Identifying mechanical property parameters of planetary soil using in-situ data obtained from exploration rovers

NASA Astrophysics Data System (ADS)

Ding, Liang; Gao, Haibo; Liu, Zhen; Deng, Zongquan; Liu, Guangjun

2015-12-01

Identifying the mechanical property parameters of planetary soil based on terramechanics models using in-situ data obtained from autonomous planetary exploration rovers is both an important scientific goal and essential for control strategy optimization and high-fidelity simulations of rovers. However, identifying all the terrain parameters is a challenging task because of the nonlinear and coupling nature of the involved functions. Three parameter identification methods are presented in this paper to serve different purposes based on an improved terramechanics model that takes into account the effects of slip, wheel lugs, etc. Parameter sensitivity and coupling of the equations are analyzed, and the parameters are grouped according to their sensitivity to the normal force, resistance moment and drawbar pull. An iterative identification method using the original integral model is developed first. In order to realize real-time identification, the model is then simplified by linearizing the normal and shearing stresses to derive decoupled closed-form analytical equations. Each equation contains one or two groups of soil parameters, making step-by-step identification of all the unknowns feasible. Experiments were performed using six different types of single-wheels as well as a four-wheeled rover moving on planetary soil simulant. All the unknown model parameters were identified using the measured data and compared with the values obtained by conventional experiments. It is verified that the proposed iterative identification method provides improved accuracy, making it suitable for scientific studies of soil properties, whereas the step-by-step identification methods based on simplified models require less calculation time, making them more suitable for real-time applications. The models have less than 10% margin of error comparing with the measured results when predicting the interaction forces and moments using the corresponding identified parameters.

MXLKID: a maximum likelihood parameter identifier. [In LRLTRAN for CDC 7600

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

Gavel, D.T.

MXLKID (MaXimum LiKelihood IDentifier) is a computer program designed to identify unknown parameters in a nonlinear dynamic system. Using noisy measurement data from the system, the maximum likelihood identifier computes a likelihood function (LF). Identification of system parameters is accomplished by maximizing the LF with respect to the parameters. The main body of this report briefly summarizes the maximum likelihood technique and gives instructions and examples for running the MXLKID program. MXLKID is implemented LRLTRAN on the CDC7600 computer at LLNL. A detailed mathematical description of the algorithm is given in the appendices. 24 figures, 6 tables.

Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems.

PubMed

Pant, Sanjay

2018-05-01

A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.

The structure of binding curves and practical identifiability of equilibrium ligand-binding parameters

PubMed Central

Middendorf, Thomas R.

2017-01-01

A critical but often overlooked question in the study of ligands binding to proteins is whether the parameters obtained from analyzing binding data are practically identifiable (PI), i.e., whether the estimates obtained from fitting models to noisy data are accurate and unique. Here we report a general approach to assess and understand binding parameter identifiability, which provides a toolkit to assist experimentalists in the design of binding studies and in the analysis of binding data. The partial fraction (PF) expansion technique is used to decompose binding curves for proteins with n ligand-binding sites exactly and uniquely into n components, each of which has the form of a one-site binding curve. The association constants of the PF component curves, being the roots of an n-th order polynomial, may be real or complex. We demonstrate a fundamental connection between binding parameter identifiability and the nature of these one-site association constants: all binding parameters are identifiable if the constants are all real and distinct; otherwise, at least some of the parameters are not identifiable. The theory is used to construct identifiability maps from which the practical identifiability of binding parameters for any two-, three-, or four-site binding curve can be assessed. Instructions for extending the method to generate identifiability maps for proteins with more than four binding sites are also given. Further analysis of the identifiability maps leads to the simple rule that the maximum number of structurally identifiable binding parameters (shown in the previous paper to be equal to n) will also be PI only if the binding curve line shape contains n resolved components. PMID:27993951

Identifying tectonic parameters that influence tsunamigenesis

NASA Astrophysics Data System (ADS)

van Zelst, Iris; Brizzi, Silvia; van Dinther, Ylona; Heuret, Arnauld; Funiciello, Francesca

2017-04-01

The role of tectonics in tsunami generation is at present poorly understood. However, the fact that some regions produce more tsunamis than others indicates that tectonics could influence tsunamigenesis. Here, we complement a global earthquake database that contains geometrical, mechanical, and seismicity parameters of subduction zones with tsunami data. We statistically analyse the database to identify the tectonic parameters that affect tsunamigenesis. The Pearson's product-moment correlation coefficients reveal high positive correlations of 0.65 between, amongst others, the maximum water height of tsunamis and the seismic coupling in a subduction zone. However, these correlations are mainly caused by outliers. The Spearman's rank correlation coefficient results in more robust correlations of 0.60 between the number of tsunamis in a subduction zone and subduction velocity (positive correlation) and the sediment thickness at the trench (negative correlation). Interestingly, there is a positive correlation between the latter and tsunami magnitude. In an effort towards multivariate statistics, a binary decision tree analysis is conducted with one variable. However, this shows that the amount of data is too scarce. To complement this limited amount of data and to assess physical causality of the tectonic parameters with regard to tsunamigenesis, we conduct a numerical study of the most promising parameters using a geodynamic seismic cycle model. We show that an increase in sediment thickness on the subducting plate results in a shift in seismic activity from outerrise normal faults to splay faults. We also show that the splay fault is the preferred rupture path for a strongly velocity strengthening friction regime in the shallow part of the subduction zone, which increases the tsunamigenic potential. A larger updip limit of the seismogenic zone results in larger vertical surface displacement.

Iterative Importance Sampling Algorithms for Parameter Estimation

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

Grout, Ray W; Morzfeld, Matthias; Day, Marcus S.

In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect scaling with the number of cores on high performance computing systems because samples are drawn independently. However, finding a suitable proposal distribution is a challenging task. Several sampling algorithms have been proposed over the past years that take an iterative approach to constructing a proposal distribution. We investigate the applicabilitymore » of such algorithms by applying them to two realistic and challenging test problems, one in subsurface flow, and one in combustion modeling. More specifically, we implement importance sampling algorithms that iterate over the mean and covariance matrix of Gaussian or multivariate t-proposal distributions. Our implementation leverages massively parallel computers, and we present strategies to initialize the iterations using 'coarse' MCMC runs or Gaussian mixture models.« less

Selection Effects in Identifying Magnetic Clouds and the Importance of the Closest Approach Parameter

NASA Technical Reports Server (NTRS)

Lepping, R. P.; Wu, Chin-Chun

2010-01-01

This study is motivated by the unusually low number of magnetic clouds (MCs) that are strictly identified within interplanetary coronal mass ejections (ICMEs), as observed at 1 AU; this is usually estimated to be around 30% or lower. But a looser definition of MCs may significantly increase this percentage. Another motivation is the unexpected shape of the occurrence distribution of the observers' "closest approach distances" (measured from a MC's axis, and called CA) which drops off somewhat rapidly as |CA| (in % of MC radius) approaches 100%, based on earlier studies. We suggest, for various geometrical and physical reasons, that the |CA|-distribution should be somewhere between a uniform one and the one actually observed, and therefore the 30% estimate should be higher. So we ask, When there is a failure to identify a MC within an ICME, is it occasionally due to a large |CA| passage, making MC identification more difficult, i.e., is it due to an event selection effect? In attempting to answer this question we examine WIND data to obtain an accurate distribution of the number of MCs vs. |CA| distance, whether the event is ICME-related or not, where initially a large number of cases (N=98) are considered. This gives a frequence distribution that is far from uniform, confirming earlier studies. This along with the fact that there are many ICME identification-parameters that do not depend on |CA| suggest that, indeed an MC event selection effect may explain at least part of the low ratio of (No. MCs)/(No. ICMEs). We also show that there is an acceptable geometrical and physical consistency in the relationships for both average "normalized" magnetic field intensity change and field direction change vs. |CA| within a MC, suggesting that our estimates of |CA|, B(sub 0) (magnetic field intensity on the axis), and choice of a proper "cloud coordinate" system (all needed in the analysis) are acceptably accurate. Therefore the MC fitting model (Lepping et al., 1990) is

Comment on “Two statistics for evaluating parameter identifiability and error reduction” by John Doherty and Randall J. Hunt

USGS Publications Warehouse

Hill, Mary C.

2010-01-01

Doherty and Hunt (2009) present important ideas for first-order-second moment sensitivity analysis, but five issues are discussed in this comment. First, considering the composite-scaled sensitivity (CSS) jointly with parameter correlation coefficients (PCC) in a CSS/PCC analysis addresses the difficulties with CSS mentioned in the introduction. Second, their new parameter identifiability statistic actually is likely to do a poor job of parameter identifiability in common situations. The statistic instead performs the very useful role of showing how model parameters are included in the estimated singular value decomposition (SVD) parameters. Its close relation to CSS is shown. Third, the idea from p. 125 that a suitable truncation point for SVD parameters can be identified using the prediction variance is challenged using results from Moore and Doherty (2005). Fourth, the relative error reduction statistic of Doherty and Hunt is shown to belong to an emerging set of statistics here named perturbed calculated variance statistics. Finally, the perturbed calculated variance statistics OPR and PPR mentioned on p. 121 are shown to explicitly include the parameter null-space component of uncertainty. Indeed, OPR and PPR results that account for null-space uncertainty have appeared in the literature since 2000.

On the identifiability of inertia parameters of planar Multi-Body Space Systems

NASA Astrophysics Data System (ADS)

Nabavi-Chashmi, Seyed Yaser; Malaek, Seyed Mohammad-Bagher

2018-04-01

This work describes a new formulation to study the identifiability characteristics of Serially Linked Multi-body Space Systems (SLMBSS). The process exploits the so called "Lagrange Formulation" to develop a linear form of Equations of Motion w.r.t the system Inertia Parameters (IPs). Having developed a specific form of regressor matrix, we aim to expedite the identification process. The new approach allows analytical as well as numerical identification and identifiability analysis for different SLMBSSs' configurations. Moreover, the explicit forms of SLMBSSs identifiable parameters are derived by analyzing the identifiability characteristics of the robot. We further show that any SLMBSS designed with Variable Configurations Joint allows all IPs to be identifiable through comparing two successive identification outcomes. This feature paves the way to design new class of SLMBSS for which accurate identification of all IPs is at hand. Different case studies reveal that proposed formulation provides fast and accurate results, as required by the space applications. Further studies might be necessary for cases where planar-body assumption becomes inaccurate.

On Finding and Using Identifiable Parameter Combinations in Nonlinear Dynamic Systems Biology Models and COMBOS: A Novel Web Implementation

PubMed Central

DiStefano, Joseph

2014-01-01

Parameter identifiability problems can plague biomodelers when they reach the quantification stage of development, even for relatively simple models. Structural identifiability (SI) is the primary question, usually understood as knowing which of P unknown biomodel parameters p 1,…, pi,…, pP are-and which are not-quantifiable in principle from particular input-output (I-O) biodata. It is not widely appreciated that the same database also can provide quantitative information about the structurally unidentifiable (not quantifiable) subset, in the form of explicit algebraic relationships among unidentifiable pi. Importantly, this is a first step toward finding what else is needed to quantify particular unidentifiable parameters of interest from new I–O experiments. We further develop, implement and exemplify novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE) systems biology models, as a user-friendly and universally-accessible web application (app)–COMBOS. Users provide the structural ODE and output measurement models in one of two standard forms to a remote server via their web browser. COMBOS provides a list of uniquely and non-uniquely SI model parameters, and–importantly-the combinations of parameters not individually SI. If non-uniquely SI, it also provides the maximum number of different solutions, with important practical implications. The behind-the-scenes symbolic differential algebra algorithms are based on computing Gröbner bases of model attributes established after some algebraic transformations, using the computer-algebra system Maxima. COMBOS was developed for facile instructional and research use as well as modeling. We use it in the classroom to illustrate SI analysis; and have simplified complex models of tumor suppressor p53 and hormone regulation, based on explicit computation of parameter combinations. It’s illustrated and validated here for models of moderate complexity

Important observations and parameters for a salt water intrusion model

USGS Publications Warehouse

Shoemaker, W.B.

2004-01-01

Sensitivity analysis with a density-dependent ground water flow simulator can provide insight and understanding of salt water intrusion calibration problems far beyond what is possible through intuitive analysis alone. Five simple experimental simulations presented here demonstrate this point. Results show that dispersivity is a very important parameter for reproducing a steady-state distribution of hydraulic head, salinity, and flow in the transition zone between fresh water and salt water in a coastal aquifer system. When estimating dispersivity, the following conclusions can be drawn about the data types and locations considered. (1) The "toe" of the transition zone is the most effective location for hydraulic head and salinity observations. (2) Areas near the coastline where submarine ground water discharge occurs are the most effective locations for flow observations. (3) Salinity observations are more effective than hydraulic head observations. (4) The importance of flow observations aligned perpendicular to the shoreline varies dramatically depending on distance seaward from the shoreline. Extreme parameter correlation can prohibit unique estimation of permeability parameters such as hydraulic conductivity and flow parameters such as recharge in a density-dependent ground water flow model when using hydraulic head and salinity observations. Adding flow observations perpendicular to the shoreline in areas where ground water is exchanged with the ocean body can reduce the correlation, potentially resulting in unique estimates of these parameter values. Results are expected to be directly applicable to many complex situations, and have implications for model development whether or not formal optimization methods are used in model calibration.

Important observations and parameters for a salt water intrusion model.

PubMed

Shoemaker, W Barclay

2004-01-01

Sensitivity analysis with a density-dependent ground water flow simulator can provide insight and understanding of salt water intrusion calibration problems far beyond what is possible through intuitive analysis alone. Five simple experimental simulations presented here demonstrate this point. Results show that dispersivity is a very important parameter for reproducing a steady-state distribution of hydraulic head, salinity, and flow in the transition zone between fresh water and salt water in a coastal aquifer system. When estimating dispersivity, the following conclusions can be drawn about the data types and locations considered. (1) The "toe" of the transition zone is the most effective location for hydraulic head and salinity observations. (2) Areas near the coastline where submarine ground water discharge occurs are the most effective locations for flow observations. (3) Salinity observations are more effective than hydraulic head observations. (4) The importance of flow observations aligned perpendicular to the shoreline varies dramatically depending on distance seaward from the shoreline. Extreme parameter correlation can prohibit unique estimation of permeability parameters such as hydraulic conductivity and flow parameters such as recharge in a density-dependent ground water flow model when using hydraulic head and salinity observations. Adding flow observations perpendicular to the shoreline in areas where ground water is exchanged with the ocean body can reduce the correlation, potentially resulting in unique estimates of these parameter values. Results are expected to be directly applicable to many complex situations, and have implications for model development whether or not formal optimization methods are used in model calibration.

Simulation of the right-angle car collision based on identified parameters

NASA Astrophysics Data System (ADS)

Kostek, R.; Aleksandrowicz, P.

2017-10-01

This article presents an influence of contact parameters on the collision pattern of vehicles. In this case a crash of two Fiat Cinquecentos with perpendicular median planes was simulated. The first vehicle was driven with a speed 50 km/h and crashed into the other one, standing still. It is a typical collision at junctions. For the first simulation, the default parameters of the V-SIM simulation program were assumed and then the parameters identified from the crash test of a Fiat Cinquecento, published by ADAC (Allgemeiner Deutscher Automobil-Club) were used. Various post-impact movements were observed for both simulations, which demonstrates a sensitivity of the simulation results to the assumed parameters. Applying the default parameters offered by the program can lead to inadequate evaluation of the collision part due to its only approximate reconstruction, which in consequence, influences the court decision. It was demonstrated how complex it is to reconstruct the pattern of the vehicles’ crash and what problems are faced by expert witnesses who tend to use default parameters.

On-orbit identifying the inertia parameters of space robotic systems using simple equivalent dynamics

NASA Astrophysics Data System (ADS)

Xu, Wenfu; Hu, Zhonghua; Zhang, Yu; Liang, Bin

2017-03-01

After being launched into space to perform some tasks, the inertia parameters of a space robotic system may change due to fuel consumption, hardware reconfiguration, target capturing, and so on. For precision control and simulation, it is required to identify these parameters on orbit. This paper proposes an effective method for identifying the complete inertia parameters (including the mass, inertia tensor and center of mass position) of a space robotic system. The key to the method is to identify two types of simple dynamics systems: equivalent single-body and two-body systems. For the former, all of the joints are locked into a designed configuration and the thrusters are used for orbital maneuvering. The object function for optimization is defined in terms of acceleration and velocity of the equivalent single body. For the latter, only one joint is unlocked and driven to move along a planned (exiting) trajectory in free-floating mode. The object function is defined based on the linear and angular momentum equations. Then, the parameter identification problems are transformed into non-linear optimization problems. The Particle Swarm Optimization (PSO) algorithm is applied to determine the optimal parameters, i.e. the complete dynamic parameters of the two equivalent systems. By sequentially unlocking the 1st to nth joints (or unlocking the nth to 1st joints), the mass properties of body 0 to n (or n to 0) are completely identified. For the proposed method, only simple dynamics equations are needed for identification. The excitation motion (orbit maneuvering and joint motion) is also easily realized. Moreover, the method does not require prior knowledge of the mass properties of any body. It is general and practical for identifying a space robotic system on-orbit.

Finding identifiable parameter combinations in nonlinear ODE models and the rational reparameterization of their input-output equations.

PubMed

Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J

2011-09-01

When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.

A modified Leslie-Gower predator-prey interaction model and parameter identifiability

NASA Astrophysics Data System (ADS)

Tripathi, Jai Prakash; Meghwani, Suraj S.; Thakur, Manoj; Abbas, Syed

2018-01-01

In this work, bifurcation and a systematic approach for estimation of identifiable parameters of a modified Leslie-Gower predator-prey system with Crowley-Martin functional response and prey refuge is discussed. Global asymptotic stability is discussed by applying fluctuation lemma. The system undergoes into Hopf bifurcation with respect to parameters intrinsic growth rate of predators (s) and prey reserve (m). The stability of Hopf bifurcation is also discussed by calculating Lyapunov number. The sensitivity analysis of the considered model system with respect to all variables is performed which also supports our theoretical study. To estimate the unknown parameter from the data, an optimization procedure (pseudo-random search algorithm) is adopted. System responses and phase plots for estimated parameters are also compared with true noise free data. It is found that the system dynamics with true set of parametric values is similar to the estimated parametric values. Numerical simulations are presented to substantiate the analytical findings.

Identifying marine Important Bird Areas using at-sea survey data

USGS Publications Warehouse

Smith, Melanie A.; Walker, Nathan J.; Free, Christopher M.; Kirchhoff, Matthew J.; Drew, Gary S.; Warnock, Nils; Stenhouse, Iain J.

2014-01-01

Effective marine bird conservation requires identification of at-sea locations used by populations for foraging, staging, and migration. Using an extensive database of at-sea survey data spanning over 30 years, we developed a standardized and data-driven spatial method for identifying globally significant marine Important Bird Areas in Alaska. To delineate these areas we developed a six-step process: binning data and accounting for unequal survey effort, filtering input data for persistence of species use, using a moving window analysis to produce maps representing a gradient from low to high abundance, drawing core area boundaries around major concentrations based on abundance thresholds, validating the results, and combining overlapping boundaries into important areas for multiple species. We identified 126 bird core areas which were merged into 59 pelagic sites important to 45 out of 57 species assessed. The final areas included approximately 34–38% of all marine birds in Alaska waters, within just 6% of the total area. We identified globally significant Important Bird Areas spanning 20 degrees of latitude and 56 degrees of longitude, in two different oceans, with climates ranging from temperate to polar. Although our maps did suffer from some data gaps, these gaps did not preclude us from identifying sites that incorporated 13% of the assessed continental waterbird population and 9% of the assessed global seabird population. The application of this technique over a large and productive region worked well for a wide range of birds, exhibiting a variety of foraging strategies and occupying a variety of ecosystem types.

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

DOE PAGES

Dai, Heng; Ye, Ming; Walker, Anthony P.; ...

2017-03-28

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

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

Dai, Heng; Ye, Ming; Walker, Anthony P.

A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods withmore » variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Identifying sensitive ranges in global warming precipitation change dependence on convective parameters

DOE PAGES

Bernstein, Diana N.; Neelin, J. David

2016-04-28

A branch-run perturbed-physics ensemble in the Community Earth System Model estimates impacts of parameters in the deep convection scheme on current hydroclimate and on end-of-century precipitation change projections under global warming. Regional precipitation change patterns prove highly sensitive to these parameters, especially in the tropics with local changes exceeding 3mm/d, comparable to the magnitude of the predicted change and to differences in global warming predictions among the Coupled Model Intercomparison Project phase 5 models. This sensitivity is distributed nonlinearly across the feasible parameter range, notably in the low-entrainment range of the parameter for turbulent entrainment in the deep convection scheme.more » This suggests that a useful target for parameter sensitivity studies is to identify such disproportionately sensitive dangerous ranges. Here, the low-entrainment range is used to illustrate the reduction in global warming regional precipitation sensitivity that could occur if this dangerous range can be excluded based on evidence from current climate.« less

Identifying sensitive ranges in global warming precipitation change dependence on convective parameters

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

Bernstein, Diana N.; Neelin, J. David

A branch-run perturbed-physics ensemble in the Community Earth System Model estimates impacts of parameters in the deep convection scheme on current hydroclimate and on end-of-century precipitation change projections under global warming. Regional precipitation change patterns prove highly sensitive to these parameters, especially in the tropics with local changes exceeding 3mm/d, comparable to the magnitude of the predicted change and to differences in global warming predictions among the Coupled Model Intercomparison Project phase 5 models. This sensitivity is distributed nonlinearly across the feasible parameter range, notably in the low-entrainment range of the parameter for turbulent entrainment in the deep convection scheme.more » This suggests that a useful target for parameter sensitivity studies is to identify such disproportionately sensitive dangerous ranges. Here, the low-entrainment range is used to illustrate the reduction in global warming regional precipitation sensitivity that could occur if this dangerous range can be excluded based on evidence from current climate.« less

Morphological Features and Important Parameters of Large Optic Discs for Diagnosing Glaucoma

PubMed Central

Okimoto, Satoshi; Yamashita, Keiko; Shibata, Tetsuo; Kiuchi, Yoshiaki

2015-01-01

Purpose To compare the optic disc parameters of glaucomatous eyes to those of non-glaucomatous eyes with large discs. Methods We studied 225 consecutive eyes with large optic discs (>2.82 mm2): 91 eyes with glaucoma and 134 eyes without glaucoma. An eye was diagnosed with glaucoma when visual field defects were detected by the Humphrey Field Analyzer. All of the Heidelberg Retina Tomograph II (HRT II) parameters were compared between the non-glaucomatous and glaucomatous eyes. A logistic regression analysis of the HRT II parameters was used to establish a new formula for diagnosing glaucoma, and the sensitivity and specificity of the Moorfields Regression Analysis (MRA) was compared to the findings made by our analyses. Results The mean disc area was 3.44±0.50 mm2 in the non-glaucomatous group and 3.40±0.52 mm2 in the glaucoma group. The cup area, cup volume, cup-to-disc area ratio, linear cup/disc ratio, mean cup depth, and the maximum cup depth were significantly larger in glaucomatous eyes than in the non-glaucomatous eyes. The rim area, rim volume, cup shape measurement, mean retinal nerve fiber layer (RNFL) thickness, and RFNL cross-sectional area were significantly smaller in glaucomatous eyes than in non-glaucomatous eyes. The cup-to-disc area ratio, the height variation contour (HVC), and the RNFL cross-sectional area were important parameters for diagnosing the early stage glaucoma, and the cup-to-disc area ratio and cup volume were useful for diagnosing advanced stage glaucoma in eyes with a large optic disc. The new formula had higher sensitivity and specificity for diagnosing glaucoma than MRA. Conclusions The cup-to-disc area ratio, HVC, RNFL cross-sectional area, and cup volume were important parameters for diagnosing glaucoma in eyes with a large optic disc. The important disc parameters to diagnose glaucoma depend on the stage of glaucoma in patients with large discs. PMID:25798580

A new process sensitivity index to identify important system processes under process model and parametric uncertainty

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

Dai, Heng; Ye, Ming; Walker, Anthony P.

Hydrological models are always composed of multiple components that represent processes key to intended model applications. When a process can be simulated by multiple conceptual-mathematical models (process models), model uncertainty in representing the process arises. While global sensitivity analysis methods have been widely used for identifying important processes in hydrologic modeling, the existing methods consider only parametric uncertainty but ignore the model uncertainty for process representation. To address this problem, this study develops a new method to probe multimodel process sensitivity by integrating the model averaging methods into the framework of variance-based global sensitivity analysis, given that the model averagingmore » methods quantify both parametric and model uncertainty. A new process sensitivity index is derived as a metric of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and model parameters. For demonstration, the new index is used to evaluate the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that converting precipitation to recharge, and the geology process is also simulated by two models of different parameterizations of hydraulic conductivity; each process model has its own random parameters. The new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.« less

Identification of Important Parameter from Leachate Solid Waste Landfill on Water Quality, Case Study of Pesanggrahan River

NASA Astrophysics Data System (ADS)

Yanidar, R.; Hartono, D. M.; Moersidik, S. S.

2018-03-01

Cipayung Landfill takes waste generation from Depok City approximately ± 750 tons/day of solid waste. The south and west boundaries of the landfill is Pesanggarahan River which 200m faraway. The objectives of this study are to indicate an important parameter which greatly affects the water quality of Pesanggrahan River and purpose the dynamic model for improving our understanding of the dynamic behavior that captures the interactions and feedbacks important parameter in river in order to identify and assess the effects of the treated leachate from final solid waste disposal activity as it responds to changes over time in the river. The high concentrations of BOD and COD are not the only cause significantly affect the quality of the pesanggrahan water, it also because the river has been contaminated in the upstream area. It need the water quality model to support the effectiveness calculation of activities for preventing a selected the pollutant sources the model should be developed for simulating and predicting the trend of water quality performance in Pesanggrahan River which can potentially be used by policy makers in strategic management to sustain river water quality as raw drinking water.

Parameter sensitivity and identifiability for a biogeochemical model of hypoxia in the northern Gulf of Mexico

EPA Science Inventory

Local sensitivity analyses and identifiable parameter subsets were used to describe numerical constraints of a hypoxia model for bottom waters of the northern Gulf of Mexico. The sensitivity of state variables differed considerably with parameter changes, although most variables ...

Identifying important nodes by adaptive LeaderRank

NASA Astrophysics Data System (ADS)

Xu, Shuang; Wang, Pei

2017-03-01

Spreading process is a common phenomenon in complex networks. Identifying important nodes in complex networks is of great significance in real-world applications. Based on the spreading process on networks, a lot of measures have been proposed to evaluate the importance of nodes. However, most of the existing measures are appropriate to static networks, which are fragile to topological perturbations. Many real-world complex networks are dynamic rather than static, meaning that the nodes and edges of such networks may change with time, which challenge numerous existing centrality measures. Based on a new weighted mechanism and the newly proposed H-index and LeaderRank (LR), this paper introduces a variant of the LR measure, called adaptive LeaderRank (ALR), which is a new member of the LR-family. Simulations on six real-world networks reveal that the new measure can well balance between prediction accuracy and robustness. More interestingly, the new measure can better adapt to the adjustment or local perturbations of network topologies, as compared with the existing measures. By discussing the detailed properties of the measures from the LR-family, we illustrate that the ALR has its competitive advantages over the other measures. The proposed algorithm enriches the measures to understand complex networks, and may have potential applications in social networks and biological systems.

Normalized sensitivities and parameter identifiability of in situ diffusion experiments on Callovo Oxfordian clay at Bure site

NASA Astrophysics Data System (ADS)

Samper, J.; Dewonck, S.; Zheng, L.; Yang, Q.; Naves, A.

Diffusion of inert and reactive tracers (DIR) is an experimental program performed by ANDRA at Bure underground research laboratory in Meuse/Haute Marne (France) to characterize diffusion and retention of radionuclides in Callovo-Oxfordian (C-Ox) argillite. In situ diffusion experiments were performed in vertical boreholes to determine diffusion and retention parameters of selected radionuclides. C-Ox clay exhibits a mild diffusion anisotropy due to stratification. Interpretation of in situ diffusion experiments is complicated by several non-ideal effects caused by the presence of a sintered filter, a gap between the filter and borehole wall and an excavation disturbed zone (EdZ). The relevance of such non-ideal effects and their impact on estimated clay parameters have been evaluated with numerical sensitivity analyses and synthetic experiments having similar parameters and geometric characteristics as real DIR experiments. Normalized dimensionless sensitivities of tracer concentrations at the test interval have been computed numerically. Tracer concentrations are found to be sensitive to all key parameters. Sensitivities are tracer dependent and vary with time. These sensitivities are useful to identify which are the parameters that can be estimated with less uncertainty and find the times at which tracer concentrations begin to be sensitive to each parameter. Synthetic experiments generated with prescribed known parameters have been interpreted automatically with INVERSE-CORE 2D and used to evaluate the relevance of non-ideal effects and ascertain parameter identifiability in the presence of random measurement errors. Identifiability analysis of synthetic experiments reveals that data noise makes difficult the estimation of clay parameters. Parameters of clay and EdZ cannot be estimated simultaneously from noisy data. Models without an EdZ fail to reproduce synthetic data. Proper interpretation of in situ diffusion experiments requires accounting for filter, gap

Parameter and observation importance in modelling virus transport in saturated porous media - Investigations in a homogenous system

USGS Publications Warehouse

Barth, Gilbert R.; Hill, M.C.

2005-01-01

This paper evaluates the importance of seven types of parameters to virus transport: hydraulic conductivity, porosity, dispersivity, sorption rate and distribution coefficient (representing physical-chemical filtration), and in-solution and adsorbed inactivation (representing virus inactivation). The first three parameters relate to subsurface transport in general while the last four, the sorption rate, distribution coefficient, and in-solution and adsorbed inactivation rates, represent the interaction of viruses with the porous medium and their ability to persist. The importance of four types of observations to estimate the virus-transport parameters are evaluated: hydraulic heads, flow, temporal moments of conservative-transport concentrations, and virus concentrations. The evaluations are conducted using one- and two-dimensional homogeneous simulations, designed from published field experiments, and recently developed sensitivity-analysis methods. Sensitivity to the transport-simulation time-step size is used to evaluate the importance of numerical solution difficulties. Results suggest that hydraulic conductivity, porosity, and sorption are most important to virus-transport predictions. Most observation types provide substantial information about hydraulic conductivity and porosity; only virus-concentration observations provide information about sorption and inactivation. The observations are not sufficient to estimate these important parameters uniquely. Even with all observation types, there is extreme parameter correlation between porosity and hydraulic conductivity and between the sorption rate and in-solution inactivation. Parameter estimation was accomplished by fixing values of porosity and in-solution inactivation.

Genes Important for Schizosaccharomyces pombe Meiosis Identified Through a Functional Genomics Screen

PubMed Central

Blyth, Julie; Makrantoni, Vasso; Barton, Rachael E.; Spanos, Christos; Rappsilber, Juri; Marston, Adele L.

2018-01-01

Meiosis is a specialized cell division that generates gametes, such as eggs and sperm. Errors in meiosis result in miscarriages and are the leading cause of birth defects; however, the molecular origins of these defects remain unknown. Studies in model organisms are beginning to identify the genes and pathways important for meiosis, but the parts list is still poorly defined. Here we present a comprehensive catalog of genes important for meiosis in the fission yeast, Schizosaccharomyces pombe. Our genome-wide functional screen surveyed all nonessential genes for roles in chromosome segregation and spore formation. Novel genes important at distinct stages of the meiotic chromosome segregation and differentiation program were identified. Preliminary characterization implicated three of these genes in centrosome/spindle pole body, centromere, and cohesion function. Our findings represent a near-complete parts list of genes important for meiosis in fission yeast, providing a valuable resource to advance our molecular understanding of meiosis. PMID:29259000

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

PubMed

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

2011-10-01

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

Pneumophonic coordination impairments in parkinsonian dysarthria: importance of aerodynamic parameters measurements.

PubMed

Moustapha, S M; Alain, G; Robert, E; Bernard, T; Mourtalla, Kâ M; Lamine, G; François, V

2012-01-01

Among Parkinsonian axial signs, dysarthria represents an important disabling symptom able to lead towards a significant reduction of oral communication. Several methods of dysarthria assessment have been used but aerodynamic evaluation is rare in the literature. To highlight the importance of aerodynamic parameters measurements in assessment of parkinsonian dysarthria. Using a dedicated system (EVA2), 24 parkinsonian patients were recorded after withdrawal of L-dopa for at least 12 h (condition called OFF DOPA) in order to evaluate intra-oral pressure (IOP), mean oral air flow (MOAF) and laryngeal resistance (LR) on six /p/ during realization of the sentence "Papa ne m'a pas parle' de beau-papa" ("Daddy did not speak to me about daddy-in-law") which corresponds to a breath group. 50 control subjects were recorded in parallel in order to define reference measurements. It appeared that there is in Parkinson's disease aerodynamic impairments which were evidenced by the fall in IOP and that of MOAF in patients compared with control subjects. The difference between the two groups was statistically significant. In addition a greater instability of LR in patients compared with control subjects was also noted. Our results show that measurements of aerodynamics parameters, by reflecting the dysfunction induced by disease, may well be relevant factors in parkinsonian dysarthria evaluation.

Identifiability of sorption parameters in stirred flow-through reactor experiments and their identification with a Bayesian approach.

PubMed

Nicoulaud-Gouin, V; Garcia-Sanchez, L; Giacalone, M; Attard, J C; Martin-Garin, A; Bois, F Y

2016-10-01

This paper addresses the methodological conditions -particularly experimental design and statistical inference- ensuring the identifiability of sorption parameters from breakthrough curves measured during stirred flow-through reactor experiments also known as continuous flow stirred-tank reactor (CSTR) experiments. The equilibrium-kinetic (EK) sorption model was selected as nonequilibrium parameterization embedding the K d approach. Parameter identifiability was studied formally on the equations governing outlet concentrations. It was also studied numerically on 6 simulated CSTR experiments on a soil with known equilibrium-kinetic sorption parameters. EK sorption parameters can not be identified from a single breakthrough curve of a CSTR experiment, because K d,1 and k - were diagnosed collinear. For pairs of CSTR experiments, Bayesian inference allowed to select the correct models of sorption and error among sorption alternatives. Bayesian inference was conducted with SAMCAT software (Sensitivity Analysis and Markov Chain simulations Applied to Transfer models) which launched the simulations through the embedded simulation engine GNU-MCSim, and automated their configuration and post-processing. Experimental designs consisting in varying flow rates between experiments reaching equilibrium at contamination stage were found optimal, because they simultaneously gave accurate sorption parameters and predictions. Bayesian results were comparable to maximum likehood method but they avoided convergence problems, the marginal likelihood allowed to compare all models, and credible interval gave directly the uncertainty of sorption parameters θ. Although these findings are limited to the specific conditions studied here, in particular the considered sorption model, the chosen parameter values and error structure, they help in the conception and analysis of future CSTR experiments with radionuclides whose kinetic behaviour is suspected. Copyright © 2016 Elsevier Ltd. All

Inflammation: an important parameter in the search of prostate cancer biomarkers

PubMed Central

2014-01-01

Background A more specific and early diagnostics for prostate cancer (PCa) is highly desirable. In this study, being inflammation the focus of our effort, serum protein profiles were analyzed in order to investigate if this parameter could interfere with the search of discriminating proteins between PCa and benign prostatic hyperplasia (BPH). Methods Patients with clinical suspect of PCa and candidates for trans-rectal ultrasound guided prostate biopsy (TRUS) were enrolled. Histological specimens were examined in order to grade and classify the tumor, identify BPH and detect inflammation. Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry (SELDI-ToF-MS) and two-dimensional gel electrophoresis (2-DE) coupled with Liquid Chromatography-MS/MS (LC-MS/MS) were used to analyze immuno-depleted serum samples from patients with PCa and BPH. Results The comparison between PCa (with and without inflammation) and BPH (with and without inflammation) serum samples by SELDI-ToF-MS analysis did not show differences in protein expression, while changes were only observed when the concomitant presence of inflammation was taken into consideration. In fact, when samples with histological sign of inflammation were excluded, 20 significantly different protein peaks were detected. Subsequent comparisons (PCa with inflammation vs PCa without inflammation, and BPH with inflammation vs BPH without inflammation) showed that 16 proteins appeared to be modified in the presence of inflammation, while 4 protein peaks were not modified. With 2-DE analysis, comparing PCa without inflammation vs PCa with inflammation, and BPH without inflammation vs the same condition in the presence of inflammation, were identified 29 and 25 differentially expressed protein spots, respectively. Excluding samples with inflammation the comparison between PCa vs BPH showed 9 unique PCa proteins, 4 of which overlapped with those previously identified in the presence of inflammation, while

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

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

Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.

2013-12-01

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less

Aerobic stabilization of biological sludge characterized by an extremely low decay rate: modeling, identifiability analysis and parameter estimation.

PubMed

Martínez-García, C G; Olguín, M T; Fall, C

2014-08-01

Aerobic digestion batch tests were run on a sludge model that contained only two fractions, the heterotrophic biomass (XH) and its endogenous residue (XP). The objective was to describe the stabilization of the sludge and estimate the endogenous decay parameters. Modeling was performed with Aquasim, based on long-term data of volatile suspended solids and chemical oxygen demand (VSS, COD). Sensitivity analyses were carried out to determine the conditions for unique identifiability of the parameters. Importantly, it was found that the COD/VSS ratio of the endogenous residues (1.06) was significantly lower than for the active biomass fraction (1.48). The decay rate constant of the studied sludge (low bH, 0.025 d(-1)) was one-tenth that usually observed (0.2d(-1)), which has two main practical significances. Digestion time required is much more long; also the oxygen uptake rate might be <1.5 mg O₂/gTSSh (biosolids standards), without there being significant decline in the biomass. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prognostic Importance of Spinopelvic Parameters in the Assessment of Conservative Treatment in Patients with Spondylolisthesis.

PubMed

M L V, Sai Krishna; Sharma, Deep; Menon, Jagdish

2018-04-01

This was a prospective, two-group comparative study. The present study aimed to determine the importance of the spinopelvic parameters in the causation and progression of spondylolisthesis. Spondylolisthesis is slippage of one vertebra over the vertebra below. Since the discovery of pelvic incidence (PI) in 1998 in addition to documentation of other parameters in spinopelvic balance, slippage in spondylolisthesis has been attributed to these parameters. Many studies on the Caucasian population have implicated high PI as a causative factor of spondylolisthesis. To the best of our knowledge, no study has described the role of these parameters in the progression of spondylolisthesis. The study was conducted in Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India. Seventy-nine patients with spondylolisthesis consented to participate in the study. All patients were advised to undergo conservative treatment and were regularly followed up according to the protocol. Seventy-five asymptomatic volunteers were recruited as a control group. Of the total of 79 patients, 54 were followed up for 6 months, during which 46 improved, eight showed no improvement, and 25 were lost to follow-up. Sagittal spinopelvic parameters were measured by a single observer using the Surgimap spine software ver. 2.1.2 (Nemaris, New York, NY, USA). Parameters measured were PI, pelvic tilt (PT), sacral slope (SS), thoracic kyphosis, and lumbar lordosis. The results from patients and controls were compared using appropriate statistical methods. The normal and spondylolisthesis groups significantly differed with respect to PI, SS, and PT ( p <0.001). There were no significant differences in the measured spinopelvic parameters between patients with high- and low-grade spondylolisthesis or between those whose condition improved and those whose condition worsened. PI, the most important of all spinopelvic parameters, is responsible for the slip in spondylolisthesis, but

Identifying criteria and establishing parameters for forest-based ecotourism in Northern Ontario, Canada

Treesearch

Stephen W. Boyd; Richard W. Butler; Wolfgang Haider

1995-01-01

This paper identifies the following criteria as indicators for ecotourism suitability within a Northern Ontario context: naturalness, wildlife, cultural heritage, landscape and community. A methodology is proposed which uses Geographical Information Systems (GIS) to identify ecotourism sites by linking criteria deemed important with actual landscape characteristics of...

Identifying Outcomes that Are Important to Living Kidney Donors: A Nominal Group Technique Study.

PubMed

Hanson, Camilla S; Chapman, Jeremy R; Gill, John S; Kanellis, John; Wong, Germaine; Craig, Jonathan C; Teixeira-Pinto, Armando; Chadban, Steve J; Garg, Amit X; Ralph, Angelique F; Pinter, Jule; Lewis, Joshua R; Tong, Allison

2018-06-07

Living kidney donor candidates accept a range of risks and benefits when they decide to proceed with nephrectomy. Informed consent around this decision assumes they receive reliable data about outcomes they regard as critical to their decision making. We identified the outcomes most important to living kidney donors and described the reasons for their choices. Previous donors were purposively sampled from three transplant units in Australia (Sydney and Melbourne) and Canada (Vancouver). In focus groups using the nominal group technique, participants identified outcomes of donation, ranked them in order of importance, and discussed the reasons for their preferences. An importance score was calculated for each outcome. Qualitative data were analyzed thematically. Across 14 groups, 123 donors aged 27-78 years identified 35 outcomes. Across all participants, the ten highest ranked outcomes were kidney function (importance=0.40, scale 0-1), time to recovery (0.27), surgical complications (0.24), effect on family (0.22), donor-recipient relationship (0.21), life satisfaction (0.18), lifestyle restrictions (0.18), kidney failure (0.14), mortality (0.13), and acute pain/discomfort (0.12). Kidney function and kidney failure were more important to Canadian participants, compared with Australian donors. The themes identified included worthwhile sacrifice, insignificance of risks and harms, confidence and empowerment, unfulfilled expectations, and heightened susceptibility. Living kidney donors prioritized a range of outcomes, with the most important being kidney health and the surgical, lifestyle, functional, and psychosocial effects of donation. Donors also valued improvements to their family life and donor-recipient relationship. There were clear regional differences in the rankings. Copyright © 2018 by the American Society of Nephrology.

A new multimedia contaminant fate model for China: how important are environmental parameters in influencing chemical persistence and long-range transport potential?

PubMed

Zhu, Ying; Price, Oliver R; Tao, Shu; Jones, Kevin C; Sweetman, Andy J

2014-08-01

We present a new multimedia chemical fate model (SESAMe) which was developed to assess chemical fate and behaviour across China. We apply the model to quantify the influence of environmental parameters on chemical overall persistence (POV) and long-range transport potential (LRTP) in China, which has extreme diversity in environmental conditions. Sobol sensitivity analysis was used to identify the relative importance of input parameters. Physicochemical properties were identified as more influential than environmental parameters on model output. Interactive effects of environmental parameters on POV and LRTP occur mainly in combination with chemical properties. Hypothetical chemicals and emission data were used to model POV and LRTP for neutral and acidic chemicals with different KOW/DOW, vapour pressure and pKa under different precipitation, wind speed, temperature and soil organic carbon contents (fOC). Generally for POV, precipitation was more influential than the other environmental parameters, whilst temperature and wind speed did not contribute significantly to POV variation; for LRTP, wind speed was more influential than the other environmental parameters, whilst the effects of other environmental parameters relied on specific chemical properties. fOC had a slight effect on POV and LRTP, and higher fOC always increased POV and decreased LRTP. Example case studies were performed on real test chemicals using SESAMe to explore the spatial variability of model output and how environmental properties affect POV and LRTP. Dibenzofuran released to multiple media had higher POV in northwest of Xinjiang, part of Gansu, northeast of Inner Mongolia, Heilongjiang and Jilin. Benzo[a]pyrene released to the air had higher LRTP in south Xinjiang and west Inner Mongolia, whilst acenaphthene had higher LRTP in Tibet and west Inner Mongolia. TCS released into water had higher LRTP in Yellow River and Yangtze River catchments. The initial case studies demonstrated that SESAMe

The Extent, Causes, and Importance of Context Effects on Item Parameters for Two Latent-Trait Models.

ERIC Educational Resources Information Center

Yen, Wendy M.

The extent, causes, and importance of context effects on item parameters for one- and three-parameter latent-trait models were examined. Items were taken from the California Achievement Tests Reading Comprehension and Mathematics Concepts and Applications subtests. The reading items were administered to 1,678 fourth-grade students, and the…

Time-varying parameter models for catchments with land use change: the importance of model structure

NASA Astrophysics Data System (ADS)

Pathiraja, Sahani; Anghileri, Daniela; Burlando, Paolo; Sharma, Ashish; Marshall, Lucy; Moradkhani, Hamid

2018-05-01

Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

Identifying the role of initial wave parameters on tsunami focusing

NASA Astrophysics Data System (ADS)

Aydın, Baran

2018-04-01

Unexpected local tsunami amplification, which is referred to as tsunami focusing, is attributed to two different mechanisms: bathymetric features of the ocean bottom such as underwater ridges and dipolar shape of the initial wave itself. In this study, we characterize the latter; that is, we explore how amplitude and location of the focusing point vary with certain geometric parameters of the initial wave such as its steepness and crest length. Our results reveal two important features of tsunami focusing: for mild waves maximum wave amplitude increases significantly with transverse length of wave crest, while location of the focusing point is almost invariant. For steep waves, on the other hand, increasing crest length dislocates focusing point significantly, while it causes a rather small increase in wave maximum.

Chromium released from leather - II: the importance of environmental parameters.

PubMed

Mathiason, Frederik; Lidén, Carola; Hedberg, Yolanda S

2015-05-01

Approximately 1-3% of the adult population in Europe are allergic to chromium (Cr). A new restriction in Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) based on the ISO 17075 standard has recently been adopted in the EU to limit Cr(VI) in consumer and occupational leather products to < 3 mg/kg. To investigate the influence of storage conditions [relative humidity, temperature, ultraviolet (UV) irradiation, and duration] on Cr release, and to assess several parameters relevant for occupational exposure (repeated exposure, wear, alkaline solutions, and sequential wet and dry exposures). A leather of relevance for work gloves was investigated for its release of Cr(III) and Cr(VI) under these different experimental conditions. Relative humidity (water content in leather) during storage prior to Cr extraction was the single most important parameter. Cr(VI) levels could vary from non-detectable to levels significantly exceeding the restriction limit, depending on the relative humidity. Leather contact with alkaline solution and UV irradiation during storage could increase the Cr(VI) levels in subsequent extractions. The amount of Cr(VI) in leather is not an intrinsic property, but is influenced by environmental conditions of relevance for occupations and skin exposure. © 2015 The Authors. Contact Dermatitis published by John Wiley & Sons Ltd.

Identifying arbitrary parameter zonation using multiple level set functions

NASA Astrophysics Data System (ADS)

Lu, Zhiming; Vesselinov, Velimir V.; Lei, Hongzhuan

2018-07-01

In this paper, we extended the analytical level set method [1,2] for identifying a piece-wisely heterogeneous (zonation) binary system to the case with an arbitrary number of materials with unknown material properties. In the developed level set approach, starting from an initial guess, the material interfaces are propagated through iterations such that the residuals between the simulated and observed state variables (hydraulic head) is minimized. We derived an expression for the propagation velocity of the interface between any two materials, which is related to the permeability contrast between the materials on two sides of the interface, the sensitivity of the head to permeability, and the head residual. We also formulated an expression for updating the permeability of all materials, which is consistent with the steepest descent of the objective function. The developed approach has been demonstrated through many examples, ranging from totally synthetic cases to a case where the flow conditions are representative of a groundwater contaminant site at the Los Alamos National Laboratory. These examples indicate that the level set method can successfully identify zonation structures, even if the number of materials in the model domain is not exactly known in advance. Although the evolution of the material zonation depends on the initial guess field, inverse modeling runs starting with different initial guesses fields may converge to the similar final zonation structure. These examples also suggest that identifying interfaces of spatially distributed heterogeneities is more important than estimating their permeability values.

Modeling of 2D diffusion processes based on microscopy data: parameter estimation and practical identifiability analysis.

PubMed

Hock, Sabrina; Hasenauer, Jan; Theis, Fabian J

2013-01-01

Diffusion is a key component of many biological processes such as chemotaxis, developmental differentiation and tissue morphogenesis. Since recently, the spatial gradients caused by diffusion can be assessed in-vitro and in-vivo using microscopy based imaging techniques. The resulting time-series of two dimensional, high-resolutions images in combination with mechanistic models enable the quantitative analysis of the underlying mechanisms. However, such a model-based analysis is still challenging due to measurement noise and sparse observations, which result in uncertainties of the model parameters. We introduce a likelihood function for image-based measurements with log-normal distributed noise. Based upon this likelihood function we formulate the maximum likelihood estimation problem, which is solved using PDE-constrained optimization methods. To assess the uncertainty and practical identifiability of the parameters we introduce profile likelihoods for diffusion processes. As proof of concept, we model certain aspects of the guidance of dendritic cells towards lymphatic vessels, an example for haptotaxis. Using a realistic set of artificial measurement data, we estimate the five kinetic parameters of this model and compute profile likelihoods. Our novel approach for the estimation of model parameters from image data as well as the proposed identifiability analysis approach is widely applicable to diffusion processes. The profile likelihood based method provides more rigorous uncertainty bounds in contrast to local approximation methods.

Understanding identifiability as a crucial step in uncertainty assessment

NASA Astrophysics Data System (ADS)

Jakeman, A. J.; Guillaume, J. H. A.; Hill, M. C.; Seo, L.

2016-12-01

The topic of identifiability analysis offers concepts and approaches to identify why unique model parameter values cannot be identified, and can suggest possible responses that either increase uniqueness or help to understand the effect of non-uniqueness on predictions. Identifiability analysis typically involves evaluation of the model equations and the parameter estimation process. Non-identifiability can have a number of undesirable effects. In terms of model parameters these effects include: parameters not being estimated uniquely even with ideal data; wildly different values being returned for different initialisations of a parameter optimisation algorithm; and parameters not being physically meaningful in a model attempting to represent a process. This presentation illustrates some of the drastic consequences of ignoring model identifiability analysis. It argues for a more cogent framework and use of identifiability analysis as a way of understanding model limitations and systematically learning about sources of uncertainty and their importance. The presentation specifically distinguishes between five sources of parameter non-uniqueness (and hence uncertainty) within the modelling process, pragmatically capturing key distinctions within existing identifiability literature. It enumerates many of the various approaches discussed in the literature. Admittedly, improving identifiability is often non-trivial. It requires thorough understanding of the cause of non-identifiability, and the time, knowledge and resources to collect or select new data, modify model structures or objective functions, or improve conditioning. But ignoring these problems is not a viable solution. Even simple approaches such as fixing parameter values or naively using a different model structure may have significant impacts on results which are too often overlooked because identifiability analysis is neglected.

Quantitative Microbial Risk Assessment Tutorial – SDMProjectBuilder: Import Local Data Files to Identify and Modify Contamination Sources and Input Parameters

EPA Science Inventory

Twelve example local data support files are automatically downloaded when the SDMProjectBuilder is installed on a computer. They allow the user to modify values to parameters that impact the release, migration, fate, and transport of microbes within a watershed, and control delin...

Identifying arbitrary parameter zonation using multiple level set functions

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

Lu, Zhiming; Vesselinov, Velimir Valentinov; Lei, Hongzhuan

In this paper, we extended the analytical level set method [1, 2] for identifying a piece-wisely heterogeneous (zonation) binary system to the case with an arbitrary number of materials with unknown material properties. In the developed level set approach, starting from an initial guess, the material interfaces are propagated through iterations such that the residuals between the simulated and observed state variables (hydraulic head) is minimized. We derived an expression for the propagation velocity of the interface between any two materials, which is related to the permeability contrast between the materials on two sides of the interface, the sensitivity ofmore » the head to permeability, and the head residual. We also formulated an expression for updating the permeability of all materials, which is consistent with the steepest descent of the objective function. The developed approach has been demonstrated through many examples, ranging from totally synthetic cases to a case where the flow conditions are representative of a groundwater contaminant site at the Los Alamos National Laboratory. These examples indicate that the level set method can successfully identify zonation structures, even if the number of materials in the model domain is not exactly known in advance. Although the evolution of the material zonation depends on the initial guess field, inverse modeling runs starting with different initial guesses fields may converge to the similar final zonation structure. These examples also suggest that identifying interfaces of spatially distributed heterogeneities is more important than estimating their permeability values.« less

Identifying arbitrary parameter zonation using multiple level set functions

DOE PAGES

Lu, Zhiming; Vesselinov, Velimir Valentinov; Lei, Hongzhuan

2018-03-14

In this paper, we extended the analytical level set method [1, 2] for identifying a piece-wisely heterogeneous (zonation) binary system to the case with an arbitrary number of materials with unknown material properties. In the developed level set approach, starting from an initial guess, the material interfaces are propagated through iterations such that the residuals between the simulated and observed state variables (hydraulic head) is minimized. We derived an expression for the propagation velocity of the interface between any two materials, which is related to the permeability contrast between the materials on two sides of the interface, the sensitivity ofmore » the head to permeability, and the head residual. We also formulated an expression for updating the permeability of all materials, which is consistent with the steepest descent of the objective function. The developed approach has been demonstrated through many examples, ranging from totally synthetic cases to a case where the flow conditions are representative of a groundwater contaminant site at the Los Alamos National Laboratory. These examples indicate that the level set method can successfully identify zonation structures, even if the number of materials in the model domain is not exactly known in advance. Although the evolution of the material zonation depends on the initial guess field, inverse modeling runs starting with different initial guesses fields may converge to the similar final zonation structure. These examples also suggest that identifying interfaces of spatially distributed heterogeneities is more important than estimating their permeability values.« less

Identifiability and estimation of multiple transmission pathways in cholera and waterborne disease.

PubMed

Eisenberg, Marisa C; Robertson, Suzanne L; Tien, Joseph H

2013-05-07

Cholera and many waterborne diseases exhibit multiple characteristic timescales or pathways of infection, which can be modeled as direct and indirect transmission. A major public health issue for waterborne diseases involves understanding the modes of transmission in order to improve control and prevention strategies. An important epidemiological question is: given data for an outbreak, can we determine the role and relative importance of direct vs. environmental/waterborne routes of transmission? We examine whether parameters for a differential equation model of waterborne disease transmission dynamics can be identified, both in the ideal setting of noise-free data (structural identifiability) and in the more realistic setting in the presence of noise (practical identifiability). We used a differential algebra approach together with several numerical approaches, with a particular emphasis on identifiability of the transmission rates. To examine these issues in a practical public health context, we apply the model to a recent cholera outbreak in Angola (2006). Our results show that the model parameters-including both water and person-to-person transmission routes-are globally structurally identifiable, although they become unidentifiable when the environmental transmission timescale is fast. Even for water dynamics within the identifiable range, when noisy data are considered, only a combination of the water transmission parameters can practically be estimated. This makes the waterborne transmission parameters difficult to estimate, leading to inaccurate estimates of important epidemiological parameters such as the basic reproduction number (R0). However, measurements of pathogen persistence time in environmental water sources or measurements of pathogen concentration in the water can improve model identifiability and allow for more accurate estimation of waterborne transmission pathway parameters as well as R0. Parameter estimates for the Angola outbreak suggest

27 CFR 478.92 - How must licensed manufacturers and licensed importers identify firearms, armor piercing...

Code of Federal Regulations, 2010 CFR

2010-04-01

... Conduct of Business § 478.92 How must licensed manufacturers and licensed importers identify firearms... business; and (E) In the case of an imported firearm, the name of the country in which it was manufactured... place of business. For additional requirements relating to imported firearms, see Customs regulations at...

Identifying hub stations and important lines of bus networks: A case study in Xiamen, China

NASA Astrophysics Data System (ADS)

Zhang, Hui; Zhuge, Chengxiang; Yu, Xiaohua

2018-07-01

Hub stations and important lines play key roles in transfers between stations. In this paper, a node failure model is proposed to identify hub stations. In the model, we introduce two new indicators called neighborhood degree ratio and transfer index to evaluate the importance of stations, which consider neighborhood stations' degree of station and the initial transfer times between stations. Moreover, line accessibility is developed to measure the importance of lines in the bus network. Xiamen bus network in 2016 is utilized to test the model. The results show that the two introduced indicators are more effective to identify hub stations compared with traditional complex network indicators such as degree, clustering coefficient and betweenness.

Estimation and Identifiability of Model Parameters in Human Nociceptive Processing Using Yes-No Detection Responses to Electrocutaneous Stimulation.

PubMed

Yang, Huan; Meijer, Hil G E; Buitenweg, Jan R; van Gils, Stephan A

2016-01-01

Healthy or pathological states of nociceptive subsystems determine different stimulus-response relations measured from quantitative sensory testing. In turn, stimulus-response measurements may be used to assess these states. In a recently developed computational model, six model parameters characterize activation of nerve endings and spinal neurons. However, both model nonlinearity and limited information in yes-no detection responses to electrocutaneous stimuli challenge to estimate model parameters. Here, we address the question whether and how one can overcome these difficulties for reliable parameter estimation. First, we fit the computational model to experimental stimulus-response pairs by maximizing the likelihood. To evaluate the balance between model fit and complexity, i.e., the number of model parameters, we evaluate the Bayesian Information Criterion. We find that the computational model is better than a conventional logistic model regarding the balance. Second, our theoretical analysis suggests to vary the pulse width among applied stimuli as a necessary condition to prevent structural non-identifiability. In addition, the numerically implemented profile likelihood approach reveals structural and practical non-identifiability. Our model-based approach with integration of psychophysical measurements can be useful for a reliable assessment of states of the nociceptive system.

Life cycle assessment and residue leaching: The importance of parameter, scenario and leaching data selection

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

Allegrini, E., E-mail: elia@env.dtu.dk; Butera, S.; Kosson, D.S.

Highlights: • Relevance of metal leaching in waste management system LCAs was assessed. • Toxic impacts from leaching could not be disregarded. • Uncertainty of toxicity, due to background activities, determines LCA outcomes. • Parameters such as pH and L/S affect LCA results. • Data modelling consistency and coverage within an LCA are crucial. - Abstract: Residues from industrial processes and waste management systems (WMSs) have been increasingly reutilised, leading to landfilling rate reductions and the optimisation of mineral resource utilisation in society. Life cycle assessment (LCA) is a holistic methodology allowing for the analysis of systems and products andmore » can be applied to waste management systems to identify environmental benefits and critical aspects thereof. From an LCA perspective, residue utilisation provides benefits such as avoiding the production and depletion of primary materials, but it can lead to environmental burdens, due to the potential leaching of toxic substances. In waste LCA studies where residue utilisation is included, leaching has generally been neglected. In this study, municipal solid waste incineration bottom ash (MSWI BA) was used as a case study into three LCA scenarios having different system boundaries. The importance of data quality and parameter selection in the overall LCA results was evaluated, and an innovative method to assess metal transport into the environment was applied, in order to determine emissions to the soil and water compartments for use in an LCA. It was found that toxic impacts as a result of leaching were dominant in systems including only MSWI BA utilisation, while leaching appeared negligible in larger scenarios including the entire waste system. However, leaching could not be disregarded a priori, due to large uncertainties characterising other activities in the scenario (e.g. electricity production). Based on the analysis of relevant parameters relative to leaching, and on general

Important caves to be identified

NASA Astrophysics Data System (ADS)

Criteria to identify significant caves on federal land are being developed by the Interior Department's Bureau of Land Management and the Agriculture Department's Forest Service under requirements of the Federal Cave Resources Protection Act of 1988. The departments gave advance notice of proposed rulemaking March 3 and invited suggestions and comments from the public for 30 days.The law requires protection, to the extent practical, of significant caves on lands administered by the Secretaries of Agriculture and Interior and includes authority to issue and revoke permits for collection and removal of cave resources and special provisions for regulation of cave resources on Indian lands. Final regulations must be published by August 18, 1989.

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

PubMed

Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

2018-01-01

Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm 2 . Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (K trans ), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

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

Kleijnen, J.P.C.; Helton, J.C.

1999-04-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are consideredmore » for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.« less

Life cycle assessment and residue leaching: the importance of parameter, scenario and leaching data selection.

PubMed

Allegrini, E; Butera, S; Kosson, D S; Van Zomeren, A; Van der Sloot, H A; Astrup, T F

2015-04-01

Residues from industrial processes and waste management systems (WMSs) have been increasingly reutilised, leading to landfilling rate reductions and the optimisation of mineral resource utilisation in society. Life cycle assessment (LCA) is a holistic methodology allowing for the analysis of systems and products and can be applied to waste management systems to identify environmental benefits and critical aspects thereof. From an LCA perspective, residue utilisation provides benefits such as avoiding the production and depletion of primary materials, but it can lead to environmental burdens, due to the potential leaching of toxic substances. In waste LCA studies where residue utilisation is included, leaching has generally been neglected. In this study, municipal solid waste incineration bottom ash (MSWI BA) was used as a case study into three LCA scenarios having different system boundaries. The importance of data quality and parameter selection in the overall LCA results was evaluated, and an innovative method to assess metal transport into the environment was applied, in order to determine emissions to the soil and water compartments for use in an LCA. It was found that toxic impacts as a result of leaching were dominant in systems including only MSWI BA utilisation, while leaching appeared negligible in larger scenarios including the entire waste system. However, leaching could not be disregarded a priori, due to large uncertainties characterising other activities in the scenario (e.g. electricity production). Based on the analysis of relevant parameters relative to leaching, and on general results of the study, recommendations are provided regarding the use of leaching data in LCA studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Different approaches for identifying important concepts in probabilistic biomedical text summarization.

PubMed

Moradi, Milad; Ghadiri, Nasser

2018-01-01

Automatic text summarization tools help users in the biomedical domain to acquire their intended information from various textual resources more efficiently. Some of biomedical text summarization systems put the basis of their sentence selection approach on the frequency of concepts extracted from the input text. However, it seems that exploring other measures rather than the raw frequency for identifying valuable contents within an input document, or considering correlations existing between concepts, may be more useful for this type of summarization. In this paper, we describe a Bayesian summarization method for biomedical text documents. The Bayesian summarizer initially maps the input text to the Unified Medical Language System (UMLS) concepts; then it selects the important ones to be used as classification features. We introduce six different feature selection approaches to identify the most important concepts of the text and select the most informative contents according to the distribution of these concepts. We show that with the use of an appropriate feature selection approach, the Bayesian summarizer can improve the performance of biomedical summarization. Using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) toolkit, we perform extensive evaluations on a corpus of scientific papers in the biomedical domain. The results show that when the Bayesian summarizer utilizes the feature selection methods that do not use the raw frequency, it can outperform the biomedical summarizers that rely on the frequency of concepts, domain-independent and baseline methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Variance Reduction Factor of Nuclear Data for Integral Neutronics Parameters

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

Chiba, G., E-mail: go_chiba@eng.hokudai.ac.jp; Tsuji, M.; Narabayashi, T.

We propose a new quantity, a variance reduction factor, to identify nuclear data for which further improvements are required to reduce uncertainties of target integral neutronics parameters. Important energy ranges can be also identified with this variance reduction factor. Variance reduction factors are calculated for several integral neutronics parameters. The usefulness of the variance reduction factors is demonstrated.

Identifying important motivational factors for professionals in Greek hospitals

PubMed Central

Kontodimopoulos, Nick; Paleologou, Victoria; Niakas, Dimitris

2009-01-01

Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements) was used. Three categories of health care professionals, doctors (N = 354), nurses (N = 581) and office workers (N = 418), working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P < 0.001). Within subgroups, motivators were similar, and only one significant difference was observed, namely between doctors and nurses in respect to co-workers (P < 0.05). Remuneration (and salary in particular) was reported as a significant incentive only for professionals in managerial positions. Health professionals in private hospitals were motivated by all factors significantly more than their public-hospital counterparts. Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation. PMID:19754968

Quantitative Microbial Risk Assessment Tutorial - SDMProjectBuilder: Import Local Data Files to Identify and Modify Contamination Sources and Input ParametersUpdated 2017

EPA Science Inventory

Twelve example local data support files are automatically downloaded when the SDMProjectBuilder is installed on a computer. They allow the user to modify values to parameters that impact the release, migration, fate, and transport of microbes within a watershed, and control delin...

Development of quantitative radioactive methodologies on paper to determine important lateral-flow immunoassay parameters.

PubMed

Mosley, Garrett L; Nguyen, Phuong; Wu, Benjamin M; Kamei, Daniel T

2016-08-07

The lateral-flow immunoassay (LFA) is a well-established diagnostic technology that has recently seen significant advancements due in part to the rapidly expanding fields of paper diagnostics and paper-fluidics. As LFA-based diagnostics become more complex, it becomes increasingly important to quantitatively determine important parameters during the design and evaluation process. However, current experimental methods for determining these parameters have certain limitations when applied to LFA systems. In this work, we describe our novel methods of combining paper and radioactive measurements to determine nanoprobe molarity, the number of antibodies per nanoprobe, and the forward and reverse rate constants for nanoprobe binding to immobilized target on the LFA test line. Using a model LFA system that detects for the presence of the protein transferrin (Tf), we demonstrate the application of our methods, which involve quantitative experimentation and mathematical modeling. We also compare the results of our rate constant experiments with traditional experiments to demonstrate how our methods more appropriately capture the influence of the LFA environment on the binding interaction. Our novel experimental approaches can therefore more efficiently guide the research process for LFA design, leading to more rapid advancement of the field of paper-based diagnostics.

Cellular signaling identifiability analysis: a case study.

PubMed

Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

2010-05-21

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

PTEN IDENTIFIED AS IMPORTANT RISK FACTOR OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE

PubMed Central

Hosgood, H Dean; Menashe, Idan; He, Xingzhou; Chanock, Stephen; Lan, Qing

2009-01-01

Common genetic variation may play an important role in altering chronic obstructive pulmonary disease (COPD) risk. In Xuanwei, China, the COPD rate is more than twice the Chinese national average, and COPD is strongly associated with in-home coal use. To identify genetic variation that may be associated with COPD in a population with substantial in-home coal smoke exposures, we evaluated 1,261 single nucleotide polymorphisms (SNPs) in 380 candidate genes potentially relevant for cancer and other human diseases in a population-based case-control study in Xuanwei (53 cases; 107 controls). PTEN was the most significantly associated gene with COPD in a minP analysis using 20,000 permutations (P = 0.00005). SNP-based analyses found that homozygote variant carriers of PTEN rs701848 (ORTT = 0.12, 95%CI = 0.03 - 0.47) had a significant decreased risk of COPD. PTEN, or phosphatase and tensin homolog, is an important regulator of cell cycle progression and cellular survival via the AKT signaling pathway. Our exploratory analysis suggests that genetic variation in PTEN may be an important risk factor of COPD in Xuanwei. However, due to the small sample size, additional studies are needed to evaluate these associations within Xuanwei and other populations with coal smoke exposures. PMID:19625176

Assessing the importance of terrain parameters on glide avalanche release

NASA Astrophysics Data System (ADS)

Peitzsch, E.; Hendrikx, J.; Fagre, D. B.

2013-12-01

avalanches failed as cohesive slabs on this bedrock surface. Consequently, surface roughness proved to be a useful descriptive variable to discriminate between slopes that avalanched and those that did not. Annual 'repeat offender' glide avalanche paths were characterized by smooth outcropping rock plates with stratification planes parallel to the slope. Combined with aspect these repeat offenders were also members of the highest glide category. Using this understanding of the role of topographic parameters on glide avalanche activity, a spatial terrain based model was developed to identify other areas with high glide avalanche potential outside of our immediate observation area.

Assessing the importance of terrain parameters on glide avalanche release

USGS Publications Warehouse

Peitzsch, Erich H.; Hendrikx, Jordy; Fagre, Daniel B.

2014-01-01

avalanches failed as cohesive slabs on this bedrock surface. Consequently, surface roughness proved to be a useful descriptive variable to discriminate between slopes that avalanched and those that did not. Annual 'repeat offender' glide avalanche paths were characterized by smooth outcropping rock plates with stratification planes parallel to the slope. Combined with aspect these repeat offenders were also members of the highest glide category. Using this understanding of the role of topographic parameters on glide avalanche activity, a spatial terrain based model was developed to identify other areas with high glide avalanche potential outside of our immediate observation area.

Surface and Atmospheric Parameter Retrieval From AVIRIS Data: The Importance of Non-Linear Effects

NASA Technical Reports Server (NTRS)

Green Robert O.; Moreno, Jose F.

1996-01-01

AVIRIS data represent a new and important approach for the retrieval of atmospheric and surface parameters from optical remote sensing data. Not only as a test for future space systems, but also as an operational airborne remote sensing system, the development of algorithms to retrieve information from AVIRIS data is an important step to these new approaches and capabilities. Many things have been learned since AVIRIS became operational, and the successive technical improvements in the hardware and the more sophisticated calibration techniques employed have increased the quality of the data to the point of almost meeting optimum user requirements. However, the potential capabilities of imaging spectrometry over the standard multispectral techniques have still not been fully demonstrated. Reasons for this are the technical difficulties in handling the data, the critical aspect of calibration for advanced retrieval methods, and the lack of proper models with which to invert the measured AVIRIS radiances in all the spectral channels. To achieve the potential of imaging spectrometry, these issues must be addressed. In this paper, an algorithm to retrieve information about both atmospheric and surface parameters from AVIRIS data, by using model inversion techniques, is described. Emphasis is put on the derivation of the model itself as well as proper inversion techniques, robust to noise in the data and an inadequate ability of the model to describe natural variability in the data. The problem of non-linear effects is addressed, as it has been demonstrated to be a major source of error in the numerical values retrieved by more simple, linear-based approaches. Non-linear effects are especially critical for the retrieval of surface parameters where both scattering and absorption effects are coupled, as well as in the cases of significant multiple-scattering contributions. However, sophisticated modeling approaches can handle such non-linear effects, which are especially

Estimate variable importance for recurrent event outcomes with an application to identify hypoglycemia risk factors.

PubMed

Duan, Ran; Fu, Haoda

2015-08-30

Recurrent event data are an important data type for medical research. In particular, many safety endpoints are recurrent outcomes, such as hypoglycemic events. For such a situation, it is important to identify the factors causing these events and rank these factors by their importance. Traditional model selection methods are not able to provide variable importance in this context. Methods that are able to evaluate the variable importance, such as gradient boosting and random forest algorithms, cannot directly be applied to recurrent events data. In this paper, we propose a two-step method that enables us to evaluate the variable importance for recurrent events data. We evaluated the performance of our proposed method by simulations and applied it to a data set from a diabetes study. Copyright © 2015 John Wiley & Sons, Ltd.

Authentic early experience in Medical Education: a socio-cultural analysis identifying important variables in learning interactions within workplaces.

PubMed

Yardley, Sarah; Brosnan, Caragh; Richardson, Jane; Hays, Richard

2013-12-01

This paper addresses the question 'what are the variables influencing social interactions and learning during Authentic Early Experience (AEE)?' AEE is a complex educational intervention for new medical students. Following critique of the existing literature, multiple qualitative methods were used to create a study framework conceptually orientated to a socio-cultural perspective. Study participants were recruited from three groups at one UK medical school: students, workplace supervisors, and medical school faculty. A series of intersecting spectra identified in the data describe dyadic variables that make explicit the parameters within which social interactions are conducted in this setting. Four of the spectra describe social processes related to being in workplaces and developing the ability to manage interactions during authentic early experiences. These are: (1) legitimacy expressed through invited participation or exclusion; (2) finding a role-a spectrum from student identity to doctor mindset; (3) personal perspectives and discomfort in transition from lay to medical; and, (4) taking responsibility for 'risk'-moving from aversion to management through graded progression of responsibility. Four further spectra describe educational consequences of social interactions. These spectra identify how the reality of learning is shaped through social interactions and are (1) generic-specific objectives, (2) parallel-integrated-learning, (3) context specific-transferable learning and (4) performing or simulating-reality. Attention to these variables is important if educators are to maximise constructive learning from AEE. Application of each of the spectra could assist workplace supervisors to maximise the positive learning potential of specific workplaces.

Surgeon Reported Outcome Measure for Spine Trauma: An International Expert Survey Identifying Parameters Relevant for the Outcome of Subaxial Cervical Spine Injuries.

PubMed

Sadiqi, Said; Verlaan, Jorrit-Jan; Lehr, A Mechteld; Dvorak, Marcel F; Kandziora, Frank; Rajasekaran, S; Schnake, Klaus J; Vaccaro, Alexander R; Oner, F Cumhur

2016-12-15

International web-based survey. To identify clinical and radiological parameters that spine surgeons consider most relevant when evaluating clinical and functional outcomes of subaxial cervical spine trauma patients. Although an outcome instrument that reflects the patients' perspective is imperative, there is also a need for a surgeon reported outcome measure to reflect the clinicians' perspective adequately. A cross-sectional online survey was conducted among a selected number of spine surgeons from all five AOSpine International world regions. They were asked to indicate the relevance of a compilation of 21 parameters, both for the short term (3 mo-2 yr) and long term (≥2 yr), on a five-point scale. The responses were analyzed using descriptive statistics, frequency analysis, and Kruskal-Wallis test. Of the 279 AOSpine International and International Spinal Cord Society members who received the survey, 108 (38.7%) participated in the study. Ten parameters were identified as relevant both for short term and long term by at least 70% of the participants. Neurological status, implant failure within 3 months, and patient satisfaction were most relevant. Bony fusion was the only parameter for the long term, whereas five parameters were identified for the short term. The remaining six parameters were not deemed relevant. Minor differences were observed when analyzing the responses according to each world region, or spine surgeons' degree of experience. The perspective of an international sample of highly experienced spine surgeons was explored on the most relevant parameters to evaluate and predict outcomes of subaxial cervical spine trauma patients. These results form the basis for the development of a disease-specific surgeon reported outcome measure, which will be a helpful tool in research and clinical practice. 4.

Mid arm circumference (MAC) and body mass index (BMI)--the two important auxologic parameters in neonates.

PubMed

Nair, R Bindu; Elizabeth, K E; Geetha, S; Varghese, Sarath

2006-10-01

Even though birth weight is the most sensitive predictor of health and outcome, accurate weighing and proper recording are not done in most developing countries. Most neonates lose 10% of body weight soon after birth and when such babies subsequently come for medical care, it becomes difficult to know whether the baby was low birth weight (LBW) at birth or not, to predict the outcome. Among the many surrogate auxologic parameters to identify LBW babies, mid arm circumference (MAC) was found to be the most useful and simplest. At a cut off of 9 cm, with a sensitivity of 92% and a specificity of 90.5% to identify LBW, MAC is recommended as an alternative measurement. Ponderal index is measured in neonatal period to identify growth retardation. Body mass index (BMI) is a very useful index in children and adults to identify obesity/chronic energy deficiency (CED). Tracking of BMI from neonatal period to adulthood is recommended to plan intervention and predict outcome. The mean BMI observed in the present study was 12.86 kg/m2 close to the expected of 13.

Technical parameters for specifying imagery requirements

NASA Technical Reports Server (NTRS)

Coan, Paul P.; Dunnette, Sheri J.

1994-01-01

Providing visual information acquired from remote events to various operators, researchers, and practitioners has become progressively more important as the application of special skills in alien or hazardous situations increases. To provide an understanding of the technical parameters required to specify imagery, we have identified, defined, and discussed seven salient characteristics of images: spatial resolution, linearity, luminance resolution, spectral discrimination, temporal discrimination, edge definition, and signal-to-noise ratio. We then describe a generalizing imaging system and identified how various parts of the system affect the image data. To emphasize the different applications of imagery, we have constrasted the common television system with the significant parameters of a televisual imaging system for technical applications. Finally, we have established a method by which the required visual information can be specified by describing certain technical parameters which are directly related to the information content of the imagery. This method requires the user to complete a form listing all pertinent data requirements for the imagery.

To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis

PubMed Central

Guan, Yiqing; Wei, Jianhui; Zhang, Danrong; Zu, Mingjuan; Zhang, Liru

2013-01-01

Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents. PMID:23737715

The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?

PubMed

Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J

2013-10-28

Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.

Theory of runaway electrons in ITER: Equations, important parameters, and implications for mitigation

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

Boozer, Allen H., E-mail: ahb17@columbia.edu

2015-03-15

The plasma current in ITER cannot be allowed to transfer from thermal to relativistic electron carriers. The potential for damage is too great. Before the final design is chosen for the mitigation system to prevent such a transfer, it is important that the parameters that control the physics be understood. Equations that determine these parameters and their characteristic values are derived. The mitigation benefits of the injection of impurities with the highest possible atomic number Z and the slowing plasma cooling during halo current mitigation to ≳40 ms in ITER are discussed. The highest possible Z increases the poloidal flux consumptionmore » required for each e-fold in the number of relativistic electrons and reduces the number of high energy seed electrons from which exponentiation builds. Slow cooling of the plasma during halo current mitigation also reduces the electron seed. Existing experiments could test physics elements required for mitigation but cannot carry out an integrated demonstration. ITER itself cannot carry out an integrated demonstration without excessive danger of damage unless the probability of successful mitigation is extremely high. The probability of success depends on the reliability of the theory. Equations required for a reliable Monte Carlo simulation are derived.« less

Unsteady hovering wake parameters identified from dynamic model tests, part 1

NASA Technical Reports Server (NTRS)

Hohenemser, K. H.; Crews, S. T.

1977-01-01

The development of a 4-bladed model rotor is reported that can be excited with a simple eccentric mechanism in progressing and regressing modes with either harmonic or transient inputs. Parameter identification methods were applied to the problem of extracting parameters for linear perturbation models, including rotor dynamic inflow effects, from the measured blade flapping responses to transient pitch stirring excitations. These perturbation models were then used to predict blade flapping response to other pitch stirring transient inputs, and rotor wake and blade flapping responses to harmonic inputs. The viability and utility of using parameter identification methods for extracting the perturbation models from transients are demonstrated through these combined analytical and experimental studies.

Identifying Elements of ICU Care That Families Report as Important But Unsatisfactory

PubMed Central

Osborn, Tristan R.; Curtis, J. Randall; Nielsen, Elizabeth L.; Back, Anthony L.; Shannon, Sarah E.

2012-01-01

Background: One in five deaths in the United States occurs in the ICU, and many of these deaths are experienced as less than optimal by families of dying people. The current study investigated the relationship between family satisfaction with ICU care and overall ratings of the quality of dying as a means of identifying targets for improving end-of-life experiences for patients and families. Methods: This multisite cross-sectional study surveyed families of patients who died in the ICU in one of 15 hospitals in western Washington State. Measures included the Family Satisfaction in the ICU (FS-ICU) and the Single-Item Quality of Dying (QOD-1) questionnaires. Associations between FS-ICU items and the QOD-1 were examined using multivariate linear regression controlling for patient and family demographics and hospital site. Results: Questionnaires were returned for 1,290 of 2,850 decedents (45%). Higher QOD-1 scores were significantly associated (all P < .05) with (1) perceived nursing skill and competence (β = 0.15), (2) support for family as decision-makers (β = 0.10), (3) family control over the patient’s care (β = 0.18), and (4) ICU atmosphere (β = 0.12). FS-ICU items that received low ratings and correlated with higher QOD-1 scores (ie, important items with room for improvement) were (1) support of family as decision-maker, (2) family control over patient’s care, and (3) ICU atmosphere. Conclusions: Increased support for families as decision-makers and for their desired level of control over patient care along with improvements in the ICU atmosphere were identified as aspects of the ICU experience that may be important targets for quality improvement. Trial registry: ClinicalTrials.gov; No.: NCT00685893; URL: www.clinicaltrials.gov. PMID:22661455

Nondimensional parameters and equations for buckling of symmetrically laminated thin elastic shallow shells

NASA Technical Reports Server (NTRS)

Nemeth, Michael P.

1991-01-01

A method of deriving nondimensional equations and identifying the fundamental parameters associated with bifurcation buckling of anisotropic shells subjected to combined loads is presented. The procedure and rationale used to obtain useful nondimensional forms of the transverse equilibrium and compatibility equations for buckling are presented. Fundamental parameters are identified that represent the importance of both membrane and bending orthotropy and anisotropy on the results.

What Parameters Do Students Value in Business School Rankings?

ERIC Educational Resources Information Center

Mårtensson, Pär; Richtnér, Anders

2015-01-01

The starting point of this paper is the question: Which issues do students think are important when choosing a higher education institution, and how are they related to the factors taken into consideration in ranking institutions? The aim is to identify and rank the parameters students perceive as important when choosing their place of education.…

Chronology: An Important (and Potentially Accessible) Parameter in Understanding Europa Surface-Subsurface Material Interchange, Burial, and Resurfacing Processes

NASA Technical Reports Server (NTRS)

Swindle, T. D.

2001-01-01

Time is an important parameter in understanding the interaction of the surface and subsurface of Europa. It should be possible to determine potassium-argon and cosmic ray exposure ages in situ on the surface of Europa. Additional information is contained in the original extended abstract.

Integrating retention soil filters into urban hydrologic models - Relevant processes and important parameters

NASA Astrophysics Data System (ADS)

Bachmann-Machnik, Anna; Meyer, Daniel; Waldhoff, Axel; Fuchs, Stephan; Dittmer, Ulrich

2018-04-01

Retention Soil Filters (RSFs), a form of vertical flow constructed wetlands specifically designed for combined sewer overflow (CSO) treatment, have proven to be an effective tool to mitigate negative impacts of CSOs on receiving water bodies. Long-term hydrologic simulations are used to predict the emissions from urban drainage systems during planning of stormwater management measures. So far no universally accepted model for RSF simulation exists. When simulating hydraulics and water quality in RSFs, an appropriate level of detail must be chosen for reasonable balancing between model complexity and model handling, considering the model input's level of uncertainty. The most crucial parameters determining the resultant uncertainties of the integrated sewer system and filter bed model were identified by evaluating a virtual drainage system with a Retention Soil Filter for CSO treatment. To determine reasonable parameter ranges for RSF simulations, data of 207 events from six full-scale RSF plants in Germany were analyzed. Data evaluation shows that even though different plants with varying loading and operation modes were examined, a simple model is sufficient to assess relevant suspended solids (SS), chemical oxygen demand (COD) and NH4 emissions from RSFs. Two conceptual RSF models with different degrees of complexity were assessed. These models were developed based on evaluation of data from full scale RSF plants and column experiments. Incorporated model processes are ammonium adsorption in the filter layer and degradation during subsequent dry weather period, filtration of SS and particulate COD (XCOD) to a constant background concentration and removal of solute COD (SCOD) by a constant removal rate during filter passage as well as sedimentation of SS and XCOD in the filter overflow. XCOD, SS and ammonium loads as well as ammonium concentration peaks are discharged primarily via RSF overflow not passing through the filter bed. Uncertainties of the integrated

Identifying pneumonia outbreaks of public health importance: can emergency department data assist in earlier identification?

PubMed

Hope, Kirsty; Durrheim, David N; Muscatello, David; Merritt, Tony; Zheng, Wei; Massey, Peter; Cashman, Patrick; Eastwood, Keith

2008-08-01

To retrospectively review the performance of a near real-time Emergency Department (ED) Syndromic Surveillance System operating in New South Wales for identifying pneumonia outbreaks of public health importance. Retrospective data was obtained from the NSW Emergency Department data collection for a rural hospital that has experienced a cluster of pneumonia diagnoses among teenage males in August 2006. ED standard reports were examined for signals in the overall count for each respiratory syndrome, and for elevated counts in individual subgroups including; age, sex and admission to hospital status. Using the current thresholds, the ED syndromic surveillance system would have trigged a signal for pneumonia syndrome in children aged 5-16 years four days earlier than the notification by a paediatrician and this signal was maintained for 14 days. If the ED syndromic surveillance system had been operating it could have identified the outbreak earlier than the paediatrician's notification. This may have permitted an earlier public health response. By understanding the behaviour of syndromes during outbreaks of public health importance, response protocols could be developed to facilitate earlier implementation of control measures.

On the importance of identifying, characterizing, and predicting fundamental phenomena towards microbial electrochemistry applications.

PubMed

Torres, César Iván

2014-06-01

The development of microbial electrochemistry research toward technological applications has increased significantly in the past years, leading to many process configurations. This short review focuses on the need to identify and characterize the fundamental phenomena that control the performance of microbial electrochemical cells (MXCs). Specifically, it discusses the importance of recent efforts to discover and characterize novel microorganisms for MXC applications, as well as recent developments to understand transport limitations in MXCs. As we increase our understanding of how MXCs operate, it is imperative to continue modeling efforts in order to effectively predict their performance, design efficient MXC technologies, and implement them commercially. Thus, the success of MXC technologies largely depends on the path of identifying, understanding, and predicting fundamental phenomena that determine MXC performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Using fixed-parameter and random-parameter ordered regression models to identify significant factors that affect the severity of drivers' injuries in vehicle-train collisions.

PubMed

Dabbour, Essam; Easa, Said; Haider, Murtaza

2017-10-01

This study attempts to identify significant factors that affect the severity of drivers' injuries when colliding with trains at railroad-grade crossings by analyzing the individual-specific heterogeneity related to those factors over a period of 15 years. Both fixed-parameter and random-parameter ordered regression models were used to analyze records of all vehicle-train collisions that occurred in the United States from January 1, 2001 to December 31, 2015. For fixed-parameter ordered models, both probit and negative log-log link functions were used. The latter function accounts for the fact that lower injury severity levels are more probable than higher ones. Separate models were developed for heavy and light-duty vehicles. Higher train and vehicle speeds, female, and young drivers (below the age of 21 years) were found to be consistently associated with higher severity of drivers' injuries for both heavy and light-duty vehicles. Furthermore, favorable weather, light-duty trucks (including pickup trucks, panel trucks, mini-vans, vans, and sports-utility vehicles), and senior drivers (above the age of 65 years) were found be consistently associated with higher severity of drivers' injuries for light-duty vehicles only. All other factors (e.g. air temperature, the type of warning devices, darkness conditions, and highway pavement type) were found to be temporally unstable, which may explain the conflicting findings of previous studies related to those factors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Barcode Identifiers as a Practical Tool for Reliable Species Assignment of Medically Important Black Yeast Species

PubMed Central

Heinrichs, Guido; de Hoog, G. Sybren

2012-01-01

Herpotrichiellaceous black yeasts and relatives comprise severe pathogens flanked by nonpathogenic environmental siblings. Reliable identification by conventional methods is notoriously difficult. Molecular identification is hampered by the sequence variability in the internal transcribed spacer (ITS) domain caused by difficult-to-sequence homopolymeric regions and by poor taxonomic attribution of sequences deposited in GenBank. Here, we present a potential solution using short barcode identifiers (27 to 50 bp) based on ITS2 ribosomal DNA (rDNA), which allows unambiguous definition of species-specific fragments. Starting from proven sequences of ex-type and authentic strains, we were able to describe 103 identifiers. Multiple BLAST searches of these proposed barcode identifiers in GenBank revealed uniqueness for 100 taxonomic entities, whereas the three remaining identifiers each matched with two entities, but the species of these identifiers could easily be discriminated by differences in the remaining ITS regions. Using the proposed barcode identifiers, a 4.1-fold increase of 100% matches in GenBank was achieved in comparison to the classical approach using the complete ITS sequences. The proposed barcode identifiers will be made accessible for the diagnostic laboratory in a permanently updated online database, thereby providing a highly practical, reliable, and cost-effective tool for identification of clinically important black yeasts and relatives. PMID:22785187

Identifying 1st instar larvae for three forensically important blowfly species using "fingerprint" cuticular hydrocarbon analysis.

PubMed

Moore, Hannah E; Adam, Craig D; Drijfhout, Falko P

2014-07-01

Calliphoridae are known to be the most forensically important insects when it comes to establishing the minimum post mortem interval (PMImin) in criminal investigations. The first step in calculating the PMImin is to identify the larvae present to species level. Accurate identification which is conventionally carried out by morphological analysis is crucial because different insects have different life stage timings. Rapid identification in the immature larvae stages would drastically cut time in criminal investigations as it would eliminate the need to rear larvae to adult flies to determine the species. Cuticular hydrocarbon analysis on 1st instar larvae has been applied to three forensically important blowflies; Lucilia sericata, Calliphora vicina and Calliphora vomitoria, using gas chromatography-mass spectrometry (GC-MS) and principal component analysis (PCA). The results show that each species holds a distinct "fingerprint" hydrocarbon profile, allowing for accurate identification to be established in 1-day old larvae, when it can be challenging to apply morphological criteria. Consequently, this GC-MS based technique could accelerate and strengthen the identification process, not only for forensically important species, but also for other entomological samples which are hard to identify using morphological features. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Important parameters affecting the cell voltage of aqueous electrical double-layer capacitors

NASA Astrophysics Data System (ADS)

Wu, Tzu-Ho; Hsu, Chun-Tsung; Hu, Chi-Chang; Hardwick, Laurence J.

2013-11-01

This study discusses and demonstrates how the open-circuit potential and charges stored in the working potential window on positive and negative electrodes affect the cell voltage of carbon-based electrical double-layer capacitors (EDLCs) in aqueous electrolytes. An EDLC consisting of two activated carbon electrodes is employed as the model system for identifying these key parameters although the potential window of water decomposition can be simply determined by voltammetric methods. First, the capacitive performances of an EDLC with the same charge on positive and negative electrodes are evaluated by cyclic voltammetric, charge-discharge, electrochemical impedance spectroscopic (EIS) analyses, and inductance-capacitance-resistance meter (LCR meter). The principles for obtaining the highest acceptable cell voltage of such symmetric ECs with excellent reversibility and capacitor-like behaviour are proposed. Aqueous charge-balanced EDLCs can be operated as high as 2.0 V with high energy efficiency (about 90%) and only 4% capacitance loss after the 600-cycle stability checking. The necessity of charge balance (but not capacitance balance) for positive and negative electrodes is substantiated from the lower acceptable cell voltage of charge-unbalanced EDLCs.

ON IDENTIFIABILITY OF NONLINEAR ODE MODELS AND APPLICATIONS IN VIRAL DYNAMICS

PubMed Central

MIAO, HONGYU; XIA, XIAOHUA; PERELSON, ALAN S.; WU, HULIN

2011-01-01

Ordinary differential equations (ODE) are a powerful tool for modeling dynamic processes with wide applications in a variety of scientific fields. Over the last 2 decades, ODEs have also emerged as a prevailing tool in various biomedical research fields, especially in infectious disease modeling. In practice, it is important and necessary to determine unknown parameters in ODE models based on experimental data. Identifiability analysis is the first step in determing unknown parameters in ODE models and such analysis techniques for nonlinear ODE models are still under development. In this article, we review identifiability analysis methodologies for nonlinear ODE models developed in the past one to two decades, including structural identifiability analysis, practical identifiability analysis and sensitivity-based identifiability analysis. Some advanced topics and ongoing research are also briefly reviewed. Finally, some examples from modeling viral dynamics of HIV, influenza and hepatitis viruses are given to illustrate how to apply these identifiability analysis methods in practice. PMID:21785515

Report: EPA Can Better Reduce Risks From Illegal Pesticides by Effectively Identifying Imports for Inspection and Sampling

EPA Pesticide Factsheets

Report #17-P-0412, September 28, 2017. Low rates of inspections and sampling can create a risk that the EPA may not be identifying and deterring the import of pesticides harmful to people or the environment.

Dynamic Contrast-Enhanced MRI of Cervical Cancers: Temporal Percentile Screening of Contrast Enhancement Identifies Parameters for Prediction of Chemoradioresistance

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

Andersen, Erlend K.F.; Hole, Knut Hakon; Lund, Kjersti V.

Purpose: To systematically screen the tumor contrast enhancement of locally advanced cervical cancers to assess the prognostic value of two descriptive parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods and Materials: This study included a prospectively collected cohort of 81 patients who underwent DCE-MRI with gadopentetate dimeglumine before chemoradiotherapy. The following descriptive DCE-MRI parameters were extracted voxel by voxel and presented as histograms for each time point in the dynamic series: normalized relative signal increase (nRSI) and normalized area under the curve (nAUC). The first to 100th percentiles of the histograms were included in a log-rank survival test,more » resulting in p value and relative risk maps of all percentile-time intervals for each DCE-MRI parameter. The maps were used to evaluate the robustness of the individual percentile-time pairs and to construct prognostic parameters. Clinical endpoints were locoregional control and progression-free survival. The study was approved by the institutional ethics committee. Results: The p value maps of nRSI and nAUC showed a large continuous region of percentile-time pairs that were significantly associated with locoregional control (p < 0.05). These parameters had prognostic impact independent of tumor stage, volume, and lymph node status on multivariate analysis. Only a small percentile-time interval of nRSI was associated with progression-free survival. Conclusions: The percentile-time screening identified DCE-MRI parameters that predict long-term locoregional control after chemoradiotherapy of cervical cancer.« less

Using the Developmental Gene Bicoid to Identify Species of Forensically Important Blowflies (Diptera: Calliphoridae)

PubMed Central

Park, Seong Hwan; Park, Chung Hyun; Zhang, Yong; Piao, Huguo; Chung, Ukhee; Kim, Seong Yoon; Ko, Kwang Soo; Yi, Cheong-Ho; Jo, Tae-Ho; Hwang, Juck-Joon

2013-01-01

Identifying species of insects used to estimate postmortem interval (PMI) is a major subject in forensic entomology. Because forensic insect specimens are morphologically uniform and are obtained at various developmental stages, DNA markers are greatly needed. To develop new autosomal DNA markers to identify species, partial genomic sequences of the bicoid (bcd) genes, containing the homeobox and its flanking sequences, from 12 blowfly species (Aldrichina grahami, Calliphora vicina, Calliphora lata, Triceratopyga calliphoroides, Chrysomya megacephala, Chrysomya pinguis, Phormia regina, Lucilia ampullacea, Lucilia caesar, Lucilia illustris, Hemipyrellia ligurriens and Lucilia sericata; Calliphoridae: Diptera) were determined and analyzed. This study first sequenced the ten blowfly species other than C. vicina and L. sericata. Based on the bcd sequences of these 12 blowfly species, a phylogenetic tree was constructed that discriminates the subfamilies of Calliphoridae (Luciliinae, Chrysomyinae, and Calliphorinae) and most blowfly species. Even partial genomic sequences of about 500 bp can distinguish most blowfly species. The short intron 2 and coding sequences downstream of the bcd homeobox in exon 3 could be utilized to develop DNA markers for forensic applications. These gene sequences are important in the evolution of insect developmental biology and are potentially useful for identifying insect species in forensic science. PMID:23586044

American Bird conservancy's approach to the U.S. Important Bird Area Program - identifying the top 500 global sites

Treesearch

Robert M. Chipley

2005-01-01

The idea for the Important Bird Area Program originated in a series of studies in the early 1980s conducted by BirdLife International. Recognizing that these studies could become a powerful tool for conservation, BirdLife International began an effort to identify and gather data regarding the most important areas for birds in Europe and to make this information...

Motion capture based identification of the human body inertial parameters.

PubMed

Venture, Gentiane; Ayusawa, Ko; Nakamura, Yoshihiko

2008-01-01

Identification of body inertia, masses and center of mass is an important data to simulate, monitor and understand dynamics of motion, to personalize rehabilitation programs. This paper proposes an original method to identify the inertial parameters of the human body, making use of motion capture data and contact forces measurements. It allows in-vivo painless estimation and monitoring of the inertial parameters. The method is described and then obtained experimental results are presented and discussed.

Capillary density: An important parameter in nailfold capillaroscopy.

PubMed

Emrani, Zahra; Karbalaie, Abdolamir; Fatemi, Alimohammad; Etehadtavakol, Mahnaz; Erlandsson, Björn-Erik

2017-01-01

Nailfold capillaroscopy is one of the various noninvasive bioengineering methods used to investigate skin microcirculation. It is an effective examination for assessing microvascular changes in the peripheral circulation; hence it has a significant role for the diagnosis of Systemic sclerosis with the classic changes of giant capillaries as well as the decline in capillary density with capillary dropout. The decline in capillary density is one of microangiopathic features existing in connective tissue disease. It is detectable with nailfold capillaroscopy. This parameter is assessed by applying quantitative measurement. In this article, we reviewed a common method for calculating the capillary density and the relation between the number of capillaries as well as the existence of digital ulcers, pulmonary arterial hypertension, autoantibodies, scleroderma patterns and different scoring system. Copyright © 2016 Elsevier Inc. All rights reserved.

A study of parameter identification

NASA Technical Reports Server (NTRS)

Herget, C. J.; Patterson, R. E., III

1978-01-01

A set of definitions for deterministic parameter identification ability were proposed. Deterministic parameter identificability properties are presented based on four system characteristics: direct parameter recoverability, properties of the system transfer function, properties of output distinguishability, and uniqueness properties of a quadratic cost functional. Stochastic parameter identifiability was defined in terms of the existence of an estimation sequence for the unknown parameters which is consistent in probability. Stochastic parameter identifiability properties are presented based on the following characteristics: convergence properties of the maximum likelihood estimate, properties of the joint probability density functions of the observations, and properties of the information matrix.

Practical identifiability analysis of a minimal cardiovascular system model.

PubMed

Pironet, Antoine; Docherty, Paul D; Dauby, Pierre C; Chase, J Geoffrey; Desaive, Thomas

2017-01-17

Parameters of mathematical models of the cardiovascular system can be used to monitor cardiovascular state, such as total stressed blood volume status, vessel elastance and resistance. To do so, the model parameters have to be estimated from data collected at the patient's bedside. This work considers a seven-parameter model of the cardiovascular system and investigates whether these parameters can be uniquely determined using indices derived from measurements of arterial and venous pressures, and stroke volume. An error vector defined the residuals between the simulated and reference values of the seven clinically available haemodynamic indices. The sensitivity of this error vector to each model parameter was analysed, as well as the collinearity between parameters. To assess practical identifiability of the model parameters, profile-likelihood curves were constructed for each parameter. Four of the seven model parameters were found to be practically identifiable from the selected data. The remaining three parameters were practically non-identifiable. Among these non-identifiable parameters, one could be decreased as much as possible. The other two non-identifiable parameters were inversely correlated, which prevented their precise estimation. This work presented the practical identifiability analysis of a seven-parameter cardiovascular system model, from limited clinical data. The analysis showed that three of the seven parameters were practically non-identifiable, thus limiting the use of the model as a monitoring tool. Slight changes in the time-varying function modeling cardiac contraction and use of larger values for the reference range of venous pressure made the model fully practically identifiable. Copyright © 2017. Published by Elsevier B.V.

The importance of consumption of the epidermis in malignant melanoma and correlation with clinicopathological prognostic parameters.

PubMed

Seçkin, Selda; Ozgũn, Elmas

2011-01-01

The aim of the study was to investigate the importance of consumption of the epidermis as an additional diagnostic criteria for malignant melanoma and to evaluate its relationship to clinicopathological findings. The age, gender, localization of the lesion and the histopathological parameters such as tumor type, Breslow thickness, ulceration, Clark's level, mitosis/mm2, lymphocytic infiltration were noted in 40 malignant melanoma cases. Consumption of the epidermis was evaluated in tumor sections. Consumption of the epidermis (COE) due to thinning of the epidermis and loss of rete ridges was noted as (+) or (-). Furthermore, COE was compared with clinical and histopathological parameters. The Shapiro Wilk and Logistic Regression tests were used for statistical analysis. The results were accepted as significant if the p value was < 0.05. COE was detected in 60% (24/40) of malignant melanoma cases. A positive correlation was present between COE and head and neck localization (p = 0,698), superficial spreading melanoma (p = 0,341), ulceration (p = 0,097) and brisk lymphocytic infiltration (p = 0,200) but the results were not statistically significant. COE was frequently detected in males but the difference was not statistically significant (p = 0.796). There was no correlation or significant statistical association between COE and age, Breslow thickness, Clark's level or the mitotic index. The detection of COE in most of the patients suggests that COE could be a histopathological criterion in the diagnosis of malignant melanoma. The frequent association between COE and the presence of ulceration could also direct attention to COE as regards prognostic importance.

Identifying content for the glaucoma-specific item bank to measure quality-of-life parameters.

PubMed

Khadka, Jyoti; McAlinden, Colm; Craig, Jamie E; Fenwick, Eva K; Lamoureux, Ecosse L; Pesudovs, Konrad

2015-01-01

Patient-reported outcomes (PROs) have become essential clinical trial end points. However, a comprehensive, multidimensional, patient-relevant, and precise glaucoma-specific PRO instrument is not available. Therefore, the purpose of this study was to identify content for a new, glaucoma-specific, quality-of-life (QOL) item bank. Content identification was undertaken in 5 phases: (1) identification of extant items in glaucoma-specific instruments and the qualitative literature; (2) focus groups and interviews with glaucoma patients; (3) item classification and selection; (4) expert review and revision of items; and (5) cognitive interviews with patients. A total of 737 unique items (extant items from PRO instruments, 247; qualitative articles, 14 items; focus groups and semistructured interviews, 476 items) were identified. These items were classified into 10 QOL domains. Four criteria (item redundancy, item inconsistent with domain definition, item content too narrow to have wider applicability, and item clarity) were used to remove and refine the items. After the cognitive interviews, the final minimally representative item set had a total of 342 unique items belonging to 10 domains: activity limitation (88), mobility (20), visual symptoms (19), ocular surface symptoms (22), general symptoms (15), convenience (39), health concerns (45), emotional well-being (49), social issues (23), and economic issues (22). The systematic content identification process identified 10 QOL domains, which were important to patients with glaucoma. The majority of the items were identified from the patient-specific focus groups and semistructured interviews suggesting that the existing PRO instruments do not adequately address QOL issues relevant to individuals with glaucoma.

Important technical parameters are not presented in reports of intraoral digital radiography in endodontic treatment: recommendations for future studies.

PubMed

Konishi, Masaru; Lindh, Christina; Nilsson, Mats; Tanimoto, Keiji; Rohlin, Madeleine

2012-08-01

The aims of this study were to review the literature on intraoral digital radiography in endodontic treatment with focus on technical parameters and to propose recommendations for improving the quality of reports in future publications. Two electronic databases were searched. Titles and abstracts were selected according to preestablished criteria. Data were extracted using a model of image acquisition and interpretation. The literature search yielded 233 titles and abstracts; 61 reports were read in full text. Recent reports presented technical parameters more thoroughly than older reports. Most reported important parameters for the x-ray unit, but for image interpretation only about one-half of the publications cited resolution of the display system and fewer than one-half bit depth of the graphics card. The methodologic quality of future publications must be improved to permit replication of studies and comparison of results between studies in dental digital radiography. Our recommendations can improve the quality of studies on diagnostic accuracy. Copyright © 2012 Mosby, Inc. All rights reserved.

Structural identifiability of cyclic graphical models of biological networks with latent variables.

PubMed

Wang, Yulin; Lu, Na; Miao, Hongyu

2016-06-13

Graphical models have long been used to describe biological networks for a variety of important tasks such as the determination of key biological parameters, and the structure of graphical model ultimately determines whether such unknown parameters can be unambiguously obtained from experimental observations (i.e., the identifiability problem). Limited by resources or technical capacities, complex biological networks are usually partially observed in experiment, which thus introduces latent variables into the corresponding graphical models. A number of previous studies have tackled the parameter identifiability problem for graphical models such as linear structural equation models (SEMs) with or without latent variables. However, the limited resolution and efficiency of existing approaches necessarily calls for further development of novel structural identifiability analysis algorithms. An efficient structural identifiability analysis algorithm is developed in this study for a broad range of network structures. The proposed method adopts the Wright's path coefficient method to generate identifiability equations in forms of symbolic polynomials, and then converts these symbolic equations to binary matrices (called identifiability matrix). Several matrix operations are introduced for identifiability matrix reduction with system equivalency maintained. Based on the reduced identifiability matrices, the structural identifiability of each parameter is determined. A number of benchmark models are used to verify the validity of the proposed approach. Finally, the network module for influenza A virus replication is employed as a real example to illustrate the application of the proposed approach in practice. The proposed approach can deal with cyclic networks with latent variables. The key advantage is that it intentionally avoids symbolic computation and is thus highly efficient. Also, this method is capable of determining the identifiability of each single parameter and

The structural identifiability and parameter estimation of a multispecies model for the transmission of mastitis in dairy cows with postmilking teat disinfection.

PubMed

White, L J; Evans, N D; Lam, T J G M; Schukken, Y H; Medley, G F; Godfrey, K R; Chappell, M J

2002-01-01

A mathematical model for the transmission of two interacting classes of mastitis causing bacterial pathogens in a herd of dairy cows is presented and applied to a specific data set. The data were derived from a field trial of a specific measure used in the control of these pathogens, where half the individuals were subjected to the control and in the others the treatment was discontinued. The resultant mathematical model (eight non-linear simultaneous ordinary differential equations) therefore incorporates heterogeneity in the host as well as the infectious agent and consequently the effects of control are intrinsic in the model structure. A structural identifiability analysis of the model is presented demonstrating that the scope of the novel method used allows application to high order non-linear systems. The results of a simultaneous estimation of six unknown system parameters are presented. Previous work has only estimated a subset of these either simultaneously or individually. Therefore not only are new estimates provided for the parameters relating to the transmission and control of the classes of pathogens under study, but also information about the relationships between them. We exploit the close link between mathematical modelling, structural identifiability analysis, and parameter estimation to obtain biological insights into the system modelled.

Parameter Validation for Evaluation of Spaceflight Hardware Reusability

NASA Technical Reports Server (NTRS)

Childress-Thompson, Rhonda; Dale, Thomas L.; Farrington, Phillip

2017-01-01

Within recent years, there has been an influx of companies around the world pursuing reusable systems for space flight. Much like NASA, many of these new entrants are learning that reusable systems are complex and difficult to acheive. For instance, in its first attempts to retrieve spaceflight hardware for future reuse, SpaceX unsuccessfully tried to land on a barge at sea, resulting in a crash-landing. As this new generation of launch developers continues to develop concepts for reusable systems, having a systematic approach for determining the most effective systems for reuse is paramount. Three factors that influence the effective implementation of reusability are cost, operability and reliability. Therefore, a method that integrates these factors into the decision-making process must be utilized to adequately determine whether hardware used in space flight should be reused or discarded. Previous research has identified seven features that contribute to the successful implementation of reusability for space flight applications, defined reusability for space flight applications, highlighted the importance of reusability, and presented areas that hinder successful implementation of reusability. The next step is to ensure that the list of reusability parameters previously identified is comprehensive, and any duplication is either removed or consolidated. The characteristics to judge the seven features as good indicators for successful reuse are identified and then assessed using multiattribute decision making. Next, discriminators in the form of metrics or descriptors are assigned to each parameter. This paper explains the approach used to evaluate these parameters, define the Measures of Effectiveness (MOE) for reusability, and quantify these parameters. Using the MOEs, each parameter is assessed for its contribution to the reusability of the hardware. Potential data sources needed to validate the approach will be identified.

Scanning genomic areas under selection sweep and association mapping as tools to identify horticultural important genes in watermelon

USDA-ARS?s Scientific Manuscript database

Watermelon (Citrullus lanatus var. lanatus) contains 88% water, sugars, and several important health-related compounds, including lycopene, citrulline, arginine, and glutathione. The current genetic diversity study uses microsatellites with known map positions to identify genomic regions that under...

Identifying effective connectivity parameters in simulated fMRI: a direct comparison of switching linear dynamic system, stochastic dynamic causal, and multivariate autoregressive models

PubMed Central

Smith, Jason F.; Chen, Kewei; Pillai, Ajay S.; Horwitz, Barry

2013-01-01

The number and variety of connectivity estimation methods is likely to continue to grow over the coming decade. Comparisons between methods are necessary to prune this growth to only the most accurate and robust methods. However, the nature of connectivity is elusive with different methods potentially attempting to identify different aspects of connectivity. Commonalities of connectivity definitions across methods upon which base direct comparisons can be difficult to derive. Here, we explicitly define “effective connectivity” using a common set of observation and state equations that are appropriate for three connectivity methods: dynamic causal modeling (DCM), multivariate autoregressive modeling (MAR), and switching linear dynamic systems for fMRI (sLDSf). In addition while deriving this set, we show how many other popular functional and effective connectivity methods are actually simplifications of these equations. We discuss implications of these connections for the practice of using one method to simulate data for another method. After mathematically connecting the three effective connectivity methods, simulated fMRI data with varying numbers of regions and task conditions is generated from the common equation. This simulated data explicitly contains the type of the connectivity that the three models were intended to identify. Each method is applied to the simulated data sets and the accuracy of parameter identification is analyzed. All methods perform above chance levels at identifying correct connectivity parameters. The sLDSf method was superior in parameter estimation accuracy to both DCM and MAR for all types of comparisons. PMID:23717258

Assessing the sensitivity of a land-surface scheme to the parameter values using a single column model

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

Pitman, A.J.

The sensitivity of a land-surface scheme (the Biosphere Atmosphere Transfer Scheme, BATS) to its parameter values was investigated using a single column model. Identifying which parameters were important in controlling the turbulent energy fluxes, temperature, soil moisture, and runoff was dependent upon many factors. In the simulation of a nonmoisture-stressed tropical forest, results were dependent on a combination of reservoir terms (soil depth, root distribution), flux efficiency terms (roughness length, stomatal resistance), and available energy (albedo). If moisture became limited, the reservoir terms increased in importance because the total fluxes predicted depended on moisture availability and not on the ratemore » of transfer between the surface and the atmosphere. The sensitivity shown by BATS depended on which vegetation type was being simulated, which variable was used to determine sensitivity, the magnitude and sign of the parameter change, the climate regime (precipitation amount and frequency), and soil moisture levels and proximity to wilting. The interactions between these factors made it difficult to identify the most important parameters in BATS. Therefore, this paper does not argue that a particular set of parameters is important in BATS, rather it shows that no general ranking of parameters is possible. It is also emphasized that using `stand-alone` forcing to examine the sensitivity of a land-surface scheme to perturbations, in either parameters or the atmosphere, is unreliable due to the lack of surface-atmospheric feedbacks.« less

Identifying the domains of context important to implementation science: a study protocol.

PubMed

Squires, Janet E; Graham, Ian D; Hutchinson, Alison M; Michie, Susan; Francis, Jill J; Sales, Anne; Brehaut, Jamie; Curran, Janet; Ivers, Noah; Lavis, John; Linklater, Stefanie; Fenton, Shannon; Noseworthy, Thomas; Vine, Jocelyn; Grimshaw, Jeremy M

2015-09-28

There is growing recognition that "context" can and does modify the effects of implementation interventions aimed at increasing healthcare professionals' use of research evidence in clinical practice. However, conceptual clarity about what exactly comprises "context" is lacking. The purpose of this research program is to develop, refine, and validate a framework that identifies the key domains of context (and their features) that can facilitate or hinder (1) healthcare professionals' use of evidence in clinical practice and (2) the effectiveness of implementation interventions. A multi-phased investigation of context using mixed methods will be conducted. The first phase is a concept analysis of context using the Walker and Avant method to distinguish between the defining and irrelevant attributes of context. This phase will result in a preliminary framework for context that identifies its important domains and their features according to the published literature. The second phase is a secondary analysis of qualitative data from 13 studies of interviews with 312 healthcare professionals on the perceived barriers and enablers to their application of research evidence in clinical practice. These data will be analyzed inductively using constant comparative analysis. For the third phase, we will conduct semi-structured interviews with key health system stakeholders and change agents to elicit their knowledge and beliefs about the contextual features that influence the effectiveness of implementation interventions and healthcare professionals' use of evidence in clinical practice. Results from all three phases will be synthesized using a triangulation protocol to refine the context framework drawn from the concept analysis. The framework will then be assessed for content validity using an iterative Delphi approach with international experts (researchers and health system stakeholders/change agents). This research program will result in a framework that identifies the

A confidence building exercise in data and identifiability: Modeling cancer chemotherapy as a case study.

PubMed

Eisenberg, Marisa C; Jain, Harsh V

2017-10-27

Mathematical modeling has a long history in the field of cancer therapeutics, and there is increasing recognition that it can help uncover the mechanisms that underlie tumor response to treatment. However, making quantitative predictions with such models often requires parameter estimation from data, raising questions of parameter identifiability and estimability. Even in the case of structural (theoretical) identifiability, imperfect data and the resulting practical unidentifiability of model parameters can make it difficult to infer the desired information, and in some cases, to yield biologically correct inferences and predictions. Here, we examine parameter identifiability and estimability using a case study of two compartmental, ordinary differential equation models of cancer treatment with drugs that are cell cycle-specific (taxol) as well as non-specific (oxaliplatin). We proceed through model building, structural identifiability analysis, parameter estimation, practical identifiability analysis and its biological implications, as well as alternative data collection protocols and experimental designs that render the model identifiable. We use the differential algebra/input-output relationship approach for structural identifiability, and primarily the profile likelihood approach for practical identifiability. Despite the models being structurally identifiable, we show that without consideration of practical identifiability, incorrect cell cycle distributions can be inferred, that would result in suboptimal therapeutic choices. We illustrate the usefulness of estimating practically identifiable combinations (in addition to the more typically considered structurally identifiable combinations) in generating biologically meaningful insights. We also use simulated data to evaluate how the practical identifiability of the model would change under alternative experimental designs. These results highlight the importance of understanding the underlying mechanisms

Simple method for quick estimation of aquifer hydrogeological parameters

NASA Astrophysics Data System (ADS)

Ma, C.; Li, Y. Y.

2017-08-01

Development of simple and accurate methods to determine the aquifer hydrogeological parameters was of importance for groundwater resources assessment and management. Aiming at the present issue of estimating aquifer parameters based on some data of the unsteady pumping test, a fitting function of Theis well function was proposed using fitting optimization method and then a unitary linear regression equation was established. The aquifer parameters could be obtained by solving coefficients of the regression equation. The application of the proposed method was illustrated, using two published data sets. By the error statistics and analysis on the pumping drawdown, it showed that the method proposed in this paper yielded quick and accurate estimates of the aquifer parameters. The proposed method could reliably identify the aquifer parameters from long distance observed drawdowns and early drawdowns. It was hoped that the proposed method in this paper would be helpful for practicing hydrogeologists and hydrologists.

Triangulating Principal Effectiveness: How Perspectives of Parents, Teachers, and Assistant Principals Identify the Central Importance of Managerial Skills

ERIC Educational Resources Information Center

Grissom, Jason A.; Loeb, Susanna

2011-01-01

While the importance of effective principals is undisputed, few studies have identified specific skills that principals need to promote school success. This study draws on unique data combining survey responses from principals, assistant principals, teachers, and parents with rich administrative data to determine which principal skills correlate…

GenSSI 2.0: multi-experiment structural identifiability analysis of SBML models.

PubMed

Ligon, Thomas S; Fröhlich, Fabian; Chis, Oana T; Banga, Julio R; Balsa-Canto, Eva; Hasenauer, Jan

2018-04-15

Mathematical modeling using ordinary differential equations is used in systems biology to improve the understanding of dynamic biological processes. The parameters of ordinary differential equation models are usually estimated from experimental data. To analyze a priori the uniqueness of the solution of the estimation problem, structural identifiability analysis methods have been developed. We introduce GenSSI 2.0, an advancement of the software toolbox GenSSI (Generating Series for testing Structural Identifiability). GenSSI 2.0 is the first toolbox for structural identifiability analysis to implement Systems Biology Markup Language import, state/parameter transformations and multi-experiment structural identifiability analysis. In addition, GenSSI 2.0 supports a range of MATLAB versions and is computationally more efficient than its previous version, enabling the analysis of more complex models. GenSSI 2.0 is an open-source MATLAB toolbox and available at https://github.com/genssi-developer/GenSSI. thomas.ligon@physik.uni-muenchen.de or jan.hasenauer@helmholtz-muenchen.de. Supplementary data are available at Bioinformatics online.

Physical characteristics and resistance parameters of typical urban cyclists.

PubMed

Tengattini, Simone; Bigazzi, Alexander York

2018-03-30

This study investigates the rolling and drag resistance parameters and bicycle and cargo masses of typical urban cyclists. These factors are important for modelling of cyclist speed, power and energy expenditure, with applications including exercise performance, health and safety assessments and transportation network analysis. However, representative values for diverse urban travellers have not been established. Resistance parameters were measured utilizing a field coast-down test for 557 intercepted cyclists in Vancouver, Canada. Masses were also measured, along with other bicycle attributes such as tire pressure and size. The average (standard deviation) of coefficient of rolling resistance, effective frontal area, bicycle plus cargo mass, and bicycle-only mass were 0.0077 (0.0036), 0.559 (0.170) m 2 , 18.3 (4.1) kg, and 13.7 (3.3) kg, respectively. The range of measured values is wider and higher than suggested in existing literature, which focusses on sport cyclists. Significant correlations are identified between resistance parameters and rider and bicycle attributes, indicating higher resistance parameters for less sport-oriented cyclists. The findings of this study are important for appropriately characterising the full range of urban cyclists, including commuters and casual riders.

An Examination of Two Procedures for Identifying Consequential Item Parameter Drift

ERIC Educational Resources Information Center

Wells, Craig S.; Hambleton, Ronald K.; Kirkpatrick, Robert; Meng, Yu

2014-01-01

The purpose of the present study was to develop and evaluate two procedures flagging consequential item parameter drift (IPD) in an operational testing program. The first procedure was based on flagging items that exhibit a meaningful magnitude of IPD using a critical value that was defined to represent barely tolerable IPD. The second procedure…

Identification of hydrological model parameter variation using ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Deng, Chao; Liu, Pan; Guo, Shenglian; Li, Zejun; Wang, Dingbao

2016-12-01

Hydrological model parameters play an important role in the ability of model prediction. In a stationary context, parameters of hydrological models are treated as constants; however, model parameters may vary with time under climate change and anthropogenic activities. The technique of ensemble Kalman filter (EnKF) is proposed to identify the temporal variation of parameters for a two-parameter monthly water balance model (TWBM) by assimilating the runoff observations. Through a synthetic experiment, the proposed method is evaluated with time-invariant (i.e., constant) parameters and different types of parameter variations, including trend, abrupt change and periodicity. Various levels of observation uncertainty are designed to examine the performance of the EnKF. The results show that the EnKF can successfully capture the temporal variations of the model parameters. The application to the Wudinghe basin shows that the water storage capacity (SC) of the TWBM model has an apparent increasing trend during the period from 1958 to 2000. The identified temporal variation of SC is explained by land use and land cover changes due to soil and water conservation measures. In contrast, the application to the Tongtianhe basin shows that the estimated SC has no significant variation during the simulation period of 1982-2013, corresponding to the relatively stationary catchment properties. The evapotranspiration parameter (C) has temporal variations while no obvious change patterns exist. The proposed method provides an effective tool for quantifying the temporal variations of the model parameters, thereby improving the accuracy and reliability of model simulations and forecasts.

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq

PubMed Central

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2018-01-01

Flax (Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits. PMID:29375606

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq.

PubMed

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2017-01-01

Flax ( Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits.

A study on a robot chasing a human using Kinect while identifying walking parameters using the back view

NASA Astrophysics Data System (ADS)

Konno, S.; Mita, A.

2014-03-01

Recently, the demand of the building spaces to respond to increase of single aged households and the diversification of life style is increasing. Smart house is one of them, but it is difficult for them to be changed and renovated. Therefore, we suggest Biofied builing. In biofied building, we use a mobile robot to get concious and unconcious information about residents and try to make it more secure and comfort builing spaces by realizing the intraction between residents and builing spaces. Walking parameters are one of the most important unconscious information about residents. They are an indicator of autonomy of elderly, and changes of stride length and walking speed may be pridictive of a future fall and a cognitive impairment. By observing their walking and informing residents their walking state, they can forestall such dangers and it helps them to live more securely and autonomously. Many methods to estimate walking parameters have been studied. The famous ones are to use accelerometers and a motion capture camera. Walking parameters estimated by them are high precise but the sensors are attached to a human body in these method and it can make human's walk different from the original walk. Furthermore, some elderly feel it to invade them. In this work, Kinect which can get information about human untouchably was used on the mobile robot. A stride time, stride length, and walking speed were estimated from the back view of human by following him or her. Evaluation was done for 10m, 5m, 4m, and 3m in whole walking. As a result, the proposal system can estimate walking parameters of the walk more than 3m.

Parameter Uncertainty on AGCM-simulated Tropical Cyclones

NASA Astrophysics Data System (ADS)

He, F.

2015-12-01

This work studies the parameter uncertainty on tropical cyclone (TC) simulations in Atmospheric General Circulation Models (AGCMs) using the Reed-Jablonowski TC test case, which is illustrated in Community Atmosphere Model (CAM). It examines the impact from 24 parameters across the physical parameterization schemes that represent the convection, turbulence, precipitation and cloud processes in AGCMs. The one-at-a-time (OAT) sensitivity analysis method first quantifies their relative importance on TC simulations and identifies the key parameters to the six different TC characteristics: intensity, precipitation, longwave cloud radiative forcing (LWCF), shortwave cloud radiative forcing (SWCF), cloud liquid water path (LWP) and ice water path (IWP). Then, 8 physical parameters are chosen and perturbed using the Latin-Hypercube Sampling (LHS) method. The comparison between OAT ensemble run and LHS ensemble run shows that the simulated TC intensity is mainly affected by the parcel fractional mass entrainment rate in Zhang-McFarlane (ZM) deep convection scheme. The nonlinear interactive effect among different physical parameters is negligible on simulated TC intensity. In contrast, this nonlinear interactive effect plays a significant role in other simulated tropical cyclone characteristics (precipitation, LWCF, SWCF, LWP and IWP) and greatly enlarge their simulated uncertainties. The statistical emulator Extended Multivariate Adaptive Regression Splines (EMARS) is applied to characterize the response functions for nonlinear effect. Last, we find that the intensity uncertainty caused by physical parameters is in a degree comparable to uncertainty caused by model structure (e.g. grid) and initial conditions (e.g. sea surface temperature, atmospheric moisture). These findings suggest the importance of using the perturbed physics ensemble (PPE) method to revisit tropical cyclone prediction under climate change scenario.

Crowd-sourced Ontology for Photoleukocoria: Identifying Common Internet Search Terms for a Potentially Important Pediatric Ophthalmic Sign.

PubMed

Staffieri, Sandra E; Kearns, Lisa S; Sanfilippo, Paul G; Craig, Jamie E; Mackey, David A; Hewitt, Alex W

2018-02-01

Leukocoria is the most common presenting sign for pediatric eye disease including retinoblastoma and cataract, with worse outcomes if diagnosis is delayed. We investigated whether individuals could identify leukocoria in photographs (photoleukocoria) and examined their subsequent Internet search behavior. Using a web-based questionnaire, in this cross-sectional study we invited adults aged over 18 years to view two photographs of a child with photoleukocoria, and then search the Internet to determine a possible diagnosis and action plan. The most commonly used search terms and websites accessed were recorded. The questionnaire was completed by 1639 individuals. Facebook advertisement was the most effective recruitment strategy. The mean age of all respondents was 38.95 ± 14.59 years (range, 18-83), 94% were female, and 59.3% had children. An abnormality in the images presented was identified by 1613 (98.4%) participants. The most commonly used search terms were: "white," "pupil," "photo," and "eye" reaching a variety of appropriate websites or links to print or social media articles. Different words or phrases were used to describe the same observation of photoleukocoria leading to a range of websites. Variations in the description of observed signs and search words influenced the sites reached, information obtained, and subsequent help-seeking intentions. Identifying the most commonly used search terms for photoleukocoria is an important step for search engine optimization. Being directed to the most appropriate websites informing of the significance of photoleukocoria and the appropriate actions to take could improve delays in diagnosis of important pediatric eye disease such as retinoblastoma or cataract.

Improved quantification of important beer quality parameters based on nonlinear calibration methods applied to FT-MIR spectra.

PubMed

Cernuda, Carlos; Lughofer, Edwin; Klein, Helmut; Forster, Clemens; Pawliczek, Marcin; Brandstetter, Markus

2017-01-01

During the production process of beer, it is of utmost importance to guarantee a high consistency of the beer quality. For instance, the bitterness is an essential quality parameter which has to be controlled within the specifications at the beginning of the production process in the unfermented beer (wort) as well as in final products such as beer and beer mix beverages. Nowadays, analytical techniques for quality control in beer production are mainly based on manual supervision, i.e., samples are taken from the process and analyzed in the laboratory. This typically requires significant lab technicians efforts for only a small fraction of samples to be analyzed, which leads to significant costs for beer breweries and companies. Fourier transform mid-infrared (FT-MIR) spectroscopy was used in combination with nonlinear multivariate calibration techniques to overcome (i) the time consuming off-line analyses in beer production and (ii) already known limitations of standard linear chemometric methods, like partial least squares (PLS), for important quality parameters Speers et al. (J I Brewing. 2003;109(3):229-235), Zhang et al. (J I Brewing. 2012;118(4):361-367) such as bitterness, citric acid, total acids, free amino nitrogen, final attenuation, or foam stability. The calibration models are established with enhanced nonlinear techniques based (i) on a new piece-wise linear version of PLS by employing fuzzy rules for local partitioning the latent variable space and (ii) on extensions of support vector regression variants (-PLSSVR and ν-PLSSVR), for overcoming high computation times in high-dimensional problems and time-intensive and inappropriate settings of the kernel parameters. Furthermore, we introduce a new model selection scheme based on bagged ensembles in order to improve robustness and thus predictive quality of the final models. The approaches are tested on real-world calibration data sets for wort and beer mix beverages, and successfully compared to

Atlas of Relations Between Climatic Parameters and Distributions of Important Trees and Shrubs in North America - Alaska Species and Ecoregions

USGS Publications Warehouse

Thompson, Robert S.; Anderson, Katherine H.; Strickland, Laura E.; Shafer, Sarah L.; Pelltier, Richard T.; Bartlein, Patrick J.

2006-01-01

Climate is the primary factor in controlling the continental-scale distribution of plant species, although the relations between climatic parameters and species' ranges is only now beginning to be quantified. Preceding volumes of this atlas explored the continental-scale relations between climatic parameters and the distributions of woody plant species across all of the continent of North America. This volume presents similar information for important woody species, groups of species, and ecoregions in more detail for the State of Alaska. For these analyses, we constructed a 25-kilometer equal-area grid of modern climatic and bioclimatic parameters for North America from instrumental weather records. We obtained a digital representation of the geographic distribution of each species or ecoregion, either from a published source or by digitizing the published distributions ourselves. The presence or absence of each species or ecoregion was then determined for each point on the 25-kilometer grid, thus providing a basis for comparison of the climatic data with the geographic distribution of each species or ecoregion. The relations between climate and these distributions are presented in graphical and tabular form.

A Particle Smoother with Sequential Importance Resampling for soil hydraulic parameter estimation: A lysimeter experiment

NASA Astrophysics Data System (ADS)

Montzka, Carsten; Hendricks Franssen, Harrie-Jan; Moradkhani, Hamid; Pütz, Thomas; Han, Xujun; Vereecken, Harry

2013-04-01

An adequate description of soil hydraulic properties is essential for a good performance of hydrological forecasts. So far, several studies showed that data assimilation could reduce the parameter uncertainty by considering soil moisture observations. However, these observations and also the model forcings were recorded with a specific measurement error. It seems a logical step to base state updating and parameter estimation on observations made at multiple time steps, in order to reduce the influence of outliers at single time steps given measurement errors and unknown model forcings. Such outliers could result in erroneous state estimation as well as inadequate parameters. This has been one of the reasons to use a smoothing technique as implemented for Bayesian data assimilation methods such as the Ensemble Kalman Filter (i.e. Ensemble Kalman Smoother). Recently, an ensemble-based smoother has been developed for state update with a SIR particle filter. However, this method has not been used for dual state-parameter estimation. In this contribution we present a Particle Smoother with sequentially smoothing of particle weights for state and parameter resampling within a time window as opposed to the single time step data assimilation used in filtering techniques. This can be seen as an intermediate variant between a parameter estimation technique using global optimization with estimation of single parameter sets valid for the whole period, and sequential Monte Carlo techniques with estimation of parameter sets evolving from one time step to another. The aims are i) to improve the forecast of evaporation and groundwater recharge by estimating hydraulic parameters, and ii) to reduce the impact of single erroneous model inputs/observations by a smoothing method. In order to validate the performance of the proposed method in a real world application, the experiment is conducted in a lysimeter environment.

A new qualitative acoustic emission parameter based on Shannon's entropy for damage monitoring

NASA Astrophysics Data System (ADS)

Chai, Mengyu; Zhang, Zaoxiao; Duan, Quan

2018-02-01

An important objective of acoustic emission (AE) non-destructive monitoring is to accurately identify approaching critical damage and to avoid premature failure by means of the evolutions of AE parameters. One major drawback of most parameters such as count and rise time is that they are strongly dependent on the threshold and other settings employed in AE data acquisition system. This may hinder the correct reflection of original waveform generated from AE sources and consequently bring difficulty for the accurate identification of the critical damage and early failure. In this investigation, a new qualitative AE parameter based on Shannon's entropy, i.e. AE entropy is proposed for damage monitoring. Since it derives from the uncertainty of amplitude distribution of each AE waveform, it is independent of the threshold and other time-driven parameters and can characterize the original micro-structural deformations. Fatigue crack growth test on CrMoV steel and three point bending test on a ductile material are conducted to validate the feasibility and effectiveness of the proposed parameter. The results show that the new parameter, compared to AE amplitude, is more effective in discriminating the different damage stages and identifying the critical damage.

Parameters of Technological Growth

ERIC Educational Resources Information Center

Starr, Chauncey; Rudman, Richard

1973-01-01

Examines the factors involved in technological growth and identifies the key parameters as societal resources and societal expectations. Concludes that quality of life can only be maintained by reducing population growth, since this parameter is the product of material levels, overcrowding, food, and pollution. (JR)

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

PubMed

Karr, Jonathan R; Williams, Alex H; Zucker, Jeremy D; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A; Bot, Brian M; Hoff, Bruce R; Kellen, Michael R; Covert, Markus W; Stolovitzky, Gustavo A; Meyer, Pablo

2015-05-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models

PubMed Central

Karr, Jonathan R.; Williams, Alex H.; Zucker, Jeremy D.; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A.; Bot, Brian M.; Hoff, Bruce R.; Kellen, Michael R.; Covert, Markus W.; Stolovitzky, Gustavo A.; Meyer, Pablo

2015-01-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model’s structure and in silico “experimental” data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation. PMID:26020786

An effective automatic procedure for testing parameter identifiability of HIV/AIDS models.

PubMed

Saccomani, Maria Pia

2011-08-01

Realistic HIV models tend to be rather complex and many recent models proposed in the literature could not yet be analyzed by traditional identifiability testing techniques. In this paper, we check a priori global identifiability of some of these nonlinear HIV models taken from the recent literature, by using a differential algebra algorithm based on previous work of the author. The algorithm is implemented in a software tool, called DAISY (Differential Algebra for Identifiability of SYstems), which has been recently released (DAISY is freely available on the web site http://www.dei.unipd.it/~pia/ ). The software can be used to automatically check global identifiability of (linear and) nonlinear models described by polynomial or rational differential equations, thus providing a general and reliable tool to test global identifiability of several HIV models proposed in the literature. It can be used by researchers with a minimum of mathematical background.

The importance of correct specification of tribological parameters in dynamical systems modelling

NASA Astrophysics Data System (ADS)

Alaci, S.; Ciornei, F. C.; Romanu, I. C.; Ciornei, M. C.

2018-01-01

When modelling the behaviour of dynamical systems, the friction phenomenon cannot be neglected. Dry and fluid friction may occur, but dry friction has more severe effects upon the behaviour of the systems, based on the fact that the introduced discontinuities are more important. In the modelling of dynamical systems, dry friction is the main cause of occurrence of the bifurcation phenomenon. These aspects become more complex if, in the case of dry friction, static and dynamic frictions are put forward. The behaviour of a simple dynamical system is studied, consisting in a prismatic body linked to the ground by a spring, placed on a conveyor belt. The theoretical model is described by a nonlinear differential equation which after numerical integration leads to the conclusion that the steady motion of the prism is an un-damped oscillatory motion. The system was qualitatively modelled using specialised software for dynamical analysis. It was impractical to obtain a steady uniform translational motion of a rigid, therefore the conveyor belt was replaced by a metallic disc in uniform rotation motion. The attempts to compare the CAD model to the theoretical model were unsuccessful because the efforts of selecting the tribological parameters directed to the conclusion that the motion of the prism is a damped oscillation. To decide which of the methods depicts reality, a test-rig was assembled and it indicated a sustained oscillation. The conclusion is that the model employed by the dynamical analysis software cannot describe the actual model and a more complex model is required in the description of the friction phenomenon.

Identifying the needs of elderly, hearing-impaired persons: the importance and utility of hearing aid attributes.

PubMed

Meister, Hartmut; Lausberg, Isabel; Kiessling, Juergen; von Wedel, Hasso; Walger, Martin

2002-11-01

Older patients represent the majority of hearing-aid users. The needs of elderly, hearing-impaired subjects are not entirely identified. The present study aims to determine the importance of fundamental hearing-aid attributes and to elicit the utility of associated hypothetical hearing aids for older patients. This was achieved using a questionnaire-based conjoint analysis--a decompositional approach to preference measurement offering a realistic study design. A random sample of 200 experienced hearing-aid users participated in the study. Though three out of the six examined attributes revealed age-related dependencies, the only significant effect was found for the attribute "handling", which was considerably more important for older than younger hearing-aid users. A trend of decreasing importance of speech intelligibility in noise and increasing significance of speech in quiet was observed for subjects older than 70 years. In general, the utility of various hypothetical hearing aids was similar for older and younger subjects. Apart from the attribute "handling", older and younger subjects have comparable needs regarding hearing-aid features. On the basis of the examined attributes, there is no requirement for hearing aids designed specifically for elderly hearing-aid users, provided that ergonomic features are considered and the benefits of modern technology are made fully available for older patients.

n-Iterative Exponential Forgetting Factor for EEG Signals Parameter Estimation

PubMed Central

Palma Orozco, Rosaura

2018-01-01

Electroencephalograms (EEG) signals are of interest because of their relationship with physiological activities, allowing a description of motion, speaking, or thinking. Important research has been developed to take advantage of EEG using classification or predictor algorithms based on parameters that help to describe the signal behavior. Thus, great importance should be taken to feature extraction which is complicated for the Parameter Estimation (PE)–System Identification (SI) process. When based on an average approximation, nonstationary characteristics are presented. For PE the comparison of three forms of iterative-recursive uses of the Exponential Forgetting Factor (EFF) combined with a linear function to identify a synthetic stochastic signal is presented. The one with best results seen through the functional error is applied to approximate an EEG signal for a simple classification example, showing the effectiveness of our proposal. PMID:29568310

Effects of important parameters variations on computing eigenspace-based minimum variance weights for ultrasound tissue harmonic imaging

NASA Astrophysics Data System (ADS)

Haji Heidari, Mehdi; Mozaffarzadeh, Moein; Manwar, Rayyan; Nasiriavanaki, Mohammadreza

2018-02-01

In recent years, the minimum variance (MV) beamforming has been widely studied due to its high resolution and contrast in B-mode Ultrasound imaging (USI). However, the performance of the MV beamformer is degraded at the presence of noise, as a result of the inaccurate covariance matrix estimation which leads to a low quality image. Second harmonic imaging (SHI) provides many advantages over the conventional pulse-echo USI, such as enhanced axial and lateral resolutions. However, the low signal-to-noise ratio (SNR) is a major problem in SHI. In this paper, Eigenspace-based minimum variance (EIBMV) beamformer has been employed for second harmonic USI. The Tissue Harmonic Imaging (THI) is achieved by Pulse Inversion (PI) technique. Using the EIBMV weights, instead of the MV ones, would lead to reduced sidelobes and improved contrast, without compromising the high resolution of the MV beamformer (even at the presence of a strong noise). In addition, we have investigated the effects of variations of the important parameters in computing EIBMV weights, i.e., K, L, and δ, on the resolution and contrast obtained in SHI. The results are evaluated using numerical data (using point target and cyst phantoms), and the proper parameters of EIBMV are indicated for THI.

Systematic reviews identify important methodological flaws in stroke rehabilitation therapy primary studies: review of reviews.

PubMed

Santaguida, Pasqualina; Oremus, Mark; Walker, Kathryn; Wishart, Laurie R; Siegel, Karen Lohmann; Raina, Parminder

2012-04-01

A "review of reviews" was undertaken to assess methodological issues in studies evaluating nondrug rehabilitation interventions in stroke patients. MEDLINE, CINAHL, PsycINFO, and the Cochrane Database of Systematic Reviews were searched from January 2000 to January 2008 within the stroke rehabilitation setting. Electronic searches were supplemented by reviews of reference lists and citations identified by experts. Eligible studies were systematic reviews; excluded citations were narrative reviews or reviews of reviews. Review characteristics and criteria for assessing methodological quality of primary studies within them were extracted. The search yielded 949 English-language citations. We included a final set of 38 systematic reviews. Cochrane reviews, which have a standardized methodology, were generally of higher methodological quality than non-Cochrane reviews. Most systematic reviews used standardized quality assessment criteria for primary studies, but not all were comprehensive. Reviews showed that primary studies had problems with randomization, allocation concealment, and blinding. Baseline comparability, adverse events, and co-intervention or contamination were not consistently assessed. Blinding of patients and providers was often not feasible and was not evaluated as a source of bias. The eligible systematic reviews identified important methodological flaws in the evaluated primary studies, suggesting the need for improvement of research methods and reporting. Copyright © 2012 Elsevier Inc. All rights reserved.

Structural Identifiability of Dynamic Systems Biology Models

PubMed Central

Villaverde, Alejandro F.

2016-01-01

A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas. PMID:27792726

Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation

NASA Astrophysics Data System (ADS)

Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei

2018-04-01

Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.

Mango (Mangifera indica L.) cv. Kent fruit mesocarp de novo transcriptome assembly identifies gene families important for ripening.

PubMed

Dautt-Castro, Mitzuko; Ochoa-Leyva, Adrian; Contreras-Vergara, Carmen A; Pacheco-Sanchez, Magda A; Casas-Flores, Sergio; Sanchez-Flores, Alejandro; Kuhn, David N; Islas-Osuna, Maria A

2015-01-01

Fruit ripening is a physiological and biochemical process genetically programmed to regulate fruit quality parameters like firmness, flavor, odor and color, as well as production of ethylene in climacteric fruit. In this study, a transcriptomic analysis of mango (Mangifera indica L.) mesocarp cv. "Kent" was done to identify key genes associated with fruit ripening. Using the Illumina sequencing platform, 67,682,269 clean reads were obtained and a transcriptome of 4.8 Gb. A total of 33,142 coding sequences were predicted and after functional annotation, 25,154 protein sequences were assigned with a product according to Swiss-Prot database and 32,560 according to non-redundant database. Differential expression analysis identified 2,306 genes with significant differences in expression between mature-green and ripe mango [1,178 up-regulated and 1,128 down-regulated (FDR ≤ 0.05)]. The expression of 10 genes evaluated by both qRT-PCR and RNA-seq data was highly correlated (R = 0.97), validating the differential expression data from RNA-seq alone. Gene Ontology enrichment analysis, showed significantly represented terms associated to fruit ripening like "cell wall," "carbohydrate catabolic process" and "starch and sucrose metabolic process" among others. Mango genes were assigned to 327 metabolic pathways according to Kyoto Encyclopedia of Genes and Genomes database, among them those involved in fruit ripening such as plant hormone signal transduction, starch and sucrose metabolism, galactose metabolism, terpenoid backbone, and carotenoid biosynthesis. This study provides a mango transcriptome that will be very helpful to identify genes for expression studies in early and late flowering mangos during fruit ripening.

Sea Oil Spill Detection Using Self-Similarity Parameter of Polarimetric SAR Data

NASA Astrophysics Data System (ADS)

Tong, S.; Chen, Q.; Liu, X.

2018-04-01

The ocean oil spills cause serious damage to the marine ecosystem. Polarimetric Synthetic Aperture Radar (SAR) is an important mean for oil spill detections on sea surface. The major challenge is how to distinguish oil slicks from look-alikes effectively. In this paper, a new parameter called self-similarity parameter, which is sensitive to the scattering mechanism of oil slicks, is introduced to identify oil slicks and reduce false alarm caused by look-alikes. Self-similarity parameter is small in oil slicks region and it is large in sea region or look-alikes region. So, this parameter can be used to detect oil slicks from look-alikes and water. In addition, evaluations and comparisons were conducted with one Radarsat-2 image and two SIR-C images. The experimental results demonstrate the effectiveness of the self-similarity parameter for oil spill detection.

Identifiability, reducibility, and adaptability in allosteric macromolecules.

PubMed

Bohner, Gergő; Venkataraman, Gaurav

2017-05-01

The ability of macromolecules to transduce stimulus information at one site into conformational changes at a distant site, termed "allostery," is vital for cellular signaling. Here, we propose a link between the sensitivity of allosteric macromolecules to their underlying biophysical parameters, the interrelationships between these parameters, and macromolecular adaptability. We demonstrate that the parameters of a canonical model of the mSlo large-conductance Ca 2+ -activated K + (BK) ion channel are non-identifiable with respect to the equilibrium open probability-voltage relationship, a common functional assay. We construct a reduced model with emergent parameters that are identifiable and expressed as combinations of the original mechanistic parameters. These emergent parameters indicate which coordinated changes in mechanistic parameters can leave assay output unchanged. We predict that these coordinated changes are used by allosteric macromolecules to adapt, and we demonstrate how this prediction can be tested experimentally. We show that these predicted parameter compensations are used in the first reported allosteric phenomena: the Bohr effect, by which hemoglobin adapts to varying pH. © 2017 Bohner and Venkataraman.

Identifiability, reducibility, and adaptability in allosteric macromolecules

PubMed Central

Bohner, Gergő

2017-01-01

The ability of macromolecules to transduce stimulus information at one site into conformational changes at a distant site, termed “allostery,” is vital for cellular signaling. Here, we propose a link between the sensitivity of allosteric macromolecules to their underlying biophysical parameters, the interrelationships between these parameters, and macromolecular adaptability. We demonstrate that the parameters of a canonical model of the mSlo large-conductance Ca2+-activated K+ (BK) ion channel are non-identifiable with respect to the equilibrium open probability-voltage relationship, a common functional assay. We construct a reduced model with emergent parameters that are identifiable and expressed as combinations of the original mechanistic parameters. These emergent parameters indicate which coordinated changes in mechanistic parameters can leave assay output unchanged. We predict that these coordinated changes are used by allosteric macromolecules to adapt, and we demonstrate how this prediction can be tested experimentally. We show that these predicted parameter compensations are used in the first reported allosteric phenomena: the Bohr effect, by which hemoglobin adapts to varying pH. PMID:28416647

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other.

PubMed

Tahmasebian, Shahram; Ghazisaeedi, Marjan; Langarizadeh, Mostafa; Mokhtaran, Mehrshad; Mahdavi-Mazdeh, Mitra; Javadian, Parisa

2017-01-01

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients' medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD.

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other

PubMed Central

Tahmasebian, Shahram; Ghazisaeedi, Marjan; Langarizadeh, Mostafa; Mokhtaran, Mehrshad; Mahdavi-Mazdeh, Mitra; Javadian, Parisa

2017-01-01

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients’ medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD. PMID:28497080

Identifying important comorbidity among cancer populations using administrative data: Prevalence and impact on survival.

PubMed

Sarfati, Diana; Gurney, Jason; Lim, Bee Teng; Bagheri, Nasser; Simpson, Andrew; Koea, Jonathan; Dennett, Elizabeth

2016-03-01

Our study sought to optimize the identification and investigate the impact of comorbidity in cancer patients using routinely collected hospitalization data. We undertook an iterative process of classification of important clinical conditions involving evaluation of relevant literature and consultation with clinicians. Patients diagnosed with colon, rectal, breast, ovarian, uterine, stomach, liver, renal or bladder cancers (n = 14,096) between 2006 and 2008 were identified from the New Zealand Cancer Registry. Conditions were identified using data on diagnoses from hospital admissions for 5 years prior to cancer diagnosis. Patients were followed up until end of 2009 using routine mortality data. Prevalence estimates for each condition by site were calculated. All-cause mortality impact of common conditions was investigated using Cox regression models adjusted for age and stage at diagnosis. Patients with liver and stomach cancers tended to have higher comorbidity and those with breast cancer, lower comorbidity than other cancer patients. Of the 50 conditions, the most common were hypertension (prevalence 8.0-20.9%), cardiac conditions (2.1-13.5%) and diabetes with (2.3-13.3%) and without (2.9-12.9%) complications. Comorbidity was associated with higher all-cause mortality but the impact varied by condition and across cancer site, with impact less for cancers with poor prognoses. Conditions most consistently associated with adverse outcomes across all cancer sites were renal disease, coagulopathies and congestive heart failure. Comorbidity is highly prevalent in cancer populations, but prevalence and impact of conditions differ markedly by cancer type. © 2013 Wiley Publishing Asia Pty Ltd.

DD3MAT - a code for yield criteria anisotropy parameters identification.

NASA Astrophysics Data System (ADS)

Barros, P. D.; Carvalho, P. D.; Alves, J. L.; Oliveira, M. C.; Menezes, L. F.

2016-08-01

This work presents the main strategies and algorithms adopted in the DD3MAT inhouse code, specifically developed for identifying the anisotropy parameters. The algorithm adopted is based on the minimization of an error function, using a downhill simplex method. The set of experimental values can consider yield stresses and r -values obtained from in-plane tension, for different angles with the rolling direction (RD), yield stress and r -value obtained for biaxial stress state, and yield stresses from shear tests performed also for different angles to RD. All these values can be defined for a specific value of plastic work. Moreover, it can also include the yield stresses obtained from in-plane compression tests. The anisotropy parameters are identified for an AA2090-T3 aluminium alloy, highlighting the importance of the user intervention to improve the numerical fit.

Electrospraying of polymer solutions: Study of formulation and process parameters.

PubMed

Smeets, Annelies; Clasen, Christian; Van den Mooter, Guy

2017-10-01

Over the past decade, electrospraying has proven to be a promising method for the preparation of amorphous solid dispersions, an established formulation strategy to improve the oral bioavailability of poorly soluble drug compounds. Due to the lack of fundamental knowledge concerning adequate single nozzle electrospraying conditions, a trial-and-error approach is currently the only option. The objective of this paper is to study/investigate the influence of the different formulation and process parameters, as well as their interplay, on the formation of a stable cone-jet mode as a prerequisite for a reproducible production of monodisperse micro- and nanoparticles. To this purpose, different polymers commonly used in the formulation of solid dispersions were electrosprayed to map out the workable parameter ranges of the process. The experiments evaluate the importance of the experimental parameters as flow rate, electric potential difference and the distance between the tip of the nozzle and collector. Based on this, the type of solvent and the concentration of the polymer solutions, along with their viscosity and conductivity, were identified as determinative formulation parameters. This information is of utmost importance to rationally design further electrospraying methods for the preparation of amorphous solid dispersions. Copyright © 2017 Elsevier B.V. All rights reserved.

Classical vs. evolved quenching parameters and procedures in scintillation measurements: The importance of ionization quenching

NASA Astrophysics Data System (ADS)

Bagán, H.; Tarancón, A.; Rauret, G.; García, J. F.

2008-07-01

The quenching parameters used to model detection efficiency variations in scintillation measurements have not evolved since the decade of 1970s. Meanwhile, computer capabilities have increased enormously and ionization quenching has appeared in practical measurements using plastic scintillation. This study compares the results obtained in activity quantification by plastic scintillation of 14C samples that contain colour and ionization quenchers, using classical (SIS, SCR-limited, SCR-non-limited, SIS(ext), SQP(E)) and evolved (MWA-SCR and WDW) parameters and following three calibration approaches: single step, which does not take into account the quenching mechanism; two steps, which takes into account the quenching phenomena; and multivariate calibration. Two-step calibration (ionization followed by colour) yielded the lowest relative errors, which means that each quenching phenomenon must be specifically modelled. In addition, the sample activity was quantified more accurately when the evolved parameters were used. Multivariate calibration-PLS also yielded better results than those obtained using classical parameters, which confirms that the quenching phenomena must be taken into account. The detection limits for each calibration method and each parameter were close to those obtained theoretically using the Currie approach.

Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation

PubMed Central

Hall, Sheldon K.; Ooi, Ean H.; Payne, Stephen J.

2015-01-01

Abstract Purpose: A sensitivity analysis has been performed on a mathematical model of radiofrequency ablation (RFA) in the liver. The purpose of this is to identify the most important parameters in the model, defined as those that produce the largest changes in the prediction. This is important in understanding the role of uncertainty and when comparing the model predictions to experimental data. Materials and methods: The Morris method was chosen to perform the sensitivity analysis because it is ideal for models with many parameters or that take a significant length of time to obtain solutions. A comprehensive literature review was performed to obtain ranges over which the model parameters are expected to vary, crucial input information. Results: The most important parameters in predicting the ablation zone size in our model of RFA are those representing the blood perfusion, electrical conductivity and the cell death model. The size of the 50 °C isotherm is sensitive to the electrical properties of tissue while the heat source is active, and to the thermal parameters during cooling. Conclusions: The parameter ranges chosen for the sensitivity analysis are believed to represent all that is currently known about their values in combination. The Morris method is able to compute global parameter sensitivities taking into account the interaction of all parameters, something that has not been done before. Research is needed to better understand the uncertainties in the cell death, electrical conductivity and perfusion models, but the other parameters are only of second order, providing a significant simplification. PMID:26000972

A bootstrap based Neyman-Pearson test for identifying variable importance.

PubMed

Ditzler, Gregory; Polikar, Robi; Rosen, Gail

2015-04-01

Selection of most informative features that leads to a small loss on future data are arguably one of the most important steps in classification, data analysis and model selection. Several feature selection (FS) algorithms are available; however, due to noise present in any data set, FS algorithms are typically accompanied by an appropriate cross-validation scheme. In this brief, we propose a statistical hypothesis test derived from the Neyman-Pearson lemma for determining if a feature is statistically relevant. The proposed approach can be applied as a wrapper to any FS algorithm, regardless of the FS criteria used by that algorithm, to determine whether a feature belongs in the relevant set. Perhaps more importantly, this procedure efficiently determines the number of relevant features given an initial starting point. We provide freely available software implementations of the proposed methodology.

Analysis of sagittal spinopelvic parameters in achondroplasia.

PubMed

Hong, Jae-Young; Suh, Seung-Woo; Modi, Hitesh N; Park, Jong-Woong; Park, Jung-Ho

2011-08-15

Prospective radiological analysis of patients with achondroplasia. To analyze sagittal spinal alignment and pelvic orientation in achondroplasia patients. Knowledge of sagittal spinopelvic parameters is important for the treatment of achondroplasia, because they differ from those of the normal population and can induce pain. The study and control groups were composed of 32 achondroplasia patients and 24 healthy volunteers, respectively. All underwent lateral radiography of the whole spine including hip joints. The radiographic parameters examined were sacral slope (SS), pelvic tilt, pelvic incidence (PI), S1 overhang, thoracic kyphosis, T10-L2 kyphosis, lumbar lordosis (LL1, LL2), and sagittal balance. Statistical analysis was performed to identify significant differences between the two groups. In addition, correlations between parameters and symptoms were sought. Sagittal spinopelvic parameters, namely, pelvic tilt, pelvic incidence, S1 overhang, thoracic kyphosis, T10-L2 kyphosis, lumbar lordosis 1 and sagittal balance were found to be significantly different in the patient and control groups (P < 0.05). In addition, sagittal parameters were found to be related to each other in the patient group (P < 0.05), that is, PI was related to SS and pelvic tilt, and LL was related to thoracic kyphosis. Furthermore, in terms of relations between spinal and pelvic parameters, LL was related to SS and PI, and sagittal balance was related to SS and PI. Furthermore, LL and T10-L2 kyphosis were found to be related to pain (P < 0.05), whereas no other parameter was found to be related to VAS scores. Sagittal parameters and possible relationships between sagittal parameters and symptoms were found to be significantly different in achondroplasia patients and normal healthy controls. The present study shows that sagittal spinal and pelvic parameters can assist the treatment of spinal disorders in achondroplasia patients.

Which are the most important parameters for modelling carbon assimilation in boreal Norway spruce under elevated [CO(2)] and temperature conditions?

PubMed

Hall, Marianne; Medlyn, Belinda E; Abramowitz, Gab; Franklin, Oskar; Räntfors, Mats; Linder, Sune; Wallin, Göran

2013-11-01

Photosynthesis is highly responsive to environmental and physiological variables, including phenology, foliage nitrogen (N) content, atmospheric CO2 concentration ([CO2]), irradiation (Q), air temperature (T) and vapour pressure deficit (D). Each of these responses is likely to be modified by long-term changes in climatic conditions such as rising air temperature and [CO2]. When modelling photosynthesis under climatic changes, which parameters are then most important to calibrate for future conditions? To assess this, we used measurements of shoot carbon assimilation rates and microclimate conditions collected at Flakaliden, northern Sweden. Twelve 40-year-old Norway spruce trees were enclosed in whole-tree chambers and exposed to elevated [CO2] and elevated air temperature, separately and in combination. The treatments imposed were elevated temperature, +2.8 °C in July/August and +5.6 °C in December above ambient, and [CO2] (ambient CO2 ∼370 μ mol mol(-1), elevated CO2 ∼700 μ mol mol(-1)). The relative importance of parameterization of Q, T and D responses for effects on the photosynthetic rate, expressed on a projected needle area, and the annual shoot carbon uptake was quantified using an empirical shoot photosynthesis model, which was developed and fitted to the measurements. The functional form of the response curves was established using an artificial neural network. The [CO2] treatment increased annual shoot carbon (C) uptake by 50%. Most important was effects on the light response curve, with a 67% increase in light-saturated photosynthetic rate, and a 52% increase in the initial slope of the light response curve. An interactive effect of light saturated photosynthetic rate was found with foliage N status, but no interactive effect for high temperature and high CO2. The air temperature treatment increased the annual shoot C uptake by 44%. The most important parameter was the seasonality, with an elongation of the growing season by almost 4

Mango (Mangifera indica L.) cv. Kent fruit mesocarp de novo transcriptome assembly identifies gene families important for ripening

PubMed Central

Dautt-Castro, Mitzuko; Ochoa-Leyva, Adrian; Contreras-Vergara, Carmen A.; Pacheco-Sanchez, Magda A.; Casas-Flores, Sergio; Sanchez-Flores, Alejandro; Kuhn, David N.; Islas-Osuna, Maria A.

2015-01-01

Fruit ripening is a physiological and biochemical process genetically programmed to regulate fruit quality parameters like firmness, flavor, odor and color, as well as production of ethylene in climacteric fruit. In this study, a transcriptomic analysis of mango (Mangifera indica L.) mesocarp cv. “Kent” was done to identify key genes associated with fruit ripening. Using the Illumina sequencing platform, 67,682,269 clean reads were obtained and a transcriptome of 4.8 Gb. A total of 33,142 coding sequences were predicted and after functional annotation, 25,154 protein sequences were assigned with a product according to Swiss-Prot database and 32,560 according to non-redundant database. Differential expression analysis identified 2,306 genes with significant differences in expression between mature-green and ripe mango [1,178 up-regulated and 1,128 down-regulated (FDR ≤ 0.05)]. The expression of 10 genes evaluated by both qRT-PCR and RNA-seq data was highly correlated (R = 0.97), validating the differential expression data from RNA-seq alone. Gene Ontology enrichment analysis, showed significantly represented terms associated to fruit ripening like “cell wall,” “carbohydrate catabolic process” and “starch and sucrose metabolic process” among others. Mango genes were assigned to 327 metabolic pathways according to Kyoto Encyclopedia of Genes and Genomes database, among them those involved in fruit ripening such as plant hormone signal transduction, starch and sucrose metabolism, galactose metabolism, terpenoid backbone, and carotenoid biosynthesis. This study provides a mango transcriptome that will be very helpful to identify genes for expression studies in early and late flowering mangos during fruit ripening. PMID:25741352

Identifying specific beliefs to target to improve restaurant employees' intentions for performing three important food safety behaviors.

PubMed

Pilling, Valerie K; Brannon, Laura A; Shanklin, Carol W; Howells, Amber D; Roberts, Kevin R

2008-06-01

Current national food safety training programs appear ineffective at improving food safety practices in foodservice operations, given the substantial number of Americans affected by foodborne illnesses after eating in restaurants each year. The Theory of Planned Behavior (TpB) was used to identify important beliefs that may be targeted to improve foodservice employees' intentions for three food safety behaviors that have the most substantial affect on public health: hand washing, using thermometers, and proper handling of food contact surfaces. In a cross-sectional design, foodservice employees (n=190) across three midwestern states completed a survey assessing TpB components and knowledge for the three food safety behaviors. Multiple regression analyses were performed on the TpB components for each behavior. Independent-samples t tests identified TpB beliefs that discriminated between participants who absolutely intend to perform the behaviors and those with lower intention. Employees' attitudes were the one consistent predictor of intentions for performing all three behaviors. However, a unique combination of important predictors existed for each separate behavior. Interventions for improving employees' behavioral intentions for food safety should focus on TpB components that predict intentions for each behavior and should bring all employees' beliefs in line with those of the employees who already intend to perform the food safety behaviors. Registered dietitians; dietetic technicians, registered; and foodservice managers can use these results to enhance training sessions and motivational programs to improve employees' food safety behaviors. Results also assist these professionals in recognizing their responsibility for enforcing and providing adequate resources for proper food safety behaviors.

Parameter identification of civil engineering structures

NASA Technical Reports Server (NTRS)

Juang, J. N.; Sun, C. T.

1980-01-01

This paper concerns the development of an identification method required in determining structural parameter variations for systems subjected to an extended exposure to the environment. The concept of structural identifiability of a large scale structural system in the absence of damping is presented. Three criteria are established indicating that a large number of system parameters (the coefficient parameters of the differential equations) can be identified by a few actuators and sensors. An eight-bay-fifteen-story frame structure is used as example. A simple model is employed for analyzing the dynamic response of the frame structure.

Imported Wines: Identifying and Removing Wines Contaminated with Diethylene Glycol.

DTIC Science & Technology

1986-03-01

at controlling health risks, BATF has used its labeling authority to prohibit the marketing of alcoholic beverages that are mislabeled by virtue of...or beverages contaminated with harmful substances into the U.S. market . DEG, a toxic substance, would be such a contaminant. The BATF’S authority in...representing a significant risk to health are identified and removed from k the market . BATF did not conduct a risk assessment or seek an assess- ment from

The Importance of Parameter Variances, Correlations Lengths, and Cross-Correlations in Reactive Transport Models: Key Considerations for Assessing the Need for Microscale Information (Invited)

NASA Astrophysics Data System (ADS)

Reimus, P. W.

2010-12-01

A process-oriented modeling approach is implemented to examine the importance of parameter variances, correlation lengths, and especially cross-correlations in contaminant transport predictions over large scales. It is shown that the most important consideration is the correlation between flow rates and retardation processes (e.g., sorption, matrix diffusion) in the system. If flow rates are negatively correlated with retardation factors in systems containing multiple flow pathways, then characterizing these negative correlation(s) may have more impact on reactive transport modeling than microscale information. Such negative correlations are expected in porous-media systems where permeability is negatively correlated with clay content and rock alteration (which are usually associated with increased sorption). Likewise, negative correlations are expected in fractured rocks where permeability is positively correlated with fracture apertures, which in turn are negatively correlated with sorption and matrix diffusion. Parameter variances and correlation lengths are also shown to have important effects on reactive transport predictions, but they are less important than parameter cross-correlations. Microscale information pertaining to contaminant transport has become more readily available as characterization methods and spectroscopic instrumentation have achieved lower detection limits, greater resolution, and better precision. Obtaining detailed mechanistic insights into contaminant-rock-water interactions is becoming a routine practice in characterizing reactive transport processes in groundwater systems (almost necessary for high-profile publications). Unfortunately, a quantitative link between microscale information and flow and transport parameter distributions or cross-correlations has not yet been established. One reason for this is that quantitative microscale information is difficult to obtain in complex, heterogeneous systems, so simple systems that lack the

Data pieces-based parameter identification for lithium-ion battery

NASA Astrophysics Data System (ADS)

Gao, Wei; Zou, Yuan; Sun, Fengchun; Hu, Xiaosong; Yu, Yang; Feng, Sen

2016-10-01

Battery characteristics vary with temperature and aging, it is necessary to identify battery parameters periodically for electric vehicles to ensure reliable State-of-Charge (SoC) estimation, battery equalization and safe operation. Aiming for on-board applications, this paper proposes a data pieces-based parameter identification (DPPI) method to identify comprehensive battery parameters including capacity, OCV (open circuit voltage)-Ah relationship and impedance-Ah relationship simultaneously only based on battery operation data. First a vehicle field test was conducted and battery operation data was recorded, then the DPPI method is elaborated based on vehicle test data, parameters of all 97 cells of the battery package are identified and compared. To evaluate the adaptability of the proposed DPPI method, it is used to identify battery parameters of different aging levels and different temperatures based on battery aging experiment data. Then a concept of ;OCV-Ah aging database; is proposed, based on which battery capacity can be identified even though the battery was never fully charged or discharged. Finally, to further examine the effectiveness of the identified battery parameters, they are used to perform SoC estimation for the test vehicle with adaptive extended Kalman filter (AEKF). The result shows good accuracy and reliability.

Identifying dominant controls on hydrologic parameter transfer from gauged to ungauged catchments: a comparative hydrology approach

USGS Publications Warehouse

Singh, R.; Archfield, S.A.; Wagener, T.

2014-01-01

Daily streamflow information is critical for solving various hydrologic problems, though observations of continuous streamflow for model calibration are available at only a small fraction of the world’s rivers. One approach to estimate daily streamflow at an ungauged location is to transfer rainfall–runoff model parameters calibrated at a gauged (donor) catchment to an ungauged (receiver) catchment of interest. Central to this approach is the selection of a hydrologically similar donor. No single metric or set of metrics of hydrologic similarity have been demonstrated to consistently select a suitable donor catchment. We design an experiment to diagnose the dominant controls on successful hydrologic model parameter transfer. We calibrate a lumped rainfall–runoff model to 83 stream gauges across the United States. All locations are USGS reference gauges with minimal human influence. Parameter sets from the calibrated models are then transferred to each of the other catchments and the performance of the transferred parameters is assessed. This transfer experiment is carried out both at the scale of the entire US and then for six geographic regions. We use classification and regression tree (CART) analysis to determine the relationship between catchment similarity and performance of transferred parameters. Similarity is defined using physical/climatic catchment characteristics, as well as streamflow response characteristics (signatures such as baseflow index and runoff ratio). Across the entire US, successful parameter transfer is governed by similarity in elevation and climate, and high similarity in streamflow signatures. Controls vary for different geographic regions though. Geology followed by drainage, topography and climate constitute the dominant similarity metrics in forested eastern mountains and plateaus, whereas agricultural land use relates most strongly with successful parameter transfer in the humid plains.

Classification of hydrological parameter sensitivity and evaluation of parameter transferability across 431 US MOPEX basins

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

Ren, Huiying; Hou, Zhangshuan; Huang, Maoyi

The Community Land Model (CLM) represents physical, chemical, and biological processes of the terrestrial ecosystems that interact with climate across a range of spatial and temporal scales. As CLM includes numerous sub-models and associated parameters, the high-dimensional parameter space presents a formidable challenge for quantifying uncertainty and improving Earth system predictions needed to assess environmental changes and risks. This study aims to evaluate the potential of transferring hydrologic model parameters in CLM through sensitivity analyses and classification across watersheds from the Model Parameter Estimation Experiment (MOPEX) in the United States. The sensitivity of CLM-simulated water and energy fluxes to hydrologicalmore » parameters across 431 MOPEX basins are first examined using an efficient stochastic sampling-based sensitivity analysis approach. Linear, interaction, and high-order nonlinear impacts are all identified via statistical tests and stepwise backward removal parameter screening. The basins are then classified accordingly to their parameter sensitivity patterns (internal attributes), as well as their hydrologic indices/attributes (external hydrologic factors) separately, using a Principal component analyses (PCA) and expectation-maximization (EM) –based clustering approach. Similarities and differences among the parameter sensitivity-based classification system (S-Class), the hydrologic indices-based classification (H-Class), and the Koppen climate classification systems (K-Class) are discussed. Within each S-class with similar parameter sensitivity characteristics, similar inversion modeling setups can be used for parameter calibration, and the parameters and their contribution or significance to water and energy cycling may also be more transferrable. This classification study provides guidance on identifiable parameters, and on parameterization and inverse model design for CLM but the methodology is applicable to other

Rational Design of Molecular Gelator - Solvent Systems Guided by Solubility Parameters

NASA Astrophysics Data System (ADS)

Lan, Yaqi

Self-assembled architectures, such as molecular gels, have attracted wide interest among chemists, physicists and engineers during the past decade. However, the mechanism behind self-assembly remains largely unknown and no capability exists to predict a priori whether a small molecule will gelate a specific solvent or not. The process of self-assembly, in molecular gels, is intricate and must balance parameters influencing solubility and those contrasting forces that govern epitaxial growth into axially symmetric elongated aggregates. Although the gelator-gelator interactions are of paramount importance in understanding gelation, the solvent-gelator specific (i.e., H-bonding) and nonspecific (dipole-dipole, dipole-induced and instantaneous dipole induced forces) intermolecular interactions are equally important. Solvent properties mediate the self-assembly of molecular gelators into their self-assembled fibrillar networks. Herein, solubility parameters of solvents, ranging from partition coefficients (logP), to Henry's law constants (HLC), to solvatochromic ET(30) parameters, to Kamlet-Taft parameters (beta, alpha and pi), to Hansen solubility parameters (deltap, deltad, deltah), etc., are correlated with the gelation ability of numerous classes of molecular gelators. Advanced solvent clustering techniques have led to the development of a priori tools that can identify the solvents that will be gelled and not gelled by molecular gelators. These tools will greatly aid in the development of novel gelators without solely relying on serendipitous discoveries.

Estimating Mass of Inflatable Aerodynamic Decelerators Using Dimensionless Parameters

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2011-01-01

This paper describes a technique for estimating mass for inflatable aerodynamic decelerators. The technique uses dimensional analysis to identify a set of dimensionless parameters for inflation pressure, mass of inflation gas, and mass of flexible material. The dimensionless parameters enable scaling of an inflatable concept with geometry parameters (e.g., diameter), environmental conditions (e.g., dynamic pressure), inflation gas properties (e.g., molecular mass), and mass growth allowance. This technique is applicable for attached (e.g., tension cone, hypercone, and stacked toroid) and trailing inflatable aerodynamic decelerators. The technique uses simple engineering approximations that were developed by NASA in the 1960s and 1970s, as well as some recent important developments. The NASA Mars Entry and Descent Landing System Analysis (EDL-SA) project used this technique to estimate the masses of the inflatable concepts that were used in the analysis. The EDL-SA results compared well with two independent sets of high-fidelity finite element analyses.

Replicates, read numbers, and other important experimental design considerations for microbial RNA-seq identified using Bacillus thuringiensis datasets

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

Lu, Tse -Yuan; Mehlhorn, Tonia L; Pelletier, Dale A.

RNA-seq is being used increasingly for gene expression studies and it is revolutionizing the fields of genomics and transcriptomics. However, the field of RNA-seq analysis is still evolving. Therefore, we specifically designed this study to contain large numbers of reads and four biological replicates per condition so we could alter these parameters and assess their impact on differential expression results. Bacillus thuringiensis strains ATCC10792 and CT43 were grown in two Luria broth medium lots on four dates and transcriptomics data were generated using one lane of sequence output from an Illumina HiSeq2000 instrument for each of the 32 samples, whichmore » were then analyzed using DESeq2. Genome coverages across samples ranged from 87 to 465X with medium lots and culture dates identified as major variation sources. Significantly differentially expressed genes (5% FDR, two-fold change) were detected for cultures grown using different medium lots and between different dates. The highly differentially expressed iron acquisition and metabolism genes, were a likely consequence of differing amounts of iron in the two media lots. Indeed, in this study RNA-seq was a tool for predictive biology since we hypothesized and confirmed the two LB medium lots had different iron contents (~two-fold difference). Furthermore, this study shows that the noise in data can be controlled and minimized with appropriate experimental design and by having the appropriate number of replicates and reads for the system being studied. We outline parameters for an efficient and cost effective microbial transcriptomics study.« less

Replicates, read numbers, and other important experimental design considerations for microbial RNA-seq identified using Bacillus thuringiensis datasets

DOE PAGES

Lu, Tse -Yuan; Mehlhorn, Tonia L; Pelletier, Dale A.; ...

2016-05-31

RNA-seq is being used increasingly for gene expression studies and it is revolutionizing the fields of genomics and transcriptomics. However, the field of RNA-seq analysis is still evolving. Therefore, we specifically designed this study to contain large numbers of reads and four biological replicates per condition so we could alter these parameters and assess their impact on differential expression results. Bacillus thuringiensis strains ATCC10792 and CT43 were grown in two Luria broth medium lots on four dates and transcriptomics data were generated using one lane of sequence output from an Illumina HiSeq2000 instrument for each of the 32 samples, whichmore » were then analyzed using DESeq2. Genome coverages across samples ranged from 87 to 465X with medium lots and culture dates identified as major variation sources. Significantly differentially expressed genes (5% FDR, two-fold change) were detected for cultures grown using different medium lots and between different dates. The highly differentially expressed iron acquisition and metabolism genes, were a likely consequence of differing amounts of iron in the two media lots. Indeed, in this study RNA-seq was a tool for predictive biology since we hypothesized and confirmed the two LB medium lots had different iron contents (~two-fold difference). Furthermore, this study shows that the noise in data can be controlled and minimized with appropriate experimental design and by having the appropriate number of replicates and reads for the system being studied. We outline parameters for an efficient and cost effective microbial transcriptomics study.« less

Replicates, Read Numbers, and Other Important Experimental Design Considerations for Microbial RNA-seq Identified Using Bacillus thuringiensis Datasets.

PubMed

Manga, Punita; Klingeman, Dawn M; Lu, Tse-Yuan S; Mehlhorn, Tonia L; Pelletier, Dale A; Hauser, Loren J; Wilson, Charlotte M; Brown, Steven D

2016-01-01

RNA-seq is being used increasingly for gene expression studies and it is revolutionizing the fields of genomics and transcriptomics. However, the field of RNA-seq analysis is still evolving. Therefore, we specifically designed this study to contain large numbers of reads and four biological replicates per condition so we could alter these parameters and assess their impact on differential expression results. Bacillus thuringiensis strains ATCC10792 and CT43 were grown in two Luria broth medium lots on four dates and transcriptomics data were generated using one lane of sequence output from an Illumina HiSeq2000 instrument for each of the 32 samples, which were then analyzed using DESeq2. Genome coverages across samples ranged from 87 to 465X with medium lots and culture dates identified as major variation sources. Significantly differentially expressed genes (5% FDR, two-fold change) were detected for cultures grown using different medium lots and between different dates. The highly differentially expressed iron acquisition and metabolism genes, were a likely consequence of differing amounts of iron in the two media lots. Indeed, in this study RNA-seq was a tool for predictive biology since we hypothesized and confirmed the two LB medium lots had different iron contents (~two-fold difference). This study shows that the noise in data can be controlled and minimized with appropriate experimental design and by having the appropriate number of replicates and reads for the system being studied. We outline parameters for an efficient and cost effective microbial transcriptomics study.

Genomic Analyses Yield Markers for Identifying Agronomically Important Genes in Potato

USDA-ARS?s Scientific Manuscript database

This study explores the genetic architecture underling the potato evolution through a comprehensive assessment of wild and cultivated potato species based on the re-sequencing of 201 accessions of Solanum section Petota with >12 × genome coverage. We identified 450 domesticated genes, which showed e...

Systematic parameter estimation and sensitivity analysis using a multidimensional PEMFC model coupled with DAKOTA.

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

Wang, Chao Yang; Luo, Gang; Jiang, Fangming

2010-05-01

Current computational models for proton exchange membrane fuel cells (PEMFCs) include a large number of parameters such as boundary conditions, material properties, and numerous parameters used in sub-models for membrane transport, two-phase flow and electrochemistry. In order to successfully use a computational PEMFC model in design and optimization, it is important to identify critical parameters under a wide variety of operating conditions, such as relative humidity, current load, temperature, etc. Moreover, when experimental data is available in the form of polarization curves or local distribution of current and reactant/product species (e.g., O2, H2O concentrations), critical parameters can be estimated inmore » order to enable the model to better fit the data. Sensitivity analysis and parameter estimation are typically performed using manual adjustment of parameters, which is also common in parameter studies. We present work to demonstrate a systematic approach based on using a widely available toolkit developed at Sandia called DAKOTA that supports many kinds of design studies, such as sensitivity analysis as well as optimization and uncertainty quantification. In the present work, we couple a multidimensional PEMFC model (which is being developed, tested and later validated in a joint effort by a team from Penn State Univ. and Sandia National Laboratories) with DAKOTA through the mapping of model parameters to system responses. Using this interface, we demonstrate the efficiency of performing simple parameter studies as well as identifying critical parameters using sensitivity analysis. Finally, we show examples of optimization and parameter estimation using the automated capability in DAKOTA.« less

Advanced Method to Estimate Fuel Slosh Simulation Parameters

NASA Technical Reports Server (NTRS)

Schlee, Keith; Gangadharan, Sathya; Ristow, James; Sudermann, James; Walker, Charles; Hubert, Carl

2005-01-01

The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. The nutation of a spacecraft spinning about its minor axis typically grows exponentially and the rate of growth is characterized by the Nutation Time Constant (NTC). For launch vehicles using spin-stabilized upper stages, fuel slosh in the spacecraft propellant tanks is usually the primary source of energy dissipation. For analytical prediction of the NTC this fuel slosh is commonly modeled using simple mechanical analogies such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Analytic determination of the slosh model parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices and elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The proposed research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics-based computer simulation of the experimental setup. Different parameter estimation and optimization approaches are evaluated and compared in order to arrive at a reliable and effective parameter identification process. To evaluate each parameter identification approach, a simple one-degree-of-freedom pendulum experiment is constructed and motion is induced using an electric motor. By applying the

Identify source location and release time for pollutants undergoing super-diffusion and decay: Parameter analysis and model evaluation

NASA Astrophysics Data System (ADS)

Zhang, Yong; Sun, HongGuang; Lu, Bingqing; Garrard, Rhiannon; Neupauer, Roseanna M.

2017-09-01

Backward models have been applied for four decades by hydrologists to identify the source of pollutants undergoing Fickian diffusion, while analytical tools are not available for source identification of super-diffusive pollutants undergoing decay. This technical note evaluates analytical solutions for the source location and release time of a decaying contaminant undergoing super-diffusion using backward probability density functions (PDFs), where the forward model is the space fractional advection-dispersion equation with decay. Revisit of the well-known MADE-2 tracer test using parameter analysis shows that the peak backward location PDF can predict the tritium source location, while the peak backward travel time PDF underestimates the tracer release time due to the early arrival of tracer particles at the detection well in the maximally skewed, super-diffusive transport. In addition, the first-order decay adds additional skewness toward earlier arrival times in backward travel time PDFs, resulting in a younger release time, although this impact is minimized at the MADE-2 site due to tritium's half-life being relatively longer than the monitoring period. The main conclusion is that, while non-trivial backward techniques are required to identify pollutant source location, the pollutant release time can and should be directly estimated given the speed of the peak resident concentration for super-diffusive pollutants with or without decay.

Relationships between remotely sensed fisheries distribution information and selected oceanographic parameters in the Mississippi Sound

NASA Technical Reports Server (NTRS)

Kemmerer, A. J.; Benigno, J. A.

1973-01-01

The author has identified the following significant results. A feasibility study to demonstrate the potential of satellites for providing fisheries significant information was conducted in the Mississippi Sound and adjacent offshore waters. Attempts were made to relate satellite acquired imagery to selected oceanographic parameters and then to relate these parameters to aircraft remotely sensed distribution patterns of resident surface schooling fishes. Initial results suggest that this approach is valid and that the satellite acquired imagery may have important fisheries resource assessment implications.

Identifying selectively important amino acid positions associated with alternative habitat environments in fish mitochondrial genomes.

PubMed

Xia, Jun Hong; Li, Hong Lian; Zhang, Yong; Meng, Zi Ning; Lin, Hao Ran

2018-05-01

Fish species inhabitating seawater (SW) or freshwater (FW) habitats have to develop genetic adaptations to alternative environment factors, especially salinity. Functional consequences of the protein variations associated with habitat environments in fish mitochondrial genomes have not yet received much attention. We analyzed 829 complete fish mitochondrial genomes and compared the amino acid differences of 13 mitochondrial protein families between FW and SW fish groups. We identified 47 specificity determining sites (SDS) that associated with FW or SW environments from 12 mitochondrial protein families. Thirty-two (68%) of the SDS sites are hydrophobic, 13 (28%) are neutral, and the remaining sites are acidic or basic. Seven of those SDS from ND1, ND2 and ND5 were scored as probably damaging to the protein structures. Furthermore, phylogenetic tree based Bayes Empirical Bayes analysis also detected 63 positive sites associated with alternative habitat environments across ten mtDNA proteins. These signatures could be important for studying mitochondrial genetic variation relevant to fish physiology and ecology.

Triangulating Principal Effectiveness: How Perspectives of Parents, Teachers, and Assistant Principals Identify the Central Importance of Managerial Skills. Working Paper 35

ERIC Educational Resources Information Center

Grissom, Jason A.; Loeb, Susanna

2009-01-01

While the importance of effective principals is undisputed, few studies have addressed what specific skills principals need to promote school success. This study draws on unique data combining survey responses from principals, assistant principals, teachers and parents with rich administrative data to identify which principal skills matter most…

Assessing the Impact of Model Parameter Uncertainty in Simulating Grass Biomass Using a Hybrid Carbon Allocation Strategy

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Adam, J. C.; Tague, C.

2016-12-01

Grasslands play an important role in agricultural production as forage for livestock; they also provide a diverse set of ecosystem services including soil carbon (C) storage. The partitioning of C between above and belowground plant compartments (i.e. allocation) is influenced by both plant characteristics and environmental conditions. The objectives of this study are to 1) develop and evaluate a hybrid C allocation strategy suitable for grasslands, and 2) apply this strategy to examine the importance of various parameters related to biogeochemical cycling, photosynthesis, allocation, and soil water drainage on above and belowground biomass. We include allocation as an important process in quantifying the model parameter uncertainty, which identifies the most influential parameters and what processes may require further refinement. For this, we use the Regional Hydro-ecologic Simulation System, a mechanistic model that simulates coupled water and biogeochemical processes. A Latin hypercube sampling scheme was used to develop parameter sets for calibration and evaluation of allocation strategies, as well as parameter uncertainty analysis. We developed the hybrid allocation strategy to integrate both growth-based and resource-limited allocation mechanisms. When evaluating the new strategy simultaneously for above and belowground biomass, it produced a larger number of less biased parameter sets: 16% more compared to resource-limited and 9% more compared to growth-based. This also demonstrates its flexible application across diverse plant types and environmental conditions. We found that higher parameter importance corresponded to sub- or supra-optimal resource availability (i.e. water, nutrients) and temperature ranges (i.e. too hot or cold). For example, photosynthesis-related parameters were more important at sites warmer than the theoretical optimal growth temperature. Therefore, larger values of parameter importance indicate greater relative sensitivity in

A lateral dynamics of a wheelchair: identification and analysis of tire parameters.

PubMed

Silva, L C A; Corrêa, F C; Eckert, J J; Santiciolli, F M; Dedini, F G

2017-02-01

In vehicle dynamics studies, the tire behaviour plays an important role in planar motion of the vehicle. Therefore, a correct representation of tire is a necessity. This paper describes a mathematical model for wheelchair tire based on the Magic Formula model. This model is widely used to represent forces and moments between the tire and the ground; however some experimental parameters must be determined. The purpose of this work is to identify the tire parameters for the wheelchair tire model, implementing them in a dynamic model of the wheelchair. For this, we developed an experimental test rig to measure the tires parameters for the lateral dynamics of a wheelchair. This dynamic model was made using a multi-body software and the wheelchair behaviour was analysed and discussed according to the tire parameters. The result of this work is one step further towards the understanding of wheelchair dynamics.

Semi-physical parameter identification for an iron-loss formula allowing loss-separation

NASA Astrophysics Data System (ADS)

Steentjes, S.; Leßmann, M.; Hameyer, K.

2013-05-01

This paper presents a semi-physical parameter identification for a recently proposed enhanced iron-loss formula, the IEM-Formula. Measurements are performed on a standardized Epstein frame by the conventional field-metric method under sinusoidal magnetic flux densities up to high magnitudes and frequencies. Quasi-static losses are identified on the one hand by point-by-point dc-measurements using a flux-meter and on the other hand by extrapolating higher frequency measurements to dc magnetization using the statistical loss-separation theory (Jacobs et al., "Magnetic material optimization for hybrid vehicle PMSM drives," in Inductica Conference, CD-Rom, Chicago/USA, 2009). Utilizing this material information, possibilities to identify the parameter of the IEM-Formula are analyzed. Along with this, the importance of excess losses in present-day non-grain oriented Fe-Si laminations is investigated. In conclusion, the calculated losses are compared to the measured losses.

Optimal Linking Design for Response Model Parameters

ERIC Educational Resources Information Center

Barrett, Michelle D.; van der Linden, Wim J.

2017-01-01

Linking functions adjust for differences between identifiability restrictions used in different instances of the estimation of item response model parameters. These adjustments are necessary when results from those instances are to be compared. As linking functions are derived from estimated item response model parameters, parameter estimation…

Brief Report: Coherent Motion Processing in Autism: Is Dot Lifetime an Important Parameter?

ERIC Educational Resources Information Center

Manning, Catherine; Charman, Tony; Pellicano, Elizabeth

2015-01-01

Contrasting reports of "reduced" and "intact" sensitivity to coherent motion in autistic individuals may be attributable to stimulus parameters. Here, we investigated whether dot lifetime contributes to elevated thresholds in children with autism. We presented a standard motion coherence task to 31 children with autism and 31…

Scalable persistent identifier systems for dynamic datasets

NASA Astrophysics Data System (ADS)

Golodoniuc, P.; Cox, S. J. D.; Klump, J. F.

2016-12-01

Reliable and persistent identification of objects, whether tangible or not, is essential in information management. Many Internet-based systems have been developed to identify digital data objects, e.g., PURL, LSID, Handle, ARK. These were largely designed for identification of static digital objects. The amount of data made available online has grown exponentially over the last two decades and fine-grained identification of dynamically generated data objects within large datasets using conventional systems (e.g., PURL) has become impractical. We have compared capabilities of various technological solutions to enable resolvability of data objects in dynamic datasets, and developed a dataset-centric approach to resolution of identifiers. This is particularly important in Semantic Linked Data environments where dynamic frequently changing data is delivered live via web services, so registration of individual data objects to obtain identifiers is impractical. We use identifier patterns and pattern hierarchies for identification of data objects, which allows relationships between identifiers to be expressed, and also provides means for resolving a single identifier into multiple forms (i.e. views or representations of an object). The latter can be implemented through (a) HTTP content negotiation, or (b) use of URI querystring parameters. The pattern and hierarchy approach has been implemented in the Linked Data API supporting the United Nations Spatial Data Infrastructure (UNSDI) initiative and later in the implementation of geoscientific data delivery for the Capricorn Distal Footprints project using International Geo Sample Numbers (IGSN). This enables flexible resolution of multi-view persistent identifiers and provides a scalable solution for large heterogeneous datasets.

Near Identifiability of Dynamical Systems

NASA Technical Reports Server (NTRS)

Hadaegh, F. Y.; Bekey, G. A.

1987-01-01

Concepts regarding approximate mathematical models treated rigorously. Paper presents new results in analysis of structural identifiability, equivalence, and near equivalence between mathematical models and physical processes they represent. Helps establish rigorous mathematical basis for concepts related to structural identifiability and equivalence revealing fundamental requirements, tacit assumptions, and sources of error. "Structural identifiability," as used by workers in this field, loosely translates as meaning ability to specify unique mathematical model and set of model parameters that accurately predict behavior of corresponding physical system.

Simultaneous Estimation of Microphysical Parameters and Atmospheric State Variables With Radar Data and Ensemble Square-root Kalman Filter

NASA Astrophysics Data System (ADS)

Tong, M.; Xue, M.

2006-12-01

An important source of model error for convective-scale data assimilation and prediction is microphysical parameterization. This study investigates the possibility of estimating up to five fundamental microphysical parameters, which are closely involved in the definition of drop size distribution of microphysical species in a commonly used single-moment ice microphysics scheme, using radar observations and the ensemble Kalman filter method. The five parameters include the intercept parameters for rain, snow and hail/graupel, and the bulk densities of hail/graupel and snow. Parameter sensitivity and identifiability are first examined. The ensemble square-root Kalman filter (EnSRF) is employed for simultaneous state and parameter estimation. OSS experiments are performed for a model-simulated supercell storm, in which the five microphysical parameters are estimated individually or in different combinations starting from different initial guesses. When error exists in only one of the microphysical parameters, the parameter can be successfully estimated without exception. The estimation of multiple parameters is found to be less robust, with end results of estimation being sensitive to the realization of the initial parameter perturbation. This is believed to be because of the reduced parameter identifiability and the existence of non-unique solutions. The results of state estimation are, however, always improved when simultaneous parameter estimation is performed, even when the estimated parameters values are not accurate.

FTIRI Parameters describing Acid Phosphate Substitution in Biologic Hydroxyapatite

PubMed Central

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

2013-01-01

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

Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model

NASA Astrophysics Data System (ADS)

Demaria, Eleonora M.; Nijssen, Bart; Wagener, Thorsten

2007-06-01

Current land surface models use increasingly complex descriptions of the processes that they represent. Increase in complexity is accompanied by an increase in the number of model parameters, many of which cannot be measured directly at large spatial scales. A Monte Carlo framework was used to evaluate the sensitivity and identifiability of ten parameters controlling surface and subsurface runoff generation in the Variable Infiltration Capacity model (VIC). Using the Monte Carlo Analysis Toolbox (MCAT), parameter sensitivities were studied for four U.S. watersheds along a hydroclimatic gradient, based on a 20-year data set developed for the Model Parameter Estimation Experiment (MOPEX). Results showed that simulated streamflows are sensitive to three parameters when evaluated with different objective functions. Sensitivity of the infiltration parameter (b) and the drainage parameter (exp) were strongly related to the hydroclimatic gradient. The placement of vegetation roots played an important role in the sensitivity of model simulations to the thickness of the second soil layer (thick2). Overparameterization was found in the base flow formulation indicating that a simplified version could be implemented. Parameter sensitivity was more strongly dictated by climatic gradients than by changes in soil properties. Results showed how a complex model can be reduced to a more parsimonious form, leading to a more identifiable model with an increased chance of successful regionalization to ungauged basins. Although parameter sensitivities are strictly valid for VIC, this model is representative of a wider class of macroscale hydrological models. Consequently, the results and methodology will have applicability to other hydrological models.

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines.

PubMed

Teodoro, George; Kurç, Tahsin M; Taveira, Luís F R; Melo, Alba C M A; Gao, Yi; Kong, Jun; Saltz, Joel H

2017-04-01

Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Source code: https://github.com/SBU-BMI/region-templates/ . teodoro@unb.br. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Importance of double-pole CFS-PML for broad-band seismic wave simulation and optimal parameters selection

NASA Astrophysics Data System (ADS)

Feng, Haike; Zhang, Wei; Zhang, Jie; Chen, Xiaofei

2017-05-01

The perfectly matched layer (PML) is an efficient absorbing technique for numerical wave simulation. The complex frequency-shifted PML (CFS-PML) introduces two additional parameters in the stretching function to make the absorption frequency dependent. This can help to suppress converted evanescent waves from near grazing incident waves, but does not efficiently absorb low-frequency waves below the cut-off frequency. To absorb both the evanescent wave and the low-frequency wave, the double-pole CFS-PML having two poles in the coordinate stretching function was developed in computational electromagnetism. Several studies have investigated the performance of the double-pole CFS-PML for seismic wave simulations in the case of a narrowband seismic wavelet and did not find significant difference comparing to the CFS-PML. Another difficulty to apply the double-pole CFS-PML for real problems is that a practical strategy to set optimal parameter values has not been established. In this work, we study the performance of the double-pole CFS-PML for broad-band seismic wave simulation. We find that when the maximum to minimum frequency ratio is larger than 16, the CFS-PML will either fail to suppress the converted evanescent waves for grazing incident waves, or produce visible low-frequency reflection, depending on the value of α. In contrast, the double-pole CFS-PML can simultaneously suppress the converted evanescent waves and avoid low-frequency reflections with proper parameter values. We analyse the different roles of the double-pole CFS-PML parameters and propose optimal selections of these parameters. Numerical tests show that the double-pole CFS-PML with the optimal parameters can generate satisfactory results for broad-band seismic wave simulations.

Three novel approaches to structural identifiability analysis in mixed-effects models.

PubMed

Janzén, David L I; Jirstrand, Mats; Chappell, Michael J; Evans, Neil D

2016-05-06

Structural identifiability is a concept that considers whether the structure of a model together with a set of input-output relations uniquely determines the model parameters. In the mathematical modelling of biological systems, structural identifiability is an important concept since biological interpretations are typically made from the parameter estimates. For a system defined by ordinary differential equations, several methods have been developed to analyse whether the model is structurally identifiable or otherwise. Another well-used modelling framework, which is particularly useful when the experimental data are sparsely sampled and the population variance is of interest, is mixed-effects modelling. However, established identifiability analysis techniques for ordinary differential equations are not directly applicable to such models. In this paper, we present and apply three different methods that can be used to study structural identifiability in mixed-effects models. The first method, called the repeated measurement approach, is based on applying a set of previously established statistical theorems. The second method, called the augmented system approach, is based on augmenting the mixed-effects model to an extended state-space form. The third method, called the Laplace transform mixed-effects extension, is based on considering the moment invariants of the systems transfer function as functions of random variables. To illustrate, compare and contrast the application of the three methods, they are applied to a set of mixed-effects models. Three structural identifiability analysis methods applicable to mixed-effects models have been presented in this paper. As method development of structural identifiability techniques for mixed-effects models has been given very little attention, despite mixed-effects models being widely used, the methods presented in this paper provides a way of handling structural identifiability in mixed-effects models previously not

Parameter estimation in Probabilistic Seismic Hazard Analysis: current problems and some solutions

NASA Astrophysics Data System (ADS)

Vermeulen, Petrus

2017-04-01

, none of which is accepted as the standard one. There is also much controversy surrounding this parameter. In practice, when estimating the above mentioned parameters from seismic catalogue, the magnitude, mmin, from which a seismic catalogue is complete becomes important.Thus, the parameter mmin is also considered as a parameter to be estimated in practice. Several methods are discussed in the literature, and no specific method is preferred. Methods usually aim at identifying the point where a frequency-magnitude plot starts to deviate from linearity due to data loss. Parameter estimation is clearly a rich field which deserves much attention and, possibly standardization, of methods. These methods should be the sound and efficient, and a query into which methods are to be used - and for that matter which ones are not to be used - is in order.

Quantitative DNA Methylation Analysis Identifies a Single CpG Dinucleotide Important for ZAP-70 Expression and Predictive of Prognosis in Chronic Lymphocytic Leukemia

PubMed Central

Claus, Rainer; Lucas, David M.; Stilgenbauer, Stephan; Ruppert, Amy S.; Yu, Lianbo; Zucknick, Manuela; Mertens, Daniel; Bühler, Andreas; Oakes, Christopher C.; Larson, Richard A.; Kay, Neil E.; Jelinek, Diane F.; Kipps, Thomas J.; Rassenti, Laura Z.; Gribben, John G.; Döhner, Hartmut; Heerema, Nyla A.; Marcucci, Guido; Plass, Christoph; Byrd, John C.

2012-01-01

Purpose Increased ZAP-70 expression predicts poor prognosis in chronic lymphocytic leukemia (CLL). Current methods for accurately measuring ZAP-70 expression are problematic, preventing widespread application of these tests in clinical decision making. We therefore used comprehensive DNA methylation profiling of the ZAP-70 regulatory region to identify sites important for transcriptional control. Patients and Methods High-resolution quantitative DNA methylation analysis of the entire ZAP-70 gene regulatory regions was conducted on 247 samples from patients with CLL from four independent clinical studies. Results Through this comprehensive analysis, we identified a small area in the 5′ regulatory region of ZAP-70 that showed large variability in methylation in CLL samples but was universally methylated in normal B cells. High correlation with mRNA and protein expression, as well as activity in promoter reporter assays, revealed that within this differentially methylated region, a single CpG dinucleotide and neighboring nucleotides are particularly important in ZAP-70 transcriptional regulation. Furthermore, by using clustering approaches, we identified a prognostic role for this site in four independent data sets of patients with CLL using time to treatment, progression-free survival, and overall survival as clinical end points. Conclusion Comprehensive quantitative DNA methylation analysis of the ZAP-70 gene in CLL identified important regions responsible for transcriptional regulation. In addition, loss of methylation at a specific single CpG dinucleotide in the ZAP-70 5′ regulatory sequence is a highly predictive and reproducible biomarker of poor prognosis in this disease. This work demonstrates the feasibility of using quantitative specific ZAP-70 methylation analysis as a relevant clinically applicable prognostic test in CLL. PMID:22564988

Diagnostic importance of 18F-FDG PET/CT parameters and total lesion glycolysis in differentiating between benign and malignant adrenal lesions.

PubMed

Ciftci, Esra; Turgut, Bulent; Cakmakcilar, Ali; Erturk, Seyit A

2017-09-01

Benign adrenal lesions are prevalent in oncologic imaging and make metastatic disease diagnoses difficult. This study evaluates the diagnostic importance of metabolic, volumetric, and metabolovolumetric parameters measured by fluorine-18-fluorodeoxyglucose (F-FDG) PET/CT in differentiating between benign and malignant adrenal lesions in cancer patients. In this retrospective study, we evaluated F-FDG PET/CT parameters of adrenal lesions of follow-up cancer patients referred to our clinic between January 2012 and November 2016. The diagnosis of adrenal malignant lesions was made on the basis of interval growth or reduction after chemotherapy. Patient demographics, analysis of metabolic parameters such as maximum standard uptake value (SUVmax), tumor SUVmax/liver SUVmean ratio (T/LR), morphologic parameters such as size, Hounsfield Units, and computed tomography (CT) volume, and metabolovolumetric parameters such as metabolic tumor volume and total lesion glycolysis (TLG) of adrenal lesions were calculated. PET/CT parameters were assessed using the Mann-Whitney U-test and receiving operating characteristic analysis. In total, 186 adrenal lesions in 163 cancer patients (108 men/54 women; mean±SD age: 64±10.9 years) were subjected to F-FDG PET/CT for tumor evaluation. SUVmax values (mean±SD) were 2.8±0.8 and 10.6±6; TLG were 10.8±9.2 and 124.4±347.9; and T/LR were 1±0.3 and 4.1±2.6 in benign and malignant adrenal lesions, respectively. On the basis of the area under the curve, adrenal lesion SUVmax and T/LR had similar highest diagnostic performance for predicting malignant lesions (area under the curve: 0.993 and 0.991, respectively, P<0.001). Multivariate logistic regression analysis showed that T/LR, adrenal lesion SUVmax, and Hounsfield Units were independent predictive factors for malignancy rather than TLG. Irrespective of whether TLG was statistically highly significant for differentiating benign from malignant adrenal lesions, it did not reach the

Critical modeling parameters identified for 3D CFD modeling of rectangular final settling tanks for New York City wastewater treatment plants.

PubMed

Ramalingam, K; Xanthos, S; Gong, M; Fillos, J; Beckmann, K; Deur, A; McCorquodale, J A

2012-01-01

New York City Environmental Protection is in the process of incorporating biological nitrogen removal (BNR) in its wastewater treatment plants (WWTPs) which entails operating the aeration tanks with higher levels of mixed liquor suspended solids (MLSS) than a conventional activated sludge process. The objective of this paper is to discuss two of the important parameters introduced in the 3D CFD model that has been developed by the City College of New York (CCNY) group: (a) the development of the 'discrete particle' measurement technique to carry out the fractionation of the solids in the final settling tank (FST) which has critical implications in the prediction of the effluent quality; and (b) the modification of the floc aggregation (K(A)) and floc break-up (K(B)) coefficients that are found in Parker's flocculation equation (Parker et al. 1970, 1971) used in the CFD model. The dependence of these parameters on the predictions of the CFD model will be illustrated with simulation results on one of the FSTs at the 26th Ward WWTP in Brooklyn, NY.

Identifying desertification risk areas using fuzzy membership and geospatial technique - A case study, Kota District, Rajasthan

NASA Astrophysics Data System (ADS)

Dasgupta, Arunima; Sastry, K. L. N.; Dhinwa, P. S.; Rathore, V. S.; Nathawat, M. S.

2013-08-01

Desertification risk assessment is important in order to take proper measures for its prevention. Present research intends to identify the areas under risk of desertification along with their severity in terms of degradation in natural parameters. An integrated model with fuzzy membership analysis, fuzzy rule-based inference system and geospatial techniques was adopted, including five specific natural parameters namely slope, soil pH, soil depth, soil texture and NDVI. Individual parameters were classified according to their deviation from mean. Membership of each individual values to be in a certain class was derived using the normal probability density function of that class. Thus if a single class of a single parameter is with mean μ and standard deviation σ, the values falling beyond μ + 2 σ and μ - 2 σ are not representing that class, but a transitional zone between two subsequent classes. These are the most important areas in terms of degradation, as they have the lowest probability to be in a certain class, hence highest probability to be extended or narrowed down in next or previous class respectively. Eventually, these are the values which can be easily altered, under extrogenic influences, hence are identified as risk areas. The overall desertification risk is derived by incorporating the different risk severity of each parameter using fuzzy rule-based interference system in GIS environment. Multicriteria based geo-statistics are applied to locate the areas under different severity of desertification risk. The study revealed that in Kota, various anthropogenic pressures are accelerating land deterioration, coupled with natural erosive forces. Four major sources of desertification in Kota are, namely Gully and Ravine erosion, inappropriate mining practices, growing urbanization and random deforestation.

Identifying the Most Important 21st Century Workforce Competencies: An Analysis of the Occupational Information Network (O*NET). Research Report. ETS RR-13-21

ERIC Educational Resources Information Center

Burrus, Jeremy; Jackson, Teresa; Xi, Nuo; Steinberg, Jonathan

2013-01-01

To identify the most important competencies for college graduates to succeed in the 21st century workforce, we conducted an analysis of the Occupational Information Network (O*NET) database. O*NET is a large job analysis operated and maintained by the U.S. Department of Labor. We specifically analyzed ratings of the importance of abilities (52…

Parameters affecting mechanical and thermal responses in bone drilling: A review.

PubMed

Lee, JuEun; Chavez, Craig L; Park, Joorok

2018-04-11

Surgical bone drilling is performed variously to correct bone fractures, install prosthetics, or for therapeutic treatment. The primary concern in bone drilling is to extract donor bone sections and create receiving holes without damaging the bone tissue either mechanically or thermally. We review current results from experimental and theoretical studies to investigate the parameters related to such effects. This leads to a comprehensive understanding of the mechanical and thermal aspects of bone drilling to reduce their unwanted complications. This review examines the important bone-drilling parameters of bone structure, drill-bit geometry, operating conditions, and material evacuation, and considers the current techniques used in bone drilling. We then analyze the associated mechanical and thermal effects and their contributions to bone-drilling performance. In this review, we identify a favorable range for each parameter to reduce unwanted complications due to mechanical or thermal effects. Copyright © 2018 Elsevier Ltd. All rights reserved.

Identifying critical road geometry parameters affecting crash rate and crash type.

PubMed

Othman, Sarbaz; Thomson, Robert; Lannér, Gunnar

2009-10-01

The objective of this traffic safety investigation was to find critical road parameters affecting crash rate (CR). The study was based on crash and road maintenance data from Western Sweden. More than 3000 crashes, reported from 2000 to 2005 on median-separated roads, were collected and combined with road geometric and surface data. The statistical analysis showed variations in CR when road elements changed confirming that road characteristics affect CR. The findings indicated that large radii right-turn curves were more dangerous than left curves, in particular, during lane changing manoeuvres. However sharper curves are more dangerous in both left and right curves. Moreover, motorway carriageways with no or limited shoulders have the highest CR when compared to other carriageway widths, while one lane carriageway sections on 2+1 roads were the safest. Road surface results showed that both wheel rut depth and road roughness have negative impacts on traffic safety.

Probabilistic parameter estimation of activated sludge processes using Markov Chain Monte Carlo.

PubMed

Sharifi, Soroosh; Murthy, Sudhir; Takács, Imre; Massoudieh, Arash

2014-03-01

One of the most important challenges in making activated sludge models (ASMs) applicable to design problems is identifying the values of its many stoichiometric and kinetic parameters. When wastewater characteristics data from full-scale biological treatment systems are used for parameter estimation, several sources of uncertainty, including uncertainty in measured data, external forcing (e.g. influent characteristics), and model structural errors influence the value of the estimated parameters. This paper presents a Bayesian hierarchical modeling framework for the probabilistic estimation of activated sludge process parameters. The method provides the joint probability density functions (JPDFs) of stoichiometric and kinetic parameters by updating prior information regarding the parameters obtained from expert knowledge and literature. The method also provides the posterior correlations between the parameters, as well as a measure of sensitivity of the different constituents with respect to the parameters. This information can be used to design experiments to provide higher information content regarding certain parameters. The method is illustrated using the ASM1 model to describe synthetically generated data from a hypothetical biological treatment system. The results indicate that data from full-scale systems can narrow down the ranges of some parameters substantially whereas the amount of information they provide regarding other parameters is small, due to either large correlations between some of the parameters or a lack of sensitivity with respect to the parameters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Isolated severe tricuspid regurgitation: the importance of identifying underlying mechanism.

PubMed

Poh, Kian Keong; Solis, Jorge; Hung, Judy

2008-07-21

An 88-year-old woman presented with right heart failure, history of diarrhoea, abdominal pain, weight lost, dyspnoea over several weeks and a new pan-systolic murmur. Echocardiography showed retracted tricuspid leaflets with incomplete coaptation resulting in severe regurgitation. Subcostal view showed an adjacent hepatic cyst leading to biopsy, which revealed neoplastic neuroendocrine cells. Her 24-hour urinary 5-hydroxyindoleacetic acid level was elevated. The unifying diagnosis was carcinoid syndrome for which she was treated. Echocardiography is an important tool for diagnosis, management and prognosis of carcinoid heart disease.

Perceived cultural importance and actual self-importance of values in cultural identification.

PubMed

Wan, Ching; Chiu, Chi-yue; Tam, Kim-pong; Lee, Sau-lai; Lau, Ivy Yee-man; Peng, Siqing

2007-02-01

Cross-cultural psychologists assume that core cultural values define to a large extent what a culture is. Typically, core values are identified through an actual self-importance approach, in which core values are those that members of the culture as a group strongly endorse. In this article, the authors propose a perceived cultural importance approach to identifying core values, in which core values are values that members of the culture as a group generally believe to be important in the culture. In 5 studies, the authors examine the utility of the perceived cultural importance approach. Results consistently showed that, compared with values of high actual self-importance, values of high perceived cultural importance play a more important role in cultural identification. These findings have important implications for conceptualizing and measuring cultures. ((c) 2007 APA, all rights reserved).

Sperm DNA damage output parameters measured by the alkaline Comet assay and their importance.

PubMed

Simon, L; Aston, K I; Emery, B R; Hotaling, J; Carrell, D T

2017-03-01

The alkaline Comet assay has shown high diagnostic value to determine male reproductive health and prognostic ability to predict ART success. Here, spermatozoon was analysed in 47 fertile donors and 238 patients, including 132 couples undergoing ART [semen was collected: Group I - within 3 months of their treatment (n = 79); and Group II - 3 months prior to their treatment (n = 53)]. We introduce four Comet distribution plots (A, B1, B2 and C) by plotting the level of DNA damage (x-axis) and percentage of comets (y-axis). Fertile donors had low mean DNA damage, olive tail moment and per cent of spermatozoa with damage and increased type A plots. Comet parameters were associated with clinical pregnancies in Group I. About 66% of couples with type A distribution plot were successful after ART, whereas couples with type B1, B2 and C distribution plots achieved 56%, 44% and 33% pregnancies respectively. The efficiency of the Comet assay was due to complete decondensation process, where the compact sperm nuclear DNA (28.2 ± 0.2 μm 3 ) is decondensed to ~63 μm 3 (before lysis) and ~1018 μm 3 (after lysis). A combinational analysis of all the Comet output parameters may provide a comprehensive evaluation of patient's reproductive health as these parameters measure different aspects of DNA damage within the spermatozoa. © 2016 Blackwell Verlag GmbH.

Identifying Critical Road Geometry Parameters Affecting Crash Rate and Crash Type

PubMed Central

Othman, Sarbaz; Thomson, Robert; Lannér, Gunnar

2009-01-01

The objective of this traffic safety investigation was to find critical road parameters affecting crash rate (CR). The study was based on crash and road maintenance data from Western Sweden. More than 3000 crashes, reported from 2000 to 2005 on median-separated roads, were collected and combined with road geometric and surface data. The statistical analysis showed variations in CR when road elements changed confirming that road characteristics affect CR. The findings indicated that large radii right-turn curves were more dangerous than left curves, in particular, during lane changing manoeuvres. However sharper curves are more dangerous in both left and right curves. Moreover, motorway carriageways with no or limited shoulders have the highest CR when compared to other carriageway widths, while one lane carriageway sections on 2+1 roads were the safest. Road surface results showed that both wheel rut depth and road roughness have negative impacts on traffic safety. PMID:20184841

Identifying Important Career Indicators of Undergraduate Geoscience Students Upon Completion of Their Degree

NASA Astrophysics Data System (ADS)

Wilson, C. E.; Keane, C. M.; Houlton, H. R.

2012-12-01

The American Geosciences Institute (AGI) decided to create the National Geoscience Student Exit Survey in order to identify the initial pathways into the workforce for these graduating students, as well as assess their preparedness for entering the workforce upon graduation. The creation of this survey stemmed from a combination of experiences with the AGI/AGU Survey of Doctorates and discussions at the following Science Education Research Center (SERC) workshops: "Developing Pathways to Strong Programs for the Future", "Strengthening Your Geoscience Program", and "Assessing Geoscience Programs". These events identified distinct gaps in understanding the experiences and perspectives of geoscience students during one of their most profound professional transitions. Therefore, the idea for the survey arose as a way to evaluate how the discipline is preparing and educating students, as well as identifying the students' desired career paths. The discussions at the workshops solidified the need for this survey and created the initial framework for the first pilot of the survey. The purpose of this assessment tool is to evaluate student preparedness for entering the geosciences workforce; identify student decision points for entering geosciences fields and remaining in the geosciences workforce; identify geosciences fields that students pursue in undergraduate and graduate school; collect information on students' expected career trajectories and geosciences professions; identify geosciences career sectors that are hiring new graduates; collect information about salary projections; overall effectiveness of geosciences departments regionally and nationally; demonstrate the value of geosciences degrees to future students, the institutions, and employers; and establish a benchmark to perform longitudinal studies of geosciences graduates to understand their career pathways and impacts of their educational experiences on these decisions. AGI's Student Exit Survey went through

Structural identifiability analysis of a cardiovascular system model.

PubMed

Pironet, Antoine; Dauby, Pierre C; Chase, J Geoffrey; Docherty, Paul D; Revie, James A; Desaive, Thomas

2016-05-01

The six-chamber cardiovascular system model of Burkhoff and Tyberg has been used in several theoretical and experimental studies. However, this cardiovascular system model (and others derived from it) are not identifiable from any output set. In this work, two such cases of structural non-identifiability are first presented. These cases occur when the model output set only contains a single type of information (pressure or volume). A specific output set is thus chosen, mixing pressure and volume information and containing only a limited number of clinically available measurements. Then, by manipulating the model equations involving these outputs, it is demonstrated that the six-chamber cardiovascular system model is structurally globally identifiable. A further simplification is made, assuming known cardiac valve resistances. Because of the poor practical identifiability of these four parameters, this assumption is usual. Under this hypothesis, the six-chamber cardiovascular system model is structurally identifiable from an even smaller dataset. As a consequence, parameter values computed from limited but well-chosen datasets are theoretically unique. This means that the parameter identification procedure can safely be performed on the model from such a well-chosen dataset. Thus, the model may be considered suitable for use in diagnosis. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Experimental assessment of the importance of amino acid positions identified by an entropy-based correlation analysis of multiple-sequence alignments.

PubMed

Dietrich, Susanne; Borst, Nadine; Schlee, Sandra; Schneider, Daniel; Janda, Jan-Oliver; Sterner, Reinhard; Merkl, Rainer

2012-07-17

The analysis of a multiple-sequence alignment (MSA) with correlation methods identifies pairs of residue positions whose occupation with amino acids changes in a concerted manner. It is plausible to assume that positions that are part of many such correlation pairs are important for protein function or stability. We have used the algorithm H2r to identify positions k in the MSAs of the enzymes anthranilate phosphoribosyl transferase (AnPRT) and indole-3-glycerol phosphate synthase (IGPS) that show a high conn(k) value, i.e., a large number of significant correlations in which k is involved. The importance of the identified residues was experimentally validated by performing mutagenesis studies with sAnPRT and sIGPS from the archaeon Sulfolobus solfataricus. For sAnPRT, five H2r mutant proteins were generated by replacing nonconserved residues with alanine or the prevalent residue of the MSA. As a control, five residues with conn(k) values of zero were chosen randomly and replaced with alanine. The catalytic activities and conformational stabilities of the H2r and control mutant proteins were analyzed by steady-state enzyme kinetics and thermal unfolding studies. Compared to wild-type sAnPRT, the catalytic efficiencies (k(cat)/K(M)) were largely unaltered. In contrast, the apparent thermal unfolding temperature (T(M)(app)) was lowered in most proteins. Remarkably, the strongest observed destabilization (ΔT(M)(app) = 14 °C) was caused by the V284A exchange, which pertains to the position with the highest correlation signal [conn(k) = 11]. For sIGPS, six H2r mutant and four control proteins with alanine exchanges were generated and characterized. The k(cat)/K(M) values of four H2r mutant proteins were reduced between 13- and 120-fold, and their T(M)(app) values were decreased by up to 5 °C. For the sIGPS control proteins, the observed activity and stability decreases were much less severe. Our findings demonstrate that positions with high conn(k) values have an

Parameter estimation using meta-heuristics in systems biology: a comprehensive review.

PubMed

Sun, Jianyong; Garibaldi, Jonathan M; Hodgman, Charlie

2012-01-01

This paper gives a comprehensive review of the application of meta-heuristics to optimization problems in systems biology, mainly focussing on the parameter estimation problem (also called the inverse problem or model calibration). It is intended for either the system biologist who wishes to learn more about the various optimization techniques available and/or the meta-heuristic optimizer who is interested in applying such techniques to problems in systems biology. First, the parameter estimation problems emerging from different areas of systems biology are described from the point of view of machine learning. Brief descriptions of various meta-heuristics developed for these problems follow, along with outlines of their advantages and disadvantages. Several important issues in applying meta-heuristics to the systems biology modelling problem are addressed, including the reliability and identifiability of model parameters, optimal design of experiments, and so on. Finally, we highlight some possible future research directions in this field.

An analysis of parameter sensitivities of preference-inspired co-evolutionary algorithms

NASA Astrophysics Data System (ADS)

Wang, Rui; Mansor, Maszatul M.; Purshouse, Robin C.; Fleming, Peter J.

2015-10-01

Many-objective optimisation problems remain challenging for many state-of-the-art multi-objective evolutionary algorithms. Preference-inspired co-evolutionary algorithms (PICEAs) which co-evolve the usual population of candidate solutions with a family of decision-maker preferences during the search have been demonstrated to be effective on such problems. However, it is unknown whether PICEAs are robust with respect to the parameter settings. This study aims to address this question. First, a global sensitivity analysis method - the Sobol' variance decomposition method - is employed to determine the relative importance of the parameters controlling the performance of PICEAs. Experimental results show that the performance of PICEAs is controlled for the most part by the number of function evaluations. Next, we investigate the effect of key parameters identified from the Sobol' test and the genetic operators employed in PICEAs. Experimental results show improved performance of the PICEAs as more preferences are co-evolved. Additionally, some suggestions for genetic operator settings are provided for non-expert users.

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

PubMed Central

Kurç, Tahsin M.; Taveira, Luís F. R.; Melo, Alba C. M. A.; Gao, Yi; Kong, Jun; Saltz, Joel H.

2017-01-01

Abstract Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Availability and Implementation: Source code: https://github.com/SBU-BMI/region-templates/. Contact: teodoro@unb.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28062445

On Markov parameters in system identification

NASA Technical Reports Server (NTRS)

Phan, Minh; Juang, Jer-Nan; Longman, Richard W.

1991-01-01

A detailed discussion of Markov parameters in system identification is given. Different forms of input-output representation of linear discrete-time systems are reviewed and discussed. Interpretation of sampled response data as Markov parameters is presented. Relations between the state-space model and particular linear difference models via the Markov parameters are formulated. A generalization of Markov parameters to observer and Kalman filter Markov parameters for system identification is explained. These extended Markov parameters play an important role in providing not only a state-space realization, but also an observer/Kalman filter for the system of interest.

Importance of optimizing chromatographic conditions and mass spectrometric parameters for supercritical fluid chromatography/mass spectrometry.

PubMed

Fujito, Yuka; Hayakawa, Yoshihiro; Izumi, Yoshihiro; Bamba, Takeshi

2017-07-28

Supercritical fluid chromatography/mass spectrometry (SFC/MS) has great potential in high-throughput and the simultaneous analysis of a wide variety of compounds, and it has been widely used in recent years. The use of MS for detection provides the advantages of high sensitivity and high selectivity. However, the sensitivity of MS detection depends on the chromatographic conditions and MS parameters. Thus, optimization of MS parameters corresponding to the SFC condition is mandatory for maximizing performance when connecting SFC to MS. The aim of this study was to reveal a way to decide the optimum composition of the mobile phase and the flow rate of the make-up solvent for MS detection in a wide range of compounds. Additionally, we also showed the basic concept for determination of the optimum values of the MS parameters focusing on the MS detection sensitivity in SFC/MS analysis. To verify the versatility of these findings, a total of 441 pesticides with a wide polarity range (logP ow from -4.21 to 7.70) and pKa (acidic, neutral and basic). In this study, a new SFC-MS interface was used, which can transfer the entire volume of eluate into the MS by directly coupling the SFC with the MS. This enabled us to compare the sensitivity or optimum MS parameters for MS detection between LC/MS and SFC/MS for the same sample volume introduced into the MS. As a result, it was found that the optimum values of some MS parameters were completely different from those of LC/MS, and that SFC/MS-specific optimization of the analytical conditions is required. Lastly, we evaluated the sensitivity of SFC/MS using fully optimized analytical conditions. As a result, we confirmed that SFC/MS showed much higher sensitivity than LC/MS when the analytical conditions were fully optimized for SFC/MS; and the high sensitivity also increase the number of the compounds that can be detected with good repeatability in real sample analysis. This result indicates that SFC/MS has potential for

A landscape ecology approach identifies important drivers of urban biodiversity.

PubMed

Turrini, Tabea; Knop, Eva

2015-04-01

Cities are growing rapidly worldwide, yet a mechanistic understanding of the impact of urbanization on biodiversity is lacking. We assessed the impact of urbanization on arthropod diversity (species richness and evenness) and abundance in a study of six cities and nearby intensively managed agricultural areas. Within the urban ecosystem, we disentangled the relative importance of two key landscape factors affecting biodiversity, namely the amount of vegetated area and patch isolation. To do so, we a priori selected sites that independently varied in the amount of vegetated area in the surrounding landscape at the 500-m scale and patch isolation at the 100-m scale, and we hold local patch characteristics constant. As indicator groups, we used bugs, beetles, leafhoppers, and spiders. Compared to intensively managed agricultural ecosystems, urban ecosystems supported a higher abundance of most indicator groups, a higher number of bug species, and a lower evenness of bug and beetle species. Within cities, a high amount of vegetated area increased species richness and abundance of most arthropod groups, whereas evenness showed no clear pattern. Patch isolation played only a limited role in urban ecosystems, which contrasts findings from agro-ecological studies. Our results show that urban areas can harbor a similar arthropod diversity and abundance compared to intensively managed agricultural ecosystems. Further, negative consequences of urbanization on arthropod diversity can be mitigated by providing sufficient vegetated space in the urban area, while patch connectivity is less important in an urban context. This highlights the need for applying a landscape ecological approach to understand the mechanisms shaping urban biodiversity and underlines the potential of appropriate urban planning for mitigating biodiversity loss. © 2015 John Wiley & Sons Ltd.

Monitoring early hydration of reinforced concrete structures using structural parameters identified by piezo sensors via electromechanical impedance technique

NASA Astrophysics Data System (ADS)

Talakokula, Visalakshi; Bhalla, Suresh; Gupta, Ashok

2018-01-01

Concrete is the most widely used material in civil engineering construction. Its life begins when the hydration process is activated after mixing the cement granulates with water. In this paper, a non-dimensional hydration parameter, obtained from piezoelectric ceramic (PZT) patches bonded to rebars embedded inside concrete, is employed to monitor the early age hydration of concrete. The non-dimensional hydration parameter is derived from the equivalent stiffness determined from the piezo-impedance transducers using the electro-mechanical impedance (EMI) technique. The focus of the study is to monitor the hydration process of cementitious materials commencing from the early hours and continue till 28 days using single non-dimensional parameter. The experimental results show that the proposed piezo-based non-dimensional hydration parameter is very effective in monitoring the early age hydration, as it has been derived from the refined structural impedance parameters, obtained by eliminating the PZT contribution, and using both the real and imaginary components of the admittance signature.

Important Physiological Parameters and Physical Activity Data for Evaluating Exposure Modeling Performance: a Synthesis

EPA Science Inventory

The purpose of this report is to develop a database of physiological parameters needed for understanding and evaluating performance of the APEX and SHEDS exposure/intake dose rate model used by the Environmental Protection Agency (EPA) as part of its regulatory activities. The A...

Defining and identifying Sleeping Beauties in science

PubMed Central

Ke, Qing; Ferrara, Emilio; Radicchi, Filippo; Flammini, Alessandro

2015-01-01

A Sleeping Beauty (SB) in science refers to a paper whose importance is not recognized for several years after publication. Its citation history exhibits a long hibernation period followed by a sudden spike of popularity. Previous studies suggest a relative scarcity of SBs. The reliability of this conclusion is, however, heavily dependent on identification methods based on arbitrary threshold parameters for sleeping time and number of citations, applied to small or monodisciplinary bibliographic datasets. Here we present a systematic, large-scale, and multidisciplinary analysis of the SB phenomenon in science. We introduce a parameter-free measure that quantifies the extent to which a specific paper can be considered an SB. We apply our method to 22 million scientific papers published in all disciplines of natural and social sciences over a time span longer than a century. Our results reveal that the SB phenomenon is not exceptional. There is a continuous spectrum of delayed recognition where both the hibernation period and the awakening intensity are taken into account. Although many cases of SBs can be identified by looking at monodisciplinary bibliographic data, the SB phenomenon becomes much more apparent with the analysis of multidisciplinary datasets, where we can observe many examples of papers achieving delayed yet exceptional importance in disciplines different from those where they were originally published. Our analysis emphasizes a complex feature of citation dynamics that so far has received little attention, and also provides empirical evidence against the use of short-term citation metrics in the quantification of scientific impact. PMID:26015563

Studies on electronic spectral parameters of doped Nd(III) ion with therapeutically important ligands in dioxane solvent

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

Bajaj, Annu, E-mail: annu.bajaj11@gmail.com; Jain, Sushma

2016-05-06

The present investigation is concerened with the studies on electronic spectral parameters viz. Oscillator strength (P), Judd-Ofelt T{sub λ} (λ=2,4,6), Slater-Condon(F{sub K}),Lande(ζ{sub 4F}),Nephelauxetic ratio(β), Bonding parameter (b{sup 1/2}) and Percent covalency parameter (δ%) for Nd(III) ion complexes with the ligands having Nitrogen,Oxygen Sulphur donor sites.The variation in the values of oscillator strength explicitly shows the relative sensitivities of the 4f-4f transition as well as the specific correlation between ligand structures and nature of Nd(III) ligand interaction.

Identifying key sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2013-09-01

This study investigates sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment, through the use of local and global sensitivity analysis tools, and contributes to an in-depth understanding of wastewater treatment modelling by revealing critical parameters and parameter interactions. One-factor-at-a-time sensitivity analysis is used to screen model parameters and identify those with significant individual effects on three performance indicators: total greenhouse gas emissions, effluent quality and operational cost. Sobol's method enables identification of parameters with significant higher order effects and of particular parameter pairs to which model outputs are sensitive. Use of a variance-based global sensitivity analysis tool to investigate parameter interactions enables identification of important parameters not revealed in one-factor-at-a-time sensitivity analysis. These interaction effects have not been considered in previous studies and thus provide a better understanding wastewater treatment plant model characterisation. It was found that uncertainty in modelled nitrous oxide emissions is the primary contributor to uncertainty in total greenhouse gas emissions, due largely to the interaction effects of three nitrogen conversion modelling parameters. The higher order effects of these parameters are also shown to be a key source of uncertainty in effluent quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

G6PD/PK ratio: a reliable parameter to identify glucose-6-phosphate dehydrogenase deficiency associated with microcytic anemia in heterozygous subjects.

PubMed

Tagarelli, Antonio; Piro, Anna; Tagarelli, Giuseppe; Bastone, Loredana; Paleari, Renata; Mosca, Andrea

2004-10-01

To determine if measuring the ratio of glucose-6-phosphate dehydrogenase (G6PD) to pyruvate kinase (PK) is more reliable than only measuring G6PD activity to identify heterozygous G6PD- individuals with associated microcytic anemia in the Calabrian population, which shows high frequencies of both the thalassaemia (thal) trait and G6PD deficiency. Measurement of G6PD and PK activities was carried out on 205 samples of whole blood from Calabrian subjects of both sexes (age range 10-50 years) using a double starter differential pH-metry technique. The G6PD/PK ratio is able to differentiate G6PD- heterozygous individuals from the normal population. G6PD/PK values also allowed us to easily identify the G6PD- heterozygous subjects with microcytic anaemia. Student's t test shows that G6PD/PK ratio is more reliable in both sample groups, relative to G6PD activity in normal subjects. G6PD/PK ratio is a reliable diagnostic parameter for mass screening for G6PD deficiency.

Hardrock Elastic Physical Properties: Birch's Seismic Parameter Revisited

NASA Astrophysics Data System (ADS)

Wu, M.; Milkereit, B.

2014-12-01

Identifying rock composition and properties is imperative in a variety of fields including geotechnical engineering, mining, and petroleum exploration, in order to accurately make any petrophysical calculations. Density is, in particular, an important parameter that allows us to differentiate between lithologies and estimate or calculate other petrophysical properties. It is well established that compressional and shear wave velocities of common crystalline rocks increase with increasing densities (i.e. the Birch and Nafe-Drake relationships). Conventional empirical relations do not take into account S-wave velocity. Physical properties of Fe-oxides and massive sulfides, however, differ significantly from the empirical velocity-density relationships. Currently, acquiring in-situ density data is challenging and problematic, and therefore, developing an approximation for density based on seismic wave velocity and elastic moduli would be beneficial. With the goal of finding other possible or better relationships between density and the elastic moduli, a database of density, P-wave velocity, S-wave velocity, bulk modulus, shear modulus, Young's modulus, and Poisson's ratio was compiled based on a multitude of lab samples. The database is comprised of isotropic, non-porous metamorphic rock. Multi-parameter cross plots of the various elastic parameters have been analyzed in order to find a suitable parameter combination that reduces high density outliers. As expected, the P-wave velocity to S-wave velocity ratios show no correlation with density. However, Birch's seismic parameter, along with the bulk modulus, shows promise in providing a link between observed compressional and shear wave velocities and rock densities, including massive sulfides and Fe-oxides.

Application of Novel Lateral Tire Force Sensors to Vehicle Parameter Estimation of Electric Vehicles.

PubMed

Nam, Kanghyun

2015-11-11

This article presents methods for estimating lateral vehicle velocity and tire cornering stiffness, which are key parameters in vehicle dynamics control, using lateral tire force measurements. Lateral tire forces acting on each tire are directly measured by load-sensing hub bearings that were invented and further developed by NSK Ltd. For estimating the lateral vehicle velocity, tire force models considering lateral load transfer effects are used, and a recursive least square algorithm is adapted to identify the lateral vehicle velocity as an unknown parameter. Using the estimated lateral vehicle velocity, tire cornering stiffness, which is an important tire parameter dominating the vehicle's cornering responses, is estimated. For the practical implementation, the cornering stiffness estimation algorithm based on a simple bicycle model is developed and discussed. Finally, proposed estimation algorithms were evaluated using experimental test data.

Forge into the Future: Identifying Core Competencies and Important Skills, Knowledge, and Abilities (SKAs) for Junior Navy Medical Service Corps Officers

DTIC Science & Technology

2008-10-20

operations and business practices, drug therapy management, and leadership, where as senior pharmacists placed a greater emphasis on the importance of SKAs...Commanders reviewed , sorted, and identified competencies from Wave I into 11 domains. From the expert analysis, the researcher developed a ...Y, a force of as many as 70 million are now beginning to embark on their career including the military health system. This generation as suggested

Risk profiles in type 2 diabetes (metabolic syndrome): integration of IL-10 polymorphisms and laboratory parameters to identify vascular damages related complications.

PubMed

Forte, G I; Pilato, G; Vaccarino, L; Sanacore, M; Candore, G; Romano, G C; Testa, R; Franceschi, C; Capri, M; Marra, M; Bonfigli, A R; Caruso, C; Scola, L; Lio, D

2010-01-01

Recently it has been reported that low serum IL-10 levels are associated with an increased susceptibility for metabolic syndrome and type 2 diabetes mellitus (T2DM). We investigated whether the -1087G/A (rs1800896), -824C/T (rs1800871), -597C/A (rs1800872) IL-10 polymorphisms were associated with type 2 diabetes in a study on a cohort of Italian Caucasians comprising 490 type 2 diabetic and 349 control subjects. Stratifying the data according to IL-10 genotypes, trends for the progressive increase of glucose and neutrophil levels were observed in -1087GG vs. -1087GA vs. -1087AA positive diabetic patients (-1087GG<-1087GA<-1087AA). In addition, evaluating the laboratory parameters according to the -597/-824/-1087 derived haplotypes a significant increase of neutrophils was found in diabetic vs. non-diabetic -597A/ -824T/-1087A positive subjects (Student t test = 3.707, p<0.01). In an attempt to integrate clinical laboratory and immunogenetic data to determine whether these factors taken together define sufficient risk sets for type 2 diabetes we performed the grade-of-membership analysis (GoM). GoM allowed to identify a population of subjects negative for IL-10 -824T allele, 74.4% of which were diabetic patients characterised by vascular damages (Chronic kidney failure and/or Myocardial Infarction), reduction of haematocrit, increase of blood urea nitrogen, creatinin and monocyte levels. These data seem to suggest that -597A/-824T/-1087A negative subjects are more prone to the major type 2 diabetic vascular damages and allow to hypothesise that the contemporary evaluation of some simple hematochemical parameters and IL-10 SNPs may allow identifying diabetic patients with the worse prognostic profile, needing both better complication prevention planning and therapeutic strategies.

Identifying High-Rate Flows Based on Sequential Sampling

NASA Astrophysics Data System (ADS)

Zhang, Yu; Fang, Binxing; Luo, Hao

We consider the problem of fast identification of high-rate flows in backbone links with possibly millions of flows. Accurate identification of high-rate flows is important for active queue management, traffic measurement and network security such as detection of distributed denial of service attacks. It is difficult to directly identify high-rate flows in backbone links because tracking the possible millions of flows needs correspondingly large high speed memories. To reduce the measurement overhead, the deterministic 1-out-of-k sampling technique is adopted which is also implemented in Cisco routers (NetFlow). Ideally, a high-rate flow identification method should have short identification time, low memory cost and processing cost. Most importantly, it should be able to specify the identification accuracy. We develop two such methods. The first method is based on fixed sample size test (FSST) which is able to identify high-rate flows with user-specified identification accuracy. However, since FSST has to record every sampled flow during the measurement period, it is not memory efficient. Therefore the second novel method based on truncated sequential probability ratio test (TSPRT) is proposed. Through sequential sampling, TSPRT is able to remove the low-rate flows and identify the high-rate flows at the early stage which can reduce the memory cost and identification time respectively. According to the way to determine the parameters in TSPRT, two versions of TSPRT are proposed: TSPRT-M which is suitable when low memory cost is preferred and TSPRT-T which is suitable when short identification time is preferred. The experimental results show that TSPRT requires less memory and identification time in identifying high-rate flows while satisfying the accuracy requirement as compared to previously proposed methods.

Genome-wide association study meta-analysis for quantitative ultrasound parameters of bone identifies five novel loci for broadband ultrasound attenuation.

PubMed

Mullin, Benjamin H; Zhao, Jing Hua; Brown, Suzanne J; Perry, John R B; Luan, Jian'an; Zheng, Hou-Feng; Langenberg, Claudia; Dudbridge, Frank; Scott, Robert; Wareham, Nick J; Spector, Tim D; Richards, J Brent; Walsh, John P; Wilson, Scott G

2017-07-15

Osteoporosis is a common and debilitating bone disease that is characterised by low bone mineral density, typically assessed using dual-energy X-ray absorptiometry. Quantitative ultrasound (QUS), commonly utilising the two parameters velocity of sound (VOS) and broadband ultrasound attenuation (BUA), is an alternative technology used to assess bone properties at peripheral skeletal sites. The genetic influence on the bone qualities assessed by QUS remains an under-studied area. We performed a comprehensive genome-wide association study (GWAS) including low-frequency variants (minor allele frequency ≥0.005) for BUA and VOS using a discovery population of individuals with whole-genome sequence (WGS) data from the UK10K project (n = 1268). These results were then meta-analysed with those from two deeply imputed GWAS replication cohorts (n = 1610 and 13 749). In the gender-combined analysis, we identified eight loci associated with BUA and five with VOS at the genome-wide significance level, including three novel loci for BUA at 8p23.1 (PPP1R3B), 11q23.1 (LOC387810) and 22q11.21 (SEPT5) (P = 2.4 × 10-8 to 1.6 × 10-9). Gene-based association testing in the gender-combined dataset revealed eight loci associated with BUA and seven with VOS after correction for multiple testing, with one novel locus for BUA at FAM167A (8p23.1) (P = 1.4 × 10-6). An additional novel locus for BUA was seen in the male-specific analysis at DEFB103B (8p23.1) (P = 1.8 × 10-6). Fracture analysis revealed significant associations between variation at the WNT16 and RSPO3 loci and fracture risk (P = 0.004 and 4.0 × 10-4, respectively). In conclusion, by performing a large GWAS meta-analysis for QUS parameters of bone using a combination of WGS and deeply imputed genotype data, we have identified five novel genetic loci associated with BUA. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email

Influence of Population Variation of Physiological Parameters in Computational Models of Space Physiology

NASA Technical Reports Server (NTRS)

Myers, J. G.; Feola, A.; Werner, C.; Nelson, E. S.; Raykin, J.; Samuels, B.; Ethier, C. R.

2016-01-01

intracranial pressure had dominant impact on the peak strains in the ONH and retro-laminar optic nerve, respectively; optic nerve and lamina cribrosa stiffness were also important. This investigation illustrates the ability of LHSPRCC to identify the most influential physiological parameters, which must therefore be well-characterized to produce the most accurate numerical results.

Finding The Most Important Actor in Online Crowd by Social Network Analysis

NASA Astrophysics Data System (ADS)

Yuliana, I.; Santosa, P. I.; Setiawan, N. A.; Sukirman

2017-02-01

Billion of people create trillions of connections through social media every single day. The increasing use of social media has led to dramatic changes in the of way science, government, healthcare, entertainment and enterprise operate. Large-scale participation in Technology-Mediated Social Participation (TMSP) system has opened up incredible new opportunities to deploy online crowd. This descriptive-correlational research used social network analysis (SNA) on data gathered from Fanpage Facebook of Greenpeace Indonesia related to important critical issues, the bushfires in 2015. SNA identifies relations on each member by sociometrics parameter such as three centrality (degree, closeness and betweenesse) for measuring and finding the most important actor in the online community. This paper use Fruchterman Rein-gold algorithm to visualize the online community in a graph, while Clauset-Newman-Moore is a technique to identify groups in community. As the result found 3735 vertices related to actors, 6927 edges as relation, 14 main actors in size order and 22 groups in Greenpeace Indonesia online community. This research contributes to organize some information for Greenpeace Indonesia managing their potency in online community to identify human behaviour.

How important is importance for prospective memory? A review

PubMed Central

Walter, Stefan; Meier, Beat

2014-01-01

Forgetting to carry out an intention as planned can have serious consequences in everyday life. People sometimes even forget intentions that they consider as very important. Here, we review the literature on the impact of importance on prospective memory performance. We highlight different methods used to manipulate the importance of a prospective memory task such as providing rewards, importance relative to other ongoing activities, absolute importance, and providing social motives. Moreover, we address the relationship between importance and other factors known to affect prospective memory and ongoing task performance such as type of prospective memory task (time-, event-, or activity-based), cognitive loads, and processing overlaps. Finally, we provide a connection to motivation, we summarize the effects of task importance and we identify important venues for future research. PMID:25018743

Parameter identification of thermophilic anaerobic degradation of valerate.

PubMed

Flotats, Xavier; Ahring, Birgitte K; Angelidaki, Irini

2003-01-01

The considered mathematical model of the decomposition of valerate presents three unknown kinetic parameters, two unknown stoichiometric coefficients, and three unknown initial concentrations for biomass. Applying a structural identifiability study, we concluded that it is necessary to perform simultaneous batch experiments with different initial conditions for estimating these parameters. Four simultaneous batch experiments were conducted at 55 degrees C, characterized by four different initial acetate concentrations. Product inhibition of valerate degradation by acetate was considered. Practical identification was done optimizing the sum of the multiple determination coefficients for all measured state variables and for all experiments simultaneously. The estimated values of kinetic parameters and stoichiometric coefficients were characterized by the parameter correlation matrix, the confidence interval, and the student's t-test at 5% significance level with positive results except for the saturation constant, for which more experiments for improving its identifiability should be conducted. In this article, we discuss kinetic parameter estimation methods.

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records.

PubMed

Peissig, Peggy L; Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries.

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

PubMed Central

Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

Objective There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. Materials and methods We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. Results An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. Discussion A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. Conclusion We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries. PMID:22319176

Setting priorities in health care organizations: criteria, processes, and parameters of success.

PubMed

Gibson, Jennifer L; Martin, Douglas K; Singer, Peter A

2004-09-08

Hospitals and regional health authorities must set priorities in the face of resource constraints. Decision-makers seek practical ways to set priorities fairly in strategic planning, but find limited guidance from the literature. Very little has been reported from the perspective of Board members and senior managers about what criteria, processes and parameters of success they would use to set priorities fairly. We facilitated workshops for board members and senior leadership at three health care organizations to assist them in developing a strategy for fair priority setting. Workshop participants identified 8 priority setting criteria, 10 key priority setting process elements, and 6 parameters of success that they would use to set priorities in their organizations. Decision-makers in other organizations can draw lessons from these findings to enhance the fairness of their priority setting decision-making. Lessons learned in three workshops fill an important gap in the literature about what criteria, processes, and parameters of success Board members and senior managers would use to set priorities fairly.

Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations

NASA Astrophysics Data System (ADS)

Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.

2016-11-01

Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.

Identifiability Results for Several Classes of Linear Compartment Models.

PubMed

Meshkat, Nicolette; Sullivant, Seth; Eisenberg, Marisa

2015-08-01

Identifiability concerns finding which unknown parameters of a model can be estimated, uniquely or otherwise, from given input-output data. If some subset of the parameters of a model cannot be determined given input-output data, then we say the model is unidentifiable. In this work, we study linear compartment models, which are a class of biological models commonly used in pharmacokinetics, physiology, and ecology. In past work, we used commutative algebra and graph theory to identify a class of linear compartment models that we call identifiable cycle models, which are unidentifiable but have the simplest possible identifiable functions (so-called monomial cycles). Here we show how to modify identifiable cycle models by adding inputs, adding outputs, or removing leaks, in such a way that we obtain an identifiable model. We also prove a constructive result on how to combine identifiable models, each corresponding to strongly connected graphs, into a larger identifiable model. We apply these theoretical results to several real-world biological models from physiology, cell biology, and ecology.

Identifiability of PBPK Models with Applications to ...

EPA Pesticide Factsheets

Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss different types of identifiability that occur in PBPK models and give reasons why they occur. We particularly focus on how the mathematical structure of a PBPK model and lack of appropriate data can lead to statistical models in which it is impossible to estimate at least some parameters precisely. Methods are reviewed which can determine whether a purely linear PBPK model is globally identifiable. We propose a theorem which determines when identifiability at a set of finite and specific values of the mathematical PBPK model (global discrete identifiability) implies identifiability of the statistical model. However, we are unable to establish conditions that imply global discrete identifiability, and conclude that the only safe approach to analysis of PBPK models involves Bayesian analysis with truncated priors. Finally, computational issues regarding posterior simulations of PBPK models are discussed. The methodology is very general and can be applied to numerous PBPK models which can be expressed as linear time-invariant systems. A real data set of a PBPK model for exposure to dimethyl arsinic acid (DMA(V)) is presented to illustrate the proposed methodology. We consider statistical analy

RMB identification based on polarization parameters inversion imaging

NASA Astrophysics Data System (ADS)

Liu, Guoyan; Gao, Kun; Liu, Xuefeng; Ni, Guoqiang

2016-10-01

Social order is threatened by counterfeit money. Conventional anti-counterfeit technology is much too old to identify its authenticity or not. The intrinsic difference between genuine notes and counterfeit notes is its paper tissue. In this paper a new technology of detecting RMB is introduced, the polarization parameter indirect microscopic imaging technique. A conventional reflection microscopic system is used as the basic optical system, and inserting into it with polarization-modulation mechanics. The near-field structural characteristics can be delivered by optical wave and material coupling. According to coupling and conduction physics, calculate the changes of optical wave parameters, then get the curves of the intensity of the image. By analyzing near-field polarization parameters in nanoscale, finally calculate indirect polarization parameter imaging of the fiber of the paper tissue in order to identify its authenticity.

Exploration of DGVM Parameter Solution Space Using Simulated Annealing: Implications for Forecast Uncertainties

NASA Astrophysics Data System (ADS)

Wells, J. R.; Kim, J. B.

2011-12-01

multiple acceptable parameter sets exist. Further we expect to demonstrate that the multiple parameter sets produce significantly divergent future forecasts in NEP, C storage, and ET and runoff; and thereby identify a highly important source of DGVM uncertainty

Identifying Important Atlantic Areas for the conservation of Balearic shearwaters: Spatial overlap with conservation areas

NASA Astrophysics Data System (ADS)

Pérez-Roda, Amparo; Delord, Karine; Boué, Amélie; Arcos, José Manuel; García, David; Micol, Thierry; Weimerskirch, Henri; Pinaud, David; Louzao, Maite

2017-07-01

Marine protected areas (MPAs) are considered one of the main tools in both fisheries and conservation management to protect threatened species and their habitats around the globe. However, MPAs are underrepresented in marine environments compared to terrestrial environments. Within this context, we studied the Atlantic non-breeding distribution of the southern population of Balearic shearwaters (Puffinus mauretanicus) breeding in Eivissa during the 2011-2012 period based on global location sensing (GLS) devices. Our objectives were (1) to identify overall Important Atlantic Areas (IAAs) from a southern population, (2) to describe spatio-temporal patterns of oceanographic habitat use, and (3) to assess whether existing conservation areas (Natura 2000 sites and marine Important Bird Areas (IBAs)) cover the main IAAs of Balearic shearwaters. Our results highlighted that the Atlantic staging (from June to October in 2011) dynamic of the southern population was driven by individual segregation at both spatial and temporal scales. Individuals ranged in the North-East Atlantic over four main IAAs (Bay of Biscay: BoB, Western Iberian shelf: WIS, Gulf of Cadiz: GoC, West of Morocco: WoM). While most individuals spent more time on the WIS or in the GoC, a small number of birds visited IAAs at the extremes of their Atlantic distribution range (i.e., BoB and WoM). The chronology of the arrivals to the IAAs showed a latitudinal gradient with northern areas reached earlier during the Atlantic staging. The IAAs coincided with the most productive areas (higher chlorophyll a values) in the NE Atlantic between July and October. The spatial overlap between IAAs and conservation areas was higher for Natura 2000 sites than marine IBAs (areas with and without legal protection, respectively). Concerning the use of these areas, a slightly higher proportion of estimated positions fell within marine IBAs compared to designated Natura 2000 sites, with Spanish and Portuguese conservation

Application of Novel Lateral Tire Force Sensors to Vehicle Parameter Estimation of Electric Vehicles

PubMed Central

Nam, Kanghyun

2015-01-01

This article presents methods for estimating lateral vehicle velocity and tire cornering stiffness, which are key parameters in vehicle dynamics control, using lateral tire force measurements. Lateral tire forces acting on each tire are directly measured by load-sensing hub bearings that were invented and further developed by NSK Ltd. For estimating the lateral vehicle velocity, tire force models considering lateral load transfer effects are used, and a recursive least square algorithm is adapted to identify the lateral vehicle velocity as an unknown parameter. Using the estimated lateral vehicle velocity, tire cornering stiffness, which is an important tire parameter dominating the vehicle’s cornering responses, is estimated. For the practical implementation, the cornering stiffness estimation algorithm based on a simple bicycle model is developed and discussed. Finally, proposed estimation algorithms were evaluated using experimental test data. PMID:26569246

Multi-Axis Identifiability Using Single-Surface Parameter Estimation Maneuvers on the X-48B Blended Wing Body

NASA Technical Reports Server (NTRS)

Ratnayake, Nalin A.; Koshimoto, Ed T.; Taylor, Brian R.

2011-01-01

The problem of parameter estimation on hybrid-wing-body type aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aero- dynamic control effectors that act in coplanar motion. This fact adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of system inputs must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, asymmetric, single-surface maneuvers are used to excite multiple axes of aircraft motion simultaneously. Time history reconstructions of the moment coefficients computed by the solved regression models are then compared to each other in order to assess relative model accuracy. The reduced flight-test time required for inner surface parameter estimation using multi-axis methods was found to come at the cost of slightly reduced accuracy and statistical confidence for linear regression methods. Since the multi-axis maneuvers captured parameter estimates similar to both longitudinal and lateral-directional maneuvers combined, the number of test points required for the inner, aileron-like surfaces could in theory have been reduced by 50%. While trends were similar, however, individual parameters as estimated by a multi-axis model were typically different by an average absolute difference of roughly 15-20%, with decreased statistical significance, than those estimated by a single-axis model. The multi-axis model exhibited an increase in overall fit error of roughly 1-5% for the linear regression estimates with respect to the single-axis model, when applied to flight data designed for each, respectively.

Bayesian Parameter Inference and Model Selection by Population Annealing in Systems Biology

PubMed Central

Murakami, Yohei

2014-01-01

Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection. Especially, the framework named approximate Bayesian computation is often used for parameter inference and model selection in systems biology. However, Monte Carlo methods needs to be used to compute Bayesian posterior distributions. In addition, the posterior distributions of parameters are sometimes almost uniform or very similar to their prior distributions. In such cases, it is difficult to choose one specific value of parameter with high credibility as the representative value of the distribution. To overcome the problems, we introduced one of the population Monte Carlo algorithms, population annealing. Although population annealing is usually used in statistical mechanics, we showed that population annealing can be used to compute Bayesian posterior distributions in the approximate Bayesian computation framework. To deal with un-identifiability of the representative values of parameters, we proposed to run the simulations with the parameter ensemble sampled from the posterior distribution, named “posterior parameter ensemble”. We showed that population annealing is an efficient and convenient algorithm to generate posterior parameter ensemble. We also showed that the simulations with the posterior parameter ensemble can, not only reproduce the data used for parameter inference, but also capture and predict the data which was not used for parameter inference. Lastly, we introduced the marginal likelihood in the approximate Bayesian computation framework for Bayesian model selection. We showed that population annealing enables us to compute the marginal likelihood in the approximate Bayesian computation framework and conduct model selection depending on the Bayes factor. PMID:25089832

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

PubMed

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.

Prediction of changes in important physical parameters during composting of separated animal slurry solid fractions.

PubMed

Chowdhury, Md Albarune; de Neergaard, Andreas; Jensen, Lars Stoumann

2014-01-01

Solid-liquid separation of animal slurry, with solid fractions used for composting, has gained interest recently. However, efficient composting of separated animal slurry solid fractions (SSFs) requires a better understanding of the process dynamics in terms of important physical parameters and their interacting physical relationships in the composting matrix. Here we monitored moisture content, bulk density, particle density and air-filled porosity (AFP) during composting of SSF collected from four commercially available solid-liquid separators. Composting was performed in laboratory-scale reactors for 30 days (d) under forced aeration and measurements were conducted on the solid samples at the beginning of composting and at 10-d intervals during composting. The results suggest that differences in initial physical properties of SSF influence the development of compost maximum temperatures (40-70 degreeC). Depending on SSF, total wet mass and volume losses (expressed as % of initial value) were up to 37% and 34%, respectively. After 30 d of composting, relative losses of total solids varied from 17.9% to 21.7% and of volatile solids (VS) from 21.3% to 27.5%, depending on SSF. VS losses in all composts showed different dynamics as described by the first-order kinetic equation. The estimated component particle density of 1441 kg m-3 for VS and 2625 kg m-3 for fixed solids can be used to improve estimates of AFP for SSF within the range tested. The linear relationship between wet bulk density and AFP reported by previous researchers held true for SSF.

Robust design of configurations and parameters of adaptable products

NASA Astrophysics Data System (ADS)

Zhang, Jian; Chen, Yongliang; Xue, Deyi; Gu, Peihua

2014-03-01

An adaptable product can satisfy different customer requirements by changing its configuration and parameter values during the operation stage. Design of adaptable products aims at reducing the environment impact through replacement of multiple different products with single adaptable ones. Due to the complex architecture, multiple functional requirements, and changes of product configurations and parameter values in operation, impact of uncertainties to the functional performance measures needs to be considered in design of adaptable products. In this paper, a robust design approach is introduced to identify the optimal design configuration and parameters of an adaptable product whose functional performance measures are the least sensitive to uncertainties. An adaptable product in this paper is modeled by both configurations and parameters. At the configuration level, methods to model different product configuration candidates in design and different product configuration states in operation to satisfy design requirements are introduced. At the parameter level, four types of product/operating parameters and relations among these parameters are discussed. A two-level optimization approach is developed to identify the optimal design configuration and its parameter values of the adaptable product. A case study is implemented to illustrate the effectiveness of the newly developed robust adaptable design method.

Photosynthetic limitations in two Antarctic vascular plants: importance of leaf anatomical traits and Rubisco kinetic parameters.

PubMed

Sáez, Patricia L; Bravo, León A; Cavieres, Lohengrin A; Vallejos, Valentina; Sanhueza, Carolina; Font-Carrascosa, Marcel; Gil-Pelegrín, Eustaquio; Javier Peguero-Pina, José; Galmés, Jeroni

2017-05-17

Particular physiological traits allow the vascular plants Deschampsia antarctica Desv. and Colobanthus quitensis (Kunth) Bartl. to inhabit Antarctica. The photosynthetic performance of these species was evaluated in situ, focusing on diffusive and biochemical constraints to CO2 assimilation. Leaf gas exchange, Chl a fluorescence, leaf ultrastructure, and Rubisco catalytic properties were examined in plants growing on King George and Lagotellerie islands. In spite of the species- and population-specific effects of the measurement temperature on the main photosynthetic parameters, CO2 assimilation was highly limited by CO2 diffusion. In particular, the mesophyll conductance (gm)-estimated from both gas exchange and leaf chlorophyll fluorescence and modeled from leaf anatomy-was remarkably low, restricting CO2 diffusion and imposing the strongest constraint to CO2 acquisition. Rubisco presented a high specificity for CO2 as determined in vitro, suggesting a tight co-ordination between CO2 diffusion and leaf biochemistry that may be critical ultimately to optimize carbon balance in these species. Interestingly, both anatomical and biochemical traits resembled those described in plants from arid environments, providing a new insight into plant functional acclimation to extreme conditions. Understanding what actually limits photosynthesis in these species is important to anticipate their responses to the ongoing and predicted rapid warming in the Antarctic Peninsula. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

An information-theoretic approach to assess practical identifiability of parametric dynamical systems.

PubMed

Pant, Sanjay; Lombardi, Damiano

2015-10-01

A new approach for assessing parameter identifiability of dynamical systems in a Bayesian setting is presented. The concept of Shannon entropy is employed to measure the inherent uncertainty in the parameters. The expected reduction in this uncertainty is seen as the amount of information one expects to gain about the parameters due to the availability of noisy measurements of the dynamical system. Such expected information gain is interpreted in terms of the variance of a hypothetical measurement device that can measure the parameters directly, and is related to practical identifiability of the parameters. If the individual parameters are unidentifiable, correlation between parameter combinations is assessed through conditional mutual information to determine which sets of parameters can be identified together. The information theoretic quantities of entropy and information are evaluated numerically through a combination of Monte Carlo and k-nearest neighbour methods in a non-parametric fashion. Unlike many methods to evaluate identifiability proposed in the literature, the proposed approach takes the measurement-noise into account and is not restricted to any particular noise-structure. Whilst computationally intensive for large dynamical systems, it is easily parallelisable and is non-intrusive as it does not necessitate re-writing of the numerical solvers of the dynamical system. The application of such an approach is presented for a variety of dynamical systems--ranging from systems governed by ordinary differential equations to partial differential equations--and, where possible, validated against results previously published in the literature. Copyright © 2015 Elsevier Inc. All rights reserved.

Target parameter estimation

NASA Technical Reports Server (NTRS)

Hocking, W. K.

1989-01-01

The objective of any radar experiment is to determine as much as possible about the entities which scatter the radiation. This review discusses many of the various parameters which can be deduced in a radar experiment, and also critically examines the procedures used to deduce them. Methods for determining the mean wind velocity, the RMS fluctuating velocities, turbulence parameters, and the shapes of the scatterers are considered. Complications with these determinations are discussed. It is seen throughout that a detailed understanding of the shape and cause of the scatterers is important in order to make better determinations of these various quantities. Finally, some other parameters, which are less easily acquired, are considered. For example, it is noted that momentum fluxes due to buoyancy waves and turbulence can be determined, and on occasions radars can be used to determine stratospheric diffusion coefficients and even temperature profiles in the atmosphere.

Uncertainty Quantification and Regional Sensitivity Analysis of Snow-related Parameters in the Canadian LAnd Surface Scheme (CLASS)

NASA Astrophysics Data System (ADS)

Badawy, B.; Fletcher, C. G.

2017-12-01

The parameterization of snow processes in land surface models is an important source of uncertainty in climate simulations. Quantifying the importance of snow-related parameters, and their uncertainties, may therefore lead to better understanding and quantification of uncertainty within integrated earth system models. However, quantifying the uncertainty arising from parameterized snow processes is challenging due to the high-dimensional parameter space, poor observational constraints, and parameter interaction. In this study, we investigate the sensitivity of the land simulation to uncertainty in snow microphysical parameters in the Canadian LAnd Surface Scheme (CLASS) using an uncertainty quantification (UQ) approach. A set of training cases (n=400) from CLASS is used to sample each parameter across its full range of empirical uncertainty, as determined from available observations and expert elicitation. A statistical learning model using support vector regression (SVR) is then constructed from the training data (CLASS output variables) to efficiently emulate the dynamical CLASS simulations over a much larger (n=220) set of cases. This approach is used to constrain the plausible range for each parameter using a skill score, and to identify the parameters with largest influence on the land simulation in CLASS at global and regional scales, using a random forest (RF) permutation importance algorithm. Preliminary sensitivity tests indicate that snow albedo refreshment threshold and the limiting snow depth, below which bare patches begin to appear, have the highest impact on snow output variables. The results also show a considerable reduction of the plausible ranges of the parameters values and hence reducing their uncertainty ranges, which can lead to a significant reduction of the model uncertainty. The implementation and results of this study will be presented and discussed in details.

Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis.

PubMed

Held, Christian; Nattkemper, Tim; Palmisano, Ralf; Wittenberg, Thomas

2013-01-01

Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline's modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided. This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs. The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum.

Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis

PubMed Central

Held, Christian; Nattkemper, Tim; Palmisano, Ralf; Wittenberg, Thomas

2013-01-01

Introduction: Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open. Methods: In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline's modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided. Results: This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs. Conclusion: The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum. PMID:23766941

Evolution of quantitative methods for the study and management of avian populations: on the importance of individual contributions

USGS Publications Warehouse

Nichols, J.D.

2004-01-01

The EURING meetings and the scientists who have attended them have contributed substantially to the growth of knowledge in the field of estimating parameters of animal populations. The contributions of David R. Anderson to process modeling, parameter estimation and decision analysis are briefly reviewed. Metrics are considered for assessing individual contributions to a field of inquiry, and it is concluded that Anderson’s contributions have been substantial. Important characteristics of Anderson and his career are the ability to identify and focus on important topics, the premium placed on dissemination of new methods to prospective users, the ability to assemble teams of complementary researchers, and the innovation and vision that characterized so much of his work. The paper concludes with a list of interesting current research topics for consideration by EURING participants.

Parameter Estimation and Sensitivity Analysis of an Urban Surface Energy Balance Parameterization at a Tropical Suburban Site

NASA Astrophysics Data System (ADS)

Harshan, S.; Roth, M.; Velasco, E.

2014-12-01

Forecasting of the urban weather and climate is of great importance as our cities become more populated and considering the combined effects of global warming and local land use changes which make urban inhabitants more vulnerable to e.g. heat waves and flash floods. In meso/global scale models, urban parameterization schemes are used to represent the urban effects. However, these schemes require a large set of input parameters related to urban morphological and thermal properties. Obtaining all these parameters through direct measurements are usually not feasible. A number of studies have reported on parameter estimation and sensitivity analysis to adjust and determine the most influential parameters for land surface schemes in non-urban areas. Similar work for urban areas is scarce, in particular studies on urban parameterization schemes in tropical cities have so far not been reported. In order to address above issues, the town energy balance (TEB) urban parameterization scheme (part of the SURFEX land surface modeling system) was subjected to a sensitivity and optimization/parameter estimation experiment at a suburban site in, tropical Singapore. The sensitivity analysis was carried out as a screening test to identify the most sensitive or influential parameters. Thereafter, an optimization/parameter estimation experiment was performed to calibrate the input parameter. The sensitivity experiment was based on the "improved Sobol's global variance decomposition method" . The analysis showed that parameters related to road, roof and soil moisture have significant influence on the performance of the model. The optimization/parameter estimation experiment was performed using the AMALGM (a multi-algorithm genetically adaptive multi-objective method) evolutionary algorithm. The experiment showed a remarkable improvement compared to the simulations using the default parameter set. The calibrated parameters from this optimization experiment can be used for further model

Parameter optimization on the convergence surface of path simulations

NASA Astrophysics Data System (ADS)

Chandrasekaran, Srinivas Niranj

Computational treatments of protein conformational changes tend to focus on the trajectories themselves, despite the fact that it is the transition state structures that contain information about the barriers that impose multi-state behavior. PATH is an algorithm that computes a transition pathway between two protein crystal structures, along with the transition state structure, by minimizing the Onsager-Machlup action functional. It is rapid but depends on several unknown input parameters whose range of different values can potentially generate different transition-state structures. Transition-state structures arising from different input parameters cannot be uniquely compared with those generated by other methods. I outline modifications that I have made to the PATH algorithm that estimates these input parameters in a manner that circumvents these difficulties, and describe two complementary tests that validate the transition-state structures found by the PATH algorithm. First, I show that although the PATH algorithm and two other approaches to computing transition pathways produce different low-energy structures connecting the initial and final ground-states with the transition state, all three methods agree closely on the configurations of their transition states. Second, I show that the PATH transition states are close to the saddle points of free-energy surfaces connecting initial and final states generated by replica-exchange Discrete Molecular Dynamics simulations. I show that aromatic side-chain rearrangements create similar potential energy barriers in the transition-state structures identified by PATH for a signaling protein, a contractile protein, and an enzyme. Finally, I observed, but cannot account for, the fact that trajectories obtained for all-atom and Calpha-only simulations identify transition state structures in which the Calpha atoms are in essentially the same positions. The consistency between transition-state structures derived by different

A Systematic Approach of Employing Quality by Design Principles: Risk Assessment and Design of Experiments to Demonstrate Process Understanding and Identify the Critical Process Parameters for Coating of the Ethylcellulose Pseudolatex Dispersion Using Non-Conventional Fluid Bed Process.

PubMed

Kothari, Bhaveshkumar H; Fahmy, Raafat; Claycamp, H Gregg; Moore, Christine M V; Chatterjee, Sharmista; Hoag, Stephen W

2017-05-01

The goal of this study was to utilize risk assessment techniques and statistical design of experiments (DoE) to gain process understanding and to identify critical process parameters for the manufacture of controlled release multiparticulate beads using a novel disk-jet fluid bed technology. The material attributes and process parameters were systematically assessed using the Ishikawa fish bone diagram and failure mode and effect analysis (FMEA) risk assessment methods. The high risk attributes identified by the FMEA analysis were further explored using resolution V fractional factorial design. To gain an understanding of the processing parameters, a resolution V fractional factorial study was conducted. Using knowledge gained from the resolution V study, a resolution IV fractional factorial study was conducted; the purpose of this IV study was to identify the critical process parameters (CPP) that impact the critical quality attributes and understand the influence of these parameters on film formation. For both studies, the microclimate, atomization pressure, inlet air volume, product temperature (during spraying and curing), curing time, and percent solids in the coating solutions were studied. The responses evaluated were percent agglomeration, percent fines, percent yield, bead aspect ratio, median particle size diameter (d50), assay, and drug release rate. Pyrobuttons® were used to record real-time temperature and humidity changes in the fluid bed. The risk assessment methods and process analytical tools helped to understand the novel disk-jet technology and to systematically develop models of the coating process parameters like process efficiency and the extent of curing during the coating process.

Neutronics Phenomena Important in Modeling and Simulation of Liquid-Fuel Molten Salt Reactors

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

Diamond, David J.

This paper discusses liquid-fuel molten salt reactors, how they will operate under normal, transient, and accident conditions, and the results of an expert elicitation to determine the corresponding neutronic phenomena important to understanding their behavior. Identifying these phenomena will enable the U.S. Nuclear Regulatory Commission (NRC) to develop or identify modeling functionalities and tools required to carry out confirmatory analyses that examine the validity and accuracy of applicants’ calculations and help determine the margin of safety in plant design. NRC frequently does an expert elicitation using a Phenomena Identification and Ranking Table (PIRT) to identify and evaluate the state ofmore » knowledge of important modeling phenomena. However, few details about the design of these reactors and the sequence of events during accidents are known, so the process used was considered a preliminary PIRT. A panel met to define phenomena that would need to be modeled and considered the impact/importance of each phenomenon with respect to specific figures-of-merit (FoMs) (e.g., power distribution, fluence, kinetics parameters and reactivity). Each FoM reflected a potential impact on radionuclide release or loss of a barrier to release. The panel considered what the path forward might be with respect to being able to model the phenomenon in a simulation code. Results are explained for both thermal and fast spectrum designs.« less

Inference of reactive transport model parameters using a Bayesian multivariate approach

NASA Astrophysics Data System (ADS)

Carniato, Luca; Schoups, Gerrit; van de Giesen, Nick

2014-08-01

Parameter estimation of subsurface transport models from multispecies data requires the definition of an objective function that includes different types of measurements. Common approaches are weighted least squares (WLS), where weights are specified a priori for each measurement, and weighted least squares with weight estimation (WLS(we)) where weights are estimated from the data together with the parameters. In this study, we formulate the parameter estimation task as a multivariate Bayesian inference problem. The WLS and WLS(we) methods are special cases in this framework, corresponding to specific prior assumptions about the residual covariance matrix. The Bayesian perspective allows for generalizations to cases where residual correlation is important and for efficient inference by analytically integrating out the variances (weights) and selected covariances from the joint posterior. Specifically, the WLS and WLS(we) methods are compared to a multivariate (MV) approach that accounts for specific residual correlations without the need for explicit estimation of the error parameters. When applied to inference of reactive transport model parameters from column-scale data on dissolved species concentrations, the following results were obtained: (1) accounting for residual correlation between species provides more accurate parameter estimation for high residual correlation levels whereas its influence for predictive uncertainty is negligible, (2) integrating out the (co)variances leads to an efficient estimation of the full joint posterior with a reduced computational effort compared to the WLS(we) method, and (3) in the presence of model structural errors, none of the methods is able to identify the correct parameter values.

A parallel genome-wide RNAi screening strategy to identify host proteins important for entry of Marburg virus and H5N1 influenza virus.

PubMed

Cheng, Han; Koning, Katie; O'Hearn, Aileen; Wang, Minxiu; Rumschlag-Booms, Emily; Varhegyi, Elizabeth; Rong, Lijun

2015-11-24

Genome-wide RNAi screening has been widely used to identify host proteins involved in replication and infection of different viruses, and numerous host factors are implicated in the replication cycles of these viruses, demonstrating the power of this approach. However, discrepancies on target identification of the same viruses by different groups suggest that high throughput RNAi screening strategies need to be carefully designed, developed and optimized prior to the large scale screening. Two genome-wide RNAi screens were performed in parallel against the entry of pseudotyped Marburg viruses and avian influenza virus H5N1 utilizing an HIV-1 based surrogate system, to identify host factors which are important for virus entry. A comparative analysis approach was employed in data analysis, which alleviated systematic positional effects and reduced the false positive number of virus-specific hits. The parallel nature of the strategy allows us to easily identify the host factors for a specific virus with a greatly reduced number of false positives in the initial screen, which is one of the major problems with high throughput screening. The power of this strategy is illustrated by a genome-wide RNAi screen for identifying the host factors important for Marburg virus and/or avian influenza virus H5N1 as described in this study. This strategy is particularly useful for highly pathogenic viruses since pseudotyping allows us to perform high throughput screens in the biosafety level 2 (BSL-2) containment instead of the BSL-3 or BSL-4 for the infectious viruses, with alleviated safety concerns. The screening strategy together with the unique comparative analysis approach makes the data more suitable for hit selection and enables us to identify virus-specific hits with a much lower false positive rate.

Impacts of Different Types of Measurements on Estimating Unsaturatedflow Parameters

NASA Astrophysics Data System (ADS)

Shi, L.

2015-12-01

This study evaluates the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Turbulent Flow and Sand Dune Dynamics: Identifying Controls on Aeolian Sediment Transport

NASA Astrophysics Data System (ADS)

Weaver, C. M.; Wiggs, G.

2007-12-01

Sediment transport models are founded on cubic power relationships between the transport rate and time averaged flow parameters. These models have achieved limited success and recent aeolian and fluvial research has focused on the modelling and measurement of sediment transport by temporally varying flow conditions. Studies have recognised turbulence as a driving force in sediment transport and have highlighted the importance of coherent flow structures in sediment transport systems. However, the exact mechanisms are still unclear. Furthermore, research in the fluvial environment has identified the significance of turbulent structures for bedform morphology and spacing. However, equivalent research in the aeolian domain is absent. This paper reports the findings of research carried out to characterise the importance of turbulent flow parameters in aeolian sediment transport and determine how turbulent energy and turbulent structures change in response to dune morphology. The relative importance of mean and turbulent wind parameters on aeolian sediment flux was examined in the Skeleton Coast, Namibia. Measurements of wind velocity (using sonic anemometers) and sand transport (using grain impact sensors) at a sampling frequency of 10 Hz were made across a flat surface and along transects on a 9 m high barchan dune. Mean wind parameters and mass sand flux were measured using cup anemometers and wedge-shaped sand traps respectively. Vertical profile data from the sonic anemometers were used to compute turbulence and turbulent stress (Reynolds stress; instantaneous horizontal and vertical fluctuations; coherent flow structures) and their relationship with respect to sand transport and evolving dune morphology. On the flat surface time-averaged parameters generally fail to characterise sand transport dynamics, particularly as the averaging interval is reduced. However, horizontal wind speed correlates well with sand transport even with short averaging times. Quadrant

New Uses for Sensitivity Analysis: How Different Movement Tasks Effect Limb Model Parameter Sensitivity

NASA Technical Reports Server (NTRS)

Winters, J. M.; Stark, L.

1984-01-01

Original results for a newly developed eight-order nonlinear limb antagonistic muscle model of elbow flexion and extension are presented. A wider variety of sensitivity analysis techniques are used and a systematic protocol is established that shows how the different methods can be used efficiently to complement one another for maximum insight into model sensitivity. It is explicitly shown how the sensitivity of output behaviors to model parameters is a function of the controller input sequence, i.e., of the movement task. When the task is changed (for instance, from an input sequence that results in the usual fast movement task to a slower movement that may also involve external loading, etc.) the set of parameters with high sensitivity will in general also change. Such task-specific use of sensitivity analysis techniques identifies the set of parameters most important for a given task, and even suggests task-specific model reduction possibilities.

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

PubMed

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

2013-05-01

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

Correlations among Stress Parameters, Meat and Carcass Quality Parameters in Pigs

PubMed Central

Dokmanovic, Marija; Baltic, Milan Z.; Duric, Jelena; Ivanovic, Jelena; Popovic, Ljuba; Todorovic, Milica; Markovic, Radmila; Pantic, Srdan

2015-01-01

Relationships among different stress parameters (lairage time and blood level of lactate and cortisol), meat quality parameters (initial and ultimate pH value, temperature, drip loss, sensory and instrumental colour, marbling) and carcass quality parameters (degree of rigor mortis and skin damages, hot carcass weight, carcass fat thickness, meatiness) were determined in pigs (n = 100) using Pearson correlations. After longer lairage, blood lactate (p<0.05) and degree of injuries (p<0.001) increased, meat became darker (p<0.001), while drip loss decreased (p<0.05). Higher lactate was associated with lower initial pH value (p<0.01), higher temperature (p<0.001) and skin blemishes score (p<0.05) and more developed rigor mortis (p<0.05), suggesting that lactate could be a predictor of both meat quality and the level of preslaughter stress. Cortisol affected carcass quality, so higher levels of cortisol were associated with increased hot carcass weight, carcass fat thickness on the back and at the sacrum and marbling, but also with decreased meatiness. The most important meat quality parameters (pH and temperature after 60 minutes) deteriorated when blood lactate concentration was above 12 mmol/L. PMID:25656214

The Use of Breast Magnetic Resonance Imaging Parameters to Identify Possible Signaling Pathways of a Serum Biomarker, HE4.

PubMed

Durur-Karakaya, Afak; Durur-Subasi, Irmak; Karaman, Adem; Akcay, Mufide Nuran; Palabiyik, Saziye Sezin; Erdemci, Burak; Alper, Fatih; Acemoglu, Hamit

2016-01-01

This study aimed to investigate the relationship between breast magnetic resonance imaging (MRI) parameters; clinical features such as age, tumor diameter, N, T, and TNM stages; and serum human epididymis protein 4 (HE4) levels in patients with breast carcinoma and use this as a means of estimating possible signaling pathways of the biomarker, HE4. Thirty-seven patients with breast cancer were evaluated by breast MRI and serum HE4 levels before therapy. Correlations between parameters including age, tumor diameter T and N, dynamic curve type, enhancement ratio (ER), slope washin (S-WI), time to peak (TTP), slope washout (S-WO), and the serum level of HE4 were investigated statistically. Human epididymis protein 4 levels of early and advanced stage of disease were also compared statistically. Breast MRI parameters showed correlation to serum HE4 levels and correlations were statistically significant. Of these MRI parameters, S-WI had higher correlation coefficient than the others. Human epididymis protein 4 levels were not statistically different in early and advanced stage of disease. High correlation with MRI parameters related to neoangiogenesis may indicate signaling pathway of HE4.

On approaches to analyze the sensitivity of simulated hydrologic fluxes to model parameters in the community land model

DOE PAGES

Bao, Jie; Hou, Zhangshuan; Huang, Maoyi; ...

2015-12-04

Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalizedmore » linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.« less

Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models.

PubMed

Cuba, Christian E; Valle, Alexander R; Ayala-Charca, Giancarlo; Villota, Elizabeth R; Coronado, Alberto M

2015-09-01

Biomolecular networks that present oscillatory behavior are ubiquitous in nature. While some design principles for robust oscillations have been identified, it is not well understood how these oscillations are affected when the kinetic parameters are constantly changing or are not precisely known, as often occurs in cellular environments. Many models of diverse complexity level, for systems such as circadian rhythms, cell cycle or the p53 network, have been proposed. Here we assess the influence of hundreds of different parameter sets on the sensitivities of two configurations of a well-known oscillatory system, the p53 core network. We show that, for both models and all parameter sets, the parameter related to the p53 positive feedback, i.e. self-promotion, is the only one that presents sizeable sensitivities on extrema, periods and delay. Moreover, varying the parameter set values to change the dynamical characteristics of the response is more restricted in the simple model, whereas the complex model shows greater tunability. These results highlight the importance of the presence of specific network patterns, in addition to the role of parameter values, when we want to characterize oscillatory biochemical systems.

Strength of selection pressure is an important parameter contributing to the complexity of antibiotic resistance evolution.

PubMed

Oz, Tugce; Guvenek, Aysegul; Yildiz, Sadik; Karaboga, Enes; Tamer, Yusuf Talha; Mumcuyan, Nirva; Ozan, Vedat Burak; Senturk, Gizem Hazal; Cokol, Murat; Yeh, Pamela; Toprak, Erdal

2014-09-01

Revealing the genetic changes responsible for antibiotic resistance can be critical for developing novel antibiotic therapies. However, systematic studies correlating genotype to phenotype in the context of antibiotic resistance have been missing. In order to fill in this gap, we evolved 88 isogenic Escherichia coli populations against 22 antibiotics for 3 weeks. For every drug, two populations were evolved under strong selection and two populations were evolved under mild selection. By quantifying evolved populations' resistances against all 22 drugs, we constructed two separate cross-resistance networks for strongly and mildly selected populations. Subsequently, we sequenced representative colonies isolated from evolved populations for revealing the genetic basis for novel phenotypes. Bacterial populations that evolved resistance against antibiotics under strong selection acquired high levels of cross-resistance against several antibiotics, whereas other bacterial populations evolved under milder selection acquired relatively weaker cross-resistance. In addition, we found that strongly selected strains against aminoglycosides became more susceptible to five other drug classes compared with their wild-type ancestor as a result of a point mutation on TrkH, an ion transporter protein. Our findings suggest that selection strength is an important parameter contributing to the complexity of antibiotic resistance problem and use of high doses of antibiotics to clear infections has the potential to promote increase of cross-resistance in clinics. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Optimal input shaping for Fisher identifiability of control-oriented lithium-ion battery models

NASA Astrophysics Data System (ADS)

Rothenberger, Michael J.

This dissertation examines the fundamental challenge of optimally shaping input trajectories to maximize parameter identifiability of control-oriented lithium-ion battery models. Identifiability is a property from information theory that determines the solvability of parameter estimation for mathematical models using input-output measurements. This dissertation creates a framework that exploits the Fisher information metric to quantify the level of battery parameter identifiability, optimizes this metric through input shaping, and facilitates faster and more accurate estimation. The popularity of lithium-ion batteries is growing significantly in the energy storage domain, especially for stationary and transportation applications. While these cells have excellent power and energy densities, they are plagued with safety and lifespan concerns. These concerns are often resolved in the industry through conservative current and voltage operating limits, which reduce the overall performance and still lack robustness in detecting catastrophic failure modes. New advances in automotive battery management systems mitigate these challenges through the incorporation of model-based control to increase performance, safety, and lifespan. To achieve these goals, model-based control requires accurate parameterization of the battery model. While many groups in the literature study a variety of methods to perform battery parameter estimation, a fundamental issue of poor parameter identifiability remains apparent for lithium-ion battery models. This fundamental challenge of battery identifiability is studied extensively in the literature, and some groups are even approaching the problem of improving the ability to estimate the model parameters. The first approach is to add additional sensors to the battery to gain more information that is used for estimation. The other main approach is to shape the input trajectories to increase the amount of information that can be gained from input

Combining Methods to Describe Important Marine Habitats for Top Predators: Application to Identify Biological Hotspots in Tropical Waters.

PubMed

Thiers, Laurie; Louzao, Maite; Ridoux, Vincent; Le Corre, Matthieu; Jaquemet, Sébastien; Weimerskirch, Henri

2014-01-01

In tropical waters resources are usually scarce and patchy, and predatory species generally show specific adaptations for foraging. Tropical seabirds often forage in association with sub-surface predators that create feeding opportunities by bringing prey close to the surface, and the birds often aggregate in large multispecific flocks. Here we hypothesize that frigatebirds, a tropical seabird adapted to foraging with low energetic costs, could be a good predictor of the distribution of their associated predatory species, including other seabirds (e.g. boobies, terns) and subsurface predators (e.g., dolphins, tunas). To test this hypothesis, we compared distribution patterns of marine predators in the Mozambique Channel based on a long-term dataset of both vessel- and aerial surveys, as well as tracking data of frigatebirds. By developing species distribution models (SDMs), we identified key marine areas for tropical predators in relation to contemporaneous oceanographic features to investigate multi-species spatial overlap areas and identify predator hotspots in the Mozambique Channel. SDMs reasonably matched observed patterns and both static (e.g. bathymetry) and dynamic (e.g. Chlorophyll a concentration and sea surface temperature) factors were important explaining predator distribution patterns. We found that the distribution of frigatebirds included the distributions of the associated species. The central part of the channel appeared to be the best habitat for the four groups of species considered in this study (frigatebirds, brown terns, boobies and sub-surface predators).

Identifyability measures to select the parameters to be estimated in a solid-state fermentation distributed parameter model.

PubMed

da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G

2016-07-08

Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.

Dynamic parameter identification of robot arms with servo-controlled electrical motors

NASA Astrophysics Data System (ADS)

Jiang, Zhao-Hui; Senda, Hiroshi

2005-12-01

This paper addresses the issue of dynamic parameter identification of the robot manipulator with servo-controlled electrical motors. An assumption is made that all kinematical parameters, such as link lengths, are known, and only dynamic parameters containing mass, moment of inertia, and their functions need to be identified. First, we derive dynamics of the robot arm with a linear form of the unknown dynamic parameters by taking dynamic characteristics of the motor and servo unit into consideration. Then, we implement the parameter identification approach to identify the unknown parameters with respect to individual link separately. A pseudo-inverse matrix is used for formulation of the parameter identification. The optimal solution is guaranteed in a sense of least-squares of the mean errors. A Direct Drive (DD) SCARA type industrial robot arm AdeptOne is used as an application example of the parameter identification. Simulations and experiments for both open loop and close loop controls are carried out. Comparison of the results confirms the correctness and usefulness of the parameter identification and the derived dynamic model.

Identifiability of large-scale non-linear dynamic network models applied to the ADM1-case study.

PubMed

Nimmegeers, Philippe; Lauwers, Joost; Telen, Dries; Logist, Filip; Impe, Jan Van

2017-06-01

In this work, both the structural and practical identifiability of the Anaerobic Digestion Model no. 1 (ADM1) is investigated, which serves as a relevant case study of large non-linear dynamic network models. The structural identifiability is investigated using the probabilistic algorithm, adapted to deal with the specifics of the case study (i.e., a large-scale non-linear dynamic system of differential and algebraic equations). The practical identifiability is analyzed using a Monte Carlo parameter estimation procedure for a 'non-informative' and 'informative' experiment, which are heuristically designed. The model structure of ADM1 has been modified by replacing parameters by parameter combinations, to provide a generally locally structurally identifiable version of ADM1. This means that in an idealized theoretical situation, the parameters can be estimated accurately. Furthermore, the generally positive structural identifiability results can be explained from the large number of interconnections between the states in the network structure. This interconnectivity, however, is also observed in the parameter estimates, making uncorrelated parameter estimations in practice difficult. Copyright © 2017. Published by Elsevier Inc.

The Body of Knowledge & Content Framework. Identifying the Important Knowledge Required for Productive Performance of a Plastics Machine Operator. Blow Molding, Extrusion, Injection Molding, Thermoforming.

ERIC Educational Resources Information Center

Society of the Plastics Industry, Inc., Washington, DC.

Designed to guide training and curriculum development to prepare machine operators for the national certification exam, this publication identifies the important knowledge required for productive performance by a plastics machine operator. Introductory material discusses the rationale for a national standard, uses of the Body of Knowledge,…

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation

PubMed Central

2017-01-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability. PMID:29186132

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

Nationwide outbreak of Salmonella Montevideo infections associated with contaminated imported black and red pepper: warehouse membership cards provide critical clues to identify the source.

PubMed

Gieraltowski, L; Julian, E; Pringle, J; Macdonald, K; Quilliam, D; Marsden-Haug, N; Saathoff-Huber, L; Von Stein, D; Kissler, B; Parish, M; Elder, D; Howard-King, V; Besser, J; Sodha, S; Loharikar, A; Dalton, S; Williams, I; Barton Behravesh, C

2013-06-01

In November 2009, we initiated a multistate investigation of Salmonella Montevideo infections with pulsed-field gel electrophoresis pattern JIXX01.0011. We identified 272 cases in 44 states with illness onset dates ranging from 1 July 2009 to 14 April 2010. To help generate hypotheses, warehouse store membership card information was collected to identify products consumed by cases. These records identified 19 ill persons who purchased company A salami products before onset of illness. A case-control study was conducted. Ready-to-eat salami consumption was significantly associated with illness (matched odds ratio 8·5, 95% confidence interval 2·1-75·9). The outbreak strain was isolated from company A salami products from an environmental sample from one manufacturing plant, and sealed containers of black and red pepper at the facility. This outbreak illustrates the importance of using membership card information to assist in identifying suspect vehicles, the potential for spices to contaminate ready-to-eat products, and preventing raw ingredient contamination of these products.

On selecting satellite conjunction filter parameters

NASA Astrophysics Data System (ADS)

Alfano, Salvatore; Finkleman, David

2014-06-01

This paper extends concepts of signal detection theory to predict the performance of conjunction screening techniques and guiding the selection of keepout and screening thresholds. The most efficient way to identify satellites likely to collide is to employ filters to identify orbiting pairs that should not come close enough over a prescribed time period to be considered hazardous. Such pairings can then be eliminated from further computation to accelerate overall processing time. Approximations inherent in filtering techniques include screening using only unperturbed Newtonian two body astrodynamics and uncertainties in orbit elements. Therefore, every filtering process is vulnerable to including objects that are not threats and excluding some that are threats, Type I and Type II errors. The approach in this paper guides selection of the best operating point for the filters suited to a user's tolerance for false alarms and unwarned threats. We demonstrate the approach using three archetypal filters with an initial three-day span, select filter parameters based on performance, and then test those parameters using eight historical snapshots of the space catalog. This work provides a mechanism for selecting filter parameters but the choices depend on the circumstances.

Impacts of different types of measurements on estimating unsaturated flow parameters

NASA Astrophysics Data System (ADS)

Shi, Liangsheng; Song, Xuehang; Tong, Juxiu; Zhu, Yan; Zhang, Qiuru

2015-05-01

This paper assesses the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

Identifying obstacles and ranking common biological control research priorities for Europe to manage most economically important pests in arable, vegetable and perennial crops.

PubMed

Lamichhane, Jay Ram; Bischoff-Schaefer, Monika; Bluemel, Sylvia; Dachbrodt-Saaydeh, Silke; Dreux, Laure; Jansen, Jean-Pierre; Kiss, Jozsef; Köhl, Jürgen; Kudsk, Per; Malausa, Thibaut; Messéan, Antoine; Nicot, Philippe C; Ricci, Pierre; Thibierge, Jérôme; Villeneuve, François

2017-01-01

EU agriculture is currently in transition from conventional crop protection to integrated pest management (IPM). Because biocontrol is a key component of IPM, many European countries recently have intensified their national efforts on biocontrol research and innovation (R&I), although such initiatives are often fragmented. The operational outputs of national efforts would benefit from closer collaboration among stakeholders via transnationally coordinated approaches, as most economically important pests are similar across Europe. This paper proposes a common European framework on biocontrol R&I. It identifies generic R&I bottlenecks and needs as well as priorities for three crop types (arable, vegetable and perennial crops). The existing gap between the market offers of biocontrol solutions and the demand of growers, the lengthy and expensive registration process for biocontrol solutions and their varying effectiveness due to variable climatic conditions and site-specific factors across Europe are key obstacles hindering the development and adoption of biocontrol solutions in Europe. Considering arable, vegetable and perennial crops, a dozen common target pests are identified for each type of crop and ranked by order of importance at European level. Such a ranked list indicates numerous topics on which future joint transnational efforts would be justified. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Image parameters for maturity determination of a composted material containing sewage sludge

NASA Astrophysics Data System (ADS)

Kujawa, S.; Nowakowski, K.; Tomczak, R. J.; Boniecki, P.; Dach, J.

2013-07-01

Composting is one of the best methods for management of sewage sludge. In a reasonably conducted composting process it is important to early identify the moment in which a material reaches the young compost stage. The objective of this study was to determine parameters contained in images of composted material's samples that can be used for evaluation of the degree of compost maturity. The study focused on two types of compost: containing sewage sludge with corn straw and sewage sludge with rapeseed straw. The photographing of the samples was carried out on a prepared stand for the image acquisition using VIS, UV-A and mixed (VIS + UV-A) light. In the case of UV-A light, three values of the exposure time were assumed. The values of 46 parameters were estimated for each of the images extracted from the photographs of the composted material's samples. Exemplary averaged values of selected parameters obtained from the images of the composted material in the following sampling days were presented. All of the parameters obtained from the composted material's images are the basis for preparation of training, validation and test data sets necessary in development of neural models for classification of the young compost stage.

Influence of tunnel and soil parameters on vibrations from underground railways

NASA Astrophysics Data System (ADS)

Gupta, S.; Stanus, Y.; Lombaert, G.; Degrande, G.

2009-10-01

A parametric study is performed to identify the key parameters which have an important influence on the generation and propagation of vibrations from underground railways. In this paper, the parameters related to the tunnel and the soil are considered and their influence on the free field response is studied. The coupled periodic finite element-boundary element model and the pipe-in-pipe model have been used for this study. Both models account for the dynamic interaction between the train, the track, the tunnel and the soil. A general analytical formulation is used to compute the response of three-dimensional invariant or periodic media that are excited by moving loads. The response to moving loads is written in terms of the axle loads and the transfer functions. The parametric study can be carried out by separately analyzing the variations in the axle loads and the transfer functions. The axle loads are mainly influenced by the parameters related to the vehicle and the track, while the transfer functions are influenced by the properties of the track, the tunnel and the soil. In the present paper, the parameters related to the tunnel and soil are investigated. It is observed that the material damping and the shear modulus of the soil have an important influence on the propagation of vibrations. The influence of structural changes to the tunnel as well as geometrical properties such as the size and shape of the tunnel is investigated. It is observed that a larger tunnel results in a smaller response above the tunnel as more energy is radiated downwards. Moreover, it is demonstrated that the tunnel geometry has a considerable influence on the response closer to the tunnel.

Estimating Colloidal Contact Model Parameters Using Quasi-Static Compression Simulations.

PubMed

Bürger, Vincent; Briesen, Heiko

2016-10-05

For colloidal particles interacting in suspensions, clusters, or gels, contact models should attempt to include all physical phenomena experimentally observed. One critical point when formulating a contact model is to ensure that the interaction parameters can be easily obtained from experiments. Experimental determinations of contact parameters for particles either are based on bulk measurements for simulations on the macroscopic scale or require elaborate setups for obtaining tangential parameters such as using atomic force microscopy. However, on the colloidal scale, a simple method is required to obtain all interaction parameters simultaneously. This work demonstrates that quasi-static compression of a fractal-like particle network provides all the necessary information to obtain particle interaction parameters using a simple spring-based contact model. These springs provide resistances against all degrees of freedom associated with two-particle interactions, and include critical forces or moments where such springs break, indicating a bond-breakage event. A position-based cost function is introduced to show the identifiability of the two-particle contact parameters, and a discrete, nonlinear, and non-gradient-based global optimization method (simplex with simulated annealing, SIMPSA) is used to minimize the cost function calculated from deviations of particle positions. Results show that, in principle, all necessary contact parameters for an arbitrary particle network can be identified, although numerical efficiency as well as experimental noise must be addressed when applying this method. Such an approach lays the groundwork for identifying particle-contact parameters from a position-based particle analysis for a colloidal system using just one experiment. Spring constants also directly influence the time step of the discrete-element method, and a detailed knowledge of all necessary interaction parameters will help to improve the efficiency of colloidal

Dynamic Testing of a Pre-stretched Flexible Tube for Identifying the Factors Affecting Modal Parameter Estimation

NASA Astrophysics Data System (ADS)

Unnikrishnan, Madhusudanan; Rajan, Akash; Basanthvihar Raghunathan, Binulal; Kochupillai, Jayaraj

2017-08-01

Experimental modal analysis is the primary tool for obtaining the fundamental dynamic characteristics like natural frequency, mode shape and modal damping ratio that determine the behaviour of any structure under dynamic loading conditions. This paper discusses about a carefully designed experimental method for calculating the dynamic characteristics of a pre-stretched horizontal flexible tube made of polyurethane material. The factors that affect the modal parameter estimation like the application time of shaker excitation, pause time between successive excitation cycles, averaging and windowing of measured signal, as well as the precautions to be taken during the experiment are explained in detail. The modal parameter estimation is done using MEscopeVESTM software. A finite element based pre-stressed modal analysis of the flexible tube is also done using ANSYS ver.14.0 software. The experimental and analytical results agreed well. The proposed experimental methodology may be extended for carrying out the modal analysis of many flexible structures like inflatables, tires and membranes.

Computational Algorithms or Identification of Distributed Parameter Systems

DTIC Science & Technology

1993-04-24

delay-differential equations, Volterra integral equations, and partial differential equations with memory terms . In particular we investigated a...tested for estimating parameters in a Volterra integral equation arising from a viscoelastic model of a flexible structure with Boltzmann damping. In...particular, one of the parameters identified was the order of the derivative in Volterra integro-differential equations containing fractional

Identifiability of conservative linear mechanical systems. [applied to large flexible spacecraft structures

NASA Technical Reports Server (NTRS)

Sirlin, S. W.; Longman, R. W.; Juang, J. N.

1985-01-01

With a sufficiently great number of sensors and actuators, any finite dimensional dynamic system is identifiable on the basis of input-output data. It is presently indicated that, for conservative nongyroscopic linear mechanical systems, the number of sensors and actuators required for identifiability is very large, where 'identifiability' is understood as a unique determination of the mass and stiffness matrices. The required number of sensors and actuators drops by a factor of two, given a relaxation of the identifiability criterion so that identification can fail only if the system parameters being identified lie in a set of measure zero. When the mass matrix is known a priori, this additional information does not significantly affect the requirements for guaranteed identifiability, though the number of parameters to be determined is reduced by a factor of two.

Predicting CYP2C19 Catalytic Parameters for Enantioselective Oxidations Using Artificial Neural Networks and a Chirality Code

PubMed Central

Hartman, Jessica H.; Cothren, Steven D.; Park, Sun-Ha; Yun, Chul-Ho; Darsey, Jerry A.; Miller, Grover P.

2013-01-01

Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (kcat, Km, and kcat/Km), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (kcat and Km) were more consistent with experimental values than those for catalytic efficiency (kcat/Km). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds. PMID:23673224

Investigation on sense of control parameters for joystick interface in remote operated container crane application

NASA Astrophysics Data System (ADS)

Abdullah, U. N. N.; Handroos, H.

2017-09-01

Introduction: This paper presents the study of sense of control parameters to improve the lack of direct motion feeling through remote operated container crane station (ROCCS) joystick interface. The investigations of the parameters in this study are important to develop the engineering parameters related to the sense of control goal in the next design process. Methodology: Structured interviews and observations were conducted to obtain the user experience data from thirteen remote container crane operators from two international terminals. Then, interview analysis, task analysis, activity analysis and time line analysis were conducted to compare and contrast the results from interviews and observations. Results: Four experience parameters were identified to support the sense of control goal in the later design improvement of the ROCC joystick interface. The significance of difficulties to control, unsynchronized movements, facilitate in control and decision making in unexpected situation as parameters to the sense of control goal were validated by' feedbacks from operators as well as analysis. Contribution: This study provides feedback directly from end users towards developing a sustainable control interface for ROCCS in specific and remote operated off-road vehicles in general.

Challenges in Identifying Patients with Type 2 Diabetes for Quality-Improvement Interventions in Primary Care Settings and the Importance of Valid Disease Registries.

PubMed

Wozniak, Lisa; Soprovich, Allison; Rees, Sandra; Johnson, Steven T; Majumdar, Sumit R; Johnson, Jeffrey A

2015-10-01

Patient registries are considered an important foundation of chronic disease management, and diabetes patient registries are associated with better processes and outcomes of care. The purpose of this article is to describe the development and use of registries in the Alberta's Caring for Diabetes (ABCD) project to identify and reach target populations for quality-improvement interventions in the primary care setting. We applied the reach, effectiveness, adoption, implementation and maintenance (RE-AIM) framework and expanded the definition of reach beyond the individual (i.e. patient) level to include the ability to identify target populations at an organizational level. To characterize reach and the implementation of registries, semistructured interviews were conducted with key informants, and a usual-care checklist was compiled for each participating Primary Care Network (PCN). Content analysis was used to analyze qualitative data. Using registries to identify and recruit participants for the ABCD interventions proved challenging. The quality of the registries depended on whether physicians granted PCN access to patient lists, the strategies used in development, the reliability of diagnostic information and the data elements collected. In addition, once a diabetes registry was developed, there was limited ability to update it. Proactive management of chronic diseases like diabetes requires the ability to reach targeted patients at the population level. We observed several challenges to the development and application of patient registries. Given the importance of valid registries, strong collaborations and novel strategies that involve policy-makers, PCNs and providers are needed to help find solutions to improve registry quality and resolve maintenance issues. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

A review of parameters and heuristics for guiding metabolic pathfinding.

PubMed

Kim, Sarah M; Peña, Matthew I; Moll, Mark; Bennett, George N; Kavraki, Lydia E

2017-09-15

Recent developments in metabolic engineering have led to the successful biosynthesis of valuable products, such as the precursor of the antimalarial compound, artemisinin, and opioid precursor, thebaine. Synthesizing these traditionally plant-derived compounds in genetically modified yeast cells introduces the possibility of significantly reducing the total time and resources required for their production, and in turn, allows these valuable compounds to become cheaper and more readily available. Most biosynthesis pathways used in metabolic engineering applications have been discovered manually, requiring a tedious search of existing literature and metabolic databases. However, the recent rapid development of available metabolic information has enabled the development of automated approaches for identifying novel pathways. Computer-assisted pathfinding has the potential to save biochemists time in the initial discovery steps of metabolic engineering. In this paper, we review the parameters and heuristics used to guide the search in recent pathfinding algorithms. These parameters and heuristics capture information on the metabolic network structure, compound structures, reaction features, and organism-specificity of pathways. No one metabolic pathfinding algorithm or search parameter stands out as the best to use broadly for solving the pathfinding problem, as each method and parameter has its own strengths and shortcomings. As assisted pathfinding approaches continue to become more sophisticated, the development of better methods for visualizing pathway results and integrating these results into existing metabolic engineering practices is also important for encouraging wider use of these pathfinding methods.

Modal Parameter Identification of a Flexible Arm System

NASA Technical Reports Server (NTRS)

Barrington, Jason; Lew, Jiann-Shiun; Korbieh, Edward; Wade, Montanez; Tantaris, Richard

1998-01-01

In this paper an experiment is designed for the modal parameter identification of a flexible arm system. This experiment uses a function generator to provide input signal and an oscilloscope to save input and output response data. For each vibrational mode, many sets of sine-wave inputs with frequencies close to the natural frequency of the arm system are used to excite the vibration of this mode. Then a least-squares technique is used to analyze the experimental input/output data to obtain the identified parameters for this mode. The identified results are compared with the analytical model obtained by applying finite element analysis.

What are the most important variables for Poaceae airborne pollen forecasting?

PubMed

Navares, Ricardo; Aznarte, José Luis

2017-02-01

In this paper, the problem of predicting future concentrations of airborne pollen is solved through a computational intelligence data-driven approach. The proposed method is able to identify the most important variables among those considered by other authors (mainly recent pollen concentrations and weather parameters), without any prior assumptions about the phenological relevance of the variables. Furthermore, an inferential procedure based on non-parametric hypothesis testing is presented to provide statistical evidence of the results, which are coherent to the literature and outperform previous proposals in terms of accuracy. The study is built upon Poaceae airborne pollen concentrations recorded in seven different locations across the Spanish province of Madrid. Copyright © 2016 Elsevier B.V. All rights reserved.

SENIORLAB: a prospective observational study investigating laboratory parameters and their reference intervals in the elderly.

PubMed

Risch, Martin; Nydegger, Urs; Risch, Lorenz

2017-01-01

In clinical practice, laboratory results are often important for making diagnostic, therapeutic, and prognostic decisions. Interpreting individual results relies on accurate reference intervals and decision limits. Despite the considerable amount of resources in clinical medicine spent on elderly patients, accurate reference intervals for the elderly are rarely available. The SENIORLAB study set out to determine reference intervals in the elderly by investigating a large variety of laboratory parameters in clinical chemistry, hematology, and immunology. The SENIORLAB study is an observational, prospective cohort study. Subjectively healthy residents of Switzerland aged 60 years and older were included for baseline examination (n = 1467), where anthropometric measurements were taken, medical history was reviewed, and a fasting blood sample was drawn under optimal preanalytical conditions. More than 110 laboratory parameters were measured, and a biobank was set up. The study participants are followed up every 3 to 5 years for quality of life, morbidity, and mortality. The primary aim is to evaluate different laboratory parameters at age-related reference intervals. The secondary aims of this study include the following: identify associations between different parameters, identify diagnostic characteristics to diagnose different circumstances, identify the prevalence of occult disease in subjectively healthy individuals, and identify the prognostic factors for the investigated outcomes, including mortality. To obtain better grounds to justify clinical decisions, specific reference intervals for laboratory parameters of the elderly are needed. Reference intervals are obtained from healthy individuals. A major obstacle when obtaining reference intervals in the elderly is the definition of health in seniors because individuals without any medical condition and any medication are rare in older adulthood. Reference intervals obtained from such individuals cannot be

Seismic stochastic inversion identify river channel sand body

NASA Astrophysics Data System (ADS)

He, Z.

2015-12-01

The technology of seismic inversion is regarded as one of the most important part of geophysics. By using the technology of seismic inversion and the theory of stochastic simulation, the concept of seismic stochastic inversion is proposed.Seismic stochastic inversion can play an significant role in the identifying river channel sand body. Accurate sand body description is a crucial parameter to measure oilfield development and oilfield stimulation during the middle and later periods. Besides, rational well spacing density is an essential condition for efficient production. Based on the geological knowledge of a certain oilfield, in line with the use of seismic stochastic inversion, the river channel sand body in the work area is identified. In this paper, firstly, the single river channel body from the composite river channel body is subdivided. Secondly, the distribution of river channel body is ascertained in order to ascertain the direction of rivers. Morever, the superimposed relationship among the sand body is analyzed, especially among the inter-well sand body. The last but not at the least, via the analysis of inversion results of first vacuating the wells and continuous infilling later, it is meeted the most needs well spacing density that can obtain the optimal inversion result. It would serve effective guidance for oilfield stimulation.

Selection of noisy measurement locations for error reduction in static parameter identification

NASA Astrophysics Data System (ADS)

Sanayei, Masoud; Onipede, Oladipo; Babu, Suresh R.

1992-09-01

An incomplete set of noisy static force and displacement measurements is used for parameter identification of structures at the element level. Measurement location and the level of accuracy in the measured data can drastically affect the accuracy of the identified parameters. A heuristic method is presented to select a limited number of degrees of freedom (DOF) to perform a successful parameter identification and to reduce the impact of measurement errors on the identified parameters. This pretest simulation uses an error sensitivity analysis to determine the effect of measurement errors on the parameter estimates. The selected DOF can be used for nondestructive testing and health monitoring of structures. Two numerical examples, one for a truss and one for a frame, are presented to demonstrate that using the measurements at the selected subset of DOF can limit the error in the parameter estimates.

Analysis of sensitivity of simulated recharge to selected parameters for seven watersheds modeled using the precipitation-runoff modeling system

USGS Publications Warehouse

Ely, D. Matthew

2006-01-01

routing parameter. Although the primary objective of this study was to identify, by geographic region, the importance of the parameter value to the simulation of ground-water recharge, the secondary objectives proved valuable for future modeling efforts. The value of a rigorous sensitivity analysis can (1) make the calibration process more efficient, (2) guide additional data collection, (3) identify model limitations, and (4) explain simulated results.

Genome-Wide QTL Mapping for Wheat Processing Quality Parameters in a Gaocheng 8901/Zhoumai 16 Recombinant Inbred Line Population.

PubMed

Jin, Hui; Wen, Weie; Liu, Jindong; Zhai, Shengnan; Zhang, Yan; Yan, Jun; Liu, Zhiyong; Xia, Xianchun; He, Zhonghu

2016-01-01

Dough rheological and starch pasting properties play an important role in determining processing quality in bread wheat (Triticum aestivum L.). In the present study, a recombinant inbred line (RIL) population derived from a Gaocheng 8901/Zhoumai 16 cross grown in three environments was used to identify quantitative trait loci (QTLs) for dough rheological and starch pasting properties evaluated by Mixograph, Rapid Visco-Analyzer (RVA), and Mixolab parameters using the wheat 90 and 660 K single nucleotide polymorphism (SNP) chip assays. A high-density linkage map constructed with 46,961 polymorphic SNP markers from the wheat 90 and 660 K SNP assays spanned a total length of 4121 cM, with an average chromosome length of 196.2 cM and marker density of 0.09 cM/marker; 6596 new SNP markers were anchored to the bread wheat linkage map, with 1046 and 5550 markers from the 90 and 660 K SNP assays, respectively. Composite interval mapping identified 119 additive QTLs on 20 chromosomes except 4D; among them, 15 accounted for more than 10% of the phenotypic variation across two or three environments. Twelve QTLs for Mixograph parameters, 17 for RVA parameters and 55 for Mixolab parameters were new. Eleven QTL clusters were identified. The closely linked SNP markers can be used in marker-assisted wheat breeding in combination with the Kompetitive Allele Specific PCR (KASP) technique for improvement of processing quality in bread wheat.

Genome-Wide QTL Mapping for Wheat Processing Quality Parameters in a Gaocheng 8901/Zhoumai 16 Recombinant Inbred Line Population

PubMed Central

Jin, Hui; Wen, Weie; Liu, Jindong; Zhai, Shengnan; Zhang, Yan; Yan, Jun; Liu, Zhiyong; Xia, Xianchun; He, Zhonghu

2016-01-01

Dough rheological and starch pasting properties play an important role in determining processing quality in bread wheat (Triticum aestivum L.). In the present study, a recombinant inbred line (RIL) population derived from a Gaocheng 8901/Zhoumai 16 cross grown in three environments was used to identify quantitative trait loci (QTLs) for dough rheological and starch pasting properties evaluated by Mixograph, Rapid Visco-Analyzer (RVA), and Mixolab parameters using the wheat 90 and 660 K single nucleotide polymorphism (SNP) chip assays. A high-density linkage map constructed with 46,961 polymorphic SNP markers from the wheat 90 and 660 K SNP assays spanned a total length of 4121 cM, with an average chromosome length of 196.2 cM and marker density of 0.09 cM/marker; 6596 new SNP markers were anchored to the bread wheat linkage map, with 1046 and 5550 markers from the 90 and 660 K SNP assays, respectively. Composite interval mapping identified 119 additive QTLs on 20 chromosomes except 4D; among them, 15 accounted for more than 10% of the phenotypic variation across two or three environments. Twelve QTLs for Mixograph parameters, 17 for RVA parameters and 55 for Mixolab parameters were new. Eleven QTL clusters were identified. The closely linked SNP markers can be used in marker-assisted wheat breeding in combination with the Kompetitive Allele Specific PCR (KASP) technique for improvement of processing quality in bread wheat. PMID:27486464

Effects of structural error on the estimates of parameters of dynamical systems

NASA Technical Reports Server (NTRS)

Hadaegh, F. Y.; Bekey, G. A.

1986-01-01

In this paper, the notion of 'near-equivalence in probability' is introduced for identifying a system in the presence of several error sources. Following some basic definitions, necessary and sufficient conditions for the identifiability of parameters are given. The effects of structural error on the parameter estimates for both the deterministic and stochastic cases are considered.

Developing a methodology for the inverse estimation of root architectural parameters from field based sampling schemes

NASA Astrophysics Data System (ADS)

Morandage, Shehan; Schnepf, Andrea; Vanderborght, Jan; Javaux, Mathieu; Leitner, Daniel; Laloy, Eric; Vereecken, Harry

2017-04-01

Root traits are increasingly important in breading of new crop varieties. E.g., longer and fewer lateral roots are suggested to improve drought resistance of wheat. Thus, detailed root architectural parameters are important. However, classical field sampling of roots only provides more aggregated information such as root length density (coring), root counts per area (trenches) or root arrival curves at certain depths (rhizotubes). We investigate the possibility of obtaining the information about root system architecture of plants using field based classical root sampling schemes, based on sensitivity analysis and inverse parameter estimation. This methodology was developed based on a virtual experiment where a root architectural model was used to simulate root system development in a field, parameterized for winter wheat. This information provided the ground truth which is normally unknown in a real field experiment. The three sampling schemes coring, trenching, and rhizotubes where virtually applied to and aggregated information computed. Morris OAT global sensitivity analysis method was then performed to determine the most sensitive parameters of root architecture model for the three different sampling methods. The estimated means and the standard deviation of elementary effects of a total number of 37 parameters were evaluated. Upper and lower bounds of the parameters were obtained based on literature and published data of winter wheat root architectural parameters. Root length density profiles of coring, arrival curve characteristics observed in rhizotubes, and root counts in grids of trench profile method were evaluated statistically to investigate the influence of each parameter using five different error functions. Number of branches, insertion angle inter-nodal distance, and elongation rates are the most sensitive parameters and the parameter sensitivity varies slightly with the depth. Most parameters and their interaction with the other parameters show

Molecular characterization of NRXN1 deletions from 19,263 clinical microarray cases identifies exons important for neurodevelopmental disease expression

PubMed Central

Lowther, Chelsea; Speevak, Marsha; Armour, Christine M.; Goh, Elaine S.; Graham, Gail E.; Li, Chumei; Zeesman, Susan; Nowaczyk, Malgorzata J.M.; Schultz, Lee-Anne; Morra, Antonella; Nicolson, Rob; Bikangaga, Peter; Samdup, Dawa; Zaazou, Mostafa; Boyd, Kerry; Jung, Jack H.; Siu, Victoria; Rajguru, Manjulata; Goobie, Sharan; Tarnopolsky, Mark A.; Prasad, Chitra; Dick, Paul T.; Hussain, Asmaa S.; Walinga, Margreet; Reijenga, Renske G.; Gazzellone, Matthew; Lionel, Anath C.; Marshall, Christian R.; Scherer, Stephen W.; Stavropoulos, Dimitri J.; McCready, Elizabeth; Bassett, Anne S.

2016-01-01

Purpose The purpose of the current study was to assess the penetrance of NRXN1 deletions. Methods We compared the prevalence and genomic extent of NRXN1 deletions identified among 19,263 clinically referred cases to that of 15,264 controls. The burden of additional clinically relevant CNVs was used as a proxy to estimate the relative penetrance of NRXN1 deletions. Results We identified 41 (0.21%) previously unreported exonic NRXN1 deletions ascertained for developmental delay/intellectual disability, significantly greater than in controls [OR=8.14 (95% CI 2.91–22.72), p< 0.0001)]. Ten (22.7%) of these had a second clinically relevant CNV. Subjects with a deletion near the 3′ end of NRXN1 were significantly more likely to have a second rare CNV than subjects with a 5′ NRXN1 deletion [OR=7.47 (95% CI 2.36–23.61), p=0.0006]. The prevalence of intronic NRXN1 deletions was not statistically different between cases and controls (p=0.618). The majority (63.2%) of intronic NRXN1 deletion cases had a second rare CNV, a two-fold greater prevalence than for exonic NRXN1 deletion cases (p=0.0035). Conclusions The results support the importance of exons near the 5′ end of NRXN1 in the expression of neurodevelopmental disorders. Intronic NRXN1 deletions do not appear to substantially increase the risk for clinical phenotypes. PMID:27195815

Molecular characterization of NRXN1 deletions from 19,263 clinical microarray cases identifies exons important for neurodevelopmental disease expression.

PubMed

Lowther, Chelsea; Speevak, Marsha; Armour, Christine M; Goh, Elaine S; Graham, Gail E; Li, Chumei; Zeesman, Susan; Nowaczyk, Malgorzata J M; Schultz, Lee-Anne; Morra, Antonella; Nicolson, Rob; Bikangaga, Peter; Samdup, Dawa; Zaazou, Mostafa; Boyd, Kerry; Jung, Jack H; Siu, Victoria; Rajguru, Manjulata; Goobie, Sharan; Tarnopolsky, Mark A; Prasad, Chitra; Dick, Paul T; Hussain, Asmaa S; Walinga, Margreet; Reijenga, Renske G; Gazzellone, Matthew; Lionel, Anath C; Marshall, Christian R; Scherer, Stephen W; Stavropoulos, Dimitri J; McCready, Elizabeth; Bassett, Anne S

2017-01-01

The purpose of the current study was to assess the penetrance of NRXN1 deletions. We compared the prevalence and genomic extent of NRXN1 deletions identified among 19,263 clinically referred cases to that of 15,264 controls. The burden of additional clinically relevant copy-number variations (CNVs) was used as a proxy to estimate the relative penetrance of NRXN1 deletions. We identified 41 (0.21%) previously unreported exonic NRXN1 deletions ascertained for developmental delay/intellectual disability that were significantly greater than in controls (odds ratio (OR) = 8.14; 95% confidence interval (CI): 2.91-22.72; P < 0.0001). Ten (22.7%) of these had a second clinically relevant CNV. Subjects with a deletion near the 3' end of NRXN1 were significantly more likely to have a second rare CNV than subjects with a 5' NRXN1 deletion (OR = 7.47; 95% CI: 2.36-23.61; P = 0.0006). The prevalence of intronic NRXN1 deletions was not statistically different between cases and controls (P = 0.618). The majority (63.2%) of intronic NRXN1 deletion cases had a second rare CNV at a prevalence twice as high as that for exonic NRXN1 deletion cases (P = 0.0035). The results support the importance of exons near the 5' end of NRXN1 in the expression of neurodevelopmental disorders. Intronic NRXN1 deletions do not appear to substantially increase the risk for clinical phenotypes.Genet Med 19 1, 53-61.

SPECT System Optimization Against A Discrete Parameter Space

PubMed Central

Meng, L. J.; Li, N.

2013-01-01

In this paper, we present an analytical approach for optimizing the design of a static SPECT system or optimizing the sampling strategy with a variable/adaptive SPECT imaging hardware against an arbitrarily given set of system parameters. This approach has three key aspects. First, it is designed to operate over a discretized system parameter space. Second, we have introduced an artificial concept of virtual detector as the basic building block of an imaging system. With a SPECT system described as a collection of the virtual detectors, one can convert the task of system optimization into a process of finding the optimum imaging time distribution (ITD) across all virtual detectors. Thirdly, the optimization problem (finding the optimum ITD) could be solved with a block-iterative approach or other non-linear optimization algorithms. In essence, the resultant optimum ITD could provide a quantitative measure of the relative importance (or effectiveness) of the virtual detectors and help to identify the system configuration or sampling strategy that leads to an optimum imaging performance. Although we are using SPECT imaging as a platform to demonstrate the system optimization strategy, this development also provides a useful framework for system optimization problems in other modalities, such as positron emission tomography (PET) and X-ray computed tomography (CT) [1, 2]. PMID:23587609

CO2 sequestration by mineral carbonation of steel slags under ambient temperature: parameters influence, and optimization.

PubMed

Ghacham, Alia Ben; Pasquier, Louis-César; Cecchi, Emmanuelle; Blais, Jean-François; Mercier, Guy

2016-09-01

This work focuses on the influence of different parameters on the efficiency of steel slag carbonation in slurry phase under ambient temperature. In the first part, a response surface methodology was used to identify the effect and the interactions of the gas pressure, liquid/solid (L/S) ratio, gas/liquid ratio (G/L), and reaction time on the CO2 removed/sample and to optimize the parameters. In the second part, the parameters' effect on the dissolution of CO2 and its conversion into carbonates were studied more in detail. The results show that the pressure and the G/L ratio have a positive effect on both the dissolution and the conversion of CO2. These results have been correlated with the higher CO2 mass introduced in the reactor. On the other hand, an important effect of the L/S ratio on the overall CO2 removal and more specifically on the carbonate precipitation has been identified. The best results were obtained L/S ratios of 4:1 and 10:1 with respectively 0.046 and 0.052 gCO2 carbonated/g sample. These yields were achieved after 10 min reaction, at ambient temperature, and 10.68 bar of total gas pressure following direct gas treatment.

Crop Damage by Primates: Quantifying the Key Parameters of Crop-Raiding Events

PubMed Central

Wallace, Graham E.; Hill, Catherine M.

2012-01-01

Human-wildlife conflict often arises from crop-raiding, and insights regarding which aspects of raiding events determine crop loss are essential when developing and evaluating deterrents. However, because accounts of crop-raiding behaviour are frequently indirect, these parameters are rarely quantified or explicitly linked to crop damage. Using systematic observations of the behaviour of non-human primates on farms in western Uganda, this research identifies number of individuals raiding and duration of raid as the primary parameters determining crop loss. Secondary factors include distance travelled onto farm, age composition of the raiding group, and whether raids are in series. Regression models accounted for greater proportions of variation in crop loss when increasingly crop and species specific. Parameter values varied across primate species, probably reflecting differences in raiding tactics or perceptions of risk, and thereby providing indices of how comfortable primates are on-farm. Median raiding-group sizes were markedly smaller than the typical sizes of social groups. The research suggests that key parameters of raiding events can be used to measure the behavioural impacts of deterrents to raiding. Furthermore, farmers will benefit most from methods that discourage raiding by multiple individuals, reduce the size of raiding groups, or decrease the amount of time primates are on-farm. This study demonstrates the importance of directly relating crop loss to the parameters of raiding events, using systematic observations of the behaviour of multiple primate species. PMID:23056378

Definitive screening design enables optimization of LC-ESI-MS/MS parameters in proteomics.

PubMed

Aburaya, Shunsuke; Aoki, Wataru; Minakuchi, Hiroyoshi; Ueda, Mitsuyoshi

2017-12-01

In proteomics, more than 100,000 peptides are generated from the digestion of human cell lysates. Proteome samples have a broad dynamic range in protein abundance; therefore, it is critical to optimize various parameters of LC-ESI-MS/MS to comprehensively identify these peptides. However, there are many parameters for LC-ESI-MS/MS analysis. In this study, we applied definitive screening design to simultaneously optimize 14 parameters in the operation of monolithic capillary LC-ESI-MS/MS to increase the number of identified proteins and/or the average peak area of MS1. The simultaneous optimization enabled the determination of two-factor interactions between LC and MS. Finally, we found two parameter sets of monolithic capillary LC-ESI-MS/MS that increased the number of identified proteins by 8.1% or the average peak area of MS1 by 67%. The definitive screening design would be highly useful for high-throughput analysis of the best parameter set in LC-ESI-MS/MS systems.

Cosmological parameter estimation using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Prasad, J.; Souradeep, T.

2014-03-01

Constraining parameters of a theoretical model from observational data is an important exercise in cosmology. There are many theoretically motivated models, which demand greater number of cosmological parameters than the standard model of cosmology uses, and make the problem of parameter estimation challenging. It is a common practice to employ Bayesian formalism for parameter estimation for which, in general, likelihood surface is probed. For the standard cosmological model with six parameters, likelihood surface is quite smooth and does not have local maxima, and sampling based methods like Markov Chain Monte Carlo (MCMC) method are quite successful. However, when there are a large number of parameters or the likelihood surface is not smooth, other methods may be more effective. In this paper, we have demonstrated application of another method inspired from artificial intelligence, called Particle Swarm Optimization (PSO) for estimating cosmological parameters from Cosmic Microwave Background (CMB) data taken from the WMAP satellite.

Selecting Sensitive Parameter Subsets in Dynamical Models With Application to Biomechanical System Identification.

PubMed

Ramadan, Ahmed; Boss, Connor; Choi, Jongeun; Peter Reeves, N; Cholewicki, Jacek; Popovich, John M; Radcliffe, Clark J

2018-07-01

Estimating many parameters of biomechanical systems with limited data may achieve good fit but may also increase 95% confidence intervals in parameter estimates. This results in poor identifiability in the estimation problem. Therefore, we propose a novel method to select sensitive biomechanical model parameters that should be estimated, while fixing the remaining parameters to values obtained from preliminary estimation. Our method relies on identifying the parameters to which the measurement output is most sensitive. The proposed method is based on the Fisher information matrix (FIM). It was compared against the nonlinear least absolute shrinkage and selection operator (LASSO) method to guide modelers on the pros and cons of our FIM method. We present an application identifying a biomechanical parametric model of a head position-tracking task for ten human subjects. Using measured data, our method (1) reduced model complexity by only requiring five out of twelve parameters to be estimated, (2) significantly reduced parameter 95% confidence intervals by up to 89% of the original confidence interval, (3) maintained goodness of fit measured by variance accounted for (VAF) at 82%, (4) reduced computation time, where our FIM method was 164 times faster than the LASSO method, and (5) selected similar sensitive parameters to the LASSO method, where three out of five selected sensitive parameters were shared by FIM and LASSO methods.

Parameters and Measures in Assessment of Motor Learning in Neurorehabilitation; A Systematic Review of the Literature

PubMed Central

Shishov, Nataliya; Melzer, Itshak; Bar-Haim, Simona

2017-01-01

Upper limb function, essential for daily life, is often impaired in individuals after stroke and cerebral palsy (CP). For an improved upper limb function, learning should occur, and therefore training with motor learning principles is included in many rehabilitation interventions. Despite accurate measurement being an important aspect for examination and optimization of treatment outcomes, there are no standard algorithms for outcome measures selection. Moreover, the ability of the chosen measures to identify learning is not well established. We aimed to review and categorize the parameters and measures utilized for identification of motor learning in stroke and CP populations. PubMed, Pedro, and Web of Science databases were systematically searched between January 2000 and March 2016 for studies assessing a form of motor learning following upper extremity training using motor control measures. Thirty-two studies in persons after stroke and 10 studies in CP of any methodological quality were included. Identified outcome measures were sorted into two categories, “parameters,” defined as identifying a form of learning, and “measures,” as tools measuring the parameter. Review's results were organized as a narrative synthesis focusing on the outcome measures. The included studies were heterogeneous in their study designs, parameters and measures. Parameters included adaptation (n = 6), anticipatory control (n = 2), after-effects (n = 3), de-adaptation (n = 4), performance (n = 24), acquisition (n = 8), retention (n = 8), and transfer (n = 14). Despite motor learning theory's emphasis on long-lasting changes and generalization, the majority of studies did not assess the retention and transfer parameters. Underlying measures included kinematic analyses in terms of speed, geometry or both (n = 39), dynamic metrics, measures of accuracy, consistency, and coordination. There is no exclusivity of measures to a specific parameter. Many factors affect task performance

Influence of dual task and frailty on gait parameters of older community-dwelling individuals

PubMed Central

Guedes, Rita C.; Dias, Rosângela C.; Pereira, Leani S. M.; Silva, Sílvia L. A.; Lustosa, Lygia P.; Dias, João M. D.

2014-01-01

Background: Gait parameters such as gait speed (GS) are important indicators of functional capacity. Frailty Syndrome is closely related to GS and is also capable of predicting adverse outcomes. The cognitive demand of gait control is usually explored with dual-task (DT) methodology. Objective: To investigate the effect of DT and frailty on the spatio-temporal parameters of gait in older people and identify which variables relate to GS. Method: The presence of frailty was verified by Fried's Frailty Criteria. Cognitive function was evaluated with the Mini-Mental State Exam (MMSE) and gait parameters were analyzed through the GAITRite(r) system in the single-task and DT conditions. The Kolmogorov-Smirnov, ANOVA, and Pearson's Correlation tests were administered. Results: The participants were assigned to the groups frail (FG), pre-frail (PFG), and non-frail (NFG). During the DT, the three groups showed a decrease in GS, cadence, and stride length and an increase in stride time (p<0.001). The reduction in the GS of the FG during the DT showed a positive correlation with the MMSE scores (r=730; p=0.001) and with grip strength (r=681; p=0.001). Conclusions: Gait parameters are more affected by the DT, especially in the frail older subjects. The reduction in GS in the FG is associated with lower grip strength and lower scores in the MMSE. The GS was able to discriminate the older adults in the three levels of frailty, being an important measure of the functional capacity in this population. PMID:25372007

Visual exploration of parameter influence on phylogenetic trees.

PubMed

Hess, Martin; Bremm, Sebastian; Weissgraeber, Stephanie; Hamacher, Kay; Goesele, Michael; Wiemeyer, Josef; von Landesberger, Tatiana

2014-01-01

Evolutionary relationships between organisms are frequently derived as phylogenetic trees inferred from multiple sequence alignments (MSAs). The MSA parameter space is exponentially large, so tens of thousands of potential trees can emerge for each dataset. A proposed visual-analytics approach can reveal the parameters' impact on the trees. Given input trees created with different parameter settings, it hierarchically clusters the trees according to their structural similarity. The most important clusters of similar trees are shown together with their parameters. This view offers interactive parameter exploration and automatic identification of relevant parameters. Biologists applied this approach to real data of 16S ribosomal RNA and protein sequences of ion channels. It revealed which parameters affected the tree structures. This led to a more reliable selection of the best trees.

Selecting Design Parameters for Flying Vehicles

NASA Astrophysics Data System (ADS)

Makeev, V. I.; Strel'nikova, E. A.; Trofimenko, P. E.; Bondar', A. V.

2013-09-01

Studying the influence of a number of design parameters of solid-propellant rockets on the longitudinal and lateral dispersion is an important applied problem. A mathematical model of a rigid body of variable mass moving in a disturbed medium exerting both wave drag and friction is considered. The model makes it possible to determine the coefficients of aerodynamic forces and moments, which affect the motion of vehicles, and to assess the effect of design parameters on their accuracy

Magnetosheath plasma stability and ULF wave occurrence as a function of location in the magnetosheath and upstream bow shock parameters

NASA Astrophysics Data System (ADS)

Soucek, Jan; Escoubet, C. Philippe; Grison, Benjamin

2015-04-01

We present the results of a statistical study of the distribution of mirror and Alfvén-ion cyclotron (AIC) waves in the magnetosheath together with plasma parameters important for the stability of ULF waves, specifically ion temperature anisotropy and ion beta. Magnetosheath crossings registered by Cluster spacecraft over the course of 2 years served as a basis for the statistics. For each observation we used bow shock, magnetopause, and magnetosheath flow models to identify the relative position of the spacecraft with respect to magnetosheath boundaries and local properties of the upstream shock crossing. A strong dependence of both plasma parameters and mirror/AIC wave occurrence on upstream ΘBn and MA is identified. We analyzed a joint dependence of the same parameters on ΘBn and fractional distance between shock and magnetopause, zenith angle, and length of the flow line. Finally, the occurrence of mirror and AIC modes was compared against the respective instability thresholds. We noted that AIC waves occurred nearly exclusively under mirror stable conditions. This is interpreted in terms of different characters of nonlinear saturation of the two modes.

DNA Barcode for Identifying Folium Artemisiae Argyi from Counterfeits.

PubMed

Mei, Quanxi; Chen, Xiaolu; Xiang, Li; Liu, Yue; Su, Yanyan; Gao, Yuqiao; Dai, Weibo; Dong, Pengpeng; Chen, Shilin

2016-01-01

Folium Artemisiae Argyi is an important herb in traditional Chinese medicine. It is commonly used in moxibustion, medicine, etc. However, identifying Artemisia argyi is difficult because this herb exhibits similar morphological characteristics to closely related species and counterfeits. To verify the applicability of DNA barcoding, ITS2 and psbA-trnH were used to identify A. argyi from 15 closely related species and counterfeits. Results indicated that total DNA was easily extracted from all the samples and that both ITS2 and psbA-trnH fragments can be easily amplified. ITS2 was a more ideal barcode than psbA-trnH and ITS2+psbA-trnH to identify A. argyi from closely related species and counterfeits on the basis of sequence character, genetic distance, and tree methods. The sequence length was 225 bp for the 56 ITS2 sequences of A. argyi, and no variable site was detected. For the ITS2 sequences, A. capillaris, A. anomala, A. annua, A. igniaria, A. maximowicziana, A. princeps, Dendranthema vestitum, and D. indicum had single nucleotide polymorphisms (SNPs). The intraspecific Kimura 2-Parameter distance was zero, which is lower than the minimum interspecific distance (0.005). A. argyi, the closely related species, and counterfeits, except for Artemisia maximowicziana and Artemisia sieversiana, were separated into pairs of divergent clusters by using the neighbor joining, maximum parsimony, and maximum likelihood tree methods. Thus, the ITS2 sequence was an ideal barcode to identify A. argyi from closely related species and counterfeits to ensure the safe use of this plant.

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

NASA Astrophysics Data System (ADS)

White, Jeremy; Stengel, Victoria; Rendon, Samuel; Banta, John

2017-08-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash-Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush

Improving Models of Photosynthetic Thermal Acclimation: Which Parameters are Most Important and How Many Should Be Modified?

NASA Astrophysics Data System (ADS)

Stinziano, J. R.; Way, D.; Bauerle, W.

2017-12-01

Photosynthetic temperature acclimation could strongly affect coupled vegetation-atmosphere feedbacks in the global carbon cycle, especially as the climate warms. Thermal acclimation of photosynthesis can be modelled as changes in the parameters describing the direct effect of temperature on photosynthetic capacity (activation energy, Ea; deactivation energy, Hd; entropy parameter, ΔS) or the basal value of photosynthetic capacity (i.e. photosynthetic capacity measured at 25 °C), however the impact of acclimating these parameters (individually or in combination) on vegetative carbon gain is relatively unexplored. Here we compare the ability of 66 photosynthetic temperature acclimation scenarios to improve predictions of a spatially explicit canopy carbon flux model, MAESTRA, for eddy covariance data from a loblolly pine forest. We show that: 1) incorporating seasonal temperature acclimation of basal photosynthetic capacity improves the model's ability to capture seasonal changes in carbon fluxes; 2) multifactor scenarios of photosynthetic temperature acclimation provide minimal (if any) improvement in model performance over single factor acclimation scenarios; 3) acclimation of enzyme activation energies should be restricted to the temperature ranges of the data from which the equations are derived; and 4) model performance is strongly affected by the choice of deactivation energy. We suggest that a renewed effort be made into understanding the thermal acclimation of enzyme activation and deactivation energies across broad temperature ranges to better understand the mechanisms underlying thermal photosynthetic acclimation.

Exploring natural variation of photosynthetic, primary metabolism and growth parameters in a large panel of Capsicum chinense accessions.

PubMed

Rosado-Souza, Laise; Scossa, Federico; Chaves, Izabel S; Kleessen, Sabrina; Salvador, Luiz F D; Milagre, Jocimar C; Finger, Fernando; Bhering, Leonardo L; Sulpice, Ronan; Araújo, Wagner L; Nikoloski, Zoran; Fernie, Alisdair R; Nunes-Nesi, Adriano

2015-09-01

Collectively, the results presented improve upon the utility of an important genetic resource and attest to a complex genetic basis for differences in both leaf metabolism and fruit morphology between natural populations. Diversity of accessions within the same species provides an alternative method to identify physiological and metabolic traits that have large effects on growth regulation, biomass and fruit production. Here, we investigated physiological and metabolic traits as well as parameters related to plant growth and fruit production of 49 phenotypically diverse pepper accessions of Capsicum chinense grown ex situ under controlled conditions. Although single-trait analysis identified up to seven distinct groups of accessions, working with the whole data set by multivariate analyses allowed the separation of the 49 accessions in three clusters. Using all 23 measured parameters and data from the geographic origin for these accessions, positive correlations between the combined phenotypes and geographic origin were observed, supporting a robust pattern of isolation-by-distance. In addition, we found that fruit set was positively correlated with photosynthesis-related parameters, which, however, do not explain alone the differences in accession susceptibility to fruit abortion. Our results demonstrated that, although the accessions belong to the same species, they exhibit considerable natural intraspecific variation with respect to physiological and metabolic parameters, presenting diverse adaptation mechanisms and being a highly interesting source of information for plant breeders. This study also represents the first study combining photosynthetic, primary metabolism and growth parameters for Capsicum to date.

Person Authentication Using Learned Parameters of Lifting Wavelet Filters

NASA Astrophysics Data System (ADS)

Niijima, Koichi

2006-10-01

This paper proposes a method for identifying persons by the use of the lifting wavelet parameters learned by kurtosis-minimization. Our learning method uses desirable properties of kurtosis and wavelet coefficients of a facial image. Exploiting these properties, the lifting parameters are trained so as to minimize the kurtosis of lifting wavelet coefficients computed for the facial image. Since this minimization problem is an ill-posed problem, it is solved by the aid of Tikhonov's regularization method. Our learning algorithm is applied to each of the faces to be identified to generate its feature vector whose components consist of the learned parameters. The constructed feature vectors are memorized together with the corresponding faces in a feature vectors database. Person authentication is performed by comparing the feature vector of a query face with those stored in the database. In numerical experiments, the lifting parameters are trained for each of the neutral faces of 132 persons (74 males and 58 females) in the AR face database. Person authentication is executed by using the smile and anger faces of the same persons in the database.

Use of a flux-based field capacity criterion to identify effective hydraulic parameters of layered soil profiles subjected to synthetic drainage experiments

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Romano, Nunzio

2016-01-01

This study explores the feasibility of identifying the effective soil hydraulic parameterization of a layered soil profile by using a conventional unsteady drainage experiment leading to field capacity. The flux-based field capacity criterion is attained by subjecting the soil profile to a synthetic drainage process implemented numerically in the Soil-Water-Atmosphere-Plant (SWAP) model. The effective hydraulic parameterization is associated to either aggregated or equivalent parameters, the former being determined by the geometrical scaling theory while the latter is obtained through the inverse modeling approach. Outcomes from both these methods depend on information that is sometimes difficult to retrieve at local scale and rather challenging or virtually impossible at larger scales. The only knowledge of topsoil hydraulic properties, for example, as retrieved by a near-surface field campaign or a data assimilation technique, is often exploited as a proxy to determine effective soil hydraulic parameterization at the largest spatial scales. Comparisons of the effective soil hydraulic characterization provided by these three methods are conducted by discussing the implications for their use and accounting for the trade-offs between required input information and model output reliability. To better highlight the epistemic errors associated to the different effective soil hydraulic properties and to provide some more practical guidance, the layered soil profiles are then grouped by using the FAO textural classes. For the moderately heterogeneous soil profiles available, all three approaches guarantee a general good predictability of the actual field capacity values and provide adequate identification of the effective hydraulic parameters. Conversely, worse performances are encountered for the highly variable vertical heterogeneity, especially when resorting to the "topsoil-only" information. In general, the best performances are guaranteed by the equivalent

Advanced Electrocardiography Can Identify Occult Cardiomyopathy in Doberman Pinschers

NASA Technical Reports Server (NTRS)

Spiljak, M.; Petric, A. Domanjko; Wilberg, M.; Olsen, L. H.; Stepancic, A.; Schlegel, T. T.; Starc, V.

2011-01-01

Recently, multiple advanced resting electrocardiographic (A-ECG) techniques have improved the diagnostic value of short-duration ECG in detection of dilated cardiomyopathy (DCM) in humans. This study investigated whether 12-lead A-ECG recordings could accurately identify the occult phase of DCM in dogs. Short-duration (3-5 min) high-fidelity 12-lead ECG recordings were obtained from 31 privately-owned, clinically healthy Doberman Pinschers (5.4 +/- 1.7 years, 11/20 males/females). Dogs were divided into 2 groups: 1) 19 healthy dogs with normal echocardiographic M-mode measurements: left ventricular internal diameter in diastole (LVIDd . 47mm) and in systole (LVIDs . 38mm) and normal 24-hour ECG recordings (<50 ventricular premature complexes, VPCs); and 2) 12 dogs with occult DCM: 11/12 dogs had increased M-mode measurements (LVIDd . 49mm and/or LVIDs . 40mm) and 5/11 dogs had also >100 VPCs/24h; 1/12 dogs had only abnormal 24-hour ECG recordings (>100 VPCs/24h). ECG recordings were evaluated via custom software programs to calculate multiple parameters of high-frequency (HF) QRS ECG, heart rate variability, QT variability, waveform complexity and 3-D ECG. Student's t-tests determined 19 ECG parameters that were significantly different (P < 0.05) between groups. Principal component factor analysis identified a 5-factor model with 81.4% explained variance. QRS dipolar and non-dipolar voltages, Cornell voltage criteria and QRS waveform residuum were increased significantly (P < 0.05), whereas mean HF QRS amplitude was decreased significantly (P < 0.05) in dogs with occult DCM. For the 5 selected parameters the prediction of occult DCM was performed using a binary logistic regression model with Chi-square tested significance (P < 0.01). ROC analyses showed that the five selected ECG parameters could identify occult ECG with sensitivity 89% and specificity 83%. Results suggest that 12-lead A-ECG might improve diagnostic value of short-duration ECG in earlier detection

Distillation tray structural parameter study: Phase 1

NASA Technical Reports Server (NTRS)

Winter, J. Ronald

1991-01-01

The purpose here is to identify the structural parameters (plate thickness, liquid level, beam size, number of beams, tray diameter, etc.) that affect the structural integrity of distillation trays in distillation columns. Once the sensitivity of the trays' dynamic response to these parameters has been established, the designer will be able to use this information to prepare more accurate specifications for the construction of new trays. Information is given on both static and dynamic analysis, modal response, and tray failure details.

Physician Rating Websites: What Aspects Are Important to Identify a Good Doctor, and Are Patients Capable of Assessing Them? A Mixed-Methods Approach Including Physicians’ and Health Care Consumers’ Perspectives

PubMed Central

Schulz, Peter J

2017-01-01

Background Physician rating websites (PRWs) offer health care consumers the opportunity to evaluate their doctor anonymously. However, physicians’ professional training and experience create a vast knowledge gap in medical matters between physicians and patients. This raises ethical concerns about the relevance and significance of health care consumers’ evaluation of physicians’ performance. Objective To identify the aspects physician rating websites should offer for evaluation, this study investigated the aspects of physicians and their practice relevant for identifying a good doctor, and whether health care consumers are capable of evaluating these aspects. Methods In a first step, a Delphi study with physicians from 4 specializations was conducted, testing various indicators to identify a good physician. These indicators were theoretically derived from Donabedian, who classifies quality in health care into pillars of structure, process, and outcome. In a second step, a cross-sectional survey with health care consumers in Switzerland (N=211) was launched based on the indicators developed in the Delphi study. Participants were asked to rate the importance of these indicators to identify a good physician and whether they would feel capable to evaluate those aspects after the first visit to a physician. All indicators were ordered into a 4×4 grid based on evaluation and importance, as judged by the physicians and health care consumers. Agreement between the physicians and health care consumers was calculated applying Holsti’s method. Results In the majority of aspects, physicians and health care consumers agreed on what facets of care were important and not important to identify a good physician and whether patients were able to evaluate them, yielding a level of agreement of 74.3%. The two parties agreed that the infrastructure, staff, organization, and interpersonal skills are both important for a good physician and can be evaluated by health care

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

PubMed

Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

2018-01-02

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour

MRI-based biomechanical parameters for carotid artery plaque vulnerability assessment.

PubMed

Speelman, Lambert; Teng, Zhongzhao; Nederveen, Aart J; van der Lugt, Aad; Gillard, Jonathan H

2016-03-01

Carotid atherosclerotic plaques are a major cause of ischaemic stroke. The biomechanical environment to which the arterial wall and plaque is subjected to plays an important role in the initiation, progression and rupture of carotid plaques. MRI is frequently used to characterize the morphology of a carotid plaque, but new developments in MRI enable more functional assessment of carotid plaques. In this review, MRI based biomechanical parameters are evaluated on their current status, clinical applicability, and future developments. Blood flow related biomechanical parameters, including endothelial wall shear stress and oscillatory shear index, have been shown to be related to plaque formation. Deriving these parameters directly from MRI flow measurements is feasible and has great potential for future carotid plaque development prediction. Blood pressure induced stresses in a plaque may exceed the tissue strength, potentially leading to plaque rupture. Multi-contrast MRI based stress calculations in combination with tissue strength assessment based on MRI inflammation imaging may provide a plaque stress-strength balance that can be used to assess the plaque rupture risk potential. Direct plaque strain analysis based on dynamic MRI is already able to identify local plaque displacement during the cardiac cycle. However, clinical evidence linking MRI strain to plaque vulnerability is still lacking. MRI based biomechanical parameters may lead to improved assessment of carotid plaque development and rupture risk. However, better MRI systems and faster sequences are required to improve the spatial and temporal resolution, as well as increase the image contrast and signal-to-noise ratio.

Applying machine learning to identify autistic adults using imitation: An exploratory study.

PubMed

Li, Baihua; Sharma, Arjun; Meng, James; Purushwalkam, Senthil; Gowen, Emma

2017-01-01

Autism spectrum condition (ASC) is primarily diagnosed by behavioural symptoms including social, sensory and motor aspects. Although stereotyped, repetitive motor movements are considered during diagnosis, quantitative measures that identify kinematic characteristics in the movement patterns of autistic individuals are poorly studied, preventing advances in understanding the aetiology of motor impairment, or whether a wider range of motor characteristics could be used for diagnosis. The aim of this study was to investigate whether data-driven machine learning based methods could be used to address some fundamental problems with regard to identifying discriminative test conditions and kinematic parameters to classify between ASC and neurotypical controls. Data was based on a previous task where 16 ASC participants and 14 age, IQ matched controls observed then imitated a series of hand movements. 40 kinematic parameters extracted from eight imitation conditions were analysed using machine learning based methods. Two optimal imitation conditions and nine most significant kinematic parameters were identified and compared with some standard attribute evaluators. To our knowledge, this is the first attempt to apply machine learning to kinematic movement parameters measured during imitation of hand movements to investigate the identification of ASC. Although based on a small sample, the work demonstrates the feasibility of applying machine learning methods to analyse high-dimensional data and suggest the potential of machine learning for identifying kinematic biomarkers that could contribute to the diagnostic classification of autism.

The Atlas of Vesta Spectral Parameters derived from Dawn/VIR data

NASA Astrophysics Data System (ADS)

Frigeri, A.; De Sanctis, M. C.; Ammannito, E.; Tosi, F.; Zambon, F.; Capaccioni, F.; Capria, M. T.; Palomba, E.; Longobardo, A.; Fonte, S.; Giardino, M.; Magni, G.; Jaumann, R.; Raymond, C. A.; Russell, C. T.

2013-09-01

The Dawn mission mapped Vesta from three different orbital heights during Survey orbit (2700 km altitude), HAMO (High Altitude Mapping Orbit, 700 km altitude), and LAMO (Low Altitude Mapping Orbit, 210 km altitude) [1]. From these orbits the Dawn's Visible and Infrared Mapping Spectrometer (VIR) acquired infrared and visible spectra from 0.2 to 5 microns, sampled in 864 channels with a spatial resolution reaching about 150 m/pixel. Studies of the comparison of spectra from remote sensed data and spectra from laboratory allows to synthesize spectral parameters, which can be combined to identify specific physical and compositional states. VIR spectra of Vesta, stored in about 4300 Planetary Data System (PDS) cubes, have been analyzed to derive spectral parameters, each of which is diagnostic of the associated mineralogy on the surface of the asteroid being observed [2]. Maps of spectral parameters show terrain units compositions in their stratigraphic context. Band centers and band depths are among the most important diagnostic parameters of the mineralogy in a spectrum. In most pyroxenes and in the basaltic achondrites there is a strong correlation between the position of BI center and BII center and the associated mineralogy. For example, orthopyroxene bands shift towards longer wavelengths with increasing amounts of iron, whereas clinopyroxene bands shift towards longer wavelengths with increasing calcium content. Band depth is related to scattering effects, thus can be related to the physical state of the material.

Sensitivity of DIVWAG to Variations in Weather Parameters

DTIC Science & Technology

1976-04-01

1 18. SUPPLEMENTARY NOTES 1 19. KEY WORDS (Continue on reverse aide if necessary and Identify by block number) DIVWAG WAR GAME SIMULATION...simulation of a Division Level War Game , to determine the signif- icance of varying battlefield parameters; i.e., artillery parameters, troop and...The only Red artillery weapons doing better in bad weather are the 130MM guns , but this statistic is tempered by the few casualties occuring in

Optimisation of shock absorber process parameters using failure mode and effect analysis and genetic algorithm

NASA Astrophysics Data System (ADS)

Mariajayaprakash, Arokiasamy; Senthilvelan, Thiyagarajan; Vivekananthan, Krishnapillai Ponnambal

2013-07-01

The various process parameters affecting the quality characteristics of the shock absorber during the process were identified using the Ishikawa diagram and by failure mode and effect analysis. The identified process parameters are welding process parameters (squeeze, heat control, wheel speed, and air pressure), damper sealing process parameters (load, hydraulic pressure, air pressure, and fixture height), washing process parameters (total alkalinity, temperature, pH value of rinsing water, and timing), and painting process parameters (flowability, coating thickness, pointage, and temperature). In this paper, the process parameters, namely, painting and washing process parameters, are optimized by Taguchi method. Though the defects are reasonably minimized by Taguchi method, in order to achieve zero defects during the processes, genetic algorithm technique is applied on the optimized parameters obtained by Taguchi method.

Estimating parameters with pre-specified accuracies in distributed parameter systems using optimal experiment design

NASA Astrophysics Data System (ADS)

Potters, M. G.; Bombois, X.; Mansoori, M.; Hof, Paul M. J. Van den

2016-08-01

Estimation of physical parameters in dynamical systems driven by linear partial differential equations is an important problem. In this paper, we introduce the least costly experiment design framework for these systems. It enables parameter estimation with an accuracy that is specified by the experimenter prior to the identification experiment, while at the same time minimising the cost of the experiment. We show how to adapt the classical framework for these systems and take into account scaling and stability issues. We also introduce a progressive subdivision algorithm that further generalises the experiment design framework in the sense that it returns the lowest cost by finding the optimal input signal, and optimal sensor and actuator locations. Our methodology is then applied to a relevant problem in heat transfer studies: estimation of conductivity and diffusivity parameters in front-face experiments. We find good correspondence between numerical and theoretical results.

Approach to identifying pollutant source and matching flow field

NASA Astrophysics Data System (ADS)

Liping, Pang; Yu, Zhang; Hongquan, Qu; Tao, Hu; Wei, Wang

2013-07-01

Accidental pollution events often threaten people's health and lives, and it is necessary to identify a pollutant source rapidly so that prompt actions can be taken to prevent the spread of pollution. But this identification process is one of the difficulties in the inverse problem areas. This paper carries out some studies on this issue. An approach using single sensor information with noise was developed to identify a sudden continuous emission trace pollutant source in a steady velocity field. This approach first compares the characteristic distance of the measured concentration sequence to the multiple hypothetical measured concentration sequences at the sensor position, which are obtained based on a source-three-parameter multiple hypotheses. Then we realize the source identification by globally searching the optimal values with the objective function of the maximum location probability. Considering the large amount of computation load resulting from this global searching, a local fine-mesh source search method based on priori coarse-mesh location probabilities is further used to improve the efficiency of identification. Studies have shown that the flow field has a very important influence on the source identification. Therefore, we also discuss the impact of non-matching flow fields with estimation deviation on identification. Based on this analysis, a method for matching accurate flow field is presented to improve the accuracy of identification. In order to verify the practical application of the above method, an experimental system simulating a sudden pollution process in a steady flow field was set up and some experiments were conducted when the diffusion coefficient was known. The studies showed that the three parameters (position, emission strength and initial emission time) of the pollutant source in the experiment can be estimated by using the method for matching flow field and source identification.

Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...

EPA Pesticide Factsheets

With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th

HIV Model Parameter Estimates from Interruption Trial Data including Drug Efficacy and Reservoir Dynamics

PubMed Central

Luo, Rutao; Piovoso, Michael J.; Martinez-Picado, Javier; Zurakowski, Ryan

2012-01-01

Mathematical models based on ordinary differential equations (ODE) have had significant impact on understanding HIV disease dynamics and optimizing patient treatment. A model that characterizes the essential disease dynamics can be used for prediction only if the model parameters are identifiable from clinical data. Most previous parameter identification studies for HIV have used sparsely sampled data from the decay phase following the introduction of therapy. In this paper, model parameters are identified from frequently sampled viral-load data taken from ten patients enrolled in the previously published AutoVac HAART interruption study, providing between 69 and 114 viral load measurements from 3–5 phases of viral decay and rebound for each patient. This dataset is considerably larger than those used in previously published parameter estimation studies. Furthermore, the measurements come from two separate experimental conditions, which allows for the direct estimation of drug efficacy and reservoir contribution rates, two parameters that cannot be identified from decay-phase data alone. A Markov-Chain Monte-Carlo method is used to estimate the model parameter values, with initial estimates obtained using nonlinear least-squares methods. The posterior distributions of the parameter estimates are reported and compared for all patients. PMID:22815727

Estimating cellular parameters through optimization procedures: elementary principles and applications.

PubMed

Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki

2015-01-01

Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.

Soil and vegetation parameter uncertainty on future terrestrial carbon sinks

NASA Astrophysics Data System (ADS)

Kothavala, Z.; Felzer, B. S.

2013-12-01

We examine the role of the terrestrial carbon cycle in a changing climate at the centennial scale using an intermediate complexity Earth system climate model that includes the effects of dynamic vegetation and the global carbon cycle. We present a series of ensemble simulations to evaluate the sensitivity of simulated terrestrial carbon sinks to three key model parameters: (a) The temperature dependence of soil carbon decomposition, (b) the upper temperature limits on the rate of photosynthesis, and (c) the nitrogen limitation of the maximum rate of carboxylation of Rubisco. We integrated the model in fully coupled mode for a 1200-year spin-up period, followed by a 300-year transient simulation starting at year 1800. Ensemble simulations were conducted varying each parameter individually and in combination with other variables. The results of the transient simulations show that terrestrial carbon uptake is very sensitive to the choice of model parameters. Changes in net primary productivity were most sensitive to the upper temperature limit on the rate of photosynthesis, which also had a dominant effect on overall land carbon trends; this is consistent with previous research that has shown the importance of climatic suppression of photosynthesis as a driver of carbon-climate feedbacks. Soil carbon generally decreased with increasing temperature, though the magnitude of this trend depends on both the net primary productivity changes and the temperature dependence of soil carbon decomposition. Vegetation carbon increased in some simulations, but this was not consistent across all configurations of model parameters. Comparing to global carbon budget observations, we identify the subset of model parameters which are consistent with observed carbon sinks; this serves to narrow considerably the future model projections of terrestrial carbon sink changes in comparison with the full model ensemble.

A new zonation algorithm with parameter estimation using hydraulic head and subsidence observations.

PubMed

Zhang, Meijing; Burbey, Thomas J; Nunes, Vitor Dos Santos; Borggaard, Jeff

2014-01-01

Parameter estimation codes such as UCODE_2005 are becoming well-known tools in groundwater modeling investigations. These programs estimate important parameter values such as transmissivity (T) and aquifer storage values (Sa ) from known observations of hydraulic head, flow, or other physical quantities. One drawback inherent in these codes is that the parameter zones must be specified by the user. However, such knowledge is often unknown even if a detailed hydrogeological description is available. To overcome this deficiency, we present a discrete adjoint algorithm for identifying suitable zonations from hydraulic head and subsidence measurements, which are highly sensitive to both elastic (Sske) and inelastic (Sskv) skeletal specific storage coefficients. With the advent of interferometric synthetic aperture radar (InSAR), distributed spatial and temporal subsidence measurements can be obtained. A synthetic conceptual model containing seven transmissivity zones, one aquifer storage zone and three interbed zones for elastic and inelastic storage coefficients were developed to simulate drawdown and subsidence in an aquifer interbedded with clay that exhibits delayed drainage. Simulated delayed land subsidence and groundwater head data are assumed to be the observed measurements, to which the discrete adjoint algorithm is called to create approximate spatial zonations of T, Sske , and Sskv . UCODE-2005 is then used to obtain the final optimal parameter values. Calibration results indicate that the estimated zonations calculated from the discrete adjoint algorithm closely approximate the true parameter zonations. This automation algorithm reduces the bias established by the initial distribution of zones and provides a robust parameter zonation distribution. © 2013, National Ground Water Association.

Role of perisynaptic parameters in neurotransmitter homeostasis - computational study of a general synapse

PubMed Central

Pendyam, Sandeep; Mohan, Ashwin; Kalivas, Peter W.; Nair, Satish S.

2015-01-01

Extracellular neurotransmitter concentrations vary over a wide range depending on the type of neurotransmitter and location in the brain. Neurotransmitter homeostasis near a synapse is achieved by a balance of several mechanisms including vesicular release from the presynapse, diffusion, uptake by transporters, non-synaptic production, and regulation of release by autoreceptors. These mechanisms are also affected by the glia surrounding the synapse. However, the role of these mechanisms in achieving neurotransmitter homeostasis is not well understood. A biophysical modeling framework was proposed to reverse engineer glial configurations and parameters related to homeostasis for synapses that support a range of neurotransmitter gradients. Model experiments reveal that synapses with extracellular neurotransmitter concentrations in the micromolar range require non-synaptic neurotransmitter sources and tight synaptic isolation by extracellular glial formations. The model was used to identify the role of perisynaptic parameters on neurotransmitter homeostasis, and to propose glial configurations that could support different levels of extracellular neurotransmitter concentrations. Ranking the parameters based on their effect on neurotransmitter homeostasis, non-synaptic sources were found to be the most important followed by transporter concentration and diffusion coefficient. PMID:22460547

Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model

NASA Astrophysics Data System (ADS)

Qian, Y.; Yang, B.; Lin, G.; Leung, R.; Zhang, Y.

2012-04-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. The latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment

A 2-year follow-up of spirometric parameters in workers of a tile and ceramic industry, Yazd, southeastern Iran.

PubMed

Mehrparvar, A H; Mirmohammadi, S J; Mostaghaci, M; Davari, M H; Hashemi, S H

2013-04-01

Respiratory diseases cause a considerable amount of morbidity and mortality in the world. Pulmonary function tests are important measures for the diagnosis and management of respiratory disorders. Workers in tile and ceramic industry are exposed to high amounts of respiratory pollutants. To identify the changes in spirometric parameters in a 2-year period among tile and ceramic workers in Yazd and compare it with a control group. The study was conducted in 5 tile and ceramic factories selected by cluster sampling between 2009 and 2011 in Yazd, southeastern Iran. Demographic data and spirometric parameters of participants were recorded. Spirometric parameters were significantly reduced during the 2 years. The largest decrease was observed in FVC (≈500 mL) in ball-mill and grinding after 2 years. Decrease in all spirometric parameters was significantly higher in industrial workers than office workers. Respiratory exposure in tile and ceramic industry can significantly affect pulmonary function tests.

The importance of risk-aversion as a measurable psychological parameter governing risk-taking behaviour

NASA Astrophysics Data System (ADS)

Thomas, P. J.

2013-09-01

A utility function with risk-aversion as its sole parameter is developed and used to examine the well-known psychological phenomenon, whereby risk averse people adopt behavioural strategies that are extreme and apparently highly risky. The pioneering work of the psychologist, John W. Atkinson, is revisited, and utility theory is used to extend his mathematical model. His explanation of the psychology involved is improved by regarding risk-aversion not as a discrete variable with three possible states: risk averse, risk neutral and risk confident, but as continuous and covering a large range. A probability distribution is derived, the "motivational density", to describe the process of selecting tasks of different degrees of difficulty. An assessment is then made of practicable methods for measuring risk-aversion.

Efficient design based on perturbed parameter ensembles to identify plausible and diverse variants of a model for climate change projections

NASA Astrophysics Data System (ADS)

Karmalkar, A.; Sexton, D.; Murphy, J.

2017-12-01

We present exploratory work towards developing an efficient strategy to select variants of a state-of-the-art but expensive climate model suitable for climate projection studies. The strategy combines information from a set of idealized perturbed parameter ensemble (PPE) and CMIP5 multi-model ensemble (MME) experiments, and uses two criteria as basis to select model variants for a PPE suitable for future projections: a) acceptable model performance at two different timescales, and b) maintaining diversity in model response to climate change. We demonstrate that there is a strong relationship between model errors at weather and climate timescales for a variety of key variables. This relationship is used to filter out parts of parameter space that do not give credible simulations of historical climate, while minimizing the impact on ranges in forcings and feedbacks that drive model responses to climate change. We use statistical emulation to explore the parameter space thoroughly, and demonstrate that about 90% can be filtered out without affecting diversity in global-scale climate change responses. This leads to identification of plausible parts of parameter space from which model variants can be selected for projection studies.

Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model

NASA Astrophysics Data System (ADS)

Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby

2013-12-01

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.

Physician Rating Websites: What Aspects Are Important to Identify a Good Doctor, and Are Patients Capable of Assessing Them? A Mixed-Methods Approach Including Physicians' and Health Care Consumers' Perspectives.

PubMed

Rothenfluh, Fabia; Schulz, Peter J

2017-05-01

Physician rating websites (PRWs) offer health care consumers the opportunity to evaluate their doctor anonymously. However, physicians' professional training and experience create a vast knowledge gap in medical matters between physicians and patients. This raises ethical concerns about the relevance and significance of health care consumers' evaluation of physicians' performance. To identify the aspects physician rating websites should offer for evaluation, this study investigated the aspects of physicians and their practice relevant for identifying a good doctor, and whether health care consumers are capable of evaluating these aspects. In a first step, a Delphi study with physicians from 4 specializations was conducted, testing various indicators to identify a good physician. These indicators were theoretically derived from Donabedian, who classifies quality in health care into pillars of structure, process, and outcome. In a second step, a cross-sectional survey with health care consumers in Switzerland (N=211) was launched based on the indicators developed in the Delphi study. Participants were asked to rate the importance of these indicators to identify a good physician and whether they would feel capable to evaluate those aspects after the first visit to a physician. All indicators were ordered into a 4×4 grid based on evaluation and importance, as judged by the physicians and health care consumers. Agreement between the physicians and health care consumers was calculated applying Holsti's method. In the majority of aspects, physicians and health care consumers agreed on what facets of care were important and not important to identify a good physician and whether patients were able to evaluate them, yielding a level of agreement of 74.3%. The two parties agreed that the infrastructure, staff, organization, and interpersonal skills are both important for a good physician and can be evaluated by health care consumers. Technical skills of a doctor and outcomes

Global Sensitivity Analysis and Parameter Calibration for an Ecosystem Carbon Model

NASA Astrophysics Data System (ADS)

Safta, C.; Ricciuto, D. M.; Sargsyan, K.; Najm, H. N.; Debusschere, B.; Thornton, P. E.

2013-12-01

We present uncertainty quantification results for a process-based ecosystem carbon model. The model employs 18 parameters and is driven by meteorological data corresponding to years 1992-2006 at the Harvard Forest site. Daily Net Ecosystem Exchange (NEE) observations were available to calibrate the model parameters and test the performance of the model. Posterior distributions show good predictive capabilities for the calibrated model. A global sensitivity analysis was first performed to determine the important model parameters based on their contribution to the variance of NEE. We then proceed to calibrate the model parameters in a Bayesian framework. The daily discrepancies between measured and predicted NEE values were modeled as independent and identically distributed Gaussians with prescribed daily variance according to the recorded instrument error. All model parameters were assumed to have uninformative priors with bounds set according to expert opinion. The global sensitivity results show that the rate of leaf fall (LEAFALL) is responsible for approximately 25% of the total variance in the average NEE for 1992-2005. A set of 4 other parameters, Nitrogen use efficiency (NUE), base rate for maintenance respiration (BR_MR), growth respiration fraction (RG_FRAC), and allocation to plant stem pool (ASTEM) contribute between 5% and 12% to the variance in average NEE, while the rest of the parameters have smaller contributions. The posterior distributions, sampled with a Markov Chain Monte Carlo algorithm, exhibit significant correlations between model parameters. However LEAFALL, the most important parameter for the average NEE, is not informed by the observational data, while less important parameters show significant updates between their prior and posterior densities. The Fisher information matrix values, indicating which parameters are most informed by the experimental observations, are examined to augment the comparison between the calibration and global

Reflectance of vegetation, soil, and water. [effects of measurable plant parameters on multispectral signal variations

NASA Technical Reports Server (NTRS)

Wiegand, C. L. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Reflectance of crop residues, that are important in reducing wind and water erosion, was more often different from bare soil in band 4 than in bands 5, 6, or 7. The plant parameters leaf area index, plant population, plant cover, and plant height explained 95.9 percent of the variation in band 7 (reflective infrared) digital counts for cotton and 78.2 percent of the variation in digital counts for the combined crops sorghum and corn; hence, measurable plant parameters explain most of the signal variation recorded for corpland. Leaf area index and plant population are both highly correlated with crop yields; since plant population can be readily measured (or possibly inferred from seeding rates), it is useful measurement for calibrating ERTS-type MSS digital data in terms of yield.

MontePython 3: Parameter inference code for cosmology

NASA Astrophysics Data System (ADS)

Brinckmann, Thejs; Lesgourgues, Julien; Audren, Benjamin; Benabed, Karim; Prunet, Simon

2018-05-01

MontePython 3 provides numerous ways to explore parameter space using Monte Carlo Markov Chain (MCMC) sampling, including Metropolis-Hastings, Nested Sampling, Cosmo Hammer, and a Fisher sampling method. This improved version of the Monte Python (ascl:1307.002) parameter inference code for cosmology offers new ingredients that improve the performance of Metropolis-Hastings sampling, speeding up convergence and offering significant time improvement in difficult runs. Additional likelihoods and plotting options are available, as are post-processing algorithms such as Importance Sampling and Adding Derived Parameter.

Parameter de-correlation and model-identification in hybrid-style terrestrial laser scanner self-calibration

NASA Astrophysics Data System (ADS)

Lichti, Derek D.; Chow, Jacky; Lahamy, Hervé

One of the important systematic error parameters identified in terrestrial laser scanners is the collimation axis error, which models the non-orthogonality between two instrumental axes. The quality of this parameter determined by self-calibration, as measured by its estimated precision and its correlation with the tertiary rotation angle κ of the scanner exterior orientation, is strongly dependent on instrument architecture. While the quality is generally very high for panoramic-type scanners, it is comparably poor for hybrid-style instruments. Two methods for improving the quality of the collimation axis error in hybrid instrument self-calibration are proposed herein: (1) the inclusion of independent observations of the tertiary rotation angle κ; and (2) the use of a new collimation axis error model. Five real datasets were captured with two different hybrid-style scanners to test each method's efficacy. While the first method achieves the desired outcome of complete decoupling of the collimation axis error from κ, it is shown that the high correlation is simply transferred to other model variables. The second method achieves partial parameter de-correlation to acceptable levels. Importantly, it does so without any adverse, secondary correlations and is therefore the method recommended for future use. Finally, systematic error model identification has been greatly aided in previous studies by graphical analyses of self-calibration residuals. This paper presents results showing the architecture dependence of this technique, revealing its limitations for hybrid scanners.

Modal parameter identification of a CMUT membrane using response data only

NASA Astrophysics Data System (ADS)

Lardiès, Joseph; Bourbon, Gilles; Moal, Patrice Le; Kacem, Najib; Walter, Vincent; Le, Thien-Phu

2018-03-01

Capacitive micromachined ultrasonic transducers (CMUTs) are microelectromechanical systems used for the generation of ultrasounds. The fundamental element of the transducer is a clamped thin metallized membrane that vibrates under voltage variations. To control such oscillations and to optimize its dynamic response it is necessary to know the modal parameters of the membrane such as resonance frequency, damping and stiffness coefficients. The purpose of this work is to identify these parameters using only the time data obtained from the membrane center displacement. Dynamic measurements are conducted in time domain and we use two methods to identify the modal parameters: a subspace method based on an innovation model of the state-space representation and the continuous wavelet transform method based on the use of the ridge of the wavelet transform of the displacement. Experimental results are presented showing the effectiveness of these two procedures in modal parameter identification.

A population-based study of the associations of stroke occurrence with weather parameters in Siberia, Russia (1982-92).

PubMed

Feigin, V L; Nikitin, Y P; Bots, M L; Vinogradova, T E; Grobbee, D E

2000-03-01

Previous studies have established a seasonal variation in stroke occurrence, but none have assessed the influence of inclement weather conditions on stroke incidence in a general population of Russia. We performed a stroke population-based study in the Oktiabrsky District of Novosibirsk, Siberia, Russia. Included in the analysis were 1929 patients with their first occurrence of ischemic stroke (IS), 215 patients with their first occurrence of intracerebral hemorrhage (ICH) and 64 patients with their first occurrence of subarachnoid hemorrhage (SAH): all patients were aged between 25 and 74 years. The cumulative daily occurrence of total strokes and stroke subtypes was evaluated in relation to aggregated daily mean values of ambient temperature, relative humidity and air pressure by means of Poisson regression analysis to estimate the rate ratio (RR) with corresponding confidence interval (CI) and to identify the weather parameters of most importance. In a multivariate analysis, with adjustment for the effects of season, solar and geomagnetic activity, and age of the patients, low ambient temperature (RR 1.32; 95% CI 1.05-1.66) and mean value of air pressure (RR 0.986; 95% CI 0.972-0.999) were important predictors of IS occurrence, while mild ambient temperature (RR 1.52; 95% CI 1. 04-2.22) was an important predictor of ICH occurrence. No relationship between SAH occurrence and any one of the weather parameters studied was revealed. There was no interaction between any meteorological variables that was statistically significant. Inclement weather conditions are associated with the occurrence of IS and ICH in Siberia, Russia. Among the meteorological parameters studied, low ambient temperature and mean air pressure are the most important predictors of IS occurrence, whereas the occurrence of ICH is associated with mild ambient temperature. There is no association between any one of the weather parameters studied and the occurrence of SAH.

Identification of two clinical hepatocellular carcinoma patient phenotypes from results of standard screening parameters

PubMed Central

Carr, Brian I.; Giannini, Edoardo G.; Farinati, Fabio; Ciccarese, Francesca; Rapaccini, Gian Ludovico; Marco, Maria Di; Benvegnù, Luisa; Zoli, Marco; Borzio, Franco; Caturelli, Eugenio; Chiaramonte, Maria; Trevisani, Franco

2014-01-01

scan data) that patients in L phenotype group had 1.5x larger mean tumor masses relative to S, p=6×10−16. Importantly, with the new data, liver test pattern-identified S-phenotype patients had typically 1.7 × longer survival compared to L-phenotype. NPS integrated the liver, tumor and basic demographic factors. Cirrhosis associated thrombocytopenia was typical for smaller S-tumors. In L-tumor phenotype, typical platelet levels increased with the tumor mass. Hepatic inflammation and tumor factors contributed to more aggressive L tumors, with parenchymal destruction and shorter survival. Summary NPS provides integrative interpretation for HCC behavior, identifying two tumor and survival phenotypes by clinical parameter patterns. The NPS classifier is provided as an Excel tool. The NPS system shows the importance of considering each tumor marker and parameter in the total context of all the other parameters of an individual patient. PMID:25023357

Effect of cinnamon on glucose control and lipid parameters.

PubMed

Baker, William L; Gutierrez-Williams, Gabriela; White, C Michael; Kluger, Jeffrey; Coleman, Craig I

2008-01-01

To perform a meta-analysis of randomized controlled trials of cinnamon to better characterize its impact on glucose and plasma lipids. A systematic literature search through July 2007 was conducted to identify randomized placebo-controlled trials of cinnamon that reported data on A1C, fasting blood glucose (FBG), or lipid parameters. The mean change in each study end point from baseline was treated as a continuous variable, and the weighted mean difference was calculated as the difference between the mean value in the treatment and control groups. A random-effects model was used. Five prospective randomized controlled trials (n = 282) were identified. Upon meta-analysis, the use of cinnamon did not significantly alter A1C, FBG, or lipid parameters. Subgroup and sensitivity analyses did not significantly change the results. Cinnamon does not appear to improve A1C, FBG, or lipid parameters in patients with type 1 or type 2 diabetes.

Identifying suitable sites for Florida panther reintroduction

USGS Publications Warehouse

Thatcher, Cindy A.; van Manen, Frank T.; Clark, Joseph D.

2006-01-01

A major objective of the 1995 Florida Panther (Puma concolor cory) Recovery Plan is the establishment of 2 additional panther populations within the historic range. Our goal was to identify prospective sites for Florida panther reintroduction within the historic range based on quantitative landscape assessments. First, we delineated 86 panther home ranges using telemetry data collected from 1981 to 2001 in south Florida to develop a Mahalanobis distance (D2) habitat model, using 4 anthropogenic variables and 3 landscape variables mapped at a 500-m resolution. From that analysis, we identified 9 potential reintroduction sites of sufficient size to support a panther population. We then developed a similar D2 model at a higher spatial resolution to quantify the area of favorable panther habitat at each site. To address potential for the population to expand, we calculated the amount of favorable habitat adjacent to each prospective reintroduction site within a range of dispersal distances of female panthers. We then added those totals to the contiguous patches to estimate the total amount of effective panther habitat at each site. Finally, we developed an expert-assisted model to rank and incorporate potentially important habitat variables that were not appropriate for our empirical analysis (e.g., area of public lands, livestock density). Anthropogenic factors heavily influenced both the landscape and the expert-assisted models. Of the 9 areas we identified, the Okefenokee National Wildlife Refuge, Ozark National Forest, and Felsenthal National Wildlife Refuge regions had the highest combination of effective habitat area and expert opinion scores. Sensitivity analyses indicated that variability among key model parameters did not affect the high ranking of those sites. Those sites should be considered as starting points for the field evaluation of potential reintroduction sites.

Figure of Merit Characteristics Compared to Engineering Parameters

NASA Technical Reports Server (NTRS)

Rickman, D.L.; Schrader, C.M.

2010-01-01

A workshop held in 2005 defined a large number of parameters of interest for users of lunar simulants. The need for formal requirements and standards in the manufacture and use of simulants necessitates certain features of measurements. They must be definable, measureable, useful, and primary rather than derived. There are also certain features that must be avoided. Analysis of the total parameter list led to the realization that almost all of the parameters could be tightly constrained, though not predicted, if only four properties were measured: Particle composition, particle size distribution, particle shape distribution, and bulk density. These four are collectively referred to as figures of merit (FoMs). An evaluation of how each of the parameters identified in 2005 is controlled by the four FoMs is given.

Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

USGS Publications Warehouse

Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Read, Emily K.; Solomon, Christopher T.; Adrian, Rita; Hanson, Paul C.

2014-01-01

Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

Structural and Practical Identifiability Issues of Immuno-Epidemiological Vector-Host Models with Application to Rift Valley Fever.

PubMed

Tuncer, Necibe; Gulbudak, Hayriye; Cannataro, Vincent L; Martcheva, Maia

2016-09-01

In this article, we discuss the structural and practical identifiability of a nested immuno-epidemiological model of arbovirus diseases, where host-vector transmission rate, host recovery, and disease-induced death rates are governed by the within-host immune system. We incorporate the newest ideas and the most up-to-date features of numerical methods to fit multi-scale models to multi-scale data. For an immunological model, we use Rift Valley Fever Virus (RVFV) time-series data obtained from livestock under laboratory experiments, and for an epidemiological model we incorporate a human compartment to the nested model and use the number of human RVFV cases reported by the CDC during the 2006-2007 Kenya outbreak. We show that the immunological model is not structurally identifiable for the measurements of time-series viremia concentrations in the host. Thus, we study the non-dimensionalized and scaled versions of the immunological model and prove that both are structurally globally identifiable. After fixing estimated parameter values for the immunological model derived from the scaled model, we develop a numerical method to fit observable RVFV epidemiological data to the nested model for the remaining parameter values of the multi-scale system. For the given (CDC) data set, Monte Carlo simulations indicate that only three parameters of the epidemiological model are practically identifiable when the immune model parameters are fixed. Alternatively, we fit the multi-scale data to the multi-scale model simultaneously. Monte Carlo simulations for the simultaneous fitting suggest that the parameters of the immunological model and the parameters of the immuno-epidemiological model are practically identifiable. We suggest that analytic approaches for studying the structural identifiability of nested models are a necessity, so that identifiable parameter combinations can be derived to reparameterize the nested model to obtain an identifiable one. This is a crucial step in

Geotechnical Parameters of Alluvial Soils from in-situ Tests

NASA Astrophysics Data System (ADS)

Młynarek, Zbigniew; Stefaniak, Katarzyna; Wierzbicki, Jędrzej

2012-10-01

The article concentrates on the identification of geotechnical parameters of alluvial soil represented by silts found near Poznan and Elblag. Strength and deformation parameters of the subsoil tested were identified by the CPTU (static penetration) and SDMT (dilatometric) methods, as well as by the vane test (VT). Geotechnical parameters of the subsoil were analysed with a view to using the soil as an earth construction material and as a foundation for buildings constructed on the grounds tested. The article includes an analysis of the overconsolidation process of the soil tested and a formula for the identification of the overconsolidation ratio OCR. Equation 9 reflects the relation between the undrained shear strength and plasticity of the silts analyzed and the OCR value. The analysis resulted in the determination of the Nkt coefficient, which might be used to identify the undrained shear strength of both sediments tested. On the basis of a detailed analysis of changes in terms of the constrained oedometric modulus M0, the relations between the said modulus, the liquidity index and the OCR value were identified. Mayne's formula (1995) was used to determine the M0 modulus from the CPTU test. The usefullness of the sediments found near Poznan as an earth construction material was analysed after their structure had been destroyed and compacted with a Proctor apparatus. In cases of samples characterised by different water content and soil particle density, the analysis of changes in terms of cohesion and the internal friction angle proved that these parameters are influenced by the soil phase composition (Fig. 18 and 19). On the basis of the tests, it was concluded that the most desirable shear strength parameters are achieved when the silt is compacted below the optimum water content.

Geotechnical Parameters of Alluvial Soils from in-situ Tests

NASA Astrophysics Data System (ADS)

Młynarek, Zbigniew; Stefaniak, Katarzyna; Wierzbicki, Jedrzej

2012-10-01

The article concentrates on the identification of geotechnical parameters of alluvial soil represented by silts found near Poznan and Elblag. Strength and deformation parameters of the subsoil tested were identified by the CPTU (static penetration) and SDMT (dilatometric) methods, as well as by the vane test (VT). Geotechnical parameters of the subsoil were analysed with a view to using the soil as an earth construction material and as a foundation for buildings constructed on the grounds tested. The article includes an analysis of the overconsolidation process of the soil tested and a formula for the identification of the overconsolidation ratio OCR. Equation 9 reflects the relation between the undrained shear strength and plasticity of the silts analyzed and the OCR value. The analysis resulted in the determination of the Nkt coefficient, which might be used to identify the undrained shear strength of both sediments tested. On the basis of a detailed analysis of changes in terms of the constrained oedometric modulus M0, the relations between the said modulus, the liquidity index and the OCR value were identified. Mayne's formula (1995) was used to determine the M0 modulus from the CPTU test. The usefullness of the sediments found near Poznan as an earth construction material was analysed after their structure had been destroyed and compacted with a Proctor apparatus. In cases of samples characterised by different water content and soil particle density, the analysis of changes in terms of cohesion and the internal friction angle proved that these parameters are influenced by the soil phase composition (Fig. 18 and 19). On the basis of the tests, it was concluded that the most desirable shear strength parameters are achieved when the silt is compacted below the optimum water content.

Individual heterogeneity and identifiability in capture-recapture models

USGS Publications Warehouse

Link, W.A.

2004-01-01

Individual heterogeneity in detection probabilities is a far more serious problem for capture-recapture modeling than has previously been recognized. In this note, I illustrate that population size is not an identifiable parameter under the general closed population mark-recapture model Mh. The problem of identifiability is obvious if the population includes individuals with pi = 0, but persists even when it is assumed that individual detection probabilities are bounded away from zero. Identifiability may be attained within parametric families of distributions for pi, but not among parametric families of distributions. Consequently, in the presence of individual heterogeneity in detection probability, capture-recapture analysis is strongly model dependent.

Computational identification of post-translational modification-based nuclear import regulations by characterizing nuclear localization signal-import receptor interaction.

PubMed

Lin, Jhih-Rong; Liu, Zhonghao; Hu, Jianjun

2014-10-01

The binding affinity between a nuclear localization signal (NLS) and its import receptor is closely related to corresponding nuclear import activity. PTM-based modulation of the NLS binding affinity to the import receptor is one of the most understood mechanisms to regulate nuclear import of proteins. However, identification of such regulation mechanisms is challenging due to the difficulty of assessing the impact of PTM on corresponding nuclear import activities. In this study we proposed NIpredict, an effective algorithm to predict nuclear import activity given its NLS, in which molecular interaction energy components (MIECs) were used to characterize the NLS-import receptor interaction, and the support vector regression machine (SVR) was used to learn the relationship between the characterized NLS-import receptor interaction and the corresponding nuclear import activity. Our experiments showed that nuclear import activity change due to NLS change could be accurately predicted by the NIpredict algorithm. Based on NIpredict, we developed a systematic framework to identify potential PTM-based nuclear import regulations for human and yeast nuclear proteins. Application of this approach has identified the potential nuclear import regulation mechanisms by phosphorylation of two nuclear proteins including SF1 and ORC6. © 2014 Wiley Periodicals, Inc.

Identification of Synchronous Machine Stability - Parameters: AN On-Line Time-Domain Approach.

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

A time-domain modeling approach is described which enables the stability-study parameters of the synchronous machine to be determined directly from input-output data measured at the terminals of the machine operating under normal conditions. The transient responses due to system perturbations are used to identify the parameters of the equivalent circuit models. The described models are verified by comparing their responses with the machine responses generated from the transient stability models of a small three-generator multi-bus power system and of a single -machine infinite-bus power network. The least-squares method is used for the solution of the model parameters. As a precaution against ill-conditioned problems, the singular value decomposition (SVD) is employed for its inherent numerical stability. In order to identify the equivalent-circuit parameters uniquely, the solution of a linear optimization problem with non-linear constraints is required. Here, the SVD appears to offer a simple solution to this otherwise difficult problem. Furthermore, the SVD yields solutions with small bias and, therefore, physically meaningful parameters even in the presence of noise in the data. The question concerning the need for a more advanced model of the synchronous machine which describes subtransient and even sub-subtransient behavior is dealt with sensibly by the concept of condition number. The concept provides a quantitative measure for determining whether such an advanced model is indeed necessary. Finally, the recursive SVD algorithm is described for real-time parameter identification and tracking of slowly time-variant parameters. The algorithm is applied to identify the dynamic equivalent power system model.

Mango (Mangifera indica L.) cv. Kent fruit mesocarp de novo transcriptome assembly identifies gene families important for ripening

USDA-ARS?s Scientific Manuscript database

Fruit ripening is a physiological and biochemical process genetically programmed to regulate fruit quality parameters like firmness, flavor, odor and color, as well as production of ethylene in climacteric fruit. In this study, a transcriptomic analysis of mango (Mangifera indica L.) mesocarp cv. "K...

A Stepwise Test Characteristic Curve Method to Detect Item Parameter Drift

ERIC Educational Resources Information Center

Guo, Rui; Zheng, Yi; Chang, Hua-Hua

2015-01-01

An important assumption of item response theory is item parameter invariance. Sometimes, however, item parameters are not invariant across different test administrations due to factors other than sampling error; this phenomenon is termed item parameter drift. Several methods have been developed to detect drifted items. However, most of the…

Material and morphology parameter sensitivity analysis in particulate composite materials

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyu; Oskay, Caglar

2017-12-01

This manuscript presents a novel parameter sensitivity analysis framework for damage and failure modeling of particulate composite materials subjected to dynamic loading. The proposed framework employs global sensitivity analysis to study the variance in the failure response as a function of model parameters. In view of the computational complexity of performing thousands of detailed microstructural simulations to characterize sensitivities, Gaussian process (GP) surrogate modeling is incorporated into the framework. In order to capture the discontinuity in response surfaces, the GP models are integrated with a support vector machine classification algorithm that identifies the discontinuities within response surfaces. The proposed framework is employed to quantify variability and sensitivities in the failure response of polymer bonded particulate energetic materials under dynamic loads to material properties and morphological parameters that define the material microstructure. Particular emphasis is placed on the identification of sensitivity to interfaces between the polymer binder and the energetic particles. The proposed framework has been demonstrated to identify the most consequential material and morphological parameters under vibrational and impact loads.

Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration

NASA Astrophysics Data System (ADS)

Bai, P.

2017-12-01

Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.

Identification of the Parameters of Menétrey -Willam Failure Surface of Calcium Silicate Units

NASA Astrophysics Data System (ADS)

Radosław, Jasiński

2017-10-01

The identification of parameters of Menétrey-Willamsurface made of concrete, masonry or autoclaved aerated concrete is not complicated. It is much more difficult to identify failure parameters of masonry units with cavities. This paper describes the concept of identifying the parameters of Menétrey-Willam failure surface (M-W-3) with reference to masonry units with vertical cavities. The M-W-3 surface is defined by uniaxial compressive strength fc, uniaxial tensile strength ft and eccentricity of elliptical function e. A test stand was built to identify surface parameters. It was used to test behaviour of masonry units under triaxial stress and conduct tests on whole masonry units in the uniaxial state. Results from tests on tens of silicate masonry units are presented in the Haigh-Westergaard (H-W) space. Statistical analyses were used to identify the shape of surface meridian, and then to determine eccentricity of the elliptical function.

Identification of Bouc-Wen hysteretic parameters based on enhanced response sensitivity approach

NASA Astrophysics Data System (ADS)

Wang, Li; Lu, Zhong-Rong

2017-05-01

This paper aims to identify parameters of Bouc-Wen hysteretic model using time-domain measured data. It follows a general inverse identification procedure, that is, identifying model parameters is treated as an optimization problem with the nonlinear least squares objective function. Then, the enhanced response sensitivity approach, which has been shown convergent and proper for such kind of problems, is adopted to solve the optimization problem. Numerical tests are undertaken to verify the proposed identification approach.

Catalogue of HI PArameters (CHIPA)

NASA Astrophysics Data System (ADS)

Saponara, J.; Benaglia, P.; Koribalski, B.; Andruchow, I.

2015-08-01

The catalogue of HI parameters of galaxies HI (CHIPA) is the natural continuation of the compilation by M.C. Martin in 1998. CHIPA provides the most important parameters of nearby galaxies derived from observations of the neutral Hydrogen line. The catalogue contains information of 1400 galaxies across the sky and different morphological types. Parameters like the optical diameter of the galaxy, the blue magnitude, the distance, morphological type, HI extension are listed among others. Maps of the HI distribution, velocity and velocity dispersion can also be display for some cases. The main objective of this catalogue is to facilitate the bibliographic queries, through searching in a database accessible from the internet that will be available in 2015 (the website is under construction). The database was built using the open source `` mysql (SQL, Structured Query Language, management system relational database) '', while the website was built with ''HTML (Hypertext Markup Language)'' and ''PHP (Hypertext Preprocessor)''.

Identifiability in N-mixture models: a large-scale screening test with bird data.

PubMed

Kéry, Marc

2018-02-01

Binomial N-mixture models have proven very useful in ecology, conservation, and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by Akaike's information criterion. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models that combine different observation models or the use of external information via informative priors or penalized likelihoods, may help. © 2017 by the Ecological Society of America.

A Bayesian approach to identifying structural nonlinearity using free-decay response: Application to damage detection in composites

USGS Publications Warehouse

Nichols, J.M.; Link, W.A.; Murphy, K.D.; Olson, C.C.

2010-01-01

This work discusses a Bayesian approach to approximating the distribution of parameters governing nonlinear structural systems. Specifically, we use a Markov Chain Monte Carlo method for sampling the posterior parameter distributions thus producing both point and interval estimates for parameters. The method is first used to identify both linear and nonlinear parameters in a multiple degree-of-freedom structural systems using free-decay vibrations. The approach is then applied to the problem of identifying the location, size, and depth of delamination in a model composite beam. The influence of additive Gaussian noise on the response data is explored with respect to the quality of the resulting parameter estimates.

The role of impulse parameters in force variability

NASA Technical Reports Server (NTRS)

Carlton, L. G.; Newell, K. M.

1986-01-01

One of the principle limitations of the human motor system is the ability to produce consistent motor responses. When asked to repeatedly make the same movement, performance outcomes are characterized by a considerable amount of variability. This occurs whether variability is expressed in terms of kinetics or kinematics. Variability in performance is of considerable importance because for tasks requiring accuracy it is a critical variable in determining the skill of the performer. What has long been sought is a description of the parameter or parameters that determine the degree of variability. Two general experimental protocals were used. One protocal is to use dynamic actions and record variability in kinematic parameters such as spatial or temporal error. A second strategy was to use isometric actions and record kinetic variables such as peak force produced. What might be the important force related factors affecting variability is examined and an experimental approach to examine the influence of each of these variables is provided.

Differences of Sagittal Lumbosacral Parameters between Patients with Lumbar Spondylolysis and Normal Adults

PubMed Central

Yin, Jin; Peng, Bao-Gan; Li, Yong-Chao; Zhang, Nai-Yang; Yang, Liang; Li, Duan-Ming

2016-01-01

Background: Recent studies have suggested an association between elevated pelvic incidence (PI) and the development of lumbar spondylolysis. However, there is still lack of investigation for Han Chinese people concerning the normal range of spinopelvic parameters and relationship between abnormal sagittal parameters and lumbar diseases. The objective of the study was to investigate sagittal lumbosacral parameters of adult lumbar spondylolysis patients in Han Chinese population. Methods: A total of 52 adult patients with symptomatic lumbar spondylolysis treated in the General Hospital of Armed Police Force (Beijing, China) were identified as the spondylolysis group. All the 52 patients were divided into two subgroups, Subgroup A: 36 patients with simple lumbar spondylolysis, and Subgroup B: 16 patients with lumbar spondylolysis accompanying with mild lumbar spondylolisthesis (slip percentage <30%). Altogether 207 healthy adults were chosen as the control group. All patients and the control group took lumbosacral lateral radiographs. Seven sagittal lumbosacral parameters, including PI, pelvic tilt (PT), sacral slope (SS), lumbar lordosis (LL), L5 incidence, L5 slope, and sacral table angle (STA), were measured in the lateral radiographs. All the parameters aforementioned were compared between the two subgroups and between the spondylolysis group and the control group with independent-sample t-test. Results: There were no statistically significant differences of all seven sagittal lumbosacral parameters between Subgroup A and Subgroup B. PI, PT, SS, and LL were higher (P < 0.05) in the spondylolysis group than those in the control group, but STA was lower (P < 0.001) in the spondylolysis group. Conclusions: Current study results suggest that increased PI and decreased STA may play important roles in the pathology of lumbar spondylolysis in Han Chinese population. PMID:27174324

Differences of Sagittal Lumbosacral Parameters between Patients with Lumbar Spondylolysis and Normal Adults.

PubMed

Yin, Jin; Peng, Bao-Gan; Li, Yong-Chao; Zhang, Nai-Yang; Yang, Liang; Li, Duan-Ming

2016-05-20

Recent studies have suggested an association between elevated pelvic incidence (PI) and the development of lumbar spondylolysis. However, there is still lack of investigation for Han Chinese people concerning the normal range of spinopelvic parameters and relationship between abnormal sagittal parameters and lumbar diseases. The objective of the study was to investigate sagittal lumbosacral parameters of adult lumbar spondylolysis patients in Han Chinese population. A total of 52 adult patients with symptomatic lumbar spondylolysis treated in the General Hospital of Armed Police Force (Beijing, China) were identified as the spondylolysis group. All the 52 patients were divided into two subgroups, Subgroup A: 36 patients with simple lumbar spondylolysis, and Subgroup B: 16 patients with lumbar spondylolysis accompanying with mild lumbar spondylolisthesis (slip percentage <30%). Altogether 207 healthy adults were chosen as the control group. All patients and the control group took lumbosacral lateral radiographs. Seven sagittal lumbosacral parameters, including PI, pelvic tilt (PT), sacral slope (SS), lumbar lordosis (LL), L5 incidence, L5 slope, and sacral table angle (STA), were measured in the lateral radiographs. All the parameters aforementioned were compared between the two subgroups and between the spondylolysis group and the control group with independent-sample t- test. There were no statistically significant differences of all seven sagittal lumbosacral parameters between Subgroup A and Subgroup B. PI, PT, SS, and LL were higher (P < 0.05) in the spondylolysis group than those in the control group, but STA was lower (P < 0.001) in the spondylolysis group. Current study results suggest that increased PI and decreased STA may play important roles in the pathology of lumbar spondylolysis in Han Chinese population.

Bead-bead interaction parameters in dissipative particle dynamics: Relation to bead-size, solubility parameter, and surface tension

NASA Astrophysics Data System (ADS)

Maiti, Amitesh; McGrother, Simon

2004-01-01

Dissipative particle dynamics (DPD) is a mesoscale modeling method for simulating equilibrium and dynamical properties of polymers in solution. The basic idea has been around for several decades in the form of bead-spring models. A few years ago, Groot and Warren [J. Chem. Phys. 107, 4423 (1997)] established an important link between DPD and the Flory-Huggins χ-parameter theory for polymer solutions. We revisit the Groot-Warren theory and investigate the DPD interaction parameters as a function of bead size. In particular, we show a consistent scheme of computing the interfacial tension in a segregated binary mixture. Results for three systems chosen for illustration are in excellent agreement with experimental results. This opens the door for determining DPD interactions using interfacial tension as a fitting parameter.

Calibrated Hydrothermal Parameters, Barrow, Alaska, 2013

DOE Data Explorer

Atchley, Adam; Painter, Scott; Harp, Dylan; Coon, Ethan; Wilson, Cathy; Liljedahl, Anna; Romanovsky, Vladimir

2015-01-29

A model-observation-experiment process (ModEx) is used to generate three 1D models of characteristic micro-topographical land-formations, which are capable of simulating present active thaw layer (ALT) from current climate conditions. Each column was used in a coupled calibration to identify moss, peat and mineral soil hydrothermal properties to be used in up-scaled simulations. Observational soil temperature data from a tundra site located near Barrow, AK (Area C) is used to calibrate thermal properties of moss, peat, and sandy loam soil to be used in the multiphysics Advanced Terrestrial Simulator (ATS) models. Simulation results are a list of calibrated hydrothermal parameters for moss, peat, and mineral soil hydrothermal parameters.

Two-dimensional advective transport in ground-water flow parameter estimation

USGS Publications Warehouse

Anderman, E.R.; Hill, M.C.; Poeter, E.P.

1996-01-01

Nonlinear regression is useful in ground-water flow parameter estimation, but problems of parameter insensitivity and correlation often exist given commonly available hydraulic-head and head-dependent flow (for example, stream and lake gain or loss) observations. To address this problem, advective-transport observations are added to the ground-water flow, parameter-estimation model MODFLOWP using particle-tracking methods. The resulting model is used to investigate the importance of advective-transport observations relative to head-dependent flow observations when either or both are used in conjunction with hydraulic-head observations in a simulation of the sewage-discharge plume at Otis Air Force Base, Cape Cod, Massachusetts, USA. The analysis procedure for evaluating the probable effect of new observations on the regression results consists of two steps: (1) parameter sensitivities and correlations calculated at initial parameter values are used to assess the model parameterization and expected relative contributions of different types of observations to the regression; and (2) optimal parameter values are estimated by nonlinear regression and evaluated. In the Cape Cod parameter-estimation model, advective-transport observations did not significantly increase the overall parameter sensitivity; however: (1) inclusion of advective-transport observations decreased parameter correlation enough for more unique parameter values to be estimated by the regression; (2) realistic uncertainties in advective-transport observations had a small effect on parameter estimates relative to the precision with which the parameters were estimated; and (3) the regression results and sensitivity analysis provided insight into the dynamics of the ground-water flow system, especially the importance of accurate boundary conditions. In this work, advective-transport observations improved the calibration of the model and the estimation of ground-water flow parameters, and use of

Critical parameters for coarse coal underground slurry haulage systems

NASA Technical Reports Server (NTRS)

Maynard, D. P.

1981-01-01

Factors are identified which must be considered in meeting the requirements of a transportation system for conveying, in a pipeline, the coal mined by a continuous mining machine to a storage location neat the mine entrance or to a coal preparation plant located near the surface. For successful operation, the slurry haulage the system should be designed to operated in the turbulent flow regime at a flow rate at least 30% greater than the deposition velocity (slurry flow rate at which the solid particles tend to settle in the pipe). The capacity of the haulage system should be compatible with the projected coal output. Partical size, solid concentration, density, and viscosity of the suspension are if importance as well as the selection of the pumps, pipes, and valves. The parameters with the greatest effect on system performance ar flow velocity, pressure coal particle size, and solids concentration.

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words

PubMed Central

Huang, Yongfeng; Wu, Xian; Li, Xing

2015-01-01

With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods. PMID:26106409

Identifying large scale structures at 1 AU using fluctuations and wavelets

NASA Astrophysics Data System (ADS)

Niembro, T.; Lara, A.

2016-12-01

The solar wind (SW) is inhomogeneous and it is dominated for two types of flows: one quasi-stationary and one related to large scale transients (such as coronal mass ejections and co-rotating interaction regions). The SW inhomogeneities can be study as fluctuations characterized by a wide range of length and time scales. We are interested in the study of the characteristic fluctuations caused by large scale transient events. To do so, we define the vector space F with the normalized moving monthly/annual deviations as the orthogonal basis. Then, we compute the norm in this space of the solar wind parameters (velocity, magnetic field, density and temperature) fluctuations using WIND data from August 1992 to August 2015. This norm gives important information about the presence of a large structure disturbance in the solar wind and by applying a wavelet transform to this norm, we are able to determine, without subjectivity, the duration of the compression regions of these large transient structures and, even more, to identify if the structure corresponds to a single or complex (or merged) event. With this method we have automatically detected most of the events identified and published by other authors.

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

USGS Publications Warehouse

White, Jeremy; Stengel, Victoria G.; Rendon, Samuel H.; Banta, John

2017-01-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush

Important operational parameters of membrane bioreactor-sludge disintegration (MBR-SD) system for zero excess sludge production.

PubMed

Yoon, Seong-Hoon

2003-04-01

In order to prevent excess sludge production during wastewater treatment, a membrane bioreactor-sludge disintegration (MBR-SD) system has been introduced, where the disintegrated sludge is recycled to the bioreactor as a feed solution. In this study, a mathematical model was developed by incorporating a sludge disintegration term into the conventional activated sludge model and the relationships among the operational parameters were investigated. A new definition of F/M ratio for the MBR-SD system was suggested to evaluate the actual organic loading rate. The actual F/M ratio was expected to be much higher than the apparent F/M ratio in MBR-SD. The kinetic parameters concerning the biodegradability of organics hardly affect the system performance. Instead, sludge solubilization ratio (alpha) in the SD process and particulate hydrolysis rate constant (k(h)) in biological reaction determine the sludge disintegration number (SDN), which is related with the overall economics of the MBR-SD system. Under reasonable alpha and k(h) values, SDN would range between 3 and 5 which means the amount of sludge required to be disintegrated would be 3-5 times higher for preventing a particular amount of sludge production. Finally, normalized sludge disintegration rate (q/V) which is needed to maintain a certain level of MLSS in the MBR-SD system was calculated as a function of F/V ratio.

Identifying rural food deserts: Methodological considerations for food environment interventions.

PubMed

Lebel, Alexandre; Noreau, David; Tremblay, Lucie; Oberlé, Céline; Girard-Gadreau, Maurie; Duguay, Mathieu; Block, Jason P

2016-06-09

Food insecurity in an important public health issue and affects 13% of Canadian households. It is associated with poor accessibility to fresh, diverse and affordable food products. However, measurement of the food environment is challenging in rural settings since the proximity of food supply sources is unevenly distributed. The objective of this study was to develop a methodology to identify food deserts in rural environments. In-store evaluations of 25 food products were performed for all food stores located in four contiguous rural counties in Quebec. The quality of food products was estimated using four indices: freshness, affordability, diversity and the relative availability. Road network distance between all residences to the closest food store with a favourable score on the four dimensions was mapped to identify residential clusters located in deprived communities without reasonable access to a "good" food source. The result was compared with the food desert parameters proposed by the US Department of Agriculture (USDA), as well as with the perceptions of a group of regional stakeholders. When food quality was considered, food deserts appeared more prevalent than when only the USDA definition was used. Objective measurements of the food environment matched stakeholders' perceptions. Food stores' characteristics are different in rural areas and require an in-store estimation to identify potential rural food deserts. The objective measurements of the food environment combined with the field knowledge of stakeholders may help to shape stronger arguments to gain the support of decision-makers to develop relevant interventions.

Correlations among the parameters of the spherical model for eclipsing binaries

NASA Technical Reports Server (NTRS)

Sobieski, S.; White, J. E.

1971-01-01

Correlation coefficients were computed to investigate the parameters for describing the spherical model of an eclipsing binary system. Regions in parameter hyperspace were identified where strong correlations exist and, by implication, the solution determinacy is low. The results are presented in tabular form for a large number of system configurations.

Determining the accuracy of maximum likelihood parameter estimates with colored residuals

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; Klein, Vladislav

1994-01-01

An important part of building high fidelity mathematical models based on measured data is calculating the accuracy associated with statistical estimates of the model parameters. Indeed, without some idea of the accuracy of parameter estimates, the estimates themselves have limited value. In this work, an expression based on theoretical analysis was developed to properly compute parameter accuracy measures for maximum likelihood estimates with colored residuals. This result is important because experience from the analysis of measured data reveals that the residuals from maximum likelihood estimation are almost always colored. The calculations involved can be appended to conventional maximum likelihood estimation algorithms. Simulated data runs were used to show that the parameter accuracy measures computed with this technique accurately reflect the quality of the parameter estimates from maximum likelihood estimation without the need for analysis of the output residuals in the frequency domain or heuristically determined multiplication factors. The result is general, although the application studied here is maximum likelihood estimation of aerodynamic model parameters from flight test data.

Evaluation of locally established reference intervals for hematology and biochemistry parameters in Western Kenya.

PubMed

Odhiambo, Collins; Oyaro, Boaz; Odipo, Richard; Otieno, Fredrick; Alemnji, George; Williamson, John; Zeh, Clement

2015-01-01

Important differences have been demonstrated in laboratory parameters from healthy persons in different geographical regions and populations, mostly driven by a combination of genetic, demographic, nutritional, and environmental factors. Despite this, European and North American derived laboratory reference intervals are used in African countries for patient management, clinical trial eligibility, and toxicity determination; which can result in misclassification of healthy persons as having laboratory abnormalities. An observational prospective cohort study known as the Kisumu Incidence Cohort Study (KICoS) was conducted to estimate the incidence of HIV seroconversion and identify determinants of successful recruitment and retention in preparation for an HIV vaccine/prevention trial among young adults and adolescents in western Kenya. Laboratory values generated from the KICoS were compared to published region-specific reference intervals and the 2004 NIH DAIDS toxicity tables used for the trial. About 1106 participants were screened for the KICoS between January 2007 and June 2010. Nine hundred and fifty-three participants aged 16 to 34 years, HIV-seronegative, clinically healthy, and non-pregnant were selected for this analysis. Median and 95% reference intervals were calculated for hematological and biochemistry parameters. When compared with both published region-specific reference values and the 2004 NIH DAIDS toxicity table, it was shown that the use of locally established reference intervals would have resulted in fewer participants classified as having abnormal hematological or biochemistry values compared to US derived reference intervals from DAIDS (10% classified as abnormal by local parameters vs. >40% by US DAIDS). Blood urea nitrogen was most often out of range if US based intervals were used: <10% abnormal by local intervals compared to >83% by US based reference intervals. Differences in reference intervals for hematological and biochemical

Comparison of two methods for calculating the P sorption capacity parameter in soils

USDA-ARS?s Scientific Manuscript database

Phosphorus (P) cycling in soils is an important process affecting P movement through the landscape. The P cycling routines in many computer models are based on the relationships developed for the EPIC model. An important parameter required for this model is the P sorption capacity parameter (PSP). I...

Inverse Modeling of Hydrologic Parameters Using Surface Flux and Runoff Observations in the Community Land Model

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

Sun, Yu; Hou, Zhangshuan; Huang, Maoyi

2013-12-10

This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Two inversion strategies, the deterministic least-square fitting and stochastic Markov-Chain Monte-Carlo (MCMC) - Bayesian inversion approaches, are evaluated by applying them to CLM4 at selected sites. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find thatmore » using model parameters calibrated by the least-square fitting provides little improvements in the model simulations but the sampling-based stochastic inversion approaches are consistent - as more information comes in, the predictive intervals of the calibrated parameters become narrower and the misfits between the calculated and observed responses decrease. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to the different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.« less

Structural identifiability analyses of candidate models for in vitro Pitavastatin hepatic uptake.

PubMed

Grandjean, Thomas R B; Chappell, Michael J; Yates, James W T; Evans, Neil D

2014-05-01

In this paper a review of the application of four different techniques (a version of the similarity transformation approach for autonomous uncontrolled systems, a non-differential input/output observable normal form approach, the characteristic set differential algebra and a recent algebraic input/output relationship approach) to determine the structural identifiability of certain in vitro nonlinear pharmacokinetic models is provided. The Organic Anion Transporting Polypeptide (OATP) substrate, Pitavastatin, is used as a probe on freshly isolated animal and human hepatocytes. Candidate pharmacokinetic non-linear compartmental models have been derived to characterise the uptake process of Pitavastatin. As a prerequisite to parameter estimation, structural identifiability analyses are performed to establish that all unknown parameters can be identified from the experimental observations available. Copyright © 2013. Published by Elsevier Ireland Ltd.

Identifying Typhoon Tracks based on Event Synchronization derived Spatially Embedded Climate Networks

NASA Astrophysics Data System (ADS)

Ozturk, Ugur; Marwan, Norbert; Kurths, Jürgen

2017-04-01

Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons. In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms' and typhoons' individual behaviors.

Structural and Practical Identifiability Analysis of Zika Epidemiological Models.

PubMed

Tuncer, Necibe; Marctheva, Maia; LaBarre, Brian; Payoute, Sabrina

2018-06-13

The Zika virus (ZIKV) epidemic has caused an ongoing threat to global health security and spurred new investigations of the virus. Use of epidemiological models for arbovirus diseases can be a powerful tool to assist in prevention and control of the emerging disease. In this article, we introduce six models of ZIKV, beginning with a general vector-borne model and gradually including different transmission routes of ZIKV. These epidemiological models use various combinations of disease transmission (vector and direct) and infectious classes (asymptomatic and pregnant), with addition to loss of immunity being included. The disease-induced death rate is omitted from the models. We test the structural and practical identifiability of the models to find whether unknown model parameters can uniquely be determined. The models were fit to obtain time-series data of cumulative incidences and pregnant infections from the Florida Department of Health Daily Zika Update Reports. The average relative estimation errors (AREs) were computed from the Monte Carlo simulations to further analyze the identifiability of the models. We show that direct transmission rates are not practically identifiable; however, fixed recovery rates improve identifiability overall. We found ARE is low for each model (only slightly higher for those that account for a pregnant class) and help to confirm a reproduction number greater than one at the start of the Florida epidemic. Basic reproduction number, [Formula: see text], is an epidemiologically important threshold value which gives the number of secondary cases generated by one infected individual in a totally susceptible population in duration of infectiousness. Elasticity of the reproduction numbers suggests that the mosquito-to-human ratio, mosquito life span and biting rate have the greatest potential for reducing the reproduction number of Zika, and therefore, corresponding control measures need to be focused on.

Reliability of diabetic patients' gait parameters in a challenging environment.

PubMed

Allet, L; Armand, S; de Bie, R A; Golay, A; Monnin, D; Aminian, K; de Bruin, E D

2008-11-01

Activities of daily life require us to move about in challenging environments and to walk on varied surfaces. Irregular terrain has been shown to influence gait parameters, especially in a population at risk for falling. A precise portable measurement system would permit objective gait analysis under such conditions. The aims of this study are to (a) investigate the reliability of gait parameters measured with the Physilog in diabetic patients walking on different surfaces (tar, grass, and stones); (b) identify the measurement error (precision); (c) identify the minimal clinical detectable change. 16 patients with Type 2 diabetes were measured twice within 8 days. After clinical examination patients walked, equipped with a Physilog, on the three aforementioned surfaces. ICC for each surface was excellent for within-visit analyses (>0.938). Inter-visit ICC's (0.753) were excellent except for the knee range parameter (>0.503). The coefficient of variation (CV) was lower than 5% for most of the parameters. Bland and Altman Plots, SEM and SDC showed precise values, distributed around zero for all surfaces. Good reliability of Physilog measurements on different surfaces suggests that Physilog could facilitate the study of diabetic patients' gait in conditions close to real-life situations. Gait parameters during complex locomotor activities (e.g. stair-climbing, curbs, slopes) have not yet been extensively investigated. Good reliability, small measurement error and values of minimal clinical detectable change recommend the utilization of Physilog for the evaluation of gait parameters in diabetic patients.

Delineating parameter unidentifiabilities in complex models

NASA Astrophysics Data System (ADS)

Raman, Dhruva V.; Anderson, James; Papachristodoulou, Antonis

2017-03-01

Scientists use mathematical modeling as a tool for understanding and predicting the properties of complex physical systems. In highly parametrized models there often exist relationships between parameters over which model predictions are identical, or nearly identical. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, as well as the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast time-scale subsystems, as well as the regimes in parameter space over which such approximations are valid. We base our algorithm on a quantification of regional parametric sensitivity that we call `multiscale sloppiness'. Traditionally, the link between parametric sensitivity and the conditioning of the parameter estimation problem is made locally, through the Fisher information matrix. This is valid in the regime of infinitesimal measurement uncertainty. We demonstrate the duality between multiscale sloppiness and the geometry of confidence regions surrounding parameter estimates made where measurement uncertainty is non-negligible. Further theoretical relationships are provided linking multiscale sloppiness to the likelihood-ratio test. From this, we show that a local sensitivity analysis (as typically done) is insufficient for determining the reliability of parameter estimation, even with simple (non)linear systems. Our algorithm can provide a tractable alternative. We finally apply our methods to a large-scale, benchmark systems biology model of necrosis factor (NF)-κ B , uncovering unidentifiabilities.

Global Sensitivity Analysis of OnGuard Models Identifies Key Hubs for Transport Interaction in Stomatal Dynamics1[CC-BY

PubMed Central

Vialet-Chabrand, Silvere; Griffiths, Howard

2017-01-01

The physical requirement for charge to balance across biological membranes means that the transmembrane transport of each ionic species is interrelated, and manipulating solute flux through any one transporter will affect other transporters at the same membrane, often with unforeseen consequences. The OnGuard systems modeling platform has helped to resolve the mechanics of stomatal movements, uncovering previously unexpected behaviors of stomata. To date, however, the manual approach to exploring model parameter space has captured little formal information about the emergent connections between parameters that define the most interesting properties of the system as a whole. Here, we introduce global sensitivity analysis to identify interacting parameters affecting a number of outputs commonly accessed in experiments in Arabidopsis (Arabidopsis thaliana). The analysis highlights synergies between transporters affecting the balance between Ca2+ sequestration and Ca2+ release pathways, notably those associated with internal Ca2+ stores and their turnover. Other, unexpected synergies appear, including with the plasma membrane anion channels and H+-ATPase and with the tonoplast TPK K+ channel. These emergent synergies, and the core hubs of interaction that they define, identify subsets of transporters associated with free cytosolic Ca2+ concentration that represent key targets to enhance plant performance in the future. They also highlight the importance of interactions between the voltage regulation of the plasma membrane and tonoplast in coordinating transport between the different cellular compartments. PMID:28432256

Parameter Estimation of a Spiking Silicon Neuron

PubMed Central

Russell, Alexander; Mazurek, Kevin; Mihalaş, Stefan; Niebur, Ernst; Etienne-Cummings, Ralph

2012-01-01

Spiking neuron models are used in a multitude of tasks ranging from understanding neural behavior at its most basic level to neuroprosthetics. Parameter estimation of a single neuron model, such that the model’s output matches that of a biological neuron is an extremely important task. Hand tuning of parameters to obtain such behaviors is a difficult and time consuming process. This is further complicated when the neuron is instantiated in silicon (an attractive medium in which to implement these models) as fabrication imperfections make the task of parameter configuration more complex. In this paper we show two methods to automate the configuration of a silicon (hardware) neuron’s parameters. First, we show how a Maximum Likelihood method can be applied to a leaky integrate and fire silicon neuron with spike induced currents to fit the neuron’s output to desired spike times. We then show how a distance based method which approximates the negative log likelihood of the lognormal distribution can also be used to tune the neuron’s parameters. We conclude that the distance based method is better suited for parameter configuration of silicon neurons due to its superior optimization speed. PMID:23852978

Local tsunamis and earthquake source parameters

USGS Publications Warehouse

Geist, Eric L.; Dmowska, Renata; Saltzman, Barry

1999-01-01

This chapter establishes the relationship among earthquake source parameters and the generation, propagation, and run-up of local tsunamis. In general terms, displacement of the seafloor during the earthquake rupture is modeled using the elastic dislocation theory for which the displacement field is dependent on the slip distribution, fault geometry, and the elastic response and properties of the medium. Specifically, nonlinear long-wave theory governs the propagation and run-up of tsunamis. A parametric study is devised to examine the relative importance of individual earthquake source parameters on local tsunamis, because the physics that describes tsunamis from generation through run-up is complex. Analysis of the source parameters of various tsunamigenic earthquakes have indicated that the details of the earthquake source, namely, nonuniform distribution of slip along the fault plane, have a significant effect on the local tsunami run-up. Numerical methods have been developed to address the realistic bathymetric and shoreline conditions. The accuracy of determining the run-up on shore is directly dependent on the source parameters of the earthquake, which provide the initial conditions used for the hydrodynamic models.

Correlations among the parameters of the spherical model for eclipsing binaries.

NASA Technical Reports Server (NTRS)

Sobieski, S.; White, J.

1973-01-01

Correlation coefficients have been computed to investigate the parameters used to describe the spherical model of an eclipsing binary system. Regions in parameter hyperspace have been identified where strong correlations exist and, by implication, the solution determinacy is low. The results are presented in tabular form for a large number of system configurations.

Examples of testing global identifiability of biological and biomedical models with the DAISY software.

PubMed

Saccomani, Maria Pia; Audoly, Stefania; Bellu, Giuseppina; D'Angiò, Leontina

2010-04-01

DAISY (Differential Algebra for Identifiability of SYstems) is a recently developed computer algebra software tool which can be used to automatically check global identifiability of (linear and) nonlinear dynamic models described by differential equations involving polynomial or rational functions. Global identifiability is a fundamental prerequisite for model identification which is important not only for biological or medical systems but also for many physical and engineering systems derived from first principles. Lack of identifiability implies that the parameter estimation techniques may not fail but any obtained numerical estimates will be meaningless. The software does not require understanding of the underlying mathematical principles and can be used by researchers in applied fields with a minimum of mathematical background. We illustrate the DAISY software by checking the a priori global identifiability of two benchmark nonlinear models taken from the literature. The analysis of these two examples includes comparison with other methods and demonstrates how identifiability analysis is simplified by this tool. Thus we illustrate the identifiability analysis of other two examples, by including discussion of some specific aspects related to the role of observability and knowledge of initial conditions in testing identifiability and to the computational complexity of the software. The main focus of this paper is not on the description of the mathematical background of the algorithm, which has been presented elsewhere, but on illustrating its use and on some of its more interesting features. DAISY is available on the web site http://www.dei.unipd.it/ approximately pia/. 2010 Elsevier Ltd. All rights reserved.

Volume-energy parameters for heat transfer to supercritical fluids

NASA Technical Reports Server (NTRS)

Kumakawa, A.; Niino, M.; Hendricks, R. C.; Giarratano, P. J.; Arp, V. D.

1986-01-01

Reduced Nusselt numbers of supercritical fluids from different sources were grouped by several volume-energy parameters. A modified bulk expansion parameter was introduced based on a comparative analysis of data scatter. Heat transfer experiments on liquefied methane were conducted under near-critical conditions in order to confirm the usefulness of the parameters. It was experimentally revealed that heat transfer characteristics of near-critical methane are similar to those of hydrogen. It was shown that the modified bulk expansion parameter and the Gibbs-energy parameter grouped the heat transfer data of hydrogen, oxygen and methane including the present data on near-critical methane. It was also indicated that the effects of surface roughness on heat transfer were very important in grouping the data of high Reynolds numbers.

Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

NASA Astrophysics Data System (ADS)

Wentworth, Mami Tonoe

Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification

Linking the salt transcriptome with physiological responses of a salt-resistant Populus species as a strategy to identify genes important for stress acclimation.

PubMed

Brinker, Monika; Brosché, Mikael; Vinocur, Basia; Abo-Ogiala, Atef; Fayyaz, Payam; Janz, Dennis; Ottow, Eric A; Cullmann, Andreas D; Saborowski, Joachim; Kangasjärvi, Jaakko; Altman, Arie; Polle, Andrea

2010-12-01

To investigate early salt acclimation mechanisms in a salt-tolerant poplar species (Populus euphratica), the kinetics of molecular, metabolic, and physiological changes during a 24-h salt exposure were measured. Three distinct phases of salt stress were identified by analyses of the osmotic pressure and the shoot water potential: dehydration, salt accumulation, and osmotic restoration associated with ionic stress. The duration and intensity of these phases differed between leaves and roots. Transcriptome analysis using P. euphratica-specific microarrays revealed clusters of coexpressed genes in these phases, with only 3% overlapping salt-responsive genes in leaves and roots. Acclimation of cellular metabolism to high salt concentrations involved remodeling of amino acid and protein biosynthesis and increased expression of molecular chaperones (dehydrins, osmotin). Leaves suffered initially from dehydration, which resulted in changes in transcript levels of mitochondrial and photosynthetic genes, indicating adjustment of energy metabolism. Initially, decreases in stress-related genes were found, whereas increases occurred only when leaves had restored the osmotic balance by salt accumulation. Comparative in silico analysis of the poplar stress regulon with Arabidopsis (Arabidopsis thaliana) orthologs was used as a strategy to reduce the number of candidate genes for functional analysis. Analysis of Arabidopsis knockout lines identified a lipocalin-like gene (AtTIL) and a gene encoding a protein with previously unknown functions (AtSIS) to play roles in salt tolerance. In conclusion, by dissecting the stress transcriptome of tolerant species, novel genes important for salt endurance can be identified.

Modal Parameter Identification and Numerical Simulation for Self-anchored Suspension Bridges Based on Ambient Vibration

NASA Astrophysics Data System (ADS)

Liu, Bing; Sun, Li Guo

2018-06-01

This paper chooses the Nanjing-Hangzhou high speed overbridge, a self-anchored suspension bridge, as the research target, trying to identify the dynamic characteristic parameters of the bridge by using the peak-picking method to analyze the velocity response data under ambient excitation collected by 7 vibration pickup sensors set on the bridge deck. The ABAQUS is used to set up a three-dimensional finite element model for the full bridge and amends the finite element model of the suspension bridge based on the identified modal parameter, and suspender force picked by the PDV100 laser vibrometer. The study shows that the modal parameter can well be identified by analyzing the bridge vibration velocity collected by 7 survey points. The identified modal parameter and measured suspender force can be used as the basis of the amendment of the finite element model of the suspension bridge. The amended model can truthfully reflect the structural physical features and it can also be the benchmark model for the long-term health monitoring and condition assessment of the bridge.

On the problem of modeling for parameter identification in distributed structures

NASA Technical Reports Server (NTRS)

Norris, Mark A.; Meirovitch, Leonard

1988-01-01

Structures are often characterized by parameters, such as mass and stiffness, that are spatially distributed. Parameter identification of distributed structures is subject to many of the difficulties involved in the modeling problem, and the choice of the model can greatly affect the results of the parameter identification process. Analogously to control spillover in the control of distributed-parameter systems, identification spillover is shown to exist as well and its effect is to degrade the parameter estimates. Moreover, as in modeling by the Rayleigh-Ritz method, it is shown that, for a Rayleigh-Ritz type identification algorithm, an inclusion principle exists in the identification of distributed-parameter systems as well, so that the identified natural frequencies approach the actual natural frequencies monotonically from above.

Dengue burden in India: recent trends and importance of climatic parameters.

PubMed

Mutheneni, Srinivasa Rao; Morse, Andrew P; Caminade, Cyril; Upadhyayula, Suryanaryana Murty

2017-08-09

For the past ten years, the number of dengue cases has gradually increased in India. Dengue is driven by complex interactions among host, vector and virus that are influenced by climatic factors. In the present study, we focused on the extrinsic incubation period (EIP) and its variability in different climatic zones of India. The EIP was calculated by using daily and monthly mean temperatures for the states of Punjab, Haryana, Gujarat, Rajasthan and Kerala. Among the studied states, a faster/low EIP in Kerala (8-15 days at 30.8 and 23.4 °C) and a generally slower/high EIP in Punjab (5.6-96.5 days at 35 and 0 °C) were simulated with daily temperatures. EIPs were calculated for different seasons, and Kerala showed the lowest EIP during the monsoon period. In addition, a significant association between dengue cases and precipitation was also observed. The results suggest that temperature is important in virus development in different climatic regions and may be useful in understanding spatio-temporal variations in dengue risk. Climate-based disease forecasting models in India should be refined and tailored for different climatic zones, instead of use of a standard model.

Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients.

PubMed

Chen, Jinying; Yu, Hong

2017-04-01

Allowing patients to access their own electronic health record (EHR) notes through online patient portals has the potential to improve patient-centered care. However, EHR notes contain abundant medical jargon that can be difficult for patients to comprehend. One way to help patients is to reduce information overload and help them focus on medical terms that matter most to them. Targeted education can then be developed to improve patient EHR comprehension and the quality of care. The aim of this work was to develop FIT (Finding Important Terms for patients), an unsupervised natural language processing (NLP) system that ranks medical terms in EHR notes based on their importance to patients. We built FIT on a new unsupervised ensemble ranking model derived from the biased random walk algorithm to combine heterogeneous information resources for ranking candidate terms from each EHR note. Specifically, FIT integrates four single views (rankers) for term importance: patient use of medical concepts, document-level term salience, word co-occurrence based term relatedness, and topic coherence. It also incorporates partial information of term importance as conveyed by terms' unfamiliarity levels and semantic types. We evaluated FIT on 90 expert-annotated EHR notes and used the four single-view rankers as baselines. In addition, we implemented three benchmark unsupervised ensemble ranking methods as strong baselines. FIT achieved 0.885 AUC-ROC for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FIT for identifying important terms from EHR notes was 0.813 AUC-ROC. Both performance scores significantly exceeded the corresponding scores from the four single rankers (P<0.001). FIT also outperformed the three ensemble rankers for most metrics. Its performance is relatively insensitive to its parameter. FIT can automatically identify EHR terms important to patients. It may help develop future interventions

Electronic surveillance and using administrative data to identify healthcare associated infections.

PubMed

Gastmeier, Petra; Behnke, Michael

2016-08-01

Traditional surveillance of healthcare associated infections (HCAI) is time consuming and error-prone. We have analysed literature of the past year to look at new developments in this field. It is divided into three parts: new algorithms for electronic surveillance, the use of administrative data for surveillance of HCAI, and the definition of new endpoints of surveillance, in accordance with an automatic surveillance approach. Most studies investigating electronic surveillance of HCAI have concentrated on bloodstream infection or surgical site infection. However, the lack of important parameters in hospital databases can lead to misleading results. The accuracy of administrative coding data was poor at identifying HCAI. New endpoints should be defined for automatic detection, with the most crucial step being to win clinicians' acceptance. Electronic surveillance with conventional endpoints is a successful method when hospital information systems implemented key changes and enhancements. One requirement is the access to systems for hospital administration and clinical databases.Although the primary source of data for HCAI surveillance is not administrative coding data, these are important components of a hospital-wide programme of automated surveillance. The implementation of new endpoints for surveillance is an approach which needs to be discussed further.

A Computational Framework for Identifiability and Ill-Conditioning Analysis of Lithium-Ion Battery Models

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

López C, Diana C.; Wozny, Günter; Flores-Tlacuahuac, Antonio

2016-03-23

The lack of informative experimental data and the complexity of first-principles battery models make the recovery of kinetic, transport, and thermodynamic parameters complicated. We present a computational framework that combines sensitivity, singular value, and Monte Carlo analysis to explore how different sources of experimental data affect parameter structural ill conditioning and identifiability. Our study is conducted on a modified version of the Doyle-Fuller-Newman model. We demonstrate that the use of voltage discharge curves only enables the identification of a small parameter subset, regardless of the number of experiments considered. Furthermore, we show that the inclusion of a single electrolyte concentrationmore » measurement significantly aids identifiability and mitigates ill-conditioning.« less

Understanding which parameters control shallow ascent of silicic effusive magma

NASA Astrophysics Data System (ADS)

Thomas, Mark E.; Neuberg, Jurgen W.

2014-11-01

The estimation of the magma ascent rate is key to predicting volcanic activity and relies on the understanding of how strongly the ascent rate is controlled by different magmatic parameters. Linking potential changes of such parameters to monitoring data is an essential step to be able to use these data as a predictive tool. We present the results of a suite of conduit flow models Soufrière that assess the influence of individual model parameters such as the magmatic water content, temperature or bulk magma composition on the magma flow in the conduit during an extrusive dome eruption. By systematically varying these parameters we assess their relative importance to changes in ascent rate. We show that variability in the rate of low frequency seismicity, assumed to correlate directly with the rate of magma movement, can be used as an indicator for changes in ascent rate and, therefore, eruptive activity. The results indicate that conduit diameter and excess pressure in the magma chamber are amongst the dominant controlling variables, but the single most important parameter is the volatile content (assumed as only water). Modeling this parameter in the range of reported values causes changes in the calculated ascent velocities of up to 800%.

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

PubMed

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.

Enhancing Important Fluctuations: Rare Events and Metadynamics from a Conceptual Viewpoint

NASA Astrophysics Data System (ADS)

Valsson, Omar; Tiwary, Pratyush; Parrinello, Michele

2016-05-01

Atomistic simulations play a central role in many fields of science. However, their usefulness is often limited by the fact that many systems are characterized by several metastable states separated by high barriers, leading to kinetic bottlenecks. Transitions between metastable states are thus rare events that occur on significantly longer timescales than one can simulate in practice. Numerous enhanced sampling methods have been introduced to alleviate this timescale problem, including methods based on identifying a few crucial order parameters or collective variables and enhancing the sampling of these variables. Metadynamics is one such method that has proven successful in a great variety of fields. Here we review the conceptual and theoretical foundations of metadynamics. As demonstrated, metadynamics is not just a practical tool but can also be considered an important development in the theory of statistical mechanics.

Control of complex dynamics and chaos in distributed parameter systems

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

Chakravarti, S.; Marek, M.; Ray, W.H.

This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in themore » complex quasi-periodic or chaotic spatiotemporal patterns.« less

Exploring the potential energy landscape over a large parameter-space

NASA Astrophysics Data System (ADS)

He, Yang-Hui; Mehta, Dhagash; Niemerg, Matthew; Rummel, Markus; Valeanu, Alexandru

2013-07-01

Solving large polynomial systems with coefficient parameters are ubiquitous and constitute an important class of problems. We demonstrate the computational power of two methods — a symbolic one called the Comprehensive Gröbner basis and a numerical one called coefficient-parameter polynomial continuation — applied to studying both potential energy landscapes and a variety of questions arising from geometry and phenomenology. Particular attention is paid to an example in flux compactification where important physical quantities such as the gravitino and moduli masses and the string coupling can be efficiently extracted.

Testing Saliency Parameters for Automatic Target Recognition

NASA Technical Reports Server (NTRS)