The distribution of cigarette prices under different tax structures: findings from the International Tobacco Control Policy Evaluation (ITC) Project.

PubMed

Shang, Ce; Chaloupka, Frank J; Zahra, Nahleen; Fong, Geoffrey T

2014-03-01

The distribution of cigarette prices has rarely been studied and compared under different tax structures. Descriptive evidence on price distributions by countries can shed light on opportunities for tax avoidance and brand switching under different tobacco tax structures, which could impact the effectiveness of increased taxation in reducing smoking. This paper aims to describe the distribution of cigarette prices by countries and to compare these distributions based on the tobacco tax structure in these countries. We employed data for 16 countries taken from the International Tobacco Control Policy Evaluation Project to construct survey-derived cigarette prices for each country. Self-reported prices were weighted by cigarette consumption and described using a comprehensive set of statistics. We then compared these statistics for cigarette prices under different tax structures. In particular, countries of similar income levels and countries that impose similar total excise taxes using different tax structures were paired and compared in mean and variance using a two-sample comparison test. Our investigation illustrates that, compared with specific uniform taxation, other tax structures, such as ad valorem uniform taxation, mixed (a tax system using ad valorem and specific taxes) uniform taxation, and tiered tax structures of specific, ad valorem and mixed taxation tend to have price distributions with greater variability. Countries that rely heavily on ad valorem and tiered taxes also tend to have greater price variability around the median. Among mixed taxation systems, countries that rely more heavily on the ad valorem component tend to have greater price variability than countries that rely more heavily on the specific component. In countries with tiered tax systems, cigarette prices are skewed more towards lower prices than are prices under uniform tax systems. The analyses presented here demonstrate that more opportunities exist for tax avoidance and brand switching when the tax structure departs from a uniform specific tax.

Measurement Model Specification Error in LISREL Structural Equation Models.

ERIC Educational Resources Information Center

Baldwin, Beatrice; Lomax, Richard

This LISREL study examines the robustness of the maximum likelihood estimates under varying degrees of measurement model misspecification. A true model containing five latent variables (two endogenous and three exogenous) and two indicator variables per latent variable was used. Measurement model misspecification considered included errors of…

Displacement Based Multilevel Structural Optimization

NASA Technical Reports Server (NTRS)

Sobieszezanski-Sobieski, J.; Striz, A. G.

1996-01-01

In the complex environment of true multidisciplinary design optimization (MDO), efficiency is one of the most desirable attributes of any approach. In the present research, a new and highly efficient methodology for the MDO subset of structural optimization is proposed and detailed, i.e., for the weight minimization of a given structure under size, strength, and displacement constraints. Specifically, finite element based multilevel optimization of structures is performed. In the system level optimization, the design variables are the coefficients of assumed polynomially based global displacement functions, and the load unbalance resulting from the solution of the global stiffness equations is minimized. In the subsystems level optimizations, the weight of each element is minimized under the action of stress constraints, with the cross sectional dimensions as design variables. The approach is expected to prove very efficient since the design task is broken down into a large number of small and efficient subtasks, each with a small number of variables, which are amenable to parallel computing.

The controlled growth method - A tool for structural optimization

NASA Technical Reports Server (NTRS)

Hajela, P.; Sobieszczanski-Sobieski, J.

1981-01-01

An adaptive design variable linking scheme in a NLP based optimization algorithm is proposed and evaluated for feasibility of application. The present scheme, based on an intuitive effectiveness measure for each variable, differs from existing methodology in that a single dominant variable controls the growth of all others in a prescribed optimization cycle. The proposed method is implemented for truss assemblies and a wing box structure for stress, displacement and frequency constraints. Substantial reduction in computational time, even more so for structures under multiple load conditions, coupled with a minimal accompanying loss in accuracy, vindicates the algorithm.

A new approach to fluid-structure interaction within graphics hardware accelerated smooth particle hydrodynamics considering heterogeneous particle size distribution

NASA Astrophysics Data System (ADS)

Eghtesad, Adnan; Knezevic, Marko

2018-07-01

A corrective smooth particle method (CSPM) within smooth particle hydrodynamics (SPH) is used to study the deformation of an aircraft structure under high-velocity water-ditching impact load. The CSPM-SPH method features a new approach for the prediction of two-way fluid-structure interaction coupling. Results indicate that the implementation is well suited for modeling the deformation of structures under high-velocity impact into water as evident from the predicted stress and strain localizations in the aircraft structure as well as the integrity of the impacted interfaces, which show no artificial particle penetrations. To reduce the simulation time, a heterogeneous particle size distribution over a complex three-dimensional geometry is used. The variable particle size is achieved from a finite element mesh with variable element size and, as a result, variable nodal (i.e., SPH particle) spacing. To further accelerate the simulations, the SPH code is ported to a graphics processing unit using the OpenACC standard. The implementation and simulation results are described and discussed in this paper.

A new approach to fluid-structure interaction within graphics hardware accelerated smooth particle hydrodynamics considering heterogeneous particle size distribution

NASA Astrophysics Data System (ADS)

Eghtesad, Adnan; Knezevic, Marko

2017-12-01

A corrective smooth particle method (CSPM) within smooth particle hydrodynamics (SPH) is used to study the deformation of an aircraft structure under high-velocity water-ditching impact load. The CSPM-SPH method features a new approach for the prediction of two-way fluid-structure interaction coupling. Results indicate that the implementation is well suited for modeling the deformation of structures under high-velocity impact into water as evident from the predicted stress and strain localizations in the aircraft structure as well as the integrity of the impacted interfaces, which show no artificial particle penetrations. To reduce the simulation time, a heterogeneous particle size distribution over a complex three-dimensional geometry is used. The variable particle size is achieved from a finite element mesh with variable element size and, as a result, variable nodal (i.e., SPH particle) spacing. To further accelerate the simulations, the SPH code is ported to a graphics processing unit using the OpenACC standard. The implementation and simulation results are described and discussed in this paper.

Using directed information for influence discovery in interconnected dynamical systems

NASA Astrophysics Data System (ADS)

Rao, Arvind; Hero, Alfred O.; States, David J.; Engel, James Douglas

2008-08-01

Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an information-theoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological datasets (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.

The influence of construction measurement and structure storey on seismic performance of masonry structure

NASA Astrophysics Data System (ADS)

Sun, Baitao; Zhao, Hexian; Yan, Peilei

2017-08-01

The damage of masonry structures in earthquakes is generally more severe than other structures. Through the analysis of two typical earthquake damage buildings in the Wenchuan earthquake in Xuankou middle school, we found that the number of storeys and the construction measures had great influence on the seismic performance of masonry structures. This paper takes a teachers’ dormitory in Xuankou middle school as an example, selected the structure arrangement and storey number as two independent variables to design working conditions. Finally we researched on the seismic performance difference of masonry structure under two variables by finite element analysis method.

Fish Assemblage Structure Under Variable Environmental Conditions in the Ouachita Mountains

Treesearch

Christopher M. Taylor; Lance R. Williams; Riccardo A. Fiorillo; R. Brent Thomas; Melvin L. Warren

2004-01-01

Abstract - Spatial and temporal variability of fish assemblages in Ouachita Mountain streams, Arkansas, were examined for association with stream size and flow variability. Fishes and habitat were sampled quarterly for four years at 12 sites (144 samples) in the Ouachita Mountains Ecosystem Management Research Project, Phase III watersheds. Detrended...

Alternative bi-Hamiltonian structures for WDVV equations of associativity

NASA Astrophysics Data System (ADS)

Kalayci, J.; Nutku, Y.

1998-01-01

The WDVV equations of associativity in two-dimensional topological field theory are completely integrable third-order Monge-Ampère equations which admit bi-Hamiltonian structure. The time variable plays a distinguished role in the discussion of Hamiltonian structure, whereas in the theory of WDVV equations none of the independent variables merits such a distinction. WDVV equations admit very different alternative Hamiltonian structures under different possible choices of the time variable, but all these various Hamiltonian formulations can be brought together in the framework of the covariant theory of symplectic structure. They can be identified as different components of the covariant Witten-Zuckerman symplectic 2-form current density where a variational formulation of the WDVV equation that leads to the Hamiltonian operator through the Dirac bracket is available.

The Influence of Individual Variability on Zooplankton Population Dynamics under Different Environmental Conditions

NASA Astrophysics Data System (ADS)

Bi, R.; Liu, H.

2016-02-01

Understanding how biological components respond to environmental changes could be insightful to predict ecosystem trajectories under different climate scenarios. Zooplankton are key components of marine ecosystems and changes in their dynamics could have major impact on ecosystem structure. We developed an individual-based model of a common coastal calanoid copepod Acartia tonsa to examine how environmental factors affect zooplankton population dynamics and explore the role of individual variability in sustaining population under various environmental conditions consisting of temperature, food concentration and salinity. Total abundance, egg production and proportion of survival were used to measure population success. Results suggested population benefits from high level of individual variability under extreme environmental conditions including unfavorable temperature, salinity, as well as low food concentration, and selection on fast-growers becomes stronger with increasing individual variability and increasing environmental stress. Multiple regression analysis showed that temperature, food concentration, salinity and individual variability have significant effects on survival of A. tonsa population. These results suggest that environmental factors have great influence on zooplankton population, and individual variability has important implications for population survivability under unfavorable conditions. Given that marine ecosystems are at risk from drastic environmental changes, understanding how individual variability sustains populations could increase our capability to predict population dynamics in a changing environment.

Structure and chemistry of the sorghum grain

USDA-ARS?s Scientific Manuscript database

Sorghum is grown around the world and often under harsh and variable environmental conditions. Combined with the high degree of genetic diversity present in sorghum, this can result in substantial variability in grain composition and grain quality. While similar to other cereal grains such as maize ...

Demonstration of the Application of Composite Load Spectra (CLS) and Probabilistic Structural Analysis (PSAM) Codes to SSME Heat Exchanger Turnaround Vane

NASA Technical Reports Server (NTRS)

Rajagopal, Kadambi R.; DebChaudhury, Amitabha; Orient, George

2000-01-01

This report describes a probabilistic structural analysis performed to determine the probabilistic structural response under fluctuating random pressure loads for the Space Shuttle Main Engine (SSME) turnaround vane. It uses a newly developed frequency and distance dependent correlation model that has features to model the decay phenomena along the flow and across the flow with the capability to introduce a phase delay. The analytical results are compared using two computer codes SAFER (Spectral Analysis of Finite Element Responses) and NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) and with experimentally observed strain gage data. The computer code NESSUS with an interface to a sub set of Composite Load Spectra (CLS) code is used for the probabilistic analysis. A Fatigue code was used to calculate fatigue damage due to the random pressure excitation. The random variables modeled include engine system primitive variables that influence the operating conditions, convection velocity coefficient, stress concentration factor, structural damping, and thickness of the inner and outer vanes. The need for an appropriate correlation model in addition to magnitude of the PSD is emphasized. The study demonstrates that correlation characteristics even under random pressure loads are capable of causing resonance like effects for some modes. The study identifies the important variables that contribute to structural alternate stress response and drive the fatigue damage for the new design. Since the alternate stress for the new redesign is less than the endurance limit for the material, the damage due high cycle fatigue is negligible.

Describing the Elephant: Structure and Function in Multivariate Data.

ERIC Educational Resources Information Center

McDonald, Roderick P.

1986-01-01

There is a unity underlying the diversity of models for the analysis of multivariate data. Essentially, they constitute a family of models, most generally nonlinear, for structural/functional relations between variables drawn from a behavior domain. (Author)

Precision Spectral Variability of L Dwarfs from the Ground

NASA Astrophysics Data System (ADS)

Burgasser, Adam J.; Schlawin, Everett; Teske, Johanna K.; Karalidi, Theodora; Gizis, John

2017-01-01

L dwarf photospheres (1500 K < T < 2500 K) contain mineral and metal condensates, which appear to organize into cloud structures as inferred from observed periodic photometric variations with amplitudes of <1%-30%. Studying the vertical structure, composition, and long-term evolution of these clouds necessitates precision spectroscopic monitoring, until recently limited to space-based facilities. Building on techniques developed for ground-based exoplanet transit spectroscopy, we present a method for precision spectral monitoring of L dwarfs with nearby visual companions. Using IRTF/SpeX, we demonstrate <0.5% spectral variability precision across the 0.9-2.4 micron band, and present results for two known L5 dwarf variables, J0835-0819 and J1821+1414, both of which show evidence of 3D cloud structure similar to that seen in space-based observations. We describe a survey of 30 systems which would sample the full L dwarf sequence and allow characterization of temperature, surface gravity, metallicity, rotation period and orientation effects on cloud structure, composition and evolution.This research is supported by funding from the National Science Foundation under award No. AST-1517177, and the National Aeronautics and Space Administration under Grant No. NNX15AI75G.

Assessment of variability in the hydrological cycle of the Loess Plateau, China: examining dependence structures of hydrological processes

NASA Astrophysics Data System (ADS)

Guo, A.; Wang, Y.

2017-12-01

Investigating variability in dependence structures of hydrological processes is of critical importance for developing an understanding of mechanisms of hydrological cycles in changing environments. In focusing on this topic, present work involves the following: (1) identifying and eliminating serial correlation and conditional heteroscedasticity in monthly streamflow (Q), precipitation (P) and potential evapotranspiration (PE) series using the ARMA-GARCH model (ARMA: autoregressive moving average; GARCH: generalized autoregressive conditional heteroscedasticity); (2) describing dependence structures of hydrological processes using partial copula coupled with the ARMA-GARCH model and identifying their variability via copula-based likelihood-ratio test method; and (3) determining conditional probability of annual Q under different climate scenarios on account of above results. This framework enables us to depict hydrological variables in the presence of conditional heteroscedasticity and to examine dependence structures of hydrological processes while excluding the influence of covariates by using partial copula-based ARMA-GARCH model. Eight major catchments across the Loess Plateau (LP) are used as study regions. Results indicate that (1) The occurrence of change points in dependence structures of Q and P (PE) varies across the LP. Change points of P-PE dependence structures in all regions almost fully correspond to the initiation of global warming, i.e., the early 1980s. (3) Conditional probabilities of annual Q under various P and PE scenarios are estimated from the 3-dimensional joint distribution of (Q, P and PE) based on the above change points. These findings shed light on mechanisms of the hydrological cycle and can guide water supply planning and management, particularly in changing environments.

Establishing Evidence for Internal Structure Using Exploratory Factor Analysis

ERIC Educational Resources Information Center

Watson, Joshua C.

2017-01-01

Exploratory factor analysis (EFA) is a data reduction technique used to condense data into smaller sets of summary variables by identifying underlying factors potentially accounting for patterns of collinearity among said variables. Using an illustrative example, the 5 general steps of EFA are described with best practices for decision making…

Estimating Latent Variable Interactions with Nonnormal Observed Data: A Comparison of Four Approaches

ERIC Educational Resources Information Center

Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S.

2012-01-01

A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…

Introduction to the special section on mixture modeling in personality assessment.

PubMed

Wright, Aidan G C; Hallquist, Michael N

2014-01-01

Latent variable models offer a conceptual and statistical framework for evaluating the underlying structure of psychological constructs, including personality and psychopathology. Complex structures that combine or compare categorical and dimensional latent variables can be accommodated using mixture modeling approaches, which provide a powerful framework for testing nuanced theories about psychological structure. This special series includes introductory primers on cross-sectional and longitudinal mixture modeling, in addition to empirical examples applying these techniques to real-world data collected in clinical settings. This group of articles is designed to introduce personality assessment scientists and practitioners to a general latent variable framework that we hope will stimulate new research and application of mixture models to the assessment of personality and its pathology.

Effects of a large wildfire on vegetation structure in a variable fire mosaic.

PubMed

Foster, C N; Barton, P S; Robinson, N M; MacGregor, C I; Lindenmayer, D B

2017-12-01

Management guidelines for many fire-prone ecosystems highlight the importance of maintaining a variable mosaic of fire histories for biodiversity conservation. Managers are encouraged to aim for fire mosaics that are temporally and spatially dynamic, include all successional states of vegetation, and also include variation in the underlying "invisible mosaic" of past fire frequencies, severities, and fire return intervals. However, establishing and maintaining variable mosaics in contemporary landscapes is subject to many challenges, one of which is deciding how the fire mosaic should be managed following the occurrence of large, unplanned wildfires. A key consideration for this decision is the extent to which the effects of previous fire history on vegetation and habitats persist after major wildfires, but this topic has rarely been investigated empirically. In this study, we tested to what extent a large wildfire interacted with previous fire history to affect the structure of forest, woodland, and heath vegetation in Booderee National Park in southeastern Australia. In 2003, a summer wildfire burned 49.5% of the park, increasing the extent of recently burned vegetation (<10 yr post-fire) to more than 72% of the park area. We tracked the recovery of vegetation structure for nine years following the wildfire and found that the strength and persistence of fire effects differed substantially between vegetation types. Vegetation structure was modified by wildfire in forest, woodland, and heath vegetation, but among-site variability in vegetation structure was reduced only by severe fire in woodland vegetation. There also were persistent legacy effects of the previous fire regime on some attributes of vegetation structure including forest ground and understorey cover, and woodland midstorey and overstorey cover. For example, woodland midstorey cover was greater on sites with higher fire frequency, irrespective of the severity of the 2003 wildfire. Our results show that even after a large, severe wildfire, underlying fire histories can contribute substantially to variation in vegetation structure. This highlights the importance of ensuring that efforts to reinstate variation in vegetation fire age after large wildfires do not inadvertently reduce variation in vegetation structure generated by the underlying invisible mosaic. © 2017 by the Ecological Society of America.

A network-based approach for semi-quantitative knowledge mining and its application to yield variability

NASA Astrophysics Data System (ADS)

Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

2016-12-01

Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

Static Structural Analysis of a Variable Span Morphing Wing for Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Bashir, M.; Rajendran, P.

2018-05-01

While the primary reason to develop an adaptive wing is the aerodynamic benefits, the primary hindrance is the structural and vibrational considerations due to the unsteady nature of the airflow during the flight. Hence this study forms an important part of the morphable wing technology. In this paper, the design of a moderate aspect ratio variable span wing will be performed. The morphing wing is modeled structurally to observe the effect of spanwise load distribution on the wing structure. For the structural design and analysis of the unmanned aerial vehicle (UAV) under this study, commercial software Solidworks and Ansys/Static Structural/Modal are used. The static structural analyses of the wing are performed under different load conditions. The results of these analyses show that the designed structure is safe within the flight envelope. It is observed that the wing-root bending moment increases drastically due to an increase in the wingspan. Thus, the bending moment along the wingspan of the morphing wing is much larger than that of the conventional wing which results in an increase in the deflection of the free-end. The maximum stress for the un-extended wing configuration increases for the extended wing configuration.

Broadband continuous-variable entanglement source using a chirped poling nonlinear crystal

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

Zhao, J. S.; Sun, L.; Yu, X. Q.

2010-01-15

Aperiodically poled nonlinear crystal can be used as a broadband continuous-variable entanglement source and has strong stability under perturbations. We study the conversion dynamics of the sum-frequency generation and the quantum correlation of the two pump fields in a chirped-structure nonlinear crystal using the quantum stochastic method. The results show that there exists a frequency window for the pumps where two optical fields can perform efficient upconversion. The two pump fields are demonstrated to be entangled in the window and the chirped-structure crystal can be used as a continuous-variable entanglement source with a broad response bandwidth.

Stability of Nonlinear Principal Components Analysis: An Empirical Study Using the Balanced Bootstrap

ERIC Educational Resources Information Center

Linting, Marielle; Meulman, Jacqueline J.; Groenen, Patrick J. F.; van der Kooij, Anita J.

2007-01-01

Principal components analysis (PCA) is used to explore the structure of data sets containing linearly related numeric variables. Alternatively, nonlinear PCA can handle possibly nonlinearly related numeric as well as nonnumeric variables. For linear PCA, the stability of its solution can be established under the assumption of multivariate…

The underlying processes of a soil mite metacommunity on a small scale.

PubMed

Dong, Chengxu; Gao, Meixiang; Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran's eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale.

The underlying processes of a soil mite metacommunity on a small scale

PubMed Central

Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran’s eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale. PMID:28481906

Exploring the potential of a structural alphabet-based tool for mining multiple target conformations and target flexibility insight

PubMed Central

Chéron, Jean-Baptiste; Triki, Dhoha; Senac, Caroline; Flatters, Delphine; Camproux, Anne-Claude

2017-01-01

Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility. This analysis is essential to improve the understanding of various mechanisms associated with protein target function and flexibility. In this study, we explored structural variability of three biological targets by analyzing different MTC sets associated with these targets. To facilitate the study of these MTC sets, we have developed an efficient tool, SA-conf, dedicated to capturing and linking the amino acid and local structure variability and analyzing the target structural variability space. The advantage of SA-conf is that it could be applied to divers sets composed of MTCs available in the PDB obtained using NMR and crystallography or homology models. This tool could also be applied to analyze MTC sets obtained by dynamics approaches. Our results showed that SA-conf tool is effective to quantify the structural variability of a MTC set and to localize the structural variable positions and regions of the target. By selecting adapted MTC subsets and comparing their variability detected by SA-conf, we highlighted different sources of target flexibility such as induced by binding partner, by mutation and intrinsic flexibility. Our results support the interest to mine available structures associated with a target using to offer valuable insight into target flexibility and interaction mechanisms. The SA-conf executable script, with a set of pre-compiled binaries are available at http://www.mti.univ-paris-diderot.fr/recherche/plateformes/logiciels. PMID:28817602

Exploring the potential of a structural alphabet-based tool for mining multiple target conformations and target flexibility insight.

PubMed

Regad, Leslie; Chéron, Jean-Baptiste; Triki, Dhoha; Senac, Caroline; Flatters, Delphine; Camproux, Anne-Claude

2017-01-01

Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility. This analysis is essential to improve the understanding of various mechanisms associated with protein target function and flexibility. In this study, we explored structural variability of three biological targets by analyzing different MTC sets associated with these targets. To facilitate the study of these MTC sets, we have developed an efficient tool, SA-conf, dedicated to capturing and linking the amino acid and local structure variability and analyzing the target structural variability space. The advantage of SA-conf is that it could be applied to divers sets composed of MTCs available in the PDB obtained using NMR and crystallography or homology models. This tool could also be applied to analyze MTC sets obtained by dynamics approaches. Our results showed that SA-conf tool is effective to quantify the structural variability of a MTC set and to localize the structural variable positions and regions of the target. By selecting adapted MTC subsets and comparing their variability detected by SA-conf, we highlighted different sources of target flexibility such as induced by binding partner, by mutation and intrinsic flexibility. Our results support the interest to mine available structures associated with a target using to offer valuable insight into target flexibility and interaction mechanisms. The SA-conf executable script, with a set of pre-compiled binaries are available at http://www.mti.univ-paris-diderot.fr/recherche/plateformes/logiciels.

Impact of Hydrologic Variability on Ecosystem Dynamics and the Sustainable Use of Soil and Water Resources

NASA Astrophysics Data System (ADS)

Porporato, A. M.

2013-05-01

We discuss the key processes by which hydrologic variability affects the probabilistic structure of soil moisture dynamics in water-controlled ecosystems. These in turn impact biogeochemical cycling and ecosystem structure through plant productivity and biodiversity as well as nitrogen availability and soil conditions. Once the long-term probabilistic structure of these processes is quantified, the results become useful to understand the impact of climatic changes and human activities on ecosystem services, and can be used to find optimal strategies of water and soil resources management under unpredictable hydro-climatic fluctuations. Particular applications regard soil salinization, phytoremediation and optimal stochastic irrigation.

Estimating Causal Effects with Ancestral Graph Markov Models

PubMed Central

Malinsky, Daniel; Spirtes, Peter

2017-01-01

We present an algorithm for estimating bounds on causal effects from observational data which combines graphical model search with simple linear regression. We assume that the underlying system can be represented by a linear structural equation model with no feedback, and we allow for the possibility of latent variables. Under assumptions standard in the causal search literature, we use conditional independence constraints to search for an equivalence class of ancestral graphs. Then, for each model in the equivalence class, we perform the appropriate regression (using causal structure information to determine which covariates to include in the regression) to estimate a set of possible causal effects. Our approach is based on the “IDA” procedure of Maathuis et al. (2009), which assumes that all relevant variables have been measured (i.e., no unmeasured confounders). We generalize their work by relaxing this assumption, which is often violated in applied contexts. We validate the performance of our algorithm on simulated data and demonstrate improved precision over IDA when latent variables are present. PMID:28217244

Metacommunity ecology meets biogeography: effects of geographical region, spatial dynamics and environmental filtering on community structure in aquatic organisms.

PubMed

Heino, Jani; Soininen, Janne; Alahuhta, Janne; Lappalainen, Jyrki; Virtanen, Risto

2017-01-01

Metacommunity patterns and underlying processes in aquatic organisms have typically been studied within a drainage basin. We examined variation in the composition of six freshwater organismal groups across various drainage basins in Finland. We first modelled spatial structures within each drainage basin using Moran eigenvector maps. Second, we partitioned variation in community structure among three groups of predictors using constrained ordination: (1) local environmental variables, (2) spatial variables, and (3) dummy variable drainage basin identity. Third, we examined turnover and nestedness components of multiple-site beta diversity, and tested the best fit patterns of our datasets using the "elements of metacommunity structure" analysis. Our results showed that basin identity and local environmental variables were significant predictors of community structure, whereas within-basin spatial effects were typically negligible. In half of the organismal groups (diatoms, bryophytes, zooplankton), basin identity was a slightly better predictor of community structure than local environmental variables, whereas the opposite was true for the remaining three organismal groups (insects, macrophytes, fish). Both pure basin and local environmental fractions were, however, significant after accounting for the effects of the other predictor variable sets. All organismal groups exhibited high levels of beta diversity, which was mostly attributable to the turnover component. Our results showed consistent Clementsian-type metacommunity structures, suggesting that subgroups of species responded similarly to environmental factors or drainage basin limits. We conclude that aquatic communities across large scales are mostly determined by environmental and basin effects, which leads to high beta diversity and prevalence of Clementsian community types.

Performance limitations of joint variable-feedback controllers due to manipulator structural flexibility

NASA Technical Reports Server (NTRS)

Cetinkunt, Sabri; Book, Wayne J.

1990-01-01

The performance limitations of manipulators under joint variable-feedback control are studied as a function of the mechanical flexibility inherent in the manipulator structure. A finite-dimensional time-domain dynamic model of a two-link two-joint planar manipulator is used in the study. Emphasis is placed on determining the limitations of control algorithms that use only joint variable-feedback information in calculations of control decisions, since most motion control systems in practice are of this kind. Both fine and gross motion cases are studied. Results for fine motion agree well with previously reported results in the literature and are also helpful in explaining the performance limitations in fast gross motions.

Identifying the control structure of multijoint coordination during pistol shooting.

PubMed

Scholz, J P; Schöner, G; Latash, M L

2000-12-01

The question of degrees of freedom in the control of multijoint movement is posed as the problem of discovering how the motor control system constrains the many possible combinations of joint postures to stabilize task-dependent essential variables. Success at a task can be achieved, in principle, by always adopting a particular joint combination. In contrast, we propose a more selective control strategy: variations of the joint configuration that leave the values of essential task variables unchanged are predicted to be less controlled (i.e., stabilized to a lesser degree) than joint configuration changes that shift the values of the task variables. Our experimental task involved shooting with a laser pistol at a target under four conditions. The seven joint angles of the arm were obtained from the recorded positions of markers on the limb segments. The joint configurations observed at each point in normalized time were analyzed with respect to trial-to-trial variability. Different hypotheses about relevant task variables were used to define sets of joint configurations ("uncontrolled manifolds" or UCMs) that, if realized, would leave essential task variables unchanged. The variability of joint configurations was decomposed into components lying parallel to those sets and components lying in their complement. The orientation of the gun's barrel relative to a vector pointing from the gun to the target was the task variable most successful at showing a difference between the two components of joint variability. This variable determines success at the task. Throughout the movement, not only while the gun was pointing at the target, fluctuations of joint configuration that affected this variable were much reduced compared with fluctuations that did not affect this variable. The UCM principle applied to relative gun orientation thus captures the structure of the motor control system across different parts of joint configuration space as the movement evolves in time. This suggests a specific control strategy in which changes of joint configuration that are irrelevant to success at the task are selectively released from control. By contrast, constraints representing an invariant spatial position of the gun or of the arm's center of mass structured joint configuration variability in the early and mid-portion of the movement trajectory, but not at the time of shooting. This specific control strategy is not trivial, because a target can be hit successfully also by controlling irrelevant directions in joint space equally to relevant ones. The results indicate that the method can be successfully used to determine the structure of coordination in joint space that underlies the control of the essential variables for a given task.

The effect of temperature on amount and structure of motor variability during 2-minute maximum voluntary contraction.

PubMed

Brazaitis, Marius; Skurvydas, Albertas; Pukėnas, Kazimieras; Daniuseviciūtė, Laura; Mickevicienė, Dalia; Solianik, Rima

2012-11-01

In this study, we questioned whether local cooling of muscle or heating involving core and muscle temperatures are the main indicators for force variability. Ten volunteers performed a 2-min maximum voluntary contraction (MVC) of the knee extensors under control (CON) conditions after passive heating (HT) and cooling (CL) of the lower body. HT increased muscle and rectal temperatures, whereas CL lowered muscle temperature but did not affect rectal temperature. During 2-min MVC, peak force decreased to a lower level in HT compared with CON and CL experiments. Greater central fatigue was found in the HT experiment, and there was less in the CL experiment than in the CON experiment. Increased core and muscle temperature increased physiological tremor and the amount and structural complexity of force variability of the exercising muscles, whereas local muscle cooling decreased all force variability variables measured. Copyright © 2012 Wiley Periodicals, Inc.

Use of Machine Learning Techniques for Identification of Robust Teleconnections to East African Rainfall Variability

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, F. R.; Funk, C.

2014-01-01

Hidden Markov models can be used to investigate structure of subseasonal variability. East African short rain variability has connections to large-scale tropical variability. MJO - Intraseasonal variations connected with appearance of "wet" and "dry" states. ENSO/IOZM SST and circulation anomalies are apparent during years of anomalous residence time in the subseasonal "wet" state. Similar results found in previous studies, but we can interpret this with respect to variations of subseasonal wet and dry modes. Reveal underlying connections between MJO/IOZM/ENSO with respect to East African rainfall.

Measuring Ventilatory Activity with Structured Light Plethysmography (SLP) Reduces Instrumental Observer Effect and Preserves Tidal Breathing Variability in Healthy and COPD

PubMed Central

Niérat, Marie-Cécile; Dubé, Bruno-Pierre; Llontop, Claudia; Bellocq, Agnès; Layachi Ben Mohamed, Lila; Rivals, Isabelle; Straus, Christian; Similowski, Thomas; Laveneziana, Pierantonio

2017-01-01

The use of a mouthpiece to measure ventilatory flow with a pneumotachograph (PNT) introduces a major perturbation to breathing (“instrumental/observer effect”) and suffices to modify the respiratory behavior. Structured light plethysmography (SLP) is a non-contact method of assessment of breathing pattern during tidal breathing. Firstly, we validated the SLP measurements by comparing timing components of the ventilatory pattern obtained by SLP vs. PNT under the same condition; secondly, we compared SLP to SLP+PNT measurements of breathing pattern to evaluate the disruption of breathing pattern and breathing variability in healthy and COPD subjects. Measurements were taken during tidal breathing with SLP alone and SLP+PNT recording in 30 COPD and healthy subjects. Measurements included: respiratory frequency (Rf), inspiratory, expiratory, and total breath time/duration (Ti, Te, and Tt). Passing-Bablok regression analysis was used to evaluate the interchangeability of timing components of the ventilatory pattern (Rf, Ti, Te, and Tt) between measurements performed under the following experimental conditions: SLP vs. PNT, SLP+PNT vs. SLP, and SLP+PNT vs. PNT. The variability of different ventilatory variables was assessed through their coefficients of variation (CVs). In healthy: according to Passing-Bablok regression, Rf, TI, TE and TT were interchangeable between measurements obtained under the three experimental conditions (SLP vs. PNT, SLP+PNT vs. SLP, and SLP+PNT vs. PNT). All the CVs describing “traditional” ventilatory variables (Rf, Ti, Te, Ti/Te, and Ti/Tt) were significantly smaller in SLP+PNT condition. This was not the case for more “specific” SLP-derived variables. In COPD: according to Passing-Bablok regression, Rf, TI, TE, and TT were interchangeable between measurements obtained under SLP vs. PNT and SLP+PNT vs. PNT, whereas only Rf, TE, and TT were interchangeable between measurements obtained under SLP+PNT vs. SLP. However, most discrete variables were significantly different between the SLP and SLP+PNT conditions and CVs were significantly lower when COPD patients were assessed in the SLP+PNT condition. Measuring ventilatory activity with SLP preserves resting tidal breathing variability, reduces instrumental observer effect and avoids any disruptions in breathing pattern induced by the use of PNT-mouthpiece-nose-clip combination. PMID:28572773

Measuring Ventilatory Activity with Structured Light Plethysmography (SLP) Reduces Instrumental Observer Effect and Preserves Tidal Breathing Variability in Healthy and COPD.

PubMed

Niérat, Marie-Cécile; Dubé, Bruno-Pierre; Llontop, Claudia; Bellocq, Agnès; Layachi Ben Mohamed, Lila; Rivals, Isabelle; Straus, Christian; Similowski, Thomas; Laveneziana, Pierantonio

2017-01-01

The use of a mouthpiece to measure ventilatory flow with a pneumotachograph (PNT) introduces a major perturbation to breathing ("instrumental/observer effect") and suffices to modify the respiratory behavior. Structured light plethysmography (SLP) is a non-contact method of assessment of breathing pattern during tidal breathing. Firstly, we validated the SLP measurements by comparing timing components of the ventilatory pattern obtained by SLP vs. PNT under the same condition; secondly, we compared SLP to SLP+PNT measurements of breathing pattern to evaluate the disruption of breathing pattern and breathing variability in healthy and COPD subjects. Measurements were taken during tidal breathing with SLP alone and SLP+PNT recording in 30 COPD and healthy subjects. Measurements included: respiratory frequency (R f ), inspiratory, expiratory, and total breath time/duration (Ti, Te, and Tt). Passing-Bablok regression analysis was used to evaluate the interchangeability of timing components of the ventilatory pattern (R f , Ti, Te, and Tt) between measurements performed under the following experimental conditions: SLP vs. PNT, SLP+PNT vs. SLP, and SLP+PNT vs. PNT. The variability of different ventilatory variables was assessed through their coefficients of variation (CVs). In healthy: according to Passing-Bablok regression, Rf, TI, TE and TT were interchangeable between measurements obtained under the three experimental conditions (SLP vs. PNT, SLP+PNT vs. SLP, and SLP+PNT vs. PNT). All the CVs describing "traditional" ventilatory variables (R f , Ti, Te, Ti/Te, and Ti/Tt) were significantly smaller in SLP+PNT condition. This was not the case for more "specific" SLP-derived variables. In COPD: according to Passing-Bablok regression, Rf, TI, TE, and TT were interchangeable between measurements obtained under SLP vs. PNT and SLP+PNT vs. PNT, whereas only Rf, TE, and TT were interchangeable between measurements obtained under SLP+PNT vs. SLP. However, most discrete variables were significantly different between the SLP and SLP+PNT conditions and CVs were significantly lower when COPD patients were assessed in the SLP+PNT condition. Measuring ventilatory activity with SLP preserves resting tidal breathing variability, reduces instrumental observer effect and avoids any disruptions in breathing pattern induced by the use of PNT-mouthpiece-nose-clip combination.

Single cell Hi-C reveals cell-to-cell variability in chromosome structure

PubMed Central

Schoenfelder, Stefan; Yaffe, Eitan; Dean, Wendy; Laue, Ernest D.; Tanay, Amos; Fraser, Peter

2013-01-01

Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single cell Hi-C, combined with genome-wide statistical analysis and structural modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of territories is a hallmark of chromosomal conformation. Single cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns. PMID:24067610

Dynamic Latent Trait Models with Mixed Hidden Markov Structure for Mixed Longitudinal Outcomes.

PubMed

Zhang, Yue; Berhane, Kiros

2016-01-01

We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMM). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study (CHS) to jointly model questionnaire based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.

Correspondence Analysis-Theory and Application in Management Accounting Research

NASA Astrophysics Data System (ADS)

Duller, Christine

2010-09-01

Correspondence analysis is an explanatory data analytic technique and is used to identify systematic relations between categorical variables. It is related to principal component analysis and the results provide information on the structure of categorical variables similar to the results given by a principal component analysis in case of metric variables. Classical correspondence analysis is designed two-dimensional, whereas multiple correspondence analysis is an extension to more than two variables. After an introductory overview of the idea and the implementation in standard software packages (PASW, SAS, R) an example in recent research is presented, which deals with strategic management accounting in family and non-family enterprises in Austria, where 70% to 80% of all enterprises can be classified as family firms. Although there is a growing body of literature focusing on various management issues in family firms, so far the state of the art of strategic management accounting in family firms is an empirically under-researched subject. In relevant literature only the (empirically untested) hypothesis can be found, that family firms tend to have less formalized management accounting systems than non-family enterprises. Creating a correspondence analysis will help to identify the underlying structure, which is responsible for differences in strategic management accounting.

[The influence of immobilized fibronectin on karyotypic variability of two rat kangaroo kidney cell lines].

PubMed

Polianskaia, G G; Goriachaia, T S; Pinaev, G P

2007-01-01

The numerical and structural karyotypic variability has been investigated in "markerless" Rat kangaroo kidney cell lines NBL-3-17 and NBL-3-11 when cultivating on a fibronectin-coated surface. In cell line NBL-3-17, cultivated on the fibronectin-coated surface for 1, 2, 4 and 8 days, the character of cell distribution for the chromosome number has changed. These changes involve a significant decrease in frequency of cells with modal number of chromosomes, and an increase in frequency of cells with lower chromosomal number. Many new additional structural variants of the karyotype (SVK) appear. The observed alterations seem to be due preference adhesion of cells with lower chromosome number, disturbances of mitotic apparatus and selection of SVK, which are more adopted to changes in culture conditions. Detachment of cells from the fibronectin-coated surface, followed by 5 days cultivation on a hydrophilic surface restored control distribution. In cell line NBL-3-11, cultivated on the fibronectin-coated surface for 1, 2, 4 and 8 days, the character of numerical karyotypic variability did not change compared to control variants. In cell line NBL-3-17 the frequency of chromosomal aberrations under cultivation on the fibronectin-coated surface for 1, 2, 4 and 8 days did not change relative to control variants. In cell line NBL-3-11 the frequency of chromosomal aberrations under the same conditions significantly increases, mainly at the expence of chromosomal, chromatid breaks and dicentrics (telomeric association) relative to control variants. We discuss possible reasons of differences in the character of numerical and structural karyotypic variability between cell lines NBL-3-17 (hypotriploid) and NBL-3-11 (hypodiploid) under cultivation on fibronectin. The reasons of the observed interline karyotypic differences possibly consist in peculiarity of karyotypic structure of cell line NBL-3-11 and in the change of gene expression, namely in a dose of certain functioning genes in the hypotryploid cell line NBL-3-17.

Force control compensation method with variable load stiffness and damping of the hydraulic drive unit force control system

NASA Astrophysics Data System (ADS)

Kong, Xiangdong; Ba, Kaixian; Yu, Bin; Cao, Yuan; Zhu, Qixin; Zhao, Hualong

2016-05-01

Each joint of hydraulic drive quadruped robot is driven by the hydraulic drive unit (HDU), and the contacting between the robot foot end and the ground is complex and variable, which increases the difficulty of force control inevitably. In the recent years, although many scholars researched some control methods such as disturbance rejection control, parameter self-adaptive control, impedance control and so on, to improve the force control performance of HDU, the robustness of the force control still needs improving. Therefore, how to simulate the complex and variable load characteristics of the environment structure and how to ensure HDU having excellent force control performance with the complex and variable load characteristics are key issues to be solved in this paper. The force control system mathematic model of HDU is established by the mechanism modeling method, and the theoretical models of a novel force control compensation method and a load characteristics simulation method under different environment structures are derived, considering the dynamic characteristics of the load stiffness and the load damping under different environment structures. Then, simulation effects of the variable load stiffness and load damping under the step and sinusoidal load force are analyzed experimentally on the HDU force control performance test platform, which provides the foundation for the force control compensation experiment research. In addition, the optimized PID control parameters are designed to make the HDU have better force control performance with suitable load stiffness and load damping, under which the force control compensation method is introduced, and the robustness of the force control system with several constant load characteristics and the variable load characteristics respectively are comparatively analyzed by experiment. The research results indicate that if the load characteristics are known, the force control compensation method presented in this paper has positive compensation effects on the load characteristics variation, i.e., this method decreases the effects of the load characteristics variation on the force control performance and enhances the force control system robustness with the constant PID parameters, thereby, the online PID parameters tuning control method which is complex needs not be adopted. All the above research provides theoretical and experimental foundation for the force control method of the quadruped robot joints with high robustness.

Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy). PMID:27555816

Anti-buckling design of variable stiffness composite cylinder under combined loading based on the multi-objective optimization method

NASA Astrophysics Data System (ADS)

Zheng, Y.; Chen, J.

2018-06-01

Variable stiffness composite structures take full advantages of composite’s design ability. An enlarged design space will make the structure’s performance more excellent. Through an optimal design of a variable stiffness cylinder, the buckling capacity of the cylinder will be increased as compared with its constant stiffness counterpart. In this paper, variable stiffness composite cylinders sustaining combined loadings are considered, and the optimization is conducted based on the multi-objective optimization method. The results indicate that variable stiffness cylinder’s loading capacity is increased significantly as compared with the constant stiffness, especially when an inhomogeneous loading is considered.

Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

NASA Astrophysics Data System (ADS)

Khan, F.; Pilz, J.; Spöck, G.

2017-12-01

Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan, Mixture models, EM algorithm.

Simultaneous analysis and design

NASA Technical Reports Server (NTRS)

Haftka, R. T.

1984-01-01

Optimization techniques are increasingly being used for performing nonlinear structural analysis. The development of element by element (EBE) preconditioned conjugate gradient (CG) techniques is expected to extend this trend to linear analysis. Under these circumstances the structural design problem can be viewed as a nested optimization problem. There are computational benefits to treating this nested problem as a large single optimization problem. The response variables (such as displacements) and the structural parameters are all treated as design variables in a unified formulation which performs simultaneously the design and analysis. Two examples are used for demonstration. A seventy-two bar truss is optimized subject to linear stress constraints and a wing box structure is optimized subject to nonlinear collapse constraints. Both examples show substantial computational savings with the unified approach as compared to the traditional nested approach.

An evaluation of the Psychache Scale on an offender population.

PubMed

Mills, Jeremy F; Green, Kate; Reddon, John R

2005-10-01

This study examined the generalizability of a self-report measure of psychache to an offender population. The factor structure, construct validity, and criterion validity of the Psychache Scale was assessed on 136 male prison inmates. The results showed the Psychache Scale has a single underlying factor structure and to be strongly associated with measures of depression and hopelessness and moderately associated with psychiatric symptoms and the criterion variable of a history of prior suicide attempts. The variables of depression, hopelessness, and psychiatric symptoms all contributed unique variance to psychache. Discussion centers on psychache's theoretical application to the prediction of suicide.

Lightweight structure design for supporting plate of primary mirror

NASA Astrophysics Data System (ADS)

Wang, Xiao; Wang, Wei; Liu, Bei; Qu, Yan Jun; Li, Xu Peng

2017-10-01

A topological optimization design for the lightweight technology of supporting plate of the primary mirror is presented in this paper. The supporting plate of the primary mirror is topologically optimized under the condition of determined shape, loads and environment. And the optimal structure is obtained. The diameter of the primary mirror in this paper is 450mm, and the material is SiC1 . It is better to select SiC/Al as the supporting material. Six points of axial relative displacement can be used as constraints in optimization2 . Establishing the supporting plate model and setting up the model parameters. After analyzing the force of the main mirror on the supporting plate, the model is applied with force and constraints. Modal analysis and static analysis of supporting plates are calculated. The continuum structure topological optimization mathematical model is created with the variable-density method. The maximum deformation of the surface of supporting plate under the gravity of the mirror and the first model frequency are assigned to response variable, and the entire volume of supporting structure is converted to object function. The structures before and after optimization are analyzed using the finite element method. Results show that the optimized fundamental frequency increases 29.85Hz and has a less displacement compared with the traditional structure.

Causal discovery and inference: concepts and recent methodological advances.

PubMed

Spirtes, Peter; Zhang, Kun

This paper aims to give a broad coverage of central concepts and principles involved in automated causal inference and emerging approaches to causal discovery from i.i.d data and from time series. After reviewing concepts including manipulations, causal models, sample predictive modeling, causal predictive modeling, and structural equation models, we present the constraint-based approach to causal discovery, which relies on the conditional independence relationships in the data, and discuss the assumptions underlying its validity. We then focus on causal discovery based on structural equations models, in which a key issue is the identifiability of the causal structure implied by appropriately defined structural equation models: in the two-variable case, under what conditions (and why) is the causal direction between the two variables identifiable? We show that the independence between the error term and causes, together with appropriate structural constraints on the structural equation, makes it possible. Next, we report some recent advances in causal discovery from time series. Assuming that the causal relations are linear with nonGaussian noise, we mention two problems which are traditionally difficult to solve, namely causal discovery from subsampled data and that in the presence of confounding time series. Finally, we list a number of open questions in the field of causal discovery and inference.

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

ERIC Educational Resources Information Center

Macho, Siegfried; Ledermann, Thomas

2011-01-01

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

Category Structure Determines the Relative Attractiveness of Global versus Local Averages

ERIC Educational Resources Information Center

Vogel, Tobias; Carr, Evan W.; Davis, Tyler; Winkielman, Piotr

2018-01-01

Stimuli that capture the central tendency of presented exemplars are often preferred--a phenomenon also known as the classic beauty-in-averageness effect. However, recent studies have shown that this effect can reverse under certain conditions. We propose that a key variable for such ugliness-in-averageness effects is the category structure of the…

Statistical physics and physiology: monofractal and multifractal approaches

NASA Technical Reports Server (NTRS)

Stanley, H. E.; Amaral, L. A.; Goldberger, A. L.; Havlin, S.; Peng, C. K.

1999-01-01

Even under healthy, basal conditions, physiologic systems show erratic fluctuations resembling those found in dynamical systems driven away from a single equilibrium state. Do such "nonequilibrium" fluctuations simply reflect the fact that physiologic systems are being constantly perturbed by external and intrinsic noise? Or, do these fluctuations actually, contain useful, "hidden" information about the underlying nonequilibrium control mechanisms? We report some recent attempts to understand the dynamics of complex physiologic fluctuations by adapting and extending concepts and methods developed very recently in statistical physics. Specifically, we focus on interbeat interval variability as an important quantity to help elucidate possibly non-homeostatic physiologic variability because (i) the heart rate is under direct neuroautonomic control, (ii) interbeat interval variability is readily measured by noninvasive means, and (iii) analysis of these heart rate dynamics may provide important practical diagnostic and prognostic information not obtainable with current approaches. The analytic tools we discuss may be used on a wider range of physiologic signals. We first review recent progress using two analysis methods--detrended fluctuation analysis and wavelets--sufficient for quantifying monofractual structures. We then describe recent work that quantifies multifractal features of interbeat interval series, and the discovery that the multifractal structure of healthy subjects is different than that of diseased subjects.

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

NASA Astrophysics Data System (ADS)

Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

2014-10-01

The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure variables from VHR satellite images. Thus an average prediction error of ˜ 1.1 m is expected on crown diameter, ˜ 0.9 m on tree spacing, ˜ 3 m on height and ˜ 0.06 m on diameter at breast height.

The Propagation of Movement Variability in Time: A Methodological Approach for Discrete Movements with Multiple Degrees of Freedom.

PubMed

Krüger, Melanie; Straube, Andreas; Eggert, Thomas

2017-01-01

In recent years, theory-building in motor neuroscience and our understanding of the synergistic control of the redundant human motor system has significantly profited from the emergence of a range of different mathematical approaches to analyze the structure of movement variability. Approaches such as the Uncontrolled Manifold method or the Noise-Tolerance-Covariance decomposition method allow to detect and interpret changes in movement coordination due to e.g., learning, external task constraints or disease, by analyzing the structure of within-subject, inter-trial movement variability. Whereas, for cyclical movements (e.g., locomotion), mathematical approaches exist to investigate the propagation of movement variability in time (e.g., time series analysis), similar approaches are missing for discrete, goal-directed movements, such as reaching. Here, we propose canonical correlation analysis as a suitable method to analyze the propagation of within-subject variability across different time points during the execution of discrete movements. While similar analyses have already been applied for discrete movements with only one degree of freedom (DoF; e.g., Pearson's product-moment correlation), canonical correlation analysis allows to evaluate the coupling of inter-trial variability across different time points along the movement trajectory for multiple DoF-effector systems, such as the arm. The theoretical analysis is illustrated by empirical data from a study on reaching movements under normal and disturbed proprioception. The results show increased movement duration, decreased movement amplitude, as well as altered movement coordination under ischemia, which results in a reduced complexity of movement control. Movement endpoint variability is not increased under ischemia. This suggests that healthy adults are able to immediately and efficiently adjust the control of complex reaching movements to compensate for the loss of proprioceptive information. Further, it is shown that, by using canonical correlation analysis, alterations in movement coordination that indicate changes in the control strategy concerning the use of motor redundancy can be detected, which represents an important methodical advance in the context of neuromechanics.

Environmental risk perception, environmental concern and propensity to participate in organic farming programmes.

PubMed

Toma, Luiza; Mathijs, Erik

2007-04-01

This paper aims to identify the factors underlying farmers' propensity to participate in organic farming programmes in a Romanian rural region that confronts non-point source pollution. For this, we employ structural equation modelling with latent variables using a specific data set collected through an agri-environmental farm survey in 2001. The model includes one 'behavioural intention' latent variable ('propensity to participate in organic farming programmes') and five 'attitude' and 'socio-economic' latent variables ('socio-demographic characteristics', 'economic characteristics', 'agri-environmental information access', 'environmental risk perception' and 'general environmental concern'). The results indicate that, overall, the model has an adequate fit to the data. All loadings are statistically significant, supporting the theoretical basis for assignment of indicators for each latent variable. The significance tests for the structural model parameters show 'environmental risk perception' as the strongest determinant of farmers' propensity to participate in organic farming programmes.

Integrated Controls-Structures Design Methodology: Redesign of an Evolutionary Test Structure

NASA Technical Reports Server (NTRS)

Maghami, Peiman G.; Gupta, Sandeep; Elliot, Kenny B.; Joshi, Suresh M.

1997-01-01

An optimization-based integrated controls-structures design methodology for a class of flexible space structures is described, and the phase-0 Controls-Structures-Integration evolutionary model, a laboratory testbed at NASA Langley, is redesigned using this integrated design methodology. The integrated controls-structures design is posed as a nonlinear programming problem to minimize the control effort required to maintain a specified line-of-sight pointing performance, under persistent white noise disturbance. Static and dynamic dissipative control strategies are employed for feedback control, and parameters of these controllers are considered as the control design variables. Sizes of strut elements in various sections of the CEM are used as the structural design variables. Design guides for the struts are developed and employed in the integrated design process, to ensure that the redesigned structure can be effectively fabricated. The superiority of the integrated design methodology over the conventional design approach is demonstrated analytically by observing a significant reduction in the average control power needed to maintain specified pointing performance with the integrated design approach.

Wing Weight Optimization Under Aeroelastic Loads Subject to Stress Constraints

NASA Technical Reports Server (NTRS)

Kapania, Rakesh K.; Issac, J.; Macmurdy, D.; Guruswamy, Guru P.

1997-01-01

A minimum weight optimization of the wing under aeroelastic loads subject to stress constraints is carried out. The loads for the optimization are based on aeroelastic trim. The design variables are the thickness of the wing skins and planform variables. The composite plate structural model incorporates first-order shear deformation theory, the wing deflections are expressed using Chebyshev polynomials and a Rayleigh-Ritz procedure is adopted for the structural formulation. The aerodynamic pressures provided by the aerodynamic code at a discrete number of grid points is represented as a bilinear distribution on the composite plate code to solve for the deflections and stresses in the wing. The lifting-surface aerodynamic code FAST is presently being used to generate the pressure distribution over the wing. The envisioned ENSAERO/Plate is an aeroelastic analysis code which combines ENSAERO version 3.0 (for analysis of wing-body configurations) with the composite plate code.

THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures.

PubMed

Theobald, Douglas L; Wuttke, Deborah S

2006-09-01

THESEUS is a command line program for performing maximum likelihood (ML) superpositions and analysis of macromolecular structures. While conventional superpositioning methods use ordinary least-squares (LS) as the optimization criterion, ML superpositions provide substantially improved accuracy by down-weighting variable structural regions and by correcting for correlations among atoms. ML superpositioning is robust and insensitive to the specific atoms included in the analysis, and thus it does not require subjective pruning of selected variable atomic coordinates. Output includes both likelihood-based and frequentist statistics for accurate evaluation of the adequacy of a superposition and for reliable analysis of structural similarities and differences. THESEUS performs principal components analysis for analyzing the complex correlations found among atoms within a structural ensemble. ANSI C source code and selected binaries for various computing platforms are available under the GNU open source license from http://monkshood.colorado.edu/theseus/ or http://www.theseus3d.org.

Improved approximations for control augmented structural synthesis

NASA Technical Reports Server (NTRS)

Thomas, H. L.; Schmit, L. A.

1990-01-01

A methodology for control-augmented structural synthesis is presented for structure-control systems which can be modeled as an assemblage of beam, truss, and nonstructural mass elements augmented by a noncollocated direct output feedback control system. Truss areas, beam cross sectional dimensions, nonstructural masses and rotary inertias, and controller position and velocity gains are treated simultaneously as design variables. The structural mass and a control-system performance index can be minimized simultaneously, with design constraints placed on static stresses and displacements, dynamic harmonic displacements and forces, structural frequencies, and closed-loop eigenvalues and damping ratios. Intermediate design-variable and response-quantity concepts are used to generate new approximations for displacements and actuator forces under harmonic dynamic loads and for system complex eigenvalues. This improves the overall efficiency of the procedure by reducing the number of complete analyses required for convergence. Numerical results which illustrate the effectiveness of the method are given.

Three-dimensional elastic-plastic finite-element analysis of fatigue crack propagation

NASA Technical Reports Server (NTRS)

Goglia, G. L.; Chermahini, R. G.

1985-01-01

Fatigue cracks are a major problem in designing structures subjected to cyclic loading. Cracks frequently occur in structures such as aircraft and spacecraft. The inspection intervals of many aircraft structures are based on crack-propagation lives. Therefore, improved prediction of propagation lives under flight-load conditions (variable-amplitude loading) are needed to provide more realistic design criteria for these structures. The main thrust was to develop a three-dimensional, nonlinear, elastic-plastic, finite element program capable of extending a crack and changing boundary conditions for the model under consideration. The finite-element model is composed of 8-noded (linear-strain) isoparametric elements. In the analysis, the material is assumed to be elastic-perfectly plastic. The cycle stress-strain curve for the material is shown Zienkiewicz's initial-stress method, von Mises's yield criterion, and Drucker's normality condition under small-strain assumptions are used to account for plasticity. The three-dimensional analysis is capable of extending the crack and changing boundary conditions under cyclic loading.

Topometry optimization of sheet metal structures for crashworthiness design using hybrid cellular automata

NASA Astrophysics Data System (ADS)

Mozumder, Chandan K.

The objective in crashworthiness design is to generate plastically deformable energy absorbing structures which can satisfy the prescribed force-displacement (FD) response. The FD behavior determines the reaction force, displacement and the internal energy that the structure should withstand. However, attempts to include this requirement in structural optimization problems remain scarce. The existing commercial optimization tools utilize models under static loading conditions because of the complexities associated with dynamic/impact loading. Due to the complexity of a crash event and the consequent time required to numerically analyze the dynamic response of the structure, classical methods (i.e., gradient-based and direct) are not well developed to solve this undertaking. This work presents an approach under the framework of the hybrid cellular automaton (HCA) method to solve the above challenge. The HCA method has been successfully applied to nonlinear transient topology optimization for crashworthiness design. In this work, the HCA algorithm has been utilized to develop an efficient methodology for synthesizing shell-based sheet metal structures with optimal material thickness distribution under a dynamic loading event using topometry optimization. This method utilizes the cellular automata (CA) computing paradigm and nonlinear transient finite element analysis (FEA) via ls-dyna. In this method, a set field variables is driven to their target states by changing a convenient set of design variables (e.g., thickness). These rules operate locally in cells within a lattice that only know local conditions. The field variables associated with the cells are driven to a setpoint to obtain the desired structure. This methodology is used to design for structures with controlled energy absorption with specified buckling zones. The peak reaction force and the maximum displacement are also constrained to meet the desired safety level according to passenger safety regulations. Design for prescribed FD response by minimizing the error between the actual response and desired FD curve is implemented. With the use of HCA rules, manufacturability constraints (e.g., rolling) and structures which can be manufactured by special techniques, such as, tailor-welded blanks (TWB), have also been implemented. This methodology is applied to shock-absorbing structural components for passengers in a crashing vehicle. These results are compared to previous designs showing the benefits of the method introduced in this work.

The underlying structure of diagnostic systems of schizophrenia: a comprehensive polydiagnostic approach.

PubMed

Peralta, Victor; Cuesta, Manuel J

2005-11-15

The objective was to ascertain the underlying factor structure of alternative definitions of schizophrenia, and to examine the distribution of schizophrenia-related variables against the resulting factor solution. Twenty-three diagnostic schemes of schizophrenia were applied to 660 patients presenting with psychotic symptoms regardless of the specific diagnosis of psychotic disorder. Factor analysis of the 23 diagnostic schemes yielded three interpretable factors explaining 58% of the variance, the first factor (general schizophrenia factor) accounting for most of the variance (36%). On the basis of the general schizophrenia factor score, the sample was divided in quintile groups representing 5 levels of schizophrenia definition (absent, doubtful, very broad, broad and narrow) and the distribution of a number of schizophrenia-related variables was examined across the groups. This grouping procedure was used for examining the comparative validity of alternative levels of categorically defined schizophrenia and an ordinal (i.e. dimensional) definition. Overall, schizophrenia-related variables displayed a dose-response relationship with level of schizophrenia definition. Logistic regression analyses revealed that the dimensional definition explained more variance in the schizophrenia-related variables than the alternative levels for defining schizophrenia categorically. These results are consistent with a unitary and dimensional construct of schizophrenia with no clear "points of rarity" at its boundaries, thus supporting the continuum hypothesis of the psychotic illness.

Effects of task and age on the magnitude and structure of force fluctuations: insights into underlying neuro-behavioral processes.

PubMed

Vieluf, Solveig; Temprado, Jean-Jacques; Berton, Eric; Jirsa, Viktor K; Sleimen-Malkoun, Rita

2015-03-13

The present study aimed at characterizing the effects of increasing (relative) force level and aging on isometric force control. To achieve this objective and to infer changes in the underlying control mechanisms, measures of information transmission, as well as magnitude and time-frequency structure of behavioral variability were applied to force-time-series. Older adults were found to be weaker, more variable, and less efficient than young participants. As a function of force level, efficiency followed an inverted-U shape in both groups, suggesting a similar organization of the force control system. The time-frequency structure of force output fluctuations was only significantly affected by task conditions. Specifically, a narrower spectral distribution with more long-range correlations and an inverted-U pattern of complexity changes were observed with increasing force level. Although not significant older participants displayed on average a less complex behavior for low and intermediate force levels. The changes in force signal's regularity presented a strong dependence on time-scales, which significantly interacted with age and condition. An inverted-U profile was only observed for the time-scale relevant to the sensorimotor control process. However, in both groups the peak was not aligned with the optimum of efficiency. Our results support the view that behavioral variability, in terms of magnitude and structure, has a functional meaning and affords non-invasive markers of the adaptations of the sensorimotor control system to various constraints. The measures of efficiency and variability ought to be considered as complementary since they convey specific information on the organization of control processes. The reported weak age effect on variability and complexity measures suggests that the behavioral expression of the loss of complexity hypothesis is not as straightforward as conventionally admitted. However, group differences did not completely vanish, which suggests that age differences can be more or less apparent depending on task properties and whether difficulty is scaled in relative or absolute terms.

Modelling Pseudocalanus elongatus stage-structured population dynamics embedded in a water column ecosystem model for the northern North Sea

NASA Astrophysics Data System (ADS)

Moll, Andreas; Stegert, Christoph

2007-01-01

This paper outlines an approach to couple a structured zooplankton population model with state variables for eggs, nauplii, two copepodites stages and adults adapted to Pseudocalanus elongatus into the complex marine ecosystem model ECOHAM2 with 13 state variables resolving the carbon and nitrogen cycle. Different temperature and food scenarios derived from laboratory culture studies were examined to improve the process parameterisation for copepod stage dependent development processes. To study annual cycles under realistic weather and hydrographic conditions, the coupled ecosystem-zooplankton model is applied to a water column in the northern North Sea. The main ecosystem state variables were validated against observed monthly mean values. Then vertical profiles of selected state variables were compared to the physical forcing to study differences between zooplankton as one biomass state variable or partitioned into five population state variables. Simulated generation times are more affected by temperature than food conditions except during the spring phytoplankton bloom. Up to six generations within the annual cycle can be discerned in the simulation.

Probabilistic Structural Evaluation of Uncertainties in Radiator Sandwich Panel Design

NASA Technical Reports Server (NTRS)

Kuguoglu, Latife; Ludwiczak, Damian

2006-01-01

The Jupiter Icy Moons Orbiter (JIMO) Space System is part of the NASA's Prometheus Program. As part of the JIMO engineering team at NASA Glenn Research Center, the structural design of the JIMO Heat Rejection Subsystem (HRS) is evaluated. An initial goal of this study was to perform sensitivity analyses to determine the relative importance of the input variables on the structural responses of the radiator panel. The desire was to let the sensitivity analysis information identify the important parameters. The probabilistic analysis methods illustrated here support this objective. The probabilistic structural performance evaluation of a HRS radiator sandwich panel was performed. The radiator panel structural performance was assessed in the presence of uncertainties in the loading, fabrication process variables, and material properties. The stress and displacement contours of the deterministic structural analysis at mean probability was performed and results presented. It is followed by a probabilistic evaluation to determine the effect of the primitive variables on the radiator panel structural performance. Based on uncertainties in material properties, structural geometry and loading, the results of the displacement and stress analysis are used as an input file for the probabilistic analysis of the panel. The sensitivity of the structural responses, such as maximum displacement and maximum tensile and compressive stresses of the facesheet in x and y directions and maximum VonMises stresses of the tube, to the loading and design variables is determined under the boundary condition where all edges of the radiator panel are pinned. Based on this study, design critical material and geometric parameters of the considered sandwich panel are identified.

Temperate Mountain Forest Biodiversity under Climate Change: Compensating Negative Effects by Increasing Structural Complexity

PubMed Central

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species’ occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species’ occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change. PMID:24823495

Temperate mountain forest biodiversity under climate change: compensating negative effects by increasing structural complexity.

PubMed

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species' occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species' occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change.

Novel characterization of landscape-level variability in historical vegetation structure.

PubMed

Collins, Brandon M; Lydersen, Jamie M; Everett, Richard G; Fry, Danny L; Stephens, Scott L

2015-07-01

We analyzed historical timber inventory data collected systematically across a large mixed-conifer-dominated landscape to gain insight into the interaction between disturbances and vegetation structure and composition prior to 20th century land management practices. Using records from over 20 000 trees, we quantified historical vegetation structure and composition for nine distinct vegetation groups. Our findings highlight some key aspects of forest structure under an intact disturbance regime: (1) forests were low density, with mean live basal area and tree density ranging from 8-30 m2 /ha and 25-79 trees/ha, respectively; (2) understory and overstory structure and composition varied considerably across the landscape; and (3) elevational gradients largely explained variability in forest structure over the landscape. Furthermore, the presence of large trees across most of the surveyed area suggests that extensive stand-replacing disturbances were rare in these forests. The vegetation structure and composition characteristics we quantified, along with evidence of largely elevational control on these characteristics, can provide guidance for restoration efforts in similar forests.

Probabilistic-Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

developed to determine the relative importance of structural components of the vehicle under differnet crash and blast scenarios. With the integration of...the vehicle under different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the...parameter variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment

Impact of small-scale vegetation structure on tephra layer preservation

PubMed Central

Cutler, Nick A.; Shears, Olivia M.; Streeter, Richard T.; Dugmore, Andrew J.

2016-01-01

The factors that influence tephra layer taphonomy are poorly understood, but vegetation cover is likely to play a role in the preservation of terrestrial tephra deposits. The impact of vegetation on tephra layer preservation is important because: 1) the morphology of tephra layers could record key characteristics of past land surfaces and 2) vegetation-driven variability in tephra thickness could affect attempts to infer eruption and dispersion parameters. We investigated small- (metre-) scale interactions between vegetation and a thin (<10 cm), recent tephra layer. We conducted surveys of vegetation structure and tephra thickness at two locations which received a similar tephra deposit, but had contrasting vegetation cover (moss vs shrub). The tephra layer was thicker and less variable under shrub cover. Vegetation structure and layer thickness were correlated on the moss site but not under shrub cover, where the canopy reduced the influence of understory vegetation on layer morphology. Our results show that vegetation structure can influence tephra layer thickness on both small and medium (site) scales. These findings suggest that some tephra layers may carry a signal of past vegetation cover. They also have implications for the sampling effort required to reliably estimate the parameters of initial deposits. PMID:27845415

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe.

PubMed

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes.

Spatial Distribution of a Large Herbivore Community at Waterholes: An Assessment of Its Stability over Years in Hwange National Park, Zimbabwe

PubMed Central

Chamaillé-Jammes, Simon; Charbonnel, Anaïs; Dray, Stéphane; Madzikanda, Hillary; Fritz, Hervé

2016-01-01

The spatial structuring of populations or communities is an important driver of their functioning and their influence on ecosystems. Identifying the (in)stability of the spatial structure of populations is a first step towards understanding the underlying causes of these structures. Here we studied the relative importance of spatial vs. interannual variability in explaining the patterns of abundance of a large herbivore community (8 species) at waterholes in Hwange National Park (Zimbabwe). We analyzed census data collected over 13 years using multivariate methods. Our results showed that variability in the census data was mostly explained by the spatial structure of the community, as some waterholes had consistently greater herbivore abundance than others. Some temporal variability probably linked to Park-scale migration dependent on annual rainfall was noticeable, however. Once this was accounted for, little temporal variability remained to be explained, suggesting that other factors affecting herbivore abundance over time had a negligible effect at the scale of the study. The extent of spatial and temporal variability in census data was also measured for each species. This study could help in projecting the consequences of surface water management, and more generally presents a methodological framework to simultaneously address the relative importance of spatial vs. temporal effects in driving the distribution of organisms across landscapes. PMID:27074044

Root attributes affecting water uptake of rice (Oryza sativa) under drought

PubMed Central

Henry, Amelia

2012-01-01

Lowland rice roots have a unique physiological response to drought because of their adaptation to flooded soil. Rice root attributes that facilitate growth under flooded conditions may affect rice response to drought, but the relative roles of root structural and functional characteristics for water uptake under drought in rice are not known. Morphological, anatomical, biochemical, and molecular attributes of soil-grown rice roots were measured to investigate the genotypic variability and genotype×environment interactions of water uptake under variable soil water regimes. Drought-resistant genotypes had the lowest night-time bleeding rates of sap from the root system in the field. Diurnal fluctuation predominated as the strongest source of variation for bleeding rates in the field and root hydraulic conductivity (Lp r) in the greenhouse, and was related to expression trends of various PIP and TIP aquaporins. Root anatomy was generally more responsive to drought treatments in drought-resistant genotypes. Suberization and compaction of sclerenchyma layer cells decreased under drought, whereas suberization of the endodermis increased, suggesting differential roles of these two cell layers for the retention of oxygen under flooded conditions (sclerenchyma layer) and retention of water under drought (endodermis). The results of this study point to the genetic variability in responsiveness to drought of rice roots in terms of morphology, anatomy, and function. PMID:22791828

Root attributes affecting water uptake of rice (Oryza sativa) under drought.

PubMed

Henry, Amelia; Cal, Andrew J; Batoto, Tristram C; Torres, Rolando O; Serraj, Rachid

2012-08-01

Lowland rice roots have a unique physiological response to drought because of their adaptation to flooded soil. Rice root attributes that facilitate growth under flooded conditions may affect rice response to drought, but the relative roles of root structural and functional characteristics for water uptake under drought in rice are not known. Morphological, anatomical, biochemical, and molecular attributes of soil-grown rice roots were measured to investigate the genotypic variability and genotype×environment interactions of water uptake under variable soil water regimes. Drought-resistant genotypes had the lowest night-time bleeding rates of sap from the root system in the field. Diurnal fluctuation predominated as the strongest source of variation for bleeding rates in the field and root hydraulic conductivity (Lpr) in the greenhouse, and was related to expression trends of various PIP and TIP aquaporins. Root anatomy was generally more responsive to drought treatments in drought-resistant genotypes. Suberization and compaction of sclerenchyma layer cells decreased under drought, whereas suberization of the endodermis increased, suggesting differential roles of these two cell layers for the retention of oxygen under flooded conditions (sclerenchyma layer) and retention of water under drought (endodermis). The results of this study point to the genetic variability in responsiveness to drought of rice roots in terms of morphology, anatomy, and function.

Accounting for Parcel-Allocation Variability in Practice: Combining Sources of Uncertainty and Choosing the Number of Allocations.

PubMed

Sterba, Sonya K; Rights, Jason D

2016-01-01

Item parceling remains widely used under conditions that can lead to parcel-allocation variability in results. Hence, researchers may be interested in quantifying and accounting for parcel-allocation variability within sample. To do so in practice, three key issues need to be addressed. First, how can we combine sources of uncertainty arising from sampling variability and parcel-allocation variability when drawing inferences about parameters in structural equation models? Second, on what basis can we choose the number of repeated item-to-parcel allocations within sample? Third, how can we diagnose and report proportions of total variability per estimate arising due to parcel-allocation variability versus sampling variability? This article addresses these three methodological issues. Developments are illustrated using simulated and empirical examples, and software for implementing them is provided.

Continuous-variable quantum teleportation in bosonic structured environments

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

He Guangqiang; Zhang Jingtao; Zhu Jun

2011-09-15

The effects of dynamics of continuous-variable entanglement under the various kinds of environments on quantum teleportation are quantitatively investigated. Only under assumption of the weak system-reservoir interaction, the evolution of teleportation fidelity is analytically derived and is numerically plotted in terms of environment parameters including reservoir temperature and its spectral density, without Markovian and rotating wave approximations. We find that the fidelity of teleportation is a monotonically decreasing function for Markovian interaction in Ohmic-like environments, while it oscillates for non-Markovian ones. According to the dynamical laws of teleportation, teleportation with better performances can be implemented by selecting the appropriate time.

What are Up, Down and Net Fluxes?

Atmospheric Science Data Center

2014-12-08

... Given the vertical layered structure of Earth atmosphere above underlying surfaces, the vertical variability of these fluxes ... for the net energy loss or gain within any two such layers. This concept is important in defining the radiative heating or cooling ...

A model for AGN variability on multiple time-scales

NASA Astrophysics Data System (ADS)

Sartori, Lia F.; Schawinski, Kevin; Trakhtenbrot, Benny; Caplar, Neven; Treister, Ezequiel; Koss, Michael J.; Urry, C. Megan; Zhang, C. E.

2018-05-01

We present a framework to link and describe active galactic nuclei (AGN) variability on a wide range of time-scales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different time-scales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio (L/LEdd) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the L/LEdd distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different time-scales, therefore providing new insights into AGN variability and black hole growth phenomena.

The structure of late-life depressive symptoms across a 20-year span: a taxometric investigation.

PubMed

Holland, Jason M; Schutte, Kathleen K; Brennan, Penny L; Moos, Rudolf H

2010-03-01

Past studies of the underlying structure of depressive symptoms have yielded mixed results, with some studies supporting a continuous conceptualization and others supporting a categorical one. However, no study has examined this research question with an exclusively older adult sample, despite the potential uniqueness of late-life depressive symptoms. In the present study, the underlying structure of late-life depressive symptoms was examined among a sample of 1,289 individuals across 3 waves of data collection spanning 20 years. The authors employed a taxometric methodology using indicators of depression derived from the Research Diagnostic Criteria (R. L. Spitzer, J. Endicott, & E. Robins, 1978). Maximum eigenvalue analyses and inchworm consistency tests generally supported a categorical conceptualization and identified a group that was primarily characterized by thoughts about death and suicide. However, compared to a categorical depression variable, depressive symptoms treated continuously were generally better predictors of relevant criterion variables. These findings suggest that thoughts of death and suicide may characterize a specific type of late-life depression, yet a continuous conceptualization still typically maximizes the predictive utility of late-life depressive symptoms.

Structural damage detection for in-service highway bridge under operational and environmental variability

NASA Astrophysics Data System (ADS)

Jin, Chenhao; Li, Jingcheng; Jang, Shinae; Sun, Xiaorong; Christenson, Richard

2015-03-01

Structural health monitoring has drawn significant attention in the past decades with numerous methodologies and applications for civil structural systems. Although many researchers have developed analytical and experimental damage detection algorithms through vibration-based methods, these methods are not widely accepted for practical structural systems because of their sensitivity to uncertain environmental and operational conditions. The primary environmental factor that influences the structural modal properties is temperature. The goal of this article is to analyze the natural frequency-temperature relationships and detect structural damage in the presence of operational and environmental variations using modal-based method. For this purpose, correlations between natural frequency and temperature are analyzed to select proper independent variables and inputs for the multiple linear regression model and neural network model. In order to capture the changes of natural frequency, confidence intervals to detect the damages for both models are generated. A long-term structural health monitoring system was installed on an in-service highway bridge located in Meriden, Connecticut to obtain vibration and environmental data. Experimental testing results show that the variability of measured natural frequencies due to temperature is captured, and the temperature-induced changes in natural frequencies have been considered prior to the establishment of the threshold in the damage warning system. This novel approach is applicable for structural health monitoring system and helpful to assess the performance of the structure for bridge management and maintenance.

Design and performance of optimal detectors for guided wave structural health monitoring

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

Dib, G.; Udpa, L.

2016-01-01

Ultrasonic guided wave measurements in a long term structural health monitoring system are affected by measurement noise, environmental conditions, transducer aging and malfunction. This results in measurement variability which affects detection performance, especially in complex structures where baseline data comparison is required. This paper derives the optimal detector structure, within the framework of detection theory, where a guided wave signal at the sensor is represented by a single feature value that can be used for comparison with a threshold. Three different types of detectors are derived depending on the underlying structure’s complexity: (i) Simple structures where defect reflections can bemore » identified without the need for baseline data; (ii) Simple structures that require baseline data due to overlap of defect scatter with scatter from structural features; (iii) Complex structure with dense structural features that require baseline data. The detectors are derived by modeling the effects of variabilities and uncertainties as random processes. Analytical solutions for the performance of detectors in terms of the probability of detection and false alarm are derived. A finite element model is used to generate guided wave signals and the performance results of a Monte-Carlo simulation are compared with the theoretical performance. initial results demonstrate that the problems of signal complexity and environmental variability can in fact be exploited to improve detection performance.« less

Changes in quantitative 3D shape features of the optic nerve head associated with age

NASA Astrophysics Data System (ADS)

Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

2013-02-01

Optic nerve head (ONH) structure is an important biological feature of the eye used by clinicians to diagnose and monitor progression of diseases such as glaucoma. ONH structure is commonly examined using stereo fundus imaging or optical coherence tomography. Stereo fundus imaging provides stereo views of the ONH that retain 3D information useful for characterizing structure. In order to quantify 3D ONH structure, we applied a stereo correspondence algorithm to a set of stereo fundus images. Using these quantitative 3D ONH structure measurements, eigen structures were derived using principal component analysis from stereo images of 565 subjects from the Ocular Hypertension Treatment Study (OHTS). To evaluate the usefulness of the eigen structures, we explored associations with the demographic variables age, gender, and race. Using regression analysis, the eigen structures were found to have significant (p < 0.05) associations with both age and race after Bonferroni correction. In addition, classifiers were constructed to predict the demographic variables based solely on the eigen structures. These classifiers achieved an area under receiver operating characteristic curve of 0.62 in predicting a binary age variable, 0.52 in predicting gender, and 0.67 in predicting race. The use of objective, quantitative features or eigen structures can reveal hidden relationships between ONH structure and demographics. The use of these features could similarly allow specific aspects of ONH structure to be isolated and associated with the diagnosis of glaucoma, disease progression and outcomes, and genetic factors.

Multiscale Analysis of Nanocomposites and Their Use in Structural Level Applications

NASA Astrophysics Data System (ADS)

Hasan, Zeaid

This research focuses on the benefits of using nanocomposites in aerospace structural components to prevent or delay the onset of unique composite failure modes, such as delamination. Analytical, numerical, and experimental analyses were conducted to provide a comprehensive understanding of how carbon nanotubes (CNTs) can provide additional structural integrity when they are used in specific hot spots within a structure. A multiscale approach was implemented to determine the mechanical and thermal properties of the nanocomposites, which were used in detailed finite element models (FEMs) to analyze interlaminar failures in T and Hat section stringers. The delamination that first occurs between the tow filler and the bondline between the stringer and skin was of particular interest. Both locations are considered to be hot spots in such structural components, and failures tend to initiate from these areas. In this research, nanocomposite use was investigated as an alternative to traditional methods of suppressing delamination. The stringer was analyzed under different loading conditions and assuming different structural defects. Initial damage, defined as the first drop in the load displacement curve was considered to be a useful variable to compare the different behaviors in this study and was detected via the virtual crack closure technique (VCCT) implemented in the FE analysis. Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance.

Harvesting Atlantic Cod under Climate Variability

NASA Astrophysics Data System (ADS)

Oremus, K. L.

2016-12-01

Previous literature links the growth of a fishery to climate variability. This study uses an age-structured bioeconomic model to compare optimal harvest in the Gulf of Maine Atlantic cod fishery under a variable climate versus a static climate. The optimal harvest path depends on the relationship between fishery growth and the interest rate, with higher interest rates dictating greater harvests now at the cost of long-term stock sustainability. Given the time horizon of a single generation of fishermen under assumptions of a static climate, the model finds that the economically optimal management strategy is to harvest the entire stock in the short term and allow the fishery to collapse. However, if the biological growth of the fishery is assumed to vary with climate conditions, such as the North Atlantic Oscillation, there will always be pulses of high growth in the stock. During some of these high-growth years, the growth of the stock and its economic yield can exceed the growth rate of the economy even under high interest rates. This implies that it is not economically optimal to exhaust the New England cod fishery if NAO is included in the biological growth function. This finding may have theoretical implications for the management of other renewable yet exhaustible resources whose growth rates are subject to climate variability.

Vibration-based structural health monitoring using adaptive statistical method under varying environmental condition

NASA Astrophysics Data System (ADS)

Jin, Seung-Seop; Jung, Hyung-Jo

2014-03-01

It is well known that the dynamic properties of a structure such as natural frequencies depend not only on damage but also on environmental condition (e.g., temperature). The variation in dynamic characteristics of a structure due to environmental condition may mask damage of the structure. Without taking the change of environmental condition into account, false-positive or false-negative damage diagnosis may occur so that structural health monitoring becomes unreliable. In order to address this problem, an approach to construct a regression model based on structural responses considering environmental factors has been usually used by many researchers. The key to success of this approach is the formulation between the input and output variables of the regression model to take into account the environmental variations. However, it is quite challenging to determine proper environmental variables and measurement locations in advance for fully representing the relationship between the structural responses and the environmental variations. One alternative (i.e., novelty detection) is to remove the variations caused by environmental factors from the structural responses by using multivariate statistical analysis (e.g., principal component analysis (PCA), factor analysis, etc.). The success of this method is deeply depending on the accuracy of the description of normal condition. Generally, there is no prior information on normal condition during data acquisition, so that the normal condition is determined by subjective perspective with human-intervention. The proposed method is a novel adaptive multivariate statistical analysis for monitoring of structural damage detection under environmental change. One advantage of this method is the ability of a generative learning to capture the intrinsic characteristics of the normal condition. The proposed method is tested on numerically simulated data for a range of noise in measurement under environmental variation. A comparative study with conventional methods (i.e., fixed reference scheme) demonstrates the superior performance of the proposed method for structural damage detection.

Spatial heterogeneity of within-stream methane concentrations

NASA Astrophysics Data System (ADS)

Crawford, John T.; Loken, Luke C.; West, William E.; Crary, Benjamin; Spawn, Seth A.; Gubbins, Nicholas; Jones, Stuart E.; Striegl, Robert G.; Stanley, Emily H.

2017-05-01

Streams, rivers, and other freshwater features may be significant sources of CH4 to the atmosphere. However, high spatial and temporal variabilities hinder our ability to understand the underlying processes of CH4 production and delivery to streams and also challenge the use of scaling approaches across large areas. We studied a stream having high geomorphic variability to assess the underlying scale of CH4 spatial variability and to examine whether the physical structure of a stream can explain the variation in surface CH4. A combination of high-resolution CH4 mapping, a survey of groundwater CH4 concentrations, quantitative analysis of methanogen DNA, and sediment CH4 production potentials illustrates the spatial and geomorphic controls on CH4 emissions to the atmosphere. We observed significant spatial clustering with high CH4 concentrations in organic-rich stream reaches and lake transitions. These sites were also enriched in the methane-producing mcrA gene and had highest CH4 production rates in the laboratory. In contrast, mineral-rich reaches had significantly lower concentrations and had lesser abundances of mcrA. Strong relationships between CH4 and the physical structure of this aquatic system, along with high spatial variability, suggest that future investigations will benefit from viewing streams as landscapes, as opposed to ecosystems simply embedded in larger terrestrial mosaics. In light of such high spatial variability, we recommend that future workers evaluate stream networks first by using similar spatial tools in order to build effective sampling programs.

Conceptual optimization using genetic algorithms for tube in tube structures

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

Pârv, Bianca Roxana; Hulea, Radu; Mojolic, Cristian

2015-03-10

The purpose of this article is to optimize the tube in tube structural systems for tall buildings under the horizontal wind loads. It is well-known that the horizontal wind loads is the main criteria when choosing the structural system, the types and the dimensions of structural elements in the majority of tall buildings. Thus, the structural response of tall buildings under the horizontal wind loads will be analyzed for 40 story buildings and a total height of 120 meters; the horizontal dimensions will be 30m × 30m for the first two optimization problems and 15m × 15m for the third.more » The optimization problems will have the following as objective function the cross section area, as restrictions the displacement of the building< the admissible displacement (H/500), and as variables the cross section dimensions of the structural elements.« less

Optimal Shakedown of the Thin-Wall Metal Structures Under Strength and Stiffness Constraints

NASA Astrophysics Data System (ADS)

Alawdin, Piotr; Liepa, Liudas

2017-06-01

Classical optimization problems of metal structures confined mainly with 1st class cross-sections. But in practice it is common to use the cross-sections of higher classes. In this paper, a new mathematical model for described shakedown optimization problem for metal structures, which elements are designed from 1st to 4th class cross-sections, under variable quasi-static loads is presented. The features of limited plastic redistribution of forces in the structure with thin-walled elements there are taken into account. Authors assume the elastic-plastic flexural buckling in one plane without lateral torsional buckling behavior of members. Design formulae for Methods 1 and 2 for members are analyzed. Structures stiffness constrains are also incorporated in order to satisfy the limit serviceability state requirements. With the help of mathematical programming theory and extreme principles the structure optimization algorithm is developed and justified with the numerical experiment for the metal plane frames.

An examination of loads and responses of a wind turbine undergoing variable-speed operation

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

Wright, A.D.; Buhl, M.L. Jr.; Bir, G.S.

1996-11-01

The National Renewable Energy Laboratory has recently developed the ability to predict turbine loads and responses for machines undergoing variable-speed operation. The wind industry has debated the potential benefits of operating wind turbine sat variable speeds for some time. Turbine system dynamic responses (structural response, resonance, and component interactions) are an important consideration for variable-speed operation of wind turbines. The authors have implemented simple, variable-speed control algorithms for both the FAST and ADAMS dynamics codes. The control algorithm is a simple one, allowing the turbine to track the optimum power coefficient (C{sub p}). The objective of this paper is tomore » show turbine loads and responses for a particular two-bladed, teetering-hub, downwind turbine undergoing variable-speed operation. The authors examined the response of the machine to various turbulent wind inflow conditions. In addition, they compare the structural responses under fixed-speed and variable-speed operation. For this paper, they restrict their comparisons to those wind-speed ranges for which limiting power by some additional control strategy (blade pitch or aileron control, for example) is not necessary. The objective here is to develop a basic understanding of the differences in loads and responses between the fixed-speed and variable-speed operation of this wind turbine configuration.« less

Structure learning in action

PubMed Central

Braun, Daniel A.; Mehring, Carsten; Wolpert, Daniel M.

2010-01-01

‘Learning to learn’ phenomena have been widely investigated in cognition, perception and more recently also in action. During concept learning tasks, for example, it has been suggested that characteristic features are abstracted from a set of examples with the consequence that learning of similar tasks is facilitated—a process termed ‘learning to learn’. From a computational point of view such an extraction of invariants can be regarded as learning of an underlying structure. Here we review the evidence for structure learning as a ‘learning to learn’ mechanism, especially in sensorimotor control where the motor system has to adapt to variable environments. We review studies demonstrating that common features of variable environments are extracted during sensorimotor learning and exploited for efficient adaptation in novel tasks. We conclude that structure learning plays a fundamental role in skill learning and may underlie the unsurpassed flexibility and adaptability of the motor system. PMID:19720086

Variable Complexity Structural Optimization of Shells

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.; Venkataraman, Satchi

1999-01-01

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-2110 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition, several modeling issues for the design of shells of revolution were studied.

Variable Complexity Structural Optimization of Shells

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.; Venkataraman, Satchi

1998-01-01

Structural designers today face both opportunities and challenges in a vast array of available analysis and optimization programs. Some programs such as NASTRAN, are very general, permitting the designer to model any structure, to any degree of accuracy, but often at a higher computational cost. Additionally, such general procedures often do not allow easy implementation of all constraints of interest to the designer. Other programs, based on algebraic expressions used by designers one generation ago, have limited applicability for general structures with modem materials. However, when applicable, they provide easy understanding of design decisions trade-off. Finally, designers can also use specialized programs suitable for designing efficiently a subset of structural problems. For example, PASCO and PANDA2 are panel design codes, which calculate response and estimate failure much more efficiently than general-purpose codes, but are narrowly applicable in terms of geometry and loading. Therefore, the problem of optimizing structures based on simultaneous use of several models and computer programs is a subject of considerable interest. The problem of using several levels of models in optimization has been dubbed variable complexity modeling. Work under NASA grant NAG1-1808 has been concerned with the development of variable complexity modeling strategies with special emphasis on response surface techniques. In addition several modeling issues for the design of shells of revolution were studied.

A fuzzy decision tree for fault classification.

PubMed

Zio, Enrico; Baraldi, Piero; Popescu, Irina C

2008-02-01

In plant accident management, the control room operators are required to identify the causes of the accident, based on the different patterns of evolution of the monitored process variables thereby developing. This task is often quite challenging, given the large number of process parameters monitored and the intense emotional states under which it is performed. To aid the operators, various techniques of fault classification have been engineered. An important requirement for their practical application is the physical interpretability of the relationships among the process variables underpinning the fault classification. In this view, the present work propounds a fuzzy approach to fault classification, which relies on fuzzy if-then rules inferred from the clustering of available preclassified signal data, which are then organized in a logical and transparent decision tree structure. The advantages offered by the proposed approach are precisely that a transparent fault classification model is mined out of the signal data and that the underlying physical relationships among the process variables are easily interpretable as linguistic if-then rules that can be explicitly visualized in the decision tree structure. The approach is applied to a case study regarding the classification of simulated faults in the feedwater system of a boiling water reactor.

ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices.

PubMed

Wilderjans, Tom F; Ceulemans, Eva; Van Mechelen, Iven; Depril, Dirk

2011-03-01

In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin's additive profile clustering model may be appropriate. In this model: (1) each object may belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix.

Reduced variance in monozygous twins for multiple MR parameters: implications for disease studies and the genetic basis of brain structure.

PubMed

Pell, Gaby S; Briellmann, Regula S; Lawrence, Kate M; Glencross, Deborah; Wellard, R Mark; Berkovic, Samuel F; Jackson, Graeme D

2010-01-15

Twin studies offer the opportunity to determine the relative contribution of genes versus environment in traits of interest. Here, we investigate the extent to which variance in brain structure is reduced in monozygous twins with identical genetic make-up. We investigate whether using twins as compared to a control population reduces variability in a number of common magnetic resonance (MR) structural measures, and we investigate the location of areas under major genetic influences. This is fundamental to understanding the benefit of using twins in studies where structure is the phenotype of interest. Twenty-three pairs of healthy MZ twins were compared to matched control pairs. Volume, T2 and diffusion MR imaging were performed as well as spectroscopy (MRS). Images were compared using (i) global measures of standard deviation and effect size, (ii) voxel-based analysis of similarity and (iii) intra-pair correlation. Global measures indicated a consistent increase in structural similarity in twins. The voxel-based and correlation analyses indicated a widespread pattern of increased similarity in twin pairs, particularly in frontal and temporal regions. The areas of increased similarity were most widespread for the diffusion trace and least widespread for T2. MRS showed consistent reduction in metabolite variation that was significant in the temporal lobe N-acetylaspartate (NAA). This study has shown the distribution and magnitude of reduced variability in brain volume, diffusion, T2 and metabolites in twins. The data suggest that evaluation of twins discordant for disease is indeed a valid way to attribute genetic or environmental influences to observed abnormalities in patients since evidence is provided for the underlying assumption of decreased variability in twins.

Variable stiffness corrugated composite structure with shape memory polymer for morphing skin applications

NASA Astrophysics Data System (ADS)

Gong, Xiaobo; Liu, Liwu; Scarpa, Fabrizio; Leng, Jinsong; Liu, Yanju

2017-03-01

This work presents a variable stiffness corrugated structure based on a shape memory polymer (SMP) composite with corrugated laminates as reinforcement that shows smooth aerodynamic surface, extreme mechanical anisotropy and variable stiffness for potential morphing skin applications. The smart composite corrugated structure shows a low in-plane stiffness to minimize the actuation energy, but also possess high out-of-plane stiffness to transfer the aerodynamic pressure load. The skin provides an external smooth aerodynamic surface because of the one-sided filling with the SMP. Due to variable stiffness of the shape memory polymer the morphing skin exhibits a variable stiffness with a change of temperature, which can help the skin adjust its stiffness according different service environments and also lock the temporary shape without external force. Analytical models related to the transverse and bending stiffness are derived and validated using finite element techniques. The stiffness of the morphing skin is further investigated by performing a parametric analysis against the geometry of the corrugation and various sets of SMP fillers. The theoretical and numerical models show a good agreement and demonstrate the potential of this morphing skin concept for morphing aircraft applications. We also perform a feasibility study of the use of this morphing skin in a variable camber morphing wing baseline. The results show that the morphing skin concept exhibits sufficient bending stiffness to withstand the aerodynamic load at low speed (less than 0.3 Ma), while demonstrating a large transverse stiffness variation (up to 191 times) that helps to create a maximum mechanical efficiency of the structure under varying external conditions.

Impact damage resistance of composite fuselage structure, part 2

NASA Technical Reports Server (NTRS)

Dost, Ernest F.; Finn, Scott R.; Murphy, Daniel P.; Huisken, Amy B.

1993-01-01

The strength of laminated composite materials may be significantly reduced by foreign object impact induced damage. An understanding of the damage state is required in order to predict the behavior of structure under operational loads or to optimize the structural configuration. Types of damage typically induced in laminated materials during an impact event include transverse matrix cracking, delamination, and/or fiber breakage. The details of the damage state and its influence on structural behavior depend on the location of the impact. Damage in the skin may act as a soft inclusion or affect panel stability, while damage occurring over a stiffener may include debonding of the stiffener flange from the skin. An experiment to characterize impact damage resistance of fuselage structure as a function of structural configuration and impact threat was performed. A wide range of variables associated with aircraft fuselage structure such as material type and stiffener geometry (termed, intrinsic variables) and variables related to the operating environment such as impactor mass and diameter (termed, extrinsic variables) were studied using a statistically based design-of-experiments technique. The experimental design resulted in thirty-two different 3-stiffener panels. These configured panels were impacted in various locations with a number of impactor configurations, weights, and energies. The results obtained from an examination of impacts in the skin midbay and hail simulation impacts are documented. The current discussion is a continuation of that work with a focus on nondiscrete characterization of the midbay hail simulation impacts and discrete characterization of impact damage for impacts over the stiffener.

Dynamic and structural control utilizing smart materials and structures

NASA Technical Reports Server (NTRS)

Rogers, C. A.; Robertshaw, H. H.

1989-01-01

An account is given of several novel 'smart material' structural control concepts that are currently under development. The thrust of these investigations is the evolution of intelligent materials and structures superceding the recently defined variable-geometry trusses and shape memory alloy-reinforced composites; the substances envisioned will be able to autonomously evaluate emergent environmental conditions and adapt to them, and even change their operational objectives. While until now the primary objective of the developmental efforts presently discussed has been materials that mimic biological functions, entirely novel concepts may be formulated in due course.

Structural variability in neptunium(V) oxalate compounds: synthesis and structural characterization of Na2NpO2(C2O4)OH.H2O.

PubMed

Bean, Amanda C; Garcia, Eduardo; Scott, Brian L; Runde, Wolfgang

2004-10-04

Reaction of a (237)Np(V) stock solution in the presence of oxalic acid, calcium chloride, and sodium hydroxide under hydrothermal conditions produces single crystals of a neptunium(V) oxalate, Na(2)NpO(2)(C(2)O(4))OH.H(2)O. The structure consists of one-dimensional chains running down the a axis and is the first example of a neptunium(V) oxalate compound containing hydroxide anions.

On the Structure of Neuronal Population Activity under Fluctuations in Attentional State

PubMed Central

Denfield, George H.; Bethge, Matthias; Tolias, Andreas S.

2016-01-01

Attention is commonly thought to improve behavioral performance by increasing response gain and suppressing shared variability in neuronal populations. However, both the focus and the strength of attention are likely to vary from one experimental trial to the next, thereby inducing response variability unknown to the experimenter. Here we study analytically how fluctuations in attentional state affect the structure of population responses in a simple model of spatial and feature attention. In our model, attention acts on the neural response exclusively by modulating each neuron's gain. Neurons are conditionally independent given the stimulus and the attentional gain, and correlated activity arises only from trial-to-trial fluctuations of the attentional state, which are unknown to the experimenter. We find that this simple model can readily explain many aspects of neural response modulation under attention, such as increased response gain, reduced individual and shared variability, increased correlations with firing rates, limited range correlations, and differential correlations. We therefore suggest that attention may act primarily by increasing response gain of individual neurons without affecting their correlation structure. The experimentally observed reduction in correlations may instead result from reduced variability of the attentional gain when a stimulus is attended. Moreover, we show that attentional gain fluctuations, even if unknown to a downstream readout, do not impair the readout accuracy despite inducing limited-range correlations, whereas fluctuations of the attended feature can in principle limit behavioral performance. SIGNIFICANCE STATEMENT Covert attention is one of the most widely studied examples of top-down modulation of neural activity in the visual system. Recent studies argue that attention improves behavioral performance by shaping of the noise distribution to suppress shared variability rather than by increasing response gain. Our work shows, however, that latent, trial-to-trial fluctuations of the focus and strength of attention lead to shared variability that is highly consistent with known experimental observations. Interestingly, fluctuations in the strength of attention do not affect coding performance. As a consequence, the experimentally observed changes in response variability may not be a mechanism of attention, but rather a side effect of attentional allocation strategies in different behavioral contexts. PMID:26843656

Quantifying networks complexity from information geometry viewpoint

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

Felice, Domenico, E-mail: domenico.felice@unicam.it; Mancini, Stefano; INFN-Sezione di Perugia, Via A. Pascoli, I-06123 Perugia

We consider a Gaussian statistical model whose parameter space is given by the variances of random variables. Underlying this model we identify networks by interpreting random variables as sitting on vertices and their correlations as weighted edges among vertices. We then associate to the parameter space a statistical manifold endowed with a Riemannian metric structure (that of Fisher-Rao). Going on, in analogy with the microcanonical definition of entropy in Statistical Mechanics, we introduce an entropic measure of networks complexity. We prove that it is invariant under networks isomorphism. Above all, considering networks as simplicial complexes, we evaluate this entropy onmore » simplexes and find that it monotonically increases with their dimension.« less

Topology optimization under stochastic stiffness

NASA Astrophysics Data System (ADS)

Asadpoure, Alireza

Topology optimization is a systematic computational tool for optimizing the layout of materials within a domain for engineering design problems. It allows variation of structural boundaries and connectivities. This freedom in the design space often enables discovery of new, high performance designs. However, solutions obtained by performing the optimization in a deterministic setting may be impractical or suboptimal when considering real-world engineering conditions with inherent variabilities including (for example) variabilities in fabrication processes and operating conditions. The aim of this work is to provide a computational methodology for topology optimization in the presence of uncertainties associated with structural stiffness, such as uncertain material properties and/or structural geometry. Existing methods for topology optimization under deterministic conditions are first reviewed. Modifications are then proposed to improve the numerical performance of the so-called Heaviside Projection Method (HPM) in continuum domains. Next, two approaches, perturbation and Polynomial Chaos Expansion (PCE), are proposed to account for uncertainties in the optimization procedure. These approaches are intrusive, allowing tight and efficient coupling of the uncertainty quantification with the optimization sensitivity analysis. The work herein develops a robust topology optimization framework aimed at reducing the sensitivity of optimized solutions to uncertainties. The perturbation-based approach combines deterministic topology optimization with a perturbation method for the quantification of uncertainties. The use of perturbation transforms the problem of topology optimization under uncertainty to an augmented deterministic topology optimization problem. The PCE approach combines the spectral stochastic approach for the representation and propagation of uncertainties with an existing deterministic topology optimization technique. The resulting compact representations for the response quantities allow for efficient and accurate calculation of sensitivities of response statistics with respect to the design variables. The proposed methods are shown to be successful at generating robust optimal topologies. Examples from topology optimization in continuum and discrete domains (truss structures) under uncertainty are presented. It is also shown that proposed methods lead to significant computational savings when compared to Monte Carlo-based optimization which involve multiple formations and inversions of the global stiffness matrix and that results obtained from the proposed method are in excellent agreement with those obtained from a Monte Carlo-based optimization algorithm.

A stochastic global identification framework for aerospace structures operating under varying flight states

NASA Astrophysics Data System (ADS)

Kopsaftopoulos, Fotis; Nardari, Raphael; Li, Yu-Hung; Chang, Fu-Kuo

2018-01-01

In this work, a novel data-based stochastic "global" identification framework is introduced for aerospace structures operating under varying flight states and uncertainty. In this context, the term "global" refers to the identification of a model that is capable of representing the structure under any admissible flight state based on data recorded from a sample of these states. The proposed framework is based on stochastic time-series models for representing the structural dynamics and aeroelastic response under multiple flight states, with each state characterized by several variables, such as the airspeed, angle of attack, altitude and temperature, forming a flight state vector. The method's cornerstone lies in the new class of Vector-dependent Functionally Pooled (VFP) models which allow the explicit analytical inclusion of the flight state vector into the model parameters and, hence, system dynamics. This is achieved via the use of functional data pooling techniques for optimally treating - as a single entity - the data records corresponding to the various flight states. In this proof-of-concept study the flight state vector is defined by two variables, namely the airspeed and angle of attack of the vehicle. The experimental evaluation and assessment is based on a prototype bio-inspired self-sensing composite wing that is subjected to a series of wind tunnel experiments under multiple flight states. Distributed micro-sensors in the form of stretchable sensor networks are embedded in the composite layup of the wing in order to provide the sensing capabilities. Experimental data collected from piezoelectric sensors are employed for the identification of a stochastic global VFP model via appropriate parameter estimation and model structure selection methods. The estimated VFP model parameters constitute two-dimensional functions of the flight state vector defined by the airspeed and angle of attack. The identified model is able to successfully represent the wing's aeroelastic response under the admissible flight states via a minimum number of estimated parameters compared to standard identification approaches. The obtained results demonstrate the high accuracy and effectiveness of the proposed global identification framework, thus constituting a first step towards the next generation of "fly-by-feel" aerospace vehicles with state awareness capabilities.

The Shock and Vibration Digest. Volume 16, Number 6

DTIC Science & Technology

1984-06-01

formulation is emphasized. Tabarrok [5] used both fluid variables to construct dual variational principles; these can be used as the basis for...Metal Working and Forming 37 STRUCTURAL SYSTEMS 39 Buildings 39 Towers 39 Foundations 40 Harbors and Dams 40 Roads and Tracks 41 Construction ...under the fating. Assuming that the super-structure is composed of idertically constructed story-units and the soil behavior is characterized by a

Wide-range simulation of elastoplastic wave fronts and failure of solids under high-speed loading

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

Saveleva, Natalia, E-mail: saveleva@icmm.ru; Bayandin, Yuriy, E-mail: buv@icmm.ru; Naimark, Oleg, E-mail: naimark@icmm.ru

2015-10-27

The aim of this paper is numerical study of deformation processes and failure of vanadium under shock-wave loading. According developed statistical theory of solid with mesoscopic defects the constitutive equations were proposed in terms of two structural variables characterizing behavior of defects ensembles: defect density tensor and structural scaling parameter. On the basis of wide-range constitutive equations the mathematical model of deformation behavior and failure of vanadium was developed taking into account the bond relaxation mechanisms, multistage of fracture and nonlinearity kinetic of defects. Results of numerical simulation allow the description of the major effects of shock wave propagation (elasticmore » precursor decay, grow of spall strength under grow strain rate)« less

Buckling and Post-Buckling Behaviors of a Variable Stiffness Composite Laminated Wing Box Structure

NASA Astrophysics Data System (ADS)

Wang, Peiyan; Huang, Xinting; Wang, Zhongnan; Geng, Xiaoliang; Wang, Yuansheng

2018-04-01

The buckling and post-buckling behaviors of variable stiffness composite laminates (VSCL) with curvilinear fibers were investigated and compared with constant stiffness composite laminates (CSCL) with straight fibers. A VSCL box structure was evaluated under a pure bending moment. The results of the comparative test showed that the critical buckling load of the VSCL box was approximately 3% higher than that of the CSCL box. However, the post-buckling load-bearing capacity was similar due to the layup angle and the immature status of the material processing technology. The properties of the VSCL and CSCL boxes under a pure bending moment were simulated using the Hashin criterion and cohesive interface elements. The simulation results are consistent with the experimental results in stiffness, critical buckling load and failure modes but not in post-buckling load capacity. The results of the experiment, the simulation and laminated plate theory show that VSCL greatly improves the critical buckling load but has little influence on the post-buckling load-bearing capacity.

Replicates in high dimensions, with applications to latent variable graphical models.

PubMed

Tan, Kean Ming; Ning, Yang; Witten, Daniela M; Liu, Han

2016-12-01

In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in this setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By collecting multiple replicates for each subject, we are able to estimate the conditional dependence relationships among the observed variables given the latent variables. To test the null hypothesis of conditional independence between two observed variables, we propose a pairwise decorrelated score test. Theoretical guarantees are established for parameter estimation and for this test. We show that our proposal is able to estimate latent variable graphical models more accurately than some existing proposals, and apply the proposed method to a brain imaging dataset.

Psychological variables underlying political orientations in an old and a new democracy: A comparative study between Sweden and Latvia.

PubMed

Dimdins, Girts; Sandgren, Maria; Montgomery, Henry

2016-10-01

This study examines in detail the psychological variables underlying ideological political orientation, and structure and contents of this orientation, in Sweden and Latvia. Individual political orientation is conceptualized on two dimensions: acceptance vs. rejection of social change and acceptance vs. rejection of inequality. Swedish (N = 320) and Latvian (N = 264) participants completed measures of political orientation, Social Dominance Orientation (SDO), Right Wing Authoritarianism (RWA), self vs. other orientation, tolerance for ambiguity, humanism and normativism, core political values, system justification, as well as moral foundations questionnaire and portrait values questionnaire. The results showed that the relation among the measured variables was similar in both samples. Swedish participants showed stronger endorsement of egalitarian attitudes and social values, whereas we found more self-enhancing and socially conservative values and attitudes among the Latvian participants. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Higher-order Peregrine combs and Peregrine walls for the variable-coefficient Lenells-Fokas equation

NASA Astrophysics Data System (ADS)

Wang, Zi-Qi; Wang, Xin; Wang, Lei; Sun, Wen-Rong; Qi, Feng-Hua

2017-02-01

In this paper, we study the variable-coefficient Lenells-Fokas (LF) model. Under large periodic modulations in the variable coefficients of the LF model, the generalized Akhmediev breathers develop into the breather multiple births (BMBs) from which we obtain the Peregrine combs (PCs). The PCs can be considered as the limiting case of the BMBs and be transformed into the Peregrine walls (PWs) with a specific amplitude of periodic modulation. We further investigate the spatiotemporal characteristics of the PCs and PWs analytically. Based on the second-order breather and rogue-wave solutions, we derive the corresponding higher-order structures (higher-order PCs and PWs) under proper periodic modulations. What is particularly noteworthy is that the second-order PC can be converted into the Peregrine pyramid which exhibits the higher amplitude and thickness. Our results could be helpful for the design of experiments in the optical fiber communications.

Continuous-variable quantum probes for structured environments

NASA Astrophysics Data System (ADS)

Bina, Matteo; Grasselli, Federico; Paris, Matteo G. A.

2018-01-01

We address parameter estimation for structured environments and suggest an effective estimation scheme based on continuous-variables quantum probes. In particular, we investigate the use of a single bosonic mode as a probe for Ohmic reservoirs, and obtain the ultimate quantum limits to the precise estimation of their cutoff frequency. We assume the probe prepared in a Gaussian state and determine the optimal working regime, i.e., the conditions for the maximization of the quantum Fisher information in terms of the initial preparation, the reservoir temperature, and the interaction time. Upon investigating the Fisher information of feasible measurements, we arrive at a remarkable simple result: homodyne detection of canonical variables allows one to achieve the ultimate quantum limit to precision under suitable, mild, conditions. Finally, upon exploiting a perturbative approach, we find the invariant sweet spots of the (tunable) characteristic frequency of the probe, able to drive the probe towards the optimal working regime.

Buckling of Thermoviscoelastic Structures Under Temporal and Spatial Temperature Variations

NASA Technical Reports Server (NTRS)

Tsuyuki, Richard; Knauss, Wolfgang G.

1992-01-01

The problem of lateral instability of a viscoelastic in-plane loaded structure is considered in terms of thermorheolgically simple materials. As an example of a generally in-plane loaded structure, we examine the simple column under axial load: Both cyclic loading is considered (with constant or in-phase variable temperature excursions) as well as the case of constant load in the presence of thermal gradients through the thickness of the structure. The latter case involves a continuous movement of the neutral axis from the center to the colder side and then back to the center. In both cases, temperature has a very strong effect on the instability evolution, and under in-phase thermal cycling the critical loads are reduced compared to those at constant temperatures. The primary effect of thermal gradients beyond that of thermally-induced rate accelerations is occasioned by the generation of an "initial imperfection" or "structural bowing." Because the coefficient of thermal expansion tends to be large for many polymeric materials, it it may be necessary to take special care in lay-up design of composite structures intended for use under compressive loads in high-temperature applications. Finally, the implications for the temperature sensitivities of composites to micro-instability (fiber crimping) are also apparent from the results delineated here.

The Winds of B Supergiants

NASA Technical Reports Server (NTRS)

Fullerton, A. W.; Massa, D. L.; Prinja, R. K.; Owocki, S. P.; Cranmer, S. R.

1998-01-01

This report summarizes the progress of the work conducted under the program "The Winds of B Supergiants," conducted by Raytheon STX Corporation. The report consists of a journal article "Wind variability in B supergiants III. Corotating spiral structures in the stellar wind of HD 64760." The first step in the project was the analysis of the 1996 time series of 2 B supergiants and an O star. These data were analyzed and reported on at the ESO workshop, "Cyclical Variability in Stellar Winds."

Invertebrate Metacommunity Structure and Dynamics in an Andean Glacial Stream Network Facing Climate Change

PubMed Central

Cauvy-Fraunié, Sophie; Espinosa, Rodrigo; Andino, Patricio; Jacobsen, Dean; Dangles, Olivier

2015-01-01

Under the ongoing climate change, understanding the mechanisms structuring the spatial distribution of aquatic species in glacial stream networks is of critical importance to predict the response of aquatic biodiversity in the face of glacier melting. In this study, we propose to use metacommunity theory as a conceptual framework to better understand how river network structure influences the spatial organization of aquatic communities in glacierized catchments. At 51 stream sites in an Andean glacierized catchment (Ecuador), we sampled benthic macroinvertebrates, measured physico-chemical and food resource conditions, and calculated geographical, altitudinal and glaciality distances among all sites. Using partial redundancy analysis, we partitioned community variation to evaluate the relative strength of environmental conditions (e.g., glaciality, food resource) vs. spatial processes (e.g., overland, watercourse, and downstream directional dispersal) in organizing the aquatic metacommunity. Results revealed that both environmental and spatial variables significantly explained community variation among sites. Among all environmental variables, the glacial influence component best explained community variation. Overland spatial variables based on geographical and altitudinal distances significantly affected community variation. Watercourse spatial variables based on glaciality distances had a unique significant effect on community variation. Within alpine catchment, glacial meltwater affects macroinvertebrate metacommunity structure in many ways. Indeed, the harsh environmental conditions characterizing glacial influence not only constitute the primary environmental filter but also, limit water-borne macroinvertebrate dispersal. Therefore, glacier runoff acts as an aquatic dispersal barrier, isolating species in headwater streams, and preventing non-adapted species to colonize throughout the entire stream network. Under a scenario of glacier runoff decrease, we expect a reduction in both environmental filtering and dispersal limitation, inducing a taxonomic homogenization of the aquatic fauna in glacierized catchments as well as the extinction of specialized species in headwater groundwater and glacier-fed streams, and consequently an irreversible reduction in regional diversity. PMID:26308853

Spatial heterogeneity of within-stream methane concentrations

USGS Publications Warehouse

Crawford, John T.; Loken, Luke C.; West, William E.; Crary, Benjamin; Spawn, Seth A.; Gubbins, Nicholas; Jones, Stuart E.; Striegl, Robert G.; Stanley, Emily H.

2017-01-01

Streams, rivers, and other freshwater features may be significant sources of CH4 to the atmosphere. However, high spatial and temporal variabilities hinder our ability to understand the underlying processes of CH4 production and delivery to streams and also challenge the use of scaling approaches across large areas. We studied a stream having high geomorphic variability to assess the underlying scale of CH4 spatial variability and to examine whether the physical structure of a stream can explain the variation in surface CH4. A combination of high-resolution CH4 mapping, a survey of groundwater CH4 concentrations, quantitative analysis of methanogen DNA, and sediment CH4 production potentials illustrates the spatial and geomorphic controls on CH4 emissions to the atmosphere. We observed significant spatial clustering with high CH4 concentrations in organic-rich stream reaches and lake transitions. These sites were also enriched in the methane-producing mcrA gene and had highest CH4 production rates in the laboratory. In contrast, mineral-rich reaches had significantly lower concentrations and had lesser abundances of mcrA. Strong relationships between CH4and the physical structure of this aquatic system, along with high spatial variability, suggest that future investigations will benefit from viewing streams as landscapes, as opposed to ecosystems simply embedded in larger terrestrial mosaics. In light of such high spatial variability, we recommend that future workers evaluate stream networks first by using similar spatial tools in order to build effective sampling programs.

75 FR 45173 - Notice of Issuance of Regulatory Guide

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-02

... coolant system for measuring process variables (e.g., pressure, level, and flow). The term ``safety- related'' refers to those structures, systems, and components necessary to ensure (1) the integrity of the... are located in the NRC's Agencywide Documents Access and Management System (ADAMS) under Accession No...

Post-Fire Recovery of Eco-Hydrologic Behavior Given Historic and Projected Climate Variability in California Mediterranean Type Environments

NASA Astrophysics Data System (ADS)

Seaby, L. P.; Tague, C. L.; Hope, A. S.

2006-12-01

The Mediterranean type environments (MTEs) of California are characterized by a distinct wet and dry season and high variability in inter-annual climate. Water limitation in MTEs makes eco-hydrological processes highly sensitive to both climate variability and frequent fire disturbance. This research modeled post-fire eco- hydrologic behavior under historical and moderate and extreme scenarios of future climate in a semi-arid chaparral dominated southern California MTE. We used a physically-based, spatially-distributed, eco- hydrological model (RHESSys - Regional Hydro-Ecologic Simulation System), to capture linkages between water and vegetation response to the combined effects of fire and historic and future climate variability. We found post-fire eco-hydrologic behavior to be strongly influenced by the episodic nature of MTE climate, which intensifies under projected climate change. Higher rates of post-fire net primary productivity were found under moderate climate change, while more extreme climate change produced water stressed conditions which were less favorable for vegetation productivity. Precipitation variability in the historic record follows the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), and these inter-annual climate characteristics intensify under climate change. Inter-annual variation in streamflow follows these precipitation patterns. Post-fire streamflow and carbon cycling trajectories are strongly dependent on climate characteristics during the first 5 years following fire, and historic intra-climate variability during this period tends to overwhelm longer term trends and variation that might be attributable to climate change. Results have implications for water resource availability, vegetation type conversion from shrubs to grassland, and changes in ecosystem structure and function.

The role of under-determined approximations in engineering and science application

NASA Technical Reports Server (NTRS)

Carpenter, William C.

1992-01-01

There is currently a great deal of interest in using response surfaces in the optimization of aircraft performance. The objective function and/or constraint equations involved in these optimization problems may come from numerous disciplines such as structures, aerodynamics, environmental engineering, etc. In each of these disciplines, the mathematical complexity of the governing equations usually dictates that numerical results be obtained from large computer programs such as a finite element method program. Thus, when performing optimization studies, response surfaces are a convenient way of transferring information from the various disciplines to the optimization algorithm as opposed to bringing all the sundry computer programs together in a massive computer code. Response surfaces offer another advantage in the optimization of aircraft structures. A characteristic of these types of optimization problems is that evaluation of the objective function and response equations (referred to as a functional evaluation) can be very expensive in a computational sense. Because of the computational expense in obtaining functional evaluations, the present study was undertaken to investigate under-determinined approximations. An under-determined approximation is one in which there are fewer training pairs (pieces of information about a function) than there are undetermined parameters (coefficients or weights) associated with the approximation. Both polynomial approximations and neural net approximations were examined. Three main example problems were investigated: (1) a function of one design variable was considered; (2) a function of two design variables was considered; and (3) a 35 bar truss with 4 design variables was considered.

Systematic review of the neural basis of social cognition in patients with mood disorders.

PubMed

Cusi, Andrée M; Nazarov, Anthony; Holshausen, Katherine; Macqueen, Glenda M; McKinnon, Margaret C

2012-05-01

This review integrates neuroimaging studies of 2 domains of social cognition--emotion comprehension and theory of mind (ToM)--in patients with major depressive disorder and bipolar disorder. The influence of key clinical and method variables on patterns of neural activation during social cognitive processing is also examined. Studies were identified using PsycINFO and PubMed (January 1967 to May 2011). The search terms were "fMRI," "emotion comprehension," "emotion perception," "affect comprehension," "affect perception," "facial expression," "prosody," "theory of mind," "mentalizing" and "empathy" in combination with "major depressive disorder," "bipolar disorder," "major depression," "unipolar depression," "clinical depression" and "mania." Taken together, neuroimaging studies of social cognition in patients with mood disorders reveal enhanced activation in limbic and emotion-related structures and attenuated activity within frontal regions associated with emotion regulation and higher cognitive functions. These results reveal an overall lack of inhibition by higher-order cognitive structures on limbic and emotion-related structures during social cognitive processing in patients with mood disorders. Critically, key variables, including illness burden, symptom severity, comorbidity, medication status and cognitive load may moderate this pattern of neural activation. Studies that did not include control tasks or a comparator group were included in this review. Further work is needed to examine the contribution of key moderator variables and to further elucidate the neural networks underlying altered social cognition in patients with mood disorders. The neural networks under lying higher-order social cognitive processes, including empathy, remain unexplored in patients with mood disorders.

Displacement based multilevel structural optimization

NASA Technical Reports Server (NTRS)

Striz, Alfred G.

1995-01-01

Multidisciplinary design optimization (MDO) is expected to play a major role in the competitive transportation industries of tomorrow, i.e., in the design of aircraft and spacecraft, of high speed trains, boats, and automobiles. All of these vehicles require maximum performance at minimum weight to keep fuel consumption low and conserve resources. Here, MDO can deliver mathematically based design tools to create systems with optimum performance subject to the constraints of disciplines such as structures, aerodynamics, controls, etc. Although some applications of MDO are beginning to surface, the key to a widespread use of this technology lies in the improvement of its efficiency. This aspect is investigated here for the MDO subset of structural optimization, i.e., for the weight minimization of a given structure under size, strength, and displacement constraints. Specifically, finite element based multilevel optimization of structures (here, statically indeterminate trusses and beams for proof of concept) is performed. In the system level optimization, the design variables are the coefficients of assumed displacement functions, and the load unbalance resulting from the solution of the stiffness equations is minimized. Constraints are placed on the deflection amplitudes and the weight of the structure. In the subsystems level optimizations, the weight of each element is minimized under the action of stress constraints, with the cross sectional dimensions as design variables. This approach is expected to prove very efficient, especially for complex structures, since the design task is broken down into a large number of small and efficiently handled subtasks, each with only a small number of variables. This partitioning will also allow for the use of parallel computing, first, by sending the system and subsystems level computations to two different processors, ultimately, by performing all subsystems level optimizations in a massively parallel manner on separate processors. It is expected that the subsystems level optimizations can be further improved through the use of controlled growth, a method which reduces an optimization to a more efficient analysis with only a slight degradation in accuracy. The efficiency of all proposed techniques is being evaluated relative to the performance of the standard single level optimization approach where the complete structure is weight minimized under the action of all given constraints by one processor and to the performance of simultaneous analysis and design which combines analysis and optimization into a single step. It is expected that the present approach can be expanded to include additional structural constraints (buckling, free and forced vibration, etc.) or other disciplines (passive and active controls, aerodynamics, etc.) for true MDO.

Design for cyclic loading endurance of composites

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Murthy, Pappu L. N.; Chamis, Christos C.; Liaw, Leslie D. G.

1993-01-01

The application of the computer code IPACS (Integrated Probabilistic Assessment of Composite Structures) to aircraft wing type structures is described. The code performs a complete probabilistic analysis for composites taking into account the uncertainties in geometry, boundary conditions, material properties, laminate lay-ups, and loads. Results of the analysis are presented in terms of cumulative distribution functions (CDF) and probability density function (PDF) of the fatigue life of a wing type composite structure under different hygrothermal environments subjected to the random pressure. The sensitivity of the fatigue life to a number of critical structural/material variables is also computed from the analysis.

A Damage Model for the Simulation of Delamination in Advanced Composites under Variable-Mode Loading

NASA Technical Reports Server (NTRS)

Turon, A.; Camanho, P. P.; Costa, J.; Davila, C. G.

2006-01-01

A thermodynamically consistent damage model is proposed for the simulation of progressive delamination in composite materials under variable-mode ratio. The model is formulated in the context of Damage Mechanics. A novel constitutive equation is developed to model the initiation and propagation of delamination. A delamination initiation criterion is proposed to assure that the formulation can account for changes in the loading mode in a thermodynamically consistent way. The formulation accounts for crack closure effects to avoid interfacial penetration of two adjacent layers after complete decohesion. The model is implemented in a finite element formulation, and the numerical predictions are compared with experimental results obtained in both composite test specimens and structural components.

Bioinformatics and variability in drug response: a protein structural perspective

PubMed Central

Lahti, Jennifer L.; Tang, Grace W.; Capriotti, Emidio; Liu, Tianyun; Altman, Russ B.

2012-01-01

Marketed drugs frequently perform worse in clinical practice than in the clinical trials on which their approval is based. Many therapeutic compounds are ineffective for a large subpopulation of patients to whom they are prescribed; worse, a significant fraction of patients experience adverse effects more severe than anticipated. The unacceptable risk–benefit profile for many drugs mandates a paradigm shift towards personalized medicine. However, prior to adoption of patient-specific approaches, it is useful to understand the molecular details underlying variable drug response among diverse patient populations. Over the past decade, progress in structural genomics led to an explosion of available three-dimensional structures of drug target proteins while efforts in pharmacogenetics offered insights into polymorphisms correlated with differential therapeutic outcomes. Together these advances provide the opportunity to examine how altered protein structures arising from genetic differences affect protein–drug interactions and, ultimately, drug response. In this review, we first summarize structural characteristics of protein targets and common mechanisms of drug interactions. Next, we describe the impact of coding mutations on protein structures and drug response. Finally, we highlight tools for analysing protein structures and protein–drug interactions and discuss their application for understanding altered drug responses associated with protein structural variants. PMID:22552919

Durability reliability analysis for corroding concrete structures under uncertainty

NASA Astrophysics Data System (ADS)

Zhang, Hao

2018-02-01

This paper presents a durability reliability analysis of reinforced concrete structures subject to the action of marine chloride. The focus is to provide insight into the role of epistemic uncertainties on durability reliability. The corrosion model involves a number of variables whose probabilistic characteristics cannot be fully determined due to the limited availability of supporting data. All sources of uncertainty, both aleatory and epistemic, should be included in the reliability analysis. Two methods are available to formulate the epistemic uncertainty: the imprecise probability-based method and the purely probabilistic method in which the epistemic uncertainties are modeled as random variables. The paper illustrates how the epistemic uncertainties are modeled and propagated in the two methods, and shows how epistemic uncertainties govern the durability reliability.

Ecohydrological Responses of Dense Canopies to Environmental Variability Part 2: Role of Acclimation Under Elevated CO2

USDA-ARS?s Scientific Manuscript database

The ability to accurately predict land-atmosphere exchange of mass, energy, and momentum over the coming century requires the consideration of plant biochemical, ecophysiological and structural acclimation to modifications of the ambient environment. Amongst the most important environmental changes ...

Exploration and confirmation of the latent variable structure of the Jefferson scale of empathy

PubMed Central

LaNoue, Marianna

2014-01-01

Objectives: To reaffirm the underlying components of the JSE by using exploratory factor analysis (EFA), and to confirm its latent variable structure by using confirmatory factor analysis (CFA). Methods Research participants included 2,612 medical students who entered Jefferson Medical College between 2002 and 2012. This sample was divided into two groups: Matriculants between 2002 and 2007 (n=1,380) and between 2008 and 2012 (n=1,232). Data for 2002-2007 matriculants were subjected to EFA (principal component factor extraction), and data for matriculants of 2008-2012 were used for CFA (structural equation modeling, and root mean square error for approximation). Results The EFA resulted in three factors: “perspective-taking,” “compassionate care” and “walking in patient’s shoes” replicating the 3-factor model reported in most of the previous studies. The CFA showed that the 3-factor model was an acceptable fit, thus confirming the latent variable structure emerged in the EFA. Corrected item-total score correlations for the total sample were all positive and statistically significant, ranging from 0.13 to 0.61 with a median of 0.44 (p<0.01). The item discrimination effect size indices (contrasting item mean scores for the top-third versus bottom-third JSE scorers) ranged from 0.50 to 1.4 indicating that the differences in item mean scores between top and bottom scorers on the JSE were of practical importance. Cronbach’s alpha coefficient of the JSE for the total sample was 0.80, ranging from 0.75 to 0.84 for matriculatnts of different years. Conclusions Findings provided further support for underlying constructs of the JSE, adding to its credibility. PMID:25341215

On the generation of climate model ensembles

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy; Phipps, Steven J.

2014-10-01

Climate model ensembles are used to estimate uncertainty in future projections, typically by interpreting the ensemble distribution for a particular variable probabilistically. There are, however, different ways to produce climate model ensembles that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the ensemble distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate ensembles: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 ensemble for comparison, we show that initial conditions ensembles, in theory representing internal variability, significantly underestimate observed variance. Structural ensembles, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model ensembles may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where ensembles are over- or under-dispersive, such as for the CMIP5 ensemble, estimates of uncertainty need to be treated with care.

Opto-mechanical analysis of nonlinear elastomer membrane deformation under hydraulic pressure for variable-focus liquid-filled microlenses.

PubMed

Choi, Seung Tae; Son, Byeong Soo; Seo, Gye Won; Park, Si-Young; Lee, Kyung-Sick

2014-03-10

Nonlinear large deformation of a transparent elastomer membrane under hydraulic pressure was analyzed to investigate its optical performance for a variable-focus liquid-filled membrane microlens. In most membrane microlenses, actuators control the hydraulic pressure of optical fluid so that the elastomer membrane together with the internal optical fluid changes its shape, which alters the light path of the microlens to adapt its optical power. A fluid-structure interaction simulation was performed to estimate the transient behavior of the microlens under the operation of electroactive polymer actuators, demonstrating that the viscosity of the optical fluid successfully stabilizes the fluctuations within a fairly short period of time during dynamic operations. Axisymmetric nonlinear plate theory was used to calculate the deformation profile of the membrane under hydrostatic pressure, with which optical characteristics of the membrane microlens were estimated. The effects of gravitation and viscoelastic behavior of the elastomer membrane on the optical performance of the membrane microlens were also evaluated with finite element analysis.

Optical Sensing of the Fatigue Damage State of CFRP under Realistic Aeronautical Load Sequences

PubMed Central

Zuluaga-Ramírez, Pablo; Arconada, Álvaro; Frövel, Malte; Belenguer, Tomás; Salazar, Félix

2015-01-01

We present an optical sensing methodology to estimate the fatigue damage state of structures made of carbon fiber reinforced polymer (CFRP), by measuring variations on the surface roughness. Variable amplitude loads (VAL), which represent realistic loads during aeronautical missions of fighter aircraft (FALSTAFF) have been applied to coupons until failure. Stiffness degradation and surface roughness variations have been measured during the life of the coupons obtaining a Pearson correlation of 0.75 between both variables. The data were compared with a previous study for Constant Amplitude Load (CAL) obtaining similar results. Conclusions suggest that the surface roughness measured in strategic zones is a useful technique for structural health monitoring of CFRP structures, and that it is independent of the type of load applied. Surface roughness can be measured in the field by optical techniques such as speckle, confocal perfilometers and interferometry, among others. PMID:25760056

Grain Refinement of AZ31 Magnesium Alloy Weldments by AC Pulsing Technique

NASA Astrophysics Data System (ADS)

Kishore Babu, N.; Cross, C. E.

2012-11-01

The current study has investigated the influence of alternating current pulsing on the structure and mechanical properties of AZ31 magnesium alloy gas tungsten arc (GTA) weldments. Autogenous full penetration bead-on-plate GTA welds were made under a variety of conditions including variable polarity (VP), variable polarity mixed (VPM), alternating current (AC), and alternating current pulsing (ACPC). AC pulsing resulted in significant refinement of weld metal when compared with the unpulsed conditions. AC pulsing leads to relatively finer and more equiaxed grain structure in GTA welds. In contrast, VP, VPM, and AC welding resulted in predominantly columnar grain structures. The reason for this grain refinement may be attributed to the periodic variations in temperature gradient and solidification rate associated with pulsing as well as weld pool oscillation observed in the ACPC welds. The observed grain refinement was shown to result in an appreciable increase in fusion zone hardness, tensile strength, and ductility.

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

Interferometry in the era of time-domain astronomy

NASA Astrophysics Data System (ADS)

Schaefer, Gail H.; Cassan, Arnaud; Gallenne, Alexandre; Roettenbacher, Rachael M.; Schneider, Jean

2018-04-01

The physical nature of time variable objects is often inferred from photometric light-curves and spectroscopic variations. Long-baseline optical interferometry has the power to resolve the spatial structure of time variable sources directly in order to measure their physical properties and test the physics of the underlying models. Recent interferometric studies of variable objects include measuring the angular expansion and spatial structure during the early stages of novae outbursts, studying the transits and tidal distortions of the components in eclipsing and interacting binaries, measuring the radial pulsations in Cepheid variables, monitoring changes in the circumstellar discs around rapidly rotating massive stars, and imaging starspots. Future applications include measuring the image size and centroid displacements in gravitational microlensing events, and imaging the transits of exoplanets. Ongoing and upcoming photometric surveys will dramatically increase the number of time-variable objects detected each year, providing many potential targets to observe interferometrically. For short-lived transient events, it is critical for interferometric arrays to have the flexibility to respond rapidly to targets of opportunity and optimize the selection of baselines and beam combiners to provide the necessary resolution and sensitivity to resolve the source as its brightness and size change. We discuss the science opportunities made possible by resolving variable sources using long baseline optical interferometry.

Time-variant random interval natural frequency analysis of structures

NASA Astrophysics Data System (ADS)

Wu, Binhua; Wu, Di; Gao, Wei; Song, Chongmin

2018-02-01

This paper presents a new robust method namely, unified interval Chebyshev-based random perturbation method, to tackle hybrid random interval structural natural frequency problem. In the proposed approach, random perturbation method is implemented to furnish the statistical features (i.e., mean and standard deviation) and Chebyshev surrogate model strategy is incorporated to formulate the statistical information of natural frequency with regards to the interval inputs. The comprehensive analysis framework combines the superiority of both methods in a way that computational cost is dramatically reduced. This presented method is thus capable of investigating the day-to-day based time-variant natural frequency of structures accurately and efficiently under concrete intrinsic creep effect with probabilistic and interval uncertain variables. The extreme bounds of the mean and standard deviation of natural frequency are captured through the embedded optimization strategy within the analysis procedure. Three particularly motivated numerical examples with progressive relationship in perspective of both structure type and uncertainty variables are demonstrated to justify the computational applicability, accuracy and efficiency of the proposed method.

Creep and cracking of concrete hinges: insight from centric and eccentric compression experiments.

PubMed

Schlappal, Thomas; Schweigler, Michael; Gmainer, Susanne; Peyerl, Martin; Pichler, Bernhard

2017-01-01

Existing design guidelines for concrete hinges consider bending-induced tensile cracking, but the structural behavior is oversimplified to be time-independent. This is the motivation to study creep and bending-induced tensile cracking of initially monolithic concrete hinges systematically. Material tests on plain concrete specimens and structural tests on marginally reinforced concrete hinges are performed. The experiments characterize material and structural creep under centric compression as well as bending-induced tensile cracking and the interaction between creep and cracking of concrete hinges. As for the latter two aims, three nominally identical concrete hinges are subjected to short-term and to longer-term eccentric compression tests. Obtained material and structural creep functions referring to centric compression are found to be very similar. The structural creep activity under eccentric compression is significantly larger because of the interaction between creep and cracking, i.e. bending-induced cracks progressively open and propagate under sustained eccentric loading. As for concrete hinges in frame-like integral bridge construction, it is concluded (i) that realistic simulation of variable loads requires consideration of the here-studied time-dependent behavior and (ii) that permanent compressive normal forces shall be limited by 45% of the ultimate load carrying capacity, in order to avoid damage of concrete hinges under sustained loading.

Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability.

PubMed

Wei, Luqing; Chen, Hong; Wu, Guo-Rong

2018-01-01

The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability.

[Diversity of parasitic protozoan mitochondria and adaptive evolution].

PubMed

Tian, Hai-Feng; Wen, Jian-Fan

2010-02-01

Eukaryotic mitochondrion generally possess a definite and canonical structure and function. However, in the unicellular parasitic protozoa, various atypical mitochondria with respect to the number, structure, and function, have been discovered consecutively, revealing the variability, plasticity and rich diversity of mitochondrion. Here, we review the mitochondrial diversity in diverse parasitic protozoa, and the underlying reason for such diversity--the adaptive evolution of mitochondrion to the micro-oxygen or anaero parasitic environment of these parasites is also analyzed and discussed.

The structure of pairwise correlation in mouse primary visual cortex reveals functional organization in the absence of an orientation map.

PubMed

Denman, Daniel J; Contreras, Diego

2014-10-01

Neural responses to sensory stimuli are not independent. Pairwise correlation can reduce coding efficiency, occur independent of stimulus representation, or serve as an additional channel of information, depending on the timescale of correlation and the method of decoding. Any role for correlation depends on its magnitude and structure. In sensory areas with maps, like the orientation map in primary visual cortex (V1), correlation is strongly related to the underlying functional architecture, but it is unclear whether this correlation structure is an essential feature of the system or arises from the arrangement of cells in the map. We assessed the relationship between functional architecture and pairwise correlation by measuring both synchrony and correlated spike count variability in mouse V1, which lacks an orientation map. We observed significant pairwise synchrony, which was organized by distance and relative orientation preference between cells. We also observed nonzero correlated variability in both the anesthetized (0.16) and awake states (0.18). Our results indicate that the structure of pairwise correlation is maintained in the absence of an underlying anatomical organization and may be an organizing principle of the mammalian visual system preserved by nonrandom connectivity within local networks. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Biomechanical mechanism of lateral trunk lean gait for knee osteoarthritis patients.

PubMed

Tokuda, Kazuki; Anan, Masaya; Takahashi, Makoto; Sawada, Tomonori; Tanimoto, Kenji; Kito, Nobuhiro; Shinkoda, Koichi

2018-01-03

The biomechanical mechanism of lateral trunk lean gait employed to reduce external knee adduction moment (KAM) for knee osteoarthritis (OA) patients is not well known. This mechanism may relate to the center of mass (COM) motion. Moreover, lateral trunk lean gait may affect motor control of the COM displacement. Uncontrolled manifold (UCM) analysis is an evaluation index used to understand motor control and variability of the motor task. Here we aimed to clarify the biomechanical mechanism to reduce KAM during lateral trunk lean gait and how motor variability controls the COM displacement. Twenty knee OA patients walked under two conditions: normal and lateral trunk lean gait conditions. UCM analysis was performed with respect to the COM displacement in the frontal plane. We also determined how the variability is structured with regards to the COM displacement as a performance variable. The peak KAM under lateral trunk lean gait was lower than that under normal gait. The reduced peak KAM observed was accompanied by medially shifted knee joint center, shortened distance of the center of pressure to knee joint center, and shortened distance of the knee-ground reaction force lever arm during the stance phase. Knee OA patients with lateral trunk lean gait could maintain kinematic synergy by utilizing greater segmental configuration variance to the performance variable. However, the COM displacement variability of lateral trunk lean gait was larger than that of normal gait. Our findings may provide clinical insights to effectively evaluate and prescribe gait modification training for knee OA patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Programmable thermal emissivity structures based on bioinspired self-shape materials

NASA Astrophysics Data System (ADS)

Athanasopoulos, N.; Siakavellas, N. J.

2015-12-01

Programmable thermal emissivity structures based on the bioinspired self-shape anisotropic materials were developed at macro-scale, and further studied theoretically at smaller scale. We study a novel concept, incorporating materials that are capable of transforming their shape via microstructural rearrangements under temperature stimuli, while avoiding the use of exotic shape memory materials or complex micro-mechanisms. Thus, programmed thermal emissivity behaviour of a surface is achievable. The self-shape structure reacts according to the temperature of the surrounding environment or the radiative heat flux. A surface which incorporates self-shape structures can be designed to quickly absorb radiative heat energy at low temperature levels, but is simultaneously capable of passively controlling its maximum temperature in order to prevent overheating. It resembles a “game” of colours, where two or more materials coexist with different values of thermal emissivity/ absorptivity/ reflectivity. The transformation of the structure conceals or reveals one of the materials, creating a surface with programmable - and therefore, variable- effective thermal emissivity. Variable thermal emissivity surfaces may be developed with a total hemispherical emissivity ratio (ɛEff_H/ɛEff_L) equal to 28.

Programmable thermal emissivity structures based on bioinspired self-shape materials

PubMed Central

Athanasopoulos, N.; Siakavellas, N. J.

2015-01-01

Programmable thermal emissivity structures based on the bioinspired self-shape anisotropic materials were developed at macro-scale, and further studied theoretically at smaller scale. We study a novel concept, incorporating materials that are capable of transforming their shape via microstructural rearrangements under temperature stimuli, while avoiding the use of exotic shape memory materials or complex micro-mechanisms. Thus, programmed thermal emissivity behaviour of a surface is achievable. The self-shape structure reacts according to the temperature of the surrounding environment or the radiative heat flux. A surface which incorporates self-shape structures can be designed to quickly absorb radiative heat energy at low temperature levels, but is simultaneously capable of passively controlling its maximum temperature in order to prevent overheating. It resembles a “game” of colours, where two or more materials coexist with different values of thermal emissivity/ absorptivity/ reflectivity. The transformation of the structure conceals or reveals one of the materials, creating a surface with programmable – and therefore, variable- effective thermal emissivity. Variable thermal emissivity surfaces may be developed with a total hemispherical emissivity ratio (εEff_H/εEff_L) equal to 28. PMID:26635316

Body size as a latent variable in a structural equation model: thermal acclimation and energetics of the leaf-eared mouse.

PubMed

Nespolo, Roberto F; Arim, Matías; Bozinovic, Francisco

2003-07-01

Body size is one of the most important determinants of energy metabolism in mammals. However, the usual physiological variables measured to characterize energy metabolism and heat dissipation in endotherms are strongly affected by thermal acclimation, and are also correlated among themselves. In addition to choosing the appropriate measurement of body size, these problems create additional complications when analyzing the relationships among physiological variables such as basal metabolism, non-shivering thermogenesis, thermoregulatory maximum metabolic rate and minimum thermal conductance, body size dependence, and the effect of thermal acclimation on them. We measured these variables in Phyllotis darwini, a murid rodent from central Chile, under conditions of warm and cold acclimation. In addition to standard statistical analyses to determine the effect of thermal acclimation on each variable and the body-mass-controlled correlation among them, we performed a Structural Equation Modeling analysis to evaluate the effects of three different measurements of body size (body mass, m(b); body length, L(b) and foot length, L(f)) on energy metabolism and thermal conductance. We found that thermal acclimation changed the correlation among physiological variables. Only cold-acclimated animals supported our a priori path models, and m(b) appeared to be the best descriptor of body size (compared with L(b) and L(f)) when dealing with energy metabolism and thermal conductance. However, while m(b) appeared to be the strongest determinant of energy metabolism, there was an important and significant contribution of L(b) (but not L(f)) to thermal conductance. This study demonstrates how additional information can be drawn from physiological ecology and general organismal studies by applying Structural Equation Modeling when multiple variables are measured in the same individuals.

Riparian vegetation structure under desertification scenarios

NASA Astrophysics Data System (ADS)

Rosário Fernandes, M.; Segurado, Pedro; Jauch, Eduardo; Ferreira, M. Teresa

2015-04-01

Riparian areas are responsible for many ecological and ecosystems services, including the filtering function, that are considered crucial to the preservation of water quality and social benefits. The main goal of this study is to quantify and understand the riparian variability under desertification scenario(s) and identify the optimal riparian indicators for water scarcity and droughts (WS&D), henceforth improving river basin management. This study was performed in the Iberian Tâmega basin, using riparian woody patches, mapped by visual interpretation on Google Earth imagery, along 130 Sampling Units of 250 m long river stretches. Eight riparian structural indicators, related with lateral dimension, weighted area and shape complexity of riparian patches were calculated using Patch Analyst extension for ArcGis 10. A set of 29 hydrological, climatic, and hydrogeomorphological variables were computed, by a water modelling system (MOHID), using monthly meteorological data between 2008 and 2014. Land-use classes were also calculated, in a 250m-buffer surrounding each sampling unit, using a classification based system on Corine Land Cover. Boosted Regression Trees identified Mean-width (MW) as the optimal riparian indicator for water scarcity and drought, followed by the Weighted Class Area (WCA) (classification accuracy =0.79 and 0.69 respectively). Average Flow and Strahler number were consistently selected, by all boosted models, as the most important explanatory variables. However, a combined effect of hidrogeomorphology and land-use can explain the high variability found in the riparian width mainly in Tâmega tributaries. Riparian patches are larger towards Tâmega river mouth although with lower shape complexity, probably related with more continuous and almost monospecific stands. Climatic, hydrological and land use scenarios, singly and combined, were used to quantify the riparian variability responding to these changes, and to assess the loss of riparian functions such as nutrient incorporation and sediment flux alterations.

Computational Discovery of New Materials Under Pressure

NASA Astrophysics Data System (ADS)

Zurek, Eva

The pressure variable opens the door towards the synthesis of materials with unique properties, ie. superconductivity, hydrogen storage media, high-energy density and superhard materials, to name a few. Indeed, recently superconductivity has been observed below 203 K and 103 K in samples of compressed sulfur dihydride and phosphine, respectively. Under pressure elements that would not normally combine may form stable compounds, or may mix in novel proportions. As a result using our chemical intuition developed at 1 atm to theoretically predict stable phases is bound to fail. In order to enable our search for superconducting hydrogen-rich systems under pressure, we have developed XtalOpt, an open-source evolutionary algorithm for crystal structure prediction. New advances in XtalOpt that enable the prediction of unit cells with greater complexity will be described. XtalOpt has been employed to find the most stable structures of hydrides with unique stoichiometries under pressure. The electronic structure and bonding of the predicted phases has been analyzed by detailed first-principles calculations based on density functional theory. The results of our computational experiments are helping us to build chemical and physical intuition for compressed solids.

On solitons: the biomolecular nonlinear transmission line models with constant and time variable coefficients

NASA Astrophysics Data System (ADS)

Raza, Nauman; Murtaza, Isma Ghulam; Sial, Sultan; Younis, Muhammad

2018-07-01

The article studies the dynamics of solitons in electrical microtubule ? model, which describes the propagation of waves in nonlinear dynamical system. Microtubules are not only a passive support of a cell but also they have highly dynamic structures involved in cell motility, intracellular transport and signaling. The underlying model has been considered with constant and variable coefficients of time function. The solitary wave ansatz has been applied successfully to extract these solitons. The corresponding integrability criteria, also known as constraint conditions, naturally emerge from the analysis of these models.

Fast and Accurate Multivariate Gaussian Modeling of Protein Families: Predicting Residue Contacts and Protein-Interaction Partners

PubMed Central

Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea

2014-01-01

In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code. PMID:24663061

Education as Anti-Structure: Non-Formal Education in Social and Ethnic Movements.

ERIC Educational Resources Information Center

Paulston, Rolland G.

The article describes how folk educational programs in the United States and in the Scandinavian countries work toward behavioral and social change efforts. The conditions under which collective change efforts create their own educational programs, the most effective pedagogical processes, and the variables associated with successful attempts to…

A Cross-Cultural Study of the Motivation of Students Learning a Second Language.

ERIC Educational Resources Information Center

Benjamin, Jane; Chen, Yih-Lan E.

This study examined the underlying factor structure of the Motivation Orientation Scale (MOS), determining its degree of consistency across two distinct cultures and identifying variables affecting students' motivation in learning a second language. The study investigated how intention theory with its three motivation orientations, and Gardner's…

Wrinkle-free design of thin membrane structures using stress-based topology optimization

NASA Astrophysics Data System (ADS)

Luo, Yangjun; Xing, Jian; Niu, Yanzhuang; Li, Ming; Kang, Zhan

2017-05-01

Thin membrane structures would experience wrinkling due to local buckling deformation when compressive stresses are induced in some regions. Using the stress criterion for membranes in wrinkled and taut states, this paper proposed a new stress-based topology optimization methodology to seek the optimal wrinkle-free design of macro-scale thin membrane structures under stretching. Based on the continuum model and linearly elastic assumption in the taut state, the optimization problem is defined as to maximize the structural stiffness under membrane area and principal stress constraints. In order to make the problem computationally tractable, the stress constraints are reformulated into equivalent ones and relaxed by a cosine-type relaxation scheme. The reformulated optimization problem is solved by a standard gradient-based algorithm with the adjoint-variable sensitivity analysis. Several examples with post-bulking simulations and experimental tests are given to demonstrate the effectiveness of the proposed optimization model for eliminating stress-related wrinkles in the novel design of thin membrane structures.

Negative Mood and Obsessive-Compulsive Related Clinical Constructs: An Examination of Underlying Factors

PubMed Central

Britton, Gary I.; Davey, Graham C. L.

2017-01-01

Emerging evidence suggests that many of the clinical constructs used to help understand and explain obsessive-compulsive (OC) symptoms, and negative mood, may be causally interrelated. One approach to understanding this interrelatedness is a motivational systems approach. This approach suggests that rather than considering clinical constructs and negative affect as separable entities, they are all features of an integrated threat management system, and as such are highly coordinated and interdependent. The aim of the present study was to examine if clinical constructs related to OC symptoms and negative mood are best treated as separable or, alternatively, if these clinical constructs and negative mood are best seen as indicators of an underlying superordinate variable, as would be predicted by a motivational systems approach. A sample of 370 student participants completed measures of mood and the clinical constructs of inflated responsibility, intolerance of uncertainty, not just right experiences, and checking stop rules. An exploratory factor analysis suggested two plausible factor structures, one where all construct items and negative mood items loaded onto one underlying superordinate variable, and a second structure comprising of five factors, where each item loaded onto a factor representative of what the item was originally intended to measure. A confirmatory factor analysis showed that the five factor model was preferential to the one factor model, suggesting the four constructs and negative mood are best conceptualized as separate variables. Given the predictions of a motivational systems approach were not supported in the current study, other possible explanations for the causal interrelatedness between clinical constructs and negative mood are discussed. PMID:28959224

Probabilistic evaluation of SSME structural components

NASA Astrophysics Data System (ADS)

Rajagopal, K. R.; Newell, J. F.; Ho, H.

1991-05-01

The application is described of Composite Load Spectra (CLS) and Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) family of computer codes to the probabilistic structural analysis of four Space Shuttle Main Engine (SSME) space propulsion system components. These components are subjected to environments that are influenced by many random variables. The applications consider a wide breadth of uncertainties encountered in practice, while simultaneously covering a wide area of structural mechanics. This has been done consistent with the primary design requirement for each component. The probabilistic application studies are discussed using finite element models that have been typically used in the past in deterministic analysis studies.

Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. I: Spike Generating Models on Converging Motifs

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons and synapses as well as the randomness of connection details, spike trains typically exhibit variability such as spatial randomness and temporal stochasticity, resulting in variability of synaptic changes under plasticity, which we call efficacy variability. How the variability of spike trains influences the efficacy variability of synapses remains unclear. In this paper, we try to understand this influence under pair-wise additive spike-timing dependent plasticity (STDP) when the mean strength of plastic synapses into a neuron is bounded (synaptic homeostasis). Specifically, we systematically study, analytically and numerically, how four aspects of statistical features, i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations, as well as their interactions influence the efficacy variability in converging motifs (simple networks in which one neuron receives from many other neurons). Neurons (including the post-synaptic neuron) in a converging motif generate spikes according to statistical models with tunable parameters. In this way, we can explicitly control the statistics of the spike patterns, and investigate their influence onto the efficacy variability, without worrying about the feedback from synaptic changes onto the dynamics of the post-synaptic neuron. We separate efficacy variability into two parts: the drift part (DriftV) induced by the heterogeneity of change rates of different synapses, and the diffusion part (DiffV) induced by weight diffusion caused by stochasticity of spike trains. Our main findings are: (1) synchronous firing and burstiness tend to increase DiffV, (2) heterogeneity of rates induces DriftV when potentiation and depression in STDP are not balanced, and (3) heterogeneity of cross-correlations induces DriftV together with heterogeneity of rates. We anticipate our work important for understanding functional processes of neuronal networks (such as memory) and neural development. PMID:26941634

Using structural equation modeling to investigate relationships among ecological variables

USGS Publications Warehouse

Malaeb, Z.A.; Kevin, Summers J.; Pugesek, B.H.

2000-01-01

Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude -0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0.1258. Natural variability had a positive direct effect on biodiversity of magnitude 0.5347 and a negative indirect effect mediated through growth potential of magnitude -0.1105 yielding a positive total effects of magnitude 0.4242. Sediment contamination had a negative direct effect on biodiversity of magnitude -0.1956 and a negative indirect effect on growth potential via biodiversity of magnitude -0.067. Biodiversity had a positive effect on growth potential of magnitude 0.8432, and growth potential had a positive effect on biodiversity of magnitude 0.3398. The correlation between biodiversity and growth potential was estimated at 0.7658 and that between sediment contamination and natural variability at -0.3769.

Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

USGS Publications Warehouse

Row, Jeffrey R.; Knick, Steven T.; Oyler-McCance, Sara J.; Lougheed, Stephen C.; Fedy, Bradley C.

2017-01-01

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

Great influence of geographic isolation on the genetic differentiation of Myriophyllum spicatum under a steep environmental gradient

PubMed Central

Wu, Zhigang; Yu, Dan; Wang, Zhong; Li, Xing; Xu, Xinwei

2015-01-01

Understanding how natural processes affect population genetic structures is an important issue in evolutionary biology. One effective method is to assess the relative importance of environmental and geographical factors in the genetic structure of populations. In this study, we examined the spatial genetic variation of thirteen Myriophyllum spicatum populations from the Qinghai-Tibetan Plateau (QTP) and adjacent highlands (Yunnan-Guizhou Plateau, YGP) by using microsatellite loci and environmental and geographical factors. Bioclim layers, hydrological properties and elevation were considered as environmental variables and reduced by principal component analysis. The genetic isolation by geographic distance (IBD) was tested by Mantel tests and the relative importance of environmental variables on population genetic differentiation was determined by a partial Mantel test and multiple matrix regression with randomization (MMRR). Two genetic clusters corresponding to the QTP and YGP were identified. Both tests and MMRR revealed a significant and strong correlation between genetic divergence and geographic isolation under the influence of environmental heterogeneity at the overall and finer spatial scales. Our findings suggested the dominant role of geography on the evolution of M. spicatum under a steep environmental gradient in the alpine landscape as a result of dispersal limitation and genetic drift. PMID:26494202

Evidence of Deterministic Components in the Apparent Randomness of GRBs: Clues of a Chaotic Dynamic

PubMed Central

Greco, G.; Rosa, R.; Beskin, G.; Karpov, S.; Romano, L.; Guarnieri, A.; Bartolini, C.; Bedogni, R.

2011-01-01

Prompt γ-ray emissions from gamma-ray bursts (GRBs) exhibit a vast range of extremely complex temporal structures with a typical variability time-scale significantly short – as fast as milliseconds. This work aims to investigate the apparent randomness of the GRB time profiles making extensive use of nonlinear techniques combining the advanced spectral method of the Singular Spectrum Analysis (SSA) with the classical tools provided by the Chaos Theory. Despite their morphological complexity, we detect evidence of a non stochastic short-term variability during the overall burst duration – seemingly consistent with a chaotic behavior. The phase space portrait of such variability shows the existence of a well-defined strange attractor underlying the erratic prompt emission structures. This scenario can shed new light on the ultra-relativistic processes believed to take place in GRB explosions and usually associated with the birth of a fast-spinning magnetar or accretion of matter onto a newly formed black hole. PMID:22355609

Evidence of deterministic components in the apparent randomness of GRBs: clues of a chaotic dynamic.

PubMed

Greco, G; Rosa, R; Beskin, G; Karpov, S; Romano, L; Guarnieri, A; Bartolini, C; Bedogni, R

2011-01-01

Prompt γ-ray emissions from gamma-ray bursts (GRBs) exhibit a vast range of extremely complex temporal structures with a typical variability time-scale significantly short - as fast as milliseconds. This work aims to investigate the apparent randomness of the GRB time profiles making extensive use of nonlinear techniques combining the advanced spectral method of the Singular Spectrum Analysis (SSA) with the classical tools provided by the Chaos Theory. Despite their morphological complexity, we detect evidence of a non stochastic short-term variability during the overall burst duration - seemingly consistent with a chaotic behavior. The phase space portrait of such variability shows the existence of a well-defined strange attractor underlying the erratic prompt emission structures. This scenario can shed new light on the ultra-relativistic processes believed to take place in GRB explosions and usually associated with the birth of a fast-spinning magnetar or accretion of matter onto a newly formed black hole.

Driving Extreme Variability: Measurements of the changing coronae and evidence for jet launching

NASA Astrophysics Data System (ADS)

Wilkins, D.; Gallo, L.; Fabian, A.; Kara, E.

2015-07-01

Through analysis of the X-rays reflected from the accretion disc, it is possible to probe the innermost structures around accreting black holes and to measure the geometry and structure of the corona that produces the intense X-ray continuum. We conducted detailed analysis of the narrow line Seyfert 1 galaxies 1H0707-495 and Markarian 335, over observations with XMM-Newton as well as Suzaku and NuSTAR spanning nearly a decade to measure the underlying changes in the structure of the X-ray emitting corona that gave rise to more than an order of magnitude variation in luminosity. Underlying this long timescale variability lies much more complex patterns of behaviour on short timescales. We are, for the first time, able to measure the changes accompanying transient phenomena including a flare from Markarian 335 seen during a low flux state. This flaring event was found to mark a reconfiguration of the corona while there is evidence that the flare itself was caused by an aborted jet-launching event. This gives us important insight into the processes by which energy is liberated from black hole accretion flows and allows observational constraints to be placed upon models of how jets are launched and how these extreme objects are powered.

A cognitive-affective system theory of personality: reconceptualizing situations, dispositions, dynamics, and invariance in personality structure.

PubMed

Mischel, W; Shoda, Y

1995-04-01

A theory was proposed to reconcile paradoxical findings on the invariance of personality and the variability of behavior across situations. For this purpose, individuals were assumed to differ in (a) the accessibility of cognitive-affective mediating units (such as encodings, expectancies and beliefs, affects, and goals) and (b) the organization of relationships through which these units interact with each other and with psychological features of situations. The theory accounts for individual differences in predictable patterns of variability across situations (e.g., if A then she X, but if B then she Y), as well as for overall average levels of behavior, as essential expressions or behavioral signatures of the same underlying personality system. Situations, personality dispositions, dynamics, and structure were reconceptualized from this perspective.

CORRECTING FOR MEASUREMENT ERROR IN LATENT VARIABLES USED AS PREDICTORS*

PubMed Central

Schofield, Lynne Steuerle

2015-01-01

This paper represents a methodological-substantive synergy. A new model, the Mixed Effects Structural Equations (MESE) model which combines structural equations modeling and item response theory is introduced to attend to measurement error bias when using several latent variables as predictors in generalized linear models. The paper investigates racial and gender disparities in STEM retention in higher education. Using the MESE model with 1997 National Longitudinal Survey of Youth data, I find prior mathematics proficiency and personality have been previously underestimated in the STEM retention literature. Pre-college mathematics proficiency and personality explain large portions of the racial and gender gaps. The findings have implications for those who design interventions aimed at increasing the rates of STEM persistence among women and under-represented minorities. PMID:26977218

Development of a variable structure-based fault detection and diagnosis strategy applied to an electromechanical system

NASA Astrophysics Data System (ADS)

Gadsden, S. Andrew; Kirubarajan, T.

2017-05-01

Signal processing techniques are prevalent in a wide range of fields: control, target tracking, telecommunications, robotics, fault detection and diagnosis, and even stock market analysis, to name a few. Although first introduced in the 1950s, the most popular method used for signal processing and state estimation remains the Kalman filter (KF). The KF offers an optimal solution to the estimation problem under strict assumptions. Since this time, a number of other estimation strategies and filters were introduced to overcome robustness issues, such as the smooth variable structure filter (SVSF). In this paper, properties of the SVSF are explored in an effort to detect and diagnosis faults in an electromechanical system. The results are compared with the KF method, and future work is discussed.

Structural and functional predictors of regional peak pressures under the foot during walking.

PubMed

Morag, E; Cavanagh, P R

1999-04-01

The objective of this study was to identify structural and functional factors which are predictors of peak pressure underneath the human foot during walking. Peak plantar pressure during walking and eight data sets of structural and functional measures were collected on 55 asymptomatic subjects between 20 and 70 yr. A best subset regression approach was used to establish models which predicted peak regional pressure under the foot. Potential predictor variables were chosen from physical characteristics, anthropometric data, passive range of motion (PROM), measurements from standardized weight bearing foot radiographs, mechanical properties of the plantar soft tissue, stride parameters, foot motion in 3D, and EMG during walking. Peak pressure values under the rearfoot, midfoot, MTH1, and hallux were measured. Heel pressure was a function of linear kinematics, longitudinal arch structure, thickness of plantar soft tissue, and age. Midfoot pressure prediction was dominated by arch structure, while MTH1 pressure was a function of radiographic measurements, talo-crural joint motion, and gastrocnemius activity. Hallux pressure was a function of structural measures and MTP1 joint motion. Foot structure and function predicted only approximately 50% of the variance in peak pressure, although the relative contributions in different anatomical regions varied dramatically. Structure was dominant in predicting peak pressure under the midfoot and MTH1, while both structure and function were important at the heel and hallux. The predictive models developed in this study give insight into potential etiological factors associated with elevated plantar pressure. They also provide direction for future studies designed to reduce elevated pressure in "at-risk" patients.

Quiet Clean Short-haul Experimental Engine (QCSEE) Under-The-Wing (UTW) composite nacelle subsystem test report. [to verify strength of selected composite materials

NASA Technical Reports Server (NTRS)

Stotler, C. L., Jr.; Johnston, E. A.; Freeman, D. S.

1977-01-01

The element and subcomponent testing conducted to verify the under the wing composite nacelle design is reported. This composite nacelle consists of an inlet, outer cowl doors, inner cowl doors, and a variable fan nozzle. The element tests provided the mechanical properties used in the nacelle design. The subcomponent tests verified that the critical panel and joint areas of the nacelle had adequate structural integrity.

Fatigue-Crack-Growth Structural Analysis

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.

1986-01-01

Elastic and plastic deformations calculated under variety of loading conditions. Prediction of fatigue-crack-growth lives made with FatigueCrack-Growth Structural Analysis (FASTRAN) computer program. As cyclic loads are applied to initial crack configuration, FASTRAN predicts crack length and other parameters until complete break occurs. Loads are tensile or compressive and of variable or constant amplitude. FASTRAN incorporates linear-elastic fracture mechanics with modifications of load-interaction effects caused by crack closure. FASTRAN considered research tool, because of lengthy calculation times. FASTRAN written in FORTRAN IV for batch execution.

Projections of limiting states for load-bearing structures of reflectors made of polymer composites

NASA Astrophysics Data System (ADS)

Doronin, S. V.

2017-12-01

This paper deals with limiting states typical for reflector antennas for terrestrial satellite communication systems. Reflectors made of polymer composites are studied. These limiting states are projected by results of the numerical analysis of the stress and strain states. The analysis is executed for reflectors under conditions of static and dynamic loading. It takes into account both overshoot of the state variables of allowed level and the processes of long-term structural material degradation.

Population Structure and Gene Flow of the Yellow Anaconda (Eunectes notaeus) in Northern Argentina

PubMed Central

McCartney-Melstad, Evan; Waller, Tomás; Micucci, Patricio A.; Barros, Mariano; Draque, Juan; Amato, George; Mendez, Martin

2012-01-01

Yellow anacondas (Eunectes notaeus) are large, semiaquatic boid snakes found in wetland systems in South America. These snakes are commercially harvested under a sustainable management plan in Argentina, so information regarding population structuring can be helpful for determination of management units. We evaluated genetic structure and migration using partial sequences from the mitochondrial control region and mitochondrial genes cyt-b and ND4 for 183 samples collected within northern Argentina. A group of landscape features and environmental variables including several treatments of temperature and precipitation were explored as potential drivers of observed genetic patterns. We found significant population structure between most putative population comparisons and bidirectional but asymmetric migration in several cases. The configuration of rivers and wetlands was found to be significantly associated with yellow anaconda population structure (IBD), and important for gene flow, although genetic distances were not significantly correlated with the environmental variables used here. More in-depth analyses of environmental data may be needed to fully understand the importance of environmental conditions on population structure and migration. These analyses indicate that our putative populations are demographically distinct and should be treated as such in Argentina's management plan for the harvesting of yellow anacondas. PMID:22675425

Reliability-based optimization of maintenance scheduling of mechanical components under fatigue

PubMed Central

Beaurepaire, P.; Valdebenito, M.A.; Schuëller, G.I.; Jensen, H.A.

2012-01-01

This study presents the optimization of the maintenance scheduling of mechanical components under fatigue loading. The cracks of damaged structures may be detected during non-destructive inspection and subsequently repaired. Fatigue crack initiation and growth show inherent variability, and as well the outcome of inspection activities. The problem is addressed under the framework of reliability based optimization. The initiation and propagation of fatigue cracks are efficiently modeled using cohesive zone elements. The applicability of the method is demonstrated by a numerical example, which involves a plate with two holes subject to alternating stress. PMID:23564979

Bayesian networks in neuroscience: a survey.

PubMed

Bielza, Concha; Larrañaga, Pedro

2014-01-01

Bayesian networks are a type of probabilistic graphical models lie at the intersection between statistics and machine learning. They have been shown to be powerful tools to encode dependence relationships among the variables of a domain under uncertainty. Thanks to their generality, Bayesian networks can accommodate continuous and discrete variables, as well as temporal processes. In this paper we review Bayesian networks and how they can be learned automatically from data by means of structure learning algorithms. Also, we examine how a user can take advantage of these networks for reasoning by exact or approximate inference algorithms that propagate the given evidence through the graphical structure. Despite their applicability in many fields, they have been little used in neuroscience, where they have focused on specific problems, like functional connectivity analysis from neuroimaging data. Here we survey key research in neuroscience where Bayesian networks have been used with different aims: discover associations between variables, perform probabilistic reasoning over the model, and classify new observations with and without supervision. The networks are learned from data of any kind-morphological, electrophysiological, -omics and neuroimaging-, thereby broadening the scope-molecular, cellular, structural, functional, cognitive and medical- of the brain aspects to be studied.

Bayesian networks in neuroscience: a survey

PubMed Central

Bielza, Concha; Larrañaga, Pedro

2014-01-01

Bayesian networks are a type of probabilistic graphical models lie at the intersection between statistics and machine learning. They have been shown to be powerful tools to encode dependence relationships among the variables of a domain under uncertainty. Thanks to their generality, Bayesian networks can accommodate continuous and discrete variables, as well as temporal processes. In this paper we review Bayesian networks and how they can be learned automatically from data by means of structure learning algorithms. Also, we examine how a user can take advantage of these networks for reasoning by exact or approximate inference algorithms that propagate the given evidence through the graphical structure. Despite their applicability in many fields, they have been little used in neuroscience, where they have focused on specific problems, like functional connectivity analysis from neuroimaging data. Here we survey key research in neuroscience where Bayesian networks have been used with different aims: discover associations between variables, perform probabilistic reasoning over the model, and classify new observations with and without supervision. The networks are learned from data of any kind–morphological, electrophysiological, -omics and neuroimaging–, thereby broadening the scope–molecular, cellular, structural, functional, cognitive and medical– of the brain aspects to be studied. PMID:25360109

Design Optimization of Irregular Cellular Structure for Additive Manufacturing

NASA Astrophysics Data System (ADS)

Song, Guo-Hua; Jing, Shi-Kai; Zhao, Fang-Lei; Wang, Ye-Dong; Xing, Hao; Zhou, Jing-Tao

2017-09-01

Irregularcellular structurehas great potential to be considered in light-weight design field. However, the research on optimizing irregular cellular structures has not yet been reporteddue to the difficulties in their modeling technology. Based on the variable density topology optimization theory, an efficient method for optimizing the topology of irregular cellular structures fabricated through additive manufacturing processes is proposed. The proposed method utilizes tangent circles to automatically generate the main outline of irregular cellular structure. The topological layoutof each cellstructure is optimized using the relative density informationobtained from the proposed modified SIMP method. A mapping relationship between cell structure and relative densityelement is builtto determine the diameter of each cell structure. The results show that the irregular cellular structure can be optimized with the proposed method. The results of simulation and experimental test are similar for irregular cellular structure, which indicate that the maximum deformation value obtained using the modified Solid Isotropic Microstructures with Penalization (SIMP) approach is lower 5.4×10-5 mm than that using the SIMP approach under the same under the same external load. The proposed research provides the instruction to design the other irregular cellular structure.

Cholera and shigellosis in Bangladesh: similarities and differences in population dynamics under climate forcing

NASA Astrophysics Data System (ADS)

Pascual, M.; Cash, B.; Reiner, R.; King, A.; Emch, M.; Yunus, M.; Faruque, A. S.

2012-12-01

The influence of climate variability on the population dynamics of infectious diseases is considered a large scale, regional, phenomenon, and as such, has been previously addressed for cholera with temporal models that do not incorporate fine-scale spatial structure. In our previous work, evidence for a role of ENSO (El Niño Southern Oscillation) on cholera in Bangladesh was elucidated, and shown to influence the regional climate through precipitation. With a probabilistic spatial model for cholera dynamics in the megacity of Dhaka, we found that the action of climate variability (ENSO and flooding) is localized: there is a climate-sensitive urban core that acts to propagate risk to the rest of the city. Here, we consider long-term surveillance data for shigellosis, another diarrheal disease that coexists with cholera in Bangladesh. We compare the patterns of association with climate variables for these two diseases in a rural setting, as well as the spatial structure in their spatio-temporal dynamics in an urban one. Evidence for similar patterns is presented, and discussed in the context of the differences in the routes of transmission of the two diseases and the proposed role of an environmental reservoir in cholera. The similarities provide evidence for a more general influence of hydrology and of socio-economic factors underlying human susceptibility and sanitary conditions.

Concave 1-norm group selection

PubMed Central

Jiang, Dingfeng; Huang, Jian

2015-01-01

Grouping structures arise naturally in many high-dimensional problems. Incorporation of such information can improve model fitting and variable selection. Existing group selection methods, such as the group Lasso, require correct membership. However, in practice it can be difficult to correctly specify group membership of all variables. Thus, it is important to develop group selection methods that are robust against group mis-specification. Also, it is desirable to select groups as well as individual variables in many applications. We propose a class of concave \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$1$\\end{document}-norm group penalties that is robust to grouping structure and can perform bi-level selection. A coordinate descent algorithm is developed to calculate solutions of the proposed group selection method. Theoretical convergence of the algorithm is proved under certain regularity conditions. Comparison with other methods suggests the proposed method is the most robust approach under membership mis-specification. Simulation studies and real data application indicate that the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$1$\\end{document}-norm concave group selection approach achieves better control of false discovery rates. An R package grppenalty implementing the proposed method is available at CRAN. PMID:25417206

Determinants of the half-turn with the ball in sub-elite youth soccer players.

PubMed

Zago, Matteo; Codari, Marina; Grilli, Massimo; Bellistri, Giuseppe; Lovecchio, Nicola; Sforza, Chiarella

2016-06-01

We explored the biomechanics of the 180° change-of-direction with the ball (half-turn) in soccer. We aimed at identifying movement strategies which enhance the players' half-turning performance, by characterising technique kinematics and understanding the structure of biomechanical and anthropometrics variables. Ten Under-13 sub-elite male players were recorded with an optoelectronic motion analyser while performing a 5-m straight dribbling followed by a half-turn with the sole. Joints kinematics differences between faster and slower trials were found in support-side hip rotation, driving-side hip adduction, trunk flexion and rotation, and arms abduction. To unveil the data-set structure, a principal component (PC) analysis and a stepwise linear discriminant analysis were performed using 30 biomechanical parameters and four anthropometric variables for each trial. Seven retained PCs explained 79% of the overall variability, featuring combinations of original variables that help in understanding the factors facilitating fast half-turns: keeping short steps, minimising lateral and forward body movements, and centre-of-mass lowering, even with ample lower limbs ranges of motion (RoM); abducting the upper limbs while limiting trunk flexion and pelvic inclination RoM. Balance and task-constrained exercises may be proposed to improve this technique. Moreover, a quantitative knowledge of the movement structure could give coaches objective insights to better instruct young players.

Remembrance of ecohydrologic extremes past

NASA Astrophysics Data System (ADS)

Band, L. E.; Hwang, T.

2013-12-01

Ecohydrological systems operate at time scales that span several orders of magnitude. Significant processes and feedbacks range from subdaily physiologic response to meteorological drivers, to soil forming and geomorphic processes ranging up through 10^3-10^4 years. While much attention in ecohydrology has focused on ecosystem optimization paradigms, these systems can show significant transience in structure and function, with apparent memory of hydroclimate extremes and regime shifts. While optimization feedbacks can be reconciled with system transience, a better understanding of the time scales and mechanisms of adjustment to increased hydroclimate variability and to specific events is required to understand and predict dynamics and vulnerability of ecosystems. Under certain circumstances of slowly varying hydroclimate, we hypothesize that ecosystems can remain adjusted to changing climate regimes, without displaying apparent system memory. Alternatively, rapid changes in hydroclimate and increased hydroclimate variability, amplified with well expressed non-linearity in the processes controlling feedbacks between water, carbon and nutrients, can move ecosystems far from adjusted states. The Coweeta Hydrological Laboratory is typical of humid, broadleaf forests in eastern North America, with a range of forest biomes from northern hardwoods at higher elevations, to oak-pine assemblages at lower elevations. The site provides almost 80 years of rainfall-runoff records for a set of watersheds under different management, along with multi-decadal forest plot structural information, soil moisture conditions and stream chemistry. An initial period of multi-decadal cooling, was followed by three decades of warming and increased hydroclimate variability. While mean temperature has risen over this time period, precipitation shows no long term trends in the mean, but has had a significant rise in variability with repeated extreme drought and wet periods. Over this latter period, intra and interannual shifts of canopy structure and phenology are discernable, along with long term canopy adjustment. We use a combination of field observations, long term remote sensing records and distributed ecohydrological modeling to investigate transient behavior, apparent memory and mechanisms of ecosystem adjustment to hydroclimate variability and change over the range of biomes in the watershed.

Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability

PubMed Central

Wei, Luqing; Chen, Hong; Wu, Guo-Rong

2018-01-01

The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability. PMID:29545744

A Comparison of Limited-Information and Full-Information Methods in M"plus" for Estimating Item Response Theory Parameters for Nonnormal Populations

ERIC Educational Resources Information Center

DeMars, Christine E.

2012-01-01

In structural equation modeling software, either limited-information (bivariate proportions) or full-information item parameter estimation routines could be used for the 2-parameter item response theory (IRT) model. Limited-information methods assume the continuous variable underlying an item response is normally distributed. For skewed and…

DIF Analysis with Multilevel Data: A Simulation Study Using the Latent Variable Approach

ERIC Educational Resources Information Center

Jin, Ying; Eason, Hershel

2016-01-01

The effects of mean ability difference (MAD) and short tests on the performance of various DIF methods have been studied extensively in previous simulation studies. Their effects, however, have not been studied under multilevel data structure. MAD was frequently observed in large-scale cross-country comparison studies where the primary sampling…

Merits and limitations of optimality criteria method for structural optimization

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Guptill, James D.; Berke, Laszlo

1993-01-01

The merits and limitations of the optimality criteria (OC) method for the minimum weight design of structures subjected to multiple load conditions under stress, displacement, and frequency constraints were investigated by examining several numerical examples. The examples were solved utilizing the Optimality Criteria Design Code that was developed for this purpose at NASA Lewis Research Center. This OC code incorporates OC methods available in the literature with generalizations for stress constraints, fully utilized design concepts, and hybrid methods that combine both techniques. Salient features of the code include multiple choices for Lagrange multiplier and design variable update methods, design strategies for several constraint types, variable linking, displacement and integrated force method analyzers, and analytical and numerical sensitivities. The performance of the OC method, on the basis of the examples solved, was found to be satisfactory for problems with few active constraints or with small numbers of design variables. For problems with large numbers of behavior constraints and design variables, the OC method appears to follow a subset of active constraints that can result in a heavier design. The computational efficiency of OC methods appears to be similar to some mathematical programming techniques.

[The analysis of the causes of variability of the relationship between leaf dry mass and area in plants].

PubMed

Vasfilov, S P

2011-01-01

The lamina dry mass: area ratio (LMA - Leaf Mass per Area) is a quite variable trait. Leaf dry mass consists of symplast mass (a set of all leaf protoplasts) and apoplast mass (a set of all cell walls in a leaf). The ratio between symplast and apoplast masses is positively related to any functional trait of leaf calculated per unit of dry mass. The value of this ratio is defined by cells size and their number per unit of leaf area, number of mesophyll cells layers and their differentiation between palisade and spongy ones, and also by density of cells packing. The LMA value is defined by leaf thickness and density. The extent and direction of variability in both leaf traits define the extent and direction of variability in LMA. Negative correlation between leaf thickness and density reduces the level of LMA variability. As a consequence of this correlation the following pattern emerges: the thinner a leaf, the denser it is. Changes in the traits that define the LMA value take place both within a species under the influence of environmental factors and between species that differ in leaf structure and functions. Light is the most powerful environmental factor that influences the LMA, increase in illumination leading to increase in LMA. This effect occurs during leaf growth at the expense of structural changes associated with the reduction of symplast/apoplast mass ratio. Under conditions of intense illumination, LMA may increase due to accumulation of starch. With regard to the majority of leaf functions, the mass of starch may be ascribed to apoplast. Starch accumulation in leaves is observed also under conditions of elevated CO2 concentration in the air. Under high illumination, however, LMA increases also due to increased apoplast contribution to leaf dry mass. Scarce mineral nutrition leads to LMA increase due to lowering of growth zones demands for phothosyntates and, therefore, to increase in starch content of leaves. High level of mineral nutrition during leaf growth period leads to LMA increase at the expense of mesophyll thickening where components of photosynthesis system are located. When additional environmental factors are involved, starch accumulation may be partly responsible for increase in LMA. LMA increase at the expense of starch accumulation, unlike that at the expense of mesophyll thickening, is accompanied by increased leaf density. Under conditions of water deficiency LMA increases, which in mature leaf may be caused by starch accumulation. LMA increase during leaf growth period under conditions of water deficiency is associated with decrease in the symplast/apoplast mass ratio.

Gray matter correlates of creative potential: A latent variable voxel-based morphometry study

PubMed Central

Jauk, Emanuel; Neubauer, Aljoscha C.; Dunst, Beate; Fink, Andreas; Benedek, Mathias

2015-01-01

There is increasing research interest in the structural and functional brain correlates underlying creative potential. Recent investigations found that interindividual differences in creative potential relate to volumetric differences in brain regions belonging to the default mode network, such as the precuneus. Yet, the complex interplay between creative potential, intelligence, and personality traits and their respective neural bases is still under debate. We investigated regional gray matter volume (rGMV) differences that can be associated with creative potential in a heterogeneous sample of N = 135 individuals using voxel-based morphometry (VBM). By means of latent variable modeling and consideration of recent psychometric advancements in creativity research, we sought to disentangle the effects of ideational originality and fluency as two independent indicators of creative potential. Intelligence and openness to experience were considered as common covariates of creative potential. The results confirmed and extended previous research: rGMV in the precuneus was associated with ideational originality, but not with ideational fluency. In addition, we found ideational originality to be correlated with rGMV in the caudate nucleus. The results indicate that the ability to produce original ideas is tied to default-mode as well as dopaminergic structures. These structural brain correlates of ideational originality were apparent throughout the whole range of intellectual ability and thus not moderated by intelligence. In contrast, structural correlates of ideational fluency, a quantitative marker of creative potential, were observed only in lower intelligent individuals in the cuneus/lingual gyrus. PMID:25676914

The Box-Cox power transformation on nursing sensitive indicators: Does it matter if structural effects are omitted during the estimation of the transformation parameter?

PubMed Central

2011-01-01

Background Many nursing and health related research studies have continuous outcome measures that are inherently non-normal in distribution. The Box-Cox transformation provides a powerful tool for developing a parsimonious model for data representation and interpretation when the distribution of the dependent variable, or outcome measure, of interest deviates from the normal distribution. The objectives of this study was to contrast the effect of obtaining the Box-Cox power transformation parameter and subsequent analysis of variance with or without a priori knowledge of predictor variables under the classic linear or linear mixed model settings. Methods Simulation data from a 3 × 4 factorial treatments design, along with the Patient Falls and Patient Injury Falls from the National Database of Nursing Quality Indicators (NDNQI®) for the 3rd quarter of 2007 from a convenience sample of over one thousand US hospitals were analyzed. The effect of the nonlinear monotonic transformation was contrasted in two ways: a) estimating the transformation parameter along with factors with potential structural effects, and b) estimating the transformation parameter first and then conducting analysis of variance for the structural effect. Results Linear model ANOVA with Monte Carlo simulation and mixed models with correlated error terms with NDNQI examples showed no substantial differences on statistical tests for structural effects if the factors with structural effects were omitted during the estimation of the transformation parameter. Conclusions The Box-Cox power transformation can still be an effective tool for validating statistical inferences with large observational, cross-sectional, and hierarchical or repeated measure studies under the linear or the mixed model settings without prior knowledge of all the factors with potential structural effects. PMID:21854614

The Box-Cox power transformation on nursing sensitive indicators: does it matter if structural effects are omitted during the estimation of the transformation parameter?

PubMed

Hou, Qingjiang; Mahnken, Jonathan D; Gajewski, Byron J; Dunton, Nancy

2011-08-19

Many nursing and health related research studies have continuous outcome measures that are inherently non-normal in distribution. The Box-Cox transformation provides a powerful tool for developing a parsimonious model for data representation and interpretation when the distribution of the dependent variable, or outcome measure, of interest deviates from the normal distribution. The objectives of this study was to contrast the effect of obtaining the Box-Cox power transformation parameter and subsequent analysis of variance with or without a priori knowledge of predictor variables under the classic linear or linear mixed model settings. Simulation data from a 3 × 4 factorial treatments design, along with the Patient Falls and Patient Injury Falls from the National Database of Nursing Quality Indicators (NDNQI® for the 3rd quarter of 2007 from a convenience sample of over one thousand US hospitals were analyzed. The effect of the nonlinear monotonic transformation was contrasted in two ways: a) estimating the transformation parameter along with factors with potential structural effects, and b) estimating the transformation parameter first and then conducting analysis of variance for the structural effect. Linear model ANOVA with Monte Carlo simulation and mixed models with correlated error terms with NDNQI examples showed no substantial differences on statistical tests for structural effects if the factors with structural effects were omitted during the estimation of the transformation parameter. The Box-Cox power transformation can still be an effective tool for validating statistical inferences with large observational, cross-sectional, and hierarchical or repeated measure studies under the linear or the mixed model settings without prior knowledge of all the factors with potential structural effects.

Insights into Inverse Materials Design from Phase Transitions in Shape Space

NASA Astrophysics Data System (ADS)

Cersonsky, Rose; van Anders, Greg; Dodd, Paul M.; Glotzer, Sharon C.

In designing new materials for synthesis, the inverse materials design approach posits that, given a structure, we can predict a building block optimized for self- assembly. How does that building block change as pressure is varied to maintain the same crystal structure? We address this question for entropically stabilized colloidal crystals by working in a generalized statistical thermodynamic ensemble where an alchemical potential variable is fixed and its conjugate variable, particle shape, is allowed to fluctuate. We show that there are multiple regions of shape behavior and phase transitions in shape space between these regions. Furthermore, while past literature has looked towards packing arguments for proposing shape-filling candidate building blocks for structure formation, we show that even at very high pressures, a structure will attain lowest free energy by modifying these space-filling shapes. U.S. Army Research Office under Grant Award No. W911NF-10-1-0518, Emerging Frontiers in Research and Innovation Award EFRI-1240264, National Science Foundation Grant Number ACI- 1053575, XSEDE award DMR 140129, Rackham Merit Fellowship Program.

Patient-tailored prioritization for a pediatric care decision support system through machine learning.

PubMed

Klann, Jeffrey G; Anand, Vibha; Downs, Stephen M

2013-12-01

Over 8 years, we have developed an innovative computer decision support system that improves appropriate delivery of pediatric screening and care. This system employs a guidelines evaluation engine using data from the electronic health record (EHR) and input from patients and caregivers. Because guideline recommendations typically exceed the scope of one visit, the engine uses a static prioritization scheme to select recommendations. Here we extend an earlier idea to create patient-tailored prioritization. We used Bayesian structure learning to build networks of association among previously collected data from our decision support system. Using area under the receiver-operating characteristic curve (AUC) as a measure of discriminability (a sine qua non for expected value calculations needed for prioritization), we performed a structural analysis of variables with high AUC on a test set. Our source data included 177 variables for 29 402 patients. The method produced a network model containing 78 screening questions and anticipatory guidance (107 variables total). Average AUC was 0.65, which is sufficient for prioritization depending on factors such as population prevalence. Structure analysis of seven highly predictive variables reveals both face-validity (related nodes are connected) and non-intuitive relationships. We demonstrate the ability of a Bayesian structure learning method to 'phenotype the population' seen in our primary care pediatric clinics. The resulting network can be used to produce patient-tailored posterior probabilities that can be used to prioritize content based on the patient's current circumstances. This study demonstrates the feasibility of EHR-driven population phenotyping for patient-tailored prioritization of pediatric preventive care services.

Molecular dynamics simulations of dislocations in TlBr crystals under an electrical field

DOE PAGES

Zhou, X. W.; Foster, M. E.; Yang, P.; ...

2016-07-13

TlBr crystals have superior radiation detection properties; however, their properties degrade in the range of hours to weeks when an operating electrical field is applied. To account for this rapid degradation using the widely-accepted vacancy migration mechanism, the vacancy concentration must be orders of magnitude higher than any conventional estimates. The present work has incorporated a new analytical variable charge model in molecular dynamics (MD) simulations to examine the structural changes of materials under electrical fields. Our simulations indicate that dislocations in TlBr move under electrical fields. As a result, this discovery can lead to new understanding of TlBr agingmore » mechanisms under external fields.« less

Spatial variability structure of soil CO2 emission and soil physical and chemical properties characterized by fractal dimension in sugarcane areas

NASA Astrophysics Data System (ADS)

Bicalho, E. S.; Teixeira, D. B.; Panosso, A. R.; Perillo, L. I.; Iamaguti, J. L.; Pereira, G. T.; La Scala, N., Jr.

2012-04-01

Soil CO2 emission (FCO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere, varying in time and space depending on environmental conditions, including the management of agricultural area. The aim of this study was to investigate the structure of spatial variability of FCO2 and soil properties by using fractal dimension (DF), derived from isotropic variograms at different scales, and construction of fractograms. The experimental area consisted of a regular grid of 60 × 60 m on sugarcane area under green management, containing 141 points spaced at minimum distances ranging from 0.5 to 10 m. Soil CO2 emission, soil temperature and soil moisture were evaluated over a period of 7 days, and soil chemical and physical properties were determined by sampling at a depth of 0.0 to 0.1 m. FCO2 showed an overall average of 1.51 µmol m-2 s-1, correlated significantly (p < 0.05) with soil physical factors such as soil bulk density, air-filled pore space, macroporosity and microporosity. Significant DF values were obtained in the characterization of FCO2 in medium and large scales (from 20 m). Variations in DF with the scale, which is the fractogram, indicate that the structure of FCO2 variability is similar to that observed for the soil temperature and total pore volume, and reverse for the other soil properties, except for macroporosity, sand content, soil organic matter, carbon stock, C/N ratio and CEC, which fractograms were not significantly correlated to the FCO2 fractogram. Thus, the structure of spatial variability for most soil properties, characterized by fractogram, presents a significant relationship with the structure of spatial variability of FCO2, generally with similar or dissimilar behavior, indicating the possibility of using the fractogram as tool to better observe the behavior of the spatial dependence of the variables along the scale.

Life Predicted in a Probabilistic Design Space for Brittle Materials With Transient Loads

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Palfi, Tamas; Reh, Stefan

2005-01-01

Analytical techniques have progressively become more sophisticated, and now we can consider the probabilistic nature of the entire space of random input variables on the lifetime reliability of brittle structures. This was demonstrated with NASA s CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code combined with the commercially available ANSYS/Probabilistic Design System (ANSYS/PDS), a probabilistic analysis tool that is an integral part of the ANSYS finite-element analysis program. ANSYS/PDS allows probabilistic loads, component geometry, and material properties to be considered in the finite-element analysis. CARES/Life predicts the time dependent probability of failure of brittle material structures under generalized thermomechanical loading--such as that found in a turbine engine hot-section. Glenn researchers coupled ANSYS/PDS with CARES/Life to assess the effects of the stochastic variables of component geometry, loading, and material properties on the predicted life of the component for fully transient thermomechanical loading and cyclic loading.

Self-similarity in nature

NASA Astrophysics Data System (ADS)

Timashev, S. F.

2000-02-01

A general phenomenological approach to the analysis of experimental temporal, spatial and energetic series for extracting truly physical non-model parameters ("passport data") is presented, which may be used to characterize and distinguish the evolution as well as the spatial and energetic structure of any open nonlinear dissipative system. This methodology is based on a postulate concerning the crucial information contained in the sequences of non-regularities of the measured dynamic variable (temporal, spatial, energetic). In accordance with this approach, multi-parametric formulas for dynamic variable power spectra as well as for structural functions of different orders are identical for every spatial-temporal-energetic level of the system under consideration. In effect, this entails the introduction of a new kind of self-similarity in Nature. An algorithm has been developed for obtaining as many "passport data" as are necessary for the characterization of a dynamic system. Applications of this approach in the analysis of various experimental series (temporal, spatial, energetic) demonstrate its potential for defining adequate phenomenological parameters of different dynamic processes and structures.

A dispersion relationship governing incompressible wall turbulence

NASA Technical Reports Server (NTRS)

Tsuge, S.

1978-01-01

The method of separation of variables is shown to make turbulent correlation equations of Karman-Howarth type tractable for shear turbulence as well under the condition of neglected triple correlation. The separated dependent variable obeys an Orr-Sommerfeld equation. A new analytical method is developed using a scaling law different from the classical one due to Heisenberg and Lin and more appropriate for wall turbulent profiles. A dispersion relationship between the wave number and the separation constant which has the dimension of a frequency is derived in support of experimental observations of wave or coherent structure of wall turbulence.

Formation of structural steady states in lamellar/sponge phase-separating fluids under shear flow

NASA Astrophysics Data System (ADS)

Panizza, P.; Courbin, L.; Cristobal, G.; Rouch, J.; Narayanan, T.

2003-05-01

We investigate the effect of shear flow on a lamellar-sponge phase-separating fluid when subjected to shear flow. We show the existence of two different steady states (droplets and ribbons structures) whose nature does not depend on the way to reach the two-phase unstable region of the phase diagram (temperature quench or stirring). The transition between ribbons and droplets is shear thickening and its nature strongly depends on what dynamical variable is imposed. If the stress is fixed, flow visualization shows the existence of shear bands at the transition, characteristic of coexistence in the cell between ribbons and droplets. In this shear-banding region, the viscosity oscillates. When the shear rate is fixed, no shear bands are observed. Instead, the transition exhibits a hysteretic behavior leading to a structural bi-stability of the phase-separating fluid under flow.

Finite element analysis and optimization of composite structures

NASA Technical Reports Server (NTRS)

Thomsen, Jan

1990-01-01

Linearly elastic fiber reinforced composite discs and laminates in plane stress with variable local orientation and concentration of one or two fiber fields embedded in the matrix material, are considered. The thicknesses and the domain of the discs or laminates are assumed to be given, together with prescribed boundary conditions and in-plane loading along the edge. The problem under study consists in determining throughout the structural domain the optimum orientations and concentrations of the fiber fields in such a way as to maximize the integral stiffness of the composite disc or laminate under the seven loading. Minimization of the integral stiffness can also be performed. The optimization is performed subject to a prescribed bound on the total cost or weight of the composite that for given unit cost factors or specific weights determines the amounts of fiber and matrix materials in the structure. Examples are presented.

Self-organizing linear output map (SOLO): An artificial neural network suitable for hydrologic modeling and analysis

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Lin; Gupta, Hoshin V.; Gao, Xiaogang; Sorooshian, Soroosh; Imam, Bisher

2002-12-01

Artificial neural networks (ANNs) can be useful in the prediction of hydrologic variables, such as streamflow, particularly when the underlying processes have complex nonlinear interrelationships. However, conventional ANN structures suffer from network training issues that significantly limit their widespread application. This paper presents a multivariate ANN procedure entitled self-organizing linear output map (SOLO), whose structure has been designed for rapid, precise, and inexpensive estimation of network structure/parameters and system outputs. More important, SOLO provides features that facilitate insight into the underlying processes, thereby extending its usefulness beyond forecast applications as a tool for scientific investigations. These characteristics are demonstrated using a classic rainfall-runoff forecasting problem. Various aspects of model performance are evaluated in comparison with other commonly used modeling approaches, including multilayer feedforward ANNs, linear time series modeling, and conceptual rainfall-runoff modeling.

Internal state variable plasticity-damage modeling of AISI 4140 steel including microstructure-property relations: temperature and strain rate effects

NASA Astrophysics Data System (ADS)

Nacif el Alaoui, Reda

Mechanical structure-property relations have been quantified for AISI 4140 steel. under different strain rates and temperatures. The structure-property relations were used. to calibrate a microstructure-based internal state variable plasticity-damage model for. monotonic tension, compression and torsion plasticity, as well as damage evolution. Strong stress state and temperature dependences were observed for the AISI 4140 steel. Tension tests on three different notched Bridgman specimens were undertaken to study. the damage-triaxiality dependence for model validation purposes. Fracture surface. analysis was performed using Scanning Electron Microscopy (SEM) to quantify the void. nucleation and void sizes in the different specimens. The stress-strain behavior exhibited. a fairly large applied stress state (tension, compression dependence, and torsion), a. moderate temperature dependence, and a relatively small strain rate dependence.

A route to possible civil engineering materials: the case of high-pressure phases of lime

NASA Astrophysics Data System (ADS)

Bouibes, A.; Zaoui, A.

2015-07-01

Lime system has a chemical composition CaO, which is known as thermodynamically stable. The purpose here is to explore further possible phases under pressure, by means of variable-composition ab initio evolutionary algorithm. The present investigation shows surprisingly new stable compounds of lime. At ambient pressure we predict, in addition to CaO, CaO2 as new thermodynamically stable compound. The latter goes through two phases transition from C2/c space group structure to Pna21 at 1.5 GPa, and Pna21 space group structure to I4/mcm at 23.4 GPa. Under increasing pressure, further compounds such as CaO3 become the most stable and stabilize in P-421m space group structure above 65 GPa. For the necessary knowledge of the new predicted compounds, we have computed their mechanical and electronic properties in order to show and to explain the main reasons leading to the structural changes.

A route to possible civil engineering materials: the case of high-pressure phases of lime.

PubMed

Bouibes, A; Zaoui, A

2015-07-23

Lime system has a chemical composition CaO, which is known as thermodynamically stable. The purpose here is to explore further possible phases under pressure, by means of variable-composition ab initio evolutionary algorithm. The present investigation shows surprisingly new stable compounds of lime. At ambient pressure we predict, in addition to CaO, CaO2 as new thermodynamically stable compound. The latter goes through two phases transition from C2/c space group structure to Pna21 at 1.5 GPa, and Pna21 space group structure to I4/mcm at 23.4 GPa. Under increasing pressure, further compounds such as CaO3 become the most stable and stabilize in P-421m space group structure above 65 GPa. For the necessary knowledge of the new predicted compounds, we have computed their mechanical and electronic properties in order to show and to explain the main reasons leading to the structural changes.

Stochastic Simulation Tool for Aerospace Structural Analysis

NASA Technical Reports Server (NTRS)

Knight, Norman F.; Moore, David F.

2006-01-01

Stochastic simulation refers to incorporating the effects of design tolerances and uncertainties into the design analysis model and then determining their influence on the design. A high-level evaluation of one such stochastic simulation tool, the MSC.Robust Design tool by MSC.Software Corporation, has been conducted. This stochastic simulation tool provides structural analysts with a tool to interrogate their structural design based on their mathematical description of the design problem using finite element analysis methods. This tool leverages the analyst's prior investment in finite element model development of a particular design. The original finite element model is treated as the baseline structural analysis model for the stochastic simulations that are to be performed. A Monte Carlo approach is used by MSC.Robust Design to determine the effects of scatter in design input variables on response output parameters. The tool was not designed to provide a probabilistic assessment, but to assist engineers in understanding cause and effect. It is driven by a graphical-user interface and retains the engineer-in-the-loop strategy for design evaluation and improvement. The application problem for the evaluation is chosen to be a two-dimensional shell finite element model of a Space Shuttle wing leading-edge panel under re-entry aerodynamic loading. MSC.Robust Design adds value to the analysis effort by rapidly being able to identify design input variables whose variability causes the most influence in response output parameters.

SITEX 2.0: Projections of protein functional sites on eukaryotic genes. Extension with orthologous genes.

PubMed

Medvedeva, Irina V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2017-04-01

Functional sites define the diversity of protein functions and are the central object of research of the structural and functional organization of proteins. The mechanisms underlying protein functional sites emergence and their variability during evolution are distinguished by duplication, shuffling, insertion and deletion of the exons in genes. The study of the correlation between a site structure and exon structure serves as the basis for the in-depth understanding of sites organization. In this regard, the development of programming resources that allow the realization of the mutual projection of exon structure of genes and primary and tertiary structures of encoded proteins is still the actual problem. Previously, we developed the SitEx system that provides information about protein and gene sequences with mapped exon borders and protein functional sites amino acid positions. The database included information on proteins with known 3D structure. However, data with respect to orthologs was not available. Therefore, we added the projection of sites positions to the exon structures of orthologs in SitEx 2.0. We implemented a search through database using site conservation variability and site discontinuity through exon structure. Inclusion of the information on orthologs allowed to expand the possibilities of SitEx usage for solving problems regarding the analysis of the structural and functional organization of proteins. Database URL: http://www-bionet.sscc.ru/sitex/ .

Analysis of Sensory/Active Piezoelectric Composite Structures in Thermal Environments

NASA Technical Reports Server (NTRS)

Lee, Ho-Jun; Saravanos, Dimitris A.

1996-01-01

Although there has been extensive development of analytical methods for modeling the behavior of piezoelectric structures, only a limited amount of research has been performed concerning the implications of thermal effects on both the active and sensory response of smart structures. Thermal effects become important when the piezoelectric structure has to operate in either extremely hot or cold temperature environments. Consequently, the purpose of this paper is to extend the previously developed discrete layer formulation of Saravanos and Heyliger to account for the coupled mechanical, electrical, and thermal response in modern smart composite beams. The mechanics accounts for thermal effects which may arise in the elastic and piezoelectric media at the material level through the constitutive equations. The displacements, electric potentials, and temperatures are introduced as state variables, allowing them to be modeled as variable fields through the laminate thickness. This unified representation leads to an inherent capability to model both the active compensation of thermal distortions in smart structures and the resultant sensory voltage when thermal loads are applied. The corresponding finite element formulation is developed and numerical results demonstrate the ability to model both the active and sensory modes of composite beams with heterogeneous plies with attached piezoelectric layers under thermal loadings.

Systematic review of the neural basis of social cognition in patients with mood disorders

PubMed Central

Cusi, Andrée M.; Nazarov, Anthony; Holshausen, Katherine; MacQueen, Glenda M.; McKinnon, Margaret C.

2012-01-01

Background This review integrates neuroimaging studies of 2 domains of social cognition — emotion comprehension and theory of mind (ToM) — in patients with major depressive disorder and bipolar disorder. The influence of key clinical and method variables on patterns of neural activation during social cognitive processing is also examined. Methods Studies were identified using PsycINFO and PubMed (January 1967 to May 2011). The search terms were “fMRI,” “emotion comprehension,” “emotion perception,” “affect comprehension,” “affect perception,” “facial expression,” “prosody,” “theory of mind,” “mentalizing” and “empathy” in combination with “major depressive disorder,” “bipolar disorder,” “major depression,” “unipolar depression,” “clinical depression” and “mania.” Results Taken together, neuroimaging studies of social cognition in patients with mood disorders reveal enhanced activation in limbic and emotion-related structures and attenuated activity within frontal regions associated with emotion regulation and higher cognitive functions. These results reveal an overall lack of inhibition by higher-order cognitive structures on limbic and emotion-related structures during social cognitive processing in patients with mood disorders. Critically, key variables, including illness burden, symptom severity, comorbidity, medication status and cognitive load may moderate this pattern of neural activation. Limitations Studies that did not include control tasks or a comparator group were included in this review. Conclusion Further work is needed to examine the contribution of key moderator variables and to further elucidate the neural networks underlying altered social cognition in patients with mood disorders. The neural networks underlying higher-order social cognitive processes, including empathy, remain unexplored in patients with mood disorders. PMID:22297065

Network structure shapes spontaneous functional connectivity dynamics.

PubMed

Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

2015-04-08

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

Analysis and Design of Variable Stiffness Composite Cylinders

NASA Technical Reports Server (NTRS)

Tatting, Brian F.; Guerdal, Zafer

1998-01-01

An investigation of the possible performance improvements of thin circular cylindrical shells through the use of the variable stiffness concept is presented. The variable stiffness concept implies that the stiffness parameters change spatially throughout the structure. This situation is achieved mainly through the use of curvilinear fibers within a fiber-reinforced composite laminate, though the possibility of thickness variations and discrete stiffening elements is also allowed. These three mechanisms are incorporated into the constitutive laws for thin shells through the use of Classical Lamination Theory. The existence of stiffness variation within the structure warrants a formulation of the static equilibrium equations from the most basic principles. The governing equations include sufficient detail to correctly model several types of nonlinearity, including the formation of a nonlinear shell boundary layer as well as the Brazier effect due to nonlinear bending of long cylinders. Stress analysis and initial buckling estimates are formulated for a general variable stiffness cylinder. Results and comparisons for several simplifications of these highly complex governing equations are presented so that the ensuing numerical solutions are considered reliable and efficient enough for in-depth optimization studies. Four distinct cases of loading and stiffness variation are chosen to investigate possible areas of improvement that the variable stiffness concept may offer over traditional constant stiffness and/or stiffened structures. The initial investigation deals with the simplest solution for cylindrical shells in which all quantities are constant around the circumference of the cylinder. This axisymmetric case includes a stiffness variation exclusively in the axial direction, and the only pertinent loading scenarios include constant loads of axial compression, pressure, and torsion. The results for these cases indicate that little improvement over traditional laminates exists through the use of curvilinear fibers, mainly due to the presence of a weak link area within the stiffness variation that limits the ultimate load that the structure can withstand. Rigorous optimization studies reveal that even though slight increases in the critical loads can be produced for designs with an arbitrary variation of the fiber orientation angle, the improvements are not significant when compared to traditional design techniques that utilize ring stiffeners and frames. The second problem that is studied involves arbitrary loading of a cylinder with a stiffness variation that changes only in the circumferential direction. The end effects of the cylinder are ignored, so that the problem takes the form of an analysis of a cross-section for a short cylinder segment. Various load cases including axial compression, pressure, torsion, bending, and transverse shear forces are investigated. It is found that the most significant improvements in load-carrying capability exist for cases which involve loads that also vary around the circumference of the shell, namely bending and shear forces. The stiffness variation of the optimal designs contribute to the increased performance in two ways: lowering the stresses in the critical areas through redistribution of the stresses; and providing a relatively stiff region that alters the buckling behavior of the structure. These results lead to an in-depth optimization study involving weight optimization of a fuselage structure subjected to typical design constraints. Comparisons of the curvilinear fiber format to traditional stiffened structures constructed of isotropic and composite materials are included. It is found that standard variable stiffness designs are quite comparable in terms of weight and load-carrying capability yet offer the added advantage of tailorability of distinct regions of the structure that experience drastically different loading conditions. The last two problems presented in this work involve the nonlinear phenomenon of long tubes under bending. Though this scenario is not as applicable to fuselage structures as the previous problems, the mechanisms that produce the nonlinear effect are ideally suited to be controlled by the variable stiffness concept. This is due to the fact that the dominating influence for long cylinders under bending is the ovalization of the cross-section, which is governed mainly by the stiffness parameters of the cylindrical shell. Possible improvement of the critical buckling moments for these structures is investigated using either a circumferential or axial stiffness variation. For the circumferential case involving infinite length cylinders, it is found that slight improvements can be observed by designing structures that resist the cross-sectional deformation yet do not detract from the buckling resistance at the critical location. The results also indicate that buckling behavior is extremely dependent on cylinder length. This effect is most easily seen in the solution of finite length cylinders under bending that contain an axial stiffness variation. For these structures, the only mechanism that exhibits improved response are those that effectively shorten the length of the cylinder, thus reducing the cross-sectional deformation due to the forced restraint at the ends. It was found that the use of curvilinear fibers was not able to achieve this effect in sufficient degree to resist the deformation, but that ring stiffeners produced the desired response admirably. Thus, it is shown that the variable stiffness concept is most effective at improving the bending response of long cylinders through the use of a circumferential stiffness variation.

A 3D moisture-stress FEM analysis for time dependent problems in timber structures

NASA Astrophysics Data System (ADS)

Fortino, Stefania; Mirianon, Florian; Toratti, Tomi

2009-11-01

This paper presents a 3D moisture-stress numerical analysis for timber structures under variable humidity and load conditions. An orthotropic viscoelastic-mechanosorptive material model is specialized on the basis of previous models. Both the constitutive model and the equations needed to describe the moisture flow across the structure are implemented into user subroutines of the Abaqus finite element code and a coupled moisture-stress analysis is performed for several types of mechanical loads and moisture changes. The presented computational approach is validated by analyzing some wood tests described in the literature and comparing the computational results with the reported experimental data.

Structural Health Monitoring System Trade Space Analysis Tool with Consideration for Crack Growth, Sensor Degradation and a Variable Detection Threshold

DTIC Science & Technology

2014-09-18

Erdogan , 1963). 26 Paris’s Law Under a fatigue stress regime Paris’s Law relates sub-critical crack growth to stress intensity factor. The basic...Paris and Erdogan , 1963). After takeoff, the model generates a probability distribution for the crack length in that specific sortie based on the...Law is one of the most widely used fatigue crack growth models and was used in this research effort (Paris and Erdogan , 1963). Paris’s Law Under a

Corrosion Mechanisms in Brazed Al-Base Alloy Sandwich Structures as a Function of Braze Alloy and Process Variables

DTIC Science & Technology

2013-02-01

aeration solution for 8 hours. A concentrated Nitric acid (HNO3) dip for 15 seconds removed corrosion products prior to post-exposure SEM imaging [25...32 to -37°C under a liquid nitrogen chill at 11.2 V for one minute [10]. The electropolishing solution was a mixture of 1/3 concentrated Nitric acid ...DATES COVERED (From - To) 03/27/06-12/31/12 4. TITLE AND SUBTITLE Corrosion Mechanisms in Brazed Al-Base Alloy Sandwich Structures as a Function

Replication Analysis in Exploratory Factor Analysis: What It Is and Why It Makes Your Analysis Better

ERIC Educational Resources Information Center

Osborne, Jason W.; Fitzpatrick, David C.

2012-01-01

Exploratory Factor Analysis (EFA) is a powerful and commonly-used tool for investigating the underlying variable structure of a psychometric instrument. However, there is much controversy in the social sciences with regard to the techniques used in EFA (Ford, MacCallum, & Tait, 1986; Henson & Roberts, 2006) and the reliability of the outcome.…

Toward Robust Estimation of the Components of Forest Population Change

Treesearch

Francis A. Roesch

2014-01-01

Multiple levels of simulation are used to test the robustness of estimators of the components of change. I first created a variety of spatial-temporal populations based on, but more variable than, an actual forest monitoring data set and then sampled those populations under a variety of sampling error structures. The performance of each of four estimation approaches is...

Rotation to a Partially Specified Target Matrix in Exploratory Factor Analysis: How Many Targets?

ERIC Educational Resources Information Center

Myers, Nicholas D.; Ahn, Soyeon; Jin, Ying

2013-01-01

The purpose of this study was to explore the influence of the number of targets specified on the quality of exploratory factor analysis solutions with a complex underlying structure and incomplete substantive measurement theory. Three Monte Carlo studies were performed based on the ratio of the number of observed variables to the number of…

Interactions between Canopy Structure and Herbaceous Biomass along Environmental Gradients in Moist Forest and Dry Miombo Woodland of Tanzania.

PubMed

Shirima, Deo D; Pfeifer, Marion; Platts, Philip J; Totland, Ørjan; Moe, Stein R

2015-01-01

We have limited understanding of how tropical canopy foliage varies along environmental gradients, and how this may in turn affect forest processes and functions. Here, we analyse the relationships between canopy leaf area index (LAI) and above ground herbaceous biomass (AGBH) along environmental gradients in a moist forest and miombo woodland in Tanzania. We recorded canopy structure and herbaceous biomass in 100 permanent vegetation plots (20 m × 40 m), stratified by elevation. We quantified tree species richness, evenness, Shannon diversity and predominant height as measures of structural variability, and disturbance (tree stumps), soil nutrients and elevation as indicators of environmental variability. Moist forest and miombo woodland differed substantially with respect to nearly all variables tested. Both structural and environmental variables were found to affect LAI and AGBH, the latter being additionally dependent on LAI in moist forest but not in miombo, where other factors are limiting. Combining structural and environmental predictors yielded the most powerful models. In moist forest, they explained 76% and 25% of deviance in LAI and AGBH, respectively. In miombo woodland, they explained 82% and 45% of deviance in LAI and AGBH. In moist forest, LAI increased non-linearly with predominant height and linearly with tree richness, and decreased with soil nitrogen except under high disturbance. Miombo woodland LAI increased linearly with stem density, soil phosphorous and nitrogen, and decreased linearly with tree species evenness. AGBH in moist forest decreased with LAI at lower elevations whilst increasing slightly at higher elevations. AGBH in miombo woodland increased linearly with soil nitrogen and soil pH. Overall, moist forest plots had denser canopies and lower AGBH compared with miombo plots. Further field studies are encouraged, to disentangle the direct influence of LAI on AGBH from complex interrelationships between stand structure, environmental gradients and disturbance in African forests and woodlands.

Highly Heterogeneous Soil Bacterial Communities around Terra Nova Bay of Northern Victoria Land, Antarctica

PubMed Central

Lim, Hyoun Soo; Hong, Soon Gyu; Kim, Ji Hee; Lee, Joohan; Choi, Taejin; Ahn, Tae Seok; Kim, Ok-Sun

2015-01-01

Given the diminished role of biotic interactions in soils of continental Antarctica, abiotic factors are believed to play a dominant role in structuring of microbial communities. However, many ice-free regions remain unexplored, and it is unclear which environmental gradients are primarily responsible for the variations among bacterial communities. In this study, we investigated the soil bacterial community around Terra Nova Bay of Victoria Land by pyrosequencing and determined which environmental variables govern the bacterial community structure at the local scale. Six bacterial phyla, Actinobacteria, Proteobacteria, Acidobacteria, Chloroflexi, Cyanobacteria, and Bacteroidetes, were dominant, but their relative abundance varied greatly across locations. Bacterial community structures were affected little by spatial distance, but structured more strongly by site, which was in accordance with the soil physicochemical compositions. At both the phylum and species levels, bacterial community structure was explained primarily by pH and water content, while certain earth elements and trace metals also played important roles in shaping community variation. The higher heterogeneity of the bacterial community structure found at this site indicates how soil bacterial communities have adapted to different compositions of edaphic variables under extreme environmental conditions. Taken together, these findings greatly advance our understanding of the adaption of soil bacterial populations to this harsh environment. PMID:25799273

[Multivariate Adaptive Regression Splines (MARS), an alternative for the analysis of time series].

PubMed

Vanegas, Jairo; Vásquez, Fabián

Multivariate Adaptive Regression Splines (MARS) is a non-parametric modelling method that extends the linear model, incorporating nonlinearities and interactions between variables. It is a flexible tool that automates the construction of predictive models: selecting relevant variables, transforming the predictor variables, processing missing values and preventing overshooting using a self-test. It is also able to predict, taking into account structural factors that might influence the outcome variable, thereby generating hypothetical models. The end result could identify relevant cut-off points in data series. It is rarely used in health, so it is proposed as a tool for the evaluation of relevant public health indicators. For demonstrative purposes, data series regarding the mortality of children under 5 years of age in Costa Rica were used, comprising the period 1978-2008. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Extracting Leading Nonlinear Modes of Changing Climate From Global SST Time Series

NASA Astrophysics Data System (ADS)

Mukhin, D.; Gavrilov, A.; Loskutov, E. M.; Feigin, A. M.; Kurths, J.

2017-12-01

Data-driven modeling of climate requires adequate principal variables extracted from observed high-dimensional data. For constructing such variables it is needed to find spatial-temporal patterns explaining a substantial part of the variability and comprising all dynamically related time series from the data. The difficulties of this task rise from the nonlinearity and non-stationarity of the climate dynamical system. The nonlinearity leads to insufficiency of linear methods of data decomposition for separating different processes entangled in the observed time series. On the other hand, various forcings, both anthropogenic and natural, make the dynamics non-stationary, and we should be able to describe the response of the system to such forcings in order to separate the modes explaining the internal variability. The method we present is aimed to overcome both these problems. The method is based on the Nonlinear Dynamical Mode (NDM) decomposition [1,2], but takes into account external forcing signals. An each mode depends on hidden, unknown a priori, time series which, together with external forcing time series, are mapped onto data space. Finding both the hidden signals and the mapping allows us to study the evolution of the modes' structure in changing external conditions and to compare the roles of the internal variability and forcing in the observed behavior. The method is used for extracting of the principal modes of SST variability on inter-annual and multidecadal time scales accounting the external forcings such as CO2, variations of the solar activity and volcanic activity. The structure of the revealed teleconnection patterns as well as their forecast under different CO2 emission scenarios are discussed.[1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101.

A variable resolution right TIN approach for gridded oceanographic data

NASA Astrophysics Data System (ADS)

Marks, David; Elmore, Paul; Blain, Cheryl Ann; Bourgeois, Brian; Petry, Frederick; Ferrini, Vicki

2017-12-01

Many oceanographic applications require multi resolution representation of gridded data such as for bathymetric data. Although triangular irregular networks (TINs) allow for variable resolution, they do not provide a gridded structure. Right TINs (RTINs) are compatible with a gridded structure. We explored the use of two approaches for RTINs termed top-down and bottom-up implementations. We illustrate why the latter is most appropriate for gridded data and describe for this technique how the data can be thinned. While both the top-down and bottom-up approaches accurately preserve the surface morphology of any given region, the top-down method of vertex placement can fail to match the actual vertex locations of the underlying grid in many instances, resulting in obscured topology/bathymetry. Finally we describe the use of the bottom-up approach and data thinning in two applications. The first is to provide thinned, variable resolution bathymetry data for tests of storm surge and inundation modeling, in particular hurricane Katrina. Secondly we consider the use of the approach for an application to an oceanographic data grid of 3-D ocean temperature.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots.

PubMed

Tošić, Tamara; Sellers, Kristin K; Fröhlich, Flavio; Fedotenkova, Mariia; Beim Graben, Peter; Hutt, Axel

2015-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots

PubMed Central

Tošić, Tamara; Sellers, Kristin K.; Fröhlich, Flavio; Fedotenkova, Mariia; beim Graben, Peter; Hutt, Axel

2016-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain. PMID:26834580

Instrumental variables estimation of exposure effects on a time-to-event endpoint using structural cumulative survival models.

PubMed

Martinussen, Torben; Vansteelandt, Stijn; Tchetgen Tchetgen, Eric J; Zucker, David M

2017-12-01

The use of instrumental variables for estimating the effect of an exposure on an outcome is popular in econometrics, and increasingly so in epidemiology. This increasing popularity may be attributed to the natural occurrence of instrumental variables in observational studies that incorporate elements of randomization, either by design or by nature (e.g., random inheritance of genes). Instrumental variables estimation of exposure effects is well established for continuous outcomes and to some extent for binary outcomes. It is, however, largely lacking for time-to-event outcomes because of complications due to censoring and survivorship bias. In this article, we make a novel proposal under a class of structural cumulative survival models which parameterize time-varying effects of a point exposure directly on the scale of the survival function; these models are essentially equivalent with a semi-parametric variant of the instrumental variables additive hazards model. We propose a class of recursive instrumental variable estimators for these exposure effects, and derive their large sample properties along with inferential tools. We examine the performance of the proposed method in simulation studies and illustrate it in a Mendelian randomization study to evaluate the effect of diabetes on mortality using data from the Health and Retirement Study. We further use the proposed method to investigate potential benefit from breast cancer screening on subsequent breast cancer mortality based on the HIP-study. © 2017, The International Biometric Society.

The Association between Tax Structure and Cigarette Price Variability: Findings from the International Tobacco Control Policy Evaluation (ITC) Project

PubMed Central

Shang, Ce; Chaloupka, Frank J.; Fong, Geoffrey T; Thompson, Mary; O’Connor, Richard J

2015-01-01

Background Recent studies have shown that more opportunities exist for tax avoidance when cigarette excise tax structure departs from a uniform specific structure. However, the association between tax structure and cigarette price variability has not been thoroughly studied in the existing literature. Objective To examine how cigarette tax structure is associated with price variability. The variability of self-reported prices is measured using the ratios of differences between higher and lower prices to the median price such as the IQR-to-median ratio. Methods We used survey data taken from the International Tobacco Control Policy Evaluation (ITC) Project in 17 countries to conduct the analysis. Cigarette prices were derived using individual purchase information and aggregated to price variability measures for each surveyed country and wave. The effect of tax structures on price variability was estimated using Generalised Estimating Equations after adjusting for year and country attributes. Findings Our study provides empirical evidence of a relationship between tax structure and cigarette price variability. We find that, compared to the specific uniform tax structure, mixed uniform and tiered (specific, ad valorem or mixed) structures are associated with greater price variability (p≤0.01). Moreover, while a greater share of the specific component in total excise taxes is associated with lower price variability (p≤0.05), a tiered tax structure is associated with greater price variability (p≤0.01). The results suggest that a uniform and specific tax structure is the most effective tax structure for reducing tobacco consumption and prevalence by limiting price variability and decreasing opportunities for tax avoidance. PMID:25855641

Effects of spatial structure of population size on the population dynamics of barnacles across their elevational range.

PubMed

Fukaya, Keiichi; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi

2014-11-01

Explanations for why population dynamics vary across the range of a species reflect two contrasting hypotheses: (i) temporal variability of populations is larger in the centre of the range compared to the margins because overcompensatory density dependence destabilizes population dynamics and (ii) population variability is larger near the margins, where populations are more susceptible to environmental fluctuations. In both of these hypotheses, positions within the range are assumed to affect population variability. In contrast, the fact that population variability is often related to mean population size implies that the spatial structure of the population size within the range of a species may also be a useful predictor of the spatial variation in temporal variability of population size over the range of the species. To explore how population temporal variability varies spatially and the underlying processes responsible for the spatial variation, we focused on the intertidal barnacle Chthamalus dalli and examined differences in its population dynamics along the tidal levels it inhabits. Changes in coverage of barnacle populations were monitored for 10.5 years at 25 plots spanning the elevational range of this species. Data were analysed by fitting a population dynamics model to estimate the effects of density-dependent and density-independent processes on population growth. We also examined the temporal mean-variance relationship of population size with parameters estimated from the population dynamics model. We found that the relative variability of populations tended to increase from the centre of the elevational range towards the margins because of an increase in the magnitude of stochastic fluctuations of growth rates. Thus, our results supported hypothesis (2). We also found that spatial variations in temporal population variability were well characterized by Taylor's power law, the relative population variability being inversely related to the mean population size. Results suggest that understanding the population dynamics of a species over its range may be facilitated by taking the spatial structure of population size into account as well as by considering changes in population processes as a function of position within the range of the species. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Nonlinear Variability of Body Sway in Patients with Phobic Postural Vertigo

PubMed Central

Schniepp, Roman; Wuehr, Max; Pradhan, Cauchy; Novozhilov, Sergej; Krafczyk, Siegbert; Brandt, Thomas; Jahn, Klaus

2013-01-01

Background: Subjective postural imbalance is a key symptom in the somatoform phobic postural vertigo (PPV). It has been assumed that more attentional control of body posture and / or co-contraction of leg muscles during standing is used to minimize the physiological body sway in PPV. Here we analyze nonlinear variability of body sway in patients with PPV in order to disclose changes in postural control strategy associated with PPV. Methods: Twenty patients with PPV and 20 age-matched healthy subjects (HS) were recorded on a stabilometer platform with eyes open (EO), eyes closed (EC), and while standing on a foam rubber with eyes closed (ECF). Spatio-temporal changes of the center of pressure (CoP) displacement were analyzed to assess the structure of postural variability by computing the scaling exponent α and the sample entropy (SEn) of the time series. Results: With EO on firm ground α and SEn of CoP displacement were significantly lower in patients (p < 0.001). For more difficult conditions (EC, ECF) postural variability in PPV assimilated to that of HS. Conclusion: Postural control in PPV patients differs from HS under normal stance condition. It is characterized by a reduced scaling behavior and higher regularity. These changes in the structure of postural variability might suggest an inappropriate attentional involvement with stabilizing strategies, which are used by HS only for more demanding balance tasks. PMID:23966974

Individual differences and time-varying features of modular brain architecture.

PubMed

Liao, Xuhong; Cao, Miao; Xia, Mingrui; He, Yong

2017-05-15

Recent studies have suggested that human brain functional networks are topologically organized into functionally specialized but inter-connected modules to facilitate efficient information processing and highly flexible cognitive function. However, these studies have mainly focused on group-level network modularity analyses using "static" functional connectivity approaches. How these extraordinary modular brain structures vary across individuals and spontaneously reconfigure over time remain largely unknown. Here, we employed multiband resting-state functional MRI data (N=105) from the Human Connectome Project and a graph-based modularity analysis to systematically investigate individual variability and dynamic properties in modular brain networks. We showed that the modular structures of brain networks dramatically vary across individuals, with higher modular variability primarily in the association cortex (e.g., fronto-parietal and attention systems) and lower variability in the primary systems. Moreover, brain regions spontaneously changed their module affiliations on a temporal scale of seconds, which cannot be simply attributable to head motion and sampling error. Interestingly, the spatial pattern of intra-subject dynamic modular variability largely overlapped with that of inter-subject modular variability, both of which were highly reproducible across repeated scanning sessions. Finally, the regions with remarkable individual/temporal modular variability were closely associated with network connectors and the number of cognitive components, suggesting a potential contribution to information integration and flexible cognitive function. Collectively, our findings highlight individual modular variability and the notable dynamic characteristics in large-scale brain networks, which enhance our understanding of the neural substrates underlying individual differences in a variety of cognition and behaviors. Copyright © 2017 Elsevier Inc. All rights reserved.

Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty.

PubMed

de Pierrefeu, Amicie; Lofstedt, Tommy; Hadj-Selem, Fouad; Dubois, Mathieu; Jardri, Renaud; Fovet, Thomas; Ciuciu, Philippe; Frouin, Vincent; Duchesnay, Edouard

2018-02-01

Principal component analysis (PCA) is an exploratory tool widely used in data analysis to uncover the dominant patterns of variability within a population. Despite its ability to represent a data set in a low-dimensional space, PCA's interpretability remains limited. Indeed, the components produced by PCA are often noisy or exhibit no visually meaningful patterns. Furthermore, the fact that the components are usually non-sparse may also impede interpretation, unless arbitrary thresholding is applied. However, in neuroimaging, it is essential to uncover clinically interpretable phenotypic markers that would account for the main variability in the brain images of a population. Recently, some alternatives to the standard PCA approach, such as sparse PCA (SPCA), have been proposed, their aim being to limit the density of the components. Nonetheless, sparsity alone does not entirely solve the interpretability problem in neuroimaging, since it may yield scattered and unstable components. We hypothesized that the incorporation of prior information regarding the structure of the data may lead to improved relevance and interpretability of brain patterns. We therefore present a simple extension of the popular PCA framework that adds structured sparsity penalties on the loading vectors in order to identify the few stable regions in the brain images that capture most of the variability. Such structured sparsity can be obtained by combining, e.g., and total variation (TV) penalties, where the TV regularization encodes information on the underlying structure of the data. This paper presents the structured SPCA (denoted SPCA-TV) optimization framework and its resolution. We demonstrate SPCA-TV's effectiveness and versatility on three different data sets. It can be applied to any kind of structured data, such as, e.g., -dimensional array images or meshes of cortical surfaces. The gains of SPCA-TV over unstructured approaches (such as SPCA and ElasticNet PCA) or structured approach (such as GraphNet PCA) are significant, since SPCA-TV reveals the variability within a data set in the form of intelligible brain patterns that are easier to interpret and more stable across different samples.

Disturbance and productivity interactions mediate stability of forest composition and structure.

PubMed

O'Connor, Christopher D; Falk, Donald A; Lynch, Ann M; Swetnam, Thomas W; Wilcox, Craig P

2017-04-01

Fire is returning to many conifer-dominated forests where species composition and structure have been altered by fire exclusion. Ecological effects of these fires are influenced strongly by the degree of forest change during the fire-free period. Response of fire-adapted species assemblages to extended fire-free intervals is highly variable, even in communities with similar historical fire regimes. This variability in plant community response to fire exclusion is not well understood; however, ecological mechanisms such as individual species' adaptations to disturbance or competition and underlying site characteristics that facilitate or impede establishment and growth have been proposed as potential drivers of assemblage response. We used spatially explicit dendrochronological reconstruction of tree population dynamics and fire regimes to examine the influence of historical disturbance frequency (a proxy for adaptation to disturbance or competition), and potential site productivity (a proxy for underlying site characteristics) on the stability of forest composition and structure along a continuous ecological gradient of pine, dry mixed-conifer, mesic mixed-conifer, and spruce-fir forests following fire exclusion. While average structural density increased in all forests, species composition was relatively stable in the lowest productivity pine-dominated and highest productivity spruce-fir-dominated sites immediately following fire exclusion and for the next 100 years, suggesting site productivity as a primary control on species composition and structure in forests with very different historical fire regimes. Species composition was least stable on intermediate productivity sites dominated by mixed-conifer forests, shifting from primarily fire-adapted species to competition-adapted, fire-sensitive species within 20 years of fire exclusion. Rapid changes to species composition and stand densities have been interpreted by some as evidence of high-severity fire. We demonstrate that the very different ecological process of fire exclusion can produce similar changes by shifting selective pressures from disturbance-mediated to productivity-mediated controls. Restoring disturbance-adapted species composition and structure to intermediate productivity forests may help to buffer them against projected increasing temperatures, lengthening fire seasons, and more frequent and prolonged moisture stress. Fewer management options are available to promote adaptation in forest assemblages historically constrained by underlying site productivity. © 2016 by the Ecological Society of America.

The hierarchical porous structure bio-char assessments produced by co-pyrolysis of municipal sewage sludge and hazelnut shell and Cu(II) adsorption kinetics.

PubMed

Zhao, Bing; Xu, Xinyang; Zeng, Fanqiang; Li, Haibo; Chen, Xi

2018-05-04

The co-pyrolysis technology was applied to municipal sewage sludge (MSS) and hazelnut shell with alkaline activating agent K 2 CO 3 under N 2 atmosphere. The innovative bio-char produced by co-pyrolysis had significant physical and chemical characteristics. The specific surface area reached 1990.23 m 2 /g, and the iodine absorption number was 1068.22 mg/g after co-pyrolysis at 850 °C. Although hazelnut shell was a kind of solid waste, it also had abundant cellulose resource, which could contribute to porous structure of bio-char during co-pyrolysis with MSS and decrease total heavy metals contents of raw material to increase security of bio-chars. Meanwhile, the residual fractions of heavy metals in bio-char were above 92.95% after co-pyrolysis at 900 °C except Cd to prevent heavy metals digestion, and the bio-char presented significant immobilization behavior from co-pyrolysis technology. Moreover, the yield and the iodine absorption number of bio-chars under different process variables were analyzed, and it was confirmed that appropriate process variables could contribute the yield and the iodine absorption number of bio-char and prevent to etch pore structure excessively to collapse. The changes of surface functional groups and crystallographic structure before and after co-pyrolysis were analyzed by FTIR and XRD, respectively. The hierarchical porous structure of bio-char was presented by SEM and N 2 adsorption-desorption isotherm. The Cu(II) adsorption capacity of the bio-char was 42.28 mg/g after 24 h, and surface functional groups acted as active binding sites for Cu(II) adsorption. Langmuir model and pseudo-second-order model can describe process of Cu(II) adsorption well.

Developmental models for estimating ecological responses to environmental variability: structural, parametric, and experimental issues.

PubMed

Moore, Julia L; Remais, Justin V

2014-03-01

Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.

Effects of parceling on model selection: Parcel-allocation variability in model ranking.

PubMed

Sterba, Sonya K; Rights, Jason D

2017-03-01

Research interest often lies in comparing structural model specifications implying different relationships among latent factors. In this context parceling is commonly accepted, assuming the item-level measurement structure is well known and, conservatively, assuming items are unidimensional in the population. Under these assumptions, researchers compare competing structural models, each specified using the same parcel-level measurement model. However, little is known about consequences of parceling for model selection in this context-including whether and when model ranking could vary across alternative item-to-parcel allocations within-sample. This article first provides a theoretical framework that predicts the occurrence of parcel-allocation variability (PAV) in model selection index values and its consequences for PAV in ranking of competing structural models. These predictions are then investigated via simulation. We show that conditions known to manifest PAV in absolute fit of a single model may or may not manifest PAV in model ranking. Thus, one cannot assume that low PAV in absolute fit implies a lack of PAV in ranking, and vice versa. PAV in ranking is shown to occur under a variety of conditions, including large samples. To provide an empirically supported strategy for selecting a model when PAV in ranking exists, we draw on relationships between structural model rankings in parcel- versus item-solutions. This strategy employs the across-allocation modal ranking. We developed software tools for implementing this strategy in practice, and illustrate them with an example. Even if a researcher has substantive reason to prefer one particular allocation, investigating PAV in ranking within-sample still provides an informative sensitivity analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Variable electronic stripe structures of the parent iron-chalcogenide superconductor Fe1 +dTe observed by STM-STS

NASA Astrophysics Data System (ADS)

Sugimoto, Akira; Ekino, Toshikazu; Gabovich, Alexander M.

2014-12-01

Nanoscale stripe structures of the parent iron-11 superconductor Fe1.033Te were investigated using low-temperature scanning tunnel microscopy-scanning tunnel spectroscopy (STM-STS). STM topographies and d I /d V maps show clear stripe structures with the bias-dependent multiple periods 2 ×a0 and a0, where a0 is the lattice constant ˜0.38 nm. The form of the stripe structures seen on d I /d V maps strongly depends on the bias voltage. Varying stripe structures are apparently driven by magnetic order appearing below the transition temperature Ts˜72 K, that is defined by the noticeable drop in the temperature dependence of resistivity, and are strongly influenced by the underlying excess Fe.

Ultrasound liquid crystal lens

NASA Astrophysics Data System (ADS)

Shimizu, Yuki; Koyama, Daisuke; Fukui, Marina; Emoto, Akira; Nakamura, Kentaro; Matsukawa, Mami

2018-04-01

A variable-focus lens using a combination of liquid crystals and ultrasound is discussed. The lens uses a technique based on ultrasound vibration to control the molecular orientation of the liquid crystal. The lens structure is simple, with no mechanical moving parts and no transparent electrodes, which is helpful for device downsizing; the structure consists of a liquid crystal layer sandwiched between two glass substrates with a piezoelectric ring. The tens-of-kHz ultrasonic resonance flexural vibration used to excite the lens generates an acoustic radiation force on the liquid crystal layer to induce changes in the molecular orientation of the liquid crystal. The orientations of the liquid crystal molecules and the optical characteristics of the lens were investigated under ultrasound excitation. Clear optical images were observed through the lens, and the focal point could be controlled using the input voltage to the piezoelectric ring to give the lens its variable-focus action.

Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data

USGS Publications Warehouse

Hagar, Joan C.; Eskelson, Bianca N.I.; Haggerty, Patricia K.; Nelson, S. Kim; Vesely, David G.

2014-01-01

LiDAR (Light Detection And Ranging) is an emerging remote-sensing tool that can provide fine-scale data describing vertical complexity of vegetation relevant to species that are responsive to forest structure. We used LiDAR data to estimate occupancy probability for the federally threatened marbled murrelet (Brachyramphus marmoratus) in the Oregon Coast Range of the United States. Our goal was to address the need identified in the Recovery Plan for a more accurate estimate of the availability of nesting habitat by developing occupancy maps based on refined measures of nest-strand structure. We used murrelet occupancy data collected by the Bureau of Land Management Coos Bay District, and canopy metrics calculated from discrete return airborne LiDAR data, to fit a logistic regression model predicting the probability of occupancy. Our final model for stand-level occupancy included distance to coast, and 5 LiDAR-derived variables describing canopy structure. With an area under the curve value (AUC) of 0.74, this model had acceptable discrimination and fair agreement (Cohen's κ = 0.24), especially considering that all sites in our sample were regarded by managers as potential habitat. The LiDAR model provided better discrimination between occupied and unoccupied sites than did a model using variables derived from Gradient Nearest Neighbor maps that were previously reported as important predictors of murrelet occupancy (AUC = 0.64, κ = 0.12). We also evaluated LiDAR metrics at 11 known murrelet nest sites. Two LiDAR-derived variables accurately discriminated nest sites from random sites (average AUC = 0.91). LiDAR provided a means of quantifying 3-dimensional canopy structure with variables that are ecologically relevant to murrelet nesting habitat, and have not been as accurately quantified by other mensuration methods.

Analysis of dynamic accumulative damage about the lining structure of high speed railway’s tunnel based on ultrasonic testing technology

NASA Astrophysics Data System (ADS)

Wang, Xiang-qiu; Zhang, Huojun; Xie, Wen-xi

2017-08-01

Based on the similar material model test of full tunnel, the theory of elastic wave propagation and the testing technology of intelligent ultrasonic wave had been used to research the dynamic accumulative damage characteristics of tunnel’s lining structure under the dynamic loads of high speed train. For the more, the dynamic damage variable of lining structure of high speed railway’s tunnel was obtained. The results shown that the dynamic cumulative damage of lining structure increases nonlinearly with the times of cumulative vibration, the weakest part of dynamic cumulative damage is the arch foot of tunnel. Much more attention should be paid to the design and operation management of high speed railway’s tunnel.

Aggressiveness as a latent personality trait of domestic dogs: Testing local independence and measurement invariance

PubMed Central

2017-01-01

Studies of animal personality attempt to uncover underlying or “latent” personality traits that explain broad patterns of behaviour, often by applying latent variable statistical models (e.g., factor analysis) to multivariate data sets. Two integral, but infrequently confirmed, assumptions of latent variable models in animal personality are: i) behavioural variables are independent (i.e., uncorrelated) conditional on the latent personality traits they reflect (local independence), and ii) personality traits are associated with behavioural variables in the same way across individuals or groups of individuals (measurement invariance). We tested these assumptions using observations of aggression in four age classes (4–10 months, 10 months–3 years, 3–6 years, over 6 years) of male and female shelter dogs (N = 4,743) in 11 different contexts. A structural equation model supported the hypothesis of two positively correlated personality traits underlying aggression across contexts: aggressiveness towards people and aggressiveness towards dogs (comparative fit index: 0.96; Tucker-Lewis index: 0.95; root mean square error of approximation: 0.03). Aggression across contexts was moderately repeatable (towards people: intraclass correlation coefficient (ICC) = 0.479; towards dogs: ICC = 0.303). However, certain contexts related to aggressiveness towards people (but not dogs) shared significant residual relationships unaccounted for by latent levels of aggressiveness. Furthermore, aggressiveness towards people and dogs in different contexts interacted with sex and age. Thus, sex and age differences in displays of aggression were not simple functions of underlying aggressiveness. Our results illustrate that the robustness of traits in latent variable models must be critically assessed before making conclusions about the effects of, or factors influencing, animal personality. Our findings are of concern because inaccurate “aggressive personality” trait attributions can be costly to dogs, recipients of aggression and society in general. PMID:28854267

Aggressiveness as a latent personality trait of domestic dogs: Testing local independence and measurement invariance.

PubMed

Goold, Conor; Newberry, Ruth C

2017-01-01

Studies of animal personality attempt to uncover underlying or "latent" personality traits that explain broad patterns of behaviour, often by applying latent variable statistical models (e.g., factor analysis) to multivariate data sets. Two integral, but infrequently confirmed, assumptions of latent variable models in animal personality are: i) behavioural variables are independent (i.e., uncorrelated) conditional on the latent personality traits they reflect (local independence), and ii) personality traits are associated with behavioural variables in the same way across individuals or groups of individuals (measurement invariance). We tested these assumptions using observations of aggression in four age classes (4-10 months, 10 months-3 years, 3-6 years, over 6 years) of male and female shelter dogs (N = 4,743) in 11 different contexts. A structural equation model supported the hypothesis of two positively correlated personality traits underlying aggression across contexts: aggressiveness towards people and aggressiveness towards dogs (comparative fit index: 0.96; Tucker-Lewis index: 0.95; root mean square error of approximation: 0.03). Aggression across contexts was moderately repeatable (towards people: intraclass correlation coefficient (ICC) = 0.479; towards dogs: ICC = 0.303). However, certain contexts related to aggressiveness towards people (but not dogs) shared significant residual relationships unaccounted for by latent levels of aggressiveness. Furthermore, aggressiveness towards people and dogs in different contexts interacted with sex and age. Thus, sex and age differences in displays of aggression were not simple functions of underlying aggressiveness. Our results illustrate that the robustness of traits in latent variable models must be critically assessed before making conclusions about the effects of, or factors influencing, animal personality. Our findings are of concern because inaccurate "aggressive personality" trait attributions can be costly to dogs, recipients of aggression and society in general.

Low-contrast lesion detection in tomosynthetic breast imaging using a realistic breast phantom

NASA Astrophysics Data System (ADS)

Zhou, Lili; Oldan, Jorge; Fisher, Paul; Gindi, Gene

2006-03-01

Tomosynthesis mammography is a potentially valuable technique for detection of breast cancer. In this simulation study, we investigate the efficacy of three different tomographic reconstruction methods, EM, SART and Backprojection, in the context of an especially difficult mammographic detection task. The task is the detection of a very low-contrast mass embedded in very dense fibro-glandular tissue - a clinically useful task for which tomosynthesis may be well suited. The project uses an anatomically realistic 3D digital breast phantom whose normal anatomic variability limits lesion conspicuity. In order to capture anatomical object variability, we generate an ensemble of phantoms, each of which comprises random instances of various breast structures. We construct medium-sized 3D breast phantoms which model random instances of ductal structures, fibrous connective tissue, Cooper's ligaments and power law structural noise for small scale object variability. Random instances of 7-8 mm irregular masses are generated by a 3D random walk algorithm and placed in very dense fibro-glandular tissue. Several other components of the breast phantom are held fixed, i.e. not randomly generated. These include the fixed breast shape and size, nipple structure, fixed lesion location, and a pectoralis muscle. We collect low-dose data using an isocentric tomosynthetic geometry at 11 angles over 50 degrees and add Poisson noise. The data is reconstructed using the three algorithms. Reconstructed slices through the center of the lesion are presented to human observers in a 2AFC (two-alternative-forced-choice) test that measures detectability by computing AUC (area under the ROC curve). The data collected in each simulation includes two sources of variability, that due to the anatomical variability of the phantom and that due to the Poisson data noise. We found that for this difficult task that the AUC value for EM (0.89) was greater than that for SART (0.83) and Backprojection (0.66).

Thermal optimum design for tracking primary mirror of Space Telescope

NASA Astrophysics Data System (ADS)

Pan, Hai-jun; Ruan, Ping; Li, Fu; Wang, Hong-Wei

2011-08-01

In the conventional method, the structural parameters of primary mirror are usually optimized just by the requirement of mechanical performance. Because the influences of structural parameters on thermal stability are not taken fully into account in this simple method, the lightweight optimum design of primary mirror usually brings the bad thermal stability, especially in the complex environment. In order to obtain better thermal stability, a new method about structure-thermal optimum design of tracking primary mirror is discussed. During the optimum process, both the lightweight ratio and thermal stability will be taken into account. The structure-thermal optimum is introduced into the analysis process and commenced after lightweight design as the secondary optimum. Using the engineering analysis of software ANSYS, a parameter finite element analysis (FEA) model of mirror is built. On the premise of appropriate lightweight ratio, the RMS of structure-thermal deformation of mirror surface and lightweight ratio are assigned to be state variables, and the maximal RMS of temperature gradient load to be object variable. The results show that certain structural parameters of tracking primary mirror have different influences on mechanical performance and thermal stability, even they are opposite. By structure-thermal optimizing, the optimized mirror model discussed in this paper has better thermal stability than the old one under the same thermal loads, which can drastically reduce difficulty in thermal control.

Optimizing weak lensing mass estimates for cluster profile uncertainty

DOE PAGES

Gruen, D.; Bernstein, G. M.; Lam, T. Y.; ...

2011-09-11

Weak lensing measurements of cluster masses are necessary for calibrating mass-observable relations (MORs) to investigate the growth of structure and the properties of dark energy. However, the measured cluster shear signal varies at fixed mass M 200m due to inherent ellipticity of background galaxies, intervening structures along the line of sight, and variations in the cluster structure due to scatter in concentrations, asphericity and substructure. We use N-body simulated halos to derive and evaluate a weak lensing circular aperture mass measurement M ap that minimizes the mass estimate variance <(M ap - M 200m) 2> in the presence of allmore » these forms of variability. Depending on halo mass and observational conditions, the resulting mass estimator improves on M ap filters optimized for circular NFW-profile clusters in the presence of uncorrelated large scale structure (LSS) about as much as the latter improve on an estimator that only minimizes the influence of shape noise. Optimizing for uncorrelated LSS while ignoring the variation of internal cluster structure puts too much weight on the profile near the cores of halos, and under some circumstances can even be worse than not accounting for LSS at all. As a result, we discuss the impact of variability in cluster structure and correlated structures on the design and performance of weak lensing surveys intended to calibrate cluster MORs.« less

Optimization of an Aeroservoelastic Wing with Distributed Multiple Control Surfaces

NASA Technical Reports Server (NTRS)

Stanford, Bret K.

2015-01-01

This paper considers the aeroelastic optimization of a subsonic transport wingbox under a variety of static and dynamic aeroelastic constraints. Three types of design variables are utilized: structural variables (skin thickness, stiffener details), the quasi-steady deflection scheduling of a series of control surfaces distributed along the trailing edge for maneuver load alleviation and trim attainment, and the design details of an LQR controller, which commands oscillatory hinge moments into those same control surfaces. Optimization problems are solved where a closed loop flutter constraint is forced to satisfy the required flight margin, and mass reduction benefits are realized by relaxing the open loop flutter requirements.

A Bayesian approach to model structural error and input variability in groundwater modeling

NASA Astrophysics Data System (ADS)

Xu, T.; Valocchi, A. J.; Lin, Y. F. F.; Liang, F.

2015-12-01

Effective water resource management typically relies on numerical models to analyze groundwater flow and solute transport processes. Model structural error (due to simplification and/or misrepresentation of the "true" environmental system) and input forcing variability (which commonly arises since some inputs are uncontrolled or estimated with high uncertainty) are ubiquitous in groundwater models. Calibration that overlooks errors in model structure and input data can lead to biased parameter estimates and compromised predictions. We present a fully Bayesian approach for a complete assessment of uncertainty for spatially distributed groundwater models. The approach explicitly recognizes stochastic input and uses data-driven error models based on nonparametric kernel methods to account for model structural error. We employ exploratory data analysis to assist in specifying informative prior for error models to improve identifiability. The inference is facilitated by an efficient sampling algorithm based on DREAM-ZS and a parameter subspace multiple-try strategy to reduce the required number of forward simulations of the groundwater model. We demonstrate the Bayesian approach through a synthetic case study of surface-ground water interaction under changing pumping conditions. It is found that explicit treatment of errors in model structure and input data (groundwater pumping rate) has substantial impact on the posterior distribution of groundwater model parameters. Using error models reduces predictive bias caused by parameter compensation. In addition, input variability increases parametric and predictive uncertainty. The Bayesian approach allows for a comparison among the contributions from various error sources, which could inform future model improvement and data collection efforts on how to best direct resources towards reducing predictive uncertainty.

Evolution of stochastic demography with life history tradeoffs in density-dependent age-structured populations.

PubMed

Lande, Russell; Engen, Steinar; Sæther, Bernt-Erik

2017-10-31

We analyze the stochastic demography and evolution of a density-dependent age- (or stage-) structured population in a fluctuating environment. A positive linear combination of age classes (e.g., weighted by body mass) is assumed to act as the single variable of population size, [Formula: see text], exerting density dependence on age-specific vital rates through an increasing function of population size. The environment fluctuates in a stationary distribution with no autocorrelation. We show by analysis and simulation of age structure, under assumptions often met by vertebrate populations, that the stochastic dynamics of population size can be accurately approximated by a univariate model governed by three key demographic parameters: the intrinsic rate of increase and carrying capacity in the average environment, [Formula: see text] and [Formula: see text], and the environmental variance in population growth rate, [Formula: see text] Allowing these parameters to be genetically variable and to evolve, but assuming that a fourth parameter, [Formula: see text], measuring the nonlinearity of density dependence, remains constant, the expected evolution maximizes [Formula: see text] This shows that the magnitude of environmental stochasticity governs the classical trade-off between selection for higher [Formula: see text] versus higher [Formula: see text] However, selection also acts to decrease [Formula: see text], so the simple life-history trade-off between [Formula: see text]- and [Formula: see text]-selection may be obscured by additional trade-offs between them and [Formula: see text] Under the classical logistic model of population growth with linear density dependence ([Formula: see text]), life-history evolution in a fluctuating environment tends to maximize the average population size. Published under the PNAS license.

Creation of Synthetic Surface Temperature and Precipitation Ensembles Through A Computationally Efficient, Mixed Method Approach

NASA Astrophysics Data System (ADS)

Hartin, C.; Lynch, C.; Kravitz, B.; Link, R. P.; Bond-Lamberty, B. P.

2017-12-01

Typically, uncertainty quantification of internal variability relies on large ensembles of climate model runs under multiple forcing scenarios or perturbations in a parameter space. Computationally efficient, standard pattern scaling techniques only generate one realization and do not capture the complicated dynamics of the climate system (i.e., stochastic variations with a frequency-domain structure). In this study, we generate large ensembles of climate data with spatially and temporally coherent variability across a subselection of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. First, for each CMIP5 model we apply a pattern emulation approach to derive the model response to external forcing. We take all the spatial and temporal variability that isn't explained by the emulator and decompose it into non-physically based structures through use of empirical orthogonal functions (EOFs). Then, we perform a Fourier decomposition of the EOF projection coefficients to capture the input fields' temporal autocorrelation so that our new emulated patterns reproduce the proper timescales of climate response and "memory" in the climate system. Through this 3-step process, we derive computationally efficient climate projections consistent with CMIP5 model trends and modes of variability, which address a number of deficiencies inherent in the ability of pattern scaling to reproduce complex climate model behavior.

The discovery of indicator variables for QSAR using inductive logic programming

NASA Astrophysics Data System (ADS)

King, Ross D.; Srinivasan, Ashwin

1997-11-01

A central problem in forming accurate regression equations in QSAR studies isthe selection of appropriate descriptors for the compounds under study. Wedescribe a novel procedure for using inductive logic programming (ILP) todiscover new indicator variables (attributes) for QSAR problems, and show thatthese improve the accuracy of the derived regression equations. ILP techniqueshave previously been shown to work well on drug design problems where thereis a large structural component or where clear comprehensible rules arerequired. However, ILP techniques have had the disadvantage of only being ableto make qualitative predictions (e.g. active, inactive) and not to predictreal numbers (regression). We unify ILP and linear regression techniques togive a QSAR method that has the strength of ILP at describing stericstructure, with the familiarity and power of linear regression. We evaluatedthe utility of this new QSAR technique by examining the prediction ofbiological activity with and without the addition of new structural indicatorvariables formed by ILP. In three out of five datasets examined the additionof ILP variables produced statistically better results (P < 0.01) over theoriginal description. The new ILP variables did not increase the overallcomplexity of the derived QSAR equations and added insight into possiblemechanisms of action. We conclude that ILP can aid in the process of drugdesign.

Relative controls of external and internal variability on time-variable transit time distributions, and the importance of StorAge Selection function approaches

NASA Astrophysics Data System (ADS)

Kim, M.; Pangle, L. A.; Cardoso, C.; Lora, M.; Meira, A.; Volkmann, T. H. M.; Wang, Y.; Harman, C. J.; Troch, P. A. A.

2015-12-01

Transit time distributions (TTDs) are an efficient way of characterizing complex transport dynamics of a hydrologic system. Time-invariant TTD has been studied extensively, but TTDs are time-varying under unsteady hydrologic systems due to both external variability (e.g., time-variability in fluxes), and internal variability (e.g., time-varying flow pathways). The use of "flow-weighted time" has been suggested to account for the effect of external variability on TTDs, but neglects the role of internal variability. Recently, to account both types of variability, StorAge Selection (SAS) function approaches were developed. One of these approaches enables the transport characteristics of a system - how the different aged water in the storage is sampled by the outflow - to be parameterized by time-variable probability distribution called the rank SAS (rSAS) function, and uses it directly to determine the time-variable TTDs resulting from a given timeseries of fluxes in and out of a system. Unlike TTDs, the form of the rSAS function varies only due to changes in flow pathways, but is not affected by the timing of fluxes alone. However, the relation between physical mechanisms and the time-varying rSAS functions are not well understood. In this study, relative effects of internal and external variability on the TTDs are examined using observations from a homogeneously packed 1 m3 sloping soil lysimeter. The observations suggest the importance of internal variability on TTDs, and reinforce the need to account for this variability using time-variable rSAS functions. Furthermore, the relative usefulness of two other formulations of SAS functions and the mortality rate (which plays a similar role to SAS functions in the McKendrick-von Foerster model of age-structured population dynamics) are also discussed. Finally, numerical modeling is used to explore the role of internal and external variability for hydrologic systems with diverse geomorphic and climate characteristics. This works will give an insight that which approach (or SAS function) is preferable under different conditions.

Structure of solar coronal streamers

NASA Astrophysics Data System (ADS)

Schultz, C. G.

The present, direct method for the solution of generalized potential problems works outward from an O-point, under an assumption of the existence of flux surfaces. At each flux surface, a Fourier filter is used for the flux surface length variable to prevent numerical error amplifications, and the value of the inverse curvature radius and the normal direction are filtered to avoid the effects of local wrinkles.

Thermal loading in the laser holography nondestructive testing of a composite structure

NASA Technical Reports Server (NTRS)

Liu, H. K.; Kurtz, R. L.

1975-01-01

A laser holographic interferometry method that has variable sensitivity to surface deformation was applied to the investigation of composite test samples under thermal loading. A successful attempt was made to detect debonds in a fiberglass-epoxy-ceramic plate. Experimental results are presented along with the mathematical analysis of the physical model of the thermal loading and current conduction in the composite material.

Finite Element Based Structural Damage Detection Using Artificial Boundary Conditions

DTIC Science & Technology

2007-09-01

C. (2005). Elementary Linear Algebra . New York: John Wiley and Sons. Avitable, Peter (2001, January) Experimental Modal Analysis, A Simple Non...variables under consideration. 3 Frequency sensitivities are the basis for a linear approximation to compute the change in the natural frequencies of a...THEORY The general problem statement for a non- linear constrained optimization problem is: To minimize ( )f x Objective Function Subject to

Internal Tooth Structure and Burial Practices: Insights into the Neolithic Necropolis of Gurgy (France, 5100-4000 cal. BC).

PubMed

Le Luyer, Mona; Coquerelle, Michael; Rottier, Stéphane; Bayle, Priscilla

2016-01-01

Variations in the dental crown form are widely studied to interpret evolutionary changes in primates as well as to assess affinities among human archeological populations. Compared to external metrics of dental crown size and shape, variables including the internal structures such as enamel thickness, tissue proportions, and the three-dimensional shape of enamel-dentin junction (EDJ), have been described as powerful measurements to study taxonomy, phylogenetic relationships, dietary, and/or developmental patterns. In addition to providing good estimate of phenotypic distances within/across archeological samples, these internal tooth variables may help to understand phylogenetic, functional, and developmental underlying causes of variation. In this study, a high resolution microtomographic-based record of upper permanent second molars from 20 Neolithic individuals of the necropolis of Gurgy (France) was applied to evaluate the intrasite phenotypic variation in crown tissue proportions, thickness and distribution of enamel, and EDJ shape. The study aims to compare interindividual dental variations with burial practices and chronocultural parameters, and suggest underlying causes of these dental variations. From the non-invasive characterization of internal tooth structure, differences have been found between individuals buried in pits with alcove and those buried in pits with container and pits with wattling. Additionally, individuals from early and recent phases of the necropolis have been distinguished from those of the principal phase from their crown tissue proportions and EDJ shape. The results suggest that the internal tooth structure may be a reliable proxy to track groups sharing similar chronocultural and burial practices. In particular, from the EDJ shape analysis, individuals buried in an alcove shared a reduction of the distolingual dentin horn tip (corresponding to the hypocone). Environmental, developmental and/or functional underlying causes might be suggested for the origin of phenotypic differences shared by these individuals buried in alcoves.

Commercialization of NESSUS: Status

NASA Technical Reports Server (NTRS)

Thacker, Ben H.; Millwater, Harry R.

1991-01-01

A plan was initiated in 1988 to commercialize the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) probabilistic structural analysis software. The goal of the on-going commercialization effort is to begin the transfer of Probabilistic Structural Analysis Method (PSAM) developed technology into industry and to develop additional funding resources in the general area of structural reliability. The commercialization effort is summarized. The SwRI NESSUS Software System is a general purpose probabilistic finite element computer program using state of the art methods for predicting stochastic structural response due to random loads, material properties, part geometry, and boundary conditions. NESSUS can be used to assess structural reliability, to compute probability of failure, to rank the input random variables by importance, and to provide a more cost effective design than traditional methods. The goal is to develop a general probabilistic structural analysis methodology to assist in the certification of critical components in the next generation Space Shuttle Main Engine.

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852

Robust multi-model control of an autonomous wind power system

NASA Astrophysics Data System (ADS)

Cutululis, Nicolas Antonio; Ceanga, Emil; Hansen, Anca Daniela; Sørensen, Poul

2006-09-01

This article presents a robust multi-model control structure for a wind power system that uses a variable speed wind turbine (VSWT) driving a permanent magnet synchronous generator (PMSG) connected to a local grid. The control problem consists in maximizing the energy captured from the wind for varying wind speeds. The VSWT-PMSG linearized model analysis reveals the resonant nature of its dynamic at points on the optimal regimes characteristic (ORC). The natural frequency of the system and the damping factor are strongly dependent on the operating point on the ORC. Under these circumstances a robust multi-model control structure is designed. The simulation results prove the viability of the proposed control structure. Copyright

A possible explanation for the divergent projection of ENSO amplitude change under global warming

NASA Astrophysics Data System (ADS)

Chen, Lin; Li, Tim; Yu, Yongqiang; Behera, Swadhin K.

2017-12-01

The El Niño-Southern Oscillation (ENSO) is the greatest climate variability on interannual time scale, yet what controls ENSO amplitude changes under global warming (GW) is uncertain. Here we show that the fundamental factor that controls the divergent projections of ENSO amplitude change within 20 coupled general circulation models that participated in the Coupled Model Intercomparison Project phase-5 is the change of climatologic mean Pacific subtropical cell (STC), whose strength determines the meridional structure of ENSO perturbations and thus the anomalous thermocline response to the wind forcing. The change of the thermocline response is a key factor regulating the strength of Bjerknes thermocline and zonal advective feedbacks, which ultimately lead to the divergent changes in ENSO amplitude. Furthermore, by forcing an ocean general circulation mode with the change of zonal mean zonal wind stress estimated by a simple theoretical model, a weakening of the STC in future is obtained. Such a change implies that ENSO variability might strengthen under GW, which could have a profound socio-economic consequence.

Synthesis of novel stable compounds in the phosphorous-nitrogen system under pressure

NASA Astrophysics Data System (ADS)

Stavrou, Elissaios; Batyrev, Iskander; Ciezak-Jenkins, Jennifer; Grivickas, Paulius; Zaug, Joseph; Greenberg, Eran; Kunz, Martin

2017-06-01

We explore the possible formation of stable, and metastable at ambient conditions, polynitrogen compounds in the P-N system under pressure using in situ X-ray diffraction and Raman spectroscopy in synergy with first-principles evolutionary structural search algorithms (USPEX). We have performed numerous synthesis experiments at pressures from near ambient up to +50 GPa using both a mixture of elemental P and N2 and relevant precursors such as P3N5. Calculation of P-N extended structures at 10, 30, and 50 GPa was done using USPEX based on density functional theory (DFT) plane-waves calculations (VASP) with ultrasoft pseudopotentials. Full convex plot was found for N rich concentrations of P-N binary system. Variable content calculations were complemented by fixed concentration calculations at certain nitrogen rich concentration. Stable structures refined by DFT calculations using norm-concerning pseudopotentials. A comparison between our results and previous studies in the same system will be also given. Part of this work was performed under the auspices of the U. S. DoE by LLNS, LLC under Contract DE-AC52-07NA27344. We thank the Joint DoD/DOE Munitions Technology Development Program and the HE science C-II program at LLNL for supporting this study.

Prediction of the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient-elution conditions.

PubMed

D'Archivio, Angelo Antonio; Maggi, Maria Anna; Ruggieri, Fabrizio

2014-08-01

In this paper, a multilayer artificial neural network is used to model simultaneously the effect of solute structure and eluent concentration profile on the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient elution. The retention data of 24 triazines, including common herbicides and their metabolites, are collected under 13 different elution modes, covering the following experimental domain: starting acetonitrile volume fraction ranging between 40 and 60% and gradient slope ranging between 0 and 1% acetonitrile/min. The gradient parameters together with five selected molecular descriptors, identified by quantitative structure-retention relationship modelling applied to individual separation conditions, are the network inputs. Predictive performance of this model is evaluated on six external triazines and four unseen separation conditions. For comparison, retention of triazines is modelled by both quantitative structure-retention relationships and response surface methodology, which describe separately the effect of molecular structure and gradient parameters on the retention. Although applied to a wider variable domain, the network provides a performance comparable to that of the above "local" models and retention times of triazines are modelled with accuracy generally better than 7%. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Regional-scale drivers of forest structure and function in northwestern Amazonia.

PubMed

Higgins, Mark A; Asner, Gregory P; Anderson, Christopher B; Martin, Roberta E; Knapp, David E; Tupayachi, Raul; Perez, Eneas; Elespuru, Nydia; Alonso, Alfonso

2015-01-01

Field studies in Amazonia have found a relationship at continental scales between soil fertility and broad trends in forest structure and function. Little is known at regional scales, however, about how discrete patterns in forest structure or functional attributes map onto underlying edaphic or geological patterns. We collected airborne LiDAR (Light Detection and Ranging) data and VSWIR (Visible to Shortwave Infrared) imaging spectroscopy measurements over 600 km2 of northwestern Amazonian lowland forests. We also established 83 inventories of plant species composition and soil properties, distributed between two widespread geological formations. Using these data, we mapped forest structure and canopy reflectance, and compared them to patterns in plant species composition, soils, and underlying geology. We found that variations in soils and species composition explained up to 70% of variation in canopy height, and corresponded to profound changes in forest vertical profiles. We further found that soils and plant species composition explained more than 90% of the variation in canopy reflectance as measured by imaging spectroscopy, indicating edaphic and compositional control of canopy chemical properties. We last found that soils explained between 30% and 70% of the variation in gap frequency in these forests, depending on the height threshold used to define gaps. Our findings indicate that a relatively small number of edaphic and compositional variables, corresponding to underlying geology, may be responsible for variations in canopy structure and chemistry over large expanses of Amazonian forest.

Climate and Edaphic Controls on Humid Tropical Forest Tree Height

NASA Astrophysics Data System (ADS)

Yang, Y.; Saatchi, S. S.; Xu, L.

2014-12-01

Uncertainty in the magnitude and spatial variations of forest carbon density in tropical regions is due to under sampling of forest structure from inventory plots and the lack of regional allometry to estimate the carbon density from structure. Here we quantify the variation of tropical forest structure by using more than 2.5 million measurements of canopy height from systematic sampling of Geoscience Laser Altimeter System (GLAS) satellite observations between 2004 to 2008 and examine the climate and edaphic variables influencing the variations. We used top canopy height of GLAS footprints (~ 0.25 ha) to grid the statistical mean and 90 percentile of samples at 0.5 degrees to capture the regional variability of large trees in tropics. GLAS heights were also aggregated based on a stratification of tropical regions using soil, elevation, and forest types. Both approaches provided consistent patterns of statistically dominant large trees and the least heterogeneity, both as strong drivers of distribution of high biomass forests. Statistical models accounting for spatial autocorrelation suggest that climate, soil and spatial features together can explain more than 60% of the variations in observed tree height information, while climate-only variables explains about one third of the first-order changes in tree height. Soil basics, including physical compositions such as clay and sand contents, chemical properties such as PH values and cation-exchange capacity, as well as biological variables such as organic matters, all present independent but statistically significant relationships to tree height variations. The results confirm other landscape and regional studies that soil fertility, geology and climate may jointly control a majority of the regional variations of forest structure in pan-tropics and influencing both biomass stocks and dynamics. Consequently, other factors such as biotic and disturbance regimes, not included in this study, may have less influence on regional variations but strongly mediate landscape and small-scale forest structure and dynamics.

Spatial structure and scaling of macropores in hydrological process at small catchment scale

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Broer, Martine; Blöschl, Günter

2013-04-01

During rainfall events, the formation of overland flow can occur under the circumstances of saturation excess and/or infiltration excess. These conditions are affected by the soil moisture state which represents the soil water content in micropores and macropores. Macropores act as pathway for the preferential flows and have been widely studied locally. However, very little is known about their spatial structure and conductivity of macropores and other flow characteristic at the catchment scale. This study will analyze these characteristics to better understand its importance in hydrological processes. The research will be conducted in Petzenkirchen Hydrological Open Air Laboratory (HOAL), a 64 ha catchment located 100 km west of Vienna. The land use is divided between arable land (87%), pasture (5%), forest (6%) and paved surfaces (2%). Video cameras will be installed on an agricultural field to monitor the overland flow pattern during rainfall events. A wireless soil moisture network is also installed within the monitored area. These field data will be combined to analyze the soil moisture state and the responding surface runoff occurrence. The variability of the macropores spatial structure of the observed area (field scale) then will be assessed based on the topography and soil data. Soil characteristics will be supported with laboratory experiments on soil matrix flow to obtain proper definitions of the spatial structure of macropores and its variability. A coupled physically based distributed model of surface and subsurface flow will be used to simulate the variability of macropores spatial structure and its effect on the flow behaviour. This model will be validated by simulating the observed rainfall events. Upscaling from field scale to catchment scale will be done to understand the effect of macropores variability on larger scales by applying spatial stochastic methods. The first phase in this study is the installation and monitoring configuration of video cameras and soil moisture monitoring equipment to obtain the initial data of overland flow occurrence and soil moisture state relationships.

Fatigue Analyses Under Constant- and Variable-Amplitude Loading Using Small-Crack Theory

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.; Phillips, E. P.; Everett, R. A., Jr.

1999-01-01

Studies on the growth of small cracks have led to the observation that fatigue life of many engineering materials is primarily "crack growth" from micro-structural features, such as inclusion particles, voids, slip-bands or from manufacturing defects. This paper reviews the capabilities of a plasticity-induced crack-closure model to predict fatigue lives of metallic materials using "small-crack theory" under various loading conditions. Constraint factors, to account for three-dimensional effects, were selected to correlate large-crack growth rate data as a function of the effective stress-intensity factor range (delta-Keff) under constant-amplitude loading. Modifications to the delta-Keff-rate relations in the near-threshold regime were needed to fit measured small-crack growth rate behavior. The model was then used to calculate small-and large-crack growth rates, and to predict total fatigue lives, for notched and un-notched specimens under constant-amplitude and spectrum loading. Fatigue lives were predicted using crack-growth relations and micro-structural features like those that initiated cracks in the fatigue specimens for most of the materials analyzed. Results from the tests and analyses agreed well.

Structure-Property Relationships of Architectural Coatings by Neutron Methods

NASA Astrophysics Data System (ADS)

Nakatani, Alan

2015-03-01

Architectural coatings formulations are multi-component mixtures containing latex polymer binder, pigment, rheology modifiers, surfactants, and colorants. In order to achieve the desired flow properties for these formulations, measures of the underlying structure of the components as a function of shear rate and the impact of formulation variables on the structure is necessary. We have conducted detailed measurements to understand the evolution under shear of local microstructure and larger scale mesostructure in model architectural coatings formulations by small angle neutron scattering (SANS) and ultra small angle neutron scattering (USANS), respectively. The SANS results show an adsorbed layer of rheology modifier molecules exist on the surface of the latex particles. However, the additional hydrodynamic volume occupied by the adsorbed surface layer is insufficient to account for the observed viscosity by standard hard sphere suspension models (Krieger-Dougherty). The USANS results show the presence of latex aggregates, which are fractal in nature. These fractal aggregates are the primary structures responsible for coatings formulation viscosity. Based on these results, a new model for the viscosity of coatings formulations has been developed, which is capable of reproducing the observed viscosity behavior.

Modeling Protein Expression and Protein Signaling Pathways

PubMed Central

Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

2015-01-01

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

NASA Astrophysics Data System (ADS)

Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

2018-04-01

As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater growing season temporal variability, and reduced levels of soil moisture, whilst projected decreasing summer precipitation may alter the feedbacks between soil moisture and vegetation water use and increase growing season soil moisture deficits.

Effects of various conditions in cold-welding of copper nanowires: A molecular dynamics study

NASA Astrophysics Data System (ADS)

Zhou, Hongjian; Wu, Wen-ping; Wu, Runni; Hu, Guoming; Xia, Re

2017-11-01

Cold-welding possesses such desirable environment as low temperature and low applied stress, thus becoming the prime candidate for nanojointing and nanoassembly techniques. To explore the welding mechanism of nanoscale structures, here, molecular dynamics was performed on copper nanowires under different welding conditions and various original characteristics to obtain an atomic-level depiction of their cold-welding behavior. By analyzing the mechanical properties of as-welded nanowires, the relations between welding quality and welding variables are revealed and identified. This comparison study will be of great importance to future mechanical processing and structural assembly of metallic nanowires.

SSME structural computer program development. Volume 2: BOPACE users manual

NASA Technical Reports Server (NTRS)

Vos, R. G.

1973-01-01

A computer program for use with a thermal-elastic-plastic-creep structural analyzer is presented. The following functions of the computer program are discussed: (1) analysis of very high temperature and large plastic-creep effects, (2) treatment of cyclic thermal and mechanical loads, (3) development of constitutive theory which closely follows actual behavior under variable temperature conditions, (4) stable numerical solution approach which avoids cumulative errors, and (5) capability of handling up to 1000 degrees of freedom. The computer program is written in FORTRAN IV and has been run on the IBM 360 and UNIVAC 1108 computer systems.

[Inequality in primary care interventions in maternal and child health care in Mexico].

PubMed

Ramírez-Tirado, Laura Alejandra; Tirado-Gómez, Laura Leticia; López-Cervantes, Malaquías

2014-04-01

To analyze the principal indicators associated with maternal mortality and mortality in children under 1 year of age and evaluate coverage levels and variability among the federative entities of Mexico. Eight interventions in maternal and child primary health care (variables) were studied: complete vaccination series, measles vaccine, and pentavalent vaccine in children under 1 year of age; early breast-feeding; prenatal care with at least one check-up by trained staff; prevalence of contraceptive use among married women of reproductive age; obstetric care in delivery by trained staff; and the administration of tetanus toxoid (TT) to pregnant women. The average and standard deviation of national coverage for each variable was calculated. Within each federative entity the proportion of municipalities with high, medium, and low marginalization was determined. States were ranked by the proportion of municipalities with high marginalization (highest to lowest) and divided into quintiles. Absolute inequality was measured using the observed difference and relative inequality, using the ratio of each variable studied. The average national coverage for the eight variables studied ranged from 86.5% to 97.5%, with administration of TT to pregnant women the lowest and administration of measles vaccine to children under 1 year of age the highest. Obstetric care in delivery, prevalence of contraceptive use, and prenatal checkup were the variables with less equitable coverage. In states with higher levels of marginalization, activities dependent on a structured health system-e.g., obstetric care in delivery-showed lower levels of coverage compared to preventive activities not requiring costly inputs or infrastructure-e.g., early breast-feeding. Interventions exhibiting greater inequity are associated with the lack of medical infrastructure and are more accentuated in federative entities with higher levels of marginalization. Greater public health expenditure is urgently needed to implement feasible, effective alternatives in terms of access and health care. Intersectoral policies and activities should be implemented to create synergies that will equitably improve the health of Mexican mothers and children.

An Avian Basal Ganglia-Forebrain Circuit Contributes Differentially to Syllable Versus Sequence Variability of Adult Bengalese Finch Song

PubMed Central

Hampton, Cara M.; Sakata, Jon T.; Brainard, Michael S.

2009-01-01

Behavioral variability is important for motor skill learning but continues to be present and actively regulated even in well-learned behaviors. In adult songbirds, two types of song variability can persist and are modulated by social context: variability in syllable structure and variability in syllable sequencing. The degree to which the control of both types of adult variability is shared or distinct remains unknown. The output of a basal ganglia-forebrain circuit, LMAN (the lateral magnocellular nucleus of the anterior nidopallium), has been implicated in song variability. For example, in adult zebra finches, neurons in LMAN actively control the variability of syllable structure. It is unclear, however, whether LMAN contributes to variability in adult syllable sequencing because sequence variability in adult zebra finch song is minimal. In contrast, Bengalese finches retain variability in both syllable structure and syllable sequencing into adulthood. We analyzed the effects of LMAN lesions on the variability of syllable structure and sequencing and on the social modulation of these forms of variability in adult Bengalese finches. We found that lesions of LMAN significantly reduced the variability of syllable structure but not of syllable sequencing. We also found that LMAN lesions eliminated the social modulation of the variability of syllable structure but did not detect significant effects on the modulation of sequence variability. These results show that LMAN contributes differentially to syllable versus sequence variability of adult song and suggest that these forms of variability are regulated by distinct neural pathways. PMID:19357331

Gamma-Ray Light Curves And Variability Of Bright Fermi -Detected Blazars

DOE PAGES

Abdo, A. A.

2010-09-22

This paper presents light curves as well as the first systematic characterization of variability of the 106 objects in the high-confidence Fermi Large Area Telescope Bright AGN Sample (LBAS). Weekly light curves of this sample, obtained during the first 11 months of the Fermi survey (2008 August 4-2009 July 4), are tested for variability and their properties are quantified through autocorrelation function and structure function analysis. For the brightest sources, 3 or 4 day binned light curves are extracted in order to determine power density spectra (PDSs) and to fit the temporal structure of major flares. More than 50% ofmore » the sources are found to be variable with high significance, where high states do not exceed 1/4 of the total observation range. Variation amplitudes are larger for flat spectrum radio quasars and low/intermediate synchrotron frequency peaked BL Lac objects. Autocorrelation timescales derived from weekly light curves vary from four to a dozen of weeks. Variable sources of the sample have weekly and 3-4 day bin light curves that can be described by 1/f α PDS, and show two kinds of gamma-ray variability: (1) rather constant baseline with sporadic flaring activity characterized by flatter PDS slopes resembling flickering and red noise with occasional intermittence and (2)—measured for a few blazars showing strong activity—complex and structured temporal profiles characterized by long-term memory and steeper PDS slopes, reflecting a random walk underlying mechanism. The average slope of the PDS of the brightest 22 FSRQs and of the 6 brightest BL Lacs is 1.5 and 1.7, respectively. The study of temporal profiles of well-resolved flares observed in the 10 brightest LBAS sources shows that they generally have symmetric profiles and that their total duration vary between 10 and 100 days. Results presented here can assist in source class recognition for unidentified sources and can serve as reference for more detailed analysis of the brightest gamma-ray blazars.« less

Bayes Factor Covariance Testing in Item Response Models.

PubMed

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

2017-12-01

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

Functional Strain-Line Pattern in the Human Left Ventricle

NASA Astrophysics Data System (ADS)

Pedrizzetti, Gianni; Kraigher-Krainer, Elisabeth; De Luca, Alessio; Caracciolo, Giuseppe; Mangual, Jan O.; Shah, Amil; Toncelli, Loira; Domenichini, Federico; Tonti, Giovanni; Galanti, Giorgio; Sengupta, Partho P.; Narula, Jagat; Solomon, Scott

2012-07-01

Analysis of deformations in terms of principal directions appears well suited for biological tissues that present an underlying anatomical structure of fiber arrangement. We applied this concept here to study deformation of the beating heart in vivo analyzing 30 subjects that underwent accurate three-dimensional echocardiographic recording of the left ventricle. Results show that strain develops predominantly along the principal direction with a much smaller transversal strain, indicating an underlying anisotropic, one-dimensional contractile activity. The strain-line pattern closely resembles the helical anatomical structure of the heart muscle. These findings demonstrate that cardiac contraction occurs along spatially variable paths and suggest a potential clinical significance of the principal strain concept for the assessment of mechanical cardiac function. The same concept can help in characterizing the relation between functional and anatomical properties of biological tissues, as well as fiber-reinforced engineered materials.

Dynamic analysis of elastic rubber tired car wheel breaking under variable normal load

NASA Astrophysics Data System (ADS)

Fedotov, A. I.; Zedgenizov, V. G.; Ovchinnikova, N. I.

2017-10-01

The purpose of the paper is to analyze the dynamics of the braking of the wheel under normal load variations. The paper uses a mathematical simulation method according to which the calculation model of an object as a mechanical system is associated with a dynamically equivalent schematic structure of the automatic control. Transfer function tool analyzing structural and technical characteristics of an object as well as force disturbances were used. It was proved that the analysis of dynamic characteristics of the wheel subjected to external force disturbances has to take into account amplitude and phase-frequency characteristics. Normal load variations impact car wheel braking subjected to disturbances. The closer slip to the critical point is, the higher the impact is. In the super-critical area, load variations cause fast wheel blocking.

Mesoscale structure of microplankton and mesoplankton assemblages under contrasting oceanographic conditions in the Catalan Sea (NW Mediterranean)

NASA Astrophysics Data System (ADS)

Villate, Fernando; Uriarte, Ibon; Olivar, M. Pilar; Maynou, Francesc; Emelianov, Mikhail; Ameztoy, Iban

2014-11-01

The abundance, composition and mesoscale variability of the microplankton (53-200 μm) and the mesoplankton (0.2-2 mm) fractions in relation to oceanographic factors and phytoplankton biomass were compared off the Catalan coast (NW Mediterranean) during the summer stratification (June) and autumn mixing (November) periods in 2005. This work aims to determine whether the two plankton fractions that more contribute to fish larval diet respond to a common variable environment, and this study constitutes the first attempt to analyse, in parallel, the spatial structure of both fractions in this area. From June to November microplankton abundance increased mainly by the increase of dinoflagellates, tintinnids and radiolarians, and mesoplankton decreased due mainly to the decrease of long-horned dinoflagellates, cladocerans, doliolids and appendicularians. Plankton mesoscale variability in relation to environmental variables showed higher complexity in June, where environmental horizontal and vertical gradients were more marked than in November. In June, the major mode of variability of the microplankton was mainly accounted by the patchy distribution of several tintinnid species dominated by Rhabdonella spiralis associated to the subsurface phytoplankton biomass. The main mode of variability of the mesoplankton was related to the intrusion of the Ebro river plume and the related aggregation of doliolids and cladocerans, dominated by Evadne spinifera. In November, the major variability pattern in both fractions was a combination of inshore-offshore and eastern-western gradients in taxa distributions shaped mainly by the course of the Catalan Current along the shelf-break. Spatial differences in planktonic food pathways in each period are discussed on the basis of literature on plankton feeding habits and types, and on the diet of fish larvae of the main species from the same surveys.

Prediction and experimental observation of damage dependent damping in laminated composite beams

NASA Technical Reports Server (NTRS)

Allen, D. H.; Harris, C. E.; Highsmith, A. L.

1987-01-01

The equations of motion are developed for laminated composite beams with load-induced matrix cracking. The damage is accounted for by utilizing internal state variables. The net result of these variables on the field equations is the introduction of both enhanced damping, and degraded stiffness. Both quantities are history dependent and spatially variable, thus resulting in nonlinear equations of motion. It is explained briefly how these equations may be quasi-linearized for laminated polymeric composites under certain types of structural loading. The coupled heat conduction equation is developed, and it is shown that an enhanced Zener damping effect is produced by the introduction of microstructural damage. The resulting equations are utilized to demonstrate how damage dependent material properties may be obtained from dynamic experiments. Finaly, experimental results are compared to model predictions for several composite layups.

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

PubMed

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

2015-02-01

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

Medical University admission test: a confirmatory factor analysis of the results.

PubMed

Luschin-Ebengreuth, Marion; Dimai, Hans P; Ithaler, Daniel; Neges, Heide M; Reibnegger, Gilbert

2016-05-01

The Graz Admission Test has been applied since the academic year 2006/2007. The validity of the Test was demonstrated by a significant improvement of study success and a significant reduction of dropout rate. The purpose of this study was a detailed analysis of the internal correlation structure of the various components of the Graz Admission Test. In particular, the question investigated was whether or not the various test parts constitute a suitable construct which might be designated as "Basic Knowledge in Natural Science." This study is an observational investigation, analyzing the results of the Graz Admission Test for the study of human medicine and dentistry. A total of 4741 applicants were included in the analysis. Principal component factor analysis (PCFA) as well as techniques from structural equation modeling, specifically confirmatory factor analysis (CFA), were employed to detect potential underlying latent variables governing the behavior of the measured variables. PCFA showed good clustering of the science test parts, including also text comprehension. A putative latent variable "Basic Knowledge in Natural Science," investigated by CFA, was indeed shown to govern the response behavior of the applicants in biology, chemistry, physics, and mathematics as well as text comprehension. The analysis of the correlation structure of the various test parts confirmed that the science test parts together with text comprehension constitute a satisfactory instrument for measuring a latent construct variable "Basic Knowledge in Natural Science." The present results suggest the fundamental importance of basic science knowledge for results obtained in the framework of the admission process for medical universities.

Research participant compensation: A matter of statistical inference as well as ethics.

PubMed

Swanson, David M; Betensky, Rebecca A

2015-11-01

The ethics of compensation of research subjects for participation in clinical trials has been debated for years. One ethical issue of concern is variation among subjects in the level of compensation for identical treatments. Surprisingly, the impact of variation on the statistical inferences made from trial results has not been examined. We seek to identify how variation in compensation may influence any existing dependent censoring in clinical trials, thereby also influencing inference about the survival curve, hazard ratio, or other measures of treatment efficacy. In simulation studies, we consider a model for how compensation structure may influence the censoring model. Under existing dependent censoring, we estimate survival curves under different compensation structures and observe how these structures induce variability in the estimates. We show through this model that if the compensation structure affects the censoring model and dependent censoring is present, then variation in that structure induces variation in the estimates and affects the accuracy of estimation and inference on treatment efficacy. From the perspectives of both ethics and statistical inference, standardization and transparency in the compensation of participants in clinical trials are warranted. Copyright © 2015 Elsevier Inc. All rights reserved.

Deterministic chaos and fractal complexity in the dynamics of cardiovascular behavior: perspectives on a new frontier.

PubMed

Sharma, Vijay

2009-09-10

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts.

Deterministic Chaos and Fractal Complexity in the Dynamics of Cardiovascular Behavior: Perspectives on a New Frontier

PubMed Central

Sharma, Vijay

2009-01-01

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts. PMID:19812706

Temporal stability in the genetic structure of Sarcoptes scabiei under the host-taxon law: empirical evidences from wildlife-derived Sarcoptes mite in Asturias, Spain

PubMed Central

2011-01-01

Background Implicitly, parasite molecular studies assume temporal genetic stability. In this study we tested, for the first time to our knowledge, the extent of changes in genetic diversity and structure of Sarcoptes mite populations from Pyrenean chamois (Rupicapra pyrenaica) in Asturias (Spain), using one multiplex of 9 microsatellite markers and Sarcoptes samples from sympatric Pyrenean chamois, red deer (Cervus elaphus), roe deer (Capreolus capreolus) and red fox (Vulpes vulpes). Results The analysis of an 11-years interval period found little change in the genetic diversity (allelic diversity, and observed and expected heterozygosity). The temporal stability in the genetic diversity was confirmed by population structure analysis, which was not significantly variable over time. Population structure analysis revealed temporal stability in the genetic diversity of Sarcoptes mite under the host-taxon law (herbivore derived- and carnivore derived-Sarcoptes mite) among the sympatric wild animals from Asturias. Conclusions The confirmation of parasite temporal genetic stability is of vital interest to allow generalizations to be made, which have further implications regarding the genetic structure, epidemiology and monitoring protocols of the ubiquitous Sarcoptes mite. This could eventually be applied to other parasite species. PMID:21794141

Dissipation of contractile forces: the missing piece in cell mechanics.

PubMed

Kurzawa, Laetitia; Vianay, Benoit; Senger, Fabrice; Vignaud, Timothée; Blanchoin, Laurent; Théry, Manuel

2017-07-07

Mechanical forces are key regulators of cell and tissue physiology. The basic molecular mechanism of fiber contraction by the sliding of actin filament upon myosin leading to conformational change has been known for decades. The regulation of force generation at the level of the cell, however, is still far from elucidated. Indeed, the magnitude of cell traction forces on the underlying extracellular matrix in culture is almost impossible to predict or experimentally control. The considerable variability in measurements of cell-traction forces indicates that they may not be the optimal readout to properly characterize cell contractile state and that a significant part of the contractile energy is not transferred to cell anchorage but instead is involved in actin network dynamics. Here we discuss the experimental, numerical, and biological parameters that may be responsible for the variability in traction force production. We argue that limiting these sources of variability and investigating the dissipation of mechanical work that occurs with structural rearrangements and the disengagement of force transmission is key for further understanding of cell mechanics. © 2017 Kurzawa et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

A nonlinear cointegration approach with applications to structural health monitoring

NASA Astrophysics Data System (ADS)

Shi, H.; Worden, K.; Cross, E. J.

2016-09-01

One major obstacle to the implementation of structural health monitoring (SHM) is the effect of operational and environmental variabilities, which may corrupt the signal of structural degradation. Recently, an approach inspired from the community of econometrics, called cointegration, has been employed to eliminate the adverse influence from operational and environmental changes and still maintain sensitivity to structural damage. However, the linear nature of cointegration may limit its application when confronting nonlinear relations between system responses. This paper proposes a nonlinear cointegration method based on Gaussian process regression (GPR); the method is constructed under the Engle-Granger framework, and tests for unit root processes are conducted both before and after the GPR is applied. The proposed approach is examined with real engineering data from the monitoring of the Z24 Bridge.

Sensitivity analysis for axis rotation diagrid structural systems according to brace angle changes

NASA Astrophysics Data System (ADS)

Yang, Jae-Kwang; Li, Long-Yang; Park, Sung-Soo

2017-10-01

General regular shaped diagrid structures can express diverse shapes because braces are installed along the exterior faces of the structures and the structures have no columns. However, since irregular shaped structures have diverse variables, studies to assess behaviors resulting from various variables are continuously required to supplement the imperfections related to such variables. In the present study, materials elastic modulus and yield strength were selected as variables for strength that would be applied to diagrid structural systems in the form of Twisters among the irregular shaped buildings classified by Vollers and that affect the structural design of these structural systems. The purpose of this study is to conduct sensitivity analysis for axial rotation diagrid structural systems according to changes in brace angles in order to identify the design variables that have relatively larger effects and the tendencies of the sensitivity of the structures according to changes in brace angles and axial rotation angles.

Characteristics and experience of the patient in psychotherapy and the psychotherapy's effectiveness. A structural approach.

PubMed

Szymańska, Agnieszka; Dobrenko, Kamila; Grzesiuk, Lidia

2017-08-29

The study concerns the relationship between three groups of variables presenting the patient's perspective: (1) "patient's characteristics" before psychotherapy, including "expectations of the therapy"; (2) "experience in the therapy", including the "psychotherapeutic relationship"; and (3) "assessment of the direct effectiveness of the psychotherapy". Data from the literature are the basis for predicting relationships between all of these variables. Measurement of the variables was conducted using a follow-up survey. The survey was sent to a total of 1,210 former patients of the Academic Center for Psychotherapy (AOP) in which the therapy is conducted mainly with the students and employees of the University of Warsaw. Responses were received from 276 people. 55% of the respondents were women and 45% were men, under 30 years of age. The analyses were performed using structural equations. Two models emerged from an analysis of the relationship between the three above-mentioned groups of variables. One concerns the relationship between (1) the patient's characteristics (2) the course of psychotherapy, in which -from the perspective of the patient - there is a good relationship with the psychotherapist and (3) psychotherapy is effective. The second model refers to (2) the patient's experience of poor psychotherapeutic relationship and (3) ineffective psychotherapy. Patient's expectations of the psychotherapy (especially "the expectation of support") proved to be important moderating variablesin the models-among the characteristics of the patient. The mathematical model also revealed strong correlation of variables measuring "the relationship with the psychotherapist" and "therapeutic interventions".

Relations between mental health team characteristics and work role performance.

PubMed

Fleury, Marie-Josée; Grenier, Guy; Bamvita, Jean-Marie; Farand, Lambert

2017-01-01

Effective mental health care requires a high performing, interprofessional team. Among 79 mental health teams in Quebec (Canada), this exploratory study aims to 1) determine the association between work role performance and a wide range of variables related to team effectiveness according to the literature, and to 2) using structural equation modelling, assess the covariance between each of these variables as well as the correlation with other exogenous variables. Work role performance was measured with an adapted version of a work role questionnaire. Various independent variables including team manager characteristics, user characteristics, team profiles, clinical activities, organizational culture, network integration strategies and frequency/satisfaction of interactions with other teams or services were analyzed under the structural equation model. The later provided a good fit with the data. Frequent use of standardized procedures and evaluation tools (e.g. screening and assessment tools for mental health disorders) and team manager seniority exerted the most direct effect on work role performance. While network integration strategies had little effect on work role performance, there was a high covariance between this variable and those directly affecting work role performance among mental health teams. The results suggest that the mental healthcare system should apply standardized procedures and evaluation tools and, to a lesser extent, clinical approaches to improve work role performance in mental health teams. Overall, a more systematic implementation of network integration strategies may contribute to improved work role performance in mental health care.

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Relations between mental health team characteristics and work role performance

PubMed Central

Grenier, Guy; Bamvita, Jean-Marie; Farand, Lambert

2017-01-01

Effective mental health care requires a high performing, interprofessional team. Among 79 mental health teams in Quebec (Canada), this exploratory study aims to 1) determine the association between work role performance and a wide range of variables related to team effectiveness according to the literature, and to 2) using structural equation modelling, assess the covariance between each of these variables as well as the correlation with other exogenous variables. Work role performance was measured with an adapted version of a work role questionnaire. Various independent variables including team manager characteristics, user characteristics, team profiles, clinical activities, organizational culture, network integration strategies and frequency/satisfaction of interactions with other teams or services were analyzed under the structural equation model. The later provided a good fit with the data. Frequent use of standardized procedures and evaluation tools (e.g. screening and assessment tools for mental health disorders) and team manager seniority exerted the most direct effect on work role performance. While network integration strategies had little effect on work role performance, there was a high covariance between this variable and those directly affecting work role performance among mental health teams. The results suggest that the mental healthcare system should apply standardized procedures and evaluation tools and, to a lesser extent, clinical approaches to improve work role performance in mental health teams. Overall, a more systematic implementation of network integration strategies may contribute to improved work role performance in mental health care. PMID:28991923

Burning fire-prone Mediterranean shrublands: immediate changes in soil microbial community structure and ecosystem functions.

PubMed

Goberna, M; García, C; Insam, H; Hernández, M T; Verdú, M

2012-07-01

Wildfires subject soil microbes to extreme temperatures and modify their physical and chemical habitat. This might immediately alter their community structure and ecosystem functions. We burned a fire-prone shrubland under controlled conditions to investigate (1) the fire-induced changes in the community structure of soil archaea, bacteria and fungi by analysing 16S or 18S rRNA gene amplicons separated through denaturing gradient gel electrophoresis; (2) the physical and chemical variables determining the immediate shifts in the microbial community structure; and (3) the microbial drivers of the change in ecosystem functions related to biogeochemical cycling. Prokaryotes and eukaryotes were structured by the local environment in pre-fire soils. Fire caused a significant shift in the microbial community structure, biomass C, respiration and soil hydrolases. One-day changes in bacterial and fungal community structure correlated to the rise in total organic C and NO(3)(-)-N caused by the combustion of plant residues. In the following week, bacterial communities shifted further forced by desiccation and increasing concentrations of macronutrients. Shifts in archaeal community structure were unrelated to any of the 18 environmental variables measured. Fire-induced changes in the community structure of bacteria, rather than archaea or fungi, were correlated to the enhanced microbial biomass, CO(2) production and hydrolysis of C and P organics. This is the first report on the combined effects of fire on the three biological domains in soils. We concluded that immediately after fire the biogeochemical cycling in Mediterranean shrublands becomes less conservative through the increased microbial biomass, activity and changes in the bacterial community structure.

Catecholamines and cognition after traumatic brain injury

PubMed Central

Jenkins, Peter O.; Mehta, Mitul A.

2016-01-01

Abstract Cognitive problems are one of the main causes of ongoing disability after traumatic brain injury. The heterogeneity of the injuries sustained and the variability of the resulting cognitive deficits makes treating these problems difficult. Identifying the underlying pathology allows a targeted treatment approach aimed at cognitive enhancement. For example, damage to neuromodulatory neurotransmitter systems is common after traumatic brain injury and is an important cause of cognitive impairment. Here, we discuss the evidence implicating disruption of the catecholamines (dopamine and noradrenaline) and review the efficacy of catecholaminergic drugs in treating post-traumatic brain injury cognitive impairments. The response to these therapies is often variable, a likely consequence of the heterogeneous patterns of injury as well as a non-linear relationship between catecholamine levels and cognitive functions. This individual variability means that measuring the structure and function of a person’s catecholaminergic systems is likely to allow more refined therapy. Advanced structural and molecular imaging techniques offer the potential to identify disruption to the catecholaminergic systems and to provide a direct measure of catecholamine levels. In addition, measures of structural and functional connectivity can be used to identify common patterns of injury and to measure the functioning of brain ‘networks’ that are important for normal cognitive functioning. As the catecholamine systems modulate these cognitive networks, these measures could potentially be used to stratify treatment selection and monitor response to treatment in a more sophisticated manner. PMID:27256296

Does beekeeping reduce genetic variability in Melipona scutellaris (Apidae, Meliponini)?

PubMed

Carvalho-Zilse, G A; Costa-Pinto, M F F; Nunes-Silva, C G; Kerr, W E

2009-06-30

Many factors have contributed to reductions in wild populations of stingless bees, such as: deforestation, displacement and destruction of nests by honey gatherers, as well as use of insecticides and other agrochemicals. All of these can potentially affect the populational structure of native species. We analyzed genetic variability and populational structure of Melipona scutellaris, based on five microsatellite loci, using heterologous primers of M. bicolor. Samples were taken from 43 meliponaries distributed among 30 sites of four northeastern states of Brazil (Pernambuco, Alagoas, Sergipe, and Bahia). Thirty-one alleles were found to be well distributed among the populations, with sizes ranging from 85 to 146 bp. In general, there was a variable distribution and frequency of alleles among populations, with either exclusive and/or fixed alleles at some sites. The population of Pernambuco was the most polymorphic, followed by Bahia, Alagoas and Sergipe. The heterozygosity was Ho = 0.36 on average, much lower than what has been reported for M. bicolor (Ho = 0.65). Most populations were not under Hardy-Weinberg equilibrium. We found a higher variation within rather than among populations, indicating no genetic structuring in those bees maintained in meliponaries. This apparent homogenization may be due to intense beekeeping activity, including exchange of genetic material among beekeepers. Based on our findings, we recommend more studies of meliponaries and of wild populations in order to help orient management and conservation of these native pollinators.

Bayesian Semiparametric Structural Equation Models with Latent Variables

ERIC Educational Resources Information Center

Yang, Mingan; Dunson, David B.

2010-01-01

Structural equation models (SEMs) with latent variables are widely useful for sparse covariance structure modeling and for inferring relationships among latent variables. Bayesian SEMs are appealing in allowing for the incorporation of prior information and in providing exact posterior distributions of unknowns, including the latent variables. In…

Characterising the latent structure and organisation of self-reported thoughts, feelings and behaviours in adolescents and young adults

PubMed Central

Neufeld, Sharon; Jones, Peter B.; Fonagy, Peter; Bullmore, Edward T.; Dolan, Raymond J.; Moutoussis, Michael; Toseeb, Umar; Goodyer, Ian M.

2017-01-01

Little is known about the underlying relationships between self-reported mental health items measuring both positive and negative emotional and behavioural symptoms at the population level in young people. Improved measurement of the full range of mental well-being and mental illness may aid in understanding the aetiological substrates underlying the development of both mental wellness as well as specific psychiatric diagnoses. A general population sample aged 14 to 24 years completed self-report questionnaires on anxiety, depression, psychotic-like symptoms, obsessionality and well-being. Exploratory and confirmatory factor models for categorical data and latent profile analyses were used to evaluate the structure of both mental wellness and illness items. First order, second order and bifactor structures were evaluated on 118 self-reported items obtained from 2228 participants. A bifactor solution was the best fitting latent variable model with one general latent factor termed ‘distress’ and five ‘distress independent’ specific factors defined as self-confidence, antisocial behaviour, worry, aberrant thinking, and mood. Next, six distinct subgroups were derived from a person-centred latent profile analysis of the factor scores. Finally, concurrent validity was assessed using information on hazardous behaviours (alcohol use, substance misuse, self-harm) and treatment for mental ill health: both discriminated between the latent traits and latent profile subgroups. The findings suggest a complex, multidimensional mental health structure in the youth population rather than the previously assumed first or second order factor structure. Additionally, the analysis revealed a low hazardous behaviour/low mental illness risk subgroup not previously described. Population sub-groups show greater validity over single variable factors in revealing mental illness risks. In conclusion, our findings indicate that the structure of self reported mental health is multidimensional in nature and uniquely finds improved prediction to mental illness risk within person-centred subgroups derived from the multidimensional latent traits. PMID:28403164

Characterising the latent structure and organisation of self-reported thoughts, feelings and behaviours in adolescents and young adults.

PubMed

St Clair, Michelle C; Neufeld, Sharon; Jones, Peter B; Fonagy, Peter; Bullmore, Edward T; Dolan, Raymond J; Moutoussis, Michael; Toseeb, Umar; Goodyer, Ian M

2017-01-01

Little is known about the underlying relationships between self-reported mental health items measuring both positive and negative emotional and behavioural symptoms at the population level in young people. Improved measurement of the full range of mental well-being and mental illness may aid in understanding the aetiological substrates underlying the development of both mental wellness as well as specific psychiatric diagnoses. A general population sample aged 14 to 24 years completed self-report questionnaires on anxiety, depression, psychotic-like symptoms, obsessionality and well-being. Exploratory and confirmatory factor models for categorical data and latent profile analyses were used to evaluate the structure of both mental wellness and illness items. First order, second order and bifactor structures were evaluated on 118 self-reported items obtained from 2228 participants. A bifactor solution was the best fitting latent variable model with one general latent factor termed 'distress' and five 'distress independent' specific factors defined as self-confidence, antisocial behaviour, worry, aberrant thinking, and mood. Next, six distinct subgroups were derived from a person-centred latent profile analysis of the factor scores. Finally, concurrent validity was assessed using information on hazardous behaviours (alcohol use, substance misuse, self-harm) and treatment for mental ill health: both discriminated between the latent traits and latent profile subgroups. The findings suggest a complex, multidimensional mental health structure in the youth population rather than the previously assumed first or second order factor structure. Additionally, the analysis revealed a low hazardous behaviour/low mental illness risk subgroup not previously described. Population sub-groups show greater validity over single variable factors in revealing mental illness risks. In conclusion, our findings indicate that the structure of self reported mental health is multidimensional in nature and uniquely finds improved prediction to mental illness risk within person-centred subgroups derived from the multidimensional latent traits.

Optimizing use of the structural chemical analyser (variable pressure FESEM-EDX Raman spectroscopy) on micro-size complex historical paintings characterization.

PubMed

Guerra, I; Cardell, C

2015-10-01

The novel Structural Chemical Analyser (hyphenated Raman spectroscopy and scanning electron microscopy equipped with an X-ray detector) is gaining popularity since it allows 3-D morphological studies and elemental, molecular, structural and electronic analyses of a single complex micro-sized sample without transfer between instruments. However, its full potential remains unexploited in painting heritage where simultaneous identification of inorganic and organic materials in paintings is critically yet unresolved. Despite benefits and drawbacks shown in literature, new challenges have to be faced analysing multifaceted paint specimens. SEM-Structural Chemical Analyser systems differ since they are fabricated ad hoc by request. As configuration influences the procedure to optimize analyses, likewise analytical protocols have to be designed ad hoc. This paper deals with the optimization of the analytical procedure of a Variable Pressure Field Emission scanning electron microscopy equipped with an X-ray detector Raman spectroscopy system to analyse historical paint samples. We address essential parameters, technical challenges and limitations raised from analysing paint stratigraphies, archaeological samples and loose pigments. We show that accurate data interpretation requires comprehensive knowledge of factors affecting Raman spectra. We tackled: (i) the in-FESEM-Raman spectroscopy analytical sequence, (ii) correlations between FESEM and Structural Chemical Analyser/laser analytical position, (iii) Raman signal intensity under different VP-FESEM vacuum modes, (iv) carbon deposition on samples under FESEM low-vacuum mode, (v) crystal nature and morphology, (vi) depth of focus and (vii) surface-enhanced Raman scattering effect. We recommend careful planning of analysis strategies prior to research which, although time consuming, guarantees reliable results. The ultimate goal of this paper is to help to guide future users of a FESEM-Structural Chemical Analyser system in order to increase applications. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Plant cell plasma membrane structure and properties under clinostatting

NASA Astrophysics Data System (ADS)

Polulakh, Yu. A.; Zhadko, S. I.; Klimchuk, D. A.; Baraboy, V. A.; Alpatov, A. N.; Sytnik, K. M.

Structural-functional organization of plasma membrane of pea roots seedling was investigated by methods of chemiluminescence, fluorescence probes, chromatography and freeze-fracture studies under normal conditions and clinostatting. Phase character of lipid peroxidation intensity was fixed. The initial phase of this process is characterized by lipid peroxidation decreasing with its next induction. The primary changes depending on free-radical mechanisms of lipid peroxidation were excellently revealed by chemiluminescence. Plasmalemma microviscosity increased on the average of 15-20 % under microgravity at the initial stages of its phenomenon. There were major changes of phosphatidilcholine and phosphatidilethanolamine contents. The total quantity of phospholipids remained rather stable. Changes of phosphatide acid concentration point to degradation and phospholipids biosynthesis. There were increases of unsaturated fatty acids mainly at the expense of linoleic and linolenic acids and also a decrease of saturated fatty acid content at the expense of palmitic and stearic acids. Unsaturation index of fatty acids increased as well. On the whole fatty acid composition was variable in comparison with phospholipids. Probably it is one of mechanisms of maintaining of microviscosity within definite limits. Considerable structural changes in organization of plasmalemma protein-lipid complex were not revealed by the freeze-fracture studies.

Determining the drivers of population structure in a highly urbanized landscape to inform conservation planning.

PubMed

Thomassen, Henri A; Harrigan, Ryan J; Semple Delaney, Kathleen; Riley, Seth P D; Serieys, Laurel E K; Pease, Katherine; Wayne, Robert K; Smith, Thomas B

2018-02-01

Understanding the environmental contributors to population structure is of paramount importance for conservation in urbanized environments. We used spatially explicit models to determine genetic population structure under current and future environmental conditions across a highly fragmented, human-dominated environment in Southern California to assess the effects of natural ecological variation and urbanization. We focused on 7 common species with diverse habitat requirements, home-range sizes, and dispersal abilities. We quantified the relative roles of potential barriers, including natural environmental characteristics and an anthropogenic barrier created by a major highway, in shaping genetic variation. The ability to predict genetic variation in our models differed among species: 11-81% of intraspecific genetic variation was explained by environmental variables. Although an anthropogenically induced barrier (a major highway) severely restricted gene flow and movement at broad scales for some species, genetic variation seemed to be primarily driven by natural environmental heterogeneity at a local level. Our results show how assessing environmentally associated variation for multiple species under current and future climate conditions can help identify priority regions for maximizing population persistence under environmental change in urbanized regions. © 2017 Society for Conservation Biology.

Genome scans for divergent selection in natural populations of the widespread hardwood species Eucalyptus grandis (Myrtaceae) using microsatellites

PubMed Central

Song, Zhijiao; Zhang, Miaomiao; Li, Fagen; Weng, Qijie; Zhou, Chanpin; Li, Mei; Li, Jie; Huang, Huanhua; Mo, Xiaoyong; Gan, Siming

2016-01-01

Identification of loci or genes under natural selection is important for both understanding the genetic basis of local adaptation and practical applications, and genome scans provide a powerful means for such identification purposes. In this study, genome-wide simple sequence repeats markers (SSRs) were used to scan for molecular footprints of divergent selection in Eucalyptus grandis, a hardwood species occurring widely in costal areas from 32° S to 16° S in Australia. High population diversity levels and weak population structure were detected with putatively neutral genomic SSRs. Using three FST outlier detection methods, a total of 58 outlying SSRs were collectively identified as loci under divergent selection against three non-correlated climatic variables, namely, mean annual temperature, isothermality and annual precipitation. Using a spatial analysis method, nine significant associations were revealed between FST outlier allele frequencies and climatic variables, involving seven alleles from five SSR loci. Of the five significant SSRs, two (EUCeSSR1044 and Embra394) contained alleles of putative genes with known functional importance for response to climatic factors. Our study presents critical information on the population diversity and structure of the important woody species E. grandis and provides insight into the adaptive responses of perennial trees to climatic variations. PMID:27748400

The phenomenon of adolescents placing pressure on their parents.

PubMed

Bester, Garfield; Marais, Amanda C

2014-01-01

Parents are under pressure from their adolescent children if they, contrary to their own convictions, are compelled to bend rules or adapt decisions to submit to the demands of their children. The objective of this investigation was to determine which factors contribute to this phenomenon. The sample comprised 177 adolescents and their parents in the Mpumalanga province. Variables taken into account were individual factors (gender, age and personality of parents and adolescents); factors related to the family (family structure, working circumstances of parents, family relationships and birth order position of adolescents); developmental factors (identity formation of adolescents); and wider contextual factors (peer pressure during adolescence). From the parents' side factors such as self-concept, personality and parent-adolescent relationship explained almost 62% of the variance in the pressure that parents experience. Only one prominent adolescent factor could be identified, namely adolescent-parent relationship (seen from the adolescents' side). The results indicate that the pressure which parents encounter from their adolescent children is associated with parental variables rather than adolescent variables. Adolescents do not deliberately plan to place their parents under pressure, but factors on the parents' side create such a situation.

New Perspectives on Southern Ocean Frontal Variability

NASA Astrophysics Data System (ADS)

Chapman, Christopher

2017-04-01

The frontal structure of the Southern Ocean is investigated using a the Wavelet/Higher Order Statistics Enhancement (WHOSE) frontal detection method, introduced in Chapman (2014). This methodology is applied to 21 years of daily gridded sea-surface height (SSH) data to obtain daily maps of the locations of the fronts. By forming frontal occurrence frequency maps and then approximating these occurrence-maps by a superposition of simple functions, the time-mean locations of the fronts, as well as a measure of their capacity to meander, are obtained and related to the frontal locations found by previous studies. The spatial and temporal variability of the frontal structure is then considered. The number of fronts is found to be highly variable throughout the Southern Ocean, increasing (`splitting') downstream of large bathymetric features and decreasing (`merging') in regions where the fronts are tightly controlled by the underlying topography. In contrast, frontal meandering remains relatively constant. Contrary to many previous studies, little no southward migration of the fronts over the 1993-2014 time period is found, and there is only weak sensitivity to atmospheric forcing related to SAM or ENSO. Finally, the implications of splitting and merging for the flux of tracers will be discussed.

Motor abundance and control structure in the golf swing.

PubMed

Morrison, A; McGrath, D; Wallace, E S

2016-04-01

Variability and control structure are under-represented areas of golf swing research. This study investigated the use of the abundant degrees of freedom in the golf swing of high and intermediate skilled golfers using uncontrolled manifold (UCM) analysis. The variance parallel to (VUCM) and orthogonal to (VOrth) the UCM with respect to the orientation and location of the clubhead were calculated. The higher skilled golfers had proportionally higher values of VUCM than lower skilled players for all measured outcome variables. Motor synergy was found in the control of the orientation of the clubhead and the combined outcome variables but not for clubhead location. Clubhead location variance zeroed-in on impact as has been previously shown, whereas clubhead orientation variance increased near impact. Both skill levels increased their control over the clubhead location leading up to impact, with more control exerted over the clubhead orientation in the early downswing. The results suggest that to achieve higher skill levels in golf may not lie simply in optimal technique, but may lie more in developing control over the abundant degrees of freedom in the body. Copyright © 2016 Elsevier B.V. All rights reserved.

FDR doesn't Tell the Whole Story: Joint Influence of Effect Size and Covariance Structure on the Distribution of the False Discovery Proportions

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Ploutz-Snyder, Robert; Fiedler, James

2011-01-01

As part of a 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report results of simulations that estimated the false discovery rate (FDR) for equally correlated test statistics using a well-known multiple-test procedure. In our study we estimate the distribution of the false discovery proportion (FDP) for the same procedure under a variety of correlation structures among multiple dependent variables in a MANOVA context. Specifically, we study the mean (the FDR), skewness, kurtosis, and percentiles of the FDP distribution in the case of multiple comparisons that give rise to correlated non-central t-statistics when results at several time periods are being compared to baseline. Even if the FDR achieves its nominal value, other aspects of the distribution of the FDP depend on the interaction between signed effect sizes and correlations among variables, proportion of true nulls, and number of dependent variables. We show examples where the mean FDP (the FDR) is 10% as designed, yet there is a surprising probability of having 30% or more false discoveries. Thus, in a real experiment, the proportion of false discoveries could be quite different from the stipulated FDR.

Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

NASA Astrophysics Data System (ADS)

Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao

2017-03-01

Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction.

Some Implications of a Behavioral Analysis of Verbal Behavior for Logic and Mathematics

PubMed Central

2013-01-01

The evident power and utility of the formal models of logic and mathematics pose a puzzle: Although such models are instances of verbal behavior, they are also essentialistic. But behavioral terms, and indeed all products of selection contingencies, are intrinsically variable and in this respect appear to be incommensurate with essentialism. A distinctive feature of verbal contingencies resolves this puzzle: The control of behavior by the nonverbal environment is often mediated by the verbal behavior of others, and behavior under control of verbal stimuli is blind to the intrinsic variability of the stimulating environment. Thus, words and sentences serve as filters of variability and thereby facilitate essentialistic model building and the formal structures of logic, mathematics, and science. Autoclitic frames, verbal chains interrupted by interchangeable variable terms, are ubiquitous in verbal behavior. Variable terms can be substituted in such frames almost without limit, a feature fundamental to formal models. Consequently, our fluency with autoclitic frames fosters generalization to formal models, which in turn permit deduction and other kinds of logical and mathematical inference. PMID:28018038

Estimating Latent Variable Interactions With Non-Normal Observed Data: A Comparison of Four Approaches

PubMed Central

Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S.

2012-01-01

A Monte Carlo simulation was conducted to investigate the robustness of four latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of non-normality of the observed exogenous variables. Results showed that the CPI and LMS approaches yielded biased estimates of the interaction effect when the exogenous variables were highly non-normal. When the violation of non-normality was not severe (normal; symmetric with excess kurtosis < 1), the LMS approach yielded the most efficient estimates of the latent interaction effect with the highest statistical power. In highly non-normal conditions, the GAPI and UPI approaches with ML estimation yielded unbiased latent interaction effect estimates, with acceptable actual Type-I error rates for both the Wald and likelihood ratio tests of interaction effect at N ≥ 500. An empirical example illustrated the use of the four approaches in testing a latent variable interaction between academic self-efficacy and positive family role models in the prediction of academic performance. PMID:23457417

Numerical solution of the wave equation with variable wave speed on nonconforming domains by high-order difference potentials

NASA Astrophysics Data System (ADS)

Britt, S.; Tsynkov, S.; Turkel, E.

2018-02-01

We solve the wave equation with variable wave speed on nonconforming domains with fourth order accuracy in both space and time. This is accomplished using an implicit finite difference (FD) scheme for the wave equation and solving an elliptic (modified Helmholtz) equation at each time step with fourth order spatial accuracy by the method of difference potentials (MDP). High-order MDP utilizes compact FD schemes on regular structured grids to efficiently solve problems on nonconforming domains while maintaining the design convergence rate of the underlying FD scheme. Asymptotically, the computational complexity of high-order MDP scales the same as that for FD.

Novel models and algorithms of load balancing for variable-structured collaborative simulation under HLA/RTI

NASA Astrophysics Data System (ADS)

Yue, Yingchao; Fan, Wenhui; Xiao, Tianyuan; Ma, Cheng

2013-07-01

High level architecture(HLA) is the open standard in the collaborative simulation field. Scholars have been paying close attention to theoretical research on and engineering applications of collaborative simulation based on HLA/RTI, which extends HLA in various aspects like functionality and efficiency. However, related study on the load balancing problem of HLA collaborative simulation is insufficient. Without load balancing, collaborative simulation under HLA/RTI may encounter performance reduction or even fatal errors. In this paper, load balancing is further divided into static problems and dynamic problems. A multi-objective model is established and the randomness of model parameters is taken into consideration for static load balancing, which makes the model more credible. The Monte Carlo based optimization algorithm(MCOA) is excogitated to gain static load balance. For dynamic load balancing, a new type of dynamic load balancing problem is put forward with regards to the variable-structured collaborative simulation under HLA/RTI. In order to minimize the influence against the running collaborative simulation, the ordinal optimization based algorithm(OOA) is devised to shorten the optimization time. Furthermore, the two algorithms are adopted in simulation experiments of different scenarios, which demonstrate their effectiveness and efficiency. An engineering experiment about collaborative simulation under HLA/RTI of high speed electricity multiple units(EMU) is also conducted to indentify credibility of the proposed models and supportive utility of MCOA and OOA to practical engineering systems. The proposed research ensures compatibility of traditional HLA, enhances the ability for assigning simulation loads onto computing units both statically and dynamically, improves the performance of collaborative simulation system and makes full use of the hardware resources.

An Analysis of the Beaufort Sea Thermohaline Structure and Variability, and Its Effects on Acoustic Propagation

DTIC Science & Technology

2016-06-01

BEAUFORT SEA THERMOHALINE STRUCTURE AND VARIABILITY, AND ITS EFFECTS ON ACOUSTIC PROPAGATION by Annalise N. Pearson June 2016 Thesis...STRUCTURE AND VARIABILITY, AND ITS EFFECTS ON ACOUSTIC PROPAGATION 5. FUNDING NUMBERS 6. AUTHOR(S) Annalise N. Pearson 7. PERFORMING ORGANIZATION...public release; distribution is unlimited AN ANALYSIS OF THE BEAUFORT SEA THERMOHALINE STRUCTURE AND VARIABILITY, AND ITS EFFECTS ON ACOUSTIC

Structural modifications induced by ion irradiation and temperature in boron carbide B4C

NASA Astrophysics Data System (ADS)

Victor, G.; Pipon, Y.; Bérerd, N.; Toulhoat, N.; Moncoffre, N.; Djourelov, N.; Miro, S.; Baillet, J.; Pradeilles, N.; Rapaud, O.; Maître, A.; Gosset, D.

2015-12-01

Already used as neutron absorber in the current French nuclear reactors, boron carbide (B4C) is also considered in the future Sodium Fast Reactors of the next generation (Gen IV). Due to severe irradiation conditions occurring in these reactors, it is of primary importance that this material presents a high structural resistance under irradiation, both in the ballistic and electronic damage regimes. Previous works have shown an important structural resistance of boron carbide even at high neutron fluences. Nevertheless, the structural modification mechanisms due to irradiation are not well understood. Therefore the aim of this paper is to study structural modifications induced in B4C samples in different damage regimes. The boron carbide pellets were shaped and sintered by using spark plasma sintering method. They were then irradiated in several conditions at room temperature or 800 °C, either by favoring the creation of ballistic damage (between 1 and 3 dpa), or by favoring the electronic excitations using 100 MeV swift iodine ions (Se ≈ 15 keV/nm). Ex situ micro-Raman spectroscopy and Doppler broadening of annihilation radiation technique with variable energy slow positrons were coupled to follow the evolution of the B4C structure under irradiation.

Environmental and management influences on temporal variability of near saturated soil hydraulic properties.

PubMed

Bodner, G; Scholl, P; Loiskandl, W; Kaul, H-P

2013-08-01

Structural porosity is a decisive property for soil productivity and soil environmental functions. Hydraulic properties in the structural range vary over time in response to management and environmental influences. Although this is widely recognized, there are few field studies that determine dominant driving forces underlying hydraulic property dynamics. During a three year field experiment we measured temporal variability of soil hydraulic properties by tension infiltrometry. Soil properties were characterized by hydraulic conductivity, effective macroporosity and Kosugi's lognormal pore size distribution model. Management related influences comprised three soil cover treatment (mustard and rye vs. fallow) and an initial mechanical soil disturbance with a rotary harrow. Environmental driving forces were derived from meteorological and soil moisture data. Soil hydraulic parameters varied over time by around one order of magnitude. The coefficient of variation of soil hydraulic conductivity K(h) decreased from 69.5% at saturation to 42.1% in the more unsaturated range (- 10 cm pressure head). A slight increase in the Kosugi parameter showing pore heterogeneity was observed under the rye cover crop, reflecting an enhanced structural porosity. The other hydraulic parameters were not significantly influenced by the soil cover treatments. Seedbed preparation with a rotary harrow resulted in a fourfold increase in macroporosity and hydraulic conductivity next to saturation, and homogenized the pore radius distribution. Re-consolidation after mechanical loosening lasted over 18 months until the soil returned to its initial state. The post-tillage trend of soil settlement could be approximated by an exponential decay function. Among environmental factors, wetting-drying cycles were identified as dominant driving force explaining short term hydraulic property changes within the season (r 2  = 0.43 to 0.59). Our results suggested that beside considering average management induced changes in soil properties (e.g. cover crop introduction), a dynamic approach to hydrological modeling is required to capture over-seasonal (tillage driven) and short term (environmental driven) variability in hydraulic parameters.

Environmental and management influences on temporal variability of near saturated soil hydraulic properties☆

PubMed Central

Bodner, G.; Scholl, P.; Loiskandl, W.; Kaul, H.-P.

2013-01-01

Structural porosity is a decisive property for soil productivity and soil environmental functions. Hydraulic properties in the structural range vary over time in response to management and environmental influences. Although this is widely recognized, there are few field studies that determine dominant driving forces underlying hydraulic property dynamics. During a three year field experiment we measured temporal variability of soil hydraulic properties by tension infiltrometry. Soil properties were characterized by hydraulic conductivity, effective macroporosity and Kosugi's lognormal pore size distribution model. Management related influences comprised three soil cover treatment (mustard and rye vs. fallow) and an initial mechanical soil disturbance with a rotary harrow. Environmental driving forces were derived from meteorological and soil moisture data. Soil hydraulic parameters varied over time by around one order of magnitude. The coefficient of variation of soil hydraulic conductivity K(h) decreased from 69.5% at saturation to 42.1% in the more unsaturated range (− 10 cm pressure head). A slight increase in the Kosugi parameter showing pore heterogeneity was observed under the rye cover crop, reflecting an enhanced structural porosity. The other hydraulic parameters were not significantly influenced by the soil cover treatments. Seedbed preparation with a rotary harrow resulted in a fourfold increase in macroporosity and hydraulic conductivity next to saturation, and homogenized the pore radius distribution. Re-consolidation after mechanical loosening lasted over 18 months until the soil returned to its initial state. The post-tillage trend of soil settlement could be approximated by an exponential decay function. Among environmental factors, wetting-drying cycles were identified as dominant driving force explaining short term hydraulic property changes within the season (r2 = 0.43 to 0.59). Our results suggested that beside considering average management induced changes in soil properties (e.g. cover crop introduction), a dynamic approach to hydrological modeling is required to capture over-seasonal (tillage driven) and short term (environmental driven) variability in hydraulic parameters. PMID:24748683

Estimating and Interpreting Latent Variable Interactions: A Tutorial for Applying the Latent Moderated Structural Equations Method

ERIC Educational Resources Information Center

Maslowsky, Julie; Jager, Justin; Hemken, Douglas

2015-01-01

Latent variables are common in psychological research. Research questions involving the interaction of two variables are likewise quite common. Methods for estimating and interpreting interactions between latent variables within a structural equation modeling framework have recently become available. The latent moderated structural equations (LMS)…

Environmental variables measured at multiple spatial scales exert uneven influence on fish assemblages of floodplain lakes

USGS Publications Warehouse

Dembkowski, Daniel J.; Miranda, Leandro E.

2014-01-01

We examined the interaction between environmental variables measured at three different scales (i.e., landscape, lake, and in-lake) and fish assemblage descriptors across a range of over 50 floodplain lakes in the Mississippi Alluvial Valley of Mississippi and Arkansas. Our goal was to identify important local- and landscape-level determinants of fish assemblage structure. Relationships between fish assemblage structure and variables measured at broader scales (i.e., landscape-level and lake-level) were hypothesized to be stronger than relationships with variables measured at finer scales (i.e., in-lake variables). Results suggest that fish assemblage structure in floodplain lakes was influenced by variables operating on three different scales. However, and contrary to expectations, canonical correlations between in-lake environmental characteristics and fish assemblage structure were generally stronger than correlations between landscape-level and lake-level variables and fish assemblage structure, suggesting a hierarchy of influence. From a resource management perspective, our study suggests that landscape-level and lake-level variables may be manipulated for conservation or restoration purposes, and in-lake variables and fish assemblage structure may be used to monitor the success of such efforts.

Inverse Ising problem in continuous time: A latent variable approach

NASA Astrophysics Data System (ADS)

Donner, Christian; Opper, Manfred

2017-12-01

We consider the inverse Ising problem: the inference of network couplings from observed spin trajectories for a model with continuous time Glauber dynamics. By introducing two sets of auxiliary latent random variables we render the likelihood into a form which allows for simple iterative inference algorithms with analytical updates. The variables are (1) Poisson variables to linearize an exponential term which is typical for point process likelihoods and (2) Pólya-Gamma variables, which make the likelihood quadratic in the coupling parameters. Using the augmented likelihood, we derive an expectation-maximization (EM) algorithm to obtain the maximum likelihood estimate of network parameters. Using a third set of latent variables we extend the EM algorithm to sparse couplings via L1 regularization. Finally, we develop an efficient approximate Bayesian inference algorithm using a variational approach. We demonstrate the performance of our algorithms on data simulated from an Ising model. For data which are simulated from a more biologically plausible network with spiking neurons, we show that the Ising model captures well the low order statistics of the data and how the Ising couplings are related to the underlying synaptic structure of the simulated network.

The effects of posterior cruciate ligament deficiency on posterolateral corner structures under gait- and squat-loading conditions

PubMed Central

Kang, K-T.; Koh, Y-G.; Jung, M.; Nam, J-H.; Son, J.; Lee, Y.H.

2017-01-01

Objectives The aim of the current study was to analyse the effects of posterior cruciate ligament (PCL) deficiency on forces of the posterolateral corner structure and on tibiofemoral (TF) and patellofemoral (PF) contact force under dynamic-loading conditions. Methods A subject-specific knee model was validated using a passive flexion experiment, electromyography data, muscle activation, and previous experimental studies. The simulation was performed on the musculoskeletal models with and without PCL deficiency using a novel force-dependent kinematics method under gait- and squat-loading conditions, followed by probabilistic analysis for material uncertain to be considered. Results Comparison of predicted passive flexion, posterior drawer kinematics and muscle activation with experimental measurements showed good agreement. Forces of the posterolateral corner structure, and TF and PF contact forces increased with PCL deficiency under gait- and squat-loading conditions. The rate of increase in PF contact force was the greatest during the squat-loading condition. The TF contact forces increased on both medial and lateral compartments during gait-loading conditions. However, during the squat-loading condition, the medial TF contact force tended to increase, while the lateral TF contact forces decreased. The posterolateral corner structure, which showed the greatest increase in force with deficiency of PCL under both gait- and squat-loading conditions, was the popliteus tendon (PT). Conclusion PCL deficiency is a factor affecting the variability of force on the PT in dynamic-loading conditions, and it could lead to degeneration of the PF joint. Cite this article: K-T. Kang, Y-G. Koh, M. Jung, J-H. Nam, J. Son, Y.H. Lee, S-J. Kim, S-H. Kim. The effects of posterior cruciate ligament deficiency on posterolateral corner structures under gait- and squat-loading conditions: A computational knee model. Bone Joint Res 2017;6:31–42. DOI: 10.1302/2046-3758.61.BJR-2016-0184.R1. PMID:28077395

[Soil and forest structure in the Colombian Amazon].

PubMed

Calle-Rendón, Bayron R; Moreno, Flavio; Cárdenas López, Dairon

2011-09-01

Forests structural differences could result of environmental variations at different scales. Because soils are an important component of plant's environment, it is possible that edaphic and structural variables are associated and that, in consequence, spatial autocorrelation occurs. This paper aims to answer two questions: (1) are structural and edaphic variables associated at local scale in a terra firme forest of Colombian Amazonia? and (2) are these variables regionalized at the scale of work? To answer these questions we analyzed the data of a 6ha plot established in a terra firme forest of the Amacayacu National Park. Structural variables included basal area and density of large trees (diameter > or = 10cm) (Gdos and Ndos), basal area and density of understory individuals (diameter < 10cm) (Gsot and Nsot) and number of species of large trees (sp). Edaphic variables included were pH, organic matter, P, Mg, Ca, K, Al, sand, silt and clay. Structural and edaphic variables were reduced through a principal component analysis (PCA); then, the association between edaphic and structural components from PCA was evaluated by multiple regressions. The existence of regionalization of these variables was studied through isotropic variograms, and autocorrelated variables were spatially mapped. PCA found two significant components for structure, corresponding to the structure of large trees (G, Gdos, Ndos and sp) and of small trees (N, Nsot and Gsot), which explained 43.9% and 36.2% of total variance, respectively. Four components were identified for edaphic variables, which globally explained 81.9% of total variance and basically represent drainage and soil fertility. Regression analyses were significant (p < 0.05) and showed that the structure of both large and small trees is associated with greater sand contents and low soil fertility, though they explained a low proportion of total variability (R2 was 4.9% and 16.5% for the structure of large trees and small tress, respectively). Variables with spatial autocorrelation were the structure of small trees, Al, silt, and sand. Among them, Nsot and sand content showed similar patterns of spatial distribution inside the plot.

Climate change risk to forests in China associated with warming.

PubMed

Yin, Yunhe; Ma, Danyang; Wu, Shaohong

2018-01-11

Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021-2050) to 27.62% (2071-2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.

Stability and dynamical properties of material flow systems on random networks

NASA Astrophysics Data System (ADS)

Anand, K.; Galla, T.

2009-04-01

The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are characteristic of flow networks in economic, ecological and biological systems. Based on results from random matrix theory, we work out the phase diagram of such systems defined on extensively connected random graphs, and study in detail how the choice of control policies and the network structure affects stability. We also present results for more complex topologies of the underlying graph, focussing on finitely connected Erdös-Réyni graphs, Small-World Networks and Barabási-Albert scale-free networks. Results indicate that variability of input-output matrix elements, and random structures of the underlying graph tend to make the system less stable, while fast price dynamics or strong responsiveness to stock accumulation promote stability.

Governance and community benefit: are nonprofit hospitals good candidates for Sarbanes-Oxley type reforms?

PubMed

Alexander, Jeffrey A; Young, Gary J; Weiner, Bryan J; Hearld, Larry R

2008-04-01

Recent investigations into the activities of nonprofit hospitals have pointed to weak or lax governance on the part of some of these organizations. As a result of these events, various federal and state initiatives are now either under way or under discussion to strengthen the governance of hospitals and other nonprofit corporations through mandatory board structures and practices. However, despite policy makers' growing interest in these types of governance reforms, there is in fact little empirical evidence to support their contribution to the effectiveness of hospital boards. The purpose of this article is to report the results of a study examining the relationship between the structure and practices of nonprofit hospital boards relative to the hospital's provision of community benefits. Our results point to modest relationships between these sets of variables, suggesting considerable limitations to what federal and state policy makers can accomplish through legislative initiatives to improve the governance of nonprofit hospitals.

Discovering Hidden Controlling Parameters using Data Analytics and Dimensional Analysis

NASA Astrophysics Data System (ADS)

Del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca

2017-11-01

Dimensional Analysis is a powerful tool, one which takes a priori information and produces important simplifications. However, if this a priori information - the list of relevant parameters - is missing a relevant quantity, then the conclusions from Dimensional Analysis will be incorrect. In this work, we present novel conclusions in Dimensional Analysis, which provide a means to detect this failure mode of missing or hidden parameters. These results are based on a restated form of the Buckingham Pi theorem that reveals a ridge function structure underlying all dimensionless physical laws. We leverage this structure by constructing a hypothesis test based on sufficient dimension reduction, allowing for an experimental data-driven detection of hidden parameters. Both theory and examples will be presented, using classical turbulent pipe flow as the working example. Keywords: experimental techniques, dimensional analysis, lurking variables, hidden parameters, buckingham pi, data analysis. First author supported by the NSF GRFP under Grant Number DGE-114747.

Natural CMT2 Variation Is Associated With Genome-Wide Methylation Changes and Temperature Seasonality

PubMed Central

Shen, Xia; De Jonge, Jennifer; Forsberg, Simon K. G.; Pettersson, Mats E.; Sheng, Zheya; Hennig, Lars; Carlborg, Örjan

2014-01-01

As Arabidopsis thaliana has colonized a wide range of habitats across the world it is an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we used public data from two collections of A. thaliana accessions to associate genetic variability at individual loci with differences in climates at the sampling sites. We use a novel method to screen the genome for plastic alleles that tolerate a broader climate range than the major allele. This approach reduces confounding with population structure and increases power compared to standard genome-wide association methods. Sixteen novel loci were found, including an association between Chromomethylase 2 (CMT2) and temperature seasonality where the genome-wide CHH methylation was different for the group of accessions carrying the plastic allele. Cmt2 mutants were shown to be more tolerant to heat-stress, suggesting genetic regulation of epigenetic modifications as a likely mechanism underlying natural adaptation to variable temperatures, potentially through differential allelic plasticity to temperature-stress. PMID:25503602

Delay compensation in integrated communication and control systems. I - Conceptual development and analysis

NASA Technical Reports Server (NTRS)

Luck, Rogelio; Ray, Asok

1990-01-01

A procedure for compensating for the effects of distributed network-induced delays in integrated communication and control systems (ICCS) is proposed. The problem of analyzing systems with time-varying and possibly stochastic delays could be circumvented by use of a deterministic observer which is designed to perform under certain restrictive but realistic assumptions. The proposed delay-compensation algorithm is based on a deterministic state estimator and a linear state-variable-feedback control law. The deterministic observer can be replaced by a stochastic observer without any structural modifications of the delay compensation algorithm. However, if a feedforward-feedback control law is chosen instead of the state-variable feedback control law, the observer must be modified as a conventional nondelayed system would be. Under these circumstances, the delay compensation algorithm would be accordingly changed. The separation principle of the classical Luenberger observer holds true for the proposed delay compensator. The algorithm is suitable for ICCS in advanced aircraft, spacecraft, manufacturing automation, and chemical process applications.

Monogamy inequality for distributed gaussian entanglement.

PubMed

Hiroshima, Tohya; Adesso, Gerardo; Illuminati, Fabrizio

2007-02-02

We show that for all n-mode Gaussian states of continuous variable systems, the entanglement shared among n parties exhibits the fundamental monogamy property. The monogamy inequality is proven by introducing the Gaussian tangle, an entanglement monotone under Gaussian local operations and classical communication, which is defined in terms of the squared negativity in complete analogy with the case of n-qubit systems. Our results elucidate the structure of quantum correlations in many-body harmonic lattice systems.

Disease phobia and disease conviction are separate dimensions underlying hypochondriasis.

PubMed

Fergus, Thomas A; Valentiner, David P

2010-12-01

The current study uses data from a large nonclinical college student sample (N = 503) to examine a structural model of hypochondriasis (HC). This model predicts the distinctiveness of two dimensions (disease phobia and disease conviction) purported to underlie the disorder, and that these two dimensions are differentially related to variables important to health anxiety and somatoform disorders, respectively. Results were generally consistent with the hypothesized model. Specifically, (a) body perception variables (somatosensory amplification and anxiety sensitivity - physical) emerged as significant predictors of disease phobia, but not disease conviction; (b) emotion dysregulation variables (cognitive avoidance and cognitive reappraisal) emerged as significant predictors of disease conviction, but not disease phobia; and (c) both disease phobia and disease conviction independently predicted medical utilization. Further, collapsing disease phobia and disease conviction onto a single latent factor provided an inadequate fit to the data. Conceptual and therapeutic implications of these results are discussed. 2010 Elsevier Ltd. All rights reserved.

Temporal variation in pelagic food chain length in response to environmental change

PubMed Central

Ruiz-Cooley, Rocio I.; Gerrodette, Tim; Fiedler, Paul C.; Chivers, Susan J.; Danil, Kerri; Ballance, Lisa T.

2017-01-01

Climate variability alters nitrogen cycling, primary productivity, and dissolved oxygen concentration in marine ecosystems. We examined the role of this variability (as measured by six variables) on food chain length (FCL) in the California Current (CC) by reconstructing a time series of amino acid–specific δ15N values derived from common dolphins, an apex pelagic predator, and using two FCL proxies. Strong declines in FCL were observed after the 1997–1999 El Niño Southern Oscillation (ENSO) event. Bayesian models revealed longer FCLs under intermediate conditions for surface temperature, chlorophyll concentration, multivariate ENSO index, and total plankton volume but not for hypoxic depth and nitrate concentration. Our results challenge the prevalent paradigm that suggested long-term stability in the food web structure in the CC and, instead, reveal that pelagic food webs respond strongly to disturbances associated with ENSO events, local oceanography, and ongoing changes in climate. PMID:29057322

Variability in group size and the evolution of collective action.

PubMed

Peña, Jorge; Nöldeke, Georg

2016-01-21

Models of the evolution of collective action typically assume that interactions occur in groups of identical size. In contrast, social interactions between animals occur in groups of widely dispersed size. This paper models collective action problems as two-strategy multiplayer games and studies the effect of variability in group size on the evolution of cooperative behavior under the replicator dynamics. The analysis identifies elementary conditions on the payoff structure of the game implying that the evolution of cooperative behavior is promoted or inhibited when the group size experienced by a focal player is more or less variable. Similar but more stringent conditions are applicable when the confounding effect of size-biased sampling, which causes the group-size distribution experienced by a focal player to differ from the statistical distribution of group sizes, is taken into account. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hidden Markov models incorporating fuzzy measures and integrals for protein sequence identification and alignment.

PubMed

Bidargaddi, Niranjan P; Chetty, Madhu; Kamruzzaman, Joarder

2008-06-01

Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.

Evaluation of Boreal Summer Monsoon Intraseasonal Variability in the GASS-YOTC Multi-Model Physical Processes Experiment

NASA Astrophysics Data System (ADS)

Mani, N. J.; Waliser, D. E.; Jiang, X.

2014-12-01

While the boreal summer monsoon intraseasonal variability (BSISV) exerts profound influence on the south Asian monsoon, the capability of present day dynamical models in simulating and predicting the BSISV is still limited. The global model evaluation project on vertical structure and diabatic processes of the Madden Julian Oscillations (MJO) is a joint venture, coordinated by the Working Group on Numerical Experimentation (WGNE) MJO Task Force and GEWEX Atmospheric System Study (GASS) program, for assessing the model deficiencies in simulating the ISV and for improving our understanding of the underlying processes. In this study the simulation of the northward propagating BSISV is investigated in 26 climate models with special focus on the vertical diabatic heating structure and clouds. Following parallel lines of inquiry as the MJO Task Force has done with the eastward propagating MJO, we utilize previously proposed and newly developed model performance metrics and process diagnostics and apply them to the global climate model simulations of BSISV.

Matching consumer feeding behaviours and resource traits: a fourth-corner problem in food-web theory.

PubMed

Monteiro, Angelo Barbosa; Faria, Lucas Del Bianco

2018-06-06

For decades, food web theory has proposed phenomenological models for the underlying structure of ecological networks. Generally, these models rely on latent niche variables that match the feeding behaviour of consumers with their resource traits. In this paper, we used a comprehensive database to evaluate different hypotheses on the best dependency structure of trait-matching patterns between consumers and resource traits. We found that consumer feeding behaviours had complex interactions with resource traits; however, few dimensions (i.e. latent variables) could reproduce the trait-matching patterns. We discuss our findings in the light of three food web models designed to reproduce the multidimensionality of food web data; additionally, we discuss how using species traits clarify food webs beyond species pairwise interactions and enable studies to infer ecological generality at larger scales, despite potential taxonomic differences, variations in ecological conditions and differences in species abundance between communities. © 2018 John Wiley & Sons Ltd/CNRS.

Optimization of extraction process by response surface methodology and preliminary structural analysis of polysaccharides from defatted peanut (Arachis hypogaea) cakes.

PubMed

Song, Yi; Du, Bingjian; Zhou, Ting; Han, Bing; Yu, Fei; Yang, Rui; Hu, Xiaosong; Ni, Yuanying; Li, Quanhong

2011-02-01

In this work, response surface methodology was used to determine optimum conditions for extraction of polysaccharides from defatted peanut cake. A central composite design including independent variables, such as extraction temperature (x(1)), extraction time (x(2)), and ethanol concentration (x(3)) was used. Selected response which evaluates the extraction process was polysaccharide yield, and the second-order model obtained for polysaccharide yield revealed coefficient of determination of 97.81%. The independent variable with the largest effect on response was ethanol concentration (x(3)). The optimum extraction conditions were found to be extraction temperature 48.7°C, extraction time 1.52 h, and ethanol concentration of 61.9% (v/v), respectively. Under these conditions, the extraction efficiency of polysaccharide can increase to 25.89%. The results of structural analysis showed that the main composition of defatted peanut cake polysaccharide was α-galactose. 2010 Elsevier Ltd. All rights reserved.

Evaluating Structural Equation Models for Categorical Outcomes: A New Test Statistic and a Practical Challenge of Interpretation.

PubMed

Monroe, Scott; Cai, Li

2015-01-01

This research is concerned with two topics in assessing model fit for categorical data analysis. The first topic involves the application of a limited-information overall test, introduced in the item response theory literature, to structural equation modeling (SEM) of categorical outcome variables. Most popular SEM test statistics assess how well the model reproduces estimated polychoric correlations. In contrast, limited-information test statistics assess how well the underlying categorical data are reproduced. Here, the recently introduced C2 statistic of Cai and Monroe (2014) is applied. The second topic concerns how the root mean square error of approximation (RMSEA) fit index can be affected by the number of categories in the outcome variable. This relationship creates challenges for interpreting RMSEA. While the two topics initially appear unrelated, they may conveniently be studied in tandem since RMSEA is based on an overall test statistic, such as C2. The results are illustrated with an empirical application to data from a large-scale educational survey.

Regional-Scale Drivers of Forest Structure and Function in Northwestern Amazonia

PubMed Central

Higgins, Mark A.; Asner, Gregory P.; Anderson, Christopher B.; Martin, Roberta E.; Knapp, David E.; Tupayachi, Raul; Perez, Eneas; Elespuru, Nydia; Alonso, Alfonso

2015-01-01

Field studies in Amazonia have found a relationship at continental scales between soil fertility and broad trends in forest structure and function. Little is known at regional scales, however, about how discrete patterns in forest structure or functional attributes map onto underlying edaphic or geological patterns. We collected airborne LiDAR (Light Detection and Ranging) data and VSWIR (Visible to Shortwave Infrared) imaging spectroscopy measurements over 600 km2 of northwestern Amazonian lowland forests. We also established 83 inventories of plant species composition and soil properties, distributed between two widespread geological formations. Using these data, we mapped forest structure and canopy reflectance, and compared them to patterns in plant species composition, soils, and underlying geology. We found that variations in soils and species composition explained up to 70% of variation in canopy height, and corresponded to profound changes in forest vertical profiles. We further found that soils and plant species composition explained more than 90% of the variation in canopy reflectance as measured by imaging spectroscopy, indicating edaphic and compositional control of canopy chemical properties. We last found that soils explained between 30% and 70% of the variation in gap frequency in these forests, depending on the height threshold used to define gaps. Our findings indicate that a relatively small number of edaphic and compositional variables, corresponding to underlying geology, may be responsible for variations in canopy structure and chemistry over large expanses of Amazonian forest. PMID:25793602

Combining measurements from three anatomical areas for glaucoma diagnosis using Fourier-domain optical coherence tomography.

PubMed

Loewen, Nils A; Zhang, Xinbo; Tan, Ou; Francis, Brian A; Greenfield, David S; Schuman, Joel S; Varma, Rohit; Huang, David

2015-09-01

To improve the diagnostic power for glaucoma by combining measurements of peripapillary nerve fibre layer (NFL), macular ganglion cell complex (GCC) and disc variables obtained with Fourier-domain optical coherence tomography (FD-OCT) into the glaucoma structural diagnostic index (GSDI). In this observational, cross-sectional study of subjects from the Advanced Imaging of Glaucoma Study, GCC and NFL of healthy and perimetrical glaucoma subjects from four major academic referral centres of the Advanced Imaging of Glaucoma Study were mapped with the RTVue FD-OCT. Global loss volume and focal loss volume parameters were defined using NFL and GCC normative reference maps. Optimal weights for NFL, GCC and disc variables were combined using multivariate logistic regression to build the GSDI. Glaucoma severity was classified using the Enhanced Glaucoma Staging System (GSS2). Diagnostic accuracy was assessed by sensitivity, specificity and the area under the receiver operator characteristic curve (AUC). We analysed 118 normal eyes of 60 subjects, 236 matched eyes of 166 subjects with perimetrical glaucoma, and 105 eyes from a healthy reference group of 61 subjects. The GSDI included composite overall thickness and focal loss volume with weighted NFL and GCC components, as well as the vertical cup-to-disc ratio. The AUC of 0.922 from leave-one-out cross validation was better than the best component variable alone (p=0.047). The partial AUC in the high specificity region was also better (p=0.01), with a sensitivity of 69% at 99% specificity, and a sensitivity of 80.3% at 95% specificity. For GSS2 stages 3-5 the sensitivity was 98% at 99% specificity, and 100% at 95% specificity. Combining structural measurements of GCC, NFL and disc variables from FD-OCT created a GSDI that improved the accuracy for glaucoma diagnosis. NCT01314326. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Intrinsic And Extrinsic Controls On Unsteady Deformation Rates, Northern Apennine Mountains, Italy

NASA Astrophysics Data System (ADS)

Anastasio, D. J.; Gunderson, K. L.; Pazzaglia, F. J.; Kodama, K. P.

2017-12-01

The slip rates of faults in the Northern Apennine Mountains were unsteady at 104-105 year timescales during the Neogene and Quaternary. Fault slip rates were recovered from growth strata and uplifted fluvial terraces associated with the Salsomaggiore, Quatto Castella, and Castevetro fault-related folds, sampled along the Stirone, Enza, and Panaro Rivers, respectively. The forelimb stratigraphy of each anticline was dated using rock magnetic-based cyclostratigraphy, which varies with Milankovitch periodicity, multispecies biostratigraphy, magnetostratigraphy, OSL luminescence dating, TCN burial dating, and radiocarbon dating of uplifted and folded fluvial terraces. Fault slip magnitudes were constrained with trishear forward models. We observed decoupled deformation and sediment accumulation rates at each structure. From 3.5Ma deformation of a thick and thin-skinned thrusts was temporally variable and controlled by intrinsic rock processes, whereas, the more regional Pede-Apenninic thrust fault, a thick-skinned thrust underlying the mountain front, was likely activated because of extrinsic forcing from foreland basin sedimentation rate accelerations since 1.4Ma. We found that reconstructed slip rate variability increased as the time resolution increased. The reconstructed slip history of the thin-skinned thrust faults was characterized relatively long, slow fold growth and associated fault slip, punctuated by shorter, more rapid periods limb rotation, and slip on the underlying thrust fault timed asynchronously. Thrust fault slip rates slip rates were ≤ 0.1 to 6 mm/yr at these intermediate timescales. The variability of slip rates on the thrusts is likely related to strain partitioning neighboring faults within the orogenic wedge. The studied structures slowed down at 1Ma when there was a switch to slower synchronous fault slip coincident with orogenic wedge thickening due to the emplacement of the out of sequence Pene-Apenninic thrust fault that was emplaced at 1.4±0.7 mm/yr. Both tectonic control and climate controlled variability on syntectonic sedimentation was observed in the growth sections.

Using structural equation modeling to detect response shifts and true change in discrete variables: an application to the items of the SF-36.

PubMed

Verdam, Mathilde G E; Oort, Frans J; Sprangers, Mirjam A G

2016-06-01

The structural equation modeling (SEM) approach for detection of response shift (Oort in Qual Life Res 14:587-598, 2005. doi: 10.1007/s11136-004-0830-y ) is especially suited for continuous data, e.g., questionnaire scales. The present objective is to explain how the SEM approach can be applied to discrete data and to illustrate response shift detection in items measuring health-related quality of life (HRQL) of cancer patients. The SEM approach for discrete data includes two stages: (1) establishing a model of underlying continuous variables that represent the observed discrete variables, (2) using these underlying continuous variables to establish a common factor model for the detection of response shift and to assess true change. The proposed SEM approach was illustrated with data of 485 cancer patients whose HRQL was measured with the SF-36, before and after start of antineoplastic treatment. Response shift effects were detected in items of the subscales mental health, physical functioning, role limitations due to physical health, and bodily pain. Recalibration response shifts indicated that patients experienced relatively fewer limitations with "bathing or dressing yourself" (effect size d = 0.51) and less "nervousness" (d = 0.30), but more "pain" (d = -0.23) and less "happiness" (d = -0.16) after antineoplastic treatment as compared to the other symptoms of the same subscale. Overall, patients' mental health improved, while their physical health, vitality, and social functioning deteriorated. No change was found for the other subscales of the SF-36. The proposed SEM approach to discrete data enables response shift detection at the item level. This will lead to a better understanding of the response shift phenomena at the item level and therefore enhances interpretation of change in the area of HRQL.

Word Naming in the L1 and L2: A Dynamic Perspective on Automatization and the Degree of Semantic Involvement in Naming.

PubMed

Plat, Rika; Lowie, Wander; de Bot, Kees

2017-01-01

Reaction time data have long been collected in order to gain insight into the underlying mechanisms involved in language processing. Means analyses often attempt to break down what factors relate to what portion of the total reaction time. From a dynamic systems theory perspective or an interaction dominant view of language processing, it is impossible to isolate discrete factors contributing to language processing, since these continually and interactively play a role. Non-linear analyses offer the tools to investigate the underlying process of language use in time, without having to isolate discrete factors. Patterns of variability in reaction time data may disclose the relative contribution of automatic (grapheme-to-phoneme conversion) processing and attention-demanding (semantic) processing. The presence of a fractal structure in the variability of a reaction time series indicates automaticity in the mental structures contributing to a task. A decorrelated pattern of variability will indicate a higher degree of attention-demanding processing. A focus on variability patterns allows us to examine the relative contribution of automatic and attention-demanding processing when a speaker is using the mother tongue (L1) or a second language (L2). A word naming task conducted in the L1 (Dutch) and L2 (English) shows L1 word processing to rely more on automatic spelling-to-sound conversion than L2 word processing. A word naming task with a semantic categorization subtask showed more reliance on attention-demanding semantic processing when using the L2. A comparison to L1 English data shows this was not only due to the amount of language use or language dominance, but also to the difference in orthographic depth between Dutch and English. An important implication of this finding is that when the same task is used to test and compare different languages, one cannot straightforwardly assume the same cognitive sub processes are involved to an equal degree using the same task in different languages.

Consensus positive position feedback control for vibration attenuation of smart structures

NASA Astrophysics Data System (ADS)

Omidi, Ehsan; Nima Mahmoodi, S.

2015-04-01

This paper presents a new network-based approach for active vibration control in smart structures. In this approach, a network with known topology connects collocated actuator/sensor elements of the smart structure to one another. Each of these actuators/sensors, i.e., agent or node, is enhanced by a separate multi-mode positive position feedback (PPF) controller. The decentralized PPF controlled agents collaborate with each other in the designed network, under a certain consensus dynamics. The consensus constraint forces neighboring agents to cooperate with each other such that the disagreement between the time-domain actuation of the agents is driven to zero. The controller output of each agent is calculated using state-space variables; hence, optimal state estimators are designed first for the proposed observer-based consensus PPF control. The consensus controller is numerically investigated for a flexible smart structure, i.e., a thin aluminum beam that is clamped at its both ends. Results demonstrate that the consensus law successfully imposes synchronization between the independently controlled agents, as the disagreements between the decentralized PPF controller variables converge to zero in a short time. The new consensus PPF controller brings extra robustness to vibration suppression in smart structures, where malfunctions of an agent can be compensated for by referencing the neighboring agents’ performance. This is demonstrated in the results by comparing the new controller with former centralized PPF approach.

Hydrothermal synthesis, crystal structure, luminescent and magnetic properties of a new mononuclear GdIII coordination complex

NASA Astrophysics Data System (ADS)

Coban, Mustafa Burak

2018-06-01

A new GdIII coordination complex, {[Gd(2-stp)2(H2O)6].2(4,4'-bipy).4(H2O)}, complex 1, (2-stp = 2-sulfoterephthalate anion and 4,4'-bipy = 4,4'-bipyridine), has been synthesized by hydrothermal method and characterized by elemental analysis, solid state UV-Vis and FT-IR spectroscopy, single-crystal X-ray diffraction, solid state photoluminescence and variable-temperature magnetic measurements. The crystal structure determination shows that GdIII ions are eight coordinated and adopt a distorted square-antiprismatic geometry. Molecules interacting through intra- and intermolecular (O-H⋯O, O-H⋯N) hydrogen bonds in complex 1, give rise to 3D hydrogen bonded structure and the discrete lattice 4,4'-bipy molecules occupy the channel of the 3D structure. π-π stacking interactions also exist 4,4'-bipy-4,4'-bipy and 4,4'-bipy-2-stp molecule rings in 3D structures. Additionally, solid state photoluminescence properties of complex 1 at room temperature have been investigated. Under the excitation of UV light (at 349 nm), the complex 1 exhibited green emissions (at 505 nm) of GdIII ion in the visible region. Furthermore, Variable-temperature magnetic susceptibility and isothermal magnetization as function of external magnetic field studies reveal that complex 1 displays possible antiferromagnetic interaction.

Juvenile zebra finches learn the underlying structural regularities of their fathers’ song

PubMed Central

Menyhart, Otília; Kolodny, Oren; Goldstein, Michael H.; DeVoogd, Timothy J.; Edelman, Shimon

2015-01-01

Natural behaviors, such as foraging, tool use, social interaction, birdsong, and language, exhibit branching sequential structure. Such structure should be learnable if it can be inferred from the statistics of early experience. We report that juvenile zebra finches learn such sequential structure in song. Song learning in finches has been extensively studied, and it is generally believed that young males acquire song by imitating tutors (Zann, 1996). Variability in the order of elements in an individual’s mature song occurs, but the degree to which variation in a zebra finch’s song follows statistical regularities has not been quantified, as it has typically been dismissed as production error (Sturdy et al., 1999). Allowing for the possibility that such variation in song is non-random and learnable, we applied a novel analytical approach, based on graph-structured finite-state grammars, to each individual’s full corpus of renditions of songs. This method does not assume syllable-level correspondence between individuals. We find that song variation can be described by probabilistic finite-state graph grammars that are individually distinct, and that the graphs of juveniles are more similar to those of their fathers than to those of other adult males. This grammatical learning is a new parallel between birdsong and language. Our method can be applied across species and contexts to analyze complex variable learned behaviors, as distinct as foraging, tool use, and language. PMID:26005428

Probabilistic Simulation of Progressive Fracture in Bolted-Joint Composite Laminates

NASA Technical Reports Server (NTRS)

Minnetyan, L.; Singhal, S. N.; Chamis, C. C.

1996-01-01

This report describes computational methods to probabilistically simulate fracture in bolted composite structures. An innovative approach that is independent of stress intensity factors and fracture toughness was used to simulate progressive fracture. The effect of design variable uncertainties on structural damage was also quantified. A fast probability integrator assessed the scatter in the composite structure response before and after damage. Then the sensitivity of the response to design variables was computed. General-purpose methods, which are applicable to bolted joints in all types of structures and in all fracture processes-from damage initiation to unstable propagation and global structure collapse-were used. These methods were demonstrated for a bolted joint of a polymer matrix composite panel under edge loads. The effects of the fabrication process were included in the simulation of damage in the bolted panel. Results showed that the most effective way to reduce end displacement at fracture is to control both the load and the ply thickness. The cumulative probability for longitudinal stress in all plies was most sensitive to the load; in the 0 deg. plies it was very sensitive to ply thickness. The cumulative probability for transverse stress was most sensitive to the matrix coefficient of thermal expansion. In addition, fiber volume ratio and fiber transverse modulus both contributed significantly to the cumulative probability for the transverse stresses in all the plies.

A Polychoric Instrumental Variable (PIV) Estimator for Structural Equation Models with Categorical Variables

ERIC Educational Resources Information Center

Bollen, Kenneth A.; Maydeu-Olivares, Albert

2007-01-01

This paper presents a new polychoric instrumental variable (PIV) estimator to use in structural equation models (SEMs) with categorical observed variables. The PIV estimator is a generalization of Bollen's (Psychometrika 61:109-121, 1996) 2SLS/IV estimator for continuous variables to categorical endogenous variables. We derive the PIV estimator…

A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures

PubMed Central

Chen, Yun; Yang, Hui

2016-01-01

In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering. PMID:27966581

A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures.

PubMed

Chen, Yun; Yang, Hui

2016-12-14

In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering.

Kinetics of human aging: I. Rates of senescence between ages 30 and 70 years in healthy people.

PubMed

Sehl, M E; Yates, F E

2001-05-01

A calculation of loss rates is reported for human structural and functional variables from a substantially larger data set than has been previously studied. Data were collected for healthy, nonsmoking human subjects of both sexes from a literature search of cross-sectional, longitudinal, and cross-sequential studies. The number of studies analyzed was 469, and the total number of subjects was 54,274. A linear model provided a fit of the data, for each variable, that was not significantly different from the best polynomial fit. Therefore, linear loss rates (as a percent decline per year from the reference value at age 30) were calculated for 445 variables from 13 organ systems, and additionally for 24 variables even more integrative, such as maximum oxygen consumption and exercise performance, that express effects of multiple contributing variables and systems. The frequency distribution of the 13 individual system linear loss rates (as percent loss per year) for a very healthy population has roughly a unimodal, right-skewed shape, with mean 0.65, median 0.5, and variance 0.32. (The actual underlying distribution could be a truncated Gaussian, an exponential, Poisson, gamma or some other). The linear estimates of loss rates were clustered between 0% and 2% per year for variables from most organ systems, with exceptions being the endocrine, thermoregulatory, and gastrointestinal systems, for which wider ranges (up to approximately 3% per year) of loss rates were found. We suggest that this set of linear losses over time, observed in healthy individuals between ages (approximately) 30 to 70 years, exposes the underlying kinetics of human senescence, independent of effects of substantial disease.

Composite sizing and ply orientation for stiffness requirements using a large finite element structural model

NASA Technical Reports Server (NTRS)

Radovcich, N. A.; Gentile, D. P.

1989-01-01

A NASTRAN bulk dataset preprocessor was developed to facilitate the integration of filamentary composite laminate properties into composite structural resizing for stiffness requirements. The NASCOMP system generates delta stiffness and delta mass matrices for input to the flutter derivative program. The flutter baseline analysis, derivative calculations, and stiffness and mass matrix updates are controlled by engineer defined processes under an operating system called CBUS. A multi-layered design variable grid system permits high fidelity resizing without excessive computer cost. The NASCOMP system uses ply layup drawings for basic input. The aeroelastic resizing for stiffness capability was used during an actual design exercise.

Research of TREETOPS Structural Dynamics Controls Simulation Upgrade

NASA Technical Reports Server (NTRS)

Yates, Rose M.

1996-01-01

Under the provisions of contract number NAS8-40194, which was entitled 'TREETOPS Structural Dynamics and Controls Simulation System Upgrade', Oakwood College contracted to produce an upgrade to the existing TREETOPS suite of analysis tools. This suite includes the main simulation program, TREETOPS, two interactive preprocessors, TREESET and TREEFLX, an interactive post processor, TREEPLOT, and an adjunct program, TREESEL. A 'Software Design Document', which provides descriptions of the argument lists and internal variables for each subroutine in the TREETOPS suite, was established. Additionally, installation guides for both DOS and UNIX platforms were developed. Finally, updated User's Manuals, as well as a Theory Manual, were generated.

A systematic multiscale modeling and experimental approach to protect grain boundaries in magnesium alloys from corrosion

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

Horstemeyer, Mark R.; Chaudhuri, Santanu

2015-09-30

A multiscale modeling Internal State Variable (ISV) constitutive model was developed that captures the fundamental structure-property relationships. The macroscale ISV model used lower length scale simulations (Butler-Volmer and Electronics Structures results) in order to inform the ISVs at the macroscale. The chemomechanical ISV model was calibrated and validated from experiments with magnesium (Mg) alloys that were investigated under corrosive environments coupled with experimental electrochemical studies. Because the ISV chemomechanical model is physically based, it can be used for other material systems to predict corrosion behavior. As such, others can use the chemomechanical model for analyzing corrosion effects on their designs.

SSME/side loads analysis for flight configuration, revision A. [structural analysis of space shuttle main engine under side load excitation

NASA Technical Reports Server (NTRS)

Holland, W.

1974-01-01

This document describes the dynamic loads analysis accomplished for the Space Shuttle Main Engine (SSME) considering the side load excitation associated with transient flow separation on the engine bell during ground ignition. The results contained herein pertain only to the flight configuration. A Monte Carlo procedure was employed to select the input variables describing the side load excitation and the loads were statistically combined. This revision includes an active thrust vector control system representation and updated orbiter thrust structure stiffness characteristics. No future revisions are planned but may be necessary as system definition and input parameters change.

Variability in snowpack accumulation and ablation associated with mountain pine beetle infestation in western forests

NASA Astrophysics Data System (ADS)

Biederman, J. A.; Harpold, A. A.; Gochis, D. J.; Reed, D.; Brooks, P. D.

2010-12-01

Seasonal snowcover is a primary source of water to urban and agricultural regions in the western United States, where Mountain Pine Beetle (MPB) has caused rapid and extensive changes to vegetation in montane forests. Levels of MPB infestation in these seasonally snow-covered systems are unprecedented, and it is unknown how this will affect water yield, especially in changing climate conditions. To address this unknown we ask: How does snow accumulation and ablation vary across forest with differing levels of impact? Our study areas in the Rocky Mountains of CO and WY are similar in latitude, elevation and forest structure before infestation, but they vary in the intensity and timing of beetle infestation and tree mortality. We present a record for winter 2010 that includes continuous snow depth as well as stand-scale snow surveys at maximum accumulation. Additional measurements include snowfall, net radiation, temperature and wind speed as well as characterization of forest structure by leaf area index. In a stand uninfested by MPB, maximum snow depth was fairly uniform under canopy (mean = 86 cm, coefficient of variation = 0.021), while canopy gaps showed greater and more variable depth (mean = 117 cm, CV = 0.111). This is consistent with several studies demonstrating that snowfall into canopy gaps depends upon gap size, orientation, wind speed and storm size. In a stand impacted in 2007, snow depth under canopy was less uniform, and there were smaller differences in both mean depth and variability between canopy (mean = 93 cm, CV = 0.072) and gaps (mean = 97 cm, CV = 0.070), consistent with decreased canopy density. In a more recently infested (2009) stand with an intermediate level of MPB impact, mean snow depths were similar between canopy (96 cm, CV = 0.016) and gaps (95 cm, CV = 0.185) but gaps showed much greater variability, suggesting controls similar to those in effect in the uninfested stand. We further use these data to model snow accumulation and ablation as a function of vegetation, topography and fine-scale climate variability, with preliminary results presented at the meeting.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components

NASA Technical Reports Server (NTRS)

1991-01-01

The fourth year of technical developments on the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) system for Probabilistic Structural Analysis Methods is summarized. The effort focused on the continued expansion of the Probabilistic Finite Element Method (PFEM) code, the implementation of the Probabilistic Boundary Element Method (PBEM), and the implementation of the Probabilistic Approximate Methods (PAppM) code. The principal focus for the PFEM code is the addition of a multilevel structural dynamics capability. The strategy includes probabilistic loads, treatment of material, geometry uncertainty, and full probabilistic variables. Enhancements are included for the Fast Probability Integration (FPI) algorithms and the addition of Monte Carlo simulation as an alternate. Work on the expert system and boundary element developments continues. The enhanced capability in the computer codes is validated by applications to a turbine blade and to an oxidizer duct.

Structure, Elastic Constants and XRD Spectra of Extended Solids under High Pressure

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

Batyrev, I. G.; Coleman, S. P.; Ciezak-Jenkins, J. A.

We present results of evolutionary simulations based on density functional calculations of a potentially new type of energetic materials called extended solids: P-N and N-H. High-density structures with covalent bonds generated using variable and fixed concentration methods were analysed in terms of thermo-dynamical stability and agreement with experimental X-ray diffraction (XRD) spectra. X-ray diffraction spectra were calculated using a virtual diffraction algorithm that computes kinematic diffraction intensity in three-dimensional reciprocal space before being reduced to a two-theta line profile. Calculated XRD patterns were used to search for the structure of extended solids present at experimental pressures by optimizing data accordingmore » to experimental XRD peak position, peak intensity and theoretically calculated enthalpy. Elastic constants has been calculated for thermodynamically stable structures of P-N system.« less

Variable Neural Adaptive Robust Control: A Switched System Approach

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

Lian, Jianming; Hu, Jianghai; Zak, Stanislaw H.

2015-05-01

Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multi-input multi-output uncertain systems. The controllers incorporate a variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. The variable-structure RBF network solves the problem of structure determination associated with fixed-structure RBF networks. It can determine the network structure on-line dynamically by adding or removing radial basis functions according to the tracking performance. The structure variation is taken into account in the stability analysis of the closed-loop system using a switched system approach with the aid of the piecewisemore » quadratic Lyapunov function. The performance of the proposed variable neural adaptive robust controllers is illustrated with simulations.« less

Structural differences between native Hen egg white lysozyme and its fibrils under different environmental conditions

NASA Astrophysics Data System (ADS)

Bhattacharya, Susmita; Ghosh, Sudeshna; Dasgupta, Swagata; Roy, Anushree

2013-10-01

The difference in molecular structure of native HEWL and its fibrils, grown at a pH value near physiological pH 7.4 and at a pH value just above the pI, 10.7 in presence and absence of Cu(II) ions, is discussed. We focus on differences between the molecular structure of the native protein and fibrils using principal component analysis of their Raman spectra. The overlap areas of the scores of each species are used to quantify the difference in the structure of the native HEWL and fibrils in different environments. The overall molecular structures are significantly different for fibrils grown at two pH values. However, in presence of Cu(II) ions, the fibrils have similarities in their molecular structures at these pH environments. Spectral variation within each species, as obtained from the standard deviations of the scores in PCA plots, reveals the variability in the structure within a particular species.

Impact of bimodal textural heterogeneity and connectivity on flow and transport through unsaturated mine waste rock

NASA Astrophysics Data System (ADS)

Appels, Willemijn M.; Ireson, Andrew M.; Barbour, S. Lee

2018-02-01

Mine waste rock dumps have highly variable flowpaths caused by contrasting textures and geometry of materials laid down during the 'plug dumping' process. Numerical experiments were conducted to investigate how these characteristics control unsaturated zone flow and transport. Hypothetical profiles of inner-lift structure were generated with multiple point statistics and populated with hydraulic parameters of a finer and coarser material. Early arrival of water and solutes at the bottom of the lifts was observed after spring snowmelt. The leaching efficiency, a measure of the proportion of a resident solute that is flushed out of the rock via infiltrating snowmelt or rainfall, was consistently high, but modified by the structure and texture of the lift. Under high rates of net percolation during snowmelt, preferential flow was generated in coarse textured part of the rock, and solutes in the fine textured parts of the rock remained stagnant. Under lower rates of net percolation during the summer and fall, finer materialswere flushed too, and the spatial variability of solute concentration in the lift was reduced. Layering of lifts leads to lower flow rates at depth, minimizing preferential flow and increased leaching of resident solutes. These findings highlight the limited role of large scale connected geometries on focusing flow and transport under dynamic surface net percolation conditions. As such, our findings agree with recent numerical results from soil studies with Gaussian connected geometries as well as recent experimental findings, emphasizing the dominant role of matrix flow and high leaching efficiency in large waste rock dumps.

An anti-hapten camelid antibody reveals a cryptic binding site with significant energetic contributions from a nonhypervariable loop

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

Fanning, Sean W.; Horn, James R.

2014-03-05

Conventional anti-hapten antibodies typically bind low-molecular weight compounds (haptens) in the crevice between the variable heavy and light chains. Conversely, heavy chain-only camelid antibodies, which lack a light chain, must rely entirely on a single variable domain to recognize haptens. While several anti-hapten VHHs have been generated, little is known regarding the underlying structural and thermodynamic basis for hapten recognition. Here, an anti-methotrexate VHH (anti-MTX VHH) was generated using grafting methods whereby the three complementarity determining regions (CDRs) were inserted onto an existing VHH framework. Thermodynamic analysis of the anti-MTX VHH CDR1-3 Graft revealed a micromolar binding affinity, while themore » crystal structure of the complex revealed a somewhat surprising noncanonical binding site which involved MTX tunneling under the CDR1 loop. Due to the close proximity of MTX to CDR4, a nonhypervariable loop, the CDR4 loop sequence was subsequently introduced into the CDR1-3 graft, which resulted in a dramatic 1000-fold increase in the binding affinity. Crystal structure analysis of both the free and complex anti-MTX CDR1-4 graft revealed CDR4 plays a significant role in both intermolecular contacts and binding site conformation that appear to contribute toward high affinity binding. Additionally, the anti-MTX VHH possessed relatively high specificity for MTX over closely related compounds aminopterin and folate, demonstrating that VHH domains are capable of binding low-molecular weight ligands with high affinity and specificity, despite their reduced interface.« less

Effects of ultraviolet radiation and nutrients on the structure-function of phytoplankton in a high mountain lake.

PubMed

Korbee, Nathalie; Carrillo, Presentación; Mata, M Teresa; Rosillo, Silvia; Medina-Sánchez, Juan Manuel; Figueroa, Félix L

2012-06-01

The combined effect of high solar ultraviolet radiation (UVR) and nutrient supply in a phytoplankton community of a high mountain lake is analyzed in a in situ experiment for 6 days with 2 × 2 factorial design. Interactive UVR × nutrient effects on structural and functional variables (algal biomass, chlorophyll a (chl a), primary production (PP), maximal electron transport rate (ETR(max)), and alkaline phosphatase activity (APA)), as well as stoichiometric ones (sestonic N per cell and N:P ratio) were found. Under non-nutrient enriched conditions, no deleterious effects of UVR on structural variables, PP, photosynthetic efficiency and ETR(max) were observed, whereas only particulate and total APA were affected by UVR. However, percentage excreted organic carbon (%EOC), dissolved APA and sestonic C and P per cell increased under UVR, leading to a decrease in algal C:P and N:P ratios. After nutrient enrichment, chl a, total algal biomass and PP were negatively affected by UVR whereas %EOC, ETR(max) and internal C, P and N content increased. We suggest that the mechanism of algal acclimation to UVR in this high UVR flux ecosystem seems to be related to the increase of internal algal P-content mediated by physiological mechanisms to save P and by a stimulatory UVR effect on dissolved extracellular APA. The mechanism involved in the unmasking effect of UVR after nutrient-enrichment may be the result of a greater sensitivity to UVR-induced cell damage, making the negative UVR effects more evident.

Variation in Vegetation Structure and Soil Properties, and the Relation Between Understory Plants and Environmental Variables Under Different Phyllostachys pubescens Forests in Southeastern China

NASA Astrophysics Data System (ADS)

Zhang, Changshun; Xie, Gaodi; Fan, Shaohui; Zhen, Lin

2010-04-01

Biodiversity maintenance and soil improvement are key sustainable forestry objectives. Research on the effects of bamboo forest management on plant diversity and soil properties are therefore necessary in bamboo-growing regions, such as southeastern China’s Shunchang County, that have not been studied from this perspective. We analyzed the effects of different Phyllostachys pubescens proportions in managed forests on vegetation structure and soil properties using pure Cunninghamia lanceolata forests as a contrast, and analyzed the relation between understory plants and environmental variables (i.e., topography, stand and soil characteristics) by canonical correspondence analysis (CCA). The forest with 80% P. pubescens and 20% hardwoods (such as Phoebe bournei, Jatropha curcas, Schima superba) maintained the highest plant diversity and best soil properties, with significantly higher plant diversity than the C. lanceolata forest, and better soil physicochemical and biological properties. The distribution of understory plants is highly related to environmental factors. Silvicultural disturbance strongly influenced the ability of different bamboo forests to maintain biodiversity and soil quality under extensive management, and the forest responses to management were consistent with the intermediate-disturbance hypothesis (i.e., diversity and soil properties were best at intermediate disturbance levels). Our results suggest that biodiversity maintenance and soil improvement are important management goals for sustainable bamboo management. To achieve those objectives, managers should balance the inputs and outputs of nutrients and protect understory plants by using appropriate fertilizer (e.g., organic fertilizer), adjusting stand structure, modifying utilization model and the harvest time, and controlling the intensity of culms and shoots harvests.

Is there a disparity in the hospital care received under a universal health insurance program in Taiwan?

PubMed

Hsiao, Yu-Yu; Cheng, Shou-Hsia

2013-07-01

To analyze the disparity in hospital care among people of various socio-economic status (SES) under a universal health insurance scheme. A survey questionnaire was mailed to discharged patients in October 2010. This study included 183 large-scale hospitals in Taiwan. A total of 3015 patients/caregivers completed the questionnaires, which yielded a response rate of 58%. Three variables were included. The two access-to-care variables were admission route and accreditation level of the hospital in which the patient stayed. A structured questionnaire, the patient-reported hospital quality (PRHQ), was included to characterize patient's experience of hospital stay. Patients with lower education were less likely to be admitted to a hospital according to a planned schedule, or to choose an Medical Center Hospital. However, SES was not associated with the PRHQ scores. Furthermore, patients with unplanned admission were associated with lower PRHQ scores than those with planned admission to the hospital. Under the universal health insurance system in Taiwan, lower education is associated with unplanned admission to a hospital, which might result in poorer perceived quality of care. Reducing unplanned admission is a challenge for health authorities in the future.

Invited Review: A review of deterministic effects in cyclic variability of internal combustion engines

DOE PAGES

Finney, Charles E.; Kaul, Brian C.; Daw, C. Stuart; ...

2015-02-18

Here we review developments in the understanding of cycle to cycle variability in internal combustion engines, with a focus on spark-ignited and premixed combustion conditions. Much of the research on cyclic variability has focused on stochastic aspects, that is, features that can be modeled as inherently random with no short term predictability. In some cases, models of this type appear to work very well at describing experimental observations, but the lack of predictability limits control options. Also, even when the statistical properties of the stochastic variations are known, it can be very difficult to discern their underlying physical causes andmore » thus mitigate them. Some recent studies have demonstrated that under some conditions, cyclic combustion variations can have a relatively high degree of low dimensional deterministic structure, which implies some degree of predictability and potential for real time control. These deterministic effects are typically more pronounced near critical stability limits (e.g. near tipping points associated with ignition or flame propagation) such during highly dilute fueling or near the onset of homogeneous charge compression ignition. We review recent progress in experimental and analytical characterization of cyclic variability where low dimensional, deterministic effects have been observed. We describe some theories about the sources of these dynamical features and discuss prospects for interactive control and improved engine designs. In conclusion, taken as a whole, the research summarized here implies that the deterministic component of cyclic variability will become a pivotal issue (and potential opportunity) as engine manufacturers strive to meet aggressive emissions and fuel economy regulations in the coming decades.« less

Refining the tobacco dependence phenotype using the Wisconsin Inventory of Smoking Dependence Motives (WISDM)

PubMed Central

Piper, Megan E.; Bolt, Daniel M.; Kim, Su-Young; Japuntich, Sandra J.; Smith, Stevens S.; Niederdeppe, Jeff; Cannon, Dale S.; Baker, Timothy B.

2008-01-01

The construct of tobacco dependence is important from both scientific and public health perspectives, but it is poorly understood. The current research integrates person-centered analyses (e.g., latent profile analysis) and variable-centered analyses (e.g., exploratory factor analysis) to understand better the latent structure of dependence and to guide distillation of the phenotype. Using data from four samples of smokers (including treatment and non-treatment samples), latent profiles were derived using the Wisconsin Inventory of Smoking Dependence Motives (WISDM) subscale scores. Across all four samples, results revealed a unique latent profile that had relative elevations on four dependence motive subscales (Automaticity, Craving, Loss of Control, and Tolerance). Variable-centered analyses supported the uniqueness of these four subscales both as measures of a common factor distinct from that underlying the other nine subscales, and as the strongest predictors of relapse, withdrawal and other dependence criteria. Conversely, the remaining nine motives carried little unique predictive validity regarding dependence. Applications of a factor mixture model further support the presence of a unique class of smokers in relation to a common factor underlying the four subscales. The results illustrate how person-centered analyses may be useful as a supplement to variable-centered analyses for uncovering variables that are necessary and/or sufficient predictors of disorder criteria, as they may uncover small segments of a population in which the variables are uniquely distributed. The results also suggest that severe dependence is associated with a pattern of smoking that is heavy, pervasive, automatic and relatively unresponsive to instrumental contingencies. PMID:19025223

Analyses of Fatigue and Fatigue-Crack Growth under Constant- and Variable-Amplitude Loading

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.

1999-01-01

Studies on the growth of small cracks have led to the observation that fatigue life of many engineering materials is primarily crack growth from micro-structural features, such as inclusion particles, voids, slip-bands or from manufacturing defects. This paper reviews the capabilities of a plasticity-induced crack-closure model to predict fatigue lives of metallic materials using small-crack theory under various loading conditions. Constraint factors, to account for three-dimensional effects, were selected to correlate large-crack growth rate data as a function of the effective stress-intensity factor range (delta K(sub eff)) under constant-amplitude loading. Modifications to the delta K(sub eff)-rate relations in the near-threshold regime were needed to fit measured small-crack growth rate behavior. The model was then used to calculate small- and large-crack growth rates, and to predict total fatigue lives, for notched and un-notched specimens under constant-amplitude and spectrum loading. Fatigue lives were predicted using crack-growth relations and micro-structural features like those that initiated cracks in the fatigue specimens for most of the materials analyzed. Results from the tests and analyses agreed well.

Observations of upper ocean stability and heat fluxes in the Antarctic from under-ice Argo float profile data.

NASA Astrophysics Data System (ADS)

Wilson, E. A.; Riser, S.

2016-12-01

Sea ice growth around Antarctica is intimately linked to the stability and thermohaline structure of the underlying ocean. As sea ice grows, the resulting brine triggers convective instabilities that deepen the mixed layer and entrain warm water from the weakly stratified pycnocline. The heat released from this process acts as a strong negative feedback to ice growth which, under the right scenarios, can exceed the initial atmospheric heat loss. Much of our current understanding of this ice-ocean interaction comes from a handful of relatively short field campaigns in the Weddell Sea. Here, we supplement those observations with an analysis of over 9000 under-ice Argo float profiles, collected between 2006-2015. These profiles provide an unprecedented view of the temporal and spatial variability of the upper ocean structure throughout the Antarctic region. With these observations and a theoretical understanding of the coupled ice-ocean system, we assess the ocean's potential to limit thermodynamic ice growth as well as its susceptibility to deep convection in different regions. Using these results, we infer how recent climatic changes may influence Antarctic sea ice growth and deep ocean ventilation in the near future.

Spatial variability in tree regeneration after wildfire delays and dampens future bark beetle outbreaks

PubMed Central

Donato, Daniel C.; Raffa, Kenneth F.; Turner, Monica G.

2016-01-01

Climate change is altering the frequency and severity of forest disturbances such as wildfires and bark beetle outbreaks, thereby increasing the potential for sequential disturbances to interact. Interactions can amplify or dampen disturbances, yet the direction and magnitude of future disturbance interactions are difficult to anticipate because underlying mechanisms remain poorly understood. We tested how variability in postfire forest development affects future susceptibility to bark beetle outbreaks, focusing on mountain pine beetle (Dendroctonus ponderosae) and Douglas-fir beetle (Dendroctonus pseudotsugae) in forests regenerating from the large high-severity fires that affected Yellowstone National Park in Wyoming in 1988. We combined extensive field data on postfire tree regeneration with a well-tested simulation model to assess susceptibility to bark beetle outbreaks over 130 y of stand development. Despite originating from the same fire event, among-stand variation in forest structure was very high and remained considerable for over a century. Thus, simulated emergence of stands susceptible to bark beetles was not temporally synchronized but was protracted by several decades, compared with stand development from spatially homogeneous regeneration. Furthermore, because of fire-mediated variability in forest structure, the habitat connectivity required to support broad-scale outbreaks and amplifying cross-scale feedbacks did not develop until well into the second century after the initial burn. We conclude that variability in tree regeneration after disturbance can dampen and delay future disturbance by breaking spatiotemporal synchrony on the landscape. This highlights the importance of fostering landscape variability in the context of ecosystem management given changing disturbance regimes. PMID:27821739

Spatial variability in tree regeneration after wildfire delays and dampens future bark beetle outbreaks.

PubMed

Seidl, Rupert; Donato, Daniel C; Raffa, Kenneth F; Turner, Monica G

2016-11-15

Climate change is altering the frequency and severity of forest disturbances such as wildfires and bark beetle outbreaks, thereby increasing the potential for sequential disturbances to interact. Interactions can amplify or dampen disturbances, yet the direction and magnitude of future disturbance interactions are difficult to anticipate because underlying mechanisms remain poorly understood. We tested how variability in postfire forest development affects future susceptibility to bark beetle outbreaks, focusing on mountain pine beetle (Dendroctonus ponderosae) and Douglas-fir beetle (Dendroctonus pseudotsugae) in forests regenerating from the large high-severity fires that affected Yellowstone National Park in Wyoming in 1988. We combined extensive field data on postfire tree regeneration with a well-tested simulation model to assess susceptibility to bark beetle outbreaks over 130 y of stand development. Despite originating from the same fire event, among-stand variation in forest structure was very high and remained considerable for over a century. Thus, simulated emergence of stands susceptible to bark beetles was not temporally synchronized but was protracted by several decades, compared with stand development from spatially homogeneous regeneration. Furthermore, because of fire-mediated variability in forest structure, the habitat connectivity required to support broad-scale outbreaks and amplifying cross-scale feedbacks did not develop until well into the second century after the initial burn. We conclude that variability in tree regeneration after disturbance can dampen and delay future disturbance by breaking spatiotemporal synchrony on the landscape. This highlights the importance of fostering landscape variability in the context of ecosystem management given changing disturbance regimes.

Error response test system and method using test mask variable

NASA Technical Reports Server (NTRS)

Gender, Thomas K. (Inventor)

2006-01-01

An error response test system and method with increased functionality and improved performance is provided. The error response test system provides the ability to inject errors into the application under test to test the error response of the application under test in an automated and efficient manner. The error response system injects errors into the application through a test mask variable. The test mask variable is added to the application under test. During normal operation, the test mask variable is set to allow the application under test to operate normally. During testing, the error response test system can change the test mask variable to introduce an error into the application under test. The error response system can then monitor the application under test to determine whether the application has the correct response to the error.

Design sensitivity analysis of rotorcraft airframe structures for vibration reduction

NASA Technical Reports Server (NTRS)

Murthy, T. Sreekanta

1987-01-01

Optimization of rotorcraft structures for vibration reduction was studied. The objective of this study is to develop practical computational procedures for structural optimization of airframes subject to steady-state vibration response constraints. One of the key elements of any such computational procedure is design sensitivity analysis. A method for design sensitivity analysis of airframes under vibration response constraints is presented. The mathematical formulation of the method and its implementation as a new solution sequence in MSC/NASTRAN are described. The results of the application of the method to a simple finite element stick model of the AH-1G helicopter airframe are presented and discussed. Selection of design variables that are most likely to bring about changes in the response at specified locations in the airframe is based on consideration of forced response strain energy. Sensitivity coefficients are determined for the selected design variable set. Constraints on the natural frequencies are also included in addition to the constraints on the steady-state response. Sensitivity coefficients for these constraints are determined. Results of the analysis and insights gained in applying the method to the airframe model are discussed. The general nature of future work to be conducted is described.

Bayesian models for cost-effectiveness analysis in the presence of structural zero costs

PubMed Central

Baio, Gianluca

2014-01-01

Bayesian modelling for cost-effectiveness data has received much attention in both the health economics and the statistical literature, in recent years. Cost-effectiveness data are characterised by a relatively complex structure of relationships linking a suitable measure of clinical benefit (e.g. quality-adjusted life years) and the associated costs. Simplifying assumptions, such as (bivariate) normality of the underlying distributions, are usually not granted, particularly for the cost variable, which is characterised by markedly skewed distributions. In addition, individual-level data sets are often characterised by the presence of structural zeros in the cost variable. Hurdle models can be used to account for the presence of excess zeros in a distribution and have been applied in the context of cost data. We extend their application to cost-effectiveness data, defining a full Bayesian specification, which consists of a model for the individual probability of null costs, a marginal model for the costs and a conditional model for the measure of effectiveness (given the observed costs). We presented the model using a working example to describe its main features. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24343868

Bayesian models for cost-effectiveness analysis in the presence of structural zero costs.

PubMed

Baio, Gianluca

2014-05-20

Bayesian modelling for cost-effectiveness data has received much attention in both the health economics and the statistical literature, in recent years. Cost-effectiveness data are characterised by a relatively complex structure of relationships linking a suitable measure of clinical benefit (e.g. quality-adjusted life years) and the associated costs. Simplifying assumptions, such as (bivariate) normality of the underlying distributions, are usually not granted, particularly for the cost variable, which is characterised by markedly skewed distributions. In addition, individual-level data sets are often characterised by the presence of structural zeros in the cost variable. Hurdle models can be used to account for the presence of excess zeros in a distribution and have been applied in the context of cost data. We extend their application to cost-effectiveness data, defining a full Bayesian specification, which consists of a model for the individual probability of null costs, a marginal model for the costs and a conditional model for the measure of effectiveness (given the observed costs). We presented the model using a working example to describe its main features. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

Genetic Moderation of Stress Effects on Corticolimbic Circuitry.

PubMed

Bogdan, Ryan; Pagliaccio, David; Baranger, David Aa; Hariri, Ahmad R

2016-01-01

Stress exposure is associated with individual differences in corticolimbic structure and function that often mirror patterns observed in psychopathology. Gene x environment interaction research suggests that genetic variation moderates the impact of stress on risk for psychopathology. On the basis of these findings, imaging genetics, which attempts to link variability in DNA sequence and structure to neural phenotypes, has begun to incorporate measures of the environment. This research paradigm, known as imaging gene x environment interaction (iGxE), is beginning to contribute to our understanding of the neural mechanisms through which genetic variation and stress increase psychopathology risk. Although awaiting replication, evidence suggests that genetic variation within the canonical neuroendocrine stress hormone system, the hypothalamic-pituitary-adrenal axis, contributes to variability in stress-related corticolimbic structure and function, which, in turn, confers risk for psychopathology. For iGxE research to reach its full potential it will have to address many challenges, of which we discuss: (i) small effects, (ii) measuring the environment and neural phenotypes, (iii) the absence of detailed mechanisms, and (iv) incorporating development. By actively addressing these challenges, iGxE research is poised to help identify the neural mechanisms underlying genetic and environmental associations with psychopathology.

Variable input observer for structural health monitoring of high-rate systems

NASA Astrophysics Data System (ADS)

Hong, Jonathan; Laflamme, Simon; Cao, Liang; Dodson, Jacob

2017-02-01

The development of high-rate structural health monitoring methods is intended to provide damage detection on timescales of 10 µs -10ms where speed of detection is critical to maintain structural integrity. Here, a novel Variable Input Observer (VIO) coupled with an adaptive observer is proposed as a potential solution for complex high-rate problems. The VIO is designed to adapt its input space based on real-time identification of the system's essential dynamics. By selecting appropriate time-delayed coordinates defined by both a time delay and an embedding dimension, the proper input space is chosen which allows more accurate estimations of the current state and a reduction of the convergence rate. The optimal time-delay is estimated based on mutual information, and the embedding dimension is based on false nearest neighbors. A simulation of the VIO is conducted on a two degree-of-freedom system with simulated damage. Results are compared with an adaptive Luenberger observer, a fixed time-delay observer, and a Kalman Filter. Under its preliminary design, the VIO converges significantly faster than the Luenberger and fixed observer. It performed similarly to the Kalman Filter in terms of convergence, but with greater accuracy.

Decreased Cerebellar-Orbitofrontal Connectivity Correlates with Stuttering Severity: Whole-Brain Functional and Structural Connectivity Associations with Persistent Developmental Stuttering.

PubMed

Sitek, Kevin R; Cai, Shanqing; Beal, Deryk S; Perkell, Joseph S; Guenther, Frank H; Ghosh, Satrajit S

2016-01-01

Persistent developmental stuttering is characterized by speech production disfluency and affects 1% of adults. The degree of impairment varies widely across individuals and the neural mechanisms underlying the disorder and this variability remain poorly understood. Here we elucidate compensatory mechanisms related to this variability in impairment using whole-brain functional and white matter connectivity analyses in persistent developmental stuttering. We found that people who stutter had stronger functional connectivity between cerebellum and thalamus than people with fluent speech, while stutterers with the least severe symptoms had greater functional connectivity between left cerebellum and left orbitofrontal cortex (OFC). Additionally, people who stutter had decreased functional and white matter connectivity among the perisylvian auditory, motor, and speech planning regions compared to typical speakers, but greater functional connectivity between the right basal ganglia and bilateral temporal auditory regions. Structurally, disfluency ratings were negatively correlated with white matter connections to left perisylvian regions and to the brain stem. Overall, we found increased connectivity among subcortical and reward network structures in people who stutter compared to controls. These connections were negatively correlated with stuttering severity, suggesting the involvement of cerebellum and OFC may underlie successful compensatory mechanisms by more fluent stutterers.

Effect of BDNF val(66)met polymorphism on declarative memory and its neural substrate: a meta-analysis.

PubMed

Kambeitz, Joseph P; Bhattacharyya, Sagnik; Kambeitz-Ilankovic, Lana M; Valli, Isabel; Collier, David A; McGuire, Philip

2012-10-01

Brain derived neurotrophic factor (BDNF) is a critical component of the molecular mechanism of memory formation. Variation in the BDNF gene, particularly the rs6265 (val(66)met) single nucleotide polymorphism (SNP), has been linked to variability in human memory performance and to both the structure and physiological response of the hippocampus, which plays a central role in memory processing. However, these effects have not been consistently reported, which may reflect the modest size of the samples studied to date. Employing a meta-analytic approach, we examined the effect of the BDNF val(66)met polymorphism on human memory (5922 subjects) and hippocampal structure (2985 subjects) and physiology (362 subjects). Our results suggest that variations in the rs6265 SNP of the BDNF gene have a significant effect on memory performance, and on both the structure and physiology of the hippocampus, with carriers of the met allele being adversely affected. These results underscore the role of BDNF in moderating variability between individuals in human memory performance and in mediating some of the neurocognitive impairments underlying neuropsychiatric disorders. Copyright © 2012 Elsevier Ltd. All rights reserved.

A model for competitiveness level analysis in sports competitions: Application to basketball

NASA Astrophysics Data System (ADS)

de Saá Guerra, Y.; Martín González, J. M.; Sarmiento Montesdeoca, S.; Rodríguez Ruiz, D.; García-Rodríguez, A.; García-Manso, J. M.

2012-05-01

The degree of overall competitiveness of a sport league is a complex phenomenon. It is difficult to assess and quantify all elements that yield the final standing. In this paper, we analyze the general behavior of the result matrices of each season and we use the corresponding results as a probably density. Thus, the results of previous seasons are a way to investigate the probability that each team has to reach a certain number of victories. We developed a model based on Shannon entropy using two extreme competitive structures (a hierarchical structure and a random structure), and applied this model to investigate the competitiveness of two of the best professional basketball leagues: the NBA (USA) and the ACB (Spain). Both leagues’ entropy levels are high (NBA mean 0.983; ACB mean 0.980), indicating high competitiveness, although the entropy of the ACB (from 0.986 to 0.972) demonstrated more seasonal variability than that of the NBA (from 0.985 to 0.990), a possible result of greater sporting gradients in the ACB. The use of this methodology has proven useful for investigating the competitiveness of sports leagues as well as their underlying variability across time.

The Winds of B Supergiants

NASA Technical Reports Server (NTRS)

Massa, Derck; West, D. (Technical Monitor)

2002-01-01

We present the most suitable data sets available in the International Ultraviolet Explorer (IUE) archive for the study of time-dependent stellar winds in early B supergiants. The UV line profile variability in 11 B0 to B3 stars is analyzed, compared and discussed, based on 16 separate data sets comprising over 600 homogeneously reduced high-resolution spectrograms. The targets include 'normal' stars with moderate rotation rates and examples of rapid rotators. A gallery of grey-scale images (dynamic spectra) is presented, which demonstrates the richness and range of wind variability and highlights different structures in the winds of these stars. This work emphasizes the suitability of B supergiants for wind studies, under-pinned by the fact that they exhibit unsaturated wind lines for a wide range of ionization. The wind activity of B supergiants is substantial and has highly varied characteristics. The variability evident in individual stars is classified and described in terms of discrete absorption components, spontaneous absorption, bowed structures, recurrence, and ionization variability and stratification. Similar structures can occur in stars of different fundamental parameters but also different structures may occur in the same star at a given epoch. We discuss the physical phenomena that may be associated with the spectral signatures, and highlight the challenges that these phenomena present to theoretical studies of time-dependent outflows in massive stars. In addition, SEI line-synthesis modelling of the UV wind lines is used to provide further information about the state of the winds in our program stars. Typically the range, implied by the line profile variability, in the product of mass-loss rate and ion fraction (M qi) is a factor of approximately 1.5, when integrated between 0.2 and 0.9 v infinity; it it can however be several times larger over localized velocity regions. At a given effective temperature the mean relative ion ratios can differ by a factor of 5. The general excess in predicted (forward-scattered) emission in the low velocity regime is discussed in turns of structured outflows. Mean ion fractions are estimated over the B0 to B1 spectral classes, and trends in the ionic ratios as a function of wind velocity are described. The low values obtained for the ion fractions of UV resonance lines may reflect the role of clumping in the wind.

A matter of hand: Causal links between hand dominance, structural organization of fronto-parietal attention networks, and variability in behavioural responses to transcranial magnetic stimulation.

PubMed

Cazzoli, Dario; Chechlacz, Magdalena

2017-01-01

Considerable evidence suggests that, on a group level, human visuospatial attention is asymmetrically organized, with a right-hemispheric dominance. The asymmetrical organization of the superior longitudinal fasciculus (SLF) has been shown to account for the right-hemispheric dominance in visual attention. However, such account is by no means universal, and large individual differences in asymmetrical performance on visuospatial tasks have been reported. Furthermore, the variability in the SLF lateralization has been shown to correlate with behavioural asymmetries. Continuous theta burst stimulation (cTBS) enables to temporarily interfere with cortical activity. cTBS applied over the posterior parietal cortex (PPC) has been previously used to systematically study attentional asymmetries. Interestingly, large individual differences in the effectiveness of stimulation have been reported. In accordance with earlier both animal and human studies, one possible cause underlying these striking individual differences might lie in the structural organization of frontoparietal pathways subserving visuospatial attention. Thus, the current study employed diffusion tractography to examine the relationship between the variability in the structural organization of the SLF and the individual differences in attentional shifts induced by a modified cTBS (cTBS mod ; triplets of pulses at 30 Hz, repeated at 6 Hz) applied over the IPS, as measured by a line bisection task. Consistent with previous studies, on a group level, cTBS mod applied over the right intraparietal sulcus (IPS) triggered a rightward bisection bias shift, and there were no significant effects of cTBS mod applied over the left IPS. However, further analyses demonstrated that both handedness and structural variability (as assessed based on hindrance modulated orientational anisotropy) within the middle and the ventral branches of the SLF predicted individual differences in the cTBS mod -induced attentional shifts. Our study thus suggests that the effects of cTBS mod over the IPS may depend on intra-hemispheric interactions between cortical loci controlling visual attention. To conclude, our findings provide converging evidence for the notion put forward previously that inter-individual variability in the structural organization of intra-hemispheric frontoparietal connections has important implications for the functional models of human visual attention. Moreover, we hypothesize that this may also be relevant for the understanding of attentional disorders and their rehabilitation. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Winds of B Supergiants

NASA Technical Reports Server (NTRS)

Massa, D.; Oliversen, R. (Technical Monitor)

2002-01-01

We present the most suitable data sets available in the International Ultraviolet Explorer (IUE) archive for the study of time-dependent stellar winds in early B supergiants. The UV line profile variability in 11 B0 to B3 stars is analyzed, compared and discussed, based on 16 separate data sets comprising over 600 homogeneously reduced high-resolution spectrograms. The targets include 'normal' stars with moderate rotation rates and examples of rapid rotators. A gallery of grey-scale images (dynamic spectra) is presented, which demonstrates the richness and range of wind variability and highlights different structures in the winds of these stars. This work emphasises the suitability of B supergiants for wind studies, under-pinned by the fact that they exhibit unsaturated wind lines for a wide range of ionization. The wind activity of B supergiants is substantial and has highly varied characteristics. The variability evident in individual stars is classified and described in terms of discrete absorption components, spontaneous absorption, bowed structures, recurrence, and ionization variability and stratification. Similar structures can occur in stars of different fundamental parameters, but also different structures may occur in the same star at a given epoch. We discuss the physical phenomena that may be associated with the spectral signatures, and highlight the challenges that these phenomena present to theoretical studies of time-dependent outflows in massive stars. In addition, SEI line-synthesis modelling of the UV wind lines is used to provide further information about the state of the winds in our program stars. Typically the range, implied by the line profile variability, in the product of mass-loss rate and ion fraction (M (dot) q(sub i)) is a factor of approximately 1.5, when integrated between 0.2 and 0.9 v infinity; it can however be several times larger over localized velocity regions. At a given effective temperature the mean relative ion ratios can differ by a factor of 5. The general excess in predicted (forward-scattered) emission in the low velocity regime is discussed in terms of structured outflows. Mean ion fractions are estimated over the B0 to B1 spectral classes, and trends in the ionic ratios as a function of wind velocity are described. The low values obtained for the ion fractions of UV resonance lines may reflect the role of clumping in the wind.

Geometric morphometric analysis of Colombian Anopheles albimanus (Diptera: Culicidae) reveals significant effect of environmental factors on wing traits and presence of a metapopulation

PubMed Central

Gómez, Giovan F.; Márquez, Edna J.; Gutiérrez, Lina A.; Conn, Jan E.; Correa, Margarita M.

2015-01-01

Anopheles albimanus is a major malaria mosquito vector in Colombia. In the present study, wing variability (size and shape) in An. albimanus populations from Colombian Maracaibo and Chocó bio-geographical eco-regions and the relationship of these phenotypic traits with environmental factors were evaluated. Microsatellite and morphometric data facilitated a comparison of the genetic and phenetic structure of this species. Wing size was influenced by elevation and relative humidity, whereas wing shape was affected by these two variables and also by rainfall, latitude, temperature and eco-region. Significant differences in mean shape between populations and eco-regions were detected, but they were smaller than those at the intra-population level. Correct assignment based on wing shape was low at the population level (<58%) and only slightly higher (>70%) at the eco-regional level, supporting the low population structure inferred from microsatellite data. Wing size was similar among populations with no significant differences between eco-regions. Population relationships in the genetic tree did not agree with those from the morphometric data; however, both datasets consistently reinforced a panmictic population of An. albimanus. Overall, site-specific population differentiation is not strongly supported by wing traits or genotypic data. We hypothesize that the metapopulation structure of An. albimanus throughout these Colombian eco-regions is favoring plasticity in wing traits, a relevant characteristic of species living under variable environmental conditions and colonizing new habitats. PMID:24704285

Relationship between mRNA secondary structure and sequence variability in Chloroplast genes: possible life history implications.

PubMed

Krishnan, Neeraja M; Seligmann, Hervé; Rao, Basuthkar J

2008-01-28

Synonymous sites are freer to vary because of redundancy in genetic code. Messenger RNA secondary structure restricts this freedom, as revealed by previous findings in mitochondrial genes that mutations at third codon position nucleotides in helices are more selected against than those in loops. This motivated us to explore the constraints imposed by mRNA secondary structure on evolutionary variability at all codon positions in general, in chloroplast systems. We found that the evolutionary variability and intrinsic secondary structure stability of these sequences share an inverse relationship. Simulations of most likely single nucleotide evolution in Psilotum nudum and Nephroselmis olivacea mRNAs, indicate that helix-forming propensities of mutated mRNAs are greater than those of the natural mRNAs for short sequences and vice-versa for long sequences. Moreover, helix-forming propensity estimated by the percentage of total mRNA in helices increases gradually with mRNA length, saturating beyond 1000 nucleotides. Protection levels of functionally important sites vary across plants and proteins: r-strategists minimize mutation costs in large genes; K-strategists do the opposite. Mrna length presumably predisposes shorter mRNAs to evolve under different constraints than longer mRNAs. The positive correlation between secondary structure protection and functional importance of sites suggests that some sites might be conserved due to packing-protection constraints at the nucleic acid level in addition to protein level constraints. Consequently, nucleic acid secondary structure a priori biases mutations. The converse (exposure of conserved sites) apparently occurs in a smaller number of cases, indicating a different evolutionary adaptive strategy in these plants. The differences between the protection levels of functionally important sites for r- and K-strategists reflect their respective molecular adaptive strategies. These converge with increasing domestication levels of K-strategists, perhaps because domestication increases reproductive output.

The macro-structural variability of the human neocortex.

PubMed

Kruggel, Frithjof

2018-05-15

The human neocortex shows a considerable individual structural variability. While primary gyri and sulci are found in all normally developed brains and bear clear-cut gross structural descriptions, secondary structures are highly variable and not present in all brains. The blend of common and individual structures poses challenges when comparing structural and functional results from quantitative neuroimaging studies across individuals, and sets limits on the precision of location information much above the spatial resolution of current neuroimaging methods. This work aimed at quantifying structural variability on the neocortex, and at assessing the spatial relationship between regions common to all brains and their individual structural variants. Based on structural MRI data provided as the "900 Subjects Release" of the Human Connectome Project, a data-driven analytic approach was employed here from which the definition of seven cortical "communities" emerged. Apparently, these communities comprise common regions of structural features, while the individual variability is confined within a community. Similarities between the community structure and the state of the brain development at gestation week 32 lead suggest that communities are segregated early. Subdividing the neocortex into communities is suggested as anatomically more meaningful than the traditional lobar structure. Copyright © 2018 Elsevier Inc. All rights reserved.

The role of discharge variation in scaling of drainage area and food chain length in rivers

USGS Publications Warehouse

Sabo, John L.; Finlay, Jacques C.; Kennedy, Theodore A.; Post, David M.

2010-01-01

Food chain length (FCL) is a fundamental component of food web structure. Studies in a variety of ecosystems suggest that FCL is determined by energy supply, environmental stability, and/or ecosystem size, but the nature of the relationship between environmental stability and FCL, and the mechanism linking ecosystem size to FCL, remain unclear. Here we show that FCL increases with drainage area and decreases with hydrologic variability and intermittency across 36 North American rivers. Our analysis further suggests that hydrologic variability is the mechanism underlying the correlation between ecosystem size and FCL in rivers. Ecosystem size lengthens river food chains by integrating and attenuating discharge variation through stream networks, thereby enhancing environmental stability in larger river systems.

The role of discharge variation in scaling of drainage area and food chain length in rivers.

PubMed

Sabo, John L; Finlay, Jacques C; Kennedy, Theodore; Post, David M

2010-11-12

Food chain length (FCL) is a fundamental component of food web structure. Studies in a variety of ecosystems suggest that FCL is determined by energy supply, environmental stability, and/or ecosystem size, but the nature of the relationship between environmental stability and FCL, and the mechanism linking ecosystem size to FCL, remain unclear. Here we show that FCL increases with drainage area and decreases with hydrologic variability and intermittency across 36 North American rivers. Our analysis further suggests that hydrologic variability is the mechanism underlying the correlation between ecosystem size and FCL in rivers. Ecosystem size lengthens river food chains by integrating and attenuating discharge variation through stream networks, thereby enhancing environmental stability in larger river systems.

Assessment of sampling stability in ecological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.

1988-01-01

A simulation study was undertaken to assess the sampling stability of the variable loadings in linear discriminant function analysis. A factorial design was used for the factors of multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. A review of 60 published studies and 142 individual analyses indicated that sample sizes in ecological studies often have met that requirement. However, individual group sample sizes frequently were very unequal, and checks of assumptions usually were not reported. The authors recommend that ecologists obtain group sample sizes that are at least three times as large as the number of variables measured.

Diurnal and Seasonal Variability of Uranus' Magnetopause under Different IMF

NASA Astrophysics Data System (ADS)

Cao, X.; Paty, C. S.

2017-12-01

In order to study the asymmetric structure of planetary magnetopause, we propose a quantitative form to measure the asymmetries of the magnetospheric boundaries. First, we use a numerical model to simulate the global magnetosphere of Uranus, which has an extreme dynamically asymmetric magnetosphere due to its large obliquity, its highly tilted and off centered dipole moment when interacting with the solar wind, under different IMF (interplanetary magnetic field) orientations. Based on the results of our model, we use the previous analytical model of planetary magnetopause to fit the magnetopause boundary of Uranus and analyze the characteristics of the magnetopause such as the variation of the flaring parameter and the cusp indentation, which give us an initial intuition of the asymmetric structure of the magnetopause. The result shows the asymmetry of the magnetopause is highly dependent on the seasons and the rotation of Uranus under different IMF orientations. The shape of the magnetopause also affected by the off-centered dipole moment. This study can be applicable for the prediction of the magnetopause boundary detection in future space missions.

Magnetic and Structural Phase Transitions in Thulium under High Pressures and Low Temperatures

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

Vohra, Yogesh K.; Tsoi, Georgiy M.; Samudrala, Gopi K.

2017-10-01

The nature of 4f electrons in many rare earth metals and compounds may be broadly characterized as being either "localized" or "itinerant", and is held responsible for a wide range of physical and chemical properties. The pressure variable has a very dramatic effect on the electronic structure of rare earth metals which in turn drives a sequence of structural and magnetic transitions. We have carried out four-probe electrical resistance measurements on rare earth metal Thulium (Tm) under high pressures to 33 GPa and low temperatures to 10 K to monitor the magnetic ordering transition. These studies are complemented by anglemore » dispersive x-ray diffraction studies to monitor crystallographic phase transitions at high pressures and low temperatures. We observe an abrupt increase in magnetic ordering temperature in Tm at a pressure of 17 GPa on phase transition from ambient pressure hcp-phase to α-Sm phase transition. In addition, measured equation of state (EOS) at low temperatures show anomalously low thermal expansion coefficients likely linked to magnetic transitions.« less

Numerical Flexural Strength Analysis of Thermally Stressed Delaminated Composite Structure under Sinusoidal Loading

NASA Astrophysics Data System (ADS)

Hirwani, C. K.; Biswash, S.; Mehar, K.; Panda, S. K.

2018-03-01

In this article, we investigate the thermomechanical deflection characteristics of the debonded composite plate structure using an isoparametric type of higher-order finite element model. The current formulation is derived using higher-order kinematic theory and the displacement variables described as constant along the thickness direction whereas varying nonlinearly for the in-plane directions. The present mid-plane kinematic model mainly obsoletes the use of shear correction factor as in the other lower-order theories. The separation between the adjacent layers is modeled via the sub-laminate technique and the intermittent continuity conditions imposed to avoid the mathematical ill conditions. The governing equation of equilibrium of the damaged plate structure under the combined state of loading are obtained using the variational principle and solved numerically to compute the deflection values. Further, the convergence test has been performed by refining the numbers of elements and validated through comparing the present results with available published values. The usefulness of the proposed formulation has been discussed by solving the different kind of numerical examples including the size, location and position of delamination.

Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in solid tumors.

PubMed

Lorz, Alexander; Lorenzi, Tommaso; Clairambault, Jean; Escargueil, Alexandre; Perthame, Benoît

2015-01-01

Histopathological evidence supports the idea that the emergence of phenotypic heterogeneity and resistance to cytotoxic drugs can be considered as a process of selection in tumor cell populations. In this framework, can we explain intra-tumor heterogeneity in terms of selection driven by the local cell environment? Can we overcome the emergence of resistance and favor the eradication of cancer cells by using combination therapies? Bearing these questions in mind, we develop a model describing cell dynamics inside a tumor spheroid under the effects of cytotoxic and cytostatic drugs. Cancer cells are assumed to be structured as a population by two real variables standing for space position and the expression level of a phenotype of resistance to cytotoxic drugs. The model takes explicitly into account the dynamics of resources and anticancer drugs as well as their interactions with the cell population under treatment. We analyze the effects of space structure and combination therapies on phenotypic heterogeneity and chemotherapeutic resistance. Furthermore, we study the efficacy of combined therapy protocols based on constant infusion and bang-bang delivery of cytotoxic and cytostatic drugs.

Probing AGN Accretion Physics through AGN Variability: Insights from Kepler

NASA Astrophysics Data System (ADS)

Kasliwal, Vishal Pramod

Active Galactic Nuclei (AGN) exhibit large luminosity variations over the entire electromagnetic spectrum on timescales ranging from hours to years. The variations in luminosity are devoid of any periodic character and appear stochastic. While complex correlations exist between the variability observed in different parts of the electromagnetic spectrum, no frequency band appears to be completely dominant, suggesting that the physical processes producing the variability are exceedingly rich and complex. In the absence of a clear theoretical explanation of the variability, phenomenological models are used to study AGN variability. The stochastic behavior of AGN variability makes formulating such models difficult and connecting them to the underlying physics exceedingly hard. We study AGN light curves serendipitously observed by the NASA Kepler planet-finding mission. Compared to previous ground-based observations, Kepler offers higher precision and a smaller sampling interval resulting in potentially higher quality light curves. Using structure functions, we demonstrate that (1) the simplest statistical model of AGN variability, the damped random walk (DRW), is insufficient to characterize the observed behavior of AGN light curves; and (2) variability begins to occur in AGN on time-scales as short as hours. Of the 20 light curves studied by us, only 3-8 may be consistent with the DRW. The structure functions of the AGN in our sample exhibit complex behavior with pronounced dips on time-scales of 10-100 d suggesting that AGN variability can be very complex and merits further analysis. We examine the accuracy of the Kepler pipeline-generated light curves and find that the publicly available light curves may require re-processing to reduce contamination from field sources. We show that while the re-processing changes the exact PSD power law slopes inferred by us, it is unlikely to change the conclusion of our structure function study-Kepler AGN light curves indicate that the DRW is insufficient to characterize AGN variability. We provide a new approach to probing accretion physics with variability by decomposing observed light curves into a set of impulses that drive diffusive processes using C-ARMA models. Applying our approach to Kepler data, we demonstrate how the time-scales reported in the literature can be interpreted in the context of the growth and decay time-scales for flux perturbations and tentatively identify the flux perturbation driving process with accretion disk turbulence on length-scales much longer than the characteristic eddy size. Our analysis technique is applicable to (1) studying the connection between AGN sub-type and variability properties; (2) probing the origins of variability by studying the multi-wavelength behavior of AGN; (3) testing numerical simulations of accretion flows with the goal of creating a library of the variability properties of different accretion mechanisms; (4) hunting for changes in the behavior of the accretion flow by block-analyzing observed light curves; and (5) constraining the sampling requirements of future surveys of AGN variability.

Linking crop structure, throughfall, soil surface conditions, runoff and soil detachment: 10 land uses analyzed in Northern Laos.

PubMed

Lacombe, Guillaume; Valentin, Christian; Sounyafong, Phabvilay; de Rouw, Anneke; Soulileuth, Bounsamai; Silvera, Norbert; Pierret, Alain; Sengtaheuanghoung, Oloth; Ribolzi, Olivier

2018-03-01

In Montane Southeast Asia, deforestation and unsuitable combinations of crops and agricultural practices degrade soils at an unprecedented rate. Typically, smallholder farmers gain income from "available" land by replacing fallow or secondary forest by perennial crops. We aimed to understand how these practices increase or reduce soil erosion. Ten land uses were monitored in Northern Laos during the 2015 monsoon, using local farmers' fields. Experiments included plots of the conventional system (food crops and fallow), and land uses corresponding to new market opportunities (e.g. commercial tree plantations). Land uses were characterized by measuring plant cover and plant mean height per vegetation layer. Recorded meteorological variables included rainfall intensity, throughfall amount, throughfall kinetic energy (TKE), and raindrop size. Runoff coefficient, soil loss, and the percentage areas of soil surface types (free aggregates and gravel; crusts; macro-faunal, vegetal and pedestal features; plant litter) were derived from observations and measurements in 1-m 2 micro-plots. Relationships between these variables were explored with multiple regression analyses. Our results indicate that TKE induces soil crusting and soil loss. By reducing rainfall infiltration, crusted area enhances runoff, which removes and transports soil particles detached by splash over non-crusted areas. TKE is lower under land uses reducing the velocity of raindrops and/or preventing an increase in their size. Optimal vegetation structures combine minimum height of the lowest layer (to reduce drop velocity at ground level) and maximum coverage (to intercept the largest amount of rainfall), as exemplified by broom grass (Thysanolaena latifolia). In contrast, high canopies with large leaves will increase TKE by enlarging raindrops, as exemplified by teak trees (Tectona grandis), unless a protective understorey exists under the trees. Policies that ban the burning of multi-layered vegetation structure under tree plantations should be enforced. Shade-tolerant shrubs and grasses with potential economic return could be promoted as understorey. Copyright © 2017 Elsevier B.V. All rights reserved.

Advanced Electronic Structures

DTIC Science & Technology

1992-10-01

Physicist Physical Electronics Laboratory SRI Project 2407 D T IC Prepared for: S ELECTEr’ Office of Naval Research DEC 0 81992 800 North Quincy Street...talk at the March 1992 meeting of the American Physical Society. The sub- ject was the use of pressure as a new variable for testing the underlying...on the MIGS model. We intend to submit to Physical Review Letters, and are only waiting for Eike to complete a draft of the ma iuscript. 1 2.1.2

Effective field theory dimensional regularization

NASA Astrophysics Data System (ADS)

Lehmann, Dirk; Prézeau, Gary

2002-01-01

A Lorentz-covariant regularization scheme for effective field theories with an arbitrary number of propagating heavy and light particles is given. This regularization scheme leaves the low-energy analytic structure of Greens functions intact and preserves all the symmetries of the underlying Lagrangian. The power divergences of regularized loop integrals are controlled by the low-energy kinematic variables. Simple diagrammatic rules are derived for the regularization of arbitrary one-loop graphs and the generalization to higher loops is discussed.

System theory as applied differential geometry. [linear system

NASA Technical Reports Server (NTRS)

Hermann, R.

1979-01-01

The invariants of input-output systems under the action of the feedback group was examined. The approach used the theory of Lie groups and concepts of modern differential geometry, and illustrated how the latter provides a basis for the discussion of the analytic structure of systems. Finite dimensional linear systems in a single independent variable are considered. Lessons of more general situations (e.g., distributed parameter and multidimensional systems) which are increasingly encountered as technology advances are presented.

Atmospheric Teleconnection and Climate Variability: Affecting Rice Productivity of Bihar, India

NASA Astrophysics Data System (ADS)

Saini, A.

2017-12-01

Climate variability brought various negative results to the environment around us and area under rice crop in Bihar has also faced a lot of negative impacts due to variability in temperature and rainfall. Location of Bihar in Northern Plain of India automatically makes it prime location for agriculture and therefore variability in climatic variables brings highly sensitive results to the agricultural production (especially rice). In this study, rainfall and temperature variables are taken into consideration to investigate the impact on rice cultivated area. Change in climate variable with the passage of time is prevailing since the start of geological time scale, how the variability in climate variables has affected the major crops. Climate index of Pacific Ocean and Indian Ocean influences the seasonal weather in Bihar and therefore role of ENSO and IOD is an interesting point of inquiry. Does there exists direct relation between climate variability and area under agricultural crops? How many important variables directly signals towards the change in area under agriculture production? These entire questions are answered with respect to change in area under rice cultivation of Bihar State of India. Temperature, rainfall and ENSO are a good indicator with respect to rice cultivation in Indian subcontinent. Impact on the area under rice has been signaled through ONI, Niño3 and DMI. Increasing range of temperature in the rice productivity declining years is observed since 1990.

Scaling Up Decision Theoretic Planning to Planetary Rover Problems

NASA Technical Reports Server (NTRS)

Meuleau, Nicolas; Dearden, Richard; Washington, Rich

2004-01-01

Because of communication limits, planetary rovers must operate autonomously during consequent durations. The ability to plan under uncertainty is one of the main components of autonomy. Previous approaches to planning under uncertainty in NASA applications are not able to address the challenges of future missions, because of several apparent limits. On another side, decision theory provides a solid principle framework for reasoning about uncertainty and rewards. Unfortunately, there are several obstacles to a direct application of decision-theoretic techniques to the rover domain. This paper focuses on the issues of structure and concurrency, and continuous state variables. We describes two techniques currently under development that address specifically these issues and allow scaling-up decision theoretic solution techniques to planetary rover planning problems involving a small number of goals.

Design and analysis of composite structures with stress concentrations

NASA Technical Reports Server (NTRS)

Garbo, S. P.

1983-01-01

An overview of an analytic procedure which can be used to provide comprehensive stress and strength analysis of composite structures with stress concentrations is given. The methodology provides designer/analysts with a user-oriented procedure which, within acceptable engineering accuracy, accounts for the effects of a wide range of application design variables. The procedure permits the strength of arbitrary laminate constructions under general bearing/bypass load conditions to be predicted with only unnotched unidirectional strength and stiffness input data required. Included is a brief discussion of the relevancy of this analysis to the design of primary aircraft structure; an overview of the analytic procedure with theory/test correlations; and an example of the use and interaction of this strength analysis relative to the design of high-load transfer bolted composite joints.

Psychological and behavioral consequences of job loss: a covariance structure analysis using Weiner's (1985) attribution model.

PubMed

Prussia, G E; Kinicki, A J; Bracker, J S

1993-06-01

B. Weiner's (1985) attribution model of achievement motivation and emotion was used as a theoretical foundation to examine the mediating processes between involuntary job loss and employment status. Seventy-nine manufacturing employees were surveyed 1 month prior to permanent displacement, and finding another job was assessed 18 months later. Covariance structure analysis was used to evaluate goodness of fit and to compare the model to alternative measurement and structural representations. Discriminant validity analyses indicated that the causal dimensions underlying the model were not independent. Model predictions were supported in that internal and stable attributions for job loss negatively influenced finding another job through expectations for re-employment. These predictions held up even after controlling for influential unmeasured variables. Practical and theoretical implications are discussed.

Medium-range structure and glass forming ability in Zr–Cu–Al bulk metallic glasses

DOE PAGES

Zhang, Pei; Maldonis, Jason J.; Besser, M. F.; ...

2016-03-05

Fluctuation electron microscopy experiments combined with hybrid reverse Monte Carlo modeling show a correlation between medium-range structure at the nanometer scale and glass forming ability in two Zr–Cu–Al bulk metallic glass (BMG) alloys. Both Zr 50Cu 35Al 15 and Zr 50Cu 45Al 5 exhibit two nanoscale structure types, one icosahedral and the other more crystal-like. In Zr 50Cu 35Al 15, the poorer glass former, the crystal-like structure is more stable under annealing below the glass transition temperature, T g, than in Zr 50Cu 45Al 5. Variable resolution fluctuation microscopy of the MRO clusters show that in Zr 50Cu 35Al 15more » on sub-Tg annealing, the crystal-like clusters shrink even as they grow more ordered, while icosahedral-like clusters grow. Furthermore, the results suggest that achieving better glass forming ability in this alloy system may depend more on destabilizing crystal-like structures than enhancing non-crystalline structures.« less

Temporal variability of soil water repellency in field conditions under humid Mediterranean climate (South of Spain)

NASA Astrophysics Data System (ADS)

Martinez-Murillo, Juan F.; Gabarron-Galeote, Miguel A.; Ruiz-Sinoga, Jose D.

2013-04-01

Soil water repellency (SWR) has become an important field of scientific study because of its effects on soil hydrological behavior, including reduced matrix infiltration, development of fingered flow in structural or textural preferential flow paths, irregular wetting fronts, and increased runoff generation and soil erosion. The aim of this study is to evaluate the temporal variability of SWR in Mediterranean rangeland under humid Mediterranean climatic conditions (Tª=14.5 °C; P=1,010 mm y-1) in South of Spain. Every month from September 2008 to May 2009 (rainy season), soil moisture and SWR was measured in field conditions by means of gravimetric method and Water Drop Penetration Test, respectively. The entire tests were performed in differente eco-geomorphological conditions in the experimental site: North and South aspect hillslopes and beneath shrub and bare soil in every of them. The results indicate that: i) climatic conditions seem to be more transcendent than the vegetal cover for explaining the temporal variability of SWR in field conditions; ii) thus, SWR appears to be controlled by the antecedent rainfall and soil moisture; iii) more severity SWR were observed in patches characterized by sandier soils and/or greater organic matter contents; and iv) the factor 'hillslope aspect' was not found very influential in the degree of SWR.

Attributions of responsibility and recovery within a no-fault insurance compensation system.

PubMed

Thompson, Jason; Berk, Michael; O'Donnell, Meaghan; Stafford, Lesley; Nordfjaern, Trond

2014-08-01

Although a great deal of literature supports the negative relationship between postinjury health outcomes and compensation, it has not fully examined the relative influence of the diverse factors that underlie compensable status. In particular, this study sought to understand the relative influence that attributions of responsibility for accidents have on mental and physical health outcomes. Using a structural equation modeling approach, we assessed the strength of relationships between demographic and accident circumstance variables, and postinjury mental and physical health for 934 road-trauma survivors compensated under a single no-fault insurance system. Analysis of direct and indirect effects demonstrated that although a range of standard demographic and accident circumstance variables influenced health outcomes, by far the greatest effect was generated from perceptions of responsibility for the accident. People who reported lower levels of responsibility for their accident showed significantly poorer mental and physical health outcomes. Perceptions of responsibility for accidents are strongly associated with postaccident mental and physical health outcomes within compensable road trauma populations. Future studies should control for attributions of responsibility when assessing the effect of compensation, or any other variable, on health outcomes among injured populations. Mechanisms underlying the effect of attributions of responsibility on outcomes, particularly in relation to its association with self-blame, warrant further exploration.

Direct evidence that density-dependent regulation underpins the temporal stability of abundant species in a diverse animal community

PubMed Central

Henderson, Peter A.; Magurran, Anne E.

2014-01-01

To understand how ecosystems are structured and stabilized, and to identify when communities are at risk of damage or collapse, we need to know how the abundances of the taxa in the entire assemblage vary over ecologically meaningful timescales. Here, we present an analysis of species temporal variability within a single large vertebrate community. Using an exceptionally complete 33-year monthly time series following the dynamics of 81 species of fishes, we show that the most abundant species are least variable in terms of temporal biomass, because they are under density-dependent (negative feedback) regulation. At the other extreme, a relatively large number of low abundance transient species exhibit the greatest population variability. The high stability of the consistently common high abundance species—a result of density-dependence—is reflected in the observation that they consistently represent over 98% of total fish biomass. This leads to steady ecosystem nutrient and energy flux irrespective of the changes in species number and abundance among the large number of low abundance transient species. While the density-dependence of the core species ensures stability under the existing environmental regime, the pool of transient species may support long-term stability by replacing core species should environmental conditions change. PMID:25100702

Patterns of variations in large pelagic fish: A comparative approach between the Indian and the Atlantic Oceans

NASA Astrophysics Data System (ADS)

Corbineau, A.; Rouyer, T.; Fromentin, J.-M.; Cazelles, B.; Fonteneau, A.; Ménard, F.

2010-07-01

Catch data of large pelagic fish such as tuna, swordfish and billfish are highly variable ranging from short to long term. Based on fisheries data, these time series are noisy and reflect mixed information on exploitation (targeting, strategy, fishing power), population dynamics (recruitment, growth, mortality, migration, etc.), and environmental forcing (local conditions or dominant climate patterns). In this work, we investigated patterns of variation of large pelagic fish (i.e. yellowfin tuna, bigeye tuna, swordfish and blue marlin) in Japanese longliners catch data from 1960 to 2004. We performed wavelet analyses on the yearly time series of each fish species in each biogeographic province of the tropical Indian and Atlantic Oceans. In addition, we carried out cross-wavelet analyses between these biological time series and a large-scale climatic index, i.e. the Southern Oscillation Index (SOI). Results showed that the biogeographic province was the most important factor structuring the patterns of variability of Japanese catch time series. Relationships between the SOI and the fish catches in the Indian and Atlantic Oceans also pointed out the role of climatic variability for structuring patterns of variation of catch time series. This work finally confirmed that Japanese longline CPUE data poorly reflect the underlying population dynamics of tunas.

Latent Variable Modeling of Brain Gray Matter Volume and Psychopathy in Incarcerated Offenders

PubMed Central

Baskin-Sommers, Arielle R.; Neumann, Craig S.; Cope, Lora M.; Kiehl, Kent A.

2016-01-01

Advanced statistical modeling has become a prominent feature in psychological science and can be a useful approach for representing the neural architecture linked to psychopathology. Psychopathy, a disorder characterized by dysfunction in interpersonal-affective and impulsive-antisocial domains, is associated with widespread neural abnormalities. Several imaging studies suggest that underlying structural deficits in paralimbic regions are associated with psychopathy. While these studies are useful, they make assumptions about the organization of the brain and its relevance to individuals displaying psychopathic features. Capitalizing on statistical modeling, the present study (N=254) used latent variable methods to examine the structure of gray matter volume in male offenders, and assessed the latent relations between psychopathy and gray matter factors reflecting paralimbic and non-paralimbic regions. Results revealed good fit for a four-factor gray matter paralimbic model and these first-order factors were accounted for by a super-ordinate paralimbic ‘system’ factor. Moreover, a super-ordinate psychopathy factor significantly predicted the paralimbic, but not the non-paralimbic factor. The latent variable paralimbic model, specifically linked with psychopathy, goes beyond understanding of single brain regions within the system and provides evidence for psychopathy-related gray matter volume reductions in the paralimbic system as a whole. PMID:27269123

Variable-Structure Control of a Model Glider Airplane

NASA Technical Reports Server (NTRS)

Waszak, Martin R.; Anderson, Mark R.

2008-01-01

A variable-structure control system designed to enable a fuselage-heavy airplane to recover from spin has been demonstrated in a hand-launched, instrumented model glider airplane. Variable-structure control is a high-speed switching feedback control technique that has been developed for control of nonlinear dynamic systems.

Mapping the structure of perceptual and visual-motor abilities in healthy young adults.

PubMed

Wang, Lingling; Krasich, Kristina; Bel-Bahar, Tarik; Hughes, Lauren; Mitroff, Stephen R; Appelbaum, L Gregory

2015-05-01

The ability to quickly detect and respond to visual stimuli in the environment is critical to many human activities. While such perceptual and visual-motor skills are important in a myriad of contexts, considerable variability exists between individuals in these abilities. To better understand the sources of this variability, we assessed perceptual and visual-motor skills in a large sample of 230 healthy individuals via the Nike SPARQ Sensory Station, and compared variability in their behavioral performance to demographic, state, sleep and consumption characteristics. Dimension reduction and regression analyses indicated three underlying factors: Visual-Motor Control, Visual Sensitivity, and Eye Quickness, which accounted for roughly half of the overall population variance in performance on this battery. Inter-individual variability in Visual-Motor Control was correlated with gender and circadian patters such that performance on this factor was better for males and for those who had been awake for a longer period of time before assessment. The current findings indicate that abilities involving coordinated hand movements in response to stimuli are subject to greater individual variability, while visual sensitivity and occulomotor control are largely stable across individuals. Copyright © 2015 Elsevier B.V. All rights reserved.

Multidisciplinary optimization of a controlled space structure using 150 design variables

NASA Technical Reports Server (NTRS)

James, Benjamin B.

1993-01-01

A controls-structures interaction design method is presented. The method coordinates standard finite-element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structure and control system of a spacecraft. Global sensitivity equations are used to account for coupling between the disciplines. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Design problems using 15, 63, and 150 design variables to optimize truss member sizes and feedback gain values are solved and the results are presented. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporation of the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables.

Determination of ensemble-average pairwise root mean-square deviation from experimental B-factors.

PubMed

Kuzmanic, Antonija; Zagrovic, Bojan

2010-03-03

Root mean-square deviation (RMSD) after roto-translational least-squares fitting is a measure of global structural similarity of macromolecules used commonly. On the other hand, experimental x-ray B-factors are used frequently to study local structural heterogeneity and dynamics in macromolecules by providing direct information about root mean-square fluctuations (RMSF) that can also be calculated from molecular dynamics simulations. We provide a mathematical derivation showing that, given a set of conservative assumptions, a root mean-square ensemble-average of an all-against-all distribution of pairwise RMSD for a single molecular species, (1/2), is directly related to average B-factors () and (1/2). We show this relationship and explore its limits of validity on a heterogeneous ensemble of structures taken from molecular dynamics simulations of villin headpiece generated using distributed-computing techniques and the Folding@Home cluster. Our results provide a basis for quantifying global structural diversity of macromolecules in crystals directly from x-ray experiments, and we show this on a large set of structures taken from the Protein Data Bank. In particular, we show that the ensemble-average pairwise backbone RMSD for a microscopic ensemble underlying a typical protein x-ray structure is approximately 1.1 A, under the assumption that the principal contribution to experimental B-factors is conformational variability. 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.