it is found that the proposed method can improve 6~8% of the fitting accuracy and reduce around 50% of the computational time compared with state-of-the-art methods.

The issue of statistical power for overall model fit in evaluating structural equation models

Directory of Open Access Journals (Sweden)

Richard HERMIDA

2015-06-01

Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.

Fitting and comparing competing models of the species abundance distribution: assessment and prospect

Directory of Open Access Journals (Sweden)

Thomas J Matthews

2014-06-01

Full Text Available A species abundance distribution (SAD characterises patterns in the commonness and rarity of all species within an ecological community. As such, the SAD provides the theoretical foundation for a number of other biogeographical and macroecological patterns, such as the species–area relationship, as well as being an interesting pattern in its own right. While there has been resurgence in the study of SADs in the last decade, less focus has been placed on methodology in SAD research, and few attempts have been made to synthesise the vast array of methods which have been employed in SAD model evaluation. As such, our review has two aims. First, we provide a general overview of SADs, including descriptions of the commonly used distributions, plotting methods and issues with evaluating SAD models. Second, we review a number of recent advances in SAD model fitting and comparison. We conclude by providing a list of recommendations for fitting and evaluating SAD models. We argue that it is time for SAD studies to move away from many of the traditional methods available for fitting and evaluating models, such as sole reliance on the visual examination of plots, and embrace statistically rigorous techniques. In particular, we recommend the use of both goodness-of-fit tests and model-comparison analyses because each provides unique information which one can use to draw inferences.

Fitting direct covariance structures by the MSTRUCT modeling language of the CALIS procedure.

Science.gov (United States)

Yung, Yiu-Fai; Browne, Michael W; Zhang, Wei

2015-02-01

This paper demonstrates the usefulness and flexibility of the general structural equation modelling (SEM) approach to fitting direct covariance patterns or structures (as opposed to fitting implied covariance structures from functional relationships among variables). In particular, the MSTRUCT modelling language (or syntax) of the CALIS procedure (SAS/STAT version 9.22 or later: SAS Institute, 2010) is used to illustrate the SEM approach. The MSTRUCT modelling language supports a direct covariance pattern specification of each covariance element. It also supports the input of additional independent and dependent parameters. Model tests, fit statistics, estimates, and their standard errors are then produced under the general SEM framework. By using numerical and computational examples, the following tests of basic covariance patterns are illustrated: sphericity, compound symmetry, and multiple-group covariance patterns. Specification and testing of two complex correlation structures, the circumplex pattern and the composite direct product models with or without composite errors and scales, are also illustrated by the MSTRUCT syntax. It is concluded that the SEM approach offers a general and flexible modelling of direct covariance and correlation patterns. In conjunction with the use of SAS macros, the MSTRUCT syntax provides an easy-to-use interface for specifying and fitting complex covariance and correlation structures, even when the number of variables or parameters becomes large. © 2014 The British Psychological Society.

A goodness-of-fit test for occupancy models with correlated within-season revisits

Science.gov (United States)

Wright, Wilson; Irvine, Kathryn M.; Rodhouse, Thomas J.

2016-01-01

Occupancy modeling is important for exploring species distribution patterns and for conservation monitoring. Within this framework, explicit attention is given to species detection probabilities estimated from replicate surveys to sample units. A central assumption is that replicate surveys are independent Bernoulli trials, but this assumption becomes untenable when ecologists serially deploy remote cameras and acoustic recording devices over days and weeks to survey rare and elusive animals. Proposed solutions involve modifying the detection-level component of the model (e.g., first-order Markov covariate). Evaluating whether a model sufficiently accounts for correlation is imperative, but clear guidance for practitioners is lacking. Currently, an omnibus goodnessof- fit test using a chi-square discrepancy measure on unique detection histories is available for occupancy models (MacKenzie and Bailey, Journal of Agricultural, Biological, and Environmental Statistics, 9, 2004, 300; hereafter, MacKenzie– Bailey test). We propose a join count summary measure adapted from spatial statistics to directly assess correlation after fitting a model. We motivate our work with a dataset of multinight bat call recordings from a pilot study for the North American Bat Monitoring Program. We found in simulations that our join count test was more reliable than the MacKenzie–Bailey test for detecting inadequacy of a model that assumed independence, particularly when serial correlation was low to moderate. A model that included a Markov-structured detection-level covariate produced unbiased occupancy estimates except in the presence of strong serial correlation and a revisit design consisting only of temporal replicates. When applied to two common bat species, our approach illustrates that sophisticated models do not guarantee adequate fit to real data, underscoring the importance of model assessment. Our join count test provides a widely applicable goodness-of-fit test and

Model fit versus biological relevance: Evaluating photosynthesis-temperature models for three tropical seagrass species

OpenAIRE

Matthew P. Adams; Catherine J. Collier; Sven Uthicke; Yan X. Ow; Lucas Langlois; Katherine R. O’Brien

2017-01-01

When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluat...

Insight into model mechanisms through automatic parameter fitting: a new methodological framework for model development.

Science.gov (United States)

Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P

2014-05-20

Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on

A GLOBAL MODEL OF THE LIGHT CURVES AND EXPANSION VELOCITIES OF TYPE II-PLATEAU SUPERNOVAE

Energy Technology Data Exchange (ETDEWEB)

Pejcha, Ondřej [Department of Astrophysical Sciences, Princeton University, 4 Ivy Lane, Princeton, NJ 08540 (United States); Prieto, Jose L., E-mail: pejcha@astro.princeton.edu [Núcleo de Astronomía de la Facultad de Ingeniería, Universidad Diego Portales, Av. Ejército 441 Santiago (Chile)

2015-02-01

We present a new self-consistent and versatile method that derives photospheric radius and temperature variations of Type II-Plateau supernovae based on their expansion velocities and photometric measurements. We apply the method to a sample of 26 well-observed, nearby supernovae with published light curves and velocities. We simultaneously fit ∼230 velocity and ∼6800 mag measurements distributed over 21 photometric passbands spanning wavelengths from 0.19 to 2.2 μm. The light-curve differences among the Type II-Plateau supernovae are well modeled by assuming different rates of photospheric radius expansion, which we explain as different density profiles of the ejecta, and we argue that steeper density profiles result in flatter plateaus, if everything else remains unchanged. The steep luminosity decline of Type II-Linear supernovae is due to fast evolution of the photospheric temperature, which we verify with a successful fit of SN 1980K. Eliminating the need for theoretical supernova atmosphere models, we obtain self-consistent relative distances, reddenings, and nickel masses fully accounting for all internal model uncertainties and covariances. We use our global fit to estimate the time evolution of any missing band tailored specifically for each supernova, and we construct spectral energy distributions and bolometric light curves. We produce bolometric corrections for all filter combinations in our sample. We compare our model to the theoretical dilution factors and find good agreement for the B and V filters. Our results differ from the theory when the I, J, H, or K bands are included. We investigate the reddening law toward our supernovae and find reasonable agreement with standard R{sub V}∼3.1 reddening law in UBVRI bands. Results for other bands are inconclusive. We make our fitting code publicly available.

Constraints on global oceanic emissions of N2O from observations and models

Science.gov (United States)

Buitenhuis, Erik T.; Suntharalingam, Parvadha; Le Quéré, Corinne

2018-04-01

We estimate the global ocean N2O flux to the atmosphere and its confidence interval using a statistical method based on model perturbation simulations and their fit to a database of ΔpN2O (n = 6136). We evaluate two submodels of N2O production. The first submodel splits N2O production into oxic and hypoxic pathways following previous publications. The second submodel explicitly represents the redox transformations of N that lead to N2O production (nitrification and hypoxic denitrification) and N2O consumption (suboxic denitrification), and is presented here for the first time. We perturb both submodels by modifying the key parameters of the N2O cycling pathways (nitrification rates; NH4+ uptake; N2O yields under oxic, hypoxic and suboxic conditions) and determine a set of optimal model parameters by minimisation of a cost function against four databases of N cycle observations. Our estimate of the global oceanic N2O flux resulting from this cost function minimisation derived from observed and model ΔpN2O concentrations is 2.4 ± 0.8 and 2.5 ± 0.8 Tg N yr-1 for the two N2O submodels. These estimates suggest that the currently available observational data of surface ΔpN2O constrain the global N2O flux to a narrower range relative to the large range of results presented in the latest IPCC report.

Efficient parallel implementation of active appearance model fitting algorithm on GPU.

Science.gov (United States)

Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou

2014-01-01

The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

Global Atmosphere Watch Workshop on Measurement-Model ...

Science.gov (United States)

The World Meteorological Organization’s (WMO) Global Atmosphere Watch (GAW) Programme coordinates high-quality observations of atmospheric composition from global to local scales with the aim to drive high-quality and high-impact science while co-producing a new generation of products and services. In line with this vision, GAW’s Scientific Advisory Group for Total Atmospheric Deposition (SAG-TAD) has a mandate to produce global maps of wet, dry and total atmospheric deposition for important atmospheric chemicals to enable research into biogeochemical cycles and assessments of ecosystem and human health effects. The most suitable scientific approach for this activity is the emerging technique of measurement-model fusion for total atmospheric deposition. This technique requires global-scale measurements of atmospheric trace gases, particles, precipitation composition and precipitation depth, as well as predictions of the same from global/regional chemical transport models. The fusion of measurement and model results requires data assimilation and mapping techniques. The objective of the GAW Workshop on Measurement-Model Fusion for Global Total Atmospheric Deposition (MMF-GTAD), an initiative of the SAG-TAD, was to review the state-of-the-science and explore the feasibility and methodology of producing, on a routine retrospective basis, global maps of atmospheric gas and aerosol concentrations as well as wet, dry and total deposition via measurement-model

ARA and ARI imperfect repair models: Estimation, goodness-of-fit and reliability prediction

International Nuclear Information System (INIS)

Toledo, Maria Luíza Guerra de; Freitas, Marta A.; Colosimo, Enrico A.; Gilardoni, Gustavo L.

2015-01-01

An appropriate maintenance policy is essential to reduce expenses and risks related to equipment failures. A fundamental aspect to be considered when specifying such policies is to be able to predict the reliability of the systems under study, based on a well fitted model. In this paper, the classes of models Arithmetic Reduction of Age and Arithmetic Reduction of Intensity are explored. Likelihood functions for such models are derived, and a graphical method is proposed for model selection. A real data set involving failures in trucks used by a Brazilian mining is analyzed considering models with different memories. Parameters, namely, shape and scale for Power Law Process, and the efficiency of repair were estimated for the best fitted model. Estimation of model parameters allowed us to derive reliability estimators to predict the behavior of the failure process. These results are a valuable information for the mining company and can be used to support decision making regarding preventive maintenance policy. - Highlights: • Likelihood functions for imperfect repair models are derived. • A goodness-of-fit technique is proposed as a tool for model selection. • Failures in trucks owned by a Brazilian mining are modeled. • Estimation allowed deriving reliability predictors to forecast the future failure process of the trucks

Person-fit to the Five Factor Model of personality

Czech Academy of Sciences Publication Activity Database

Allik, J.; Realo, A.; Mõttus, R.; Borkenau, P.; Kuppens, P.; Hřebíčková, Martina

2012-01-01

Roč. 71, č. 1 (2012), s. 35-45 ISSN 1421-0185 R&D Projects: GA ČR GAP407/10/2394 Institutional research plan: CEZ:AV0Z70250504 Keywords : Five Factor Model * cross - cultural comparison * person-fit Subject RIV: AN - Psychology Impact factor: 0.638, year: 2012

Study on fitness functions of genetic algorithm for dynamically correcting nuclide atmospheric diffusion model

International Nuclear Information System (INIS)

Ji Zhilong; Ma Yuanwei; Wang Dezhong

2014-01-01

Background: In radioactive nuclides atmospheric diffusion models, the empirical dispersion coefficients were deduced under certain experiment conditions, whose difference with nuclear accident conditions is a source of deviation. A better estimation of the radioactive nuclide's actual dispersion process could be done by correcting dispersion coefficients with observation data, and Genetic Algorithm (GA) is an appropriate method for this correction procedure. Purpose: This study is to analyze the fitness functions' influence on the correction procedure and the forecast ability of diffusion model. Methods: GA, coupled with Lagrange dispersion model, was used in a numerical simulation to compare 4 fitness functions' impact on the correction result. Results: In the numerical simulation, the fitness function with observation deviation taken into consideration stands out when significant deviation exists in the observed data. After performing the correction procedure on the Kincaid experiment data, a significant boost was observed in the diffusion model's forecast ability. Conclusion: As the result shows, in order to improve dispersion models' forecast ability using GA, observation data should be given different weight in the fitness function corresponding to their error. (authors)

Model Fitting for Predicted Precipitation in Darwin: Some Issues with Model Choice

Science.gov (United States)

Farmer, Jim

2010-01-01

In Volume 23(2) of the "Australian Senior Mathematics Journal," Boncek and Harden present an exercise in fitting a Markov chain model to rainfall data for Darwin Airport (Boncek & Harden, 2009). Days are subdivided into those with precipitation and precipitation-free days. The author abbreviates these labels to wet days and dry days.…

The Structure of Fitness Landscapes in Antibiotic-Resistant Bacteria

Science.gov (United States)

Deris, Barrett; Kim, Minsu; Zhang, Zhongge; Okano, Hiroyuki; Hermsen, Rutger; Gore, Jeff; Hwa, Terence

2014-03-01

To predict the emergence of antibiotic resistance, quantitative relations must be established between the fitness of drug-resistant organisms and the molecular mechanisms conferring resistance. We have investigated E. coli strains expressing resistance to translation-inhibiting antibiotics. We show that resistance expression and drug inhibition are linked in a positive feedback loop arising from an innate, global effect of drug-inhibited growth on gene expression. This feedback leads generically to plateau-shaped fitness landscapes and concomitantly, for strains expressing at least moderate degrees of drug resistance, gives rise to an abrupt drop in growth rates of cultures at threshold drug concentrations. A simple quantitative model of bacterial growth based on this innate feedback accurately predicts experimental observations without ad hoc parameter fitting. We describe how drug-inhibited growth rate and the threshold drug concentration (the minimum inhibitory concentration, or MIC) depend on the few biochemical parameters that characterize the molecular details of growth inhibition and drug resistance (e.g., the drug-target dissociation constant). And finally, we discuss how these parameters can shape fitness landscapes to determine evolutionary dynamics and evolvability.

Marine Geoid Undulation Assessment Over South China Sea Using Global Geopotential Models and Airborne Gravity Data

Science.gov (United States)

Yazid, N. M.; Din, A. H. M.; Omar, K. M.; Som, Z. A. M.; Omar, A. H.; Yahaya, N. A. Z.; Tugi, A.

2016-09-01

Global geopotential models (GGMs) are vital in computing global geoid undulations heights. Based on the ellipsoidal height by Global Navigation Satellite System (GNSS) observations, the accurate orthometric height can be calculated by adding precise and accurate geoid undulations model information. However, GGMs also provide data from the satellite gravity missions such as GRACE, GOCE and CHAMP. Thus, this will assist to enhance the global geoid undulations data. A statistical assessment has been made between geoid undulations derived from 4 GGMs and the airborne gravity data provided by Department of Survey and Mapping Malaysia (DSMM). The goal of this study is the selection of the best possible GGM that best matches statistically with the geoid undulations of airborne gravity data under the Marine Geodetic Infrastructures in Malaysian Waters (MAGIC) Project over marine areas in Sabah. The correlation coefficients and the RMS value for the geoid undulations of GGM and airborne gravity data were computed. The correlation coefficients between EGM 2008 and airborne gravity data is 1 while RMS value is 0.1499.In this study, the RMS value of EGM 2008 is the lowest among the others. Regarding to the statistical analysis, it clearly represents that EGM 2008 is the best fit for marine geoid undulations throughout South China Sea.

On global and regional spectral evaluation of global geopotential models

International Nuclear Information System (INIS)

Ustun, A; Abbak, R A

2010-01-01

Spectral evaluation of global geopotential models (GGMs) is necessary to recognize the behaviour of gravity signal and its error recorded in spherical harmonic coefficients and associated standard deviations. Results put forward in this wise explain the whole contribution of gravity data in different kinds that represent various sections of the gravity spectrum. This method is more informative than accuracy assessment methods, which use external data such as GPS-levelling. Comparative spectral evaluation for more than one model can be performed both in global and local sense using many spectral tools. The number of GGMs has grown with the increasing number of data collected by the dedicated satellite gravity missions, CHAMP, GRACE and GOCE. This fact makes it necessary to measure the differences between models and to monitor the improvements in the gravity field recovery. In this paper, some of the satellite-only and combined models are examined in different scales, globally and regionally, in order to observe the advances in the modelling of GGMs and their strengths at various expansion degrees for geodetic and geophysical applications. The validation of the published errors of model coefficients is a part of this evaluation. All spectral tools explicitly reveal the superiority of the GRACE-based models when compared against the models that comprise the conventional satellite tracking data. The disagreement between models is large in local/regional areas if data sets are different, as seen from the example of the Turkish territory

Global sensitivity analysis of a filtration model for submerged anaerobic membrane bioreactors (AnMBR).

Science.gov (United States)

Robles, A; Ruano, M V; Ribes, J; Seco, A; Ferrer, J

2014-04-01

The results of a global sensitivity analysis of a filtration model for submerged anaerobic MBRs (AnMBRs) are assessed in this paper. This study aimed to (1) identify the less- (or non-) influential factors of the model in order to facilitate model calibration and (2) validate the modelling approach (i.e. to determine the need for each of the proposed factors to be included in the model). The sensitivity analysis was conducted using a revised version of the Morris screening method. The dynamic simulations were conducted using long-term data obtained from an AnMBR plant fitted with industrial-scale hollow-fibre membranes. Of the 14 factors in the model, six were identified as influential, i.e. those calibrated using off-line protocols. A dynamic calibration (based on optimisation algorithms) of these influential factors was conducted. The resulting estimated model factors accurately predicted membrane performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling.

Science.gov (United States)

Klijn, Sven L; Weijenberg, Matty P; Lemmens, Paul; van den Brandt, Piet A; Lima Passos, Valéria

2017-10-01

Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.

X-ray/UV Observing Campaign on the Mrk 279 AGN Outflow: A Global Fitting Analysis of the UV Absorption

Energy Technology Data Exchange (ETDEWEB)

Gabel, J.

2005-03-17

We present an analysis of the intrinsic UV absorption in the Seyfert 1 galaxy Mrk 279 based on simultaneous long observations with the ''Hubble Space Telescope'' (41 ks) and the ''Far Ultraviolet Spectroscopic Explorer'' (91 ks). To extract the line-of-sight covering factors and ionic column densities, we separately fit two groups of absorption lines: the Lyman series and the CNO lithium-like doublets. For the CNO doublets we assume that all three ions share the same covering factors. The fitting method applied here overcomes some limitations of the traditional method using individual doublet pairs; it allows for the treatment of more complex, physically realistic scenarios for the absorption-emission geometry and eliminates systematic errors that we show are introduced by spectral noise. We derive velocity-dependent solutions based on two models of geometrical covering--a single covering factor for all background emission sources, and separate covering factors for the continuum and emission lines. Although both models give good statistical fits to the observed absorption, we favor the model with two covering factors because: (a) the best-fit covering factors for both emission sources are similar for the independent Lyman series and CNO doublet fits; (b) the fits are consistent with full coverage of the continuum source and partial coverage of the emission lines by the absorbers, as expected from the relative sizes of the nuclear emission components; and (c) it provides a natural explanation for variability in the Lya absorption detected in an earlier epoch. We also explore physical and geometrical constraints on the outflow from these results.

Exotic Endurance: Tourism, Fitness and the Marathon des Sables

OpenAIRE

Lisle, Debbie

2016-01-01

This paper critically examines the intersections of global tourism and fitness in the Marathon des Sables, an annual ultramarathon in the Sahara desert in which over a thousand athletes run the equivalent of five marathons in six days. It demonstrates how the globalization of health and fitness resonates with familiar Western productions of exotic cultures for the purposes of tourist consumption. Of particular interest here is how established colonial asymmetries are recast in a neoliberal co...

Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU

Directory of Open Access Journals (Sweden)

Jinwei Wang

2014-01-01

Full Text Available The active appearance model (AAM is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA on the Nvidia’s GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.

Reconceptualising transnational governance: Making global institutions fit for purpose

OpenAIRE

Cleary, Seán

2017-01-01

Tensions between national democratic accountability and transnational challenges undermine trust and collective action. Asymmetry between an integrated global economy, fragmented global community, and defective global polity, causes social turbulence. Facing technological disruption, we need a new order to address inequality; transform education; and build social capital. Diplomatic exchanges will not suffice, bur the Paris Agreement and Agenda 2030 were enabled by bottom-up deliberations. Th...

Local and omnibus goodness-of-fit tests in classical measurement error models

KAUST Repository

Ma, Yanyuan

2010-09-14

We consider functional measurement error models, i.e. models where covariates are measured with error and yet no distributional assumptions are made about the mismeasured variable. We propose and study a score-type local test and an orthogonal series-based, omnibus goodness-of-fit test in this context, where no likelihood function is available or calculated-i.e. all the tests are proposed in the semiparametric model framework. We demonstrate that our tests have optimality properties and computational advantages that are similar to those of the classical score tests in the parametric model framework. The test procedures are applicable to several semiparametric extensions of measurement error models, including when the measurement error distribution is estimated non-parametrically as well as for generalized partially linear models. The performance of the local score-type and omnibus goodness-of-fit tests is demonstrated through simulation studies and analysis of a nutrition data set.

Universal Rate Model Selector: A Method to Quickly Find the Best-Fit Kinetic Rate Model for an Experimental Rate Profile

Science.gov (United States)

2017-08-01

k2 – k1) 3.3 Universal Kinetic Rate Platform Development Kinetic rate models range from pure chemical reactions to mass transfer...14 8. The rate model that best fits the experimental data is a first-order or homogeneous catalytic reaction ...Avrami (7), and intraparticle diffusion (6) rate equations to name a few. A single fitting algorithm (kinetic rate model ) for a reaction does not

Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

Science.gov (United States)

Chaney, Nathaniel W.; Herman, Jonathan D.; Ek, Michael B.; Wood, Eric F.

2016-11-01

With their origins in numerical weather prediction and climate modeling, land surface models aim to accurately partition the surface energy balance. An overlooked challenge in these schemes is the role of model parameter uncertainty, particularly at unmonitored sites. This study provides global parameter estimates for the Noah land surface model using 85 eddy covariance sites in the global FLUXNET network. The at-site parameters are first calibrated using a Latin Hypercube-based ensemble of the most sensitive parameters, determined by the Sobol method, to be the minimum stomatal resistance (rs,min), the Zilitinkevich empirical constant (Czil), and the bare soil evaporation exponent (fxexp). Calibration leads to an increase in the mean Kling-Gupta Efficiency performance metric from 0.54 to 0.71. These calibrated parameter sets are then related to local environmental characteristics using the Extra-Trees machine learning algorithm. The fitted Extra-Trees model is used to map the optimal parameter sets over the globe at a 5 km spatial resolution. The leave-one-out cross validation of the mapped parameters using the Noah land surface model suggests that there is the potential to skillfully relate calibrated model parameter sets to local environmental characteristics. The results demonstrate the potential to use FLUXNET to tune the parameterizations of surface fluxes in land surface models and to provide improved parameter estimates over the globe.

Robust global identifiability theory using potentials--Application to compartmental models.

Science.gov (United States)

Wongvanich, N; Hann, C E; Sirisena, H R

2015-04-01

This paper presents a global practical identifiability theory for analyzing and identifying linear and nonlinear compartmental models. The compartmental system is prolonged onto the potential jet space to formulate a set of input-output equations that are integrals in terms of the measured data, which allows for robust identification of parameters without requiring any simulation of the model differential equations. Two classes of linear and non-linear compartmental models are considered. The theory is first applied to analyze the linear nitrous oxide (N2O) uptake model. The fitting accuracy of the identified models from differential jet space and potential jet space identifiability theories is compared with a realistic noise level of 3% which is derived from sensor noise data in the literature. The potential jet space approach gave a match that was well within the coefficient of variation. The differential jet space formulation was unstable and not suitable for parameter identification. The proposed theory is then applied to a nonlinear immunological model for mastitis in cows. In addition, the model formulation is extended to include an iterative method which allows initial conditions to be accurately identified. With up to 10% noise, the potential jet space theory predicts the normalized population concentration infected with pathogens, to within 9% of the true curve. Copyright © 2015 Elsevier Inc. All rights reserved.

The direct limit on the Higgs Mass and the SM Fit

International Nuclear Information System (INIS)

Chanowitz, Michael S.

2003-01-01

Because of two 3σ anomalies, the Standard Model (SM) fit of the precision electroweak data has a poor confidence level, CL = 0.02. Since both anomalies involve challenging systematic issues, it might appear that the SM could still be valid if the anomalies resulted from underestimated systematic error. Indeed the CL of the global fit could then increase to 0.71, but that fit predicts a small Higgs boson mass, m H = 45 GeV, that is inconsistent at 95% CL with the lower limit, m H > 114 GeV, established by direct searches. The data then favor new physics whether the anomalous measurements are excluded from the fit or not, and the Higgs boson mass cannot be predicted until the new physics is understood. Some measure of statistical fluctuation would be needed to maintain the validity of the SM. New physics is favored, but the SM is not definitively excluded

Constraints on global oceanic emissions of N2O from observations and models

Directory of Open Access Journals (Sweden)

E. T. Buitenhuis

2018-04-01

Full Text Available We estimate the global ocean N2O flux to the atmosphere and its confidence interval using a statistical method based on model perturbation simulations and their fit to a database of ΔpN2O (n =  6136. We evaluate two submodels of N2O production. The first submodel splits N2O production into oxic and hypoxic pathways following previous publications. The second submodel explicitly represents the redox transformations of N that lead to N2O production (nitrification and hypoxic denitrification and N2O consumption (suboxic denitrification, and is presented here for the first time. We perturb both submodels by modifying the key parameters of the N2O cycling pathways (nitrification rates; NH4+ uptake; N2O yields under oxic, hypoxic and suboxic conditions and determine a set of optimal model parameters by minimisation of a cost function against four databases of N cycle observations. Our estimate of the global oceanic N2O flux resulting from this cost function minimisation derived from observed and model ΔpN2O concentrations is 2.4 ± 0.8 and 2.5 ± 0.8 Tg N yr−1 for the two N2O submodels. These estimates suggest that the currently available observational data of surface ΔpN2O constrain the global N2O flux to a narrower range relative to the large range of results presented in the latest IPCC report.

USING GEM - GLOBAL ECONOMIC MODEL IN ACHIEVING A GLOBAL ECONOMIC FORECAST

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Camelia Madalina Orac

2013-12-01

Full Text Available The global economic development model has proved to be insufficiently reliable under the new economic crisis. As a result, the entire theoretical construction about the global economy needs rethinking and reorientation. In this context, it is quite clear that only through effective use of specific techniques and tools of economic-mathematical modeling, statistics, regional analysis and economic forecasting it is possible to obtain an overview of the future economy.

Residuals and the Residual-Based Statistic for Testing Goodness of Fit of Structural Equation Models

Science.gov (United States)

Foldnes, Njal; Foss, Tron; Olsson, Ulf Henning

2012-01-01

The residuals obtained from fitting a structural equation model are crucial ingredients in obtaining chi-square goodness-of-fit statistics for the model. The authors present a didactic discussion of the residuals, obtaining a geometrical interpretation by recognizing the residuals as the result of oblique projections. This sheds light on the…

Total kinetic energy in four global eddying ocean circulation models and over 5000 current meter records

KAUST Repository

Scott, Robert B.

2010-01-01

We compare the total kinetic energy (TKE) in four global eddying ocean circulation simulations with a global dataset of over 5000, quality controlled, moored current meter records. At individual mooring sites, there was considerable scatter between models and observations that was greater than estimated statistical uncertainty. Averaging over all current meter records in various depth ranges, all four models had mean TKE within a factor of two of observations above 3500. m, and within a factor of three below 3500. m. With the exception of observations between 20 and 100. m, the models tended to straddle the observations. However, individual models had clear biases. The free running (no data assimilation) model biases were largest below 2000. m. Idealized simulations revealed that the parameterized bottom boundary layer tidal currents were not likely the source of the problem, but that reducing quadratic bottom drag coefficient may improve the fit with deep observations. Data assimilation clearly improved the model-observation comparison, especially below 2000. m, despite assimilated data existing mostly above this depth and only south of 47°N. Different diagnostics revealed different aspects of the comparison, though in general the models appeared to be in an eddying-regime with TKE that compared reasonably well with observations. © 2010 Elsevier Ltd.

Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

Science.gov (United States)

DeCarlo, Lawrence T

2003-02-01

The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

A high-resolution global flood hazard model

Science.gov (United States)

Sampson, Christopher C.; Smith, Andrew M.; Bates, Paul B.; Neal, Jeffrey C.; Alfieri, Lorenzo; Freer, Jim E.

2015-09-01

Floods are a natural hazard that affect communities worldwide, but to date the vast majority of flood hazard research and mapping has been undertaken by wealthy developed nations. As populations and economies have grown across the developing world, so too has demand from governments, businesses, and NGOs for modeled flood hazard data in these data-scarce regions. We identify six key challenges faced when developing a flood hazard model that can be applied globally and present a framework methodology that leverages recent cross-disciplinary advances to tackle each challenge. The model produces return period flood hazard maps at ˜90 m resolution for the whole terrestrial land surface between 56°S and 60°N, and results are validated against high-resolution government flood hazard data sets from the UK and Canada. The global model is shown to capture between two thirds and three quarters of the area determined to be at risk in the benchmark data without generating excessive false positive predictions. When aggregated to ˜1 km, mean absolute error in flooded fraction falls to ˜5%. The full complexity global model contains an automatically parameterized subgrid channel network, and comparison to both a simplified 2-D only variant and an independently developed pan-European model shows the explicit inclusion of channels to be a critical contributor to improved model performance. While careful processing of existing global terrain data sets enables reasonable model performance in urban areas, adoption of forthcoming next-generation global terrain data sets will offer the best prospect for a step-change improvement in model performance.

Natural priors, CMSSM fits and LHC weather forecasts

International Nuclear Information System (INIS)

Allanach, Benjamin C.; Cranmer, Kyle; Lester, Christopher G.; Weber, Arne M.

2007-01-01

Previous LHC forecasts for the constrained minimal supersymmetric standard model (CMSSM), based on current astrophysical and laboratory measurements, have used priors that are flat in the parameter tan β, while being constrained to postdict the central experimental value of M Z . We construct a different, new and more natural prior with a measure in μ and B (the more fundamental MSSM parameters from which tan β and M Z are actually derived). We find that as a consequence this choice leads to a well defined fine-tuning measure in the parameter space. We investigate the effect of such on global CMSSM fits to indirect constraints, providing posterior probability distributions for Large Hadron Collider (LHC) sparticle production cross sections. The change in priors has a significant effect, strongly suppressing the pseudoscalar Higgs boson dark matter annihilation region, and diminishing the probable values of sparticle masses. We also show how to interpret fit information from a Markov Chain Monte Carlo in a frequentist fashion; namely by using the profile likelihood. Bayesian and frequentist interpretations of CMSSM fits are compared and contrasted

Fitting Diffusion Item Response Theory Models for Responses and Response Times Using the R Package diffIRT

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Dylan Molenaar

2015-08-01

Full Text Available In the psychometric literature, item response theory models have been proposed that explicitly take the decision process underlying the responses of subjects to psychometric test items into account. Application of these models is however hampered by the absence of general and flexible software to fit these models. In this paper, we present diffIRT, an R package that can be used to fit item response theory models that are based on a diffusion process. We discuss parameter estimation and model fit assessment, show the viability of the package in a simulation study, and illustrate the use of the package with two datasets pertaining to extraversion and mental rotation. In addition, we illustrate how the package can be used to fit the traditional diffusion model (as it has been originally developed in experimental psychology to data.

Physical self-concept and physical fitness in elderly individuals.

Science.gov (United States)

Amesberger, G; Finkenzeller, T; Würth, S; Müller, E

2011-08-01

This investigation examined the relations between physical self-concept and physical fitness (endurance, balance, muscle strength, muscle power) for gaining knowledge about the interrelationship between subjective ratings and objective fitness scores in the elderly in three steps: (1) detecting correlations and changes in time, (2) clarifying the influence of gender, and (3) of a skiing intervention lasting 12 weeks. Physical self-concept was assessed using a modified version of the Physical Self-Concepts (PSK) scales (Stiller et al., 2004) reflecting three first-order factors (endurance, strength, general sportiness) and one second-order factor (global fitness). Objective fitness scores were obtained by VO(2 max), counter movement jump, concentric muscle strength, and static balance. The results reveal that elderly individuals' global physical self and general sportiness are mainly linked to VO(2 max) and concentric muscle strength. Global physical self is predicted by VO(2 max) in females and by physical strength (concentric muscle strength) in males, indicating gender differences. Over time, correlations between subjective ratings and objective fitness scores become stronger in the sense of convergent validity in the skiing intervention group, whereas convergent and divergent validity cannot be supported by data of the control group. In sum, physical self-concept is an important factor in the context of physical intervention programs in the elderly. © 2011 John Wiley & Sons A/S.

Sustained fitness gains and variability in fitness trajectories in the long-term evolution experiment with Escherichia coli

Science.gov (United States)

Lenski, Richard E.; Wiser, Michael J.; Ribeck, Noah; Blount, Zachary D.; Nahum, Joshua R.; Morris, J. Jeffrey; Zaman, Luis; Turner, Caroline B.; Wade, Brian D.; Maddamsetti, Rohan; Burmeister, Alita R.; Baird, Elizabeth J.; Bundy, Jay; Grant, Nkrumah A.; Card, Kyle J.; Rowles, Maia; Weatherspoon, Kiyana; Papoulis, Spiridon E.; Sullivan, Rachel; Clark, Colleen; Mulka, Joseph S.; Hajela, Neerja

2015-01-01

Many populations live in environments subject to frequent biotic and abiotic changes. Nonetheless, it is interesting to ask whether an evolving population's mean fitness can increase indefinitely, and potentially without any limit, even in a constant environment. A recent study showed that fitness trajectories of Escherichia coli populations over 50 000 generations were better described by a power-law model than by a hyperbolic model. According to the power-law model, the rate of fitness gain declines over time but fitness has no upper limit, whereas the hyperbolic model implies a hard limit. Here, we examine whether the previously estimated power-law model predicts the fitness trajectory for an additional 10 000 generations. To that end, we conducted more than 1100 new competitive fitness assays. Consistent with the previous study, the power-law model fits the new data better than the hyperbolic model. We also analysed the variability in fitness among populations, finding subtle, but significant, heterogeneity in mean fitness. Some, but not all, of this variation reflects differences in mutation rate that evolved over time. Taken together, our results imply that both adaptation and divergence can continue indefinitely—or at least for a long time—even in a constant environment. PMID:26674951

A flexible, interactive software tool for fitting the parameters of neuronal models.

Science.gov (United States)

Friedrich, Péter; Vella, Michael; Gulyás, Attila I; Freund, Tamás F; Káli, Szabolcs

2014-01-01

The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible) the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation) of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problems of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire) neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting tool.

A flexible, interactive software tool for fitting the parameters of neuronal models

Directory of Open Access Journals (Sweden)

Péter eFriedrich

2014-07-01

Full Text Available The construction of biologically relevant neuronal models as well as model-based analysis of experimental data often requires the simultaneous fitting of multiple model parameters, so that the behavior of the model in a certain paradigm matches (as closely as possible the corresponding output of a real neuron according to some predefined criterion. Although the task of model optimization is often computationally hard, and the quality of the results depends heavily on technical issues such as the appropriate choice (and implementation of cost functions and optimization algorithms, no existing program provides access to the best available methods while also guiding the user through the process effectively. Our software, called Optimizer, implements a modular and extensible framework for the optimization of neuronal models, and also features a graphical interface which makes it easy for even non-expert users to handle many commonly occurring scenarios. Meanwhile, educated users can extend the capabilities of the program and customize it according to their needs with relatively little effort. Optimizer has been developed in Python, takes advantage of open-source Python modules for nonlinear optimization, and interfaces directly with the NEURON simulator to run the models. Other simulators are supported through an external interface. We have tested the program on several different types of problem of varying complexity, using different model classes. As targets, we used simulated traces from the same or a more complex model class, as well as experimental data. We successfully used Optimizer to determine passive parameters and conductance densities in compartmental models, and to fit simple (adaptive exponential integrate-and-fire neuronal models to complex biological data. Our detailed comparisons show that Optimizer can handle a wider range of problems, and delivers equally good or better performance than any other existing neuronal model fitting

A high resolution global scale groundwater model

Science.gov (United States)

de Graaf, Inge; Sutanudjaja, Edwin; van Beek, Rens; Bierkens, Marc

2014-05-01

As the world's largest accessible source of freshwater, groundwater plays a vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and supplies water for agricultural and industrial activities. During times of drought, groundwater storage provides a large natural buffer against water shortage and sustains flows to rivers and wetlands, supporting ecosystem habitats and biodiversity. Yet, the current generation of global scale hydrological models (GHMs) do not include a groundwater flow component, although it is a crucial part of the hydrological cycle. Thus, a realistic physical representation of the groundwater system that allows for the simulation of groundwater head dynamics and lateral flows is essential for GHMs that increasingly run at finer resolution. In this study we present a global groundwater model with a resolution of 5 arc-minutes (approximately 10 km at the equator) using MODFLOW (McDonald and Harbaugh, 1988). With this global groundwater model we eventually intend to simulate the changes in the groundwater system over time that result from variations in recharge and abstraction. Aquifer schematization and properties of this groundwater model were developed from available global lithological maps and datasets (Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moosdorf, 2013), combined with our estimate of aquifer thickness for sedimentary basins. We forced the groundwater model with the output from the global hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the net groundwater recharge and average surface water levels derived from routed channel discharge. For the parameterization, we relied entirely on available global datasets and did not calibrate the model so that it can equally be expanded to data poor environments. Based on our sensitivity analysis, in which we run the model with various hydrogeological parameter settings, we observed that most variance in groundwater

Analysing model fit of psychometric process models: An overview, a new test and an application to the diffusion model.

Science.gov (United States)

Ranger, Jochen; Kuhn, Jörg-Tobias; Szardenings, Carsten

2017-05-01

Cognitive psychometric models embed cognitive process models into a latent trait framework in order to allow for individual differences. Due to their close relationship to the response process the models allow for profound conclusions about the test takers. However, before such a model can be used its fit has to be checked carefully. In this manuscript we give an overview over existing tests of model fit and show their relation to the generalized moment test of Newey (Econometrica, 53, 1985, 1047) and Tauchen (J. Econometrics, 30, 1985, 415). We also present a new test, the Hausman test of misspecification (Hausman, Econometrica, 46, 1978, 1251). The Hausman test consists of a comparison of two estimates of the same item parameters which should be similar if the model holds. The performance of the Hausman test is evaluated in a simulation study. In this study we illustrate its application to two popular models in cognitive psychometrics, the Q-diffusion model and the D-diffusion model (van der Maas, Molenaar, Maris, Kievit, & Boorsboom, Psychol Rev., 118, 2011, 339; Molenaar, Tuerlinckx, & van der Maas, J. Stat. Softw., 66, 2015, 1). We also compare the performance of the test to four alternative tests of model fit, namely the M 2 test (Molenaar et al., J. Stat. Softw., 66, 2015, 1), the moment test (Ranger et al., Br. J. Math. Stat. Psychol., 2016) and the test for binned time (Ranger & Kuhn, Psychol. Test. Asess. , 56, 2014b, 370). The simulation study indicates that the Hausman test is superior to the latter tests. The test closely adheres to the nominal Type I error rate and has higher power in most simulation conditions. © 2017 The British Psychological Society.

Review of electroweak fits of the SM and beyond, after the Higgs discovery -- with Gfitter

CERN Document Server

Baak, M

2014-01-01

We present an update of the global Standard Model (SM) fit to electroweak precision data under the assumption that the new particle discovered at the LHC is the SM Higgs boson. In this scenario all parameters entering the calculations of electroweak precision observables are known, allowing to over-constrain the SM at the electroweak scale and to assert its validity. Within the SM the W boson mass and the effective weak mixing angle can now be accurately predicted from the global fit. Their results exceed in precision the direct measurements. A determination of the S , T and U parameters, which parametrize the oblique vacuum corrections, is given. We examine the impact of the STU observables on a model of modified couplings of the Higgs boson to gauge bosons, and compare this with the corresponding analysis of LHC measurements of the signal strength of Higgs channels. Future measurements at the International Linear Collider (ILC) promise to improve significantly the experimental precision of key observables u...

A statistical light use efficiency model explains 85% variations in global GPP

Science.gov (United States)

Jiang, C.; Ryu, Y.

2016-12-01

Photosynthesis is a complicated process whose modeling requires different levels of assumptions, simplification, and parameterization. Among models, light use efficiency (LUE) model is highly compact but powerful in monitoring gross primary production (GPP) from satellite data. Most of LUE models adopt a multiplicative from of maximum LUE, absorbed photosynthetically active radiation (APAR), and temperature and water stress functions. However, maximum LUE is a fitting parameter with large spatial variations, but most studies only use several biome dependent constants. In addition, stress functions are empirical and arbitrary in literatures. Moreover, meteorological data used are usually coarse-resolution, e.g., 1°, which could cause large errors. Finally, sunlit and shade canopy have completely different light responses but little considered. Targeting these issues, we derived a new statistical LUE model from a process-based and satellite-driven model, the Breathing Earth System Simulator (BESS). We have already derived a set of global radiation (5-km resolution), carbon and water fluxes (1-km resolution) products from 2000 to 2015 from BESS. By exploring these datasets, we found strong correlation between APAR and GPP for sunlit (R2=0.84) and shade (R2=0.96) canopy, respectively. A simple model, only driven by sunlit and shade APAR, was thus built based on linear relationships. The slopes of the linear function act as effective LUE of global ecosystem, with values of 0.0232 and 0.0128 umol C/umol quanta for sunlit and shade canopy, respectively. When compared with MPI-BGC GPP products, a global proxy of FLUXNET data, BESS-LUE achieved an overall accuracy of R2 = 0.85, whereas original BESS was R2 = 0.83 and MODIS GPP product was R2 = 0.76. We investigated spatiotemporal variations of the effective LUE. Spatially, the ratio of sunlit to shade values ranged from 0.1 (wet tropic) to 4.5 (dry inland). By using maps of sunlit and shade effective LUE the accuracy of

eWaterCycle: A global operational hydrological forecasting model

Science.gov (United States)

van de Giesen, Nick; Bierkens, Marc; Donchyts, Gennadii; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin

2015-04-01

Development of an operational hyper-resolution hydrological global model is a central goal of the eWaterCycle project (www.ewatercycle.org). This operational model includes ensemble forecasts (14 days) to predict water related stress around the globe. Assimilation of near-real time satellite data is part of the intended product that will be launched at EGU 2015. The challenges come from several directions. First, there are challenges that are mainly computer science oriented but have direct practical hydrological implications. For example, we aim to make use as much as possible of existing standards and open-source software. For example, different parts of our system are coupled through the Basic Model Interface (BMI) developed in the framework of the Community Surface Dynamics Modeling System (CSDMS). The PCR-GLOBWB model, built by Utrecht University, is the basic hydrological model that is the engine of the eWaterCycle project. Re-engineering of parts of the software was needed for it to run efficiently in a High Performance Computing (HPC) environment, and to be able to interface using BMI, and run on multiple compute nodes in parallel. The final aim is to have a spatial resolution of 1km x 1km, which is currently 10 x 10km. This high resolution is computationally not too demanding but very memory intensive. The memory bottleneck becomes especially apparent for data assimilation, for which we use OpenDA. OpenDa allows for different data assimilation techniques without the need to build these from scratch. We have developed a BMI adaptor for OpenDA, allowing OpenDA to use any BMI compatible model. To circumvent memory shortages which would result from standard applications of the Ensemble Kalman Filter, we have developed a variant that does not need to keep all ensemble members in working memory. At EGU, we will present this variant and how it fits well in HPC environments. An important step in the eWaterCycle project was the coupling between the hydrological and

A Global Stock and Bond Model

OpenAIRE

Connor, Gregory

1996-01-01

Factor models are now widely used to support asset selection decisions. Global asset allocation, the allocation between stocks versus bonds and among nations, usually relies instead on correlation analysis of international equity and bond indexes. It would be preferable to have a single integrated framework for both asset selection and asset allocation. This framework would require a factor model applicable at an asset or country level, as well as at a global level,...

Feature extraction through least squares fit to a simple model

International Nuclear Information System (INIS)

Demuth, H.B.

1976-01-01

The Oak Ridge National Laboratory (ORNL) presented the Los Alamos Scientific Laboratory (LASL) with 18 radiographs of fuel rod test bundles. The problem is to estimate the thickness of the gap between some cylindrical rods and a flat wall surface. The edges of the gaps are poorly defined due to finite source size, x-ray scatter, parallax, film grain noise, and other degrading effects. The radiographs were scanned and the scan-line data were averaged to reduce noise and to convert the problem to one dimension. A model of the ideal gap, convolved with an appropriate point-spread function, was fit to the averaged data with a least squares program; and the gap width was determined from the final fitted-model parameters. The least squares routine did converge and the gaps obtained are of reasonable size. The method is remarkably insensitive to noise. This report describes the problem, the techniques used to solve it, and the results and conclusions. Suggestions for future work are also given

A Simple Model of Global Aerosol Indirect Effects

Science.gov (United States)

Ghan, Steven J.; Smith, Steven J.; Wang, Minghuai; Zhang, Kai; Pringle, Kirsty; Carslaw, Kenneth; Pierce, Jeffrey; Bauer, Susanne; Adams, Peter

2013-01-01

Most estimates of the global mean indirect effect of anthropogenic aerosol on the Earth's energy balance are from simulations by global models of the aerosol lifecycle coupled with global models of clouds and the hydrologic cycle. Extremely simple models have been developed for integrated assessment models, but lack the flexibility to distinguish between primary and secondary sources of aerosol. Here a simple but more physically based model expresses the aerosol indirect effect (AIE) using analytic representations of cloud and aerosol distributions and processes. Although the simple model is able to produce estimates of AIEs that are comparable to those from some global aerosol models using the same global mean aerosol properties, the estimates by the simple model are sensitive to preindustrial cloud condensation nuclei concentration, preindustrial accumulation mode radius, width of the accumulation mode, size of primary particles, cloud thickness, primary and secondary anthropogenic emissions, the fraction of the secondary anthropogenic emissions that accumulates on the coarse mode, the fraction of the secondary mass that forms new particles, and the sensitivity of liquid water path to droplet number concentration. Estimates of present-day AIEs as low as 5 W/sq m and as high as 0.3 W/sq m are obtained for plausible sets of parameter values. Estimates are surprisingly linear in emissions. The estimates depend on parameter values in ways that are consistent with results from detailed global aerosol-climate simulation models, which adds to understanding of the dependence on AIE uncertainty on uncertainty in parameter values.

Global Geopotential Energy & Stress Field

DEFF Research Database (Denmark)

Schiffer, Christian; Nielsen, S.B.

of the oceanic lithosphere. An entire modelling of the shallow Geopotential Energy is hereby approached, not taking into account possible deeper signals but all lithospheric signals for the subsequent stress calculation. Therefore a global lithospheric density model is necessary to calculate the corresponding...... response to Geopotential Energy and the Geoid. A linearized inverse method fits a lithospheric reference model to reproduce measured data sets, such as topography and surface heat flow, while assuming isostasy and solving the steady state heat equation. A FEM code solves the equations of equilibrium...

Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

Science.gov (United States)

Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

2013-07-01

Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

The status and challenge of global fire modelling

Science.gov (United States)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao

2016-06-01

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

Global nuclear material flow/control model

International Nuclear Information System (INIS)

Dreicer, J.S.; Rutherford, D.S.; Fasel, P.K.; Riese, J.M.

1997-01-01

This is the final report of a two-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The nuclear danger can be reduced by a system for global management, protection, control, and accounting as part of an international regime for nuclear materials. The development of an international fissile material management and control regime requires conceptual research supported by an analytical and modeling tool which treats the nuclear fuel cycle as a complete system. The prototype model developed visually represents the fundamental data, information, and capabilities related to the nuclear fuel cycle in a framework supportive of national or an international perspective. This includes an assessment of the global distribution of military and civilian fissile material inventories, a representation of the proliferation pertinent physical processes, facility specific geographic identification, and the capability to estimate resource requirements for the management and control of nuclear material. The model establishes the foundation for evaluating the global production, disposition, and safeguards and security requirements for fissile nuclear material and supports the development of other pertinent algorithmic capabilities necessary to undertake further global nuclear material related studies

Modeling of the Global Water Cycle - Analytical Models

Science.gov (United States)

Yongqiang Liu; Roni Avissar

2005-01-01

Both numerical and analytical models of coupled atmosphere and its underlying ground components (land, ocean, ice) are useful tools for modeling the global and regional water cycle. Unlike complex three-dimensional climate models, which need very large computing resources and involve a large number of complicated interactions often difficult to interpret, analytical...

Validation of A Global Hydrological Model

Science.gov (United States)

Doell, P.; Lehner, B.; Kaspar, F.; Vassolo, S.

Freshwater availability has been recognized as a global issue, and its consistent quan- tification not only in individual river basins but also at the global scale is required to support the sustainable use of water. The Global Hydrology Model WGHM, which is a submodel of the global water use and availability model WaterGAP 2, computes sur- face runoff, groundwater recharge and river discharge at a spatial resolution of 0.5. WGHM is based on the best global data sets currently available, including a newly developed drainage direction map and a data set of wetlands, lakes and reservoirs. It calculates both natural and actual discharge by simulating the reduction of river discharge by human water consumption (as computed by the water use submodel of WaterGAP 2). WGHM is calibrated against observed discharge at 724 gauging sta- tions (representing about 50% of the global land area) by adjusting a parameter of the soil water balance. It not only computes the long-term average water resources but also water availability indicators that take into account the interannual and seasonal variability of runoff and discharge. The reliability of the model results is assessed by comparing observed and simulated discharges at the calibration stations and at se- lected other stations. We conclude that reliable results can be obtained for basins of more than 20,000 km2. In particular, the 90% reliable monthly discharge is simu- lated well. However, there is the tendency that semi-arid and arid basins are modeled less satisfactorily than humid ones, which is partially due to neglecting river channel losses and evaporation of runoff from small ephemeral ponds in the model. Also, the hydrology of highly developed basins with large artificial storages, basin transfers and irrigation schemes cannot be simulated well. The seasonality of discharge in snow- dominated basins is overestimated by WGHM, and if the snow-dominated basin is uncalibrated, discharge is likely to be underestimated

Fitness cost

DEFF Research Database (Denmark)

Nielsen, Karen L.; Pedersen, Thomas M.; Udekwu, Klas I.

2012-01-01

phage types, predominantly only penicillin resistant. We investigated whether isolates of this epidemic were associated with a fitness cost, and we employed a mathematical model to ask whether these fitness costs could have led to the observed reduction in frequency. Bacteraemia isolates of S. aureus...... from Denmark have been stored since 1957. We chose 40 S. aureus isolates belonging to phage complex 83A, clonal complex 8 based on spa type, ranging in time of isolation from 1957 to 1980 and with varyous antibiograms, including both methicillin-resistant and -susceptible isolates. The relative fitness...... of each isolate was determined in a growth competition assay with a reference isolate. Significant fitness costs of 215 were determined for the MRSA isolates studied. There was a significant negative correlation between number of antibiotic resistances and relative fitness. Multiple regression analysis...

GOODNESS-OF-FIT TEST FOR THE ACCELERATED FAILURE TIME MODEL BASED ON MARTINGALE RESIDUALS

Czech Academy of Sciences Publication Activity Database

Novák, Petr

2013-01-01

Roč. 49, č. 1 (2013), s. 40-59 ISSN 0023-5954 R&D Projects: GA MŠk(CZ) 1M06047 Grant - others:GA MŠk(CZ) SVV 261315/2011 Keywords : accelerated failure time model * survival analysis * goodness-of-fit Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/SI/novak-goodness-of-fit test for the aft model based on martingale residuals.pdf

Statistical models of global Langmuir mixing

Science.gov (United States)

Li, Qing; Fox-Kemper, Baylor; Breivik, Øyvind; Webb, Adrean

2017-05-01

The effects of Langmuir mixing on the surface ocean mixing may be parameterized by applying an enhancement factor which depends on wave, wind, and ocean state to the turbulent velocity scale in the K-Profile Parameterization. Diagnosing the appropriate enhancement factor online in global climate simulations is readily achieved by coupling with a prognostic wave model, but with significant computational and code development expenses. In this paper, two alternatives that do not require a prognostic wave model, (i) a monthly mean enhancement factor climatology, and (ii) an approximation to the enhancement factor based on the empirical wave spectra, are explored and tested in a global climate model. Both appear to reproduce the Langmuir mixing effects as estimated using a prognostic wave model, with nearly identical and substantial improvements in the simulated mixed layer depth and intermediate water ventilation over control simulations, but significantly less computational cost. Simpler approaches, such as ignoring Langmuir mixing altogether or setting a globally constant Langmuir number, are found to be deficient. Thus, the consequences of Stokes depth and misaligned wind and waves are important.

A variant of the anomaly initialisation approach for global climate forecast models

Science.gov (United States)

Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco; Hawkins, Ed; Nichols, Nancy; Carrassi, Alberto

2014-05-01

This work presents a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following particularities: - the use of a weight to the anomalies, in order to avoid the risk of introducing too big anomalies recorded in the observed state, whose amplitude does not fit the range of the internal variability generated by the model. - the AI of the temperature and density ocean state variables instead of the temperature and salinity. Results show that the use of such refinements improve the skill over the Arctic region, part of the North and South Atlantic, part of the North and South Pacific and the Mediterranean Sea. In the Tropical Pacific the full field initialised experiment performs better. This is probably due to a displacement of the observed anomalies caused by the use of the AI technique. Furthermore, preliminary results of an anomaly nudging experiment are discussed.

Physical Fitness and Serum Vitamin D and Cognition in Elderly Koreans.

Science.gov (United States)

Ahn, Jeong-Deok; Kang, Hyunsik

2015-12-01

Poor physical fitness and low serum vitamin D are known to be modifiable risk factors for cognitive declines with normal aging. We investigated the association of physical fitness and serum vitamin D levels with global cognitive function in older adults. In this cross-sectional study, a total of 412 older Korean adults (108 men aged 74.4 ± 6.0 years and 304 women aged 73.1 ± 5.4 years) completed the Korean version of Mini-Mental State Examination (MMSE) to assess global cognitive performance and the senior fitness test to assess strength, flexibility, agility, and endurance domains of physical fitness. Body mass index, percent body fat, serum vitamin D, geriatric depression scale (GDS), level of education, smoking, and history of cardiovascular or cerebrovascular disease were also assessed as covariates. Age, sex, GDS, and body fatness were negatively associated with MMSE-based cognitive performance. Serum vitamin D and physical fitness were positively associated with MMSE-based cognitive performance. Multivariate linear regression showed that agility (partial R(2) = -0.184, p = 0.029) and endurance (partial R(2) = 0.191, p = 0.022) domains of physical fitness along with serum vitamin D (partial R(2) = 0.210, p = 0.012) were significant predictors for global cognitive performance after controlling for covariates (i.e., age, sex, education, GDS, body fatness, and comorbidity index). The current findings of the study suggest that promotion of physical fitness and vitamin D supplementation should be key components of interventions to prevent cognitive decline with normal aging. Key pointsCognitive declines are associated with normal aging as well as modifiable lifestyle risk factors, and there is an increasing need to identify the modifiable risk factors for the onset of cognitive declines and to provide evidence-based strategies for healthy and successful aging.In Korea, little is known about the relationships of physical fitness and serum vitamin D with cognitive

Assessing model fit in latent class analysis when asymptotics do not hold

NARCIS (Netherlands)

van Kollenburg, Geert H.; Mulder, Joris; Vermunt, Jeroen K.

2015-01-01

The application of latent class (LC) analysis involves evaluating the LC model using goodness-of-fit statistics. To assess the misfit of a specified model, say with the Pearson chi-squared statistic, a p-value can be obtained using an asymptotic reference distribution. However, asymptotic p-values

Applicability of Zero-Inflated Models to Fit the Torrential Rainfall Count Data with Extra Zeros in South Korea

Directory of Open Access Journals (Sweden)

Cheol-Eung Lee

2017-02-01

Full Text Available Several natural disasters occur because of torrential rainfalls. The change in global climate most likely increases the occurrences of such downpours. Hence, it is necessary to investigate the characteristics of the torrential rainfall events in order to introduce effective measures for mitigating disasters such as urban floods and landslides. However, one of the major problems is evaluating the number of torrential rainfall events from a statistical viewpoint. If the number of torrential rainfall occurrences during a month is considered as count data, their frequency distribution could be identified using a probability distribution. Generally, the number of torrential rainfall occurrences has been analyzed using the Poisson distribution (POI or the Generalized Poisson Distribution (GPD. However, it was reported that POI and GPD often overestimated or underestimated the observed count data when additional or fewer zeros were included. Hence, in this study, a zero-inflated model concept was applied to solve this problem existing in the conventional models. Zero-Inflated Poisson (ZIP model, Zero-Inflated Generalized Poisson (ZIGP model, and the Bayesian ZIGP model have often been applied to fit the count data having additional or fewer zeros. However, the applications of these models in water resource management have been very limited despite their efficiency and accuracy. The five models, namely, POI, GPD, ZIP, ZIGP, and Bayesian ZIGP, were applied to the torrential rainfall data having additional zeros obtained from two rain gauges in South Korea, and their applicability was examined in this study. In particular, the informative prior distributions evaluated via the empirical Bayes method using ten rain gauges were developed in the Bayesian ZIGP model. Finally, it was suggested to avoid using the POI and GPD models to fit the frequency of torrential rainfall data. In addition, it was concluded that the Bayesian ZIGP model used in this study

Fourier series models through transformation | Omekara | Global ...

African Journals Online (AJOL)

As a result, the square transformation which outperforms the others is adopted. Consequently, each of the multiplicative and additive FSA models fitted to the transformed data are then subjected to a test for white noise based on spectral analysis. The result of this test shows that only the multiplicative model is adequate.

GEM - The Global Earthquake Model

Science.gov (United States)

Smolka, A.

2009-04-01

Over 500,000 people died in the last decade due to earthquakes and tsunamis, mostly in the developing world, where the risk is increasing due to rapid population growth. In many seismic regions, no hazard and risk models exist, and even where models do exist, they are intelligible only by experts, or available only for commercial purposes. The Global Earthquake Model (GEM) answers the need for an openly accessible risk management tool. GEM is an internationally sanctioned public private partnership initiated by the Organisation for Economic Cooperation and Development (OECD) which will establish an authoritative standard for calculating and communicating earthquake hazard and risk, and will be designed to serve as the critical instrument to support decisions and actions that reduce earthquake losses worldwide. GEM will integrate developments on the forefront of scientific and engineering knowledge of earthquakes, at global, regional and local scale. The work is organized in three modules: hazard, risk, and socio-economic impact. The hazard module calculates probabilities of earthquake occurrence and resulting shaking at any given location. The risk module calculates fatalities, injuries, and damage based on expected shaking, building vulnerability, and the distribution of population and of exposed values and facilities. The socio-economic impact module delivers tools for making educated decisions to mitigate and manage risk. GEM will be a versatile online tool, with open source code and a map-based graphical interface. The underlying data will be open wherever possible, and its modular input and output will be adapted to multiple user groups: scientists and engineers, risk managers and decision makers in the public and private sectors, and the public-at- large. GEM will be the first global model for seismic risk assessment at a national and regional scale, and aims to achieve broad scientific participation and independence. Its development will occur in a

Technology Learning Ratios in Global Energy Models

International Nuclear Information System (INIS)

Varela, M.

2001-01-01

The process of introduction of a new technology supposes that while its production and utilisation increases, also its operation improves and its investment costs and production decreases. The accumulation of experience and learning of a new technology increase in parallel with the increase of its market share. This process is represented by the technological learning curves and the energy sector is not detached from this process of substitution of old technologies by new ones. The present paper carries out a brief revision of the main energy models that include the technology dynamics (learning). The energy scenarios, developed by global energy models, assume that the characteristics of the technologies are variables with time. But this trend is incorporated in a exogenous way in these energy models, that is to say, it is only a time function. This practice is applied to the cost indicators of the technology such as the specific investment costs or to the efficiency of the energy technologies. In the last years, the new concept of endogenous technological learning has been integrated within these global energy models. This paper examines the concept of technological learning in global energy models. It also analyses the technological dynamics of the energy system including the endogenous modelling of the process of technological progress. Finally, it makes a comparison of several of the most used global energy models (MARKAL, MESSAGE and ERIS) and, more concretely, about the use these models make of the concept of technological learning. (Author) 17 refs

Joining the Global Village: Teaching Globalization with Wikipedia

Science.gov (United States)

Konieczny, Piotr

2017-01-01

This paper presents an analysis of my experiences with a teaching activity that engages students in publishing in Wikipedia on issues relating to globalization. It begins with a short overview of some of the current debates revolving around teaching globalization, which lay ground for the assignment. I discuss how this teaching tool fits with a…

Usefulness and limitations of global flood risk models

Science.gov (United States)

Ward, Philip; Jongman, Brenden; Salamon, Peter; Simpson, Alanna; Bates, Paul; De Groeve, Tom; Muis, Sanne; Coughlan de Perez, Erin; Rudari, Roberto; Mark, Trigg; Winsemius, Hessel

2016-04-01

Global flood risk models are now a reality. Initially, their development was driven by a demand from users for first-order global assessments to identify risk hotspots. Relentless upward trends in flood damage over the last decade have enhanced interest in such assessments. The adoption of the Sendai Framework for Disaster Risk Reduction and the Warsaw International Mechanism for Loss and Damage Associated with Climate Change Impacts have made these efforts even more essential. As a result, global flood risk models are being used more and more in practice, by an increasingly large number of practitioners and decision-makers. However, they clearly have their limits compared to local models. To address these issues, a team of scientists and practitioners recently came together at the Global Flood Partnership meeting to critically assess the question 'What can('t) we do with global flood risk models?'. The results of this dialogue (Ward et al., 2013) will be presented, opening a discussion on similar broader initiatives at the science-policy interface in other natural hazards. In this contribution, examples are provided of successful applications of global flood risk models in practice (for example together with the World Bank, Red Cross, and UNISDR), and limitations and gaps between user 'wish-lists' and model capabilities are discussed. Finally, a research agenda is presented for addressing these limitations and reducing the gaps. Ward et al., 2015. Nature Climate Change, doi:10.1038/nclimate2742

Regionalizing global climate models

NARCIS (Netherlands)

Pitman, A.J.; Arneth, A.; Ganzeveld, L.N.

2012-01-01

Global climate models simulate the Earth's climate impressively at scales of continents and greater. At these scales, large-scale dynamics and physics largely define the climate. At spatial scales relevant to policy makers, and to impacts and adaptation, many other processes may affect regional and

Global identifiability of linear compartmental models--a computer algebra algorithm.

Science.gov (United States)

Audoly, S; D'Angiò, L; Saccomani, M P; Cobelli, C

1998-01-01

A priori global identifiability deals with the uniqueness of the solution for the unknown parameters of a model and is, thus, a prerequisite for parameter estimation of biological dynamic models. Global identifiability is however difficult to test, since it requires solving a system of algebraic nonlinear equations which increases both in nonlinearity degree and number of terms and unknowns with increasing model order. In this paper, a computer algebra tool, GLOBI (GLOBal Identifiability) is presented, which combines the topological transfer function method with the Buchberger algorithm, to test global identifiability of linear compartmental models. GLOBI allows for the automatic testing of a priori global identifiability of general structure compartmental models from general multi input-multi output experiments. Examples of usage of GLOBI to analyze a priori global identifiability of some complex biological compartmental models are provided.

Tempo of Diversification of Global Amphibians: One-Constant Rate, One-Continuous Shift or Multiple-Discrete Shifts?

OpenAIRE

Youhua Chen

2014-01-01

In this brief report, alternative time-varying diversification rate models were fitted onto the phylogeny of global amphibians by considering one-constant-rate (OCR), one-continuous-shift (OCS) and multiplediscrete- shifts (MDS) situations. The OCS diversification model was rejected by γ statistic (γ=-5.556, p⁄ 0.001), implying the existence of shifting diversification rates for global amphibian phylogeny. Through model selection, MDS diversification model outperformed OCS and OCR...

Globalization and Shanghai Model: A Retrospective and Prospective Analysis

Directory of Open Access Journals (Sweden)

Linsun Cheng

2012-11-01

Full Text Available Intended to shed light on the debate on the results of globalization and providebetter understanding of the influences of globalization upon China as well as theworld, this article traces the history of Shanghai’s economic globalization over thepast 170 years since 1843 and demonstrates the benefits and problems Shanghaireceived from (or connected to its economic globalization. Divided into threesections (Globalization, de-globalization and re-globalization of Shanghai’s economy;Manufacturing-Oriented vs. Tertiary-oriented—Shanghai’s Double PriorityStrategy of Economic Growth; Free market, state enterprises, and Shanghai’s mixedeconomy the article summarizes and analyzes several characteristics that madeShanghai a unique model in the history of globalization: In adapting and adoptinginevitable economic globalization, Shanghai created its unique model of economicdevelopment—widely embracing economic globalization; placing Shanghai’seconomy on a solid foundation of both strong modern manufacturing and strongtertiary industry (consisting of finance and insurance, real estate, transportations,post and telecommunication, wholesale and retailing; and creating a mixedeconomic structure with hybrid of private and state owned enterprises. TheShanghai model proves that globalization has been an unavoidable trend as scienceand technology have made the world “smaller” and “smaller.” Actively engaging intoeconomic globalization is the only way for Shanghai, as well as many developingcountries, to accelerate its economic growth.

Global empirical wind model for the upper mesosphere/lower thermosphere. I. Prevailing wind

Directory of Open Access Journals (Sweden)

Y. I. Portnyagin

Full Text Available An updated empirical climatic zonally averaged prevailing wind model for the upper mesosphere/lower thermosphere (70-110 km, extending from 80°N to 80°S is presented. The model is constructed from the fitting of monthly mean winds from meteor radar and MF radar measurements at more than 40 stations, well distributed over the globe. The height-latitude contour plots of monthly mean zonal and meridional winds for all months of the year, and of annual mean wind, amplitudes and phases of annual and semiannual harmonics of wind variations are analyzed to reveal the main features of the seasonal variation of the global wind structures in the Northern and Southern Hemispheres. Some results of comparison between the ground-based wind models and the space-based models are presented. It is shown that, with the exception of annual mean systematic bias between the zonal winds provided by the ground-based and space-based models, a good agreement between the models is observed. The possible origin of this bias is discussed.

Key words: Meteorology and Atmospheric dynamics (general circulation; middle atmosphere dynamics; thermospheric dynamics

New Temperature-based Models for Predicting Global Solar Radiation

International Nuclear Information System (INIS)

Hassan, Gasser E.; Youssef, M. Elsayed; Mohamed, Zahraa E.; Ali, Mohamed A.; Hanafy, Ahmed A.

2016-01-01

Highlights: • New temperature-based models for estimating solar radiation are investigated. • The models are validated against 20-years measured data of global solar radiation. • The new temperature-based model shows the best performance for coastal sites. • The new temperature-based model is more accurate than the sunshine-based models. • The new model is highly applicable with weather temperature forecast techniques. - Abstract: This study presents new ambient-temperature-based models for estimating global solar radiation as alternatives to the widely used sunshine-based models owing to the unavailability of sunshine data at all locations around the world. Seventeen new temperature-based models are established, validated and compared with other three models proposed in the literature (the Annandale, Allen and Goodin models) to estimate the monthly average daily global solar radiation on a horizontal surface. These models are developed using a 20-year measured dataset of global solar radiation for the case study location (Lat. 30°51′N and long. 29°34′E), and then, the general formulae of the newly suggested models are examined for ten different locations around Egypt. Moreover, the local formulae for the models are established and validated for two coastal locations where the general formulae give inaccurate predictions. Mostly common statistical errors are utilized to evaluate the performance of these models and identify the most accurate model. The obtained results show that the local formula for the most accurate new model provides good predictions for global solar radiation at different locations, especially at coastal sites. Moreover, the local and general formulas of the most accurate temperature-based model also perform better than the two most accurate sunshine-based models from the literature. The quick and accurate estimations of the global solar radiation using this approach can be employed in the design and evaluation of performance for

FitSKIRT: genetic algorithms to automatically fit dusty galaxies with a Monte Carlo radiative transfer code

Science.gov (United States)

De Geyter, G.; Baes, M.; Fritz, J.; Camps, P.

2013-02-01

We present FitSKIRT, a method to efficiently fit radiative transfer models to UV/optical images of dusty galaxies. These images have the advantage that they have better spatial resolution compared to FIR/submm data. FitSKIRT uses the GAlib genetic algorithm library to optimize the output of the SKIRT Monte Carlo radiative transfer code. Genetic algorithms prove to be a valuable tool in handling the multi- dimensional search space as well as the noise induced by the random nature of the Monte Carlo radiative transfer code. FitSKIRT is tested on artificial images of a simulated edge-on spiral galaxy, where we gradually increase the number of fitted parameters. We find that we can recover all model parameters, even if all 11 model parameters are left unconstrained. Finally, we apply the FitSKIRT code to a V-band image of the edge-on spiral galaxy NGC 4013. This galaxy has been modeled previously by other authors using different combinations of radiative transfer codes and optimization methods. Given the different models and techniques and the complexity and degeneracies in the parameter space, we find reasonable agreement between the different models. We conclude that the FitSKIRT method allows comparison between different models and geometries in a quantitative manner and minimizes the need of human intervention and biasing. The high level of automation makes it an ideal tool to use on larger sets of observed data.

A scaled Lagrangian method for performing a least squares fit of a model to plant data

International Nuclear Information System (INIS)

Crisp, K.E.

1988-01-01

Due to measurement errors, even a perfect mathematical model will not be able to match all the corresponding plant measurements simultaneously. A further discrepancy may be introduced if an un-modelled change in conditions occurs within the plant which should have required a corresponding change in model parameters - e.g. a gradual deterioration in the performance of some component(s). Taking both these factors into account, what is required is that the overall discrepancy between the model predictions and the plant data is kept to a minimum. This process is known as 'model fitting', A method is presented for minimising any function which consists of the sum of squared terms, subject to any constraints. Its most obvious application is in the process of model fitting, where a weighted sum of squares of the differences between model predictions and plant data is the function to be minimised. When implemented within existing Central Electricity Generating Board computer models, it will perform a least squares fit of a model to plant data within a single job submission. (author)

Physical Fitness and Serum Vitamin D and Cognition in Elderly Koreans

Directory of Open Access Journals (Sweden)

Jeong-Deok Ahn, Hyunsik Kang

2015-12-01

Full Text Available Poor physical fitness and low serum vitamin D are known to be modifiable risk factors for cognitive declines with normal aging. We investigated the association of physical fitness and serum vitamin D levels with global cognitive function in older adults. In this cross-sectional study, a total of 412 older Korean adults (108 men aged 74.4 ± 6.0 years and 304 women aged 73.1 ± 5.4 years completed the Korean version of Mini-Mental State Examination (MMSE to assess global cognitive performance and the senior fitness test to assess strength, flexibility, agility, and endurance domains of physical fitness. Body mass index, percent body fat, serum vitamin D, geriatric depression scale (GDS, level of education, smoking, and history of cardiovascular or cerebrovascular disease were also assessed as covariates. Age, sex, GDS, and body fatness were negatively associated with MMSE-based cognitive performance. Serum vitamin D and physical fitness were positively associated with MMSE-based cognitive performance. Multivariate linear regression showed that agility (partial R2 = -0.184, p = 0.029 and endurance (partial R2 = 0.191, p = 0.022 domains of physical fitness along with serum vitamin D (partial R2 = 0.210, p = 0.012 were significant predictors for global cognitive performance after controlling for covariates (i.e., age, sex, education, GDS, body fatness, and comorbidity index. The current findings of the study suggest that promotion of physical fitness and vitamin D supplementation should be key components of interventions to prevent cognitive decline with normal aging.

Global warming and coral reefs: modelling the effect of temperature on Acropora palmata colony growth.

Science.gov (United States)

Crabbe, M James C

2007-08-01

Data on colony growth of the branching coral Acropora palmata from fringing reefs off Discovery Bay on the north coast of Jamaica have been obtained over the period 2002-2007 using underwater photography and image analysis by both SCUBA and remotely using an ROV incorporating twin lasers. Growth modelling shows that while logarithmic growth is an approximate model for growth, a 3:3 rational polynomial function provides a significantly better fit to growth data for this coral species. Over the period 2002-2007, involving several cycles of sea surface temperature (SST) change, the rate of growth of A. palmata was largely proportional to rate of change of SST, with R(2)=0.935. These results have implications for the influence of global warming and climate change on coral reef ecosystems.

The disconnected values model improves mental well-being and fitness in an employee wellness program.

Science.gov (United States)

Anshel, Mark H; Brinthaupt, Thomas M; Kang, Minsoo

2010-01-01

This study examined the effect of a 10-week wellness program on changes in physical fitness and mental well-being. The conceptual framework for this study was the Disconnected Values Model (DVM). According to the DVM, detecting the inconsistencies between negative habits and values (e.g., health, family, faith, character) and concluding that these "disconnects" are unacceptable promotes the need for health behavior change. Participants were 164 full-time employees at a university in the southeastern U.S. The program included fitness coaching and a 90-minute orientation based on the DVM. Multivariate Mixed Model analyses indicated significantly improved scores from pre- to post-intervention on selected measures of physical fitness and mental well-being. The results suggest that the Disconnected Values Model provides an effective cognitive-behavioral approach to generating health behavior change in a 10-week workplace wellness program.

Some Improved Diagnostics for Failure of The Rasch Model.

Science.gov (United States)

Molenaar, Ivo W.

1983-01-01

Goodness of fit tests for the Rasch model are typically large-sample, global measures. This paper offers suggestions for small-sample exploratory techniques for examining the fit of item data to the Rasch model. (Author/JKS)

Validation of a Global Hydrodynamic Flood Inundation Model

Science.gov (United States)

Bates, P. D.; Smith, A.; Sampson, C. C.; Alfieri, L.; Neal, J. C.

2014-12-01

In this work we present first validation results for a hyper-resolution global flood inundation model. We use a true hydrodynamic model (LISFLOOD-FP) to simulate flood inundation at 1km resolution globally and then use downscaling algorithms to determine flood extent and depth at 90m spatial resolution. Terrain data are taken from a custom version of the SRTM data set that has been processed specifically for hydrodynamic modelling. Return periods of flood flows along the entire global river network are determined using: (1) empirical relationships between catchment characteristics and index flood magnitude in different hydroclimatic zones derived from global runoff data; and (2) an index flood growth curve, also empirically derived. Bankful return period flow is then used to set channel width and depth, and flood defence impacts are modelled using empirical relationships between GDP, urbanization and defence standard of protection. The results of these simulations are global flood hazard maps for a number of different return period events from 1 in 5 to 1 in 1000 years. We compare these predictions to flood hazard maps developed by national government agencies in the UK and Germany using similar methods but employing detailed local data, and to observed flood extent at a number of sites including St. Louis, USA and Bangkok in Thailand. Results show that global flood hazard models can have considerable skill given careful treatment to overcome errors in the publicly available data that are used as their input.

GOSSIP: SED fitting code

Science.gov (United States)

Franzetti, Paolo; Scodeggio, Marco

2012-10-01

GOSSIP fits the electro-magnetic emission of an object (the SED, Spectral Energy Distribution) against synthetic models to find the simulated one that best reproduces the observed data. It builds-up the observed SED of an object (or a large sample of objects) combining magnitudes in different bands and eventually a spectrum; then it performs a chi-square minimization fitting procedure versus a set of synthetic models. The fitting results are used to estimate a number of physical parameters like the Star Formation History, absolute magnitudes, stellar mass and their Probability Distribution Functions.

Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

Energy Technology Data Exchange (ETDEWEB)

Zarzalejo, L.F.; Ramirez, L.; Polo, J. [DER-CIEMAT, Madrid (Spain). Renewable Energy Dept.

2005-07-01

Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models. (author)

Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

International Nuclear Information System (INIS)

Zarzalejo, Luis F.; Ramirez, Lourdes; Polo, Jesus

2005-01-01

Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models

COLUMBUS. A global gas market model

Energy Technology Data Exchange (ETDEWEB)

Hecking, Harald; Panke, Timo

2012-03-15

A model of the global gas market is presented which in its basic version optimises the future development of production, transport and storage capacities as well as the actual gas flows around the world assuming perfect competition. Besides the transport of natural gas via pipelines also the global market for liquefied natural gas (LNG) is modelled using a hub-and-spoke approach. While in the basic version of the model an inelastic demand and a piecewise-linear supply function are used, both can be changed easily, e.g. to a Golombek style production function or a constant elasticity of substitution (CES) demand function. Due to the usage of mixed complementary programming (MCP) the model additionally allows for the simulation of strategic behaviour of different players in the gas market, e.g. the gas producers.

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications

Science.gov (United States)

W. Hasan, W. Z.

2018-01-01

The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system’s modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model. PMID:29351554

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

Science.gov (United States)

Sabry, A H; W Hasan, W Z; Ab Kadir, M Z A; Radzi, M A M; Shafie, S

2018-01-01

The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications.

Directory of Open Access Journals (Sweden)

A H Sabry

Full Text Available The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.

Global study of nuclear modifications on parton distribution functions

Directory of Open Access Journals (Sweden)

Rong Wang

2017-07-01

Full Text Available A global analysis of nuclear medium modifications of parton distributions is presented using deeply inelastic scattering data of various nuclear targets. Two obtained data sets are provided for quark and gluon nuclear modification factors, referred as nIMParton16. One is from the global fit only to the experimental data of isospin-scalar nuclei (Set A, and the other is from the fit to all the measured nuclear data (Set B. The scale-dependence is described by DGLAP equations with nonlinear corrections in this work. The Fermi motion and off-shell effect, nucleon swelling, and parton–parton recombination are taken into account together for modeling the complicated x-dependence of nuclear modification. The nuclear gluon shadowing in this paper is dynamically generated by the QCD evolution of parton splitting and recombination processes with zero gluon density at the input scale. Sophisticated nuclear dependence of nuclear medium effects is studied with only two free parameters. With the obtained free parameters from the global analysis, the nuclear modifications of parton distribution functions of unmeasured nuclei can be predicted in our model. Nuclear modification of deuteron is also predicted and shown with recent measurement at JLab.

A Bayesian Approach to Multistage Fitting of the Variation of the Skeletal Age Features

Directory of Open Access Journals (Sweden)

Dong Hua

2009-01-01

Full Text Available Accurate assessment of skeletal maturity is important clinically. Skeletal age assessment is usually based on features encoded in ossification centers. Therefore, it is critical to design a mechanism to capture as much as possible characteristics of features. We have observed that given a feature, there exist stages of the skeletal age such that the variation pattern of the feature differs in these stages. Based on this observation, we propose a Bayesian cut fitting to describe features in response to the skeletal age. With our approach, appropriate positions for stage separation are determined automatically by a Bayesian approach, and a model is used to fit the variation of a feature within each stage. Our experimental results show that the proposed method surpasses the traditional fitting using only one line or one curve not only in the efficiency and accuracy of fitting but also in global and local feature characterization.

A global reference model of Moho depths based on WGM2012

Science.gov (United States)

Zhou, D.; Li, C.

2017-12-01

The crust-mantle boundary (Moho discontinuity) represents the largest density contrast in the lithosphere, which can be detected by Bouguer gravity anomaly. We present our recent inversion of global Moho depths from World Gravity Map 2012. Because oceanic lithospheres increase in density as they cool, we perform thermal correction based on the plate cooling model. We adopt a temperature Tm=1300°C at the bottom of lithosphere. The plate thickness is tested by varying by 5 km from 90 to 140 km, and taken as 130 km that gives a best-fit crustal thickness constrained by seismic crustal thickness profiles. We obtain the residual Bouguer gravity anomalies by subtracting the thermal correction from WGM2012, and then estimate Moho depths based on the Parker-Oldenburg algorithm. Taking the global model Crust1.0 as a priori constraint, we adopt Moho density contrasts of 0.43 and 0.4 g/cm3 , and initial mean Moho depths of 37 and 20 km in the continental and oceanic domains, respectively. The number of iterations in the inversion is set to be 150, which is large enough to obtain an error lower than a pre-assigned convergence criterion. The estimated Moho depths range between 0 76 km, and are averaged at 36 and 15 km in continental and oceanic domain, respectively. Our results correlate very well with Crust1.0 with differences mostly within ±5.0 km. Compared to the low resolution of Crust1.0 in oceanic domain, our results have a much larger depth range reflecting diverse structures such as ridges, seamounts, volcanic chains and subduction zones. Base on this model, we find that young(95mm/yr) we observe relatively thicker crust. Conductive cooling of lithosphere may constrain the melting of the mantle at ultraslow spreading centers. Lower mantle temperatures indicated by deeper Curie depths at slow and fast spreading ridges may decrease the volume of magmatism and crustal thickness. This new global model of gravity-derived Moho depth, combined with geochemical and Curie

Impact of the heavy quark matching scales in PDF fits

Energy Technology Data Exchange (ETDEWEB)

Bertone, V. [VU Univ., Amsterdam (Netherlands). Dept. of Physics and Astronomy; Nikhef Theory Goup, Amsterdam (Netherlands); Britzger, D. [DESY, Hamburg (Germany); Camarda, S. [CERN, Geneva (Switzerland); Collaboration: The xFitter Developers' Team; and others

2017-07-15

We investigate the impact of displaced heavy quark matching scales in a global fit. The heavy quark matching scale μ{sub m} determines at which energy scale μ the QCD theory transitions from N{sub F} to N{sub F}+1 in the Variable Flavor Number Scheme (VFNS) for the evolution of the Parton Distribution Functions (PDFs) and strong coupling α{sub S}(μ). We study the variation of the matching scales, and their impact on a global PDF fit of the combined HERA data. As the choice of the matching scale μ{sub m} effectively is a choice of scheme, this represents a theoretical uncertainty; ideally, we would like to see minimal dependence on this parameter. For the transition across the charm quark (from N{sub F}=3 to 4), we find a large μ{sub m}=μ{sub c} dependence of the global fit χ{sup 2} at NLO, but this is significantly reduced at NNLO. For the transition across the bottom quark (from N{sub F}=4 to 5), we have a reduced μ{sub m}=μ{sub b} dependence of the χ{sup 2} at both NLO and NNLO as compared to the charm. This feature is now implemented in xFitter 2.0.0, an open source QCD fit framework.

Synergy effects of fluoxetine and variability in temperature lead to proportionally greater fitness costs in Daphnia: A multigenerational test.

Science.gov (United States)

Barbosa, Miguel; Inocentes, Núrya; Soares, Amadeu M V M; Oliveira, Miguel

2017-12-01

Increased variability in water temperature is predicted to impose disproportionally greater fitness costs than mean increase in temperature. Additionally, water contaminants are currently a major source of human-induced stress likely to produce fitness costs. Global change models forecast an increase in these two human-induced stressors. Yet, in spite the growing interest in understanding how organisms respond to global change, the joint fitness effects of water pollution and increased variability in temperature remain unclear. Here, using a multigenerational design, we test the hypothesis that exposure to high concentrations of fluoxetine, a human medicine commonly found in freshwater systems, causes increased lifetime fitness costs, when associated with increased variability in temperature. Although fluoxetine and variability in temperature elicited some fitness cost when tested alone, when both stressors acted together the costs were disproportionally greater. The combined effect of fluoxetine and variability in temperature led to a reduction of 37% in lifetime reproductive success and a 17.9% decrease in population growth rate. Interestingly, fluoxetine and variability in temperature had no effect on the probability of survival. Freshwater systems are among the most imperilled ecosystems, often exposed to multiple human-induced stressors. Our results indicate that organisms face greater fitness risk when exposed to multiple stressors at the same time than when each stress acts alone. Our study highlights the importance of using a multi-generational approach to fully understand individual environmental tolerance and its responses to a global change scenario in aquatic systems. Copyright © 2017 Elsevier B.V. All rights reserved.

A general psychopathology factor (P factor) in children: Structural model analysis and external validation through familial risk and child global executive function.

Science.gov (United States)

Martel, Michelle M; Pan, Pedro M; Hoffmann, Maurício S; Gadelha, Ary; do Rosário, Maria C; Mari, Jair J; Manfro, Gisele G; Miguel, Eurípedes C; Paus, Tomás; Bressan, Rodrigo A; Rohde, Luis A; Salum, Giovanni A

2017-01-01

High rates of comorbidities and poor validity of disorder diagnostic criteria for mental disorders hamper advances in mental health research. Recent work has suggested the utility of continuous cross-cutting dimensions, including general psychopathology and specific factors of externalizing and internalizing (e.g., distress and fear) syndromes. The current study evaluated the reliability of competing structural models of psychopathology and examined external validity of the best fitting model on the basis of family risk and child global executive function (EF). A community sample of 8,012 families from Brazil with children ages 6-12 years completed structured interviews about the child and parental psychiatric syndromes, and a subsample of 2,395 children completed tasks assessing EF (i.e., working memory, inhibitory control, and time processing). Confirmatory factor analyses tested a series of structural models of psychopathology in both parents and children. The model with a general psychopathology factor ("P factor") with 3 specific factors (fear, distress, and externalizing) exhibited the best fit. The general P factor accounted for most of the variance in all models, with little residual variance explained by each of the 3 specific factors. In addition, associations between child and parental factors were mainly significant for the P factors and nonsignificant for the specific factors from the respective models. Likewise, the child P factor-but not the specific factors-was significantly associated with global child EF. Overall, our results provide support for a latent overarching P factor characterizing child psychopathology, supported by familial associations and child EF. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Modelling water use in global hydrological models: review, challenges and directions

Science.gov (United States)

Bierkens, M. F.; de Graaf, I.; Wada, Y.; Wanders, N.; Van Beek, L. P.

2017-12-01

During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments using regional statistics of water use and observations of meteorological and hydrological variables. Shortly thereafter, the first macroscale hydrological models (MHM) appeared. In these models, blue water (i.e., surface water and renewable groundwater) availability was calculated by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand for agriculture, industry and households. In this talk we review the evolution of human impact modelling in global land models with a focus on global water resources, touching upon developments of the last 15 years: i.e. calculating human water scarcity; estimating groundwater depletion; adding dams and reservoirs; fully integrating water use (demand, withdrawal, consumption, return flow) in the hydrology; simulating the effects of land use change. We show example studies for each of these steps. We identify We identify major challenges that hamper the further development of integrated water resources modelling. Examples of these are: 1) simulating reservoir operations; 2) including local infrastructure and redistribution; 3) using the correct allocations rules; 4) projecting future water demand and water use. For each of these challenges we signify promising directions for further research.

Sample Size and Statistical Conclusions from Tests of Fit to the Rasch Model According to the Rasch Unidimensional Measurement Model (Rumm) Program in Health Outcome Measurement.

Science.gov (United States)

Hagell, Peter; Westergren, Albert

Sample size is a major factor in statistical null hypothesis testing, which is the basis for many approaches to testing Rasch model fit. Few sample size recommendations for testing fit to the Rasch model concern the Rasch Unidimensional Measurement Models (RUMM) software, which features chi-square and ANOVA/F-ratio based fit statistics, including Bonferroni and algebraic sample size adjustments. This paper explores the occurrence of Type I errors with RUMM fit statistics, and the effects of algebraic sample size adjustments. Data with simulated Rasch model fitting 25-item dichotomous scales and sample sizes ranging from N = 50 to N = 2500 were analysed with and without algebraically adjusted sample sizes. Results suggest the occurrence of Type I errors with N less then or equal to 500, and that Bonferroni correction as well as downward algebraic sample size adjustment are useful to avoid such errors, whereas upward adjustment of smaller samples falsely signal misfit. Our observations suggest that sample sizes around N = 250 to N = 500 may provide a good balance for the statistical interpretation of the RUMM fit statistics studied here with respect to Type I errors and under the assumption of Rasch model fit within the examined frame of reference (i.e., about 25 item parameters well targeted to the sample).

pytc: Open-Source Python Software for Global Analyses of Isothermal Titration Calorimetry Data.

Science.gov (United States)

Duvvuri, Hiranmayi; Wheeler, Lucas C; Harms, Michael J

2018-05-08

Here we describe pytc, an open-source Python package for global fits of thermodynamic models to multiple isothermal titration calorimetry experiments. Key features include simplicity, the ability to implement new thermodynamic models, a robust maximum likelihood fitter, a fast Bayesian Markov-Chain Monte Carlo sampler, rigorous implementation, extensive documentation, and full cross-platform compatibility. pytc fitting can be done using an application program interface or via a graphical user interface. It is available for download at https://github.com/harmslab/pytc .

The bystander effect model of Brenner and Sachs fitted to lung cancer data in 11 cohorts of underground miners, and equivalence of fit of a linear relative risk model with adjustment for attained age and age at exposure

International Nuclear Information System (INIS)

Little, M P

2004-01-01

Bystander effects following exposure to α-particles have been observed in many experimental systems, and imply that linearly extrapolating low dose risks from high dose data might materially underestimate risk. Brenner and Sachs (2002 Int. J. Radiat. Biol. 78 593-604; 2003 Health Phys. 85 103-8) have recently proposed a model of the bystander effect which they use to explain the inverse dose rate effect observed for lung cancer in underground miners exposed to radon daughters. In this paper we fit the model of the bystander effect proposed by Brenner and Sachs to 11 cohorts of underground miners, taking account of the covariance structure of the data and the period of latency between the development of the first pre-malignant cell and clinically overt cancer. We also fitted a simple linear relative risk model, with adjustment for age at exposure and attained age. The methods that we use for fitting both models are different from those used by Brenner and Sachs, in particular taking account of the covariance structure, which they did not, and omitting certain unjustifiable adjustments to the miner data. The fit of the original model of Brenner and Sachs (with 0 y period of latency) is generally poor, although it is much improved by assuming a 5 or 6 y period of latency from the first appearance of a pre-malignant cell to cancer. The fit of this latter model is equivalent to that of a linear relative risk model with adjustment for age at exposure and attained age. In particular, both models are capable of describing the observed inverse dose rate effect in this data set

Spherical Process Models for Global Spatial Statistics

KAUST Repository

Jeong, Jaehong

2017-11-28

Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture the spatial and temporal behavior of these global data sets. Though the geodesic distance is the most natural metric for measuring distance on the surface of a sphere, mathematical limitations have compelled statisticians to use the chordal distance to compute the covariance matrix in many applications instead, which may cause physically unrealistic distortions. Therefore, covariance functions directly defined on a sphere using the geodesic distance are needed. We discuss the issues that arise when dealing with spherical data sets on a global scale and provide references to recent literature. We review the current approaches to building process models on spheres, including the differential operator, the stochastic partial differential equation, the kernel convolution, and the deformation approaches. We illustrate realizations obtained from Gaussian processes with different covariance structures and the use of isotropic and nonstationary covariance models through deformations and geographical indicators for global surface temperature data. To assess the suitability of each method, we compare their log-likelihood values and prediction scores, and we end with a discussion of related research problems.

Improved parameterization of managed grassland in a global process-based vegetation model using Bayesian statistics

Science.gov (United States)

Rolinski, S.; Müller, C.; Lotze-Campen, H.; Bondeau, A.

2010-12-01

More than a quarter of the Earth’s land surface is covered by grassland, which is also the major part (~ 70 %) of the agricultural area. Most of this area is used for livestock production in different degrees of intensity. The dynamic global vegetation model LPJmL (Sitch et al., Global Change Biology, 2003; Bondeau et al., Global Change Biology, 2007) is one of few process-based model that simulates biomass production on managed grasslands at the global scale. The implementation of managed grasslands and its evaluation has received little attention so far, as reference data on grassland productivity are scarce and the definition of grassland extent and usage are highly uncertain. However, grassland productivity is related to large areas, and strongly influences global estimates of carbon and water budgets and should thus be improved. Plants are implemented in LPJmL in an aggregated form as plant functional types assuming that processes concerning carbon and water fluxes are quite similar between species of the same type. Therefore, the parameterization of a functional type is possible with parameters in a physiologically meaningful range of values. The actual choice of the parameter values from the possible and reasonable phase space should satisfy the condition of the best fit of model results and measured data. In order to improve the parameterization of managed grass we follow a combined procedure using model output and measured data of carbon and water fluxes. By comparing carbon and water fluxes simultaneously, we expect well-balanced refinements and avoid over-tuning of the model in only one direction. The comparison of annual biomass from grassland to data from the Food and Agriculture Organization of the United Nations (FAO) per country provide an overview about the order of magnitude and the identification of deviations. The comparison of daily net primary productivity, soil respiration and water fluxes at specific sites (FluxNet Data) provides

Fitting measurement models to vocational interest data: are dominance models ideal?

Science.gov (United States)

Tay, Louis; Drasgow, Fritz; Rounds, James; Williams, Bruce A

2009-09-01

In this study, the authors examined the item response process underlying 3 vocational interest inventories: the Occupational Preference Inventory (C.-P. Deng, P. I. Armstrong, & J. Rounds, 2007), the Interest Profiler (J. Rounds, T. Smith, L. Hubert, P. Lewis, & D. Rivkin, 1999; J. Rounds, C. M. Walker, et al., 1999), and the Interest Finder (J. E. Wall & H. E. Baker, 1997; J. E. Wall, L. L. Wise, & H. E. Baker, 1996). Item response theory (IRT) dominance models, such as the 2-parameter and 3-parameter logistic models, assume that item response functions (IRFs) are monotonically increasing as the latent trait increases. In contrast, IRT ideal point models, such as the generalized graded unfolding model, have IRFs that peak where the latent trait matches the item. Ideal point models are expected to fit better because vocational interest inventories ask about typical behavior, as opposed to requiring maximal performance. Results show that across all 3 interest inventories, the ideal point model provided better descriptions of the response process. The importance of specifying the correct item response model for precise measurement is discussed. In particular, scores computed by a dominance model were shown to be sometimes illogical: individuals endorsing mostly realistic or mostly social items were given similar scores, whereas scores based on an ideal point model were sensitive to which type of items respondents endorsed.

A model for global cycling of tritium

International Nuclear Information System (INIS)

Killough, G.G.; Kocher, D.C.

1988-01-01

Dynamic compartment models are widely used to describe global cycling of radionuclides for purposes of dose estimation. In this paper the authors present a new global tritium model that reproduces environmental time-series data on concentrations in precipitation, ocean surface waters, and surface fresh waters in the northern hemisphere, concentrations of atmospheric tritium in the southern hemisphere, and the latitude dependence of tritium in both hemispheres. Names TRICYCLE (for TRItium CYCLE) the model is based on the global hydrologic cycle and includes hemispheric stratospheric compartments, disaggregation of the troposphere and ocean surface waters into eight latitude zones, consideration of the different concentrations of atmospheric tritium over land and over the ocean, and a diffusive model for transport in the ocean. TRICYCLE reproduces the environmental data if it is assumed that about 50% of the tritium from atmospheric weapons testing was injected directly into the northern stratosphere as HTO. The model's latitudinal disaggregation permits taking into account the distribution of population. For a uniformly distributed release of HTO into the worldwide troposphere, TRICYCLE predicts a collective dose commitment to the world population that exceeds the NCRP model's corresponding prediction by a factor of three

A model for global cycling of tritium

International Nuclear Information System (INIS)

Killough, G.G.; Kocher, D.C.

1988-01-01

Dynamic compartment models are widely used to describe global cycling of radionuclides for purposes of dose estimation. In this paper, we present a new global tritium model that reproduces environmental time-series data on concentrations in precipitation, ocean surface waters, and surface fresh waters in the northern hemisphere, concentrations of atmospheric tritium in the soutehrn hemisphere, and the latitude dependence of tritium in both hemispheres. Named TRICYCLE for Tritium CYCLE, the model is based on the global hydrologic cycle and includes hemisphereic stratospheric compartments, disaggregation of the troposphere and ocean surface waters into eight latitudezones, consideration of the different concentrations of atmospheric tritium over land and over the ocean, and a diffusive model for transport in the ocean. TRICYCLE reproduces the environmental data if we assume that about 50% of the tritium from atmospheric weapons testing was injected directly into the northern stratosphere as HTO. The models latitudinal disaggregation permits taking into account the distribution of population. For a unfiormaly distributed release of HTO into the worldwide troposphere, TRICYCLE predicts a collective dose commitment to the world population that exceeds the corresponding prediction by the NCRP model by about a factor of 3. 11 refs., 5 figs., 1 tab

Global modelling of Cryptosporidium in surface water

Science.gov (United States)

Vermeulen, Lucie; Hofstra, Nynke

2016-04-01

Introduction Waterborne pathogens that cause diarrhoea, such as Cryptosporidium, pose a health risk all over the world. In many regions quantitative information on pathogens in surface water is unavailable. Our main objective is to model Cryptosporidium concentrations in surface waters worldwide. We present the GloWPa-Crypto model and use the model in a scenario analysis. A first exploration of global Cryptosporidium emissions to surface waters has been published by Hofstra et al. (2013). Further work has focused on modelling emissions of Cryptosporidium and Rotavirus to surface waters from human sources (Vermeulen et al 2015, Kiulia et al 2015). A global waterborne pathogen model can provide valuable insights by (1) providing quantitative information on pathogen levels in data-sparse regions, (2) identifying pathogen hotspots, (3) enabling future projections under global change scenarios and (4) supporting decision making. Material and Methods GloWPa-Crypto runs on a monthly time step and represents conditions for approximately the year 2010. The spatial resolution is a 0.5 x 0.5 degree latitude x longitude grid for the world. We use livestock maps (http://livestock.geo-wiki.org/) combined with literature estimates to calculate spatially explicit livestock Cryptosporidium emissions. For human Cryptosporidium emissions, we use UN population estimates, the WHO/UNICEF JMP sanitation country data and literature estimates of wastewater treatment. We combine our emissions model with a river routing model and data from the VIC hydrological model (http://vic.readthedocs.org/en/master/) to calculate concentrations in surface water. Cryptosporidium survival during transport depends on UV radiation and water temperature. We explore pathogen emissions and concentrations in 2050 with the new Shared Socio-economic Pathways (SSPs) 1 and 3. These scenarios describe plausible future trends in demographics, economic development and the degree of global integration. Results and

Ozone impacts of gas-aerosol uptake in global chemistry transport models

Science.gov (United States)

Stadtler, Scarlet; Simpson, David; Schröder, Sabine; Taraborrelli, Domenico; Bott, Andreas; Schultz, Martin

2018-03-01

The impact of six heterogeneous gas-aerosol uptake reactions on tropospheric ozone and nitrogen species was studied using two chemical transport models, the Meteorological Synthesizing Centre-West of the European Monitoring and Evaluation Programme (EMEP MSC-W) and the European Centre Hamburg general circulation model combined with versions of the Hamburg Aerosol Model and Model for Ozone and Related chemical Tracers (ECHAM-HAMMOZ). Species undergoing heterogeneous reactions in both models include N2O5, NO3, NO2, O3, HNO3, and HO2. Since heterogeneous reactions take place at the aerosol surface area, the modelled surface area density (Sa) of both models was compared to a satellite product retrieving the surface area. This comparison shows a good agreement in global pattern and especially the capability of both models to capture the extreme aerosol loadings in east Asia. The impact of the heterogeneous reactions was evaluated by the simulation of a reference run containing all heterogeneous reactions and several sensitivity runs. One reaction was turned off in each sensitivity run to compare it with the reference run. The analysis of the sensitivity runs confirms that the globally most important heterogeneous reaction is the one of N2O5. Nevertheless, NO2, HNO3, and HO2 heterogeneous reactions gain relevance particularly in east Asia due to the presence of high NOx concentrations and high Sa in the same region. The heterogeneous reaction of O3 itself on dust is of minor relevance compared to the other heterogeneous reactions. The impacts of the N2O5 reactions show strong seasonal variations, with the biggest impacts on O3 in springtime when photochemical reactions are active and N2O5 levels still high. Evaluation of the models with northern hemispheric ozone surface observations yields a better agreement of the models with observations in terms of concentration levels, variability, and temporal correlations at most sites when the heterogeneous reactions are

Fitted HBT radii versus space-time variances in flow-dominated models

International Nuclear Information System (INIS)

Lisa, Mike; Frodermann, Evan; Heinz, Ulrich

2007-01-01

The inability of otherwise successful dynamical models to reproduce the 'HBT radii' extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the 'RHIC HBT Puzzle'. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source which can be directly computed from the emission function, without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models some of which exhibit significant deviations from simple Gaussian behaviour. By Fourier transforming the emission function we compute the 2-particle correlation function and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and measured HBT radii remain, we show that a more 'apples-to-apples' comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data. (author)

Groundwater development stress: Global-scale indices compared to regional modeling

Science.gov (United States)

Alley, William; Clark, Brian R.; Ely, Matt; Faunt, Claudia

2018-01-01

The increased availability of global datasets and technologies such as global hydrologic models and the Gravity Recovery and Climate Experiment (GRACE) satellites have resulted in a growing number of global-scale assessments of water availability using simple indices of water stress. Developed initially for surface water, such indices are increasingly used to evaluate global groundwater resources. We compare indices of groundwater development stress for three major agricultural areas of the United States to information available from regional water budgets developed from detailed groundwater modeling. These comparisons illustrate the potential value of regional-scale analyses to supplement global hydrological models and GRACE analyses of groundwater depletion. Regional-scale analyses allow assessments of water stress that better account for scale effects, the dynamics of groundwater flow systems, the complexities of irrigated agricultural systems, and the laws, regulations, engineering, and socioeconomic factors that govern groundwater use. Strategic use of regional-scale models with global-scale analyses would greatly enhance knowledge of the global groundwater depletion problem.

Global Multi-isotopologue fit of measured rotation and vibration-rotation line positions of CO in X1Σ+ state and new set of mass-independent Dunham coefficients

International Nuclear Information System (INIS)

Velichko, T.I.; Mikhailenko, S.N.; Tashkun, S.A.

2012-01-01

A set of mass-independent U mj and Δ mj parameters globally describing vibration-rotation energy levels of the CO molecule in the X 1 Σ + ground electronic state was fitted to more than 19,000 transitions of 12 C 16 O, 13 C 16 O, 14 C 16 O, 12 C 17 O, 13 C 17 O, 12 C 18 O, and 13 C 18 O isotopologues collected from the literature. The maximal values of the vibrational V and the rotational J quantum numbers included in the fit was 41 and 128, respectively. The weighted standard deviation of the fit is .66. Fitted parameters were used for calculation of Dunham coefficients Y mj for nine isotopologues 12 C 16 O, 13 C 16 O, 14 C 16 O, 12 C 17 O, 13 C 17 O, 14 C 17 O, 12 C 18 O, 13 C 18 O, and 14 C 18 O. Calculated transition frequencies based on the fitted parameters were compared with previously reported. A critical analysis of the CO HITRAN and HITEMP data is also presented.

The CAFE model: A net production model for global ocean phytoplankton

Science.gov (United States)

Silsbe, Greg M.; Behrenfeld, Michael J.; Halsey, Kimberly H.; Milligan, Allen J.; Westberry, Toby K.

2016-12-01

The Carbon, Absorption, and Fluorescence Euphotic-resolving (CAFE) net primary production model is an adaptable framework for advancing global ocean productivity assessments by exploiting state-of-the-art satellite ocean color analyses and addressing key physiological and ecological attributes of phytoplankton. Here we present the first implementation of the CAFE model that incorporates inherent optical properties derived from ocean color measurements into a mechanistic and accurate model of phytoplankton growth rates (μ) and net phytoplankton production (NPP). The CAFE model calculates NPP as the product of energy absorption (QPAR), and the efficiency (ϕμ) by which absorbed energy is converted into carbon biomass (CPhyto), while μ is calculated as NPP normalized to CPhyto. The CAFE model performance is evaluated alongside 21 other NPP models against a spatially robust and globally representative set of direct NPP measurements. This analysis demonstrates that the CAFE model explains the greatest amount of variance and has the lowest model bias relative to other NPP models analyzed with this data set. Global oceanic NPP from the CAFE model (52 Pg C m-2 yr-1) and mean division rates (0.34 day-1) are derived from climatological satellite data (2002-2014). This manuscript discusses and validates individual CAFE model parameters (e.g., QPAR and ϕμ), provides detailed sensitivity analyses, and compares the CAFE model results and parameterization to other widely cited models.

The global nitrogen regulator, FNR1, regulates fungal nutrition-genes and fitness during Fusarium oxysporum pathogenesis.

Science.gov (United States)

Divon, Hege Hvattum; Ziv, Carmit; Davydov, Olga; Yarden, Oded; Fluhr, Robert

2006-11-01

SUMMARY Fusarium oxysporum is a soil-borne pathogen that infects plants through the roots and uses the vascular system for host ingress. Specialized for this route of infection, F. oxysporum is able to adapt to the scarce nutrient environment in the xylem vessels. Here we report the cloning of the F. oxysporum global nitrogen regulator, Fnr1, and show that it is one of the determinants for fungal fitness during in planta growth. The Fnr1 gene has a single conserved GATA-type zinc finger domain and is 96% and 48% identical to AREA-GF from Gibberella fujikuroi, and NIT2 from Neurospora crassa, respectively. Fnr1 cDNA, expressed under a constitutive promoter, was able to complement functionally an N. crassa nit-2(RIP) mutant, restoring the ability of the mutant to utilize nitrate. Fnr1 disruption mutants showed high tolerance to chlorate and reduced ability to utilize several secondary nitrogen sources such as amino acids, hypoxanthine and uric acid, whereas growth on favourable nitrogen sources was not affected. Fnr1 disruption also abolished in vitro expression of nutrition genes, normally induced during the early phase of infection. In an infection assay on tomato seedlings, infection rate of disruption mutants was significantly delayed in comparison with the parental strain. Our results indicate that FNR1 mediates adaptation to nitrogen-poor conditions in planta through the regulation of secondary nitrogen acquisition, and as such acts as a determinant for fungal fitness during infection.

Regional forecasting with global atmospheric models

International Nuclear Information System (INIS)

Crowley, T.J.; North, G.R.; Smith, N.R.

1994-05-01

This report was prepared by the Applied Research Corporation (ARC), College Station, Texas, under subcontract to Pacific Northwest Laboratory (PNL) as part of a global climate studies task. The task supports site characterization work required for the selection of a potential high-level nuclear waste repository and is part of the Performance Assessment Scientific Support (PASS) Program at PNL. The work is under the overall direction of the Office of Civilian Radioactive Waste Management (OCRWM), US Department of Energy Headquarters, Washington, DC. The scope of the report is to present the results of the third year's work on the atmospheric modeling part of the global climate studies task. The development testing of computer models and initial results are discussed. The appendices contain several studies that provide supporting information and guidance to the modeling work and further details on computer model development. Complete documentation of the models, including user information, will be prepared under separate reports and manuals

GEM-AQ/EC, an on-line global multi-scale chemical weather modelling system: model development and evaluation of global aerosol climatology

Directory of Open Access Journals (Sweden)

S. L. Gong

2012-09-01

Full Text Available A global air quality modeling system GEM-AQ/EC was developed by implementing tropospheric chemistry and aerosol processes on-line into the Global Environmental Multiscale weather prediction model – GEM. Due to the multi-scale features of the GEM, the integrated model, GEM-AQ/EC, is able to investigate chemical weather at scales from global to urban domains. The current chemical mechanism is comprised of 50 gas-phase species, 116 chemical and 19 photolysis reactions, and is complemented by a sectional aerosol module CAM (The Canadian Aerosol Module with 5 aerosols types: sulphate, black carbon, organic carbon, sea-salt and soil dust. Monthly emission inventories of black carbon and organic carbon from boreal and temperate vegetation fires were assembled using the most reliable areas burned datasets by countries, from statistical databases and derived from remote sensing products of 1995–2004. The model was run for ten years from from 1995–2004 with re-analyzed meteorology on a global uniform 1° × 1° horizontal resolution domain and 28 hybrid levels extending up to 10 hPa. The simulating results were compared with various observations including surface network around the globe and satellite data. Regional features of global aerosols are reasonably captured including emission, surface concentrations and aerosol optical depth. For various types of aerosols, satisfactory correlations were achieved between modeled and observed with some degree of systematic bias possibly due to large uncertainties in the emissions used in this study. A global distribution of natural aerosol contributions to the total aerosols is obtained and compared with observations.

A cautionary note on the use of information fit indexes in covariance structure modeling with means

NARCIS (Netherlands)

Wicherts, J.M.; Dolan, C.V.

2004-01-01

Information fit indexes such as Akaike Information Criterion, Consistent Akaike Information Criterion, Bayesian Information Criterion, and the expected cross validation index can be valuable in assessing the relative fit of structural equation models that differ regarding restrictiveness. In cases

Assessing performance of Bayesian state-space models fit to Argos satellite telemetry locations processed with Kalman filtering.

Directory of Open Access Journals (Sweden)

Mónica A Silva

Full Text Available Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF. The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6 ± 5.6 km was nearly half that of LS estimates (11.6 ± 8.4 km. Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.

A high-resolution global-scale groundwater model

Science.gov (United States)

de Graaf, I. E. M.; Sutanudjaja, E. H.; van Beek, L. P. H.; Bierkens, M. F. P.

2015-02-01

Groundwater is the world's largest accessible source of fresh water. It plays a vital role in satisfying basic needs for drinking water, agriculture and industrial activities. During times of drought groundwater sustains baseflow to rivers and wetlands, thereby supporting ecosystems. Most global-scale hydrological models (GHMs) do not include a groundwater flow component, mainly due to lack of geohydrological data at the global scale. For the simulation of lateral flow and groundwater head dynamics, a realistic physical representation of the groundwater system is needed, especially for GHMs that run at finer resolutions. In this study we present a global-scale groundwater model (run at 6' resolution) using MODFLOW to construct an equilibrium water table at its natural state as the result of long-term climatic forcing. The used aquifer schematization and properties are based on available global data sets of lithology and transmissivities combined with the estimated thickness of an upper, unconfined aquifer. This model is forced with outputs from the land-surface PCRaster Global Water Balance (PCR-GLOBWB) model, specifically net recharge and surface water levels. A sensitivity analysis, in which the model was run with various parameter settings, showed that variation in saturated conductivity has the largest impact on the groundwater levels simulated. Validation with observed groundwater heads showed that groundwater heads are reasonably well simulated for many regions of the world, especially for sediment basins (R2 = 0.95). The simulated regional-scale groundwater patterns and flow paths demonstrate the relevance of lateral groundwater flow in GHMs. Inter-basin groundwater flows can be a significant part of a basin's water budget and help to sustain river baseflows, especially during droughts. Also, water availability of larger aquifer systems can be positively affected by additional recharge from inter-basin groundwater flows.

Development of a Sampling-Based Global Sensitivity Analysis Workflow for Multiscale Computational Cancer Models

Science.gov (United States)

Wang, Zhihui; Deisboeck, Thomas S.; Cristini, Vittorio

2014-01-01

There are two challenges that researchers face when performing global sensitivity analysis (GSA) on multiscale in silico cancer models. The first is increased computational intensity, since a multiscale cancer model generally takes longer to run than does a scale-specific model. The second problem is the lack of a best GSA method that fits all types of models, which implies that multiple methods and their sequence need to be taken into account. In this article, we therefore propose a sampling-based GSA workflow consisting of three phases – pre-analysis, analysis, and post-analysis – by integrating Monte Carlo and resampling methods with the repeated use of analysis of variance (ANOVA); we then exemplify this workflow using a two-dimensional multiscale lung cancer model. By accounting for all parameter rankings produced by multiple GSA methods, a summarized ranking is created at the end of the workflow based on the weighted mean of the rankings for each input parameter. For the cancer model investigated here, this analysis reveals that ERK, a downstream molecule of the EGFR signaling pathway, has the most important impact on regulating both the tumor volume and expansion rate in the algorithm used. PMID:25257020

Global dynamics of a dengue epidemic mathematical model

International Nuclear Information System (INIS)

Cai Liming; Guo Shumin; Li, XueZhi; Ghosh, Mini

2009-01-01

The paper investigates the global stability of a dengue epidemic model with saturation and bilinear incidence. The constant human recruitment rate and exponential natural death, as well as vector population with asymptotically constant population, are incorporated into the model. The model exhibits two equilibria, namely, the disease-free equilibrium and the endemic equilibrium. The stability of these two equilibria is controlled by the threshold number R 0 . It is shown that if R 0 is less than one, the disease-free equilibrium is globally asymptotically stable and in such a case the endemic equilibrium does not exist; if R 0 is greater than one, then the disease persists and the unique endemic equilibrium is globally asymptotically stable.

Rules, culture, and fitness.

Science.gov (United States)

Baum, W M

1995-01-01

Behavior analysis risks intellectual isolation unless it integrates its explanations with evolutionary theory. Rule-governed behavior is an example of a topic that requires an evolutionary perspective for a full understanding. A rule may be defined as a verbal discriminative stimulus produced by the behavior of a speaker under the stimulus control of a long-term contingency between the behavior and fitness. As a discriminative stimulus, the rule strengthens listener behavior that is reinforced in the short run by socially mediated contingencies, but which also enters into the long-term contingency that enhances the listener's fitness. The long-term contingency constitutes the global context for the speaker's giving the rule. When a rule is said to be "internalized," the listener's behavior has switched from short- to long-term control. The fitness-enhancing consequences of long-term contingencies are health, resources, relationships, or reproduction. This view ties rules both to evolutionary theory and to culture. Stating a rule is a cultural practice. The practice strengthens, with short-term reinforcement, behavior that usually enhances fitness in the long run. The practice evolves because of its effect on fitness. The standard definition of a rule as a verbal statement that points to a contingency fails to distinguish between a rule and a bargain ("If you'll do X, then I'll do Y"), which signifies only a single short-term contingency that provides mutual reinforcement for speaker and listener. In contrast, the giving and following of a rule ("Dress warmly; it's cold outside") can be understood only by reference also to a contingency providing long-term enhancement of the listener's fitness or the fitness of the listener's genes. Such a perspective may change the way both behavior analysts and evolutionary biologists think about rule-governed behavior.

Tree-Based Global Model Tests for Polytomous Rasch Models

Science.gov (United States)

Komboz, Basil; Strobl, Carolin; Zeileis, Achim

2018-01-01

Psychometric measurement models are only valid if measurement invariance holds between test takers of different groups. Global model tests, such as the well-established likelihood ratio (LR) test, are sensitive to violations of measurement invariance, such as differential item functioning and differential step functioning. However, these…

Impact of the heavy-quark matching scales in PDF fits

Energy Technology Data Exchange (ETDEWEB)

Bertone, V. [VU University, Department of Physics and Astronomy, Amsterdam (Netherlands); Nikhef Theory Group Science Park 105, Amsterdam (Netherlands); Britzger, D.; Geiser, A.; Glazov, A.; Zenaiev, O. [DESY, Hamburg (Germany); Camarda, S. [CERN, Geneva (Switzerland); Cooper-Sarkar, A.; Giuli, F. [University of Oxford (United Kingdom); Godat, E.; Lyonnet, F.; Olness, F. [SMU Physics, Dallas, TX (United States); Kusina, A. [Universite Grenoble Alpes, CNRS/IN2P3, Laboratoire de Physique Subatomique et de Cosmologie, Grenoble (France); Polish Academy of Sciences, Institute of Nuclear Physics, Krakow (Poland); Luszczak, A. [T. Kosciuszko Cracow University of Technology, Krakow (Poland); Placakyte, R. [Universitaet Hamburg, Institut fuer Theoretische Physik, Hamburg (Germany); Radescu, V. [DESY, Hamburg (Germany); CERN, Geneva (Switzerland); Schienbein, I. [Universite Grenoble Alpes, CNRS/IN2P3, Laboratoire de Physique Subatomique et de Cosmologie, Grenoble (France); Collaboration: The xFitter Developers' Team

2017-12-15

We investigate the impact of displaced heavy-quark matching scales in a global fit. The heavy-quark matching scale μ{sub m} determines at which energy scale μ the QCD theory transitions from N{sub F} to N{sub F} + 1 in the variable flavor number scheme (VFNS) for the evolution of the parton distribution functions (PDFs) and strong coupling α{sub S}(μ). We study the variation of the matching scales, and their impact on a global PDF fit of the combined HERA data. As the choice of the matching scale μ{sub m} effectively is a choice of scheme, this represents a theoretical uncertainty; ideally, we would like to see minimal dependence on this parameter. For the transition across the charm quark (from N{sub F} = 3 to 4), we find a large μ{sub m} = μ{sub c} dependence of the global fit χ{sup 2} at NLO, but this is significantly reduced at NNLO. For the transition across the bottom quark (from N{sub F} = 4 to 5), we have a reduced μ{sub m} = μ{sub b} dependence of the χ{sup 2} at both NLO and NNLO as compared to the charm. This feature is now implemented in xFitter 2.0.0, an open source QCD fit framework. (orig.)

A self-fitting hearing aid: need and concept.

Science.gov (United States)

Convery, Elizabeth; Keidser, Gitte; Dillon, Harvey; Hartley, Lisa

2011-12-01

The need for reliable access to hearing health care services is growing globally, particularly in developing countries and in remotely located, underserved regions in many parts of the developed world. Individuals with hearing loss in these areas are at a significant disadvantage due to the scarcity of local hearing health care professionals and the high cost of hearing aids. Current approaches to making hearing rehabilitation services more readily available to underserved populations include teleaudiology and the provision of amplification devices outside of the traditional provider-client relationship. Both strategies require access to such resources as dedicated equipment and/or specially trained staff. Another possible strategy is a self-fitting hearing aid, a personal amplification device that is equipped with an onboard tone generator to enable user-controlled, automated, in situ audiometry; an onboard prescription to determine the initial hearing aid settings; and a trainable algorithm to enable user-controlled fine-tuning. The device is thus assembled, fitted, and managed by the user without the need for audiological or computer support. This article details the self-fitting concept and its potential application in both developing and developed countries. Potential advantages and disadvantages of such a device are discussed, and considerations for further investigations into the concept are presented. Overall, the concept is considered technologically viable with the main challenges anticipated to be development of clear, simple user instructions and a delivery model that ensures reliable supplies of instant-fit ear tips and batteries.

WMAP constraints on inflationary models with global defects

International Nuclear Information System (INIS)

Bevis, Neil; Hindmarsh, Mark; Kunz, Martin

2004-01-01

We use the cosmic microwave background angular power spectra to place upper limits on the degree to which global defects may have aided cosmic structure formation. We explore this under the inflationary paradigm, but with the addition of textures resulting from the breaking of a global O(4) symmetry during the early stages of the Universe. As a measure of their contribution, we use the fraction of the temperature power spectrum that is attributed to the defects at a multipole of 10. However, we find a parameter degeneracy enabling a fit to the first-year WMAP data to be made even with a significant defect fraction. This degeneracy involves the baryon fraction and the Hubble constant, plus the normalization and tilt of the primordial power spectrum. Hence, constraints on these cosmological parameters are weakened. Combining the WMAP data with a constraint on the physical baryon fraction from big bang nucleosynthesis calculations and high-redshift deuterium abundance limits the extent of the degeneracy and gives an upper bound on the defect fraction of 0.13 (95% confidence)

Cuckoo Search with Lévy Flights for Weighted Bayesian Energy Functional Optimization in Global-Support Curve Data Fitting

Directory of Open Access Journals (Sweden)

Akemi Gálvez

2014-01-01

for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way.

Reducing uncertainty based on model fitness: Application to a ...

African Journals Online (AJOL)

A weakness of global sensitivity and uncertainty analysis methodologies is the often subjective definition of prior parameter probability distributions, especially ... The reservoir representing the central part of the wetland, where flood waters separate into several independent distributaries, is a keystone area within the model.

An Improved Cognitive Model of the Iowa and Soochow Gambling Tasks With Regard to Model Fitting Performance and Tests of Parameter Consistency

Directory of Open Access Journals (Sweden)

Junyi eDai

2015-03-01

Full Text Available The Iowa Gambling Task (IGT and the Soochow Gambling Task (SGT are two experience-based risky decision-making tasks for examining decision-making deficits in clinical populations. Several cognitive models, including the expectancy-valence learning model (EVL and the prospect valence learning model (PVL, have been developed to disentangle the motivational, cognitive, and response processes underlying the explicit choices in these tasks. The purpose of the current study was to develop an improved model that can fit empirical data better than the EVL and PVL models and, in addition, produce more consistent parameter estimates across the IGT and SGT. Twenty-six opiate users (mean age 34.23; SD 8.79 and 27 control participants (mean age 35; SD 10.44 completed both tasks. Eighteen cognitive models varying in evaluation, updating, and choice rules were fit to individual data and their performances were compared to that of a statistical baseline model to find a best fitting model. The results showed that the model combining the prospect utility function treating gains and losses separately, the decay-reinforcement updating rule, and the trial-independent choice rule performed the best in both tasks. Furthermore, the winning model produced more consistent individual parameter estimates across the two tasks than any of the other models.

An Instructional Development Model for Global Organizations: The GOaL Model.

Science.gov (United States)

Hara, Noriko; Schwen, Thomas M.

1999-01-01

Presents an instructional development model, GOaL (Global Organization Localization), for use by global organizations. Topics include gaps in language, culture, and needs; decentralized processes; collaborative efforts; predetermined content; multiple perspectives; needs negotiation; learning within context; just-in-time training; and bilingual…

Spatiotemporal models of global soil organic carbon stock to support land degradation assessments at regional and global scales: limitations, challenges and opportunities

Science.gov (United States)

Hengl, Tomislav; Heuvelink, Gerard; Sanderman, Jonathan; MacMillan, Robert

2017-04-01

There is an increasing interest in fitting and applying spatiotemporal models that can be used to assess and monitor soil organic carbon stocks (SOCS), for example, in support of the '4 pourmille' initiative aiming at soil carbon sequestration towards climate change adaptation and mitigation and UN's Land Degradation Neutrality indicators and similar degradation assessment projects at regional and global scales. The land cover mapping community has already produced several spatiotemporal data sets with global coverage and at relatively fine resolution e.g. USGS MODIS land cover annual maps for period 2000-2014; European Space Agency land cover maps at 300 m resolution for the year 2000, 2005 and 2010; Chinese GlobeLand30 dataset available for years 2000 and 2010; Columbia University's WRI GlobalForestWatch with deforestation maps at 30 m resolution for the period 2000-2016 (Hansen et al. 2013). These data sets can be used for land degradation assessment and scenario testing at global and regional scales (Wei et al 2014). Currently, however, no compatible global spatiotemporal data sets exist on status of soil quality and/or soil health (Powlson et al. 2013). This paper describes an initial effort to devise and evaluate a procedure for mapping spatio-temporal changes in SOC stocks using a complete stack of soil forming factors (climate, relief, land cover, land use, lithology and living organisms) represented mainly through remote sensing based time series of Earth images. For model building we used some 75,000 geo-referenced soil profiles and a stacks space-time covariates (land cover, land use, biomass, climate) at two standard resolutions: (1) 10 km resolution with data available for period 1920-2014 and (2) 1000 m resolution with data available for period 2000-2014. The initial results show that, although it is technically feasible to produce space time estimates of SOCS that demonstrate the procedure, the estimates are relatively uncertain (<45% of variation

Qualitative models of global warming amplifiers

NARCIS (Netherlands)

Milošević, U.; Bredeweg, B.; de Kleer, J.; Forbus, K.D.

2010-01-01

There is growing interest from ecological experts to create qualitative models of phenomena for which numerical information is sparse or missing. We present a number of successful models in the field of environmental science, namely, the domain of global warming. The motivation behind the effort is

Global dynamics of a dengue epidemic mathematical model

Energy Technology Data Exchange (ETDEWEB)

Cai Liming [Department of Mathematics, Xinyang Normal University, Xinyang 464000 (China); Academy of Mathematics and Systems Science, Academia Sinica, Beijing 100080 (China)], E-mail: lmcai06@yahoo.com.cn; Guo Shumin [Beijing Institute of Information Control, Beijing 100037 (China); Li, XueZhi [Department of Mathematics, Xinyang Normal University, Xinyang 464000 (China); Ghosh, Mini [School of Mathematics and Computer Application, Thapar University, Patiala 147004 (India)

2009-11-30

The paper investigates the global stability of a dengue epidemic model with saturation and bilinear incidence. The constant human recruitment rate and exponential natural death, as well as vector population with asymptotically constant population, are incorporated into the model. The model exhibits two equilibria, namely, the disease-free equilibrium and the endemic equilibrium. The stability of these two equilibria is controlled by the threshold number R{sub 0}. It is shown that if R{sub 0} is less than one, the disease-free equilibrium is globally asymptotically stable and in such a case the endemic equilibrium does not exist; if R{sub 0} is greater than one, then the disease persists and the unique endemic equilibrium is globally asymptotically stable.

Regional forecasting with global atmospheric models

International Nuclear Information System (INIS)

Crowley, T.J.; North, G.R.; Smith, N.R.

1994-05-01

The scope of the report is to present the results of the fourth year's work on the atmospheric modeling part of the global climate studies task. The development testing of computer models and initial results are discussed. The appendices contain studies that provide supporting information and guidance to the modeling work and further details on computer model development. Complete documentation of the models, including user information, will be prepared under separate reports and manuals

A global treatment of VMD physics up to the φ: II. τ decay and hadronic contributions to g-2

International Nuclear Information System (INIS)

Benayoun, M.; David, P.; DelBuono, L.; Leitner, O.

2010-01-01

Relying on the Hidden Local Symmetry (HLS) model equipped with a mechanism breaking the U(3)/SU(3)/SU(2) symmetries and generating a dynamical vector meson mixing, it has been shown that a global fit successfully describes the cross sections for the e + e - →π + π - , e + e - →(π 0 /η)γ and e + e - →π 0 π + π - annihilation channels. One extends this global fit in order to include also the dipion spectra from the τ decay, taking into account all reported information on their statistical and systematic errors. A model accounting for lineshape distortions of the ρ ± spectrum relative to ρ 0 is also examined when analyzing the τ data behavior within the global fit framework. One shows that a successful account for e + e - annihilation data and τ spectra can be simultaneously reached. Then, issues related with non-perturbative hadronic contributions to the muon g-2 are examined in details. It is shown that all e + e - data considered together allow for improved and motivated estimates for the a μ (π + π - ), the π + π - loop contribution to the muon g-2; for instance, integrated between 0.630 and 0.958 GeV, we find a μ (π + π - )=359.62 ±1.62 (in units of 10 -10 ), a 40% improvement of the current uncertainty. The effects of the various τ samples in the context of a global fit procedure leads to conclude that different lineshape distortions are revealed by the ALEPH, BELLE and CLEO data samples. Relying on global fits to the data quoted above, one also provides motivated estimates of the π + π - , π 0 γ, η γ and π 0 π + π - contributions to a μ up to 1 GeV with the smallest possible uncertainties. These estimates are based on various global fit configurations, each yielding a good probability. (orig.)

Principle component analysis (PCA) and second-order global hard-modelling for the complete resolution of transition metal ions complex formation with 1,10-phenantroline

International Nuclear Information System (INIS)

Shariati-Rad, Masoud; Hasani, Masoumeh

2009-01-01

Second-order global hard-modelling was applied to resolve the complex formation between Co 2+ , Ni 2+ , and Cd 2+ cations and 1,10-phenantroline. The highly correlated spectral and concentration profiles of the species in these systems and low concentration of some species in the individual collected data matrices prevent the well-resolution of the profiles. Therefore, a collection of six equilibrium data matrices including series of absorption spectra taken with pH changes at different reactant ratios were analyzed. Firstly, a precise principle component analysis (PCA) of different augmented arrangements of the individual data matrices was used to distinguish the number of species involved in the equilibria. Based on the results of PCA, the equilibria included in the data were specified and second-order global hard-modelling of the appropriate arrangement of six collected equilibrium data matrices resulted in well-resolved profiles and equilibrium constants. The protonation constant of the ligand (1,10-phenantroline) and spectral profiles of its protonated and unprotonated forms are the additional information obtained by global analysis. For comparison, multivariate curve resolution-alternating least squares (MCR-ALS) was applied to the same data. The results showed that second-order global hard-modelling is more convenient compared with MCR-ALS especially for systems with completely known model. It can completely resolve the system and the concentration profiles which are closer to correct ones. Moreover, parameters showing the goodness of fit are better with second-order global hard-modelling.

Principle component analysis (PCA) and second-order global hard-modelling for the complete resolution of transition metal ions complex formation with 1,10-phenantroline

Energy Technology Data Exchange (ETDEWEB)

Shariati-Rad, Masoud [Faculty of Chemistry, Bu-Ali Sina University, Hamedan 65174 (Iran, Islamic Republic of); Hasani, Masoumeh, E-mail: hasani@basu.ac.ir [Faculty of Chemistry, Bu-Ali Sina University, Hamedan 65174 (Iran, Islamic Republic of)

2009-08-19

Second-order global hard-modelling was applied to resolve the complex formation between Co{sup 2+}, Ni{sup 2+}, and Cd{sup 2+} cations and 1,10-phenantroline. The highly correlated spectral and concentration profiles of the species in these systems and low concentration of some species in the individual collected data matrices prevent the well-resolution of the profiles. Therefore, a collection of six equilibrium data matrices including series of absorption spectra taken with pH changes at different reactant ratios were analyzed. Firstly, a precise principle component analysis (PCA) of different augmented arrangements of the individual data matrices was used to distinguish the number of species involved in the equilibria. Based on the results of PCA, the equilibria included in the data were specified and second-order global hard-modelling of the appropriate arrangement of six collected equilibrium data matrices resulted in well-resolved profiles and equilibrium constants. The protonation constant of the ligand (1,10-phenantroline) and spectral profiles of its protonated and unprotonated forms are the additional information obtained by global analysis. For comparison, multivariate curve resolution-alternating least squares (MCR-ALS) was applied to the same data. The results showed that second-order global hard-modelling is more convenient compared with MCR-ALS especially for systems with completely known model. It can completely resolve the system and the concentration profiles which are closer to correct ones. Moreover, parameters showing the goodness of fit are better with second-order global hard-modelling.

Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes

Science.gov (United States)

Leite, Walter L.; Stapleton, Laura M.

2011-01-01

In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…

Fitting the Fractional Polynomial Model to Non-Gaussian Longitudinal Data

Directory of Open Access Journals (Sweden)

Ji Hoon Ryoo

2017-08-01

Full Text Available As in cross sectional studies, longitudinal studies involve non-Gaussian data such as binomial, Poisson, gamma, and inverse-Gaussian distributions, and multivariate exponential families. A number of statistical tools have thus been developed to deal with non-Gaussian longitudinal data, including analytic techniques to estimate parameters in both fixed and random effects models. However, as yet growth modeling with non-Gaussian data is somewhat limited when considering the transformed expectation of the response via a linear predictor as a functional form of explanatory variables. In this study, we introduce a fractional polynomial model (FPM that can be applied to model non-linear growth with non-Gaussian longitudinal data and demonstrate its use by fitting two empirical binary and count data models. The results clearly show the efficiency and flexibility of the FPM for such applications.

Tanning Shade Gradations of Models in Mainstream Fitness and Muscle Enthusiast Magazines: Implications for Skin Cancer Prevention in Men.

Science.gov (United States)

Basch, Corey H; Hillyer, Grace Clarke; Ethan, Danna; Berdnik, Alyssa; Basch, Charles E

2015-07-01

Tanned skin has been associated with perceptions of fitness and social desirability. Portrayal of models in magazines may reflect and perpetuate these perceptions. Limited research has investigated tanning shade gradations of models in men's versus women's fitness and muscle enthusiast magazines. Such findings are relevant in light of increased incidence and prevalence of melanoma in the United States. This study evaluated and compared tanning shade gradations of adult Caucasian male and female model images in mainstream fitness and muscle enthusiast magazines. Sixty-nine U.S. magazine issues (spring and summer, 2013) were utilized. Two independent reviewers rated tanning shade gradations of adult Caucasian male and female model images on magazines' covers, advertisements, and feature articles. Shade gradations were assessed using stock photographs of Caucasian models with varying levels of tanned skin on an 8-shade scale. A total of 4,683 images were evaluated. Darkest tanning shades were found among males in muscle enthusiast magazines and lightest among females in women's mainstream fitness magazines. By gender, male model images were 54% more likely to portray a darker tanning shade. In this study, images in men's (vs. women's) fitness and muscle enthusiast magazines portrayed Caucasian models with darker skin shades. Despite these magazines' fitness-related messages, pro-tanning images may promote attitudes and behaviors associated with higher skin cancer risk. To date, this is the first study to explore tanning shades in men's magazines of these genres. Further research is necessary to identify effects of exposure to these images among male readers. © The Author(s) 2014.

Source Localization with Acoustic Sensor Arrays Using Generative Model Based Fitting with Sparse Constraints

Directory of Open Access Journals (Sweden)

Javier Macias-Guarasa

2012-10-01

Full Text Available This paper presents a novel approach for indoor acoustic source localization using sensor arrays. The proposed solution starts by defining a generative model, designed to explain the acoustic power maps obtained by Steered Response Power (SRP strategies. An optimization approach is then proposed to fit the model to real input SRP data and estimate the position of the acoustic source. Adequately fitting the model to real SRP data, where noise and other unmodelled effects distort the ideal signal, is the core contribution of the paper. Two basic strategies in the optimization are proposed. First, sparse constraints in the parameters of the model are included, enforcing the number of simultaneous active sources to be limited. Second, subspace analysis is used to filter out portions of the input signal that cannot be explained by the model. Experimental results on a realistic speech database show statistically significant localization error reductions of up to 30% when compared with the SRP-PHAT strategies.

An approximation to the adaptive exponential integrate-and-fire neuron model allows fast and predictive fitting to physiological data

Directory of Open Access Journals (Sweden)

Loreen eHertäg

2012-09-01

Full Text Available For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f-I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron's response under a wide range of mean input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f-I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating ('in-vivo-like' input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model's generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a 'high-throughput' model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available.

[Human-robot global Simulink modeling and analysis for an end-effector upper limb rehabilitation robot].

Science.gov (United States)

Liu, Yali; Ji, Linhong

2018-02-01

Robot rehabilitation has been a primary therapy method for the urgent rehabilitation demands of paralyzed patients after a stroke. The parameters in rehabilitation training such as the range of the training, which should be adjustable according to each participant's functional ability, are the key factors influencing the effectiveness of rehabilitation therapy. Therapists design rehabilitation projects based on the semiquantitative functional assessment scales and their experience. But these therapies based on therapists' experience cannot be implemented in robot rehabilitation therapy. This paper modeled the global human-robot by Simulink in order to analyze the relationship between the parameters in robot rehabilitation therapy and the patients' movement functional abilities. We compared the shoulder and elbow angles calculated by simulation with the angles recorded by motion capture system while the healthy subjects completed the simulated action. Results showed there was a remarkable correlation between the simulation data and the experiment data, which verified the validity of the human-robot global Simulink model. Besides, the relationship between the circle radius in the drawing tasks in robot rehabilitation training and the active movement degrees of shoulder as well as elbow was also matched by a linear, which also had a remarkable fitting coefficient. The matched linear can be a quantitative reference for the robot rehabilitation training parameters.

The Global Flood Model

Science.gov (United States)

Williams, P.; Huddelston, M.; Michel, G.; Thompson, S.; Heynert, K.; Pickering, C.; Abbott Donnelly, I.; Fewtrell, T.; Galy, H.; Sperna Weiland, F.; Winsemius, H.; Weerts, A.; Nixon, S.; Davies, P.; Schiferli, D.

2012-04-01

Recently, a Global Flood Model (GFM) initiative has been proposed by Willis, UK Met Office, Esri, Deltares and IBM. The idea is to create a global community platform that enables better understanding of the complexities of flood risk assessment to better support the decisions, education and communication needed to mitigate flood risk. The GFM will provide tools for assessing the risk of floods, for devising mitigation strategies such as land-use changes and infrastructure improvements, and for enabling effective pre- and post-flood event response. The GFM combines humanitarian and commercial motives. It will benefit: - The public, seeking to preserve personal safety and property; - State and local governments, seeking to safeguard economic activity, and improve resilience; - NGOs, similarly seeking to respond proactively to flood events; - The insurance sector, seeking to understand and price flood risk; - Large corporations, seeking to protect global operations and supply chains. The GFM is an integrated and transparent set of modules, each composed of models and data. For each module, there are two core elements: a live "reference version" (a worked example) and a framework of specifications, which will allow development of alternative versions. In the future, users will be able to work with the reference version or substitute their own models and data. If these meet the specification for the relevant module, they will interoperate with the rest of the GFM. Some "crowd-sourced" modules could even be accredited and published to the wider GFM community. Our intent is to build on existing public, private and academic work, improve local adoption, and stimulate the development of multiple - but compatible - alternatives, so strengthening mankind's ability to manage flood impacts. The GFM is being developed and managed by a non-profit organization created for the purpose. The business model will be inspired from open source software (eg Linux): - for non-profit usage

Global distribution of urban parameters derived from high-resolution global datasets for weather modelling

Science.gov (United States)

Kawano, N.; Varquez, A. C. G.; Dong, Y.; Kanda, M.

2016-12-01

Numerical model such as Weather Research and Forecasting model coupled with single-layer Urban Canopy Model (WRF-UCM) is one of the powerful tools to investigate urban heat island. Urban parameters such as average building height (Have), plain area index (λp) and frontal area index (λf), are necessary inputs for the model. In general, these parameters are uniformly assumed in WRF-UCM but this leads to unrealistic urban representation. Distributed urban parameters can also be incorporated into WRF-UCM to consider a detail urban effect. The problem is that distributed building information is not readily available for most megacities especially in developing countries. Furthermore, acquiring real building parameters often require huge amount of time and money. In this study, we investigated the potential of using globally available satellite-captured datasets for the estimation of the parameters, Have, λp, and λf. Global datasets comprised of high spatial resolution population dataset (LandScan by Oak Ridge National Laboratory), nighttime lights (NOAA), and vegetation fraction (NASA). True samples of Have, λp, and λf were acquired from actual building footprints from satellite images and 3D building database of Tokyo, New York, Paris, Melbourne, Istanbul, Jakarta and so on. Regression equations were then derived from the block-averaging of spatial pairs of real parameters and global datasets. Results show that two regression curves to estimate Have and λf from the combination of population and nightlight are necessary depending on the city's level of development. An index which can be used to decide which equation to use for a city is the Gross Domestic Product (GDP). On the other hand, λphas less dependence on GDP but indicated a negative relationship to vegetation fraction. Finally, a simplified but precise approximation of urban parameters through readily-available, high-resolution global datasets and our derived regressions can be utilized to estimate a

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DEFF Research Database (Denmark)

Ding, Tao; Li, Cheng; Huang, Can

2018-01-01

–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost......In order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master...... optimality. Numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods....

Technology Learning Ratios in Global Energy Models; Ratios de Aprendizaje Tecnologico en Modelos Energeticos Globales

Energy Technology Data Exchange (ETDEWEB)

Varela, M.

2001-07-01

The process of introduction of a new technology supposes that while its production and utilisation increases, also its operation improves and its investment costs and production decreases. The accumulation of experience and learning of a new technology increase in parallel with the increase of its market share. This process is represented by the technological learning curves and the energy sector is not detached from this process of substitution of old technologies by new ones. The present paper carries out a brief revision of the main energy models that include the technology dynamics (learning). The energy scenarios, developed by global energy models, assume that the characteristics of the technologies are variables with time. But this tend is incorporated in a exogenous way in these energy models, that is to say, it is only a time function. This practice is applied to the cost indicators of the technology such as the specific investment costs or to the efficiency of the energy technologies. In the last years, the new concept of endogenous technological learning has been integrated within these global energy models. This paper examines the concept of technological learning in global energy models. It also analyses the technological dynamics of the energy systems including the endogenous modelling of the process of technological progress. Finally, it makes a comparison of several of the most used global energy models (MARKAL, MESSAGE and ERIS) and, more concretely, about the use these models make of the concept of technological learning. (Author) 17 refs.

Global Modeling Study of the Bioavailable Atmospheric Iron Supply to the Global Ocean

Science.gov (United States)

Myriokefalitakis, S.; Krol, M. C.; van Noije, T.; Le Sager, P.

2017-12-01

Atmospheric deposition of trace constituents acts as a nutrient source to the open ocean and affect marine ecosystem. Dust is known as a major source of nutrients to the global ocean, but only a fraction of these nutrients is released in a bioavailable form that can be assimilated by the marine biota. Iron (Fe) is a key micronutrient that significantly modulates gross primary production in the High-Nutrient-Low-Chlorophyll (HNLC) oceans, where macronutrients like nitrate are abundant, but primary production is limited by Fe scarcity. The global atmospheric Fe cycle is here parameterized in the state-of-the-art global Earth System Model EC-Earth. The model takes into account the primary emissions of both insoluble and soluble Fe forms, associated with mineral dust and combustion aerosols. The impact of atmospheric acidity and organic ligands on mineral dissolution processes, is parameterized based on updated experimental and theoretical findings. Model results are also evaluated against available observations. Overall, the link between the labile Fe atmospheric deposition and atmospheric composition changes is here demonstrated and quantified. This work has been financed by the Marie-Curie H2020-MSCA-IF-2015 grant (ID 705652) ODEON (Online DEposition over OceaNs; modeling the effect of air pollution on ocean bio-geochemistry in an Earth System Model).

Modeling global distribution of agricultural insecticides in surface waters

International Nuclear Information System (INIS)

Ippolito, Alessio; Kattwinkel, Mira; Rasmussen, Jes J.; Schäfer, Ralf B.; Fornaroli, Riccardo; Liess, Matthias

2015-01-01

Agricultural insecticides constitute a major driver of animal biodiversity loss in freshwater ecosystems. However, the global extent of their effects and the spatial extent of exposure remain largely unknown. We applied a spatially explicit model to estimate the potential for agricultural insecticide runoff into streams. Water bodies within 40% of the global land surface were at risk of insecticide runoff. We separated the influence of natural factors and variables under human control determining insecticide runoff. In the northern hemisphere, insecticide runoff presented a latitudinal gradient mainly driven by insecticide application rate; in the southern hemisphere, a combination of daily rainfall intensity, terrain slope, agricultural intensity and insecticide application rate determined the process. The model predicted the upper limit of observed insecticide exposure measured in water bodies (n = 82) in five different countries reasonably well. The study provides a global map of hotspots for insecticide contamination guiding future freshwater management and conservation efforts. - Highlights: • First global map on insecticide runoff through modelling. • Model predicts upper limit of insecticide exposure when compared to field data. • Water bodies in 40% of global land surface may be at risk of adverse effects. • Insecticide application rate, terrain slope and rainfall main drivers of exposure. - We provide the first global map on insecticide runoff to surface water predicting that water bodies in 40% of global land surface may be at risk of adverse effects

A Data-Driven Method for Selecting Optimal Models Based on Graphical Visualisation of Differences in Sequentially Fitted ROC Model Parameters

Directory of Open Access Journals (Sweden)

K S Mwitondi

2013-05-01

Full Text Available Differences in modelling techniques and model performance assessments typically impinge on the quality of knowledge extraction from data. We propose an algorithm for determining optimal patterns in data by separately training and testing three decision tree models in the Pima Indians Diabetes and the Bupa Liver Disorders datasets. Model performance is assessed using ROC curves and the Youden Index. Moving differences between sequential fitted parameters are then extracted, and their respective probability density estimations are used to track their variability using an iterative graphical data visualisation technique developed for this purpose. Our results show that the proposed strategy separates the groups more robustly than the plain ROC/Youden approach, eliminates obscurity, and minimizes over-fitting. Further, the algorithm can easily be understood by non-specialists and demonstrates multi-disciplinary compliance.

Global and Regional Ecosystem Modeling: Databases of Model Drivers and Validation Measurements

Energy Technology Data Exchange (ETDEWEB)

Olson, R.J.

2002-03-19

Understanding global-scale ecosystem responses to changing environmental conditions is important both as a scientific question and as the basis for making policy decisions. The confidence in regional models depends on how well the field data used to develop the model represent the region of interest, how well the environmental model driving variables (e.g., vegetation type, climate, and soils associated with a site used to parameterize ecosystem models) represent the region of interest, and how well regional model predictions agree with observed data for the region. To assess the accuracy of global model forecasts of terrestrial carbon cycling, two Ecosystem Model-Data Intercomparison (EMDI) workshops were held (December 1999 and April 2001). The workshops included 17 biogeochemical, satellite-driven, detailed process, and dynamic vegetation global model types. The approach was to run regional or global versions of the models for sites with net primary productivity (NPP) measurements (i.e., not fine-tuned for specific site conditions) and analyze the model-data differences. Extensive worldwide NPP data were assembled with model driver data, including vegetation, climate, and soils data, to perform the intercomparison. This report describes the compilation of NPP estimates for 2,523 sites and 5,164 0.5{sup o}-grid cells under the Global Primary Production Data Initiative (GPPDI) and the results of the EMDI review and outlier analysis that produced a refined set of NPP estimates and model driver data. The EMDI process resulted in 81 Class A sites, 933 Class B sites, and 3,855 Class C cells derived from the original synthesis of NPP measurements and associated driver data. Class A sites represent well-documented study sites that have complete aboveground and below ground NPP measurements. Class B sites represent more numerous ''extensive'' sites with less documentation and site-specific information available. Class C cells represent estimates of

Association of Physical Fitness With Fibromyalgia Severity in Women

DEFF Research Database (Denmark)

Soriano-Maldonado, Alberto; Henriksen, Marius; Segura-Jiménez, Víctor

2015-01-01

OBJECTIVES: To assess the association between physical fitness and fibromyalgia (FM) severity in women with FM as well as to assess whether different fitness components present an independent relation with FM severity. DESIGN: Population-based cross-sectional study. SETTING: University facilities...... and FM associations. PARTICIPANTS: Women with FM (N=444). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: FM severity was assessed with the Revised Fibromyalgia Impact Questionnaire (FIQR). Aerobic fitness (6-min walk test), muscle strength (handgrip, chair stand, and arm curl tests), flexibility...... (chair sit and reach and back scratch tests), and motor agility (8 foot Up and Go test) were measured with the Senior Fitness Test battery and digital dynamometry. A standardized composite score (hereafter "global fitness profile") was calculated and divided into quintiles. RESULTS: Overall, physical...

Fast fitting of non-Gaussian state-space models to animal movement data via Template Model Builder

DEFF Research Database (Denmark)

Albertsen, Christoffer Moesgaard; Whoriskey, Kim; Yurkowski, David

2015-01-01

recommend using the Laplace approximation combined with automatic differentiation (as implemented in the novel R package Template Model Builder; TMB) for the fast fitting of continuous-time multivariate non-Gaussian SSMs. Through Argos satellite tracking data, we demonstrate that the use of continuous...... are able to estimate additional parameters compared to previous methods, all without requiring a substantial increase in computational time. The model implementation is made available through the R package argosTrack....

Log-normal frailty models fitted as Poisson generalized linear mixed models.

Science.gov (United States)

Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver

2016-12-01

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Spherical Process Models for Global Spatial Statistics

KAUST Repository

Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.

2017-01-01

Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture

Smartphone Applications for Patients' Health and Fitness.

Science.gov (United States)

Higgins, John P

2016-01-01

Healthcare providers are often looking for ways to objectively monitor and improve their patients' health and fitness, especially in between patient visits. Some insurance companies are using applications data as incentives to improve health and lower premiums. As more and more people start to use smartphones, they may provide a tool to help improve a patient's health and fitness. Specifically, fitness applications or "apps" on smartphones are programs that use data collected from a smartphone's inbuilt tools, such as the Global Positioning System, accelerometer, microphone, speaker, and camera, to measure health and fitness parameters. The apps then analyze these data and summarize them, as well as devise individualized plans based on users' goals, provide frequent feedback, personalized coaching, and additional motivation by allowing milestones to be shared on social media. This article introduces evidence that apps can better help patients reach their health and fitness goals. It then discusses what features to look for in an app, followed by an overview of popular health and fitness apps. Last, patient scenarios with app recommendations, limitations of apps, and future research are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

A coupled chemotaxis-fluid model: Global existence

KAUST Repository

Liu, Jian-Guo; Lorz, Alexander

2011-01-01

We consider a model arising from biology, consisting of chemotaxis equations coupled to viscous incompressible fluid equations through transport and external forcing. Global existence of solutions to the Cauchy problem is investigated under certain conditions. Precisely, for the chemotaxis-Navier- Stokes system in two space dimensions, we obtain global existence for large data. In three space dimensions, we prove global existence of weak solutions for the chemotaxis-Stokes system with nonlinear diffusion for the cell density.© 2011 Elsevier Masson SAS. All rights reserved.

A coupled chemotaxis-fluid model: Global existence

KAUST Repository

Liu, Jian-Guo

2011-09-01

We consider a model arising from biology, consisting of chemotaxis equations coupled to viscous incompressible fluid equations through transport and external forcing. Global existence of solutions to the Cauchy problem is investigated under certain conditions. Precisely, for the chemotaxis-Navier- Stokes system in two space dimensions, we obtain global existence for large data. In three space dimensions, we prove global existence of weak solutions for the chemotaxis-Stokes system with nonlinear diffusion for the cell density.© 2011 Elsevier Masson SAS. All rights reserved.

Multiple organ definition in CT using a Bayesian approach for 3D model fitting

Science.gov (United States)

Boes, Jennifer L.; Weymouth, Terry E.; Meyer, Charles R.

1995-08-01

Organ definition in computed tomography (CT) is of interest for treatment planning and response monitoring. We present a method for organ definition using a priori information about shape encoded in a set of biometric organ models--specifically for the liver and kidney-- that accurately represents patient population shape information. Each model is generated by averaging surfaces from a learning set of organ shapes previously registered into a standard space defined by a small set of landmarks. The model is placed in a specific patient's data set by identifying these landmarks and using them as the basis for model deformation; this preliminary representation is then iteratively fit to the patient's data based on a Bayesian formulation of the model's priors and CT edge information, yielding a complete organ surface. We demonstrate this technique using a set of fifteen abdominal CT data sets for liver surface definition both before and after the addition of a kidney model to the fitting; we demonstrate the effectiveness of this tool for organ surface definition in this low-contrast domain.

Multi-scale climate modelling over Southern Africa using a variable-resolution global model

CSIR Research Space (South Africa)

Engelbrecht, FA

2011-12-01

Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

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

Institute of Scientific and Technical Information of China (English)

Hua CHEN; Han-Qin TIAN

2005-01-01

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

Global Carbon-and-Conservation Models, Global Eco-States? Ecuador’s Yasuní-ITT Initiative and Governance Implications

Directory of Open Access Journals (Sweden)

Conny Davidsen

2013-05-01

Full Text Available The “global carbon age” marks a structural change far beyond the economic realms of implementing carbon trade, affecting the fabric of global environmental governance and its actors. Carbon trade and conservation in the Global South have taken on various forms, and climate change mitigation efforts in light of continued rainforest deforestation are scrambling to establish effective approaches. Ecuador’s Yasuní-ITT Initiative proposes a new global carbon-and-conservation model in the Ecuadorian Amazon that leaves oil reserves of the Yasuní Ishpingo Tambococha Tiputini (ITT oil fields underground, in exchange for international compensation payments that would be based on voluntary contributions of governments and nongovernmental actors in an international conservation partnership and trust fund under the auspices of the United Nations Development Programme. This model suggests far-reaching consequences, as it introduces new global scales for the sharing and management of environmental costs within a framework of neoliberal cost internalization. The analysis in this paper uses the concept of the “ecological state” (Duit, 2008 as a theoretical point of departure to examine the trans-scalar implications of such a carbon-and-conservation model on global governance structures toward a “global ecological state” (or global eco-state.

The 'fitting problem' in cosmology

International Nuclear Information System (INIS)

Ellis, G.F.R.; Stoeger, W.

1987-01-01

The paper considers the best way to fit an idealised exactly homogeneous and isotropic universe model to a realistic ('lumpy') universe; whether made explicit or not, some such approach of necessity underlies the use of the standard Robertson-Walker models as models of the real universe. Approaches based on averaging, normal coordinates and null data are presented, the latter offering the best opportunity to relate the fitting procedure to data obtainable by astronomical observations. (author)

A fitting LEGACY – modelling Kepler's best stars

Directory of Open Access Journals (Sweden)

Aarslev Magnus J.

2017-01-01

Full Text Available The LEGACY sample represents the best solar-like stars observed in the Kepler mission[5, 8]. The 66 stars in the sample are all on the main sequence or only slightly more evolved. They each have more than one year's observation data in short cadence, allowing for precise extraction of individual frequencies. Here we present model fits using a modified ASTFIT procedure employing two different near-surface-effect corrections, one by Christensen-Dalsgaard[4] and a newer correction proposed by Ball & Gizon[1]. We then compare the results obtained using the different corrections. We find that using the latter correction yields lower masses and significantly lower χ2 values for a large part of the sample.

A global renewable energy system: A modelling exercise in ETSAP/TIAM

DEFF Research Database (Denmark)

Føyn, Tullik Helene Ystanes; Karlsson, Kenneth Bernard; Balyk, Olexandr

2011-01-01

This paper aims to test the ETSAP2-TIAM global energy system model and to try out how far it can go towards a global 100% renewable energy system with the existing model database. This will show where limits in global resources are met and where limits in the data fed to the model until now are met...

UK energy policy ambition and UK energy modelling-fit for purpose?

International Nuclear Information System (INIS)

Strachan, Neil

2011-01-01

Aiming to lead amongst other G20 countries, the UK government has classified the twin energy policy priorities of decarbonisation and security of supply as a 'centennial challenge'. This viewpoint discusses the UK's capacity for energy modelling and scenario building as a critical underpinning of iterative decision making to meet these policy ambitions. From a nadir, over the last decade UK modelling expertise has been steadily built up. However extreme challenges remain in the level and consistency of funding of core model teams - critical to ensure a full scope of energy model types and hence insights, and in developing new state-of-the-art models to address evolving uncertainties. Meeting this challenge will facilitate a broad scope of types and geographical scale of UK's analytical tools to responsively deliver the evidence base for a range of public and private sector decision makers, and ensure that the UK contributes to global efforts to advance the field of energy-economic modelling. - Research highlights: → Energy modelling capacity is a critical underpinning for iterative energy policy making. → Full scope of energy models and analytical approaches is required. → Extreme challenges remain in consistent and sustainable funding of energy modelling teams. → National governments that lead in global energy policy also need to invest in modelling capacity.

Fitting the CDO correlation skew: a tractable structural jump-diffusion model

DEFF Research Database (Denmark)

Willemann, Søren

2007-01-01

We extend a well-known structural jump-diffusion model for credit risk to handle both correlations through diffusion of asset values and common jumps in asset value. Through a simplifying assumption on the default timing and efficient numerical techniques, we develop a semi-analytic framework...... allowing for instantaneous calibration to heterogeneous CDS curves and fast computation of CDO tranche spreads. We calibrate the model to CDX and iTraxx data from February 2007 and achieve a satisfactory fit. To price the senior tranches for both indices, we require a risk-neutral probability of a market...

A fuzzy regression with support vector machine approach to the estimation of horizontal global solar radiation

International Nuclear Information System (INIS)

Baser, Furkan; Demirhan, Haydar

2017-01-01

Accurate estimation of the amount of horizontal global solar radiation for a particular field is an important input for decision processes in solar radiation investments. In this article, we focus on the estimation of yearly mean daily horizontal global solar radiation by using an approach that utilizes fuzzy regression functions with support vector machine (FRF-SVM). This approach is not seriously affected by outlier observations and does not suffer from the over-fitting problem. To demonstrate the utility of the FRF-SVM approach in the estimation of horizontal global solar radiation, we conduct an empirical study over a dataset collected in Turkey and applied the FRF-SVM approach with several kernel functions. Then, we compare the estimation accuracy of the FRF-SVM approach to an adaptive neuro-fuzzy system and a coplot supported-genetic programming approach. We observe that the FRF-SVM approach with a Gaussian kernel function is not affected by both outliers and over-fitting problem and gives the most accurate estimates of horizontal global solar radiation among the applied approaches. Consequently, the use of hybrid fuzzy functions and support vector machine approaches is found beneficial in long-term forecasting of horizontal global solar radiation over a region with complex climatic and terrestrial characteristics. - Highlights: • A fuzzy regression functions with support vector machines approach is proposed. • The approach is robust against outlier observations and over-fitting problem. • Estimation accuracy of the model is superior to several existent alternatives. • A new solar radiation estimation model is proposed for the region of Turkey. • The model is useful under complex terrestrial and climatic conditions.

Development and design of a late-model fitness test instrument based on LabView

Science.gov (United States)

Xie, Ying; Wu, Feiqing

2010-12-01