Input variable selection for interpolating high-resolution climate ...

African Journals Online (AJOL)

Although the primary input data of climate interpolations are usually meteorological data, other related (independent) variables are frequently incorporated in the interpolation process. One such variable is elevation, which is known to have a strong influence on climate. This research investigates the potential of 4 additional ...

Speaker Input Variability Does Not Explain Why Larger Populations Have Simpler Languages.

Science.gov (United States)

Atkinson, Mark; Kirby, Simon; Smith, Kenny

2015-01-01

A learner's linguistic input is more variable if it comes from a greater number of speakers. Higher speaker input variability has been shown to facilitate the acquisition of phonemic boundaries, since data drawn from multiple speakers provides more information about the distribution of phonemes in a speech community. It has also been proposed that speaker input variability may have a systematic influence on individual-level learning of morphology, which can in turn influence the group-level characteristics of a language. Languages spoken by larger groups of people have less complex morphology than those spoken in smaller communities. While a mechanism by which the number of speakers could have such an effect is yet to be convincingly identified, differences in speaker input variability, which is thought to be larger in larger groups, may provide an explanation. By hindering the acquisition, and hence faithful cross-generational transfer, of complex morphology, higher speaker input variability may result in structural simplification. We assess this claim in two experiments which investigate the effect of such variability on language learning, considering its influence on a learner's ability to segment a continuous speech stream and acquire a morphologically complex miniature language. We ultimately find no evidence to support the proposal that speaker input variability influences language learning and so cannot support the hypothesis that it explains how population size determines the structural properties of language.

Response of spiking neurons to correlated inputs

International Nuclear Information System (INIS)

Moreno, Ruben; Rocha, Jaime de la; Renart, Alfonso; Parga, Nestor

2002-01-01

The effect of a temporally correlated afferent current on the firing rate of a leaky integrate-and-fire neuron is studied. This current is characterized in terms of rates, autocorrelations, and cross correlations, and correlation time scale τ c of excitatory and inhibitory inputs. The output rate ν out is calculated in the Fokker-Planck formalism in the limit of both small and large τ c compared to the membrane time constant τ of the neuron. By simulations we check the analytical results, provide an interpolation valid for all τ c , and study the neuron's response to rapid changes in the correlation magnitude

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

International Nuclear Information System (INIS)

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

2017-01-01

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. (paper)

Generating Correlated QPSK Waveforms By Exploiting Real Gaussian Random Variables

KAUST Repository

Jardak, Seifallah

2012-11-01

The design of waveforms with specified auto- and cross-correlation properties has a number of applications in multiple-input multiple-output (MIMO) radar, one of them is the desired transmit beampattern design. In this work, an algorithm is proposed to generate quadrature phase shift- keying (QPSK) waveforms with required cross-correlation properties using real Gaussian random-variables (RV’s). This work can be considered as the extension of what was presented in [1] to generate BPSK waveforms. This work will be extended for the generation of correlated higher-order phase shift-keying (PSK) and quadrature amplitude modulation (QAM) schemes that can better approximate the desired beampattern.

Generating Correlated QPSK Waveforms By Exploiting Real Gaussian Random Variables

KAUST Repository

Jardak, Seifallah; Ahmed, Sajid; Alouini, Mohamed-Slim

2012-01-01

The design of waveforms with specified auto- and cross-correlation properties has a number of applications in multiple-input multiple-output (MIMO) radar, one of them is the desired transmit beampattern design. In this work, an algorithm is proposed to generate quadrature phase shift- keying (QPSK) waveforms with required cross-correlation properties using real Gaussian random-variables (RV’s). This work can be considered as the extension of what was presented in [1] to generate BPSK waveforms. This work will be extended for the generation of correlated higher-order phase shift-keying (PSK) and quadrature amplitude modulation (QAM) schemes that can better approximate the desired beampattern.

Statistical screening of input variables in a complex computer code

International Nuclear Information System (INIS)

Krieger, T.J.

1982-01-01

A method is presented for ''statistical screening'' of input variables in a complex computer code. The object is to determine the ''effective'' or important input variables by estimating the relative magnitudes of their associated sensitivity coefficients. This is accomplished by performing a numerical experiment consisting of a relatively small number of computer runs with the code followed by a statistical analysis of the results. A formula for estimating the sensitivity coefficients is derived. Reference is made to an earlier work in which the method was applied to a complex reactor code with good results

Generation of correlated finite alphabet waveforms using gaussian random variables

KAUST Repository

Ahmed, Sajid

2016-01-13

Various examples of methods and systems are provided for generation of correlated finite alphabet waveforms using Gaussian random variables in, e.g., radar and communication applications. In one example, a method includes mapping an input signal comprising Gaussian random variables (RVs) onto finite-alphabet non-constant-envelope (FANCE) symbols using a predetermined mapping function, and transmitting FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The FANCE waveforms can be based upon the mapping of the Gaussian RVs onto the FANCE symbols. In another example, a system includes a memory unit that can store a plurality of digital bit streams corresponding to FANCE symbols and a front end unit that can transmit FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The system can include a processing unit that can encode the input signal and/or determine the mapping function.

Generation of correlated finite alphabet waveforms using gaussian random variables

KAUST Repository

Ahmed, Sajid; Alouini, Mohamed-Slim; Jardak, Seifallah

2016-01-01

Various examples of methods and systems are provided for generation of correlated finite alphabet waveforms using Gaussian random variables in, e.g., radar and communication applications. In one example, a method includes mapping an input signal comprising Gaussian random variables (RVs) onto finite-alphabet non-constant-envelope (FANCE) symbols using a predetermined mapping function, and transmitting FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The FANCE waveforms can be based upon the mapping of the Gaussian RVs onto the FANCE symbols. In another example, a system includes a memory unit that can store a plurality of digital bit streams corresponding to FANCE symbols and a front end unit that can transmit FANCE waveforms through a uniform linear array of antenna elements to obtain a corresponding beampattern. The system can include a processing unit that can encode the input signal and/or determine the mapping function.

Segmented correlation measurements on superconducting bandpass delta-sigma modulator with and without input tone

International Nuclear Information System (INIS)

Bulzacchelli, John F; Lee, Hae-Seung; Hong, Merit Y; Misewich, James A; Ketchen, Mark B

2003-01-01

Segmented correlation is a useful technique for testing a superconducting analogue-to-digital converter, as it allows the output spectrum to be estimated with fine frequency resolution even when data record lengths are limited by small on-chip acquisition memories. Previously, we presented segmented correlation measurements on a superconducting bandpass delta-sigma modulator sampling at 40.2 GHz under idle channel (no input) conditions. This paper compares the modulator output spectra measured by segmented correlation with and without an input tone. Important practical considerations of calculating segmented correlations are discussed in detail. Resolution enhancement by segmented correlation does reduce the spectral width of the input tone in the desired manner, but the signal power due to the input increases the variance of the spectral estimate near the input frequency, hindering accurate calculation of the in-band noise. This increased variance, which is predicted by theory, must be considered carefully in the application of segmented correlation. Methods for obtaining more accurate estimates of the quantization noise spectrum which are closer to those measured with no input are described

Input Variability Facilitates Unguided Subcategory Learning in Adults

Science.gov (United States)

Eidsvåg, Sunniva Sørhus; Austad, Margit; Plante, Elena; Asbjørnsen, Arve E.

2015-01-01

Purpose: This experiment investigated whether input variability would affect initial learning of noun gender subcategories in an unfamiliar, natural language (Russian), as it is known to assist learning of other grammatical forms. Method: Forty adults (20 men, 20 women) were familiarized with examples of masculine and feminine Russian words. Half…

Attributing uncertainty in streamflow simulations due to variable inputs via the Quantile Flow Deviation metric

Science.gov (United States)

Shoaib, Syed Abu; Marshall, Lucy; Sharma, Ashish

2018-06-01

Every model to characterise a real world process is affected by uncertainty. Selecting a suitable model is a vital aspect of engineering planning and design. Observation or input errors make the prediction of modelled responses more uncertain. By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications. The Quantile Flow Deviation (QFD) metric is used to assess these alternate sources of uncertainty. The Australian Water Availability Project (AWAP) precipitation data for four different Australian catchments is used to analyse the impact of spatial rainfall variability on simulated streamflow variability via the QFD. The QFD metric attributes the variability in flow ensembles to uncertainty associated with the selection of a model structure and input time series. For the case study catchments, the relative contribution of input uncertainty due to rainfall is higher than that due to potential evapotranspiration, and overall input uncertainty is significant compared to model structure and parameter uncertainty. Overall, this study investigates the propagation of input uncertainty in a daily streamflow modelling scenario and demonstrates how input errors manifest across different streamflow magnitudes.

Generation of correlated finite alphabet waveforms using gaussian random variables

KAUST Repository

Jardak, Seifallah

2014-09-01

Correlated waveforms have a number of applications in different fields, such as radar and communication. It is very easy to generate correlated waveforms using infinite alphabets, but for some of the applications, it is very challenging to use them in practice. Moreover, to generate infinite alphabet constant envelope correlated waveforms, the available research uses iterative algorithms, which are computationally very expensive. In this work, we propose simple novel methods to generate correlated waveforms using finite alphabet constant and non-constant-envelope symbols. To generate finite alphabet waveforms, the proposed method map the Gaussian random variables onto the phase-shift-keying, pulse-amplitude, and quadrature-amplitude modulation schemes. For such mapping, the probability-density-function of Gaussian random variables is divided into M regions, where M is the number of alphabets in the corresponding modulation scheme. By exploiting the mapping function, the relationship between the cross-correlation of Gaussian and finite alphabet symbols is derived. To generate equiprobable symbols, the area of each region is kept same. If the requirement is to have each symbol with its own unique probability, the proposed scheme allows us that as well. Although, the proposed scheme is general, the main focus of this paper is to generate finite alphabet waveforms for multiple-input multiple-output radar, where correlated waveforms are used to achieve desired beampatterns. © 2014 IEEE.

Perils of correlating CUSUM-transformed variables to infer ecological relationships (Breton et al. 2006; Glibert 2010)

Science.gov (United States)

Cloern, James E.; Jassby, Alan D.; Carstensen, Jacob; Bennett, William A.; Kimmerer, Wim; Mac Nally, Ralph; Schoellhamer, David H.; Winder, Monika

2012-01-01

We comment on a nonstandard statistical treatment of time-series data first published by Breton et al. (2006) in Limnology and Oceanography and, more recently, used by Glibert (2010) in Reviews in Fisheries Science. In both papers, the authors make strong inferences about the underlying causes of population variability based on correlations between cumulative sum (CUSUM) transformations of organism abundances and environmental variables. Breton et al. (2006) reported correlations between CUSUM-transformed values of diatom biomass in Belgian coastal waters and the North Atlantic Oscillation, and between meteorological and hydrological variables. Each correlation of CUSUM-transformed variables was judged to be statistically significant. On the basis of these correlations, Breton et al. (2006) developed "the first evidence of synergy between climate and human-induced river-based nitrate inputs with respect to their effects on the magnitude of spring Phaeocystis colony blooms and their dominance over diatoms."

Harmonize input selection for sediment transport prediction

Science.gov (United States)

Afan, Haitham Abdulmohsin; Keshtegar, Behrooz; Mohtar, Wan Hanna Melini Wan; El-Shafie, Ahmed

2017-09-01

In this paper, three modeling approaches using a Neural Network (NN), Response Surface Method (RSM) and response surface method basis Global Harmony Search (GHS) are applied to predict the daily time series suspended sediment load. Generally, the input variables for forecasting the suspended sediment load are manually selected based on the maximum correlations of input variables in the modeling approaches based on NN and RSM. The RSM is improved to select the input variables by using the errors terms of training data based on the GHS, namely as response surface method and global harmony search (RSM-GHS) modeling method. The second-order polynomial function with cross terms is applied to calibrate the time series suspended sediment load with three, four and five input variables in the proposed RSM-GHS. The linear, square and cross corrections of twenty input variables of antecedent values of suspended sediment load and water discharge are investigated to achieve the best predictions of the RSM based on the GHS method. The performances of the NN, RSM and proposed RSM-GHS including both accuracy and simplicity are compared through several comparative predicted and error statistics. The results illustrated that the proposed RSM-GHS is as uncomplicated as the RSM but performed better, where fewer errors and better correlation was observed (R = 0.95, MAE = 18.09 (ton/day), RMSE = 25.16 (ton/day)) compared to the ANN (R = 0.91, MAE = 20.17 (ton/day), RMSE = 33.09 (ton/day)) and RSM (R = 0.91, MAE = 20.06 (ton/day), RMSE = 31.92 (ton/day)) for all types of input variables.

Synaptic input correlations leading to membrane potential decorrelation of spontaneous activity in cortex.

Science.gov (United States)

Graupner, Michael; Reyes, Alex D

2013-09-18

Correlations in the spiking activity of neurons have been found in many regions of the cortex under multiple experimental conditions and are postulated to have important consequences for neural population coding. While there is a large body of extracellular data reporting correlations of various strengths, the subthreshold events underlying the origin and magnitude of signal-independent correlations (called noise or spike count correlations) are unknown. Here we investigate, using intracellular recordings, how synaptic input correlations from shared presynaptic neurons translate into membrane potential and spike-output correlations. Using a pharmacologically activated thalamocortical slice preparation, we perform simultaneous recordings from pairs of layer IV neurons in the auditory cortex of mice and measure synaptic potentials/currents, membrane potentials, and spiking outputs. We calculate cross-correlations between excitatory and inhibitory inputs to investigate correlations emerging from the network. We furthermore evaluate membrane potential correlations near resting potential to study how excitation and inhibition combine and affect spike-output correlations. We demonstrate directly that excitation is correlated with inhibition thereby partially canceling each other and resulting in weak membrane potential and spiking correlations between neurons. Our data suggest that cortical networks are set up to partially cancel correlations emerging from the connections between neurons. This active decorrelation is achieved because excitation and inhibition closely track each other. Our results suggest that the numerous shared presynaptic inputs do not automatically lead to increased spiking correlations.

Study of input variables in group method of data handling methodology

International Nuclear Information System (INIS)

Pereira, Iraci Martinez; Bueno, Elaine Inacio

2013-01-01

The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a pre-selected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and ANN methodologies, and applied to the IPEN research Reactor IEA-1. The system performs the monitoring by comparing the GMDH and ANN calculated values with measured ones. As the GMDH is a self-organizing methodology, the input variables choice is made automatically. On the other hand, the results of ANN methodology are strongly dependent on which variables are used as neural network input. (author)

Variable Selection via Partial Correlation.

Science.gov (United States)

Li, Runze; Liu, Jingyuan; Lou, Lejia

2017-07-01

Partial correlation based variable selection method was proposed for normal linear regression models by Bühlmann, Kalisch and Maathuis (2010) as a comparable alternative method to regularization methods for variable selection. This paper addresses two important issues related to partial correlation based variable selection method: (a) whether this method is sensitive to normality assumption, and (b) whether this method is valid when the dimension of predictor increases in an exponential rate of the sample size. To address issue (a), we systematically study this method for elliptical linear regression models. Our finding indicates that the original proposal may lead to inferior performance when the marginal kurtosis of predictor is not close to that of normal distribution. Our simulation results further confirm this finding. To ensure the superior performance of partial correlation based variable selection procedure, we propose a thresholded partial correlation (TPC) approach to select significant variables in linear regression models. We establish the selection consistency of the TPC in the presence of ultrahigh dimensional predictors. Since the TPC procedure includes the original proposal as a special case, our theoretical results address the issue (b) directly. As a by-product, the sure screening property of the first step of TPC was obtained. The numerical examples also illustrate that the TPC is competitively comparable to the commonly-used regularization methods for variable selection.

Recurrent network models for perfect temporal integration of fluctuating correlated inputs.

Directory of Open Access Journals (Sweden)

Hiroshi Okamoto

2009-06-01

Full Text Available Temporal integration of input is essential to the accumulation of information in various cognitive and behavioral processes, and gradually increasing neuronal activity, typically occurring within a range of seconds, is considered to reflect such computation by the brain. Some psychological evidence suggests that temporal integration by the brain is nearly perfect, that is, the integration is non-leaky, and the output of a neural integrator is accurately proportional to the strength of input. Neural mechanisms of perfect temporal integration, however, remain largely unknown. Here, we propose a recurrent network model of cortical neurons that perfectly integrates partially correlated, irregular input spike trains. We demonstrate that the rate of this temporal integration changes proportionately to the probability of spike coincidences in synaptic inputs. We analytically prove that this highly accurate integration of synaptic inputs emerges from integration of the variance of the fluctuating synaptic inputs, when their mean component is kept constant. Highly irregular neuronal firing and spike coincidences are the major features of cortical activity, but they have been separately addressed so far. Our results suggest that the efficient protocol of information integration by cortical networks essentially requires both features and hence is heterotic.

Construction of an input sensitivity variable CAMAC module for measuring DC voltage

International Nuclear Information System (INIS)

Noda, Nobuaki.

1979-03-01

In on-line experimental data processing systems, the collection of DC voltage data is frequently required. In plasma confinement experiments, for example, the range of input voltage is very wide from over 1 kV applied to photomultiplier tubes to 10 mV full scale of the controller output for ionization vacuum gauges. A DC voltmeter CAMAC module with variable input range, convenient for plasma experiments and inexpensive, has been constructed for trial. The number of input channels is 16, and the input range is changeable in six steps from +-10 mV to +-200 V; these are all set by commands from a computer. The module is actually used for the on-line data processing system for JIPP T-2 experiment. The ideas behind its development, and the functions, features and usage of the module are described in this report. (J.P.N.)

Wide Input Range Power Converters Using a Variable Turns Ratio Transformer

DEFF Research Database (Denmark)

Ouyang, Ziwei; Andersen, Michael A. E.

2016-01-01

A new integrated transformer with variable turns ratio is proposed to enable dc-dc converters operating over a wide input voltage range. The integrated transformer employs a new geometry of magnetic core with “four legs”, two primary windings with orthogonal arrangement, and “8” shape connection...... of diagonal secondary windings, in order to make the transformer turns ratio adjustable by controlling the phase between the two current excitations subjected to the two primary windings. Full-bridge boost dc-dc converter is employed with the proposed transformer to demonstrate the feasibility of the variable...

Energy Inputs Uncertainty: Total Amount, Distribution and Correlation Between Different Forms of Energy

Science.gov (United States)

Deng, Yue

2014-01-01

Describes solar energy inputs contributing to ionospheric and thermospheric weather processes, including total energy amounts, distributions and the correlation between particle precipitation and Poynting flux.

Remote Sensing Analysis of Malawi's Agricultural Inputs Subsidy and Climate Variability Impacts on Productivity

Science.gov (United States)

Galford, G. L.; Fiske, G. J.; Sedano, F.; Michelson, H.

2016-12-01

Agriculture in sub-Saharan Africa is characterized by smallholder production and low yields ( 1 ton ha-1 year-1 since records began in 1961) for staple food crops such as maize (Zea mays). Many years of low-input farming have depleted much of the region's agricultural land of critical soil carbon and nitrogen, further reducing yield potentials. Malawi is a 98,000 km2 subtropical nation with a short rainy season from November to May, with most rainfall occurring between December and mid-April. This short growing season supports the cultivation of one primary crop, maize. In Malawi, many smallholder farmers face annual nutrient deficits as nutrients removed as grain harvest and residues are beyond replenishment levels. As a result, Malawi has had stagnant maize yields averaging 1.2 ton ha-1 year-1 for decades. After multiple years of drought and widespread hunger in the early 2000s, Malawi introduced an agricultural input support program (fertilizer and seed subsidy) in time for the 2006 harvest that was designed to restore soil nutrients, improve maize production, and decrease dependence on food aid. Malawi's subsidy program targets 50-67% of smallholder farmers who cultivate half a hectare or less, yet collectively supply 80% of the country's maize. The country has achieved significant increases in crop yields (now 2 tons/ha/year) and, as our analysis shows, benefited from a new resilience against drought. We utilized Landsat time series to determine cropland extent from 2000-present and identify areas of marginal and/or intermittent production. We found a strong latitudinal gradient of precipitation variability from north to south in CHIRPS data. We used the precipitation variability to normalize trends in a productivity proxy derived from MODIS EVI. After normalization of productivity to precipitation variability, we found significant productivity trends correlated to subsidy distribution. This work was conducted with Google's Earth Engine, a cloud-based platform

PCC/SRC, PCC and SRC Calculation from Multivariate Input for Sensitivity Analysis

International Nuclear Information System (INIS)

Iman, R.L.; Shortencarier, M.J.; Johnson, J.D.

1995-01-01

1 - Description of program or function: PCC/SRC is designed for use in conjunction with sensitivity analyses of complex computer models. PCC/SRC calculates the partial correlation coefficients (PCC) and the standardized regression coefficients (SRC) from the multivariate input to, and output from, a computer model. 2 - Method of solution: PCC/SRC calculates the coefficients on either the original observations or on the ranks of the original observations. These coefficients provide alternative measures of the relative contribution (importance) of each of the various input variables to the observed variations in output. Relationships between the coefficients and differences in their interpretations are identified. If the computer model output has an associated time or spatial history, PCC/SRC will generate a graph of the coefficients over time or space for each input-variable, output- variable combination of interest, indicating the importance of each input value over time or space. 3 - Restrictions on the complexity of the problem - Maxima of: 100 observations, 100 different time steps or intervals between successive dependent variable readings, 50 independent variables (model input), 20 dependent variables (model output). 10 ordered triples specifying intervals between dependent variable readings

Correlated Temporal and Spectral Variability

Science.gov (United States)

Swank, Jean H.

2007-01-01

The variability of neutron star and black hole X-ray sources has several dimensions, because of the roles played by different important time-scales. The variations on time scales of hours, weeks, and months, ranging from 50% to orders of magnitude, arise out of changes in the flow in the disk. The most important driving forces for those changes are probably various possible instabilities in the disk, though there may be effects with other dominant causes. The changes in the rate of flow appear to be associated with changes in the flow's configuration, as the accreting material approaches the compact object, for there are generally correlated changes in both the Xray spectra and the character of the faster temporal variability. There has been a lot of progress in tracking these correlations, both for Z and Atoll neutron star low-mass X-ray binaries, and for black hole binaries. I will discuss these correlations and review briefly what they tell us about the physical states of the systems.

Wavelet Correlation Coefficient of 'strongly correlated' financial time series

OpenAIRE

Razdan, Ashok

2003-01-01

In this paper we use wavelet concepts to show that correlation coefficient between two financial data's is not constant but varies with scale from high correlation value to strongly anti-correlation value This studies is important because correlation coefficient is used to quantify degree of independence between two variables. In econophysics correlation coefficient forms important input to evolve hierarchial tree and minimum spanning tree of financial data.

Wood phenology, not carbon input, controls the interannual variability of wood growth in a temperate oak forest.

Science.gov (United States)

Delpierre, Nicolas; Berveiller, Daniel; Granda, Elena; Dufrêne, Eric

2016-04-01

Although the analysis of flux data has increased our understanding of the interannual variability of carbon inputs into forest ecosystems, we still know little about the determinants of wood growth. Here, we aimed to identify which drivers control the interannual variability of wood growth in a mesic temperate deciduous forest. We analysed a 9-yr time series of carbon fluxes and aboveground wood growth (AWG), reconstructed at a weekly time-scale through the combination of dendrometer and wood density data. Carbon inputs and AWG anomalies appeared to be uncorrelated from the seasonal to interannual scales. More than 90% of the interannual variability of AWG was explained by a combination of the growth intensity during a first 'critical period' of the wood growing season, occurring close to the seasonal maximum, and the timing of the first summer growth halt. Both atmospheric and soil water stress exerted a strong control on the interannual variability of AWG at the study site, despite its mesic conditions, whilst not affecting carbon inputs. Carbon sink activity, not carbon inputs, determined the interannual variations in wood growth at the study site. Our results provide a functional understanding of the dependence of radial growth on precipitation observed in dendrological studies. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Correlations between Optical Variability and Physical Parameters of ...

Indian Academy of Sciences (India)

ever, the predicted positive correlation between variability and black hole mass seems to be ... Introduction. Variability is one of the .... Accompanied by the slope b_X and y-axis intercept value a_X, the Pearson product- moment correlation ...

Graphical user interface for input output characterization of single variable and multivariable highly nonlinear systems

Directory of Open Access Journals (Sweden)

Shahrukh Adnan Khan M. D.

2017-01-01

Full Text Available This paper presents a Graphical User Interface (GUI software utility for the input/output characterization of single variable and multivariable nonlinear systems by obtaining the sinusoidal input describing function (SIDF of the plant. The software utility is developed on MATLAB R2011a environment. The developed GUI holds no restriction on the nonlinearity type, arrangement and system order; provided that output(s of the system is obtainable either though simulation or experiments. An insight to the GUI and its features are presented in this paper and example problems from both single variable and multivariable cases are demonstrated. The formulation of input/output behavior of the system is discussed and the nucleus of the MATLAB command underlying the user interface has been outlined. Some of the industries that would benefit from this software utility includes but not limited to aerospace, defense technology, robotics and automotive.

Determination of Correlation for Extreme Metocean Variables

Directory of Open Access Journals (Sweden)

Nizamani Zafarullah

2017-01-01

Full Text Available Metocean environmental load includes wind, wave and currents. Offshore structures are designed for two environmental load design conditions i.e. extreme and operational load conditions of environmental loads are evaluated. The ccorrelation between load variables using Joint probability distribution, Pearson correlation coefficient and Spearman’s rank correlation coefficients methods in Peninsular Malaysia (PM, Sabah and Sarawak are computed. Joint probability distribution method is considered as a reliable method among three different methods to determine the relationship between load variables. The PM has good correlation between the wind-wave and wave-current; Sabah has both strong relationships of wind-wave and wind-current with 50 year return period; Sarawak has good correlation between wind and current in both 50 years and 100 years return period. Since Sabah has good correlation between the associated load variables, no matter in 50 years or 100 years of return period of load combination. Thus, method 1 of ISO 19901-1, specimen provides guideline for metocean loading conditions, can be adopted for design for offshore structure in Sabah. However, due to weak correlations in PM and Sarawak, this method cannot be applied and method 2, which is current practice in offshore industry, should continueto be used.

Not All Children Agree: Acquisition of Agreement when the Input Is Variable

Science.gov (United States)

Miller, Karen

2012-01-01

In this paper we investigate the effect of variable input on the acquisition of grammar. More specifically, we examine the acquisition of the third person singular marker -s on the auxiliary "do" in comprehension and production in two groups of children who are exposed to similar varieties of English but that differ with respect to adult…

Variability of δ15N in soil and plants at a New Zealand hill country site: correlations with soil chemistry and nutrient inputs

International Nuclear Information System (INIS)

Hawke, D.J.

2000-01-01

This study investigated 15 N enrichment and nutrient cycling in hill country used for semi-extensive pastoral agriculture, at a site where pre-European seabird breeding occurred. Soil (>15 cm) and plant samples were taken from 18 ridgeline and sideslope transects. Three stock camps (locations which grazing animals frequent) were identified within the study area, two on the ridgeline and one on the sideslope. Soil 15 N enrichment was greatest at stock camps, and lowest where stock input was minimal. Soil natural abundance 15 N (815N) was therefore an index of stock nutrient inputs. Soil δ 15 N increased with decreasing C:N ratio, consistent with N loss through volatilisation and/or nitrate leaching from net mineralisation. Plant δ 15 N from stock camps was lower than its associated soil, implying that 15 N enrichment of plant-available N was lower than that of total soil N. However, the correlation between plant δ 15 N and soil δ 15 N varied between stock camps, indicating differences in N cycling. Olsen P was higher at stock camps, although again differences were found between stock camps. Total P and N were correlated neither with stock camps nor topography, but were higher than expected from parent material concentrations and literature results, respectively. It is postulated that significant contributions of both elements from former seabird breeding remain in the soil. Copyright (2000) CSIRO Publishing

Continuous-variable quantum cloning of coherent states with phase-conjugate input modes using linear optics

International Nuclear Information System (INIS)

Chen, Haixia; Zhang, Jing

2007-01-01

We propose a scheme for continuous-variable quantum cloning of coherent states with phase-conjugate input modes using linear optics. The quantum cloning machine yields M identical optimal clones from N replicas of a coherent state and N replicas of its phase conjugate. This scheme can be straightforwardly implemented with the setups accessible at present since its optical implementation only employs simple linear optical elements and homodyne detection. Compared with the original scheme for continuous-variable quantum cloning with phase-conjugate input modes proposed by Cerf and Iblisdir [Phys. Rev. Lett. 87, 247903 (2001)], which utilized a nondegenerate optical parametric amplifier, our scheme loses the output of phase-conjugate clones and is regarded as irreversible quantum cloning

Groundwater travel time uncertainty analysis. Sensitivity of results to model geometry, and correlations and cross correlations among input parameters

International Nuclear Information System (INIS)

Clifton, P.M.

1985-03-01

This study examines the sensitivity of the travel time distribution predicted by a reference case model to (1) scale of representation of the model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross correlations between transmissivity and effective thickness. The basis for the reference model is the preliminary stochastic travel time model previously documented by the Basalt Waste Isolation Project. Results of this study show the following. The variability of the predicted travel times can be adequately represented when the ratio between the size of the zones used to represent the model parameters and the log-transmissivity correlation range is less than about one-fifth. The size of the model domain and the types of boundary conditions can have a strong impact on the distribution of travel times. Longer log-transmissivity correlation ranges cause larger variability in the predicted travel times. Positive cross correlation between transmissivity and effective thickness causes a decrease in the travel time variability. These results demonstrate the need for a sound conceptual model prior to conducting a stochastic travel time analysis

Spatiotemporal Correlations between Water Footprint and Agricultural Inputs: A Case Study of Maize Production in Northeast China

Directory of Open Access Journals (Sweden)

Peili Duan

2015-07-01

Full Text Available To effectively manage water resources in agricultural production, it is necessary to understand the spatiotemporal variation of the water footprint (WF and the influences of agricultural inputs. Employing spatial autocorrelation analysis and a geographically weighted regression (GWR model, we explored the spatial variations of the WF and their relationships with agricultural inputs from 1998 to 2012 in Northeast China. The results indicated that: (1 the spatial distribution of WFs for the 36 major maize production prefectures was heterogeneous in Northeast China; (2 a cluster of high WFs was found in southeast Liaoning Province, while a cluster of low WFs was found in central Jilin Province, and (3 spatial and temporal differentiation in the correlations between the WF of maize production and agricultural inputs existed according to the GWR model. These correlations increased over time. Our results suggested that localized strategies for reducing the WF should be formulated based on specific relationships between the WF and agricultural inputs.

Urban vs. Rural CLIL: An Analysis of Input-Related Variables, Motivation and Language Attainment

Science.gov (United States)

Alejo, Rafael; Piquer-Píriz, Ana

2016-01-01

The present article carries out an in-depth analysis of the differences in motivation, input-related variables and linguistic attainment of the students at two content and language integrated learning (CLIL) schools operating within the same institutional and educational context, the Spanish region of Extremadura, and differing only in terms of…

The GRB variability/peak luminosity correlation: new results

International Nuclear Information System (INIS)

Guidorzi, C.; Rossi, F.; Hurley, K.; Mundell, C.G.

2005-01-01

We test the correlation between time variability and isotropic-equivalent peak luminosity found by Reichart et al. (ApJ, 552 (2001) 57) using a set of 26 Gamma-Ray Bursts (GRBs) with known redshift. We confirm the correlation, thought with a larger spread around the best-fit power-law obtained by Reichart et al. which in turn does not provide an acceptable description any longer. In addiction, we find no evidence for correlation between variability and beaming-corrected peak luminosity for a subset of 14 GRBs whose beaming angles have been taken from Ghirlanda et al. (ApJ, 616 (2004) 331). Finally, we investigate the possible connection for some GRBs between the location in the variability/peak luminosity space and some afterglow properties, such as the detectability in the optical band, by adding some GRBs whose redshifts, unknown from direct measurements, have been derived assuming the Amati at al. (AeA, 390 (2002) 81) relationship

'Quantization' of stochastic variables: description and effects on the input noise sources in a BWR

International Nuclear Information System (INIS)

Matthey, M.

1979-01-01

A set of macrostochastic and discrete variables, with Markovian properties, is used to characterize the state of a BWR, whose input noise sources are of interest. The ratio between the auto-power spectral density (APSD) of the neutron noise fluctuations and the square modulus of the transfer function (SMTF) defines 'the total input noise source' (TINS), the components of which are the different noise source corresponding to the relevant variables. A white contribution to TINS arises from the birth and death processes of neutrons in the reactor and corresponds to a 'shot noise' (SN). Non-white contributions arise from fluctuations of the neutron cross-sections caused by fuel temperature and steam content variations. These terms called 'Flicker noises' (FN) are characterized by cut-off frequencies related to time constants of reactivity feedback effects. The respective magnitudes of the shot and flicker noises depend not only on the frequency, the feedback reactivity coefficients or the power of the reactor, but also on the 'quantization' of the continuous variables introduced such as fuel temperature and steam content. The effects of this last 'quantization' on the shapes of the noise sources and their sum are presented in this paper. (author)

Generation of correlated finite alphabet waveforms using gaussian random variables

KAUST Repository

Jardak, Seifallah; Ahmed, Sajid; Alouini, Mohamed-Slim

2014-01-01

, the proposed scheme is general, the main focus of this paper is to generate finite alphabet waveforms for multiple-input multiple-output radar, where correlated waveforms are used to achieve desired beampatterns. © 2014 IEEE.

Comparison Study on Empirical Correlation for Mass Transfer Coefficient with Gas Hold-up and Input Power of Aeration Process

International Nuclear Information System (INIS)

Park, Sang Kyoo; Yang, Hei Cheon

2017-01-01

As stricter environmental regulation have led to an increase in the water treatment cost, it is necessary to quantitatively study the input power of the aeration process to improve the energy efficiency of the water treatment processes. The objective of this study is to propose the empirical correlations for the mass transfer coefficient with the gas hold-up and input power in order to investigate the mass transfer characteristics of the aeration process. It was found that as the input power increases, the mass transfer coefficient increases because of the decrease of gas hold-up and increase of Reynolds number, the penetration length, and dispersion of mixed flow. The correlations for the volumetric mass transfer coefficients with gas hold-up and input power were consistent with the experimental data, with the maximum deviation less than approximately ±10.0%.

Comparison Study on Empirical Correlation for Mass Transfer Coefficient with Gas Hold-up and Input Power of Aeration Process

Energy Technology Data Exchange (ETDEWEB)

Park, Sang Kyoo; Yang, Hei Cheon [Chonnam Nat’l Univ., Gwangju (Korea, Republic of)

2017-06-15

As stricter environmental regulation have led to an increase in the water treatment cost, it is necessary to quantitatively study the input power of the aeration process to improve the energy efficiency of the water treatment processes. The objective of this study is to propose the empirical correlations for the mass transfer coefficient with the gas hold-up and input power in order to investigate the mass transfer characteristics of the aeration process. It was found that as the input power increases, the mass transfer coefficient increases because of the decrease of gas hold-up and increase of Reynolds number, the penetration length, and dispersion of mixed flow. The correlations for the volumetric mass transfer coefficients with gas hold-up and input power were consistent with the experimental data, with the maximum deviation less than approximately ±10.0%.

Long-Term Variability of Surface Albedo and Its Correlation with Climatic Variables over Antarctica

Directory of Open Access Journals (Sweden)

Minji Seo

2016-11-01

Full Text Available The cryosphere is an essential part of the earth system for understanding climate change. Components of the cryosphere, such as ice sheets and sea ice, are generally decreasing over time. However, previous studies have indicated differing trends between the Antarctic and the Arctic. The South Pole also shows internal differences in trends. These phenomena indicate the importance of continuous observation of the Polar Regions. Albedo is a main indicator for analyzing Antarctic climate change and is an important variable with regard to the radiation budget because it can provide positive feedback on polar warming and is related to net radiation and atmospheric heating in the mainly snow- and ice-covered Antarctic. Therefore, in this study, we analyzed long-term temporal and spatial variability of albedo and investigated the interrelationships between albedo and climatic variables over Antarctica. We used broadband surface albedo data from the Satellite Application Facility on Climate Monitoring and data for several climatic variables such as temperature and Antarctic oscillation index (AAO during the period of 1983 to 2009. Time series analysis and correlation analysis were performed through linear regression using albedo and climatic variables. The results of this research indicated that albedo shows two trends, west trend and an east trend, over Antarctica. Most of the western side of Antarctica showed a negative trend of albedo (about −0.0007 to −0.0015 year−1, but the other side showed a positive trend (about 0.0006 year−1. In addition, albedo and surface temperature had a negative correlation, but this relationship was weaker in west Antarctica than in east Antarctica. The correlation between albedo and AAO revealed different relationships in the two regions; west Antarctica had a negative correlation and east Antarctica showed a positive correlation. In addition, the correlation between albedo and AAO was weaker in the west. This

Quantum correlations for bipartite continuous-variable systems

Science.gov (United States)

Ma, Ruifen; Hou, Jinchuan; Qi, Xiaofei; Wang, Yangyang

2018-04-01

Two quantum correlations Q and Q_P for (m+n)-mode continuous-variable systems are introduced in terms of average distance between the reduced states under the local Gaussian positive operator-valued measurements, and analytical formulas of these quantum correlations for bipartite Gaussian states are provided. It is shown that the product states do not contain these quantum correlations, and conversely, all (m+n)-mode Gaussian states with zero quantum correlations are product states. Generally, Q≥ Q_{P}, but for the symmetric two-mode squeezed thermal states, these quantum correlations are the same and a computable formula is given. In addition, Q is compared with Gaussian geometric discord for symmetric squeezed thermal states.

Data analytics using canonical correlation analysis and Monte Carlo simulation

Science.gov (United States)

Rickman, Jeffrey M.; Wang, Yan; Rollett, Anthony D.; Harmer, Martin P.; Compson, Charles

2017-07-01

A canonical correlation analysis is a generic parametric model used in the statistical analysis of data involving interrelated or interdependent input and output variables. It is especially useful in data analytics as a dimensional reduction strategy that simplifies a complex, multidimensional parameter space by identifying a relatively few combinations of variables that are maximally correlated. One shortcoming of the canonical correlation analysis, however, is that it provides only a linear combination of variables that maximizes these correlations. With this in mind, we describe here a versatile, Monte-Carlo based methodology that is useful in identifying non-linear functions of the variables that lead to strong input/output correlations. We demonstrate that our approach leads to a substantial enhancement of correlations, as illustrated by two experimental applications of substantial interest to the materials science community, namely: (1) determining the interdependence of processing and microstructural variables associated with doped polycrystalline aluminas, and (2) relating microstructural decriptors to the electrical and optoelectronic properties of thin-film solar cells based on CuInSe2 absorbers. Finally, we describe how this approach facilitates experimental planning and process control.

Statistical learning from nonrecurrent experience with discrete input variables and recursive-error-minimization equations

Science.gov (United States)

Carter, Jeffrey R.; Simon, Wayne E.

1990-08-01

Neural networks are trained using Recursive Error Minimization (REM) equations to perform statistical classification. Using REM equations with continuous input variables reduces the required number of training experiences by factors of one to two orders of magnitude over standard back propagation. Replacing the continuous input variables with discrete binary representations reduces the number of connections by a factor proportional to the number of variables reducing the required number of experiences by another order of magnitude. Undesirable effects of using recurrent experience to train neural networks for statistical classification problems are demonstrated and nonrecurrent experience used to avoid these undesirable effects. 1. THE 1-41 PROBLEM The statistical classification problem which we address is is that of assigning points in ddimensional space to one of two classes. The first class has a covariance matrix of I (the identity matrix) the covariance matrix of the second class is 41. For this reason the problem is known as the 1-41 problem. Both classes have equal probability of occurrence and samples from both classes may appear anywhere throughout the ddimensional space. Most samples near the origin of the coordinate system will be from the first class while most samples away from the origin will be from the second class. Since the two classes completely overlap it is impossible to have a classifier with zero error. The minimum possible error is known as the Bayes error and

Biologic variability and correlation of platelet function testing in healthy dogs.

Science.gov (United States)

Blois, Shauna L; Lang, Sean T; Wood, R Darren; Monteith, Gabrielle

2015-12-01

Platelet function tests are influenced by biologic variability, including inter-individual (CVG ) and intra-individual (CVI ), as well as analytic (CVA ) variability. Variability in canine platelet function testing is unknown, but if excessive, would make it difficult to interpret serial results. Additionally, the correlation between platelet function tests is poor in people, but not well described in dogs. The aims were to: (1) identify the effect of variation in preanalytic factors (venipuncture, elapsed time until analysis) on platelet function tests; (2) calculate analytic and biologic variability of adenosine diphosphate (ADP) and arachidonic acid (AA)-induced thromboelastograph platelet mapping (TEG-PM), ADP-, AA-, and collagen-induced whole blood platelet aggregometry (WBA), and collagen/ADP and collagen/epinephrine platelet function analysis (PFA-CADP, PFA-CEPI); and (3) determine the correlation between these variables. In this prospective observational trial, platelet function was measured once every 7 days, for 4 consecutive weeks, in 9 healthy dogs. In addition, CBC, TEG-PM, WBA, and PFA were performed. Overall coefficients of variability ranged from 13.3% to 87.8% for the platelet function tests. Biologic variability was highest for AA-induced maximum amplitude generated during TEG-PM (MAAA; CVG = 95.3%, CVI = 60.8%). Use of population-based reference intervals (RI) was determined appropriate only for PFA-CADP (index of individuality = 10.7). There was poor correlation between most platelet function tests. Use of population-based RI appears inappropriate for most platelet function tests, and tests poorly correlate with one another. Future studies on biologic variability and correlation of platelet function tests should be performed in dogs with platelet dysfunction and those treated with antiplatelet therapy. © 2015 American Society for Veterinary Clinical Pathology.

Correlation between some environmental variables and abundance ...

African Journals Online (AJOL)

Correlation between some environmental variables and abundance of Almophrya mediovacuolata (Ciliophora: Anoplophryidae) endocommensal ciliate of an ... The survey primarily involved soil samples collection from the same spots of EW collection and preparation for physico-chemical analysis; evaluation in situ of the ...

Extension of Latin hypercube samples with correlated variables

Energy Technology Data Exchange (ETDEWEB)

Sallaberry, C.J. [Sandia National Laboratories, Department 6784, MS 0776, Albuquerque, NM 87185-0776 (United States); Helton, J.C. [Department of Mathematics and Statistics, Arizona State University, Tempe, AZ 85287-1804 (United States)], E-mail: jchelto@sandia.gov; Hora, S.C. [University of Hawaii at Hilo, Hilo, HI 96720-4091 (United States)

2008-07-15

A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations.

Extension of Latin hypercube samples with correlated variables

International Nuclear Information System (INIS)

Sallaberry, C.J.; Helton, J.C.; Hora, S.C.

2008-01-01

A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations

Extension of latin hypercube samples with correlated variables.

Energy Technology Data Exchange (ETDEWEB)

Hora, Stephen Curtis (University of Hawaii at Hilo, HI); Helton, Jon Craig (Arizona State University, Tempe, AZ); Sallaberry, Cedric J. PhD. (.; .)

2006-11-01

A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number of model evaluations.

Variable angle correlation spectroscopy

International Nuclear Information System (INIS)

Lee, Y.K.; Lawrence Berkeley Lab., CA

1994-05-01

In this dissertation, a novel nuclear magnetic resonance (NMR) technique, variable angle correlation spectroscopy (VACSY) is described and demonstrated with 13 C nuclei in rapidly rotating samples. These experiments focus on one of the basic problems in solid state NMR: how to extract the wealth of information contained in the anisotropic component of the NMR signal while still maintaining spectral resolution. Analysis of the anisotropic spectral patterns from poly-crystalline systems reveal information concerning molecular structure and dynamics, yet in all but the simplest of systems, the overlap of spectral patterns from chemically distinct sites renders the spectral analysis difficult if not impossible. One solution to this problem is to perform multi-dimensional experiments where the high-resolution, isotropic spectrum in one dimension is correlated with the anisotropic spectral patterns in the other dimensions. The VACSY technique incorporates the angle between the spinner axis and the static magnetic field as an experimental parameter that may be incremented during the course of the experiment to help correlate the isotropic and anisotropic components of the spectrum. The two-dimensional version of the VACSY experiments is used to extract the chemical shift anisotropy tensor values from multi-site organic molecules, study molecular dynamics in the intermediate time regime, and to examine the ordering properties of partially oriented samples. The VACSY technique is then extended to three-dimensional experiments to study slow molecular reorientations in a multi-site polymer system

Impact of Formal Financial Market Participation on Farm Size and Expenditure on Variable Farm Inputs: The Case of Maize Farmers in Ghana

OpenAIRE

Awunyo-Vitor, Dadson; Al-Hassan, Ramatu M.; Sarpong, Daniel B.

2014-01-01

The study examined maize farmers’ participation in the formal financial market and its impact on farm size and expenditure on variable farm inputs. A multistage sampling method was used in selecting 595 maize farmers from the seven districts in Ashanti and Brong Ahafo Regions of Ghana. A structured questionnaire and interview schedule were used to elicit information from the respondents. The impact of formal financial market participation on farm size and expenditure on variable inputs was es...

Nonlinear canonical correlation analysis with k sets of variables

NARCIS (Netherlands)

van der Burg, Eeke; de Leeuw, Jan

1987-01-01

The multivariate technique OVERALS is introduced as a non-linear generalization of canonical correlation analysis (CCA). First, two sets CCA is introduced. Two sets CCA is a technique that computes linear combinations of sets of variables that correlate in an optimal way. Two sets CCA is then

Variability of interconnected wind plants: correlation length and its dependence on variability time scale

Science.gov (United States)

St. Martin, Clara M.; Lundquist, Julie K.; Handschy, Mark A.

2015-04-01

The variability in wind-generated electricity complicates the integration of this electricity into the electrical grid. This challenge steepens as the percentage of renewably-generated electricity on the grid grows, but variability can be reduced by exploiting geographic diversity: correlations between wind farms decrease as the separation between wind farms increases. But how far is far enough to reduce variability? Grid management requires balancing production on various timescales, and so consideration of correlations reflective of those timescales can guide the appropriate spatial scales of geographic diversity grid integration. To answer ‘how far is far enough,’ we investigate the universal behavior of geographic diversity by exploring wind-speed correlations using three extensive datasets spanning continents, durations and time resolution. First, one year of five-minute wind power generation data from 29 wind farms span 1270 km across Southeastern Australia (Australian Energy Market Operator). Second, 45 years of hourly 10 m wind-speeds from 117 stations span 5000 km across Canada (National Climate Data Archive of Environment Canada). Finally, four years of five-minute wind-speeds from 14 meteorological towers span 350 km of the Northwestern US (Bonneville Power Administration). After removing diurnal cycles and seasonal trends from all datasets, we investigate dependence of correlation length on time scale by digitally high-pass filtering the data on 0.25-2000 h timescales and calculating correlations between sites for each high-pass filter cut-off. Correlations fall to zero with increasing station separation distance, but the characteristic correlation length varies with the high-pass filter applied: the higher the cut-off frequency, the smaller the station separation required to achieve de-correlation. Remarkable similarities between these three datasets reveal behavior that, if universal, could be particularly useful for grid management. For high

A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data

KAUST Repository

Babuška, Ivo; Nobile, Fabio; Tempone, Raul

2010-01-01

This work proposes and analyzes a stochastic collocation method for solving elliptic partial differential equations with random coefficients and forcing terms. These input data are assumed to depend on a finite number of random variables. The method consists of a Galerkin approximation in space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space, and naturally leads to the solution of uncoupled deterministic problems as in the Monte Carlo approach. It treats easily a wide range of situations, such as input data that depend nonlinearly on the random variables, diffusivity coefficients with unbounded second moments, and random variables that are correlated or even unbounded. We provide a rigorous convergence analysis and demonstrate exponential convergence of the “probability error” with respect to the number of Gauss points in each direction of the probability space, under some regularity assumptions on the random input data. Numerical examples show the effectiveness of the method. Finally, we include a section with developments posterior to the original publication of this work. There we review sparse grid stochastic collocation methods, which are effective collocation strategies for problems that depend on a moderately large number of random variables.

Essentials aspects on macroeconomic variables and their correlations

OpenAIRE

Constantin ANGHELACHE; Alexandru MANOLE; Mădălina Gabriela ANGHEL; Aurelian DIACONU

2016-01-01

The measurement of the correlations between macroeconomic variables, including the cause-effect links, provide useful information for policy makers in the government and public agencies. Especially important is the system of relationships that reveals the influence of certain factors on the Gross Domestic Product. This paper outlines the influence of the unemployment, measured through the unemployment rate, the inflation. Also, the authors discuss the correlations of the econom...

Using multiple-accumulator CMACs to improve efficiency of the X part of an input-buffered FX correlator

Science.gov (United States)

Lapshev, Stepan; Hasan, S. M. Rezaul

2017-04-01

This paper presents the approach of using complex multiplier-accumulators (CMACs) with multiple accumulators to reduce the total number of memory operations in an input-buffered architecture for the X part of an FX correlator. A processing unit of this architecture uses an array of CMACs that are reused for different groups of baselines. The disadvantage of processing correlations in this way is that each input data sample has to be read multiple times from the memory because each input signal is used in many of these baseline groups. While a one-accumulator CMAC cannot switch to a different baseline until it is finished integrating the current one, a multiple-accumulator CMAC can. Thus, the array of multiple-accumulator CMACs can switch between processing different baselines that share some input signals at any moment to reuse the current data in the processing buffers. In this way significant reductions in the number of memory read operations are achieved with only a few accumulators per CMAC. For example, for a large number of input signals three-accumulator CMACs reduce the total number of memory operations by more than a third. Simulated energy measurements of four VLSI designs in a high-performance 28 nm CMOS technology are presented in this paper to demonstrate that using multiple accumulators can also lead to reduced power dissipation of the processing array. Using three accumulators as opposed to one has been found to reduce the overall energy of 8-bit CMACs by 1.4% through the reduction of the switching activity within their circuits, which is in addition to a more than 30% reduction in the memory.

Spatial variability of correlated color temperature of lightning channels

Directory of Open Access Journals (Sweden)

Nobuaki Shimoji

Full Text Available In this paper, we present the spatial variability of the correlated color temperature of lightning channel shown in a digital still image. In order to analyze the correlated color temperature, we calculated chromaticity coordinates of the lightning channels in the digital still image. From results, the spatial variation of the correlated color temperature of the lightning channel was confirmed. Moreover, the results suggest that the correlated color temperature and peak current of the lightning channels are related to each other. Keywords: Lightning, Color analysis, Correlated color temperature, Chromaticity coordinate, CIE 1931 xy-chromaticity diagram

Physical-mathematical model for cybernetic description of the human organs with trace element concentrations as input variables

International Nuclear Information System (INIS)

Mihai, Maria; Popescu, I.V.

2003-01-01

In this paper we report a physical-mathematical model for studying the organs and humans fluids by cybernetic principle. The input variables represent the trace elements which are determined by atomic and nuclear methods of elemental analysis. We have determined the health limits between which the organs might function. (authors)

Variable ultrasonography findings of extremity lymphangioma: Pathologic correlation

International Nuclear Information System (INIS)

Oh, Jong Young; Nam, Kyung Jin; Lee, Ki Nam; Kim, Chan Sung; Lee, Jin Hwa; Kim, Dae Chul

2002-01-01

The great majority of lymphangiomas occur in the neck (75%) and axilla (20%), but extremity lymphangioma is rare. We correlate variable sonographic features of extremity lymphangioma with pathologic findings. We reviewed the sonographic findings of extremity lymphangioma in 14 patients (M:F=8:6). The all cases were histologically confirmed by operation. The variable sonographic features of extremity lymphangioma were compared to pathologic findings. The multilocular cystic mass with ill defined boundaries was distinctive sonographic appearance of extremity lymphangioma. But there were variable sonographic findings such as heterogeneous echogenic mass or homogeneous echogenic portion. The histologic section of echogenic lesion reveals clusters of abnormal

Data interpolation for vibration diagnostics using two-variable correlations

International Nuclear Information System (INIS)

Branagan, L.

1991-01-01

This paper reports that effective machinery vibration diagnostics require a clear differentiation between normal vibration changes caused by plant process conditions and those caused by degradation. The normal relationship between vibration and a process parameter can be quantified by developing the appropriate correlation. The differences in data acquisition requirements between dynamic signals (vibration spectra) and static signals (pressure, temperature, etc.) result in asynchronous data acquisition; the development of any correlation must then be based on some form of interpolated data. This interpolation can reproduce or distort the original measured quantity depending on the characteristics of the data and the interpolation technique. Relevant data characteristics, such as acquisition times, collection cycle times, compression method, storage rate, and the slew rate of the measured variable, are dependent both on the data handling and on the measured variable. Linear and staircase interpolation, along with the use of clustering and filtering, provide the necessary options to develop accurate correlations. The examples illustrate the appropriate application of these options

Ergodic channel capacity of spatial correlated multiple-input multiple-output free space optical links using multipulse pulse-position modulation

Science.gov (United States)

Wang, Huiqin; Wang, Xue; Cao, Minghua

2017-02-01

The spatial correlation extensively exists in the multiple-input multiple-output (MIMO) free space optical (FSO) communication systems due to the channel fading and the antenna space limitation. Wilkinson's method was utilized to investigate the impact of spatial correlation on the MIMO FSO communication system employing multipulse pulse-position modulation. Simulation results show that the existence of spatial correlation reduces the ergodic channel capacity, and the reception diversity is more competent to resist this kind of performance degradation.

Generalized inequalities for quantum correlations with hidden variables

International Nuclear Information System (INIS)

Vinduska, M.

1991-01-01

Renowned inequalities for quantum correlations are generalized for the case when quantum system cannot be described with an absolute independent measure of the probability. Such a formulation appears to be suitable for the formulation of the hidden variables theory in terms of non-Euclidean geometry. 10 refs

GIS and correlation analysis of geo-environmental variables ...

African Journals Online (AJOL)

GIS and correlation analysis of geo-environmental variables influencing malaria prevalence in the Saboba district of Northern Ghana. ... The study also applied spline interpolation technique to map malaria prevalence in the district using standardised malaria incidence. The result indicates that distance to marshy areas is ...

Correlations between Sportsmen’s Morpho-Functional Measurements and Voice Acoustic Variables

Directory of Open Access Journals (Sweden)

Rexhepi Agron M.

2016-12-01

Full Text Available Purpose. Since human voice characteristics are specific to each individual, numerous anthropological studies have been oriented to find significant relationships between voice and morpho-functional features. The goal of this study was to identify the correlation between seven morpho-functional variables and six voice acoustic parameters in sportsmen. Methods. Following the protocols of the International Biological Program, seven morpho-functional variables and six voice acoustic parameters have been measured in 88 male professional athletes from Kosovo, aged 17-35 years, during the period of April-October 2013. The statistical analysis was accomplished through the SPSS program, version 20. The obtained data were analysed through descriptive parameters and with Spearman’s method of correlation analysis. Results. Spearman’s method of correlation showed significant negative correlations (R = -0.215 to -0.613; p = 0.05 between three voice acoustic variables of the fundamental frequency of the voice sample (Mean, Minimum, and Maximum Pitch and six morpho-functional measures (Body Height, Body Weight, Margaria-Kalamen Power Test, Sargent Jump Test, Pull-up Test, and VO2max.abs. Conclusions. The significant correlations imply that the people with higher stature have longer vocal cords and a lower voice. These results encourage investigations on predicting sportsmen’s functional abilities on the basis of their voice acoustic parameters.

Approximate entropy and point correlation dimension of heart rate variability in healthy subjects

DEFF Research Database (Denmark)

Storella, R J; Wood, H W; Mills, K M

1999-01-01

The contribution of nonlinear dynamics to heart rate variability in healthy humans was examined using surrogate data analysis. Several measures of heart rate variability were used and compared. Heart rates were recorded for three hours and original data sets of 8192 R-R intervals created. For each...... original data set (n = 34), three surrogate data sets were made by shuffling the order of the R-R intervals while retaining their linear correlations. The difference in heart rate variability between the original and surrogate data sets reflects the amount of nonlinear structure in the original data set....... Heart rate variability was analyzed by two different nonlinear methods, point correlation dimension and approximate entropy. Nonlinearity, though under 10 percent, could be detected with both types of heart rate variability measures. More importantly, not only were the correlations between...

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

Science.gov (United States)

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Response sensitivity of barrel neuron subpopulations to simulated thalamic input.

Science.gov (United States)

Pesavento, Michael J; Rittenhouse, Cynthia D; Pinto, David J

2010-06-01

Our goal is to examine the relationship between neuron- and network-level processing in the context of a well-studied cortical function, the processing of thalamic input by whisker-barrel circuits in rodent neocortex. Here we focus on neuron-level processing and investigate the responses of excitatory and inhibitory barrel neurons to simulated thalamic inputs applied using the dynamic clamp method in brain slices. Simulated inputs are modeled after real thalamic inputs recorded in vivo in response to brief whisker deflections. Our results suggest that inhibitory neurons require more input to reach firing threshold, but then fire earlier, with less variability, and respond to a broader range of inputs than do excitatory neurons. Differences in the responses of barrel neuron subtypes depend on their intrinsic membrane properties. Neurons with a low input resistance require more input to reach threshold but then fire earlier than neurons with a higher input resistance, regardless of the neuron's classification. Our results also suggest that the response properties of excitatory versus inhibitory barrel neurons are consistent with the response sensitivities of the ensemble barrel network. The short response latency of inhibitory neurons may serve to suppress ensemble barrel responses to asynchronous thalamic input. Correspondingly, whereas neurons acting as part of the barrel circuit in vivo are highly selective for temporally correlated thalamic input, excitatory barrel neurons acting alone in vitro are less so. These data suggest that network-level processing of thalamic input in barrel cortex depends on neuron-level processing of the same input by excitatory and inhibitory barrel neurons.

Estimating severity of sideways fall using a generic multi linear regression model based on kinematic input variables.

Science.gov (United States)

van der Zijden, A M; Groen, B E; Tanck, E; Nienhuis, B; Verdonschot, N; Weerdesteyn, V

2017-03-21

Many research groups have studied fall impact mechanics to understand how fall severity can be reduced to prevent hip fractures. Yet, direct impact force measurements with force plates are restricted to a very limited repertoire of experimental falls. The purpose of this study was to develop a generic model for estimating hip impact forces (i.e. fall severity) in in vivo sideways falls without the use of force plates. Twelve experienced judokas performed sideways Martial Arts (MA) and Block ('natural') falls on a force plate, both with and without a mat on top. Data were analyzed to determine the hip impact force and to derive 11 selected (subject-specific and kinematic) variables. Falls from kneeling height were used to perform a stepwise regression procedure to assess the effects of these input variables and build the model. The final model includes four input variables, involving one subject-specific measure and three kinematic variables: maximum upper body deceleration, body mass, shoulder angle at the instant of 'maximum impact' and maximum hip deceleration. The results showed that estimated and measured hip impact forces were linearly related (explained variances ranging from 46 to 63%). Hip impact forces of MA falls onto the mat from a standing position (3650±916N) estimated by the final model were comparable with measured values (3698±689N), even though these data were not used for training the model. In conclusion, a generic linear regression model was developed that enables the assessment of fall severity through kinematic measures of sideways falls, without using force plates. Copyright © 2017 Elsevier Ltd. All rights reserved.

Egocentric and allocentric alignment tasks are affected by otolith input.

Science.gov (United States)

Tarnutzer, Alexander A; Bockisch, Christopher J; Olasagasti, Itsaso; Straumann, Dominik

2012-06-01

otolith input. Such a shared mechanism for both paradigms and frames of reference is supported by the significantly correlated trial-to-trial variabilities.

Work hardening correlation for monotonic loading based on state variables

International Nuclear Information System (INIS)

Huang, F.H.; Li, C.Y.

1977-01-01

An absolute work hardening correlation in terms of the hardness parameter and the internal stress based on the state variable approach was developed. It was found applicable to a variety of metals and alloys. This correlation predicts strain rate insensitive work hardening properties at low homologous temperatures and produces strain rate effects at higher homologous temperatures without involving thermally induced recovery processes

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

Science.gov (United States)

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-04

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Variability and correlations between characteristics in pumpkin varieties (Cucurbita maxima Duch. ex Lam.

Directory of Open Access Journals (Sweden)

Mladenović Emina

2012-01-01

Full Text Available Variability and correlations among morphological features of eight ornamental pumpkin varieties were studied under field conditions. The variability of plant height, fruit length, fruit width, fruith weight, fruit peel thickness, length and circumference of handle grip, leaf length, leaf width, seed length, seed width, seed thickness and number of fruits per plant in the examined material was high. The highest variability was related to the fruit properties. This variability represents a good source for future breeding programs. Correlations between the traits indicated a significant influence of leaf and seed characteristics on fruit properties. Multivariate statistical analysis provided differentiation of varieties on two phenotypically different groups.

A robust hybrid model integrating enhanced inputs based extreme learning machine with PLSR (PLSR-EIELM) and its application to intelligent measurement.

Science.gov (United States)

He, Yan-Lin; Geng, Zhi-Qiang; Xu, Yuan; Zhu, Qun-Xiong

2015-09-01

In this paper, a robust hybrid model integrating an enhanced inputs based extreme learning machine with the partial least square regression (PLSR-EIELM) was proposed. The proposed PLSR-EIELM model can overcome two main flaws in the extreme learning machine (ELM), i.e. the intractable problem in determining the optimal number of the hidden layer neurons and the over-fitting phenomenon. First, a traditional extreme learning machine (ELM) is selected. Second, a method of randomly assigning is applied to the weights between the input layer and the hidden layer, and then the nonlinear transformation for independent variables can be obtained from the output of the hidden layer neurons. Especially, the original input variables are regarded as enhanced inputs; then the enhanced inputs and the nonlinear transformed variables are tied together as the whole independent variables. In this way, the PLSR can be carried out to identify the PLS components not only from the nonlinear transformed variables but also from the original input variables, which can remove the correlation among the whole independent variables and the expected outputs. Finally, the optimal relationship model of the whole independent variables with the expected outputs can be achieved by using PLSR. Thus, the PLSR-EIELM model is developed. Then the PLSR-EIELM model served as an intelligent measurement tool for the key variables of the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. The experimental results show that the predictive accuracy of PLSR-EIELM is stable, which indicate that PLSR-EIELM has good robust character. Moreover, compared with ELM, PLSR, hierarchical ELM (HELM), and PLSR-ELM, PLSR-EIELM can achieve much smaller predicted relative errors in these two applications. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Quality of early parent input predicts child vocabulary 3 years later.

Science.gov (United States)

Cartmill, Erica A; Armstrong, Benjamin F; Gleitman, Lila R; Goldin-Meadow, Susan; Medina, Tamara N; Trueswell, John C

2013-07-09

Children vary greatly in the number of words they know when they enter school, a major factor influencing subsequent school and workplace success. This variability is partially explained by the differential quantity of parental speech to preschoolers. However, the contexts in which young learners hear new words are also likely to vary in referential transparency; that is, in how clearly word meaning can be inferred from the immediate extralinguistic context, an aspect of input quality. To examine this aspect, we asked 218 adult participants to guess 50 parents' words from (muted) videos of their interactions with their 14- to 18-mo-old children. We found systematic differences in how easily individual parents' words could be identified purely from this socio-visual context. Differences in this kind of input quality correlated with the size of the children's vocabulary 3 y later, even after controlling for differences in input quantity. Although input quantity differed as a function of socioeconomic status, input quality (as here measured) did not, suggesting that the quality of nonverbal cues to word meaning that parents offer to their children is an individual matter, widely distributed across the population of parents.

Characteristic length scale of input data in distributed models: implications for modeling grid size

Science.gov (United States)

Artan, G. A.; Neale, C. M. U.; Tarboton, D. G.

2000-01-01

The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model response. The semi-variogram and the characteristic length calculated from the spatial autocorrelation were used to determine the scale of variability of the remotely sensed and GIS-generated model input data. The data were collected from two hillsides at Upper Sheep Creek, a sub-basin of the Reynolds Creek Experimental Watershed, in southwest Idaho. The data were analyzed in terms of the semivariance and the integral of the autocorrelation. The minimum characteristic length associated with the variability of the data used in the analysis was 15 m. Simulated and observed radiometric surface temperature fields at different spatial resolutions were compared. The correlation between agreement simulated and observed fields sharply declined after a 10×10 m2 modeling grid size. A modeling grid size of about 10×10 m2 was deemed to be the best compromise to achieve: (a) reduction of computation time and the size of the support data; and (b) a reproduction of the observed radiometric surface temperature.

Characteristic length scale of input data in distributed models: implications for modeling grain size

Science.gov (United States)

Artan, Guleid A.; Neale, C. M. U.; Tarboton, D. G.

2000-01-01

The appropriate spatial scale for a distributed energy balance model was investigated by: (a) determining the scale of variability associated with the remotely sensed and GIS-generated model input data; and (b) examining the effects of input data spatial aggregation on model response. The semi-variogram and the characteristic length calculated from the spatial autocorrelation were used to determine the scale of variability of the remotely sensed and GIS-generated model input data. The data were collected from two hillsides at Upper Sheep Creek, a sub-basin of the Reynolds Creek Experimental Watershed, in southwest Idaho. The data were analyzed in terms of the semivariance and the integral of the autocorrelation. The minimum characteristic length associated with the variability of the data used in the analysis was 15 m. Simulated and observed radiometric surface temperature fields at different spatial resolutions were compared. The correlation between agreement simulated and observed fields sharply declined after a 10×10 m2 modeling grid size. A modeling grid size of about 10×10 m2 was deemed to be the best compromise to achieve: (a) reduction of computation time and the size of the support data; and (b) a reproduction of the observed radiometric surface temperature.

Variability, correlation and path coefficient analysis of seedling traits ...

African Journals Online (AJOL)

Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient analysis.

Variability, correlation and path coefficient analysis of seedling traits ...

African Journals Online (AJOL)

use

2011-12-12

Dec 12, 2011 ... Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient ...

A CATASTROPHIC-CUM-RESTORATIVE QUEUING SYSTEM WITH CORRELATED BATCH ARRIVALS AND VARIABLE CAPACITY

Directory of Open Access Journals (Sweden)

Rakesh Kumar

2008-07-01

Full Text Available In this paper, we study a catastrophic-cum-restorative queuing system with correlated batch arrivals and service in batches of variable sizes. We perform the transient analysis of the queuing model. We obtain the Laplace Transform of the probability generating function of system size. Finally, some particular cases of the model have been derived and discussed. Keywords: Queue length, Catastrophes, Correlated batch arrivals, Broadband services, Variable service capacity, and Restoration.

Population coding in mouse visual cortex: response reliability and dissociability of stimulus tuning and noise correlation

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Jorrit S. Montijn

2014-06-01

Full Text Available The primary visual cortex is an excellent model system for investigating how neuronal populations encode information, because of well-documented relationships between stimulus characteristics and neuronal activation patterns. We used two-photon calcium imaging data to relate the performance of different methods for studying population coding (population vectors, template matching, and Bayesian decoding algorithms to their underlying assumptions. We show that the variability of neuronal responses may hamper the decoding of population activity, and that a normalization to correct for this variability may be of critical importance for correct decoding of population activity. Second, by comparing noise correlations and stimulus tuning we find that these properties have dissociated anatomical correlates, even though noise correlations have been previously hypothesized to reflect common synaptic input. We hypothesize that noise correlations arise from large non-specific increases in spiking activity acting on many weak synapses simultaneously, while neuronal stimulus response properties are dependent on more reliable connections. Finally, this paper provides practical guidelines for further research on population coding and shows that population coding cannot be approximated by a simple summation of inputs, but is heavily influenced by factors such as input reliability and noise correlation structure.

Dose uncertainties for large solar particle events: Input spectra variability and human geometry approximations

International Nuclear Information System (INIS)

Townsend, Lawrence W.; Zapp, E. Neal

1999-01-01

The true uncertainties in estimates of body organ absorbed dose and dose equivalent, from exposures of interplanetary astronauts to large solar particle events (SPEs), are essentially unknown. Variations in models used to parameterize SPE proton spectra for input into space radiation transport and shielding computer codes can result in uncertainty about the reliability of dose predictions for these events. Also, different radiation transport codes and their input databases can yield significant differences in dose predictions, even for the same input spectra. Different results may also be obtained for the same input spectra and transport codes if different spacecraft and body self-shielding distributions are assumed. Heretofore there have been no systematic investigations of the variations in dose and dose equivalent resulting from these assumptions and models. In this work we present a study of the variability in predictions of organ dose and dose equivalent arising from the use of different parameters to represent the same incident SPE proton data and from the use of equivalent sphere approximations to represent human body geometry. The study uses the BRYNTRN space radiation transport code to calculate dose and dose equivalent for the skin, ocular lens and bone marrow using the October 1989 SPE as a model event. Comparisons of organ dose and dose equivalent, obtained with a realistic human geometry model and with the oft-used equivalent sphere approximation, are also made. It is demonstrated that variations of 30-40% in organ dose and dose equivalent are obtained for slight variations in spectral fitting parameters obtained when various data points are included or excluded from the fitting procedure. It is further demonstrated that extrapolating spectra from low energy (≤30 MeV) proton fluence measurements, rather than using fluence data extending out to 100 MeV results in dose and dose equivalent predictions that are underestimated by factors as large as 2

Soil organic carbon dynamics jointly controlled by climate, carbon inputs, soil properties and soil carbon fractions.

Science.gov (United States)

Luo, Zhongkui; Feng, Wenting; Luo, Yiqi; Baldock, Jeff; Wang, Enli

2017-10-01

Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions. However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively. Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (r C , Mg C ha -1  yr -1 ). Among these variables, we found that the most influential variables on r C were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials. Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on r C , followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24%. Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining r C . The direct correlation of r C with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa. These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics. Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process-based SOC models. © 2017 John Wiley & Sons Ltd.

Input Selection for Return Temperature Estimation in Mixing Loops using Partial Mutual Information with Flow Variable Delay

DEFF Research Database (Denmark)

Overgaard, Anders; Kallesøe, Carsten Skovmose; Bendtsen, Jan Dimon

2017-01-01

adgang til data, er ønsker at skabe en datadreven model til kontrol. Grundet den store mængde tilgængelig data anvendes der en metode til valg af inputs kaldet "Partial Mutual Information" (PMI). Denne artikel introducerer en metode til at inkluderer flow variable forsinkelser i PMI. Data fra en...... kontorbygning i Bjerringbro anvendes til analyse. Det vises at "Mutual Information" og et "Generalized Regression Neural Network" begge forbedres ved at anvende flow variabelt forsinkelse i forhold til at anvende konstante delay....

The sequential hypothesis of sleep function. IV. A correlative analysis of sleep variables in learning and nonlearning rats.

Science.gov (United States)

Langella, M; Colarieti, L; Ambrosini, M V; Giuditta, A

1992-02-01

Female adult rats were trained for a two-way active avoidance task (4 h), and allowed free sleep (3 h). Control rats (C) were left in their home cages during the acquisition period. Dural electrodes and an intraventricular cannula, implanted one week in advance, were used for EEG recording during the period of sleep and for the injection of [3H]thymidine at the beginning of the training session, respectively. Rats were killed at the end of the sleep period, and the DNA-specific activity was determined in the main brain regions and in liver. Correlations among sleep, behavioral and biochemical variables were assessed using Spearman's nonparametric method. In learning rats (L), the number of avoidances was negatively correlated with SS-W variables, and positively correlated with SS-PS variables (episodes of synchronized sleep followed by wakefulness or paradoxical sleep, respectively) and with PS variables. An inverse pattern of correlations was shown by the number of escapes or freezings. No correlations occurred in rats unable to achieve the learning criterion (NL). In L rats, the specific activity of brain DNA was negatively correlated with SS-W variables and positively correlated with SS-PS variables, while essentially no correlation concerned PS variables. On the other hand, in NL rats, comparable correlations were positive with SS-W variables and negative with SS-PS and PS variables. Few and weak correlations occurred in C rats. The data support a role of SS in brain information processing, as postulated by the sequential hypothesis on the function of sleep. In addition, they suggest that the elimination of nonadaptive memory traces may require several SS-W episodes and a terminal SS-PS episode. During PS episodes, adaptive memory traces cleared of nonadaptive components may be copied in more suitable brain sites.

ETFOD: a point model physics code with arbitrary input

International Nuclear Information System (INIS)

Rothe, K.E.; Attenberger, S.E.

1980-06-01

ETFOD is a zero-dimensional code which solves a set of physics equations by minimization. The technique used is different than normally used, in that the input is arbitrary. The user is supplied with a set of variables from which he specifies which variables are input (unchanging). The remaining variables become the output. Presently the code is being used for ETF reactor design studies. The code was written in a manner to allow easy modificaton of equations, variables, and physics calculations. The solution technique is presented along with hints for using the code

Measures of the sheep-goat variable, transliminality, and their correlates.

Science.gov (United States)

Thalbourne, M A

2001-04-01

In this study a battery of pencil-and-paper tests was given to 125 first-year psychology students (27% men). This battery included as measures of belief in the paranormal (the so-called "sheep-goat variable") the Australian Sheep-Goat Scale, Tobacyk's Revised Paranormal Belief Scale (comprised of two scales--New Age Philosophy and Traditional Paranormal Beliefs), and the Anomalous Experience Inventory (comprised of five scales: Anomalous/Paranormal Experience, Belief, Ability, Fear, and Drug Use). Also included were the 29-item Transliminality Scale, a 35-item Kundalini Scale, an experimental 13-item Determinism/Free Will scale, and a number of single-question items aimed specifically at transliminality. The results were, first, that virtually all the measures of the sheep-goat variable were intercorrelated with each other (range, .34 to .77), thereby providing support for their convergent validity. Second, scores on the Kundalini Scale and Drug Use correlated significantly with scores on the sheep-goat variable, replicating previous findings. And, finally, many correlates of transliminality were found, again including scores on the Kundalini Scale and Drug Use (prescribed and illicit) as well as certain determinism-related beliefs. Beliefs, experiences, and behaviors associated with transliminality and the Kundalini experience may reflect a desire to escape a negative state of being.

Computer Generated Inputs for NMIS Processor Verification

International Nuclear Information System (INIS)

J. A. Mullens; J. E. Breeding; J. A. McEvers; R. W. Wysor; L. G. Chiang; J. R. Lenarduzzi; J. T. Mihalczo; J. K. Mattingly

2001-01-01

Proper operation of the Nuclear Identification Materials System (NMIS) processor can be verified using computer-generated inputs [BIST (Built-In-Self-Test)] at the digital inputs. Preselected sequences of input pulses to all channels with known correlation functions are compared to the output of the processor. These types of verifications have been utilized in NMIS type correlation processors at the Oak Ridge National Laboratory since 1984. The use of this test confirmed a malfunction in a NMIS processor at the All-Russian Scientific Research Institute of Experimental Physics (VNIIEF) in 1998. The NMIS processor boards were returned to the U.S. for repair and subsequently used in NMIS passive and active measurements with Pu at VNIIEF in 1999

Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

Science.gov (United States)

He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong

2016-03-01

In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Fish functional traits correlated with environmental variables in a temperate biodiversity hotspot.

Directory of Open Access Journals (Sweden)

Benjamin P Keck

Full Text Available The global biodiversity crisis has invigorated the search for generalized patterns in most disciplines within the natural sciences. Studies based on organismal functional traits attempt to broaden implications of results by identifying the response of functional traits, instead of taxonomic units, to environmental variables. Determining the functional trait responses enables more direct comparisons with, or predictions for, communities of different taxonomic composition. The North American freshwater fish fauna is both diverse and increasingly imperiled through human mediated disturbances, including climate change. The Tennessee River, USA, contains one of the most diverse assemblages of freshwater fish in North America and has more imperiled species than other rivers, but there has been no trait-based study of community structure in the system. We identified 211 localities in the upper Tennessee River that were sampled by the Tennessee Valley Authority between 2009 and 2011 and compiled fish functional traits for the observed species and environmental variables for each locality. Using fourth corner analysis, we identified significant correlations between many fish functional traits and environmental variables. Functional traits associated with an opportunistic life history strategy were correlated with localities subject to greater land use disturbance and less flow regulation, while functional traits associated with a periodic life history strategy were correlated with localities subject to regular disturbance and regulated flow. These are patterns observed at the continental scale, highlighting the generalizability of trait-based methods. Contrary to studies that found no community structure differences when considering riparian buffer zones, we found that fish functional traits were correlated with different environmental variables between analyses with buffer zones vs. entire catchment area land cover proportions. Using existing databases

Fish functional traits correlated with environmental variables in a temperate biodiversity hotspot.

Science.gov (United States)

Keck, Benjamin P; Marion, Zachary H; Martin, Derek J; Kaufman, Jason C; Harden, Carol P; Schwartz, John S; Strange, Richard J

2014-01-01

The global biodiversity crisis has invigorated the search for generalized patterns in most disciplines within the natural sciences. Studies based on organismal functional traits attempt to broaden implications of results by identifying the response of functional traits, instead of taxonomic units, to environmental variables. Determining the functional trait responses enables more direct comparisons with, or predictions for, communities of different taxonomic composition. The North American freshwater fish fauna is both diverse and increasingly imperiled through human mediated disturbances, including climate change. The Tennessee River, USA, contains one of the most diverse assemblages of freshwater fish in North America and has more imperiled species than other rivers, but there has been no trait-based study of community structure in the system. We identified 211 localities in the upper Tennessee River that were sampled by the Tennessee Valley Authority between 2009 and 2011 and compiled fish functional traits for the observed species and environmental variables for each locality. Using fourth corner analysis, we identified significant correlations between many fish functional traits and environmental variables. Functional traits associated with an opportunistic life history strategy were correlated with localities subject to greater land use disturbance and less flow regulation, while functional traits associated with a periodic life history strategy were correlated with localities subject to regular disturbance and regulated flow. These are patterns observed at the continental scale, highlighting the generalizability of trait-based methods. Contrary to studies that found no community structure differences when considering riparian buffer zones, we found that fish functional traits were correlated with different environmental variables between analyses with buffer zones vs. entire catchment area land cover proportions. Using existing databases and fourth corner

Effects of input uncertainty on cross-scale crop modeling

Science.gov (United States)

Waha, Katharina; Huth, Neil; Carberry, Peter

2014-05-01

The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input

Input and language development in bilingually developing children.

Science.gov (United States)

Hoff, Erika; Core, Cynthia

2013-11-01

Language skills in young bilingual children are highly varied as a result of the variability in their language experiences, making it difficult for speech-language pathologists to differentiate language disorder from language difference in bilingual children. Understanding the sources of variability in bilingual contexts and the resulting variability in children's skills will help improve language assessment practices by speech-language pathologists. In this article, we review literature on bilingual first language development for children under 5 years of age. We describe the rate of development in single and total language growth, we describe effects of quantity of input and quality of input on growth, and we describe effects of family composition on language input and language growth in bilingual children. We provide recommendations for language assessment of young bilingual children and consider implications for optimizing children's dual language development. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

National IQs: A Review of Their Educational, Cognitive, Economic, Political, Demographic, Sociological, Epidemiological, Geographic and Climatic Correlates

Science.gov (United States)

Lynn, Richard; Vanhanen, Tatu

2012-01-01

This paper summarizes the results of 244 correlates of national IQs that have been published from 2002 through 2012 and include educational attainment, cognitive output, educational input, per capita income, economic growth, other economic variables, crime, political institutions, health, fertility, sociological variables, and geographic and…

Sensitivity analysis of complex models: Coping with dynamic and static inputs

International Nuclear Information System (INIS)

Anstett-Collin, F.; Goffart, J.; Mara, T.; Denis-Vidal, L.

2015-01-01

In this paper, we address the issue of conducting a sensitivity analysis of complex models with both static and dynamic uncertain inputs. While several approaches have been proposed to compute the sensitivity indices of the static inputs (i.e. parameters), the one of the dynamic inputs (i.e. stochastic fields) have been rarely addressed. For this purpose, we first treat each dynamic as a Gaussian process. Then, the truncated Karhunen–Loève expansion of each dynamic input is performed. Such an expansion allows to generate independent Gaussian processes from a finite number of independent random variables. Given that a dynamic input is represented by a finite number of random variables, its variance-based sensitivity index is defined by the sensitivity index of this group of variables. Besides, an efficient sampling-based strategy is described to estimate the first-order indices of all the input factors by only using two input samples. The approach is applied to a building energy model, in order to assess the impact of the uncertainties of the material properties (static inputs) and the weather data (dynamic inputs) on the energy performance of a real low energy consumption house. - Highlights: • Sensitivity analysis of models with uncertain static and dynamic inputs is performed. • Karhunen–Loève (KL) decomposition of the spatio/temporal inputs is performed. • The influence of the dynamic inputs is studied through the modes of the KL expansion. • The proposed approach is applied to a building energy model. • Impact of weather data and material properties on performance of real house is given

The Mixed Effects of Phonetic Input Variability on Relative Ease of L2 Learning: Evidence from English Learners’ Production of French and Spanish Stop-Rhotic Clusters

Directory of Open Access Journals (Sweden)

Laura Colantoni

2018-04-01

Full Text Available We examined the consequences of within-category phonetic variability in the input on non-native learners’ production accuracy. Following previous empirical research on the L2 acquisition of phonetics and the lexicon, we tested the hypothesis that phonetic variability facilitates learning by analyzing English-speaking learners’ production of French and Spanish word-medial stop-rhotic clusters, which differ from their English counterparts in terms of stop and rhotic voicing and manner. Crucially, for both the stops and rhotics, there are differences in within-language variability. Twenty native speakers per language and 39 L1 English-learners of French (N = 20 and Spanish (N = 19 of intermediate and advanced proficiency performed a carrier-sentence reading task. A given parameter was deemed to have been acquired when the learners’ production fell within the range of attested native speaker values. An acoustic analysis of the data partially supports the facilitative effect of phonetic variability. To account for the unsupported hypotheses, we discuss a number of issues, including the difficulty of measuring variability, the need to determine the extent to which learners’ perception shapes intake, and the challenge of teasing apart the effects of input variability from those of transferred L1 articulatory patterns.

What Can We Learn about GRB from the Variability Timescale Related Correlations?

Energy Technology Data Exchange (ETDEWEB)

Xie, Wei; Lei, Wei-Hua; Wang, Ding-Xiong, E-mail: leiwh@hust.edu.cn [School of Physics, Huazhong University of Science and Technology, Wuhan 430074 (China)

2017-04-01

Recently, two empirical correlations related to the minimum variability timescale (MTS) of the light curves are discovered in gamma-ray bursts (GRBs). One is the anti-correlation between MTS and Lorentz factor Γ, and the other is the anti-correlation between the MTS and gamma-ray luminosity L {sub γ}. Both of the two correlations might be used to explore the activity of the central engine of GRBs. In this paper, we try to understand these empirical correlations by combining two popular black hole central engine models (namely, the Blandford and Znajek mechanism (BZ) and the neutrino-dominated accretion flow (NDAF)). By taking the MTS as the timescale of viscous instability of the NDAF, we find that these correlations favor the scenario in which the jet is driven by the BZ mechanism.

What Can We Learn about GRB from the Variability Timescale Related Correlations?

International Nuclear Information System (INIS)

Xie, Wei; Lei, Wei-Hua; Wang, Ding-Xiong

2017-01-01

Recently, two empirical correlations related to the minimum variability timescale (MTS) of the light curves are discovered in gamma-ray bursts (GRBs). One is the anti-correlation between MTS and Lorentz factor Γ, and the other is the anti-correlation between the MTS and gamma-ray luminosity L γ . Both of the two correlations might be used to explore the activity of the central engine of GRBs. In this paper, we try to understand these empirical correlations by combining two popular black hole central engine models (namely, the Blandford and Znajek mechanism (BZ) and the neutrino-dominated accretion flow (NDAF)). By taking the MTS as the timescale of viscous instability of the NDAF, we find that these correlations favor the scenario in which the jet is driven by the BZ mechanism.

An Examination of the Demographic and Environmental Variables Correlated with Lyme Disease Emergence in Virginia.

Science.gov (United States)

Seukep, Sara E; Kolivras, Korine N; Hong, Yili; Li, Jie; Prisley, Stephen P; Campbell, James B; Gaines, David N; Dymond, Randel L

2015-12-01

Lyme disease is the United States' most significant vector-borne illness. Virginia, on the southern edge of the disease's currently expanding range, has experienced an increase in Lyme disease both spatially and temporally, with steadily increasing rates over the past decade and disease spread from the northern to the southwestern part of the state. This study used a Geographic Information System and a spatial Poisson regression model to examine correlations between demographic and land cover variables, and human Lyme disease from 2006 to 2010 in Virginia. Analysis indicated that herbaceous land cover is positively correlated with Lyme disease incidence rates. Areas with greater interspersion between herbaceous and forested land were also positively correlated with incidence rates. In addition, income and age were positively correlated with incidence rates. Levels of development, interspersion of herbaceous and developed land, and population density were negatively correlated with incidence rates. Abundance of forest fragments less than 2 hectares in area was not significantly correlated. Our results support some findings of previous studies on ecological variables and Lyme disease in endemic areas, but other results have not been found in previous studies, highlighting the potential contribution of new variables as Lyme disease continues to emerge southward.

Spatial and temporal variability of sediment deposition on artificial-lawn traps in a floodplain of the River Elbe

Energy Technology Data Exchange (ETDEWEB)

Baborowski, M. [Department of River Ecology, Helmholtz Centre for Environmental Research - UFZ, Brueckstrasse 3a, 39114 Magdeburg (Germany)]. E-mail: martina.baborowski@ufz.de; Buettner, O. [Department of Lake Research, Helmholtz Centre for Environmental Research - UFZ, Brueckstrasse 3a, 39114 Magdeburg (Germany); Morgenstern, P. [Department of Analytical Chemistry, Helmholtz Centre for Environmental Research - UFZ, Permoserstrasse 15, 04318 Leipzig (Germany); Krueger, F. [ELANA Boden Wasser Monitoring, Dorfstrasse 55, 39615 Falkenberg (Germany); Lobe, I. [Department of River Ecology, Helmholtz Centre for Environmental Research - UFZ, Brueckstrasse 3a, 39114 Magdeburg (Germany); Rupp, H. [Department of Soil Physics, Helmholtz Centre for Environmental Research - UFZ, Dorfstrasse 55, 39615 Falkenberg (Germany); Tuempling, W. v. [Department of River Ecology, Helmholtz Centre for Environmental Research - UFZ, Brueckstrasse 3a, 39114 Magdeburg (Germany)

2007-08-15

Artificial-lawn mats were used as sediment traps in floodplains to measure sediment input and composition during flood events. To estimate the natural variability, 10 traps were installed during two flood waves at three different morphological units in a meander loop of the River Elbe. The geochemical composition of deposited and suspended matter was compared. The sediment input showed weak correlations with concentration and composition of river water. It also correlated poorly with flood duration and level as well as distance of trap position from the main river. This is due to the high variability of the inundation, different morphological conditions and the variability of sources. The composition of the deposits and the suspended matter in the river water was comparable. Hence, for the investigated river reach, the expected pollution of the floodplain sediments can be derived from the pollution of the suspended matter in the river during the flood wave. - The deposition of polluted sediments on floodplains is characterised by a high local variability.

Spatial and temporal variability of sediment deposition on artificial-lawn traps in a floodplain of the River Elbe

International Nuclear Information System (INIS)

Baborowski, M.; Buettner, O.; Morgenstern, P.; Krueger, F.; Lobe, I.; Rupp, H.; Tuempling, W. v.

2007-01-01

Artificial-lawn mats were used as sediment traps in floodplains to measure sediment input and composition during flood events. To estimate the natural variability, 10 traps were installed during two flood waves at three different morphological units in a meander loop of the River Elbe. The geochemical composition of deposited and suspended matter was compared. The sediment input showed weak correlations with concentration and composition of river water. It also correlated poorly with flood duration and level as well as distance of trap position from the main river. This is due to the high variability of the inundation, different morphological conditions and the variability of sources. The composition of the deposits and the suspended matter in the river water was comparable. Hence, for the investigated river reach, the expected pollution of the floodplain sediments can be derived from the pollution of the suspended matter in the river during the flood wave. - The deposition of polluted sediments on floodplains is characterised by a high local variability

Image scale measurement with correlation filters in a volume holographic optical correlator

Science.gov (United States)

Zheng, Tianxiang; Cao, Liangcai; He, Qingsheng; Jin, Guofan

2013-08-01

A search engine containing various target images or different part of a large scene area is of great use for many applications, including object detection, biometric recognition, and image registration. The input image captured in realtime is compared with all the template images in the search engine. A volume holographic correlator is one type of these search engines. It performs thousands of comparisons among the images at a super high speed, with the correlation task accomplishing mainly in optics. However, the inputted target image always contains scale variation to the filtering template images. At the time, the correlation values cannot properly reflect the similarity of the images. It is essential to estimate and eliminate the scale variation of the inputted target image. There are three domains for performing the scale measurement, as spatial, spectral and time domains. Most methods dealing with the scale factor are based on the spatial or the spectral domains. In this paper, a method with the time domain is proposed to measure the scale factor of the input image. It is called a time-sequential scaled method. The method utilizes the relationship between the scale variation and the correlation value of two images. It sends a few artificially scaled input images to compare with the template images. The correlation value increases and decreases with the increasing of the scale factor at the intervals of 0.8~1 and 1~1.2, respectively. The original scale of the input image can be measured by estimating the largest correlation value through correlating the artificially scaled input image with the template images. The measurement range for the scale can be 0.8~4.8. Scale factor beyond 1.2 is measured by scaling the input image at the factor of 1/2, 1/3 and 1/4, correlating the artificially scaled input image with the template images, and estimating the new corresponding scale factor inside 0.8~1.2.

Input saturation in nonlinear multivariable processes resolved by nonlinear decoupling

Directory of Open Access Journals (Sweden)

Jens G. Balchen

1995-04-01

Full Text Available A new method is presented for the resolution of the problem of input saturation in nonlinear multivariable process control by means of elementary nonlinear decoupling (END. Input saturation can have serious consequences particularly in multivariable control because it may lead to very undesirable system behaviour and quite often system instability. Many authors have searched for systematic techniques for designing multivariable control systems in which saturation may occur in any of the control variables (inputs, manipulated variables. No generally accepted method seems to have been presented so far which gives a solution in closed form. The method of elementary nonlinear decoupling (END can be applied directly to the case of saturation control variables by deriving as many control strategies as there are combinations of saturating control variables. The method is demonstrated by the multivariable control of a simulated Fluidized Catalytic Cracker (FCC with very convincing results.

Heart Rate Variability Correlates to Functional Aerobic Impairment in Hemodialysis Patients

Directory of Open Access Journals (Sweden)

Maria Angela Magalhães de Queiroz Carreira

2015-06-01

Full Text Available Background: Autonomic dysfunction (AD is highly prevalent in hemodialysis (HD patients and has been implicated in their increased risk of cardiovascular mortality. Objective: To correlate heart rate variability (HRV during exercise treadmill test (ETT with the values obtained when measuring functional aerobic impairment (FAI in HD patients and controls. Methods: Cross-sectional study involving HD patients and a control group. Clinical examination, blood sampling, transthoracic echocardiogram, 24-hour Holter, and ETT were performed. A symptom-limited ramp treadmill protocol with active recovery was employed. Heart rate variability was evaluated in time domain at exercise and recovery periods. Results: Forty-one HD patients and 41 controls concluded the study. HD patients had higher FAI and lower HRV than controls (p<0.001 for both. A correlation was found between exercise HRV (SDNN and FAI in both groups. This association was independent of age, sex, smoking, body mass index, diabetes, and clonidine or beta-blocker use, but not of hemoglobin levels. Conclusion: No association was found between FAI and HRV on 24-hour Holter or at the recovery period of ETT. Of note, exercise HRV was inversely correlated with FAI in HD patients and controls. (Arq Bras Cardiol. 2015; [online]. ahead print, PP.0-0

Intraclass Correlation Coefficients in Hierarchical Designs: Evaluation Using Latent Variable Modeling

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Raykov, Tenko

2011-01-01

Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…

Automatic individual arterial input functions calculated from PCA outperform manual and population-averaged approaches for the pharmacokinetic modeling of DCE-MR images.

Science.gov (United States)

Sanz-Requena, Roberto; Prats-Montalbán, José Manuel; Martí-Bonmatí, Luis; Alberich-Bayarri, Ángel; García-Martí, Gracián; Pérez, Rosario; Ferrer, Alberto

2015-08-01

To introduce a segmentation method to calculate an automatic arterial input function (AIF) based on principal component analysis (PCA) of dynamic contrast enhanced MR (DCE-MR) imaging and compare it with individual manually selected and population-averaged AIFs using calculated pharmacokinetic parameters. The study included 65 individuals with prostate examinations (27 tumors and 38 controls). Manual AIFs were individually extracted and also averaged to obtain a population AIF. Automatic AIFs were individually obtained by applying PCA to volumetric DCE-MR imaging data and finding the highest correlation of the PCs with a reference AIF. Variability was assessed using coefficients of variation and repeated measures tests. The different AIFs were used as inputs to the pharmacokinetic model and correlation coefficients, Bland-Altman plots and analysis of variance tests were obtained to compare the results. Automatic PCA-based AIFs were successfully extracted in all cases. The manual and PCA-based AIFs showed good correlation (r between pharmacokinetic parameters ranging from 0.74 to 0.95), with differences below the manual individual variability (RMSCV up to 27.3%). The population-averaged AIF showed larger differences (r from 0.30 to 0.61). The automatic PCA-based approach minimizes the variability associated to obtaining individual volume-based AIFs in DCE-MR studies of the prostate. © 2014 Wiley Periodicals, Inc.

READDATA: a FORTRAN 77 codeword input package

International Nuclear Information System (INIS)

Lander, P.A.

1983-07-01

A new codeword input package has been produced as a result of the incompatibility between different dialects of FORTRAN, especially when character variables are passed as parameters. This report is for those who wish to use a codeword input package with FORTRAN 77. The package, called ''Readdata'', attempts to combine the best features of its predecessors such as BINPUT and pseudo-BINPUT. (author)

Tritium Records to Trace Stratospheric Moisture Inputs in Antarctica

Science.gov (United States)

Fourré, E.; Landais, A.; Cauquoin, A.; Jean-Baptiste, P.; Lipenkov, V.; Petit, J.-R.

2018-03-01

Better assessing the dynamic of stratosphere-troposphere exchange is a key point to improve our understanding of the climate dynamic in the East Antarctica Plateau, a region where stratospheric inputs are expected to be important. Although tritium (3H or T), a nuclide naturally produced mainly in the stratosphere and rapidly entering the water cycle as HTO, seems a first-rate tracer to study these processes, tritium data are very sparse in this region. We present the first high-resolution measurements of tritium concentration over the last 50 years in three snow pits drilled at the Vostok station. Natural variability of the tritium records reveals two prominent frequencies, one at about 10 years (to be related to the solar Schwabe cycles) and the other one at a shorter periodicity: despite dating uncertainty at this short scale, a good correlation is observed between 3H and Na+ and an anticorrelation between 3H and δ18O measured on an individual pit. The outputs from the LMDZ Atmospheric General Circulation Model including stable water isotopes and tritium show the same 3H-δ18O anticorrelation and allow further investigation on the associated mechanism. At the interannual scale, the modeled 3H variability matches well with the Southern Annular Mode index. At the seasonal scale, we show that modeled stratospheric tritium inputs in the troposphere are favored in winter cold and dry conditions.

Correlation Between Fracture Network Properties and Stress Variability in Geological Media

Science.gov (United States)

Lei, Qinghua; Gao, Ke

2018-05-01

We quantitatively investigate the stress variability in fractured geological media under tectonic stresses. The fracture systems studied include synthetic fracture networks following power law length scaling and natural fracture patterns based on outcrop mapping. The stress field is derived from a finite-discrete element model, and its variability is analyzed using a set of mathematical formulations that honor the tensorial nature of stress data. We show that local stress perturbation, quantified by the Euclidean distance of a local stress tensor to the mean stress tensor, has a positive, linear correlation with local fracture intensity, defined as the total fracture length per unit area within a local sampling window. We also evaluate the stress dispersion of the entire stress field using the effective variance, that is, a scalar-valued measure of the overall stress variability. The results show that a well-connected fracture system under a critically stressed state exhibits strong local and global stress variabilities.

Performance analysis of MIMO wireless optical communication system with Q-ary PPM over correlated log-normal fading channel

Science.gov (United States)

Wang, Huiqin; Wang, Xue; Lynette, Kibe; Cao, Minghua

2018-06-01

The performance of multiple-input multiple-output wireless optical communication systems that adopt Q-ary pulse position modulation over spatial correlated log-normal fading channel is analyzed in terms of its un-coded bit error rate and ergodic channel capacity. The analysis is based on the Wilkinson's method which approximates the distribution of a sum of correlated log-normal random variables to a log-normal random variable. The analytical and simulation results corroborate the increment of correlation coefficients among sub-channels lead to system performance degradation. Moreover, the receiver diversity has better performance in resistance of spatial correlation caused channel fading.

Air pollution forecast in cities by an air pollution index highly correlated with meteorological variables

International Nuclear Information System (INIS)

Cogliani, E.

2001-01-01

There are many different air pollution indexes which represent the global urban air pollution situation. The daily index studied here is also highly correlated with meteorological variables and this index is capable of identifying those variables that significantly affect the air pollution. The index is connected with attention levels of NO 2 , CO and O 3 concentrations. The attention levels are fixed by a law proposed by the Italian Ministries of Health and Environment. The relation of that index with some meteorological variables is analysed by the linear multiple partial correlation statistical method. Florence, Milan and Vicence were selected to show the correlation among the air pollution index and the daily thermic excursion, the previous day's air pollution index and the wind speed. During the January-March period the correlation coefficient reaches 0.85 at Milan. The deterministic methods of forecasting air pollution concentrations show very high evaluation errors and are applied on limited areas around the observation stations, as opposed to the whole urban areas. The global air pollution, instead of the concentrations at specific observation stations, allows the evaluation of the level of the sanitary risk regarding the whole urban population. (Author)

Lithium inputs to subduction zones

NARCIS (Netherlands)

Bouman, C.; Elliott, T.R.; Vroon, P.Z.

2004-01-01

We have studied the sedimentary and basaltic inputs of lithium to subduction zones. Various sediments from DSDP and ODP drill cores in front of the Mariana, South Sandwich, Banda, East Sunda and Lesser Antilles island arcs have been analysed and show highly variable Li contents and δ

The human motor neuron pools receive a dominant slow‐varying common synaptic input

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Negro, Francesco; Yavuz, Utku Şükrü

2016-01-01

Key points Motor neurons in a pool receive both common and independent synaptic inputs, although the proportion and role of their common synaptic input is debated.Classic correlation techniques between motor unit spike trains do not measure the absolute proportion of common input and have limitations as a result of the non‐linearity of motor neurons.We propose a method that for the first time allows an accurate quantification of the absolute proportion of low frequency common synaptic input (60%) of common input, irrespective of their different functional and control properties.These results increase our knowledge about the role of common and independent input to motor neurons in force control. Abstract Motor neurons receive both common and independent synaptic inputs. This observation is classically based on the presence of a significant correlation between pairs of motor unit spike trains. The functional significance of different relative proportions of common input across muscles, individuals and conditions is still debated. One of the limitations in our understanding of correlated input to motor neurons is that it has not been possible so far to quantify the absolute proportion of common input with respect to the total synaptic input received by the motor neurons. Indeed, correlation measures of pairs of output spike trains only allow for relative comparisons. In the present study, we report for the first time an approach for measuring the proportion of common input in the low frequency bandwidth (60%) proportion of common low frequency oscillations with respect to their total synaptic input. These results suggest that the central nervous system provides a large amount of common input to motor neuron pools, in a similar way to that for muscles with different functional and control properties. PMID:27151459

Uncertainty correlation in stochastic safety analysis of natural circulation decay heat removal of liquid metal reactor

International Nuclear Information System (INIS)

Takata, Takashi; Yamaguchi, Akira

2009-01-01

Since various uncertainties of input variables are involved and nonlinearly-correlated in the Best Estimate (BE) plant dynamics code, it is of importance to evaluate the importance of input uncertainty to the computational results and to estimate the accuracy of the confidence level of the results. In order to estimate the importance and the accuracy, the authors have applied the stochastic safety analysis procedure using the Latin Hypercube sampling method to Liquid Metal Reactor (LMR) natural circulation Decay Heat Removal (DHR) phenomenon in the present paper. 17 input variables are chosen for the analyses and 5 influential variables, which affect the maximum coolant temperature at the core in a short period of time (several tens seconds), are selected to investigate the importance by comparing with the full-scope parametric analysis. As a result, it has been demonstrated that a comparative small number of samples is sufficient enough to estimate the dominant input variable and the confidence level. Furthermore, the influence of the sampling method on the accuracy of the upper tolerance limit (confidence level of 95%) has been examined based on the Wilks' formula. (author)

Handwriting generates variable visual input to facilitate symbol learning

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Li, Julia X.; James, Karin H.

2015-01-01

Recent research has demonstrated that handwriting practice facilitates letter categorization in young children. The present experiments investigated why handwriting practice facilitates visual categorization by comparing two hypotheses: That handwriting exerts its facilitative effect because of the visual-motor production of forms, resulting in a direct link between motor and perceptual systems, or because handwriting produces variable visual instances of a named category in the environment that then changes neural systems. We addressed these issues by measuring performance of 5 year-old children on a categorization task involving novel, Greek symbols across 6 different types of learning conditions: three involving visual-motor practice (copying typed symbols independently, tracing typed symbols, tracing handwritten symbols) and three involving visual-auditory practice (seeing and saying typed symbols of a single typed font, of variable typed fonts, and of handwritten examples). We could therefore compare visual-motor production with visual perception both of variable and similar forms. Comparisons across the six conditions (N=72) demonstrated that all conditions that involved studying highly variable instances of a symbol facilitated symbol categorization relative to conditions where similar instances of a symbol were learned, regardless of visual-motor production. Therefore, learning perceptually variable instances of a category enhanced performance, suggesting that handwriting facilitates symbol understanding by virtue of its environmental output: supporting the notion of developmental change though brain-body-environment interactions. PMID:26726913

A probabilistic graphical model based stochastic input model construction

International Nuclear Information System (INIS)

Wan, Jiang; Zabaras, Nicholas

2014-01-01

Model reduction techniques have been widely used in modeling of high-dimensional stochastic input in uncertainty quantification tasks. However, the probabilistic modeling of random variables projected into reduced-order spaces presents a number of computational challenges. Due to the curse of dimensionality, the underlying dependence relationships between these random variables are difficult to capture. In this work, a probabilistic graphical model based approach is employed to learn the dependence by running a number of conditional independence tests using observation data. Thus a probabilistic model of the joint PDF is obtained and the PDF is factorized into a set of conditional distributions based on the dependence structure of the variables. The estimation of the joint PDF from data is then transformed to estimating conditional distributions under reduced dimensions. To improve the computational efficiency, a polynomial chaos expansion is further applied to represent the random field in terms of a set of standard random variables. This technique is combined with both linear and nonlinear model reduction methods. Numerical examples are presented to demonstrate the accuracy and efficiency of the probabilistic graphical model based stochastic input models. - Highlights: • Data-driven stochastic input models without the assumption of independence of the reduced random variables. • The problem is transformed to a Bayesian network structure learning problem. • Examples are given in flows in random media

Simulation model structure numerically robust to changes in magnitude and combination of input and output variables

DEFF Research Database (Denmark)

Rasmussen, Bjarne D.; Jakobsen, Arne

1999-01-01

Mathematical models of refrigeration systems are often based on a coupling of component models forming a “closed loop” type of system model. In these models the coupling structure of the component models represents the actual flow path of refrigerant in the system. Very often numerical...... instabilities prevent the practical use of such a system model for more than one input/output combination and for other magnitudes of refrigerating capacities.A higher numerical robustness of system models can be achieved by making a model for the refrigeration cycle the core of the system model and by using...... variables with narrow definition intervals for the exchange of information between the cycle model and the component models.The advantages of the cycle-oriented method are illustrated by an example showing the refrigeration cycle similarities between two very different refrigeration systems....

An input feature selection method applied to fuzzy neural networks for signal esitmation

International Nuclear Information System (INIS)

Na, Man Gyun; Sim, Young Rok

2001-01-01

It is well known that the performance of a fuzzy neural networks strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output. As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural networks and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PAC), genetic algorithms (GA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods

Correlation of iodine uptake and perfusion parameters between dual-energy CT imaging and first-pass dual-input perfusion CT in lung cancer.

Science.gov (United States)

Chen, Xiaoliang; Xu, Yanyan; Duan, Jianghui; Li, Chuandong; Sun, Hongliang; Wang, Wu

2017-07-01

To investigate the potential relationship between perfusion parameters from first-pass dual-input perfusion computed tomography (DI-PCT) and iodine uptake levels estimated from dual-energy CT (DE-CT).The pre-experimental part of this study included a dynamic DE-CT protocol in 15 patients to evaluate peak arterial enhancement of lung cancer based on time-attenuation curves, and the scan time of DE-CT was determined. In the prospective part of the study, 28 lung cancer patients underwent whole-volume perfusion CT and single-source DE-CT using 320-row CT. Pulmonary flow (PF, mL/min/100 mL), aortic flow (AF, mL/min/100 mL), and a perfusion index (PI = PF/[PF + AF]) were automatically generated by in-house commercial software using the dual-input maximum slope method for DI-PCT. For the dual-energy CT data, iodine uptake was estimated by the difference (λ) and the slope (λHU). λ was defined as the difference of CT values between 40 and 70 KeV monochromatic images in lung lesions. λHU was calculated by the following equation: λHU = |λ/(70 - 40)|. The DI-PCT and DE-CT parameters were analyzed by Pearson/Spearman correlation analysis, respectively.All subjects were pathologically proved as lung cancer patients (including 16 squamous cell carcinoma, 8 adenocarcinoma, and 4 small cell lung cancer) by surgery or CT-guided biopsy. Interobserver reproducibility in DI-PCT (PF, AF, PI) and DE-CT (λ, λHU) were relatively good to excellent (intraclass correlation coefficient [ICC]Inter = 0.8726-0.9255, ICCInter = 0.8179-0.8842; ICCInter = 0.8881-0.9177, ICCInter = 0.9820-0.9970, ICCInter = 0.9780-0.9971, respectively). Correlation coefficient between λ and AF, and PF were as follows: 0.589 (P input CT perfusion analysis method can be applied to assess blood supply of lung cancer patients. Preliminary results demonstrated that the iodine uptake relevant parameters derived from DE-CT significantly correlated with perfusion

Correlation of Metabolic Variables with the Number of ORFs in Human Pathogenic and Phylogenetically Related Non- or Less-Pathogenic Bacteria.

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Brambila-Tapia, Aniel Jessica Leticia; Poot-Hernández, Augusto Cesar; Garcia-Guevara, Jose Fernando; Rodríguez-Vázquez, Katya

2016-06-01

To date, a few works have performed a correlation of metabolic variables in bacteria; however specific correlations with these variables have not been reported. In this work, we included 36 human pathogenic bacteria and 18 non- or less-pathogenic-related bacteria and obtained all metabolic variables, including enzymes, metabolic pathways, enzymatic steps and specific metabolic pathways, and enzymatic steps of particular metabolic processes, from a reliable metabolic database (KEGG). Then, we correlated the number of the open reading frames (ORF) with these variables and with the proportions of these variables, and we observed a negative correlation with the proportion of enzymes (r = -0.506, p < 0.0001), metabolic pathways (r = -0.871, p < 00.0001), enzymatic reactions (r = -0.749, p < 00.0001), and with the proportions of central metabolism variables as well as a positive correlation with the proportions of multistep reactions (r = 0.650, p < 00.0001) and secondary metabolism variables. The proportion of multifunctional reactions (r: -0.114, p = 0.41) and the proportion of enzymatic steps (r: -0.205, p = 0.14) did not present a significant correlation. These correlations indicate that as the size of a genome (measured in the number of ORFs) increases, the proportion of genes that encode enzymes significantly diminishes (especially those related to central metabolism), suggesting that when essential metabolic pathways are complete, an increase in the number of ORFs does not require a similar increase in the metabolic pathways and enzymes, but only a slight increase is sufficient to cope with a large genome.

Pearson's Correlation between Three Variables; Using Students' Basic Knowledge of Geometry for an Exercise in Mathematical Statistics

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Vos, Pauline

2009-01-01

When studying correlations, how do the three bivariate correlation coefficients between three variables relate? After transforming Pearson's correlation coefficient r into a Euclidean distance, undergraduate students can tackle this problem using their secondary school knowledge of geometry (Pythagoras' theorem and similarity of triangles).…

Correlation of mRNA Expression and Signal Variability in Chronic Intracortical Electrodes.

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Falcone, Jessica D; Carroll, Sheridan L; Saxena, Tarun; Mandavia, Dev; Clark, Alexus; Yarabarla, Varun; Bellamkonda, Ravi V

2018-01-01

The goal for this research was to identify molecular mechanisms that explain animal-to-animal variability in chronic intracortical recordings. Microwire electrodes were implanted into Sprague Dawley rats at an acute (1 week) and a chronic (14 weeks) time point. Weekly recordings were conducted, and action potentials were evoked in the barrel cortex by deflecting the rat's whiskers. At 1 and 14 weeks, tissue was collected, and mRNA was extracted. mRNA expression was compared between 1 and 14 weeks using a high throughput multiplexed qRT-PCR. Pearson correlation coefficients were calculated between mRNA expression and signal-to-noise ratios at 14 weeks. At 14 weeks, a positive correlation between signal-to-noise ratio (SNR) and NeuN and GFAP mRNA expression was observed, indicating a relationship between recording strength and neuronal population, as well as reactive astrocyte activity. The inflammatory state around the electrode interface was evaluated using M1-like and M2-like markers. Expression for both M1-like and M2-like mRNA markers remained steady from 1 to 14 weeks. Anti-inflammatory markers, CD206 and CD163, however, demonstrated a significant positive correlation with SNR quality at 14 weeks. VE-cadherin, a marker for adherens junctions, and PDGFR-β, a marker for pericytes, both partial representatives of blood-brain barrier health, had a positive correlation with SNR at 14 weeks. Endothelial adhesion markers revealed a significant increase in expression at 14 weeks, while CD45, a pan-leukocyte marker, significantly decreased at 14 weeks. No significant correlation was found for either the endothelial adhesion or pan-leukocyte markers. A positive correlation between anti-inflammatory and blood-brain barrier health mRNA markers with electrophysiological efficacy of implanted intracortical electrodes has been demonstrated. These data reveal potential mechanisms for further evaluation to determine potential target mechanisms to improve

Variability of concrete properties: experimental characterisation and probabilistic modelling for calcium leaching

International Nuclear Information System (INIS)

De Larrard, Th.

2010-09-01

Evaluating structures durability requires taking into account the variability of material properties. The thesis has two main aspects: on the one hand, an experimental campaign aimed at quantifying the variability of many indicators of concrete behaviour; on the other hand, a simple numerical model for calcium leaching is developed in order to implement probabilistic methods so as to estimate the lifetime of structures such as those related to radioactive waste disposal. The experimental campaign consisted in following up two real building sites, and quantifying the variability of these indicators, studying their correlation, and characterising the random fields variability for the considered variables (especially the correlation length). To draw any conclusion from the accelerated leaching tests with ammonium nitrate by overcoming the effects of temperature, an inverse analysis tool based on the theory of artificial neural networks was developed. Simple numerical tools are presented to investigate the propagation of variability in durability issues, quantify the influence of this variability on the lifespan of structures and explain the variability of the input parameters of the numerical model and the physical measurable quantities of the material. (author)

Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

Science.gov (United States)

Morelli, Eugene A.; Klein, Vladislav

1990-01-01

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

Science.gov (United States)

Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

2018-05-01

Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

Variability of consumer impacts from energy efficiency standards

Energy Technology Data Exchange (ETDEWEB)

McMahon, James E.; Liu, Xiaomin

2000-06-15

A typical prospective analysis of the expected impact of energy efficiency standards on consumers is based on average economic conditions (e.g., energy price) and operating characteristics. In fact, different consumers face different economic conditions and exhibit different behaviors when using an appliance. A method has been developed to characterize the variability among individual households and to calculate the life-cycle cost of appliances taking into account those differences. Using survey data, this method is applied to a distribution of consumers representing the U.S. Examples of clothes washer standards are shown for which 70-90% of the population benefit, compared to 10-30% who are expected to bear increased costs due to new standards. In some cases, sufficient data exist to distinguish among demographic subgroups (for example, low income or elderly households) who are impacted differently from the general population. Rank order correlations between the sampled input distributions and the sampled output distributions are calculated to determine which variability inputs are main factors. This ''importance analysis'' identifies the key drivers contributing to the range of results. Conversely, the importance analysis identifies variables that, while uncertain, make so little difference as to be irrelevant in deciding a particular policy. Examples will be given from analysis of water heaters to illustrate the dominance of the policy implications by a few key variables.

Quantum correlation games

International Nuclear Information System (INIS)

Iqbal, Azhar; Weigert, Stefan

2004-01-01

A new approach to play games quantum mechanically is proposed. We consider two players who perform measurements in an EPR-type setting. The payoff relations are defined as functions of correlations, i.e. without reference to classical or quantum mechanics. Classical bi-matrix games are reproduced if the input states are classical and perfectly anti-correlated, that is, for a classical correlation game. However, for a quantum correlation game, with an entangled singlet state as input, qualitatively different solutions are obtained. For example, the Prisoners' Dilemma acquires a Nash equilibrium if both players apply a mixed strategy. It appears to be conceptually impossible to reproduce the properties of quantum correlation games within the framework of classical games

A Parallel Approach in Computing Correlation Immunity up to Six Variables

Science.gov (United States)

2015-07-24

failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 23 JUL 2015 2. REPORT TYPE...second step, we specify that a condition hold across all assignments of values to the variables chosen in the first step. For pedagogical reasons, we could...table of the function whose correlation immunity is currently being computed. When this circuit is used in exhaustive enumeration, the Function

Synchronization properties of coupled chaotic neurons: The role of random shared input

International Nuclear Information System (INIS)

Kumar, Rupesh; Bilal, Shakir; Ramaswamy, Ram

2016-01-01

Spike-time correlations of neighbouring neurons depend on their intrinsic firing properties as well as on the inputs they share. Studies have shown that periodically firing neurons, when subjected to random shared input, exhibit asynchronicity. Here, we study the effect of random shared input on the synchronization of weakly coupled chaotic neurons. The cases of so-called electrical and chemical coupling are both considered, and we observe a wide range of synchronization behaviour. When subjected to identical shared random input, there is a decrease in the threshold coupling strength needed for chaotic neurons to synchronize in-phase. The system also supports lag–synchronous states, and for these, we find that shared input can cause desynchronization. We carry out a master stability function analysis for a network of such neurons and show agreement with the numerical simulations. The contrasting role of shared random input for complete and lag synchronized neurons is useful in understanding spike-time correlations observed in many areas of the brain.

Synchronization properties of coupled chaotic neurons: The role of random shared input

Energy Technology Data Exchange (ETDEWEB)

Kumar, Rupesh [School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067 (India); Bilal, Shakir [Department of Physics and Astrophysics, University of Delhi, Delhi 110 007 (India); Ramaswamy, Ram [School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi 110067 (India); School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067 (India)

2016-06-15

Spike-time correlations of neighbouring neurons depend on their intrinsic firing properties as well as on the inputs they share. Studies have shown that periodically firing neurons, when subjected to random shared input, exhibit asynchronicity. Here, we study the effect of random shared input on the synchronization of weakly coupled chaotic neurons. The cases of so-called electrical and chemical coupling are both considered, and we observe a wide range of synchronization behaviour. When subjected to identical shared random input, there is a decrease in the threshold coupling strength needed for chaotic neurons to synchronize in-phase. The system also supports lag–synchronous states, and for these, we find that shared input can cause desynchronization. We carry out a master stability function analysis for a network of such neurons and show agreement with the numerical simulations. The contrasting role of shared random input for complete and lag synchronized neurons is useful in understanding spike-time correlations observed in many areas of the brain.

Burst firing enhances neural output correlation

Directory of Open Access Journals (Sweden)

Ho Ka eChan

2016-05-01

Full Text Available Neurons communicate and transmit information predominantly through spikes. Given that experimentally observed neural spike trains in a variety of brain areas can be highly correlated, it is important to investigate how neurons process correlated inputs. Most previous work in this area studied the problem of correlation transfer analytically by making significant simplifications on neural dynamics. Temporal correlation between inputs that arises from synaptic filtering, for instance, is often ignored when assuming that an input spike can at most generate one output spike. Through numerical simulations of a pair of leaky integrate-and-fire (LIF neurons receiving correlated inputs, we demonstrate that neurons in the presence of synaptic filtering by slow synapses exhibit strong output correlations. We then show that burst firing plays a central role in enhancing output correlations, which can explain the above-mentioned observation because synaptic filtering induces bursting. The observed changes of correlations are mostly on a long time scale. Our results suggest that other features affecting the prevalence of neural burst firing in biological neurons, e.g., adaptive spiking mechanisms, may play an important role in modulating the overall level of correlations in neural networks.

Correlations between respiratory and functional variables in heart failure

Directory of Open Access Journals (Sweden)

Fábio Cangeri Di Naso

2009-09-01

Full Text Available Background: Respiratory alterations can impact on the functional performance of patients with heart failure. Aim: To correlate maximum inspiratory muscular force and lung function variables with functional capacity in heart failure patients. Methods: A transversal study January-July 2007 with 42 chronic heart disease patients (28 males with no prior pulmonary illness. The patients were in New York Heart Association Functional Class I, II and III. The variables used were maximum inspiratory pressure, forced vital capacity and forced expiratory volume in the first second. Respiratory variables measured were distance covered in the six-minute walk test, NYHA functional class and the physical functioning domain of the Short Form-36 Quality of Life Questionnaire. Results: Maximum inspiratory pressure correlated with the six-minute walk test (r = 0.543 and p < 0.001, functional capacity (r = −0.566 and p < 0.001 and the physical functioning domain score of the Short Form-36 (r = 0.459 and p = 0.002. The same was true of forced vital capacity and the six-minute walk test (r = 0.501 and p = 0.001, functional capacity (r = −0.477 and p = 0.001 and Short Form-36 (r = 0.314 and p = 0.043 variables. Forced expiratory volume correlated with the distance covered in the six-minute walk test (r = 0.514 and p < 0.001 and functional capacity (r = −0.383 and p = 0.012. Conclusion: Lung function and inspiratory muscular force respiratory variables correlated with functional variables in patients with heart failure. Resumo: Fundamento: Alterações respiratórias podem influenciar o desempenho funcional em doentes com insuficiência cardíaca (IC. Objectivo: Correlacionar a força muscular inspiratória máxima (PImax e as variáveis da função pulmonar com a capacidade funcional em doentes com IC. Métodos: Estudo transversal

Variability Properties of Four Million Sources in the TESS Input Catalog Observed with the Kilodegree Extremely Little Telescope Survey

Science.gov (United States)

Oelkers, Ryan J.; Rodriguez, Joseph E.; Stassun, Keivan G.; Pepper, Joshua; Somers, Garrett; Kafka, Stella; Stevens, Daniel J.; Beatty, Thomas G.; Siverd, Robert J.; Lund, Michael B.; Kuhn, Rudolf B.; James, David; Gaudi, B. Scott

2018-01-01

The Kilodegree Extremely Little Telescope (KELT) has been surveying more than 70% of the celestial sphere for nearly a decade. While the primary science goal of the survey is the discovery of transiting, large-radii planets around bright host stars, the survey has collected more than 106 images, with a typical cadence between 10–30 minutes, for more than four million sources with apparent visual magnitudes in the approximate range 7TESS Input catalog and the AAVSO Variable Star Index to precipitate the follow-up and classification of each source. The catalog is maintained as a living database on the Filtergraph visualization portal at the URL https://filtergraph.com/kelt_vars.

Sleep pattern in patients with Chronic Obstructive Pulmonary Disease and correlation among gasometric, spirometric, and polysomnographic variables

Directory of Open Access Journals (Sweden)

Santos Carlos Eduardo Ventura Gaio dos

2003-01-01

Full Text Available OBJECTIVE: There are few studies on chronic obstructive pulmonary disease (COPD establishing differences between the functional parameters of the disease and sleep variables. The aim of the study was to describe the sleep pattern of these patients and to correlate spirometric, gasometric and polysomnographic variables. METHODS: Transversal study using COPD patients submitted to spirometry, arterial gasometry, and polysomnography. RESULTS: 21 male patients were studied with average age = 67 ± 9; 7 ± 4 average points in the Epworth sleepiness scale, average Tiffenau's index (FEV1/FVC = 54 ± 13.0%, average PaO2 = 68 ± 11 mmHg, average PaCO2 = 37 ± 6 mmHg. Sleep efficiency decreased (65 ± 16% with the reduction of slow wave sleep (8 ± 9% and rapid eye movement (REM sleep (15 ± 8%. Average T90 was 43 ± 41%. Average apnea-hypopnea index (AHI = 3 ± 5/h, where two patients (9.5% presented obstructive sleep apnea. A significant correlation was observed between PaO2 and T90 (p < 0.01, PaCO2 and T90 (p < 0.05, and AHI and the cardiac rate during REM (p < 0.01. A higher number of arousals and stage change was observed. There was no linear correlation between spirometric and polysomnographic variables. CONCLUSION: Poor sleep quality of these patients was characterized by low sleep efficiency, high number of awakenings and shift of stages. There were no correlations between the spirometric and polysomnographic variables.

Personality Traits and Socio-Demographic Variables as Correlates of Counselling Effectiveness of Counsellors in Enugu State, Nigeria

Science.gov (United States)

Onyekuru, Bruno U.; Ibegbunam, Josephat

2015-01-01

Quality personality traits and socio-demographic variables are essential elements of effective counselling. This correlational study investigated personality traits and socio-demographic variables as predictors of counselling effectiveness of counsellors in Enugu State. The instruments for data collection were Personality Traits Assessment Scale…

Amplification factor variable amplifier

NARCIS (Netherlands)

Akitsugu, Oshita; Nauta, Bram

2007-01-01

PROBLEM TO BE SOLVED: To provide an amplification factor variable amplifier capable of achieving temperature compensation of an amplification factor over a wide variable amplification factor range. ; SOLUTION: A Gilbert type amplification factor variable amplifier 11 amplifies an input signal and

Identification of input variables for feature based artificial neural networks-saccade detection in EOG recordings.

Science.gov (United States)

Tigges, P; Kathmann, N; Engel, R R

1997-07-01

Though artificial neural networks (ANN) are excellent tools for pattern recognition problems when signal to noise ratio is low, the identification of decision relevant features for ANN input data is still a crucial issue. The experience of the ANN designer and the existing knowledge and understanding of the problem seem to be the only links for a specific construction. In the present study a backpropagation ANN based on modified raw data inputs showed encouraging results. Investigating the specific influences of prototypical input patterns on a specially designed ANN led to a new sparse and efficient input data presentation. This data coding obtained by a semiautomatic procedure combining existing expert knowledge and the internal representation structures of the raw data based ANN yielded a list of feature vectors, each representing the relevant information for saccade identification. The feature based ANN produced a reduction of the error rate of nearly 40% compared with the raw data ANN. An overall correct classification of 92% of so far unknown data was realized. The proposed method of extracting internal ANN knowledge for the production of a better input data representation is not restricted to EOG recordings, and could be used in various fields of signal analysis.

Flow variability and hillslope hydrology

Energy Technology Data Exchange (ETDEWEB)

Huff, D D; O' Neill, R V; Emanuel, W R; Elwood, J W; Newbold, J D

1982-01-01

Examination of spatial variability of streamflow in headwater areas can provide important insight about factors that influence hillslope hydrology. Detailed observations of variations in stream channel input, based on a tracer experiment, indicate that topography alone cannot explain flow variability. However, determination of changes in channel input on a small spatial scale can provide valuable clues to factors, such as structural geology that control subsurface flows.

Quantum cryptography with a predetermined key, using continuous-variable Einstein-Podolsky-Rosen correlations

Science.gov (United States)

Reid, M. D.

2000-12-01

Correlations of the type discussed by EPR in their original 1935 paradox for continuous variables exist for the quadrature phase amplitudes of two spatially separated fields. These correlations were first experimentally reported in 1992. We propose to use such EPR beams in quantum cryptography, to transmit with high efficiency messages in such a way that the receiver and sender may later determine whether eavesdropping has occurred. The merit of the new proposal is in the possibility of transmitting a reasonably secure yet predetermined key. This would allow relay of a cryptographic key over long distances in the presence of lossy channels.

Amplification factor variable amplifier

NARCIS (Netherlands)

Akitsugu, Oshita; Nauta, Bram

2010-01-01

PROBLEM TO BE SOLVED: To provide an amplification factor variable amplifier capable of achieving temperature compensation of an amplification factor over a wide variable amplification factor range. ;SOLUTION: A Gilbert type amplification factor variable amplifier 11 amplifies an input signal and can

Topic Correlation Analysis for Bearing Fault Diagnosis Under Variable Operating Conditions

Science.gov (United States)

Chen, Chao; Shen, Fei; Yan, Ruqiang

2017-05-01

This paper presents a Topic Correlation Analysis (TCA) based approach for bearing fault diagnosis. In TCA, Joint Mixture Model (JMM), a model which adapts Probability Latent Semantic Analysis (PLSA), is constructed first. Then, JMM models the shared and domain-specific topics using “fault vocabulary” . After that, the correlations between two kinds of topics are computed and used to build a mapping matrix. Furthermore, a new shared space spanned by the shared and mapped domain-specific topics is set up where the distribution gap between different domains is reduced. Finally, a classifier is trained with mapped features which follow a different distribution and then the trained classifier is tested on target bearing data. Experimental results justify the superiority of the proposed approach over the stat-of-the-art baselines and it can diagnose bearing fault efficiently and effectively under variable operating conditions.

In-process tool rotational speed variation with constant heat input in friction stir welding of AZ31 sheets with variable thickness

Science.gov (United States)

Buffa, Gianluca; Campanella, Davide; Forcellese, Archimede; Fratini, Livan; Simoncini, Michela

2017-10-01

In the present work, friction stir welding experiments on AZ31 magnesium alloy sheets, characterized by a variable thickness along the welding line, were carried out. The approach adapted during welding consisted in maintaining constant the heat input to the joint. To this purpose, the rotational speed of the pin tool was increased with decreasing thickness and decreased with increasing thickness in order to obtain the same temperatures during welding. The amount by which the rotational speed was changed as a function of the sheet thickness was defined on the basis of the results given by FEM simulations of the FSW process. Finally, the effect of the in-process variation of the tool rotational speed on the mechanical and microstructural properties of FSWed joints was analysed by comparing both the nominal stress vs. nominal strain curves and microstructure of FSWed joints obtained in different process conditions. It was observed that FSW performed by keeping constant the heat input to the joint leads to almost coincident results both in terms of the curve shape, ultimate tensile strength and ultimate elongation values, and microstructure.

The Einstein-Podolsky-Rosen Paradox and Entanglement 1: Signatures of EPR correlations for continuous variables

OpenAIRE

Reid, M. D.

2001-01-01

A generalization of the 1935 Einstein-Podolsky-Rosen (EPR) argument for measurements with continuous variable outcomes is presented to establish criteria for the demonstration of the EPR paradox, for situations where the correlation between spatially separated subsystems is not perfect. Two types of criteria for EPR correlations are determined. The first type are based on measurements of the variances of conditional probability distributions and are necessary to reflect directly the situation...

A new chance-constrained DEA model with birandom input and output data

OpenAIRE

Tavana, M.; Shiraz, R. K.; Hatami-Marbini, A.

2013-01-01

The purpose of conventional Data Envelopment Analysis (DEA) is to evaluate the performance of a set of firms or Decision-Making Units using deterministic input and output data. However, the input and output data in the real-life performance evaluation problems are often stochastic. The stochastic input and output data in DEA can be represented with random variables. Several methods have been proposed to deal with the random input and output data in DEA. In this paper, we propose a new chance-...

A statistical survey of heat input parameters into the cusp thermosphere

Science.gov (United States)

Moen, J. I.; Skjaeveland, A.; Carlson, H. C.

2017-12-01

Based on three winters of observational data, we present those ionosphere parameters deemed most critical to realistic space weather ionosphere and thermosphere representation and prediction, in regions impacted by variability in the cusp. The CHAMP spacecraft revealed large variability in cusp thermosphere densities, measuring frequent satellite drag enhancements, up to doublings. The community recognizes a clear need for more realistic representation of plasma flows and electron densities near the cusp. Existing average-value models produce order of magnitude errors in these parameters, resulting in large under estimations of predicted drag. We fill this knowledge gap with statistics-based specification of these key parameters over their range of observed values. The EISCAT Svalbard Radar (ESR) tracks plasma flow Vi , electron density Ne, and electron, ion temperatures Te, Ti , with consecutive 2-3 minute windshield-wipe scans of 1000x500 km areas. This allows mapping the maximum Ti of a large area within or near the cusp with high temporal resolution. In magnetic field-aligned mode the radar can measure high-resolution profiles of these plasma parameters. By deriving statistics for Ne and Ti , we enable derivation of thermosphere heating deposition under background and frictional-drag-dominated magnetic reconnection conditions. We separate our Ne and Ti profiles into quiescent and enhanced states, which are not closely correlated due to the spatial structure of the reconnection foot point. Use of our data-based parameter inputs can make order of magnitude corrections to input data driving thermosphere models, enabling removal of previous two fold drag errors.

Soil properties and not inputs control carbon, nitrogen, phosphorus ratios in cropped soils in the long-term

Science.gov (United States)

Frossard, E.; Buchmann, N.; Bünemann, E. K.; Kiba, D. I.; Lompo, F.; Oberson, A.; Tamburini, F.; Traoré, O. Y. A.

2015-09-01

Stoichiometric approaches have been applied to understand the relationship between soil organic matter dynamics and biological nutrient transformations. However, very few studies explicitly considered the effects of agricultural management practices on soil C : N : P ratio. The aim of this study was to assess how different input types and rates would affect the C : N : P molar ratios of bulk soil, organic matter and microbial biomass in cropped soils in the long-term. Thus, we analysed the C, N and P inputs and budgets as well as soil properties in three long-term experiments established on different soil types: the Saria soil fertility trial (Burkina Faso), the Wagga Wagga rotation/stubble management/soil preparation trial (Australia), and the DOK cropping system trial (Switzerland). In each of these trials, there was a large range of C, N and P inputs which had a strong impact on element concentrations in soils. However, although C : N : P ratios of the inputs were highly variable, they had only weak effects on soil C : N : P ratios. At Saria, a positive correlation was found between the N : P ratio of inputs and microbial biomass, while no relation was observed between the nutrient ratios of inputs and soil organic matter. At Wagga Wagga, the C : P ratio of inputs was significantly correlated to total soil C : P, N : P and C : N ratios, but had no impact on the elemental composition of microbial biomass. In the DOK trial, a positive correlation was found between the C budget and the C to organic P ratio in soils, while the nutrient ratios of inputs were not related to those in the microbial biomass. We argue that these responses are due to differences in soil properties among sites. At Saria, the soil is dominated by quartz and some kaolinite, has a coarse texture, a fragile structure and a low nutrient content. Thus, microorganisms feed on inputs (plant residues, manure). In contrast, the soil at Wagga Wagga contains illite and haematite, is richer in clay and

Soil properties and not inputs control carbon : nitrogen : phosphorus ratios in cropped soils in the long term

Science.gov (United States)

Frossard, Emmanuel; Buchmann, Nina; Bünemann, Else K.; Kiba, Delwende I.; Lompo, François; Oberson, Astrid; Tamburini, Federica; Traoré, Ouakoltio Y. A.

2016-02-01

Stoichiometric approaches have been applied to understand the relationship between soil organic matter dynamics and biological nutrient transformations. However, very few studies have explicitly considered the effects of agricultural management practices on the soil C : N : P ratio. The aim of this study was to assess how different input types and rates would affect the C : N : P molar ratios of bulk soil, organic matter and microbial biomass in cropped soils in the long term. Thus, we analysed the C, N, and P inputs and budgets as well as soil properties in three long-term experiments established on different soil types: the Saria soil fertility trial (Burkina Faso), the Wagga Wagga rotation/stubble management/soil preparation trial (Australia), and the DOK (bio-Dynamic, bio-Organic, and "Konventionell") cropping system trial (Switzerland). In each of these trials, there was a large range of C, N, and P inputs which had a strong impact on element concentrations in soils. However, although C : N : P ratios of the inputs were highly variable, they had only weak effects on soil C : N : P ratios. At Saria, a positive correlation was found between the N : P ratio of inputs and microbial biomass, while no relation was observed between the nutrient ratios of inputs and soil organic matter. At Wagga Wagga, the C : P ratio of inputs was significantly correlated to total soil C : P, N : P, and C : N ratios, but had no impact on the elemental composition of microbial biomass. In the DOK trial, a positive correlation was found between the C budget and the C to organic P ratio in soils, while the nutrient ratios of inputs were not related to those in the microbial biomass. We argue that these responses are due to differences in soil properties among sites. At Saria, the soil is dominated by quartz and some kaolinite, has a coarse texture, a fragile structure, and a low nutrient content. Thus, microorganisms feed on inputs (plant residues, manure). In contrast, the soil at

Pooling and correlated neural activity

Directory of Open Access Journals (Sweden)

Robert Rosenbaum

2010-04-01

Full Text Available Correlations between spike trains can strongly modulate neuronal activity and affect the ability of neurons to encode information. Neurons integrate inputs from thousands of afferents. Similarly, a number of experimental techniques are designed to record pooled cell activity. We review and generalize a number of previous results that show how correlations between cells in a population can be amplified and distorted in signals that reflect their collective activity. The structure of the underlying neuronal response can significantly impact correlations between such pooled signals. Therefore care needs to be taken when interpreting pooled recordings, or modeling networks of cells that receive inputs from large presynaptic populations. We also show that the frequently observed runaway synchrony in feedforward chains is primarily due to the pooling of correlated inputs.

The importance of input interactions in the uncertainty and sensitivity analysis of nuclear fuel behavior

Energy Technology Data Exchange (ETDEWEB)

Ikonen, T., E-mail: timo.ikonen@vtt.fi; Tulkki, V.

2014-08-15

Highlights: • Uncertainty and sensitivity analysis of modeled nuclear fuel behavior is performed. • Burnup dependency of the uncertainties and sensitivities is characterized. • Input interactions significantly increase output uncertainties for irradiated fuel. • Identification of uncertainty sources is greatly improved with higher order methods. • Results stress the importance of using methods that take interactions into account. - Abstract: The propagation of uncertainties in a PWR fuel rod under steady-state irradiation is analyzed by computational means. A hypothetical steady-state scenario of the Three Mile Island 1 reactor fuel rod is modeled with the fuel performance FRAPCON, using realistic input uncertainties for the fabrication and model parameters, boundary conditions and material properties. The uncertainty and sensitivity analysis is performed by extensive Monte Carlo sampling of the inputs’ probability distribution and by applying correlation coefficient and Sobol’ variance decomposition analyses. The latter includes evaluation of the second order and total effect sensitivity indices, allowing the study of interactions between input variables. The results show that the interactions play a large role in the propagation of uncertainties, and first order methods such as the correlation coefficient analyses are in general insufficient for sensitivity analysis of the fuel rod. Significant improvement over the first order methods can be achieved by using higher order methods. The results also show that both the magnitude of the uncertainties and their propagation depends not only on the output in question, but also on burnup. The latter is due to onset of new phenomena (such as the fission gas release) and the gradual closure of the pellet-cladding gap with increasing burnup. Increasing burnup also affects the importance of input interactions. Interaction effects are typically highest in the moderate burnup (of the order of 10–40 MWd

Four years of experience with the use of calculated isotopic correlations in establishing input balances at the La Hague plant

International Nuclear Information System (INIS)

Aries, M.; Patigny, P.; Bouchard, J.; Giacometti, A.; Girieud, R.

1983-01-01

For more than four years the La Hague reprocessing plant has been using calculated isotopic correlations to establish and check its input balances. The masses of uranium and plutonium entering the plant are determined by the gravimetric balance method, which utilizes the burnup obtained by calculated isotopic correlation as well as the Pu/U ratio measured at the dissolver after cross-checking with the values obtained by correlation. Further, a verification of all the parameters needed to establish these balances - whether physical or chemical in origin - is carried out systematically by means of internal coherence constants which make it possible to detect any anomalies in the dissolution data. The calculated isotopic correlations were evaluated when the analyses of numerous representative samples of irradiated fuel and experimental results of separated isotopic irradiation in water reactor spectra had been interpreted. The accuracy achieved was improved by allowing in the neutron calculations for effects inherent in the first reactor core and by selecting a set of calculation functions which attenuates (by compensation effects) the various perturbations in the irradiation history. The results obtained at La Hague with calculated isotopic correlations on nearly 600 t of reprocessed UO 2 , because of their large number and above all their high quality, suggest that it be proposed extending the method to other reprocessing plants. This could be done by the operator himself or by national or international control bodies within the framework of a safeguards arrangement. (author)

Noise and crosstalk in two quorum-sensing inputs of Vibrio fischeri

Directory of Open Access Journals (Sweden)

Weiss Joel T

2011-09-01

Full Text Available Abstract Background One of the puzzles in bacterial quorum sensing is understanding how an organism integrates the information gained from multiple input signals. The marine bacterium Vibrio fischeri regulates its bioluminescence through a quorum sensing mechanism that receives input from three pheromone signals, including two acyl homoserine lactone (HSL signals. While the role of the 3-oxo-C6 homoserine lactone (3OC6HSL signal in activating the lux genes has been extensively studied and modeled, the role of the C8 homoserine lactone (C8HSL is less obvious, as it can either activate luminescence or block its activation. It remains unclear how crosstalk between C8HSL and 3OC6HSL affects the information that the bacterium obtains through quorum sensing. Results We have used microfluidic methods to measure the response of individual V.fischeri cells to combinations of C8HSL and 3OC6HSL. By measuring the fluorescence of individual V.fischeri cells containing a chromosomal gfp-reporter for the lux genes, we study how combinations of exogenous HSLs affect both the population average and the cell-to-cell variability of lux activation levels. At the level of a population average, the crosstalk between the C8HSL and 3OC6HSL inputs is well-described by a competitive inhibition model. At the level of individual cells, the heterogeneity in the lux response depends only on the average degree of activation, so that the noise in the output is not reduced by the presence of the second HSL signal. Overall we find that the mutual information between the signal inputs and the lux output is less than one bit. A nonlinear correlation between fluorescence and bioluminescence outputs from lux leads to different noise properties for these reporters. Conclusions The lux genes in V.fischeri do not appear to distinguish between the two HSL inputs, and even with two signal inputs the regulation of lux is extremely noisy. Hence the role of crosstalk from the C8HSL input

The Effects of Type and Quantity of Input on Iranian EFL Learners’ Oral Language Proficiency

Directory of Open Access Journals (Sweden)

Zahra Hassanzadeh

2014-05-01

Full Text Available In the written texts on foreign language learning, a group of studies has stressed the function of learning context and learning chances for learners’ language input. The present thesis had two main goals: on the one hand, different types of input to which Iranian grade four high school EFL learners’ are exposed were looked at; on the other hand, the possible relationship between types and quantity of input and Iranian EFL learners’ oral proficiency was investigated. It was supposed that EFL learners who have access to more input will show better oral proficiency than those who do not have. Instruments used in the present study for the purpose of data collation included  PET test, researcher- made questionnaire, oral language proficiency test and face- to -face interview. Data were gathered from 50 Iranian female grade four high school foreign language learners who were selected from among 120 students whose score on PET test were +1SD from the mean score. The results of the Spearman rank –order correlation test for the types of input and oral language proficiency scores, showed that the participants’ oral proficiency score significantly correlated with the intended four sources of input including spoken (rho= 0.416, sig=0.003, written (rho= 0.364, sig=0.009, aural (rho= 0.343, sig=0.015 and visual or audio-visual types of input (rho= 0.47, sig=0.00. The findings of Spearman rank –order correlation test for the quantity of input and oral language proficiency scores also showed a significant relationship between quantity of input and oral language proficiency (rho= 0.543, sig= 0.00. The findings showed that EFL learners’ oral proficiency is significantly correlated with efficient and effective input. The findings may also suggest  answers to the question why most Iranian English learners fail to speak English fluently, which might be due to  lack of effective input. This may emphasize the importance of the types and quantity of

Latitudinal and seasonal variability of the micrometeor input function: A study using model predictions and observations from Arecibo and PFISR

Science.gov (United States)

Fentzke, J. T.; Janches, D.; Sparks, J. J.

2009-05-01

In this work, we use a semi-empirical model of the micrometeor input function (MIF) together with meteor head-echo observations obtained with two high power and large aperture (HPLA) radars, the 430 MHz Arecibo Observatory (AO) radar in Puerto Rico (18°N, 67°W) and the 450 MHz Poker flat incoherent scatter radar (PFISR) in Alaska (65°N, 147°W), to study the seasonal and geographical dependence of the meteoric flux in the upper atmosphere. The model, recently developed by Janches et al. [2006a. Modeling the global micrometeor input function in the upper atmosphere observed by high power and large aperture radars. Journal of Geophysical Research 111] and Fentzke and Janches [2008. A semi-empirical model of the contribution from sporadic meteoroid sources on the meteor input function observed at arecibo. Journal of Geophysical Research (Space Physics) 113 (A03304)], includes an initial mass flux that is provided by the six known meteor sources (i.e. orbital families of dust) as well as detailed modeling of meteoroid atmospheric entry and ablation physics. In addition, we use a simple ionization model to treat radar sensitivity issues by defining minimum electron volume density production thresholds required in the meteor head-echo plasma for detection. This simplified approach works well because we use observations from two radars with similar frequencies, but different sensitivities and locations. This methodology allows us to explore the initial input of particles and how it manifests in different parts of the MLT as observed by these instruments without the need to invoke more sophisticated plasma models, which are under current development. The comparisons between model predictions and radar observations show excellent agreement between diurnal, seasonal, and latitudinal variability of the detected meteor rate and radial velocity distributions, allowing us to understand how individual meteoroid populations contribute to the overall flux at a particular

Spatio-temporal variability of airborne bacterial communities and their correlation with particulate matter chemical composition across two urban areas.

Science.gov (United States)

Gandolfi, I; Bertolini, V; Bestetti, G; Ambrosini, R; Innocente, E; Rampazzo, G; Papacchini, M; Franzetti, A

2015-06-01

The study of spatio-temporal variability of airborne bacterial communities has recently gained importance due to the evidence that airborne bacteria are involved in atmospheric processes and can affect human health. In this work, we described the structure of airborne microbial communities in two urban areas (Milan and Venice, Northern Italy) through the sequencing, by the Illumina platform, of libraries containing the V5-V6 hypervariable regions of the 16S rRNA gene and estimated the abundance of airborne bacteria with quantitative PCR (qPCR). Airborne microbial communities were dominated by few taxa, particularly Burkholderiales and Actinomycetales, more abundant in colder seasons, and Chloroplasts, more abundant in warmer seasons. By partitioning the variation in bacterial community structure, we could assess that environmental and meteorological conditions, including variability between cities and seasons, were the major determinants of the observed variation in bacterial community structure, while chemical composition of atmospheric particulate matter (PM) had a minor contribution. Particularly, Ba, SO4 (2-) and Mg(2+) concentrations were significantly correlated with microbial community structure, but it was not possible to assess whether they simply co-varied with seasonal shifts of bacterial inputs to the atmosphere, or their variation favoured specific taxa. Both local sources of bacteria and atmospheric dispersal were involved in the assembling of airborne microbial communities, as suggested, to the one side by the large abundance of bacteria typical of lagoon environments (Rhodobacterales) observed in spring air samples from Venice and to the other by the significant effect of wind speed in shaping airborne bacterial communities at all sites.

Sequence variability is correlated with weak immunogenicity in Streptococcus pyogenes M protein

Science.gov (United States)

Lannergård, Jonas; Kristensen, Bodil M; Gustafsson, Mattias C U; Persson, Jenny J; Norrby-Teglund, Anna; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

2015-01-01

The M protein of Streptococcus pyogenes, a major bacterial virulence factor, has an amino-terminal hypervariable region (HVR) that is a target for type-specific protective antibodies. Intriguingly, the HVR elicits a weak antibody response, indicating that it escapes host immunity by two mechanisms, sequence variability and weak immunogenicity. However, the properties influencing the immunogenicity of regions in an M protein remain poorly understood. Here, we studied the antibody response to different regions of the classical M1 and M5 proteins, in which not only the HVR but also the adjacent fibrinogen-binding B repeat region exhibits extensive sequence divergence. Analysis of antisera from S. pyogenes-infected patients, infected mice, and immunized mice showed that both the HVR and the B repeat region elicited weak antibody responses, while the conserved carboxy-terminal part was immunodominant. Thus, we identified a correlation between sequence variability and weak immunogenicity for M protein regions. A potential explanation for the weak immunogenicity was provided by the demonstration that protease digestion selectively eliminated the HVR-B part from whole M protein-expressing bacteria. These data support a coherent model, in which the entire variable HVR-B part evades antibody attack, not only by sequence variability but also by weak immunogenicity resulting from protease attack. PMID:26175306

Reconstruction of organochlorine compound inputs in the Tagus Prodelta.

Science.gov (United States)

Mil-Homens, Mário; Vicente, Maria; Grimalt, Joan O; Micaelo, Cristina; Abrantes, Fátima

2016-01-01

Twenty century time-resolved variability of riverine deposits of polychlorobiphenyls (PCBs), DDTs, hexachlorocyclohexanes (HCHs) and hexachlorobenzene (HCB) was studied in three (210)Pb dated sediment cores collected in a depositional shelf area adjacent to the Tagus estuary (the Tagus Prodelta). The geographic and temporal distribution patterns were consistent with discharge of these organochlorine compounds (OCs) in the area associated with the Tagus mouth. Their concentrations were not correlated with the sedimentary total organic carbon. The PCB down-core profiles were dominated by CB138 and CB153 (hexa-CBs) congeners followed by CB180 (hepta-CBs). Principal Component Analysis of the congener distributions of these compounds did not define temporal down-core trends. The ratios of DDT metabolites (p,p'-DDE/p,p'-DDT) were consistent with recent DDT inputs into the environment and/or earlier applications and long-term residence in soils/sediments until these were eroded and remobilized. Copyright © 2015 Elsevier B.V. All rights reserved.

A novel methodology improves reservoir characterization models using geologic fuzzy variables

Energy Technology Data Exchange (ETDEWEB)

Soto B, Rodolfo [DIGITOIL, Maracaibo (Venezuela); Soto O, David A. [Texas A and M University, College Station, TX (United States)

2004-07-01

One of the research projects carried out in Cusiana field to explain its rapid decline during the last years was to get better permeability models. The reservoir of this field has a complex layered system that it is not easy to model using conventional methods. The new technique included the development of porosity and permeability maps from cored wells following the same trend of the sand depositions for each facie or layer according to the sedimentary facie and the depositional system models. Then, we used fuzzy logic to reproduce those maps in three dimensions as geologic fuzzy variables. After multivariate statistical and factor analyses, we found independence and a good correlation coefficient between the geologic fuzzy variables and core permeability and porosity. This means, the geologic fuzzy variable could explain the fabric, the grain size and the pore geometry of the reservoir rock trough the field. Finally, we developed a neural network permeability model using porosity, gamma ray and the geologic fuzzy variable as input variables. This model has a cross-correlation coefficient of 0.873 and average absolute error of 33% compared with the actual model with a correlation coefficient of 0.511 and absolute error greater than 250%. We tested different methodologies, but this new one showed dramatically be a promiser way to get better permeability models. The use of the models have had a high impact in the explanation of well performance and workovers, and reservoir simulation models. (author)

Numeric Input Relations for Relational Learning with Applications to Community Structure Analysis

DEFF Research Database (Denmark)

Jiang, Jiuchuan; Jaeger, Manfred

2015-01-01

distribution is defined by the model from numerical input variables that are only used for conditioning the distribution of discrete response variables. We show how numerical input relations can very easily be used in the Relational Bayesian Network framework, and that existing inference and learning methods......Most work in the area of statistical relational learning (SRL) is focussed on discrete data, even though a few approaches for hybrid SRL models have been proposed that combine numerical and discrete variables. In this paper we distinguish numerical random variables for which a probability...... use the augmented RBN framework to define probabilistic models for multi-relational (social) networks in which the probability of a link between two nodes depends on numeric latent feature vectors associated with the nodes. A generic learning procedure can be used to obtain a maximum-likelihood fit...

Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models

Directory of Open Access Journals (Sweden)

B. M. Brentan

2017-01-01

Full Text Available Operational and economic aspects of water distribution make water demand forecasting paramount for water distribution systems (WDSs management. However, water demand introduces high levels of uncertainty in WDS hydraulic models. As a result, there is growing interest in developing accurate methodologies for water demand forecasting. Several mathematical models can serve this purpose. One crucial aspect is the use of suitable predictive variables. The most used predictive variables involve weather and social aspects. To improve the interrelation knowledge between water demand and various predictive variables, this study applies three algorithms, namely, classical Principal Component Analysis (PCA and machine learning powerful algorithms such as Self-Organizing Maps (SOMs and Random Forest (RF. We show that these last algorithms help corroborate the results found by PCA, while they are able to unveil hidden features for PCA, due to their ability to cope with nonlinearities. This paper presents a correlation study of three district metered areas (DMAs from Franca, a Brazilian city, exploring weather and social variables to improve the knowledge of residential demand for water. For the three DMAs, temperature, relative humidity, and hour of the day appear to be the most important predictive variables to build an accurate regression model.

Quantitative assessment of drivers of recent climate variability

DEFF Research Database (Denmark)

Bhaskar, Ankush; Ramesh, Durbha Sai; Vichare, Geeta

2016-01-01

Identification and quantification of possible drivers of recent climate variability remain a challenging task. This important issue is addressed adopting a non-parametric information theory technique, the Transfer Entropy and its normalized variant. It distinctly quantifies actual information...... exchanged along with the directional flow of information between any two variables with no bearing on their common history or inputs, unlike correlation, mutual information etc. Measurements of greenhouse gases, CO2, CH4, and N2O; volcanic aerosols; solar activity: UV radiation, total solar irradiance (TSI...... ) and cosmic ray flux (CR); El Nino Southern Oscillation (ENSO) and Global Mean Temperature Anomaly (GMTA) made during 1984-2005 are utilized to distinguish driving and responding climate signals. Estimates of their relative contributions reveal that CO 2 (~24%), CH 4 (~19%) and volcanic aerosols (~23...

Correlation between Very Short and Short-Term Blood Pressure Variability in Diabetic-Hypertensive and Healthy Subjects.

Science.gov (United States)

Casali, Karina R; Schaan, Beatriz D; Montano, Nicola; Massierer, Daniela; M F Neto, Flávio; Teló, Gabriela H; Ledur, Priscila S; Reinheimer, Marilia; Sbruzzi, Graciele; Gus, Miguel

2018-02-01

Blood pressure (BP) variability can be evaluated by 24-hour ambulatory BP monitoring (24h-ABPM), but its concordance with results from finger BP measurement (FBPM) has not been established yet. The aim of this study was to compare parameters of short-term (24h-ABPM) with very short-term BP variability (FBPM) in healthy (C) and diabetic-hypertensive (DH) subjects. Cross-sectional study with 51 DH subjects and 12 C subjects who underwent 24h-ABPM [extracting time-rate, standard deviation (SD), coefficient of variation (CV)] and short-term beat-to-beat recording at rest and after standing-up maneuvers [FBPM, extracting BP and heart rate (HR) variability parameters in the frequency domain, autoregressive spectral analysis]. Spearman correlation coefficient was used to correlate BP and HR variability parameters obtained from both FBPM and 24h-ABPM (divided into daytime, nighttime, and total). Statistical significance was set at p ABPM) and LF component of short-term variability (FBPM, total, R = 0.591, p = 0.043); standard deviation (24h-ABPM) with LF component BPV (FBPM, total, R = 0.608, p = 0.036), coefficient of variation (24h-ABPM) with total BPV (FBPM, daytime, -0.585, p = 0.046) and alpha index (FBPM, daytime, -0.592, p = 0.043), time rate (24h-ABPM) and delta LF/HF (FBPM, total, R = 0.636, p = 0.026; daytime R = 0,857, p ABPM (total, daytime) reflect BP and HR variability evaluated by FBPM in healthy individuals. This does not apply for DH subjects.

Joint statistics of strongly correlated neurons via dimensionality reduction

International Nuclear Information System (INIS)

Deniz, Taşkın; Rotter, Stefan

2017-01-01

The relative timing of action potentials in neurons recorded from local cortical networks often shows a non-trivial dependence, which is then quantified by cross-correlation functions. Theoretical models emphasize that such spike train correlations are an inevitable consequence of two neurons being part of the same network and sharing some synaptic input. For non-linear neuron models, however, explicit correlation functions are difficult to compute analytically, and perturbative methods work only for weak shared input. In order to treat strong correlations, we suggest here an alternative non-perturbative method. Specifically, we study the case of two leaky integrate-and-fire neurons with strong shared input. Correlation functions derived from simulated spike trains fit our theoretical predictions very accurately. Using our method, we computed the non-linear correlation transfer as well as correlation functions that are asymmetric due to inhomogeneous intrinsic parameters or unequal input. (paper)

Correlation structures in short-term variabilities of stock indices and exchange rates

Science.gov (United States)

Nakamura, Tomomichi; Small, Michael

2007-09-01

Financial data usually show irregular fluctuations and some trends. We investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) among financial data from the viewpoint of deterministic dynamical systems. Our method is based on the small-shuffle surrogate method. The data we use are daily closing price of Standard & Poor's 500 and the volume, and daily foreign exchange rates, Euro/US Dollar (USD), British Pound/USD and Japanese Yen/USD. We found that these data are not independent.

Correlations between Learners' Initial EFL Proficiency and Variables of Clicker-Aided Flipped EFL Class

Science.gov (United States)

Yu, Zhonggen; Yu, Liheng

2017-01-01

Although the flipped class has been hotly discussed, the clicker-aided flipped EFL class (CFEC) still remains a mystery for most scholars. This study aims to determine the correlations between the initial EFL proficiency and other variables of the clicker-aided EFL flipped class. The sample was made up of randomly selected 79 participants (Female…

The behaviour of random forest permutation-based variable importance measures under predictor correlation.

Science.gov (United States)

Nicodemus, Kristin K; Malley, James D; Strobl, Carolin; Ziegler, Andreas

2010-02-27

Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observed. Recent works on permutation-based variable importance measures (VIMs) used in RF have come to apparently contradictory conclusions. We present an extended simulation study to synthesize results. In the case when both predictor correlation was present and predictors were associated with the outcome (HA), the unconditional RF VIM attributed a higher share of importance to correlated predictors, while under the null hypothesis that no predictors are associated with the outcome (H0) the unconditional RF VIM was unbiased. Conditional VIMs showed a decrease in VIM values for correlated predictors versus the unconditional VIMs under HA and was unbiased under H0. Scaled VIMs were clearly biased under HA and H0. Unconditional unscaled VIMs are a computationally tractable choice for large datasets and are unbiased under the null hypothesis. Whether the observed increased VIMs for correlated predictors may be considered a "bias" - because they do not directly reflect the coefficients in the generating model - or if it is a beneficial attribute of these VIMs is dependent on the application. For example, in genetic association studies, where correlation between markers may help to localize the functionally relevant variant, the increased importance of correlated predictors may be an advantage. On the other hand, we show examples where this increased importance may result in spurious signals.

Correlation between maximum isometric strength variables and specific performance of Brazilian military judokas

Directory of Open Access Journals (Sweden)

Michel Moraes Gonçalves

2017-06-01

Full Text Available It was our objective to correlate specific performance in the Special Judo Fitness Test (SJFT and the maximum isometric handgrip (HGSMax, scapular traction (STSMax and lumbar traction (LTSMax strength tests in military judo athletes. Twenty-two military athletes from the judo team of the Brazilian Navy Almirante Alexandrino Instruction Centre, with average age of 26.14 ± 3.31 years old, and average body mass of 83.23 ± 14.14 kg participated in the study. Electronic dynamometry tests for HGSMax, STSMax and LTSMax were conducted. Then, after approximately 1 hour-interval, the SJFT protocol was applied. All variables were adjusted to the body mass of the athletes. Pearson correlation coefficient for statistical analysis was used. The results showed moderate negative correlation between the SJFT index and STSMax (r= -0.550, p= 0.008, strong negative correlations between the SJFT index and HGSMax (r= -0.706, p< 0.001, SJFT index and LTSMax (r= -0.721; p= 0.001, besides the correlation between the sum of the three maximum isometric strength tests and the SJFT index (r= -0.786, p< 0.001. This study concludes that negative correlations occur between the SJFT index and maximum isometric handgrip, shoulder and lumbar traction strength and the sum of the three maximum isometric strength tests in military judokas.

A Simple K-Map Based Variable Selection Scheme in the Direct ...

African Journals Online (AJOL)

A multiplexer with (n-l) data select inputs can realise directly a function of n variables. In this paper, a simple k-map based variable selection scheme is proposed such that an n variable logic function can be synthesised using a multiplexer with (n-q) data input variables and q data select variables. The procedure is based on ...

Sequence variability is correlated with weak immunogenicity in Streptococcus pyogenes M protein.

Science.gov (United States)

Lannergård, Jonas; Kristensen, Bodil M; Gustafsson, Mattias C U; Persson, Jenny J; Norrby-Teglund, Anna; Stålhammar-Carlemalm, Margaretha; Lindahl, Gunnar

2015-10-01

The M protein of Streptococcus pyogenes, a major bacterial virulence factor, has an amino-terminal hypervariable region (HVR) that is a target for type-specific protective antibodies. Intriguingly, the HVR elicits a weak antibody response, indicating that it escapes host immunity by two mechanisms, sequence variability and weak immunogenicity. However, the properties influencing the immunogenicity of regions in an M protein remain poorly understood. Here, we studied the antibody response to different regions of the classical M1 and M5 proteins, in which not only the HVR but also the adjacent fibrinogen-binding B repeat region exhibits extensive sequence divergence. Analysis of antisera from S. pyogenes-infected patients, infected mice, and immunized mice showed that both the HVR and the B repeat region elicited weak antibody responses, while the conserved carboxy-terminal part was immunodominant. Thus, we identified a correlation between sequence variability and weak immunogenicity for M protein regions. A potential explanation for the weak immunogenicity was provided by the demonstration that protease digestion selectively eliminated the HVR-B part from whole M protein-expressing bacteria. These data support a coherent model, in which the entire variable HVR-B part evades antibody attack, not only by sequence variability but also by weak immunogenicity resulting from protease attack. © 2015 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

Directory of Open Access Journals (Sweden)

Yeqing Zhang

2018-02-01

Full Text Available For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully.

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

Science.gov (United States)

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-01-01

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully. PMID:29495301

Interpretation of correlated neural variability from models of feed-forward and recurrent circuits

Science.gov (United States)

2018-01-01

Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures—recurrent connections, shared feed-forward projections, and shared gain fluctuations—on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing. PMID:29408930

Interpretation of correlated neural variability from models of feed-forward and recurrent circuits.

Directory of Open Access Journals (Sweden)

Volker Pernice

2018-02-01

Full Text Available Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures-recurrent connections, shared feed-forward projections, and shared gain fluctuations-on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged covariances on firing rates, for different network architectures. In turn, these relations can be used to analyze data on population activity. We examine recordings from neural populations in mouse auditory cortex. We find that a recurrent network model with random effective connections captures the observed statistics. Furthermore, using our circuit model, we investigate the relation between network parameters, correlations, and how well different stimuli can be discriminated from one another based on the population activity. As such, our approach allows us to relate properties of the neural circuit to information processing.

Reprocessing input data validation

International Nuclear Information System (INIS)

Persiani, P.J.; Bucher, R.G.; Pond, R.B.; Cornella, R.J.

1990-01-01

The Isotope Correlation Technique (ICT), in conjunction with the gravimetric (Pu/U ratio) method for mass determination, provides an independent verification of the input accountancy at the dissolver or accountancy stage of the reprocessing plant. The Isotope Correlation Technique has been applied to many classes of domestic and international reactor systems (light-water, heavy-water, graphite, and liquid-metal) operating in a variety of modes (power, research, production, and breeder), and for a variety of reprocessing fuel cycle management strategies. Analysis of reprocessing operations data based on isotopic correlations derived for assemblies in a PWR environment and fuel management scheme, yielded differences between the measurement-derived and ICT-derived plutonium mass determinations of (-0.02 ± 0.23)% for the measured U-235 and (+0.50 ± 0.31)% for the measured Pu-239, for a core campaign. The ICT analyses has been implemented for the plutonium isotopics in a depleted uranium assembly in a heavy-water, enriched uranium system and for the uranium isotopes in the fuel assemblies in light-water, highly-enriched systems. 7 refs., 5 figs., 4 tabs

Plasticity of the cis-regulatory input function of a gene.

Directory of Open Access Journals (Sweden)

Avraham E Mayo

2006-04-01

Full Text Available The transcription rate of a gene is often controlled by several regulators that bind specific sites in the gene's cis-regulatory region. The combined effect of these regulators is described by a cis-regulatory input function. What determines the form of an input function, and how variable is it with respect to mutations? To address this, we employ the well-characterized lac operon of Escherichia coli, which has an elaborate input function, intermediate between Boolean AND-gate and OR-gate logic. We mapped in detail the input function of 12 variants of the lac promoter, each with different point mutations in the regulator binding sites, by means of accurate expression measurements from living cells. We find that even a few mutations can significantly change the input function, resulting in functions that resemble Pure AND gates, OR gates, or single-input switches. Other types of gates were not found. The variant input functions can be described in a unified manner by a mathematical model. The model also lets us predict which functions cannot be reached by point mutations. The input function that we studied thus appears to be plastic, in the sense that many of the mutations do not ruin the regulation completely but rather result in new ways to integrate the inputs.

Correlation of mechanical and electrical properties with processing variables in MWCNT reinforced thermoplastic nanocomposites

DEFF Research Database (Denmark)

Doagou-Rad, Saeed; Islam, Aminul; Jensen, Jakob Søndergaard

2018-01-01

The influence of the processing variables and nanotube content on the mechanical and electrical properties of polyamide 6,6-based nanocomposites reinforced with multi-walled carbon nanotubes is investigated. Results show that variation in the processing variables such as compounding method....... Different processing parameters required for achieving optimal mechanical and electrical performances are also found. Correlation between processing parameters and microstructure within the nanocomposites is studied. Results show that variation of the processing parameters defines the existence or absence...... discussed using scanning and transmission electron microscopy, rheological and crystallization investigations. The research provides a recipe to manufacture the tailored nanocomposite with the specified properties for various industrial applications....

Chaos Synchronization Based on Unknown Input Proportional Multiple-Integral Fuzzy Observer

Directory of Open Access Journals (Sweden)

T. Youssef

2013-01-01

Full Text Available This paper presents an unknown input Proportional Multiple-Integral Observer (PIO for synchronization of chaotic systems based on Takagi-Sugeno (TS fuzzy chaotic models subject to unmeasurable decision variables and unknown input. In a secure communication configuration, this unknown input is regarded as a message encoded in the chaotic system and recovered by the proposed PIO. Both states and outputs of the fuzzy chaotic models are subject to polynomial unknown input with kth derivative zero. Using Lyapunov stability theory, sufficient design conditions for synchronization are proposed. The PIO gains matrices are obtained by resolving linear matrix inequalities (LMIs constraints. Simulation results show through two TS fuzzy chaotic models the validity of the proposed method.

Pronounced centennial-scale Atlantic Ocean climate variability correlated with Western Hemisphere hydroclimate

Science.gov (United States)

Thirumalai, Kaustubh; Quinn, Terrence M.; Okumura, Yuko; Richey, Julie; Partin, Judson W.; Poore, Richard Z.; Moreno-Chamarro, Eduardo

2018-01-01

Surface-ocean circulation in the northern Atlantic Ocean influences Northern Hemisphere climate. Century-scale circulation variability in the Atlantic Ocean, however, is poorly constrained due to insufficiently-resolved paleoceanographic records. Here we present a replicated reconstruction of sea-surface temperature and salinity from a site sensitive to North Atlantic circulation in the Gulf of Mexico which reveals pronounced centennial-scale variability over the late Holocene. We find significant correlations on these timescales between salinity changes in the Atlantic, a diagnostic parameter of circulation, and widespread precipitation anomalies using three approaches: multiproxy synthesis, observational datasets, and a transient simulation. Our results demonstrate links between centennial changes in northern Atlantic surface-circulation and hydroclimate changes in the adjacent continents over the late Holocene. Notably, our findings reveal that weakened surface-circulation in the Atlantic Ocean was concomitant with well-documented rainfall anomalies in the Western Hemisphere during the Little Ice Age.

Pronounced centennial-scale Atlantic Ocean climate variability correlated with Western Hemisphere hydroclimate.

Science.gov (United States)

Thirumalai, Kaustubh; Quinn, Terrence M; Okumura, Yuko; Richey, Julie N; Partin, Judson W; Poore, Richard Z; Moreno-Chamarro, Eduardo

2018-01-26

Surface-ocean circulation in the northern Atlantic Ocean influences Northern Hemisphere climate. Century-scale circulation variability in the Atlantic Ocean, however, is poorly constrained due to insufficiently-resolved paleoceanographic records. Here we present a replicated reconstruction of sea-surface temperature and salinity from a site sensitive to North Atlantic circulation in the Gulf of Mexico which reveals pronounced centennial-scale variability over the late Holocene. We find significant correlations on these timescales between salinity changes in the Atlantic, a diagnostic parameter of circulation, and widespread precipitation anomalies using three approaches: multiproxy synthesis, observational datasets, and a transient simulation. Our results demonstrate links between centennial changes in northern Atlantic surface-circulation and hydroclimate changes in the adjacent continents over the late Holocene. Notably, our findings reveal that weakened surface-circulation in the Atlantic Ocean was concomitant with well-documented rainfall anomalies in the Western Hemisphere during the Little Ice Age.

Input/Output linearizing control of a nuclear reactor

International Nuclear Information System (INIS)

Perez C, V.

1994-01-01

The feedback linearization technique is an approach to nonlinear control design. The basic idea is to transform, by means of algebraic methods, the dynamics of a nonlinear control system into a full or partial linear system. As a result of this linearization process, the well known basic linear control techniques can be used to obtain some desired dynamic characteristics. When full linearization is achieved, the method is referred to as input-state linearization, whereas when partial linearization is achieved, the method is referred to as input-output linearization. We will deal with the latter. By means of input-output linearization, the dynamics of a nonlinear system can be decomposed into an external part (input-output), and an internal part (unobservable). Since the external part consists of a linear relationship among the output of the plant and the auxiliary control input mentioned above, it is easy to design such an auxiliary control input so that we get the output to behave in a predetermined way. Since the internal dynamics of the system is known, we can check its dynamics behavior on order of to ensure that the internal states are bounded. The linearization method described here can be applied to systems with one-input/one-output, as well as to systems with multiple-inputs/multiple-outputs. Typical control problems such as stabilization and reference path tracking can be solved using this technique. In this work, the input/output linearization theory is presented, as well as the problem of getting the output variable to track some desired trayectories. Further, the design of an input/output control system applied to the nonlinear model of a research nuclear reactor is included, along with the results obtained by computer simulation. (Author)

Role of environmental variables on radon concentration in soil

International Nuclear Information System (INIS)

Climent, H.; Bakalowicz, M.; Monnin, M.

1998-01-01

In the frame of an European project, radon concentrations in soil and measurements of environmental variables such as the nature of the soil or climatic variables were monitored. The data have been analysed by time-series analysis methods, i.e. Correlation and Spectrum Analysis, to point out relations between radon concentrations and some environmental variables. This approach is a compromise between direct observation and modelling. The observation of the rough time series is unable to point out the relation between radon concentrations and an environmental variable because of the overlapping of the influences of several variables, and the time delay induced by the medium. The Cross Spectrum function between the time series of radon and of an environmental variable describes the nature of the relation and gives the response time in the case of a cause to effect relation. It requires the only hypothesis that the environmental variable is the input function and radon concentration the output function. This analysis is an important preliminary study for modelling. By that way the importance of soil nature has been pointed out. The internal variables of the medium (permeability, porosity) appear to restrain the influence of the environmental variables such as humidity, temperature or atmospheric pressure. (author)

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.

Science.gov (United States)

Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

2015-10-20

It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs

Directory of Open Access Journals (Sweden)

Qing Gu

2015-10-01

Full Text Available It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006–2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes. According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

Does Input Quality Drive Measured Differences in Firm Productivity?

DEFF Research Database (Denmark)

Fox, Jeremy T.; Smeets, Valerie Anne Rolande

is roughly of the same order of magnitude as some competitive effects found in the literature, but input quality measures do not explain most productivity dispersion, despite economically large production function coefficients. We find that the wage bill explains as much dispersion as human capital measures.......Firms in the same industry can differ in measured productivity by multiples of 3. Griliches (1957) suggests one explanation: the quality of inputs differs across firms. We add labor market history variables such as experience and firm and industry tenure, as well as general human capital measures...

Interseason variability in isokinetic strength and poor correlation with Nordic hamstring eccentric strength in football players.

Science.gov (United States)

van Dyk, N; Witvrouw, E; Bahr, R

2018-04-25

In elite sport, the use of strength testing to establish muscle function and performance is common. Traditionally, isokinetic strength tests have been used, measuring torque during concentric and eccentric muscle action. A device that measures eccentric hamstring muscle strength while performing the Nordic hamstring exercise is now also frequently used. The study aimed to investigate the variability of isokinetic muscle strength over time, for example, between seasons, and the relationship between isokinetic testing and the new Nordic hamstring exercise device. All teams (n = 18) eligible to compete in the premier football league in Qatar underwent a comprehensive strength assessment during their periodic health evaluation at Aspetar Orthopaedic and Sports Medicine Hospital in Qatar. Isokinetic strength was investigated for measurement error, and correlated to Nordic hamstring exercise strength. Of the 529 players included, 288 players had repeated tests with 1/2 seasons between test occasions. Variability (measurement error) between test occasions was substantial, as demonstrated by the measurement error (approximately 25 Nm, 15%), whether separated by 1 or 2 seasons. Considering hamstring injuries, the same pattern was observed among injured (n = 60) and uninjured (n = 228) players. A poor correlation (r = .35) was observed between peak isokinetic hamstring eccentric torque and Nordic hamstring exercise peak force. The strength imbalance between limbs calculated for both test modes was not correlated (r = .037). There is substantial intraindividual variability in all isokinetic test measures, whether separated by 1 or 2 seasons, irrespective of injury. Also, eccentric hamstring strength and limb-to-limb imbalance were poorly correlated between the isokinetic and Nordic hamstring exercise tests. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Motor skills in kindergarten: Internal structure, cognitive correlates and relationships to background variables.

Science.gov (United States)

Oberer, Nicole; Gashaj, Venera; Roebers, Claudia M

2017-04-01

The present study aimed to contribute to the discussion about the relation between motor coordination and executive functions in preschool children. Specifically, the relation between gross and fine motor skills and executive functions as well as the relation to possible background variables (SES, physical activity) were investigated. Based on the data of N=156 kindergarten children the internal structure of motor skills was investigated and confirmed the theoretically assumed subdivision of gross and fine motor skills. Both, gross and fine motor skills correlated significantly with executive functions, whereas the background variables seemed to have no significant impact on the executive functions and motor skills. Higher order control processes are discussed as an explanation of the relation between executive functions and motor skills. Copyright © 2017 Elsevier B.V. All rights reserved.

Correlations of the glycemic variability with oxidative stress and erythrocytes membrane stability in patients with type 1 diabetes under intensive treatment.

Science.gov (United States)

Rodrigues, Ricardo; Alves de Medeiros, Luciana; Moreira Cunha, Lucas; da Silva Garrote-Filho, Mario; Bernardino Neto, Morun; Tannus Jorge, Paulo; Santos Resende, Elmiro; Penha-Silva, Nilson

2018-02-07

This study aimed to evaluate the correlations of glycemic variability with erythrocyte membrane stability parameters and oxidative stress markers in patients with DM1 under intensive treatment. 90 patients with DM1 and under intensive treatment of the disease were evaluated in relation to anthropometric indices, records of glycemic averages and parameters of glycemic variability, biochemical dosages (glucose, uric acid, lipidogram, glycated hemoglobin, microalbuminuria, creatinine and iron) reticulocyte count, erythrocyte membrane stability parameters and oxidative stress markers (thiobarbituric acid reactive substances, TBARS, and glutathione reductase, GR). Indicators of glycemic variability in the short and long term showed correlations with parameters of membrane stability and markers of oxidative stress (GR). In addition, the comparison of these same parameters between the subgroups consisting of quartiles of GV or glycemic control also showed significant differences. In the DM1 patients studied here, glycemic variability showed correlations with oxidative stress and erythrocyte membrane stability variables. This corroborates the hypothesis that glycemic fluctuations interfere with lipid peroxidation and cell membrane behavior, emphasizing its participation in mechanisms related to the development of chronic complications of diabetes. Copyright © 2018 Elsevier B.V. All rights reserved.

How model and input uncertainty impact maize yield simulations in West Africa

Science.gov (United States)

Waha, Katharina; Huth, Neil; Carberry, Peter; Wang, Enli

2015-02-01

Crop models are common tools for simulating crop yields and crop production in studies on food security and global change. Various uncertainties however exist, not only in the model design and model parameters, but also and maybe even more important in soil, climate and management input data. We analyze the performance of the point-scale crop model APSIM and the global scale crop model LPJmL with different climate and soil conditions under different agricultural management in the low-input maize-growing areas of Burkina Faso, West Africa. We test the models’ response to different levels of input information from little to detailed information on soil, climate (1961-2000) and agricultural management and compare the models’ ability to represent the observed spatial (between locations) and temporal variability (between years) in crop yields. We found that the resolution of different soil, climate and management information influences the simulated crop yields in both models. However, the difference between models is larger than between input data and larger between simulations with different climate and management information than between simulations with different soil information. The observed spatial variability can be represented well from both models even with little information on soils and management but APSIM simulates a higher variation between single locations than LPJmL. The agreement of simulated and observed temporal variability is lower due to non-climatic factors e.g. investment in agricultural research and development between 1987 and 1991 in Burkina Faso which resulted in a doubling of maize yields. The findings of our study highlight the importance of scale and model choice and show that the most detailed input data does not necessarily improve model performance.

Ensemble standar deviation of wind speed and direction of the FDDA input to WRF

Data.gov (United States)

U.S. Environmental Protection Agency — NetCDF file of the SREF standard deviation of wind speed and direction that was used to inject variability in the FDDA input. variable U_NDG_OLD contains standard...

Intraclass Correlation Coefficients in Hierarchical Design Studies with Discrete Response Variables: A Note on a Direct Interval Estimation Procedure

Science.gov (United States)

Raykov, Tenko; Marcoulides, George A.

2015-01-01

A latent variable modeling procedure that can be used to evaluate intraclass correlation coefficients in two-level settings with discrete response variables is discussed. The approach is readily applied when the purpose is to furnish confidence intervals at prespecified confidence levels for these coefficients in setups with binary or ordinal…

Antenna Correlation From Input Parameters for Arbitrary Topologies and Terminations

DEFF Research Database (Denmark)

Alrabadi, Osama; Andersen, Jørgen Bach; Pedersen, Gert Frølund

2012-01-01

The spatial correlation between pairs of antennas in a system comprised of N RF ports is found by extending the N × N scattering matrix to (N + 1)×(N + 1) spatial scattering matrix, where the extra space dimension accounts for the reference port patterns. The lossless property of the spatial...... scattering matrix in a 3D uniform field is employed for expressing the spatial correlation between the port patterns at arbitrary complex terminations merely from the reference scattering parameters and the complex terminations without any far-field calculation....

A Method to Select Software Test Cases in Consideration of Past Input Sequence

International Nuclear Information System (INIS)

Kim, Hee Eun; Kim, Bo Gyung; Kang, Hyun Gook

2015-01-01

In the Korea Nuclear I and C Systems (KNICS) project, the software for the fully-digitalized reactor protection system (RPS) was developed under a strict procedure. Even though the behavior of the software is deterministic, the randomness of input sequence produces probabilistic behavior of software. A software failure occurs when some inputs to the software occur and interact with the internal state of the digital system to trigger a fault that was introduced into the software during the software lifecycle. In this paper, the method to select test set for software failure probability estimation is suggested. This test set reflects past input sequence of software, which covers all possible cases. In this study, the method to select test cases for software failure probability quantification was suggested. To obtain profile of paired state variables, relationships of the variables need to be considered. The effect of input from human operator also have to be considered. As an example, test set of PZR-PR-Lo-Trip logic was examined. This method provides framework for selecting test cases of safety-critical software

Global sensitivity analysis of computer models with functional inputs

International Nuclear Information System (INIS)

Iooss, Bertrand; Ribatet, Mathieu

2009-01-01

Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.

Effect of variable heat input on the heat transfer characteristics in an Organic Rankine Cycle system

Directory of Open Access Journals (Sweden)

Aboaltabooq Mahdi Hatf Kadhum

2016-01-01

Full Text Available This paper analyzes the heat transfer characteristics of an ORC evaporator applied on a diesel engine using measured data from experimental work such as flue gas mass flow rate and flue gas temperature. A mathematical model was developed with regard to the preheater, boiler and the superheater zones of a counter flow evaporator. Each of these zones has been subdivided into a number of cells. The hot source of the ORC cycle was modeled. The study involves the variable heat input's dependence on the ORC system's heat transfer characteristics, with especial emphasis on the evaporator. The results show that the refrigerant's heat transfer coefficient has a higher value for a 100% load from the diesel engine, and decreases with the load decrease. Also, on the exhaust gas side, the heat transfer coefficient decreases with the decrease of the load. The refrigerant's heat transfer coefficient increased normally with the evaporator's tube length in the preheater zone, and then increases rapidly in the boiler zone, followed by a decrease in the superheater zone. The exhaust gases’ heat transfer coefficient increased with the evaporator’ tube length in all zones. The results were compared with result by other authors and were found to be in agreement.

Genotypic Variability of the Components and their Effects on the Rice Yield: Correlation and Path Analysis Study

Directory of Open Access Journals (Sweden)

Sharkhawat Hossain

2008-06-01

Full Text Available Twenty modern Boro rice varieties were evaluated with a view to find variability and genetic association for grain yield and yield components characters. Genotypic and Phenotypic correlation among these characters were computed. Both genotypic and phenotypic correlation coefficients were significant between plant height and number of effective tillers per plant followed by panicle length. There was a positive significant correlation between yield and number of effective tillers per plant followed by percent filled grain per panicle. Path coefficient showed that number of effective tiller per plant and plant height are the characters that contribute largely to grain yield.

Heat input control in coke ovens battery using artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Kumar, R.; Kannan, C.; Sistla, S.; Kumar, D. [Tata Steel, Jamshedpur (India)

2005-07-01

Controlled heating is very essential for producing coke with certain desired properties. Controlled heating involves controlling the heat input into the battery dynamically depending on the various process parameters like current battery temperature, the set point of battery temperature, moisture in coal, ambient temperature, coal fineness, cake breakage etc. An artificial intelligence (AI) based heat input control has been developed in which currently some of the above mentioned process parameters are considered and used for calculating the pause time which is applied between reversal during the heating process. The AI based model currently considers 3 input variables, temperature deviation history, current deviation of the battery temperature from the target temperature and the actual heat input into the battery. Work is in progress to control the standard deviation of coke end temperature using this model. The new system which has been developed in-house has replaced Hoogovens supplied model. 7 figs.

High accurate volume holographic correlator with 4000 parallel correlation channels

Science.gov (United States)

Ni, Kai; Qu, Zongyao; Cao, Liangcai; Su, Ping; He, Qingsheng; Jin, Guofan

2008-03-01

Volume holographic correlator allows simultaneously calculate the two-dimensional inner product between the input image and each stored image. We have recently experimentally implemented in VHC 4000 parallel correlation channels with better than 98% output accuracy in a single location in a crystal. The speckle modulation is used to suppress the sidelobes of the correlation patterns, allowing more correlation spots to be contained in the output plane. A modified exposure schedule is designed to ensure the hologram in each channel with unity diffraction efficiency. In this schedule, a restricted coefficient was introduced into the original exposure schedule to solve the problem that the sensitivity and time constant of the crystal will change as a time function when in high-capacity storage. An interleaving method is proposed to improve the output accuracy. By unifying the distribution of the input and stored image patterns without changing the inner products between them, this method could eliminate the impact of correlation pattern variety on calculated inner product values. Moreover, by using this method, the maximum correlation spot size is reduced, which decreases the required minimum safe clearance between neighboring spots in the output plane, allowing more spots to be parallely detected without crosstalk. The experimental results are given and analyzed.

Correlations between the Poincaré plot and conventional heart rate variability parameters assessed during paced breathing

NARCIS (Netherlands)

Guzik, P.; Piskorski, J.; Krauze, T.; Schneider, R.; Wesseling, K.H.; Wykrȩtowicz, A.; Wysocki, H.

2007-01-01

Aim: To analyze the correlation of the Poincaré plot descriptors of RR intervals with standard measures of heart rate variability (HRV) and spontaneous baroreflex sensitivity (BRS). A physiological model of changing respiratory rates from 6 to 15 breaths/min provided a wide range of RR intervals for

Framework for Modelling Multiple Input Complex Aggregations for Interactive Installations

DEFF Research Database (Denmark)

Padfield, Nicolas; Andreasen, Troels

2012-01-01

on fuzzy logic and provides a method for variably balancing interaction and user input with the intention of the artist or director. An experimental design is presented, demonstrating an intuitive interface for parametric modelling of a complex aggregation function. The aggregation function unifies...

Learning a Novel Pattern through Balanced and Skewed Input

Science.gov (United States)

McDonough, Kim; Trofimovich, Pavel

2013-01-01

This study compared the effectiveness of balanced and skewed input at facilitating the acquisition of the transitive construction in Esperanto, characterized by the accusative suffix "-n" and variable word order (SVO, OVS). Thai university students (N = 98) listened to 24 sentences under skewed (one noun with high token frequency) or…

Correlations between dentoskeletal variables and deep bite in Class II Division 1 individuals

Directory of Open Access Journals (Sweden)

Leandro Silva Marques

2011-02-01

Full Text Available This study aimed to evaluate the cephalometric pattern of Class II Division 1 individuals with deep bite, and to determine possible correlations between dentoskeletal variables and deep bite. Comparisons were also made between genders and cases that were to be treated both with and without premolar extraction. A total of 70 lateral cephalograms were used, from both male (n = 35 and female (n = 35 individuals with an average age of 11.6 years, who simultaneously presented with ANB > 5º and overbite > 4 mm. Statistical analysis involved parametric (t-test and non-parametric (Mann-Whitney tests for independent samples, as well as the Spearman correlation test (p < 0.05. The values of Go-Me, Ar-Pog, PM-1 and PM-CMI were higher in males (p < 0.05. However, no significant differences were found among the averages of the cephalometric measurements when the sample was divided by treatment with and without extraction. Deep bite was positively correlated to the PM-1 and SNA measurements, and negatively correlated to the Go-Me, Ar-Pog, SNB and SNGoMe measurements. The main factors associated with the determination of deep bite in Angle's Class II Division 1 cases were: greater lower anterior dentoalveolar growth and/or lower incisor extrusion, horizontal growth pattern, maxillary protrusion and mandibular retrusion.

Superadditive correlation

International Nuclear Information System (INIS)

Giraud, B.G.; Heumann, J.M.; Lapedes, A.S.

1999-01-01

The fact that correlation does not imply causation is well known. Correlation between variables at two sites does not imply that the two sites directly interact, because, e.g., correlation between distant sites may be induced by chaining of correlation between a set of intervening, directly interacting sites. Such 'noncausal correlation' is well understood in statistical physics: an example is long-range order in spin systems, where spins which have only short-range direct interactions, e.g., the Ising model, display correlation at a distance. It is less well recognized that such long-range 'noncausal' correlations can in fact be stronger than the magnitude of any causal correlation induced by direct interactions. We call this phenomenon superadditive correlation (SAC). We demonstrate this counterintuitive phenomenon by explicit examples in (i) a model spin system and (ii) a model continuous variable system, where both models are such that two variables have multiple intervening pathways of indirect interaction. We apply the technique known as decimation to explain SAC as an additive, constructive interference phenomenon between the multiple pathways of indirect interaction. We also explain the effect using a definition of the collective mode describing the intervening spin variables. Finally, we show that the SAC effect is mirrored in information theory, and is true for mutual information measures in addition to correlation measures. Generic complex systems typically exhibit multiple pathways of indirect interaction, making SAC a potentially widespread phenomenon. This affects, e.g., attempts to deduce interactions by examination of correlations, as well as, e.g., hierarchical approximation methods for multivariate probability distributions, which introduce parameters based on successive orders of correlation. copyright 1999 The American Physical Society

Grayscale Optical Correlator Workbench

Science.gov (United States)

Hanan, Jay; Zhou, Hanying; Chao, Tien-Hsin

2006-01-01

Grayscale Optical Correlator Workbench (GOCWB) is a computer program for use in automatic target recognition (ATR). GOCWB performs ATR with an accurate simulation of a hardware grayscale optical correlator (GOC). This simulation is performed to test filters that are created in GOCWB. Thus, GOCWB can be used as a stand-alone ATR software tool or in combination with GOC hardware for building (target training), testing, and optimization of filters. The software is divided into three main parts, denoted filter, testing, and training. The training part is used for assembling training images as input to a filter. The filter part is used for combining training images into a filter and optimizing that filter. The testing part is used for testing new filters and for general simulation of GOC output. The current version of GOCWB relies on the mathematical software tools from MATLAB binaries for performing matrix operations and fast Fourier transforms. Optimization of filters is based on an algorithm, known as OT-MACH, in which variables specified by the user are parameterized and the best filter is selected on the basis of an average result for correct identification of targets in multiple test images.

Does Input Quality Drive Measured Differences in Firm Productivity?

DEFF Research Database (Denmark)

Fox, Jeremy T.; Smeets, Valerie Anne Rolande

2011-01-01

One explanation for productivity dispersion is that the quality of inputs differs across firms. We add labor market history variables such as experience and firm and industry tenure, as well as general human capital measures such as schooling and sex. Adding these variables decreases the ratio...... of the 90th to 10th productivity quantiles from 3.27 to 2.68 across eight Danish manufacturing and service industries. We also use the wage bill and worker fixed effects. We find that the wage bill explains as much dispersion as human capital measures....

Enhancing the comparability of costing methods: cross-country variability in the prices of non-traded inputs to health programmes.

Science.gov (United States)

Johns, Benjamin; Adam, Taghreed; Evans, David B

2006-04-24

National and international policy makers have been increasing their focus on developing strategies to enable poor countries achieve the millennium development goals. This requires information on the costs of different types of health interventions and the resources needed to scale them up, either singly or in combinations. Cost data also guides decisions about the most appropriate mix of interventions in different settings, in view of the increasing, but still limited, resources available to improve health. Many cost and cost-effectiveness studies include only the costs incurred at the point of delivery to beneficiaries, omitting those incurred at other levels of the system such as administration, media, training and overall management. The few studies that have measured them directly suggest that they can sometimes account for a substantial proportion of total costs, so that their omission can result in biased estimates of the resources needed to run a programme or the relative cost-effectiveness of different choices. However, prices of different inputs used in the production of health interventions can vary substantially within a country. Basing cost estimates on a single price observation runs the risk that the results are based on an outlier observation rather than the typical costs of the input. We first explore the determinants of the observed variation in the prices of selected "non-traded" intermediate inputs to health programmes--printed matter and media advertising, and water and electricity--accounting for variation within and across countries. We then use the estimated relationship to impute average prices for countries where limited data are available with uncertainty intervals. Prices vary across countries with GDP per capita and a number of determinants of supply and demand. Media and printing were inelastic with respect to GDP per capita, with a positive correlation, while the utilities had a surprisingly negative relationship. All equations had

Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity.

Science.gov (United States)

Lin, I-Chun; Xing, Dajun; Shapley, Robert

2012-12-01

One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1's function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.

SOERP, Statistics and 2. Order Error Propagation for Function of Random Variables

International Nuclear Information System (INIS)

Cox, N. D.; Miller, C. F.

1985-01-01

1 - Description of problem or function: SOERP computes second-order error propagation equations for the first four moments of a function of independently distributed random variables. SOERP was written for a rigorous second-order error propagation of any function which may be expanded in a multivariable Taylor series, the input variables being independently distributed. The required input consists of numbers directly related to the partial derivatives of the function, evaluated at the nominal values of the input variables and the central moments of the input variables from the second through the eighth. 2 - Method of solution: The development of equations for computing the propagation of errors begins by expressing the function of random variables in a multivariable Taylor series expansion. The Taylor series expansion is then truncated, and statistical operations are applied to the series in order to obtain equations for the moments (about the origin) of the distribution of the computed value. If the Taylor series is truncated after powers of two, the procedure produces second-order error propagation equations. 3 - Restrictions on the complexity of the problem: The maximum number of component variables allowed is 30. The IBM version will only process one set of input data per run

Geometric correlations and multifractals

International Nuclear Information System (INIS)

Amritkar, R.E.

1991-07-01

There are many situations where the usual statistical methods are not adequate to characterize correlations in the system. To characterize such situations we introduce mutual correlation dimensions which describe geometric correlations in the system. These dimensions allow us to distinguish between variables which are perfectly correlated with or without a phase lag, variables which are uncorrelated and variables which are partially correlated. We demonstrate the utility of our formalism by considering two examples from dynamical systems. The first example is about the loss of memory in chaotic signals and describes auto-correlations while the second example is about synchronization of chaotic signals and describes cross-correlations. (author). 19 refs, 6 figs

A MAD Explanation for the Correlation between Bulk Lorentz Factor and Minimum Variability Timescale

Science.gov (United States)

Lloyd-Ronning, Nicole; Lei, Wei-hua; Xie, Wei

2018-04-01

We offer an explanation for the anti-correlation between the minimum variability timescale (MTS) in the prompt emission light curve of gamma-ray bursts (GRBs) and the estimated bulk Lorentz factor of these GRBs, in the context of a magnetically arrested disk (MAD) model. In particular, we show that previously derived limits on the maximum available energy per baryon in a Blandford-Znajek jet leads to a relationship between the characteristic MAD timescale in GRBs and the maximum bulk Lorentz factor: tMAD∝Γ-6, somewhat steeper than (although within the error bars of) the fitted relationship found in the GRB data. Similarly, the MAD model also naturally accounts for the observed anti-correlation between MTS and gamma-ray luminosity L in the GRB data, and we estimate the accretion rates of the GRB disk (given these luminosities) in the context of this model. Both of these correlations (MTS - Γ and MTS - L) are also observed in the AGN data, and we discuss the implications of our results in the context of both GRB and blazar systems.

Presentation of valid correlations in some morphological variables and basic and specific motor skills in young people aged 13-14 years engaged in basketball

Directory of Open Access Journals (Sweden)

Florian Miftari

2018-05-01

Full Text Available Study-research deals with younger students of both sexes aged 13-14, who, besides attending classes of physical education and sports, also practice in basketball schools in the city of Pristina. The experiment contains a total of 7 morphological variables, while four tests of basic motion skills and seven variables are from specific motion skills. In this study, the verification and analysis of the correlation of morphological characteristics and basic and situational motor skills in both groups of both sexes (boys and girls were treated. Based on the results obtained between several variables, valid correlations with high coefficients are presented, whereas among the variables are presented correlations with optimal values. The experimentation in question includes the number of 80 entities of both sexes; the group of 40 boys and the other group consisting of 40 girls who have undergone the tests for this study-experiment.

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

Science.gov (United States)

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

2018-06-01

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

Suprathreshold stochastic resonance in neural processing tuned by correlation.

Science.gov (United States)

Durrant, Simon; Kang, Yanmei; Stocks, Nigel; Feng, Jianfeng

2011-07-01

Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.

Correlations between the changes in patients' dental-facial morphology at the end of the orthodontic treatment and the psychological variables.

Science.gov (United States)

Vaida, Ligia; Pirte, Adriana; Corega, Claudia; Slăvescu, D; Muţiu, Gabriela

2009-01-01

The purpose of this research was to assess the impact that the improvement of patients' dental-facial morphology has at the end of the orthodontic treatment upon the following psychological variables: self-esteem, current self-related thoughts as well as upon the variables of social self-esteem and performance. The number of patients included in the study was of 168 (82 children and 86 adolescents) who carried out the orthodontic treatment. At the end of the active treatment, we applied to all patients the assessment instruments for the level of self- esteem and self-related current thoughts: the Rosenberg's Self-Esteem Scale and the Heatherton & Polivy Current Thoughts Scale. As far as the patients in the study are concerned, the improvement of their facial aspect at the end of the treatment showed a significantly positive correlation with the variables of global self-esteem, self-related current thoughts, social self-esteem and performance, with the exception of the girls in children study group who showed no correlations between physical aspect and the performance variable.

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

Science.gov (United States)

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

A Novel Coupled State/Input/Parameter Identification Method for Linear Structural Systems

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Zhimin Wan

2018-01-01

Full Text Available In many engineering applications, unknown states, inputs, and parameters exist in the structures. However, most methods require one or two of these variables to be known in order to identify the other(s. Recently, the authors have proposed a method called EGDF for coupled state/input/parameter identification for nonlinear system in state space. However, the EGDF method based solely on acceleration measurements is found to be unstable, which can cause the drift of the identified inputs and displacements. Although some regularization methods can be adopted for solving the problem, they are not suitable for joint input-state identification in real time. In this paper, a strategy of data fusion of displacement and acceleration measurements is used to avoid the low-frequency drift in the identified inputs and structural displacements for linear structural systems. Two numerical examples about a plane truss and a single-stage isolation system are conducted to verify the effectiveness of the proposed modified EGDF algorithm.

Inverse Tasks In The Tsunami Problem: Nonlinear Regression With Inaccurate Input Data

Science.gov (United States)

Lavrentiev, M.; Shchemel, A.; Simonov, K.

A variant of modified training functional that allows considering inaccurate input data is suggested. A limiting case when a part of input data is completely undefined, and, therefore, a problem of reconstruction of hidden parameters should be solved, is also considered. Some numerical experiments are presented. It is assumed that a dependence of known output variables on known input ones should be found is the classic problem definition, which is widely used in the majority of neural nets algorithms. The quality of approximation is evaluated as a performance function. Often the error of the task is evaluated as squared distance between known input data and predicted data multiplied by weighed coefficients. These coefficients may be named "precision coefficients". When inputs are not known exactly, natural generalization of performance function is adding member that responsible for distance between known inputs and shifted inputs, which lessen model's error. It is desirable that the set of variable parameters is compact for training to be con- verging. In the above problem it is possible to choose variants of demands of a priori compactness, which allow meaningful interpretation in the smoothness of the model dependence. Two kinds of regularization was used, first limited squares of coefficients responsible for nonlinearity and second limited multiplication of the above coeffi- cients and linear coefficients. Asymptotic universality of neural net ability to approxi- mate various smooth functions with any accuracy by increase of the number of tunable parameters is often the base for selecting a type of neural net approximation. It is pos- sible to show that used neural net will approach to Fourier integral transform, which approximate abilities are known, with increasing of the number of tunable parameters. In the limiting case, when input data is set with zero precision, the problem of recon- struction of hidden parameters with observed output data appears. The

VARIABILITY AND CORRELATION OF AGRONOMIC CHARACTERS OF MUNGBEAN GERMPLASM AND THEIR UTILIZATION FOR VARIETY IMPROVEMENT PROGRAM Lukman Hakim

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Lukman Hakim

2016-10-01

Full Text Available Information on the variability and correlation between agronomic characters of mungbean accessions with their yield are important for supporting breeding program of the plant. A total of 350 mungbean accessions were evaluated at Muara Experimental Farm, Indonesian Center for Food Crops Research and Development, Bogor, during the dry season of 2005. The experiment was conducted in a completely randomized block design with three replications. Each accession was planted in two rows of 5 m long. Plant spacing was 40 cm x 20 cm, two plants per hill. Correlation and path coefficient analyses were used to quantifythe magnitude of the relationship between yield components and grain yield. The variability among the accessions was significant for most of the characters studied, especially for days to maturity, plant height, pods per plant, and seed size. Among the yield components, the number of pods per plant and plant height positively correlated with the grain yield, but theseed size negatively correlated with grain yield. The direct effects of the number of pods per plant and plant height on seed yield as indicated by path coefficient were the highest, while other causal effects were small or negative. Yield variation (1- R2 attributable to the nine yield component variables was slightly high (61.23%, which means that mungbean accessions with high grain yield should have sufficient plant height and high number of pods per plant. Therefore, these parameters (number of pods per plant and plant height can be used as the selection criteria in mungbean breeding program. These criteria can be visualized during bulk selection on the early generation stage of F2 to F4, and subsequently on line development of individual plant (pedigree of F5.

Facies interpretations and lateral variability based on correlation of conventional core in the Logan canyon and Mississauga formations of the Scotian Basin

Energy Technology Data Exchange (ETDEWEB)

Piper, D.J.W. [Geological Survey of Canada (Canada); Gould, K.M.; Pe-Piper, G. [Saint Mary' s University (Canada)], email: 075353g@acadiau.ca

2011-07-01

In the Lower Cretaceous of the Scotian Basin in Canada, sediment facies have been interpreted mostly using vertical successions of rock. However, other studies show that the lateral extent and variability of sediment facies must be understood to assess reservoir extent and connectivity. The aim of this paper is to present the investigation of two areas of the Scotian Basin. In each area, a regional correlation was performed using gamma ray well logs and the lithology, sedimentary and biogenic structures were determined for 67 different cores. It was found that the determination of facies and vertical successions was useful for comparing and correlating across multiple wells. In addition it was shown that gamma logs are effective for regional correlation but can only correlate major changes. This paper demonstrated that gamma logs are useful for performing facies interpretations and determining lateral variability.

Experimental demonstration of continuous variable cloning with phase-conjugate inputs

DEFF Research Database (Denmark)

Sabuncu, Metin; Andersen, Ulrik Lund; Leuchs, G.

2007-01-01

We report the first experimental demonstration of continuous variable cloning of phase-conjugate coherent states as proposed by Cerf and Iblisdir [Phys. Rev. Lett. 87, 247903 (2001)]. In contrast to this proposal, the cloning transformation is accomplished using only linear optical components......, homodyne detection, and feedforward. As a result of combining phase conjugation with a joint measurement strategy, superior cloning is demonstrated with cloning fidelities reaching 89%....

CD117 immunoexpression in canine mast cell tumours: correlations with pathological variables and proliferation markers

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Pires Maria A

2007-08-01

Full Text Available Abstract Background Cutaneous mast cell tumours are one of the most common neoplasms in dogs and show a highly variable biologic behaviour. Several prognosis tools have been proposed for canine mast cell tumours, including histological grading and cell proliferation markers. CD117 is a receptor tyrosine kinase thought to play a key role in human and canine mast cell neoplasms. Normal (membrane-associated and aberrant (cytoplasmic, focal or diffuse CD117 immunoexpression patterns have been identified in canine mast cell tumours. Cytoplasmic CD117 expression has been found to correlate with higher histological grade and with a worsened post-surgical prognosis. This study addresses the role of CD117 in canine mast cell tumours by studying the correlations between CD117 immunoexpression patterns, two proliferation markers (Ki67 and AgNORs histological grade, and several other pathological variables. Results Highly significant (p Conclusion These findings highlight the key role of CD117 in the biopathology of canine MCTs and confirm the relationship between aberrant CD117 expression and increased cell proliferation and higher histological grade. Further studies are needed to unravel the cellular mechanisms underlying focal and diffuse cytoplasmic CD117 staining patterns, and their respective biopathologic relevance.

Quantum-optical input-output relations for dispersive and lossy multilayer dielectric plates

International Nuclear Information System (INIS)

Gruner, T.; Welsch, D.

1996-01-01

Using the Green-function approach to the problem of quantization of the phenomenological Maxwell theory, the propagation of quantized radiation through dispersive and absorptive multilayer dielectric plates is studied. Input-output relations are derived, with special emphasis on the determination of the quantum noise generators associated with the absorption of radiation inside the dielectric matter. The input-output relations are used to express arbitrary correlation functions of the outgoing field in terms of correlation functions of the incoming field and those of the noise generators. To illustrate the theory, photons at dielectric tunneling barriers are considered. It is shown that inclusion in the calculations of losses in the photonic band gaps may substantially change the barrier traversal times. copyright 1996 The American Physical Society

Genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah

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Ellen Grippi Lira

Full Text Available ABSTRACT: Sunflower (Helianthus annuus L. is an annual crop that stands out for its production of high quality oil and for an efficient selection, being necessary to estimate the components of genetic and phenotypic variance. This study aimed to estimate genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah, evaluating the characters grain yield (YIELD, days to start flowering (DFL based on flowering date in R5, chapter length (CL, weight of a thousand achenes (WTA, plant height (H and oil content (OilC of 16 sunflower genotypes. The experiment was conducted at Embrapa Cerrados, Planaltina, DF, situated at 15º 35’ 30”S latitude, 47º 42’ 30”W longitude and 1.007m above sea level, in soil classified as dystroferric Oxisol. The experimental design used was a complete randomized block with four replicates. The nature for the effects of genotypes and blocks was fixed. Except for the character chapter length, genetic variance was the main component of the phenotypic variance among the genotypes, indicating high genetic variability and experimental efficiency with proper environmental control. In absolute terms, the genetic correlations were superior to phenotypic and environmental. The high values reported for heritability and selective accuracy indicated efficiency of phenotypic selection. Results showed high genetic variability among genotypes, which may contribute to the genetic improvement of sunflower.

Correlated binomial models and correlation structures

International Nuclear Information System (INIS)

Hisakado, Masato; Kitsukawa, Kenji; Mori, Shintaro

2006-01-01

We discuss a general method to construct correlated binomial distributions by imposing several consistent relations on the joint probability function. We obtain self-consistency relations for the conditional correlations and conditional probabilities. The beta-binomial distribution is derived by a strong symmetric assumption on the conditional correlations. Our derivation clarifies the 'correlation' structure of the beta-binomial distribution. It is also possible to study the correlation structures of other probability distributions of exchangeable (homogeneous) correlated Bernoulli random variables. We study some distribution functions and discuss their behaviours in terms of their correlation structures

Fine-scale geographic variations of inflammatory bowel disease in France: correlation with socioeconomic and house equipment variables.

Science.gov (United States)

Nerich, Virginie; Monnet, Elisabeth; Weill, Alain; Vallier, Nathalie; Vanbockstael, Vincent; Auleley, Guy-Robert; Balaire, Corine; Dubost, Patrick; Rican, Stéphane; Allemand, Hubert; Carbonnel, Franck

2010-05-01

In a previous study we found a north-south gradient for Crohn's disease (CD) incidence in France. The aim of the present study was to determine if socioeconomic factors may influence the geographic distribution of CD and ulcerative colitis (UC) in France. Using the national health insurance databases, incidence rates of CD and UC were estimated for each of 341 metropolitan "job areas" in 2000-2002. Relationships between incidence rates and relevant contextual variables from the 1999 French census were tested for significance using a Poisson regression. Mapping of smoothed relative risks (sRR) for CD and UC at the scale of job areas, using a Bayesian approach and adjusting for significant contextual variables, was carried out in order to search for geographic variations. CD incidence rates were negatively related to the percentage of farmers and to the percentage of housing with bathroom and toilets and positively related to the unemployment rate and to the percentage of households below the poverty threshold. Mapping of sRR for CD showed a clear north-south gradient, which was slightly improved after including the percentage of farmers and the percentage of housing with toilets. In UC we found no significant correlation between either incidence and socioeconomic variables or incidence and house equipment variables, and there was no north-south gradient. However, there was a positive and significant correlation between CD and UC incidence. The present study shows that geographic risk factors of CD in France are northern latitude, nonrural areas, and areas with poor sanitary house equipment. Among these factors the most important is northern latitude.

Sensory Synergy as Environmental Input Integration

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Fady eAlnajjar

2015-01-01

Full Text Available The development of a method to feed proper environmental inputs back to the central nervous system (CNS remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with 9 healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis’ sensory system to make the controller simpler

Sensory synergy as environmental input integration.

Science.gov (United States)

Alnajjar, Fady; Itkonen, Matti; Berenz, Vincent; Tournier, Maxime; Nagai, Chikara; Shimoda, Shingo

2014-01-01

The development of a method to feed proper environmental inputs back to the central nervous system (CNS) remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with nine healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis' sensory system to make the controller simpler.

Enhancing the comparability of costing methods: cross-country variability in the prices of non-traded inputs to health programmes

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Evans David B

2006-04-01

Full Text Available Abstract Background National and international policy makers have been increasing their focus on developing strategies to enable poor countries achieve the millennium development goals. This requires information on the costs of different types of health interventions and the resources needed to scale them up, either singly or in combinations. Cost data also guides decisions about the most appropriate mix of interventions in different settings, in view of the increasing, but still limited, resources available to improve health. Many cost and cost-effectiveness studies include only the costs incurred at the point of delivery to beneficiaries, omitting those incurred at other levels of the system such as administration, media, training and overall management. The few studies that have measured them directly suggest that they can sometimes account for a substantial proportion of total costs, so that their omission can result in biased estimates of the resources needed to run a programme or the relative cost-effectiveness of different choices. However, prices of different inputs used in the production of health interventions can vary substantially within a country. Basing cost estimates on a single price observation runs the risk that the results are based on an outlier observation rather than the typical costs of the input. Methods We first explore the determinants of the observed variation in the prices of selected "non-traded" intermediate inputs to health programmes – printed matter and media advertising, and water and electricity – accounting for variation within and across countries. We then use the estimated relationship to impute average prices for countries where limited data are available with uncertainty intervals. Results Prices vary across countries with GDP per capita and a number of determinants of supply and demand. Media and printing were inelastic with respect to GDP per capita, with a positive correlation, while the utilities

Relationship between radionuclides and sedimentological variables in the South Atlantic Continental Margin

International Nuclear Information System (INIS)

Ferreira, Paulo A.L.; Figueira, Rubens C.L.

2015-01-01

There is a lack of information regarding marine radioactivity in sediments of the Continental Margin of the South Atlantic. "1"3"7Cs and "4"0K radioactivity and sedimentological variables were determined in superficial sediment samples. It was demonstrated that "4"0K is a good indicator for sediment granulometry, whilst "1"3"7Cs presents a good correlation with its chemical composition. Moreover, it was identified through the radiometric data the occurrence of input of allochtonous matter to the Brazilian southernmost compartment from the Rio de La Plata estuary, as previously reported in the literature. (author)

Computational Techniques for Model Predictive Control of Large-Scale Systems with Continuous-Valued and Discrete-Valued Inputs

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Koichi Kobayashi

2013-01-01

Full Text Available We propose computational techniques for model predictive control of large-scale systems with both continuous-valued control inputs and discrete-valued control inputs, which are a class of hybrid systems. In the proposed method, we introduce the notion of virtual control inputs, which are obtained by relaxing discrete-valued control inputs to continuous variables. In online computation, first, we find continuous-valued control inputs and virtual control inputs minimizing a cost function. Next, using the obtained virtual control inputs, only discrete-valued control inputs at the current time are computed in each subsystem. In addition, we also discuss the effect of quantization errors. Finally, the effectiveness of the proposed method is shown by a numerical example. The proposed method enables us to reduce and decentralize the computation load.

Weather on Other Worlds. IV. Hα Emission and Photometric Variability Are Not Correlated in L0–T8 Dwarfs

International Nuclear Information System (INIS)

Miles-Páez, Paulo A.; Metchev, Stanimir A.; Heinze, Aren; Apai, Dániel

2017-01-01

Recent photometric studies have revealed that surface spots that produce flux variations are present on virtually all L and T dwarfs. Their likely magnetic or dusty nature has been a much-debated problem, the resolution to which has been hindered by paucity of diagnostic multi-wavelength observations. To test for a correlation between magnetic activity and photometric variability, we searched for H α emission among eight L3–T2 ultra-cool dwarfs with extensive previous photometric monitoring, some of which are known to be variable at 3.6 μ m or 4.5 μ m. We detected H α only in the non-variable T2 dwarf 2MASS J12545393−0122474. The remaining seven objects do not show H α emission, even though six of them are known to vary photometrically. Combining our results with those for 86 other L and T dwarfs from the literature show that the detection rate of H α emission is very high (94%) for spectral types between L0 and L3.5 and much smaller (20%) for spectral types ≥L4, while the detection rate of photometric variability is approximately constant (30%–55%) from L0 to T8 dwarfs. We conclude that chromospheric activity, as evidenced by H α emission, and large-amplitude photometric variability are not correlated. Consequently, dust clouds are the dominant driver of the observed variability of ultra-cool dwarfs at spectral types, at least as early as L0.

Weather on Other Worlds. IV. Hα Emission and Photometric Variability Are Not Correlated in L0–T8 Dwarfs

Energy Technology Data Exchange (ETDEWEB)

Miles-Páez, Paulo A.; Metchev, Stanimir A. [Department of Physics and Astronomy and Centre for Planetary Science and Exploration, The University of Western Ontario, London, Ontario N6A 3K7 (Canada); Heinze, Aren [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Apai, Dániel, E-mail: ppaez@uwo.ca [The University of Arizona, Department of Astronomy, 933 North Cherry Avenue, Tucson, AZ 85721 (United States)

2017-05-10

Recent photometric studies have revealed that surface spots that produce flux variations are present on virtually all L and T dwarfs. Their likely magnetic or dusty nature has been a much-debated problem, the resolution to which has been hindered by paucity of diagnostic multi-wavelength observations. To test for a correlation between magnetic activity and photometric variability, we searched for H α emission among eight L3–T2 ultra-cool dwarfs with extensive previous photometric monitoring, some of which are known to be variable at 3.6 μ m or 4.5 μ m. We detected H α only in the non-variable T2 dwarf 2MASS J12545393−0122474. The remaining seven objects do not show H α emission, even though six of them are known to vary photometrically. Combining our results with those for 86 other L and T dwarfs from the literature show that the detection rate of H α emission is very high (94%) for spectral types between L0 and L3.5 and much smaller (20%) for spectral types ≥L4, while the detection rate of photometric variability is approximately constant (30%–55%) from L0 to T8 dwarfs. We conclude that chromospheric activity, as evidenced by H α emission, and large-amplitude photometric variability are not correlated. Consequently, dust clouds are the dominant driver of the observed variability of ultra-cool dwarfs at spectral types, at least as early as L0.

Influence of forced respiration on nonlinear dynamics in heart rate variability

DEFF Research Database (Denmark)

Kanters, J K; Højgaard, M V; Agner, E

1997-01-01

Although it is doubtful whether the normal sinus rhythm can be described as low-dimensional chaos, there is evidence for inherent nonlinear dynamics and determinism in time series of consecutive R-R intervals. However, the physiological origin for these nonlinearities is unknown. The aim...... with a metronome set to 12 min(-1). Nonlinear dynamics were measured as the correlation dimension and the nonlinear prediction error. Complexity expressed as correlation dimension was unchanged from normal respiration, 9.1 +/- 0.5, compared with forced respiration, 9.3 +/- 0.6. Also, nonlinear determinism...... expressed as the nonlinear prediction error did not differ between spontaneous respiration, 32.3 +/- 3.4 ms, and forced respiration, 31.9 +/- 5.7. It is concluded that the origin of the nonlinear dynamics in heart rate variability is not a nonlinear input from the respiration into the cardiovascular...

Learning from correlated patterns by simple perceptrons

Energy Technology Data Exchange (ETDEWEB)

Shinzato, Takashi; Kabashima, Yoshiyuki [Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama 226-8502 (Japan)], E-mail: shinzato@sp.dis.titech.ac.jp, E-mail: kaba@dis.titech.ac.jp

2009-01-09

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance.

Learning from correlated patterns by simple perceptrons

Science.gov (United States)

Shinzato, Takashi; Kabashima, Yoshiyuki

2009-01-01

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance.

Learning from correlated patterns by simple perceptrons

International Nuclear Information System (INIS)

Shinzato, Takashi; Kabashima, Yoshiyuki

2009-01-01

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance

Learning from input and memory evolution: points of vulnerability on a pathway to mastery in word learning.

Science.gov (United States)

Storkel, Holly L

2015-02-01

Word learning consists of at least two neurocognitive processes: learning from input during training and memory evolution during gaps between training sessions. Fine-grained analysis of word learning by normal adults provides evidence that learning from input is swift and stable, whereas memory evolution is a point of potential vulnerability on the pathway to mastery. Moreover, success during learning from input is linked to positive outcomes from memory evolution. These two neurocognitive processes can be overlaid on to components of clinical treatment with within-session variables (i.e. dose form and dose) potentially linked to learning from input and between-session variables (i.e. dose frequency) linked to memory evolution. Collecting data at the beginning and end of a treatment session can be used to identify the point of vulnerability in word learning for a given client and the appropriate treatment component can then be adjusted to improve the client's word learning. Two clinical cases are provided to illustrate this approach.

TART input manual

International Nuclear Information System (INIS)

Kimlinger, J.R.; Plechaty, E.F.

1982-01-01

The TART code is a Monte Carlo neutron/photon transport code that is only on the CRAY computer. All the input cards for the TART code are listed, and definitions for all input parameters are given. The execution and limitations of the code are described, and input for two sample problems are given

Does linguistic input play the same role in language learning for children with and without early brain injury?

Science.gov (United States)

Rowe, Meredith L; Levine, Susan C; Fisher, Joan A; Goldin-Meadow, Susan

2009-01-01

Children with unilateral pre- or perinatal brain injury (BI) show remarkable plasticity for language learning. Previous work highlights the important role that lesion characteristics play in explaining individual variation in plasticity in the language development of children with BI. The current study examines whether the linguistic input that children with BI receive from their caregivers also contributes to this early plasticity, and whether linguistic input plays a similar role in children with BI as it does in typically developing (TD) children. Growth in vocabulary and syntactic production is modeled for 80 children (53 TD, 27 BI) between 14 and 46 months. Findings indicate that caregiver input is an equally potent predictor of vocabulary growth in children with BI and in TD children. In contrast, input is a more potent predictor of syntactic growth for children with BI than for TD children. Controlling for input, lesion characteristics (lesion size, type, seizure history) also affect the language trajectories of children with BI. Thus, findings illustrate how both variability in the environment (linguistic input) and variability in the organism (lesion characteristics) work together to contribute to plasticity in language learning.

Quantum Correlations in Nonlocal Boson Sampling.

Science.gov (United States)

Shahandeh, Farid; Lund, Austin P; Ralph, Timothy C

2017-09-22

Determination of the quantum nature of correlations between two spatially separated systems plays a crucial role in quantum information science. Of particular interest is the questions of if and how these correlations enable quantum information protocols to be more powerful. Here, we report on a distributed quantum computation protocol in which the input and output quantum states are considered to be classically correlated in quantum informatics. Nevertheless, we show that the correlations between the outcomes of the measurements on the output state cannot be efficiently simulated using classical algorithms. Crucially, at the same time, local measurement outcomes can be efficiently simulated on classical computers. We show that the only known classicality criterion violated by the input and output states in our protocol is the one used in quantum optics, namely, phase-space nonclassicality. As a result, we argue that the global phase-space nonclassicality inherent within the output state of our protocol represents true quantum correlations.

A Practical pedestrian approach to parsimonious regression with inaccurate inputs

Directory of Open Access Journals (Sweden)

Seppo Karrila

2014-04-01

Full Text Available A measurement result often dictates an interval containing the correct value. Interval data is also created by roundoff, truncation, and binning. We focus on such common interval uncertainty in data. Inaccuracy in model inputs is typically ignored on model fitting. We provide a practical approach for regression with inaccurate data: the mathematics is easy, and the linear programming formulations simple to use even in a spreadsheet. This self-contained elementary presentation introduces interval linear systems and requires only basic knowledge of algebra. Feature selection is automatic; but can be controlled to find only a few most relevant inputs; and joint feature selection is enabled for multiple modeled outputs. With more features than cases, a novel connection to compressed sensing emerges: robustness against interval errors-in-variables implies model parsimony, and the input inaccuracies determine the regularization term. A small numerical example highlights counterintuitive results and a dramatic difference to total least squares.

Input-output interactions and optimal monetary policy

DEFF Research Database (Denmark)

Petrella, Ivan; Santoro, Emiliano

2011-01-01

This paper deals with the implications of factor demand linkages for monetary policy design in a two-sector dynamic general equilibrium model. Part of the output of each sector serves as a production input in both sectors, in accordance with a realistic input–output structure. Strategic...... complementarities induced by factor demand linkages significantly alter the transmission of shocks and amplify the loss of social welfare under optimal monetary policy, compared to what is observed in standard two-sector models. The distinction between value added and gross output that naturally arises...... in this context is of key importance to explore the welfare properties of the model economy. A flexible inflation targeting regime is close to optimal only if the central bank balances inflation and value added variability. Otherwise, targeting gross output variability entails a substantial increase in the loss...

Correlating multidimensional fetal heart rate variability analysis with acid-base balance at birth

International Nuclear Information System (INIS)

Frasch, Martin G; Durosier, Lucien D; Xu, Yawen; Wang, Xiaogang; Gao, Xin; Stampalija, Tamara; Herry, Christophe; Seely, Andrew JE; Casati, Daniela; Ferrazzi, Enrico; Alfirevic, Zarko

2014-01-01

Fetal monitoring during labour currently fails to accurately detect acidemia. We developed a method to assess the multidimensional properties of fetal heart rate variability (fHRV) from trans-abdominal fetal electrocardiogram (fECG) during labour. We aimed to assess this novel bioinformatics approach for correlation between fHRV and neonatal pH or base excess (BE) at birth. We enrolled a prospective pilot cohort of uncomplicated singleton pregnancies at 38–42 weeks’ gestation in Milan, Italy, and Liverpool, UK. Fetal monitoring was performed by standard cardiotocography. Simultaneously, with fECG (high sampling frequency) was recorded. To ensure clinician blinding, fECG information was not displayed. Data from the last 60 min preceding onset of second-stage labour were analyzed using clinically validated continuous individualized multiorgan variability analysis (CIMVA) software in 5 min overlapping windows. CIMVA allows simultaneous calculation of 101 fHRV measures across five fHRV signal analysis domains. We validated our mathematical prediction model internally with 80:20 cross-validation split, comparing results to cord pH and BE at birth. The cohort consisted of 60 women with neonatal pH values at birth ranging from 7.44 to 6.99 and BE from −0.3 to −18.7 mmol L −1 . Our model predicted pH from 30 fHRV measures (R 2 = 0.90, P < 0.001) and BE from 21 fHRV measures (R 2 = 0.77, P < 0.001). Novel bioinformatics approach (CIMVA) applied to fHRV derived from trans-abdominal fECG during labor correlated well with acid-base balance at birth. Further refinement and validation in larger cohorts are needed. These new measurements of fHRV might offer a new opportunity to predict fetal acid-base balance at birth. (fast track communication)

Variable identification in group method of data handling methodology

Energy Technology Data Exchange (ETDEWEB)

Pereira, Iraci Martinez, E-mail: martinez@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Bueno, Elaine Inacio [Instituto Federal de Educacao, Ciencia e Tecnologia, Guarulhos, SP (Brazil)

2011-07-01

The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a preselected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and Artificial Neural Network - ANN methodologies, and applied to the IPEN research Reactor IEA-R1. The GMDH was used to study the best set of variables to be used to train an ANN, resulting in a best monitoring variable estimative. The system performs the monitoring by comparing these estimative calculated values with measured ones. The IPEN Reactor Data Acquisition System is composed of 58 variables (process and nuclear variables). As the GMDH is a self-organizing methodology, the input variables choice is made automatically, and the real input variables used in the Monitoring and Diagnosis System were not showed in the final result. This work presents a study of variable identification of GMDH methodology by means of an algorithm that works in parallel with the GMDH algorithm and traces the initial variables paths, resulting in an identification of the variables that composes the best Monitoring and Diagnosis Model. (author)

Variable identification in group method of data handling methodology

International Nuclear Information System (INIS)

Pereira, Iraci Martinez; Bueno, Elaine Inacio

2011-01-01

The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a preselected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and Artificial Neural Network - ANN methodologies, and applied to the IPEN research Reactor IEA-R1. The GMDH was used to study the best set of variables to be used to train an ANN, resulting in a best monitoring variable estimative. The system performs the monitoring by comparing these estimative calculated values with measured ones. The IPEN Reactor Data Acquisition System is composed of 58 variables (process and nuclear variables). As the GMDH is a self-organizing methodology, the input variables choice is made automatically, and the real input variables used in the Monitoring and Diagnosis System were not showed in the final result. This work presents a study of variable identification of GMDH methodology by means of an algorithm that works in parallel with the GMDH algorithm and traces the initial variables paths, resulting in an identification of the variables that composes the best Monitoring and Diagnosis Model. (author)

Simulation of speckle patterns with pre-defined correlation distributions

Science.gov (United States)

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S.

2016-01-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques. PMID:27231589

Using correlation functions as free decays

DEFF Research Database (Denmark)

Brincker, Rune; Amador, Sandro; Juul, Martin

It is a general assumption in OMA that correlation functions are free decays. In multiple input OMA this assumption also implies that any column in the correlation function matrix is to be considered as multiple output free decays. This assumption is discussed in this paper together with issues...... concerning estimation and application of correlations functions in OMA....

Input-output supervisor

International Nuclear Information System (INIS)

Dupuy, R.

1970-01-01

The input-output supervisor is the program which monitors the flow of informations between core storage and peripheral equipments of a computer. This work is composed of three parts: 1 - Study of a generalized input-output supervisor. With sample modifications it looks like most of input-output supervisors which are running now on computers. 2 - Application of this theory on a magnetic drum. 3 - Hardware requirement for time-sharing. (author) [fr

Evaluating the effects of variable water chemistry on bacterial transport during infiltration.

Science.gov (United States)

Zhang, Haibo; Nordin, Nahjan Amer; Olson, Mira S

2013-07-01

Bacterial infiltration through the subsurface has been studied experimentally under different conditions of interest and is dependent on a variety of physical, chemical and biological factors. However, most bacterial transport studies fail to adequately represent the complex processes occurring in natural systems. Bacteria are frequently detected in stormwater runoff, and may present risk of microbial contamination during stormwater recharge into groundwater. Mixing of stormwater runoff with groundwater during infiltration results in changes in local solution chemistry, which may lead to changes in both bacterial and collector surface properties and subsequent bacterial attachment rates. This study focuses on quantifying changes in bacterial transport behavior under variable solution chemistry, and on comparing the influences of chemical variability and physical variability on bacterial attachment rates. Bacterial attachment rate at the soil-water interface was predicted analytically using a combined rate equation, which varies temporally and spatially with respect to changes in solution chemistry. Two-phase Monte Carlo analysis was conducted and an overall input-output correlation coefficient was calculated to quantitatively describe the importance of physiochemical variation on the estimates of attachment rate. Among physical variables, soil particle size has the highest correlation coefficient, followed by porosity of the soil media, bacterial size and flow velocity. Among chemical variables, ionic strength has the highest correlation coefficient. A semi-reactive microbial transport model was developed within HP1 (HYDRUS1D-PHREEQC) and applied to column transport experiments with constant and variable solution chemistries. Bacterial attachment rates varied from 9.10×10(-3)min(-1) to 3.71×10(-3)min(-1) due to mixing of synthetic stormwater (SSW) with artificial groundwater (AGW), while bacterial attachment remained constant at 9.10×10(-3)min(-1) in a constant

Identification of Hadronically-Decaying W Boson Top Quarks Using High-Level Features as Input to Boosted Decision Trees and Deep Neural Networks in ATLAS at #sqrt{s} = 13 TeV

CERN Document Server

Nitta, Tatsumi; The ATLAS collaboration

2017-01-01

The application of boosted decision trees and deep neural networks to the identification of hadronically-decaying W bosons and top quarks using high-level jet observables as inputs is investigated using Monte Carlo simulations. In the case of both boosted decision trees and deep neural networks, the use of machine learning techniques is found to improve the background rejection with respect to simple reference single jet substructure and mass taggers. Linear correlations between the resulting classifiers and the substructure variables are also presented.

Implementation of isotope correlation technique for safeguards

International Nuclear Information System (INIS)

Persiani, P.J.; Bucher, R.G.

1989-01-01

The isotopic correlation technique (ICT) is based on the fundamental physics principle that the isotopic compositions of nuclear material in the fuel cycle systems contain information regarding the design and history of nuclear material flow from fuel fabrication, reactor operation, and through input to the reprocessing plant. Isotopic Correlation in conjunction with the gravimetric (or Pu/U) method for mass determination can be developed to provide an independent in-field verification of the reprocessing input accountancy at the dissolver and/or accountancy stage of the reprocessing plant. The Argonne National Laboratory program in isotope correlation techniques is based on three-dimensional reactor physics calculations of characteristic geometries/composition in each reactor class. 10 refs., 1 fig., 3 tabs

Gaseous isotope correlation technique for safeguards at reprocessing facilities

International Nuclear Information System (INIS)

Ohkubo, Michiaki.

1988-03-01

The isotope correlation technique based on gaseous stable fission products can be used as a means of verifying the input measurement to fuel reprocessing plants. This paper reviews the theoretical background of the gaseous fission product isotope correlation technique. The correlations considered are those between burnup and various isotopic ratios of Kr and Xe nuclides. The feasibility of gaseous ICT application to Pu input accountancy of reprocessing facilities is also discussed. The technique offers the possibility of in situ measurement verification by the inspector. (author). 16 refs, 7 figs

Effect of input data variability on estimations of the equivalent constant temperature time for microbial inactivation by HTST and retort thermal processing.

Science.gov (United States)

Salgado, Diana; Torres, J Antonio; Welti-Chanes, Jorge; Velazquez, Gonzalo

2011-08-01

Consumer demand for food safety and quality improvements, combined with new regulations, requires determining the processor's confidence level that processes lowering safety risks while retaining quality will meet consumer expectations and regulatory requirements. Monte Carlo calculation procedures incorporate input data variability to obtain the statistical distribution of the output of prediction models. This advantage was used to analyze the survival risk of Mycobacterium avium subspecies paratuberculosis (M. paratuberculosis) and Clostridium botulinum spores in high-temperature short-time (HTST) milk and canned mushrooms, respectively. The results showed an estimated 68.4% probability that the 15 sec HTST process would not achieve at least 5 decimal reductions in M. paratuberculosis counts. Although estimates of the raw milk load of this pathogen are not available to estimate the probability of finding it in pasteurized milk, the wide range of the estimated decimal reductions, reflecting the variability of the experimental data available, should be a concern to dairy processors. Knowledge of the C. botulinum initial load and decimal thermal time variability was used to estimate an 8.5 min thermal process time at 110 °C for canned mushrooms reducing the risk to 10⁻⁹ spores/container with a 95% confidence. This value was substantially higher than the one estimated using average values (6.0 min) with an unacceptable 68.6% probability of missing the desired processing objective. Finally, the benefit of reducing the variability in initial load and decimal thermal time was confirmed, achieving a 26.3% reduction in processing time when standard deviation values were lowered by 90%. In spite of novel technologies, commercialized or under development, thermal processing continues to be the most reliable and cost-effective alternative to deliver safe foods. However, the severity of the process should be assessed to avoid under- and over

Biostatistics Series Module 6: Correlation and Linear Regression.

Science.gov (United States)

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Gain tuning and fidelity in continuous-variable quantum teleportation

International Nuclear Information System (INIS)

Ide, Toshiki; Hofmann, Holger F.; Furusawa, Akira; Kobayashi, Takayoshi

2002-01-01

The fidelity of continuous-variable teleportation can be optimized by changing the gain in the modulation of the output field. We discuss the gain dependence of fidelity for coherent, vacuum, and one-photon inputs and propose optimal gain tuning strategies for corresponding input selections

Lattice QCD inputs to the CKM unitarity triangle analysis

International Nuclear Information System (INIS)

Laiho, Jack; Lunghi, E.; Van de Water, Ruth S.

2010-01-01

We perform a global fit to the Cabibbo-Kobayashi-Maskawa unitarity triangle using the latest experimental and theoretical constraints. Our emphasis is on the hadronic weak matrix elements that enter the analysis, which must be computed using lattice QCD or other nonperturbative methods. Realistic lattice QCD calculations which include the effects of the dynamical up, down, and strange quarks are now available for all of the standard inputs to the global fit. We therefore present lattice averages for all of the necessary hadronic weak matrix elements. We attempt to account for correlations between lattice QCD results in a reasonable but conservative manner: whenever there are reasons to believe that an error is correlated between two lattice calculations, we take the degree of correlation to be 100%. These averages are suitable for use as inputs both in the global Cabibbo-Kobayashi-Maskawa unitarity triangle fit and other phenomenological analyses. In order to illustrate the impact of the lattice averages, we make standard model predictions for the parameters B-circumflex K , |V cb |, and |V ub |/|V cb |. We find a (2-3)σ tension in the unitarity triangle, depending upon whether we use the inclusive or exclusive determination of |V cb |. If we interpret the tension as a sign of new physics in either neutral kaon or B mixing, we find that the scenario with new physics in kaon mixing is preferred by present data.

Mass Measurements of AGN from Multi-Lorentzian Models of X-ray Variability. I. Sampling Effects in Theoretical Models of the rms^2-M_BH Correlation

DEFF Research Database (Denmark)

Pessah, Martin Elias

2006-01-01

Recent X-ray variability studies suggest that the log of the square of the fractional rms variability amplitude, rms^2, seems to correlate with the log of the AGN black-hole mass, M_BH, with larger black holes being less variable for a fixed time interval. This has motivated the theoretical...

Automatic creation of LabVIEW network shared variables

International Nuclear Information System (INIS)

Kluge, T.; Schroeder, H.

2012-01-01

We are in the process of preparing the LabVIEW controlled system components of our Solid State Direct Drive experiments for the integration into a Supervisory Control And Data Acquisition (SCADA) or distributed control system. The predetermined route to this is the generation of LabVIEW network shared variables that can easily be exported by LabVIEW to the SCADA system using OLE for Process Control (OPC) or other means. Many repetitive tasks are associated with the creation of the shared variables and the required code. We are introducing an efficient and inexpensive procedure that automatically creates shared variable libraries and sets default values for the shared variables. Furthermore, LabVIEW controls are created that are used for managing the connection to the shared variable inside the LabVIEW code operating on the shared variables. The procedure takes as input an XML spread-sheet defining the required input. The procedure utilizes XSLT and LabVIEW scripting. In a later state of the project the code generation can be expanded to also create code and configuration files that will become necessary in order to access the shared variables from the SCADA system of choice. (authors)

Identification of Hadronically-Decaying W Bosons and Top Quarks Using High-Level Features as Input to Boosted Decision Trees and Deep Neural Networks in ATLAS at $\\sqrt{s}$ = 13 TeV

CERN Document Server

The ATLAS collaboration

2017-01-01

The application of boosted decision trees and deep neural networks to the identification of hadronically-decaying W bosons and top quarks using high-level jet observables as inputs is investigated using Monte Carlo simulations. In the case of both boosted decision trees and deep neural networks, the use of machine learning techniques is found to improve the background rejection with respect to simple reference single jet substructure and mass taggers. Linear correlations between the resulting classifiers and the substructure variables are also presented.

Correlated X-ray/UV/optical emission and short-term variability in a Seyfert 1 galaxy NGC 4593

Science.gov (United States)

Pal, Main; Naik, Sachindra

2018-03-01

We present a detailed multifrequency analysis of an intense monitoring programme of Seyfert 1 galaxy NGC 4593 over a duration of nearly for a month with Swift observatory. We used 185 pointings to study the variability in six ultraviolet/optical and two soft (0.3-1.5 keV) and hard X-ray (1.5-10 keV) bands. The amplitude of the observed variability is found to decrease from high energy to low energy (X-ray to optical) bands. Count-count plots of ultraviolet/optical bands with hard X-rays clearly suggest the presence of a mixture of two major components: (i) highly variable component such as hard X-ray emission, and (ii) slowly varying disc-like component. The variations observed in the ultraviolet/optical emission are strongly correlated with the hard X-ray band. Cross-correlation analysis provides the lags for the longer wavelengths compared to the hard X-rays. Such lags clearly suggest that the changes in the ultraviolet/optical bands follow the variations in the hard X-ray band. This implies that the observed variation in longer wavelengths is due to X-ray reprocessing. Though, the measured lag spectrum (lag versus wavelength) is well described by λ4/3 as expected from the standard disc model, the observed lags are found to be longer than the predicted values from standard disc model. This implies that the actual size of the disc of NGC 4593 is larger than the estimated size of standard thin disc as reported in active galactic nuclei such as NGC 5548 and Fairall 9.

Behavioral and electrophysiological evidence for early and automatic detection of phonological equivalence in variable speech inputs.

Science.gov (United States)

Kharlamov, Viktor; Campbell, Kenneth; Kazanina, Nina

2011-11-01

Speech sounds are not always perceived in accordance with their acoustic-phonetic content. For example, an early and automatic process of perceptual repair, which ensures conformity of speech inputs to the listener's native language phonology, applies to individual input segments that do not exist in the native inventory or to sound sequences that are illicit according to the native phonotactic restrictions on sound co-occurrences. The present study with Russian and Canadian English speakers shows that listeners may perceive phonetically distinct and licit sound sequences as equivalent when the native language system provides robust evidence for mapping multiple phonetic forms onto a single phonological representation. In Russian, due to an optional but productive t-deletion process that affects /stn/ clusters, the surface forms [sn] and [stn] may be phonologically equivalent and map to a single phonological form /stn/. In contrast, [sn] and [stn] clusters are usually phonologically distinct in (Canadian) English. Behavioral data from identification and discrimination tasks indicated that [sn] and [stn] clusters were more confusable for Russian than for English speakers. The EEG experiment employed an oddball paradigm with nonwords [asna] and [astna] used as the standard and deviant stimuli. A reliable mismatch negativity response was elicited approximately 100 msec postchange in the English group but not in the Russian group. These findings point to a perceptual repair mechanism that is engaged automatically at a prelexical level to ensure immediate encoding of speech inputs in phonological terms, which in turn enables efficient access to the meaning of a spoken utterance.

Neural correlates of language variability in preschool-aged boys with autism spectrum disorder.

Science.gov (United States)

Naigles, Letitia R; Johnson, Ryan; Mastergeorge, Ann; Ozonoff, Sally; Rogers, Sally J; Amaral, David G; Nordahl, Christine Wu

2017-06-01

Children with autism vary widely in their language abilities, yet the neural correlates of this language variability remain unclear, especially early in development. Diffusion tensor imaging (DTI) was used to examine diffusivity measures along the length of 18 major fiber tracts in 104 preschool-aged boys with autism spectrum disorder (ASD). The boys were assigned to subgroups according to their level of language development (Low: no/low language, Middle: small vocabulary, High: large vocabulary and grammar), based on their raw scores on the expressive language (EL) and receptive language (RL) sections of the Mullen Scales of Early Learning (MSEL). Results indicate that the subgroups differed in fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) along the inferior longitudinal fasciculus (ILF) in both hemispheres. Moreover, FA correlated significantly with Mullen EL and RL raw scores, but not ADOS severity score, along the left and right ILF. Subgroups also differed in MD (but not FA) along the left superior longitudinal fasiculus and left corticospinal tract, but these differences were not correlated with language scores. These findings suggest that white matter microstructure in the left and right ILF varies in relation to lexical development in young males with ASD. The findings also support the use of raw scores on language-relevant standardized tests for assessing early language-brain relationships. Autism Res 2017. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 1107-1119. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Observation of non-classical correlations in sequential measurements of photon polarization

International Nuclear Information System (INIS)

Suzuki, Yutaro; Iinuma, Masataka; Hofmann, Holger F

2016-01-01

A sequential measurement of two non-commuting quantum observables results in a joint probability distribution for all output combinations that can be explained in terms of an initial joint quasi-probability of the non-commuting observables, modified by the resolution errors and back-action of the initial measurement. Here, we show that the error statistics of a sequential measurement of photon polarization performed at different measurement strengths can be described consistently by an imaginary correlation between the statistics of resolution and back-action. The experimental setup was designed to realize variable strength measurements with well-controlled imaginary correlation between the statistical errors caused by the initial measurement of diagonal polarizations, followed by a precise measurement of the horizontal/vertical polarization. We perform the experimental characterization of an elliptically polarized input state and show that the same complex joint probability distribution is obtained at any measurement strength. (paper)

A novel feedforward compensation canceling input filter-regulator interaction

Science.gov (United States)

Kelkar, S. S.; Lee, F. C.

1983-01-01

The interaction between the input and the control loop of switching regulators often results in deterimental effects, such as loop instability, degradation of transient response, and audiosusceptibility, etc. The concept of pole-zero cancelation is employed to mitigate some of these detrimental effects and is implemented using a novel feedforward loop, in addition to existing feedback loops of a buck regulator. Experimental results are presented which show excellent correlation with theory.

Sequential designs for sensitivity analysis of functional inputs in computer experiments

International Nuclear Information System (INIS)

Fruth, J.; Roustant, O.; Kuhnt, S.

2015-01-01

Computer experiments are nowadays commonly used to analyze industrial processes aiming at achieving a wanted outcome. Sensitivity analysis plays an important role in exploring the actual impact of adjustable parameters on the response variable. In this work we focus on sensitivity analysis of a scalar-valued output of a time-consuming computer code depending on scalar and functional input parameters. We investigate a sequential methodology, based on piecewise constant functions and sequential bifurcation, which is both economical and fully interpretable. The new approach is applied to a sheet metal forming problem in three sequential steps, resulting in new insights into the behavior of the forming process over time. - Highlights: • Sensitivity analysis method for functional and scalar inputs is presented. • We focus on the discovery of most influential parts of the functional domain. • We investigate economical sequential methodology based on piecewise constant functions. • Normalized sensitivity indices are introduced and investigated theoretically. • Successful application to sheet metal forming on two functional inputs

COPD phenotypes on computed tomography and its correlation with selected lung function variables in severe patients

Directory of Open Access Journals (Sweden)

da Silva SMD

2016-03-01

Full Text Available Silvia Maria Doria da Silva, Ilma Aparecida Paschoal, Eduardo Mello De Capitani, Marcos Mello Moreira, Luciana Campanatti Palhares, Mônica Corso PereiraPneumology Service, Department of Internal Medicine, School of Medical Sciences, State University of Campinas (UNICAMP, Campinas, São Paulo, BrazilBackground: Computed tomography (CT phenotypic characterization helps in understanding the clinical diversity of chronic obstructive pulmonary disease (COPD patients, but its clinical relevance and its relationship with functional features are not clarified. Volumetric capnography (VC uses the principle of gas washout and analyzes the pattern of CO2 elimination as a function of expired volume. The main variables analyzed were end-tidal concentration of carbon dioxide (ETCO2, Slope of phase 2 (Slp2, and Slope of phase 3 (Slp3 of capnogram, the curve which represents the total amount of CO2 eliminated by the lungs during each breath.Objective: To investigate, in a group of patients with severe COPD, if the phenotypic analysis by CT could identify different subsets of patients, and if there was an association of CT findings and functional variables.Subjects and methods: Sixty-five patients with COPD Gold III–IV were admitted for clinical evaluation, high-resolution CT, and functional evaluation (spirometry, 6-minute walk test [6MWT], and VC. The presence and profusion of tomography findings were evaluated, and later, the patients were identified as having emphysema (EMP or airway disease (AWD phenotype. EMP and AWD groups were compared; tomography findings scores were evaluated versus spirometric, 6MWT, and VC variables.Results: Bronchiectasis was found in 33.8% and peribronchial thickening in 69.2% of the 65 patients. Structural findings of airways had no significant correlation with spirometric variables. Air trapping and EMP were strongly correlated with VC variables, but in opposite directions. There was some overlap between the EMP and AWD

Correlation between sea surface temperature and wind speed in Greenland Sea and their relationships with NAO variability

Directory of Open Access Journals (Sweden)

Bo Qu

2012-09-01

Full Text Available The North Atlantic Oscillation (NAO is one of the major causes of many recent changes in the Arctic Ocean. Generally, it is related to wind speed, sea surface temperature (SST, and sea ice cover. In this study, we analyzed the distributions of and correlations between SST, wind speed, NAO, and sea ice cover from 2003 to 2009 in the Greenland Sea at 10°W to 10°E, 65°N to 80°N. SST reached its peak in July, while wind speed reached its minimum in July. Seasonal variability of SST and wind speed was different for different regions. SST and wind speed mainly had negative correlations. Detailed correlation research was focused on the 75°N to 80°N band. Regression analysis shows that in this band, the variation of SST lagged three months behind that of wind speed. Ice cover and NAO had a positive correlation, and the correlation coefficient between ice cover and NAO in the year 2007 was 0.61. SST and NAO also had a positive correlation, and SST influenced NAO one month in advance. The correlation coefficients between SST and NAO reached 0.944 for the year 2005, 0.7 for the year 2008, and 0.74 for the year 2009 after shifting SST one month later. NAO also had a positive correlation with wind speed, and it also influenced wind speed one month in advance. The correlation coefficients between NAO and wind speed reached 0.783, 0.813, and 0.818 for the years 2004, 2005, and 2008, respectively, after shifting wind speed one month earlier.

Analysis of event tree with imprecise inputs by fuzzy set theory

International Nuclear Information System (INIS)

Ahn, Kwang Il; Chun, Moon Hyun

1990-01-01

Fuzzy set theory approach is proposed as a method to analyze event trees with imprecise or linguistic input variables such as 'likely' or 'improbable' instead of the numerical probability. In this paper, it is shown how the fuzzy set theory can be applied to the event tree analysis. The result of this study shows that the fuzzy set theory approach can be applied as an acceptable and effective tool for analysis of the event tree with fuzzy type of inputs. Comparisons of the fuzzy theory approach with the probabilistic approach of computing probabilities of final states of the event tree through subjective weighting factors and LHS technique show that the two approaches have common factors and give reasonable results

The Generalization of Mutual Information as the Information between a Set of Variables: The Information Correlation Function Hierarchy and the Information Structure of Multi-Agent Systems

Science.gov (United States)

Wolf, David R.

2004-01-01

The topic of this paper is a hierarchy of information-like functions, here named the information correlation functions, where each function of the hierarchy may be thought of as the information between the variables it depends upon. The information correlation functions are particularly suited to the description of the emergence of complex behaviors due to many- body or many-agent processes. They are particularly well suited to the quantification of the decomposition of the information carried among a set of variables or agents, and its subsets. In more graphical language, they provide the information theoretic basis for understanding the synergistic and non-synergistic components of a system, and as such should serve as a forceful toolkit for the analysis of the complexity structure of complex many agent systems. The information correlation functions are the natural generalization to an arbitrary number of sets of variables of the sequence starting with the entropy function (one set of variables) and the mutual information function (two sets). We start by describing the traditional measures of information (entropy) and mutual information.

ColloInputGenerator

DEFF Research Database (Denmark)

2013-01-01

This is a very simple program to help you put together input files for use in Gries' (2007) R-based collostruction analysis program. It basically puts together a text file with a frequency list of lexemes in the construction and inserts a column where you can add the corpus frequencies. It requires...... it as input for basic collexeme collostructional analysis (Stefanowitsch & Gries 2003) in Gries' (2007) program. ColloInputGenerator is, in its current state, based on programming commands introduced in Gries (2009). Projected updates: Generation of complete work-ready frequency lists....

Estimating net present value variability for deterministic models

NARCIS (Netherlands)

van Groenendaal, W.J.H.

1995-01-01

For decision makers the variability in the net present value (NPV) of an investment project is an indication of the project's risk. So-called risk analysis is one way to estimate this variability. However, risk analysis requires knowledge about the stochastic character of the inputs. For large,

Input frequency and lexical variability in phonological development: a survival analysis of word-initial cluster production.

Science.gov (United States)

Ota, Mitsuhiko; Green, Sam J

2013-06-01

Although it has been often hypothesized that children learn to produce new sound patterns first in frequently heard words, the available evidence in support of this claim is inconclusive. To re-examine this question, we conducted a survival analysis of word-initial consonant clusters produced by three children in the Providence Corpus (0 ; 11-4 ; 0). The analysis took account of several lexical factors in addition to lexical input frequency, including the age of first production, production frequency, neighborhood density and number of phonemes. The results showed that lexical input frequency was a significant predictor of the age at which the accuracy level of cluster production in each word first reached 80%. The magnitude of the frequency effect differed across cluster types. Our findings indicate that some of the between-word variance found in the development of sound production can indeed be attributed to the frequency of words in the child's ambient language.

Sea-Level Trend Uncertainty With Pacific Climatic Variability and Temporally-Correlated Noise

Science.gov (United States)

Royston, Sam; Watson, Christopher S.; Legrésy, Benoît; King, Matt A.; Church, John A.; Bos, Machiel S.

2018-03-01

Recent studies have identified climatic drivers of the east-west see-saw of Pacific Ocean satellite altimetry era sea level trends and a number of sea-level trend and acceleration assessments attempt to account for this. We investigate the effect of Pacific climate variability, together with temporally-correlated noise, on linear trend error estimates and determine new time-of-emergence (ToE) estimates across the Indian and Pacific Oceans. Sea-level trend studies often advocate the use of auto-regressive (AR) noise models to adequately assess formal uncertainties, yet sea level often exhibits colored but non-AR(1) noise. Standard error estimates are over- or under-estimated by an AR(1) model for much of the Indo-Pacific sea level. Allowing for PDO and ENSO variability in the trend estimate only reduces standard errors across the tropics and we find noise characteristics are largely unaffected. Of importance for trend and acceleration detection studies, formal error estimates remain on average up to 1.6 times those from an AR(1) model for long-duration tide gauge data. There is an even chance that the observed trend from the satellite altimetry era exceeds the noise in patches of the tropical Pacific and Indian Oceans and the south-west and north-east Pacific gyres. By including climate indices in the trend analysis, the time it takes for the observed linear sea-level trend to emerge from the noise reduces by up to 2 decades.

Input-output linearizing tracking control of induction machine with the included magnetic saturation

DEFF Research Database (Denmark)

Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd

2003-01-01

The tracking control design of an induction motor, based on input-output linearisation with magnetic saturation included is addressed. The magnetic saturation is represented by a nonlinear magnetising curve for the iron core and is used in the control, the observer of the state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances. It is based on the mixed 'stator current - rotor flux linkage' induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with saturation included behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....

Variability in the Second Language Acquisition of Verb Morphology ...

African Journals Online (AJOL)

This article seeks to make a developmental study of variability in the acquisition of verb morphology by second language (L2) pupils who learn at an English input impoverished school where variability in learner language is often presumed to be quite extensive. By studying variability in such settings, it is hoped that we can ...

The Effect of Visual Variability on the Learning of Academic Concepts.

Science.gov (United States)

Bourgoyne, Ashley; Alt, Mary

2017-06-10

The purpose of this study was to identify effects of variability of visual input on development of conceptual representations of academic concepts for college-age students with normal language (NL) and those with language-learning disabilities (LLD). Students with NL (n = 11) and LLD (n = 11) participated in a computer-based training for introductory biology course concepts. Participants were trained on half the concepts under a low-variability condition and half under a high-variability condition. Participants completed a posttest in which they were asked to identify and rate the accuracy of novel and trained visual representations of the concepts. We performed separate repeated measures analyses of variance to examine the accuracy of identification and ratings. Participants were equally accurate on trained and novel items in the high-variability condition, but were less accurate on novel items only in the low-variability condition. The LLD group showed the same pattern as the NL group; they were just less accurate. Results indicated that high-variability visual input may facilitate the acquisition of academic concepts in college students with NL and LLD. High-variability visual input may be especially beneficial for generalization to novel representations of concepts. Implicit learning methods may be harnessed by college courses to provide students with basic conceptual knowledge when they are entering courses or beginning new units.

Predicting the La Niña of 2020-21: Termination of Solar Cycles and Correlated Variance in Solar and Atmospheric Variability

Science.gov (United States)

Leamon, R. J.; McIntosh, S. W.

2017-12-01

Establishing a solid physical connection between solar and tropospheric variability has posed a considerable challenge across the spectrum of Earth-system science. Over the past few years a new picture to describe solar variability has developed, based on observing, understanding and tracing the progression, interaction and intrinsic variability of the magnetized activity bands that belong to the Sun's 22-year magnetic activity cycle. The intra- and extra-hemispheric interaction of these magnetic bands appear to explain the occurrence of decadal scale variability that primarily manifests itself in the sunspot cycle. However, on timescales of ten months or so, those bands posses their own internal variability with an amplitude of the same order of magnitude as the decadal scale. The latter have been tied to the existence of magnetized Rossby waves in the solar convection zone that result in surges of magnetic flux emergence that correspondingly modulate our star's radiative and particulate output. One of the most important events in the progression of these bands is their (apparent) termination at the solar equator that signals a global increase in magnetic flux emergence that becomes the new solar cycle. We look at the particulate and radiative implications of these termination points, their temporal recurrence and signature, from the Sun to the Earth, and show the correlated signature of solar cycle termination events and major oceanic oscillations that extend back many decades. A combined one-two punch of reduced particulate forcing and increased radiative forcing that result from the termination of one solar cycle and rapid blossoming of another correlates strongly with a shift from El Niño to La Niña conditions in the Pacific Ocean. This shift does not occur at solar minima, nor solar maxima, but at a particular, non-periodic, time in between. The failure to identify these termination points, and their relative irregularity, have inhibited a correlation to be

The input and output management of solid waste using DEA models: A case study at Jengka, Pahang

Science.gov (United States)

Mohamed, Siti Rosiah; Ghazali, Nur Fadzrina Mohd; Mohd, Ainun Hafizah

2017-08-01

Data Envelopment Analysis (DEA) as a tool for obtaining performance indices has been used extensively in several of organizations sector. The ways to improve the efficiency of Decision Making Units (DMUs) is impractical because some of inputs and outputs are uncontrollable and in certain situation its produce weak efficiency which often reflect the impact for operating environment. Based on the data from Alam Flora Sdn. Bhd Jengka, the researcher wants to determine the efficiency of solid waste management (SWM) in town Jengka Pahang using CCRI and CCRO model of DEA and duality formulation with vector average input and output. Three input variables (length collection in meter, frequency time per week in hour and number of garbage truck) and 2 outputs variables (frequency collection and the total solid waste collection in kilogram) are analyzed. As a conclusion, it shows only three roads from 23 roads are efficient that achieve efficiency score 1. Meanwhile, 20 other roads are in an inefficient management.

Effect of input variability on the quality of laser shock processing

Energy Technology Data Exchange (ETDEWEB)

Arif, Abul Fazal M. [King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia)

2009-10-15

Laser shock processing (LSP) involves high-energy laser radiation combined with suitable overlays to generate highpressure pulses on the surface of the metal. The stress wave generated due to high pressure pulses propagates into the material causing the surface layer to yield and plastically deform, and thereby, develop a significant residual compressive stress in the surface region of the substrate material. The developed compressive stress field is beneficial to improve surface properties such as fatigue, wear, and corrosion. To improve the understanding of the shock hardening process, investigation into the physical processes involved is necessary. In the first part of this paper, the temporal variation in the pressure intensity and spot size is calculated by using a two-dimensional recoil pressure prediction model. Using an explicit non-linear FEA code, ANSYS LS-DYNA, the deformation behavior and residual stresses in the substrate material are predicted. In the second part, a probabilistic approach to the modeling and analysis of LSP is presented in this paper. Various factors that affect the probabilistic performance of the LSP are grouped into categories and a select number of factors known to be significant, for which the variability could be assessed, are modeled as random variables (such as recoil pressure, laser beam spot size, substrate material properties and others). The potential of the probabilistic approach in predicting the structural integrity of the laser-shocked components is addressed

Effect of input variability on the quality of laser shock processing

International Nuclear Information System (INIS)

Arif, Abul Fazal M.

2009-01-01

Laser shock processing (LSP) involves high-energy laser radiation combined with suitable overlays to generate highpressure pulses on the surface of the metal. The stress wave generated due to high pressure pulses propagates into the material causing the surface layer to yield and plastically deform, and thereby, develop a significant residual compressive stress in the surface region of the substrate material. The developed compressive stress field is beneficial to improve surface properties such as fatigue, wear, and corrosion. To improve the understanding of the shock hardening process, investigation into the physical processes involved is necessary. In the first part of this paper, the temporal variation in the pressure intensity and spot size is calculated by using a two-dimensional recoil pressure prediction model. Using an explicit non-linear FEA code, ANSYS LS-DYNA, the deformation behavior and residual stresses in the substrate material are predicted. In the second part, a probabilistic approach to the modeling and analysis of LSP is presented in this paper. Various factors that affect the probabilistic performance of the LSP are grouped into categories and a select number of factors known to be significant, for which the variability could be assessed, are modeled as random variables (such as recoil pressure, laser beam spot size, substrate material properties and others). The potential of the probabilistic approach in predicting the structural integrity of the laser-shocked components is addressed

Air temperature variability in a high-elevation Himalayan catchment

NARCIS (Netherlands)

Heynen, Martin; Miles, Evan; Ragettli, Silvan; Buri, Pascal; Immerzeel, Walter W.; Pellicciotti, Francesca

2016-01-01

Air temperature is a key control of processes affecting snow and glaciers in high-elevation catchments, including melt, snowfall and sublimation. It is therefore a key input variable to models of land-surface-atmosphere interaction. Despite this importance, its spatial variability is poorly

Modeling Short-Range Soil Variability and its Potential Use in Variable-Rate Treatment of Experimental Plots

Directory of Open Access Journals (Sweden)

A Moameni

2011-02-01

Full Text Available Abstract In Iran, the experimental plots under fertilizer trials are managed in such a way that the whole plot area uniformly receives agricultural inputs. This could lead to biased research results and hence to suppressing of the efforts made by the researchers. This research was conducted in a selected site belonging to the Gonbad Agricultural Research Station, located in the semiarid region, northeastern Iran. The aim was to characterize the short-range spatial variability of the inherent and management-depended soil properties and to determine if this variation is large and can be managed at practical scales. The soils were sampled using a grid 55 m apart. In total, 100 composite soil samples were collected from topsoil (0-30 cm and were analyzed for calcium carbonate equivalent, organic carbon, clay, available phosphorus, available potassium, iron, copper, zinc and manganese. Descriptive statistics were applied to check data trends. Geostatistical analysis was applied to variography, model fitting and contour mapping. Sampling at 55 m made it possible to split the area of the selected experimental plot into relatively uniform areas that allow application of agricultural inputs with variable rates. Keywords: Short-range soil variability, Within-field soil variability, Interpolation, Precision agriculture, Geostatistics

How to regress and predict in a Bland-Altman plot? Review and contribution based on tolerance intervals and correlated-errors-in-variables models.

Science.gov (United States)

Francq, Bernard G; Govaerts, Bernadette

2016-06-30

Two main methodologies for assessing equivalence in method-comparison studies are presented separately in the literature. The first one is the well-known and widely applied Bland-Altman approach with its agreement intervals, where two methods are considered interchangeable if their differences are not clinically significant. The second approach is based on errors-in-variables regression in a classical (X,Y) plot and focuses on confidence intervals, whereby two methods are considered equivalent when providing similar measures notwithstanding the random measurement errors. This paper reconciles these two methodologies and shows their similarities and differences using both real data and simulations. A new consistent correlated-errors-in-variables regression is introduced as the errors are shown to be correlated in the Bland-Altman plot. Indeed, the coverage probabilities collapse and the biases soar when this correlation is ignored. Novel tolerance intervals are compared with agreement intervals with or without replicated data, and novel predictive intervals are introduced to predict a single measure in an (X,Y) plot or in a Bland-Atman plot with excellent coverage probabilities. We conclude that the (correlated)-errors-in-variables regressions should not be avoided in method comparison studies, although the Bland-Altman approach is usually applied to avert their complexity. We argue that tolerance or predictive intervals are better alternatives than agreement intervals, and we provide guidelines for practitioners regarding method comparison studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Simplex-based optimization of numerical and categorical inputs in early bioprocess development: Case studies in HT chromatography.

Science.gov (United States)

Konstantinidis, Spyridon; Titchener-Hooker, Nigel; Velayudhan, Ajoy

2017-08-01

Bioprocess development studies often involve the investigation of numerical and categorical inputs via the adoption of Design of Experiments (DoE) techniques. An attractive alternative is the deployment of a grid compatible Simplex variant which has been shown to yield optima rapidly and consistently. In this work, the method is combined with dummy variables and it is deployed in three case studies wherein spaces are comprised of both categorical and numerical inputs, a situation intractable by traditional Simplex methods. The first study employs in silico data and lays out the dummy variable methodology. The latter two employ experimental data from chromatography based studies performed with the filter-plate and miniature column High Throughput (HT) techniques. The solute of interest in the former case study was a monoclonal antibody whereas the latter dealt with the separation of a binary system of model proteins. The implemented approach prevented the stranding of the Simplex method at local optima, due to the arbitrary handling of the categorical inputs, and allowed for the concurrent optimization of numerical and categorical, multilevel and/or dichotomous, inputs. The deployment of the Simplex method, combined with dummy variables, was therefore entirely successful in identifying and characterizing global optima in all three case studies. The Simplex-based method was further shown to be of equivalent efficiency to a DoE-based approach, represented here by D-Optimal designs. Such an approach failed, however, to both capture trends and identify optima, and led to poor operating conditions. It is suggested that the Simplex-variant is suited to development activities involving numerical and categorical inputs in early bioprocess development. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A simple approach to ignoring irrelevant variables by population decoding based on multisensory neurons

Science.gov (United States)

Kim, HyungGoo R.; Pitkow, Xaq; Angelaki, Dora E.

2016-01-01

Sensory input reflects events that occur in the environment, but multiple events may be confounded in sensory signals. For example, under many natural viewing conditions, retinal image motion reflects some combination of self-motion and movement of objects in the world. To estimate one stimulus event and ignore others, the brain can perform marginalization operations, but the neural bases of these operations are poorly understood. Using computational modeling, we examine how multisensory signals may be processed to estimate the direction of self-motion (i.e., heading) and to marginalize out effects of object motion. Multisensory neurons represent heading based on both visual and vestibular inputs and come in two basic types: “congruent” and “opposite” cells. Congruent cells have matched heading tuning for visual and vestibular cues and have been linked to perceptual benefits of cue integration during heading discrimination. Opposite cells have mismatched visual and vestibular heading preferences and are ill-suited for cue integration. We show that decoding a mixed population of congruent and opposite cells substantially reduces errors in heading estimation caused by object motion. In addition, we present a general formulation of an optimal linear decoding scheme that approximates marginalization and can be implemented biologically by simple reinforcement learning mechanisms. We also show that neural response correlations induced by task-irrelevant variables may greatly exceed intrinsic noise correlations. Overall, our findings suggest a general computational strategy by which neurons with mismatched tuning for two different sensory cues may be decoded to perform marginalization operations that dissociate possible causes of sensory inputs. PMID:27334948

Quantifying Variability and Correlation in Biomarker and Mineralogical Measurements: Lessons from Five Astrobiological Mars Analogue Expeditions in Iceland

Science.gov (United States)

Gentry, D.; Amador, E. S.; Cable, M. L.; Cantrell, T.; Chaudry, N.; Duca, Z. A.; Jacobsen, M. B.; Kirby, J.; McCaig, H. C.; Murukesan, G.; Rader, E.; Cullen, T.; Rennie, V.; Schwieterman, E. W.; Stevens, A. H.; Sutton, S. A.; Tan, G.; Yin, C.; Cullen, D.; Geppert, W.; Stockton, A. M.

2017-12-01

Studies in planetary analogue sites correlating remote imagery, mineralogy, and biomarker assay results help predict biomarker distribution and preservation. The FELDSPAR team has conducted five expeditions (2012-2017) to Icelandic Mars analogue sites with an increasingly refined battery of physicochemical measurements and biomarker assays. Two additional expeditions are planned; here we report intermediate results.The biomarker assays performed represent a diversity of potential biomarker types: ATP, cell counts, qPCR with domain-level primers, and DNA content. Mineralogical, chemical, and physical measurements and observations include temperature, pH, moisture content, and Raman, near-IR reflectance, and X-ray fluorescence spectra. Sites are geologically recent basaltic lava flows (Fimmvörðuháls, Eldfell, Holuhraun) and barren basaltic sand plains (Mælifellssandur, Dyngjusandur). All samples were 'homogeneous' at the 1 m to 1 km scale in apparent color, morphology, and grain size.[1]Sample locations were arranged in hierarchically nested grids at 10 cm, 1 m, 10 m, 100 m, and >1 km scales. Several measures of spatial distribution and variability were derived: unbiased sample variance, F- and pairwise t-tests with Bonferroni correction, and the non-parametric H- and u-tests. All assay results, including preliminary mineralogical information in the form of notable spectral bands, were then tested for correlation using the non-parametric Spearman's rank test.[2] For Fimmvörðuháls, four years of data were also examined for temporal trends.Biomarker quantification (other than cell count) was generally well correlated, although all assays showed notable variability even at the smallest examined spatial scale. Pairwise comparisons proved to be the most intuitive measure of variability; non-parametric characterization indicated trends at the >100 m scale, but required more replicates than were feasible at smaller scales. Future work will integrate additional

Hypothesis: Low frequency heart rate variability (LF-HRV) is an input for undisclosed yet biological adaptive control, governing the cardiovascular regulations to assure optimal functioning.

Science.gov (United States)

Gabbay, Uri; Bobrovsky, Ben Zion

2012-02-01

Cardiovascular regulation is considered today as having three levels: autoregulations, neural regulations and hormonal regulations. We hypothesize that the cardiovascular regulation has an additional (fourth) control level which is outer, hierarchical (adaptive) loop where LF-HRV amplitude serves as a reference input which the neural cardiovascular center detects and responses in order to maintain LF-HRV around some prescribed level. Supporting evidences: LF-HRV absence during artificial cardiac pacing may be associated with "pacemaker syndrome" which had not been sufficiently understood regardless of apparently unimpaired cardiovascular performance. The hypothesis may provide an essential basis for understanding several cardiovascular morbidities and insight toward diagnostic measures and treatments (including but not limited to adding variability to the pulse generator of artificial pacemakers to eliminate "pace maker syndrome"). Copyright © 2011 Elsevier Ltd. All rights reserved.

Total dose induced increase in input offset voltage in JFET input operational amplifiers

International Nuclear Information System (INIS)

Pease, R.L.; Krieg, J.; Gehlhausen, M.; Black, J.

1999-01-01

Four different types of commercial JFET input operational amplifiers were irradiated with ionizing radiation under a variety of test conditions. All experienced significant increases in input offset voltage (Vos). Microprobe measurement of the electrical characteristics of the de-coupled input JFETs demonstrates that the increase in Vos is a result of the mismatch of the degraded JFETs. (authors)

Maturation of GABAergic inhibition promotes strengthening of temporally coherent inputs among convergent pathways.

Directory of Open Access Journals (Sweden)

Sandra J Kuhlman

2010-06-01

Full Text Available Spike-timing-dependent plasticity (STDP, a form of Hebbian plasticity, is inherently stabilizing. Whether and how GABAergic inhibition influences STDP is not well understood. Using a model neuron driven by converging inputs modifiable by STDP, we determined that a sufficient level of inhibition was critical to ensure that temporal coherence (correlation among presynaptic spike times of synaptic inputs, rather than initial strength or number of inputs within a pathway, controlled postsynaptic spike timing. Inhibition exerted this effect by preferentially reducing synaptic efficacy, the ability of inputs to evoke postsynaptic action potentials, of the less coherent inputs. In visual cortical slices, inhibition potently reduced synaptic efficacy at ages during but not before the critical period of ocular dominance (OD plasticity. Whole-cell recordings revealed that the amplitude of unitary IPSCs from parvalbumin positive (Pv+ interneurons to pyramidal neurons increased during the critical period, while the synaptic decay time-constant decreased. In addition, intrinsic properties of Pv+ interneurons matured, resulting in an increase in instantaneous firing rate. Our results suggest that maturation of inhibition in visual cortex ensures that the temporally coherent inputs (e.g. those from the open eye during monocular deprivation control postsynaptic spike times of binocular neurons, a prerequisite for Hebbian mechanisms to induce OD plasticity.

Modified Regression Correlation Coefficient for Poisson Regression Model

Science.gov (United States)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Correlation Coefficients: Appropriate Use and Interpretation.

Science.gov (United States)

Schober, Patrick; Boer, Christa; Schwarte, Lothar A

2018-05-01

Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positive correlation) or in the opposite (negative correlation) direction. Most often, the term correlation is used in the context of a linear relationship between 2 continuous variables and expressed as Pearson product-moment correlation. The Pearson correlation coefficient is typically used for jointly normally distributed data (data that follow a bivariate normal distribution). For nonnormally distributed continuous data, for ordinal data, or for data with relevant outliers, a Spearman rank correlation can be used as a measure of a monotonic association. Both correlation coefficients are scaled such that they range from -1 to +1, where 0 indicates that there is no linear or monotonic association, and the relationship gets stronger and ultimately approaches a straight line (Pearson correlation) or a constantly increasing or decreasing curve (Spearman correlation) as the coefficient approaches an absolute value of 1. Hypothesis tests and confidence intervals can be used to address the statistical significance of the results and to estimate the strength of the relationship in the population from which the data were sampled. The aim of this tutorial is to guide researchers and clinicians in the appropriate use and interpretation of correlation coefficients.

Modelling Implicit Communication in Multi-Agent Systems with Hybrid Input/Output Automata

Directory of Open Access Journals (Sweden)

Marta Capiluppi

2012-10-01

Full Text Available We propose an extension of Hybrid I/O Automata (HIOAs to model agent systems and their implicit communication through perturbation of the environment, like localization of objects or radio signals diffusion and detection. To this end we decided to specialize some variables of the HIOAs whose values are functions both of time and space. We call them world variables. Basically they are treated similarly to the other variables of HIOAs, but they have the function of representing the interaction of each automaton with the surrounding environment, hence they can be output, input or internal variables. Since these special variables have the role of simulating implicit communication, their dynamics are specified both in time and space, because they model the perturbations induced by the agent to the environment, and the perturbations of the environment as perceived by the agent. Parallel composition of world variables is slightly different from parallel composition of the other variables, since their signals are summed. The theory is illustrated through a simple example of agents systems.

Correlations and Non-Linear Probability Models

DEFF Research Database (Denmark)

Breen, Richard; Holm, Anders; Karlson, Kristian Bernt

2014-01-01

the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under......Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between...... certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models....

Interpreting canonical correlation analysis through biplots of stucture correlations and weights

NARCIS (Netherlands)

Braak, ter C.J.F.

1990-01-01

This paper extends the biplot technique to canonical correlation analysis and redundancy analysis. The plot of structure correlations is shown to the optimal for displaying the pairwise correlations between the variables of the one set and those of the second. The link between multivariate

Multimedia Environmental Pollutant Assessment System (MEPAS) application guidance. Guidelines for evaluating MEPAS input parameters for Version 3.1

International Nuclear Information System (INIS)

Buck, J.W.; Whelan, G.; Droppo, J.G. Jr.; Strenge, D.L.; Castleton, K.J.; McDonald, J.P.; Sato, C.; Streile, G.P.

1995-02-01

The Multimedia Environmental Pollutant Assessment System (MEPAS) was developed by Pacific Northwest Laboratory (PNL) for the U.S. Department of Energy (DOE) Office of Environment, Safety and Health and Office of Environmental Management and Environmental Restoration. MEPAS is a set of computer codes developed to provide decision makers with risk information integrated for hazardous, radioactive, and mixed-waste sites based on their potential hazard to public health. It is applicable to a wide range of environmental management and regulatory conditions, including inactive sites covered under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) and active air and water releases covered under the Clean Air Act, the Clean Water Act, and the Resource Conservation and Recovery Act. MEPAS integrates contaminant release, transport, and exposure models into a single system. An interactive user interface assists the investigator in defining problems, assembling data and entering input, and developing reports. PNL has compiled two documents that explain the methodology behind the MEPAS model and instruct the user in how to input, retrieve, and evaluate data. This report contains detailed guidelines for defining the input data required to conduct an analysis with MEPAS. Entries for each variable have a short definition, units, and text explaining what a variable is and how it can be quantified. As appropriate, ranges and typical values are given. This report also contains listings of the input screens (worksheets) that are used in the MEPAS user interface for these variables

Neuronal discrimination capacity

International Nuclear Information System (INIS)

Deng Yingchun; Williams, Peter; Feng Jianfeng; Liu Feng

2003-01-01

We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals

Neuronal discrimination capacity

Energy Technology Data Exchange (ETDEWEB)

Deng Yingchun [Department of Mathematics, Hunan Normal University 410081, Changsha (China); COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Williams, Peter; Feng Jianfeng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Liu Feng [COGS, University of Sussex at Brighton, BN1 9QH (United Kingdom); Physics Department, Nanjing University (China)

2003-12-19

We explore neuronal mechanisms of discriminating between masked signals. It is found that when the correlation between input signals is zero, the output signals are separable if and only if input signals are separable. With positively (negatively) correlated signals, the output signals are separable (mixed) even when input signals are mixed (separable). Exact values of discrimination capacity are obtained for two most interesting cases: the exactly balanced inhibitory and excitatory input case and the uncorrelated input case. Interestingly, the discrimination capacity obtained in these cases is independent of model parameters, input distribution and is universal. Our results also suggest a functional role of inhibitory inputs and correlated inputs or, more generally, the large variability of efferent spike trains observed in in vivo experiments: the larger the variability of efferent spike trains, the easier it is to discriminate between masked input signals.

Auxiliary variables for the mapping of the drainage network: spatial correlation between relieve units, lithotypes and springs in Benevente River basin-ES

Directory of Open Access Journals (Sweden)

Tony Vinicius Moreira Sampaio

2014-12-01

Full Text Available Process of the drainage network mapping present methodological limitations re- sulting in inaccurate maps, restricting their use in environmental studies. Such problems demand the realization of long field surveys to verify the error and the search for auxiliary variables to optimize this works and turn possible the analysis of map accuracy. This research aims at the measurement of the correlation be- tween springs, lithotypes and relieve units, characterized by Roughness Concentration Index (RCI in River Basin Benevente-ES, focusing on the operations of map algebra and the use of spatial statistical techniques. These procedures have identified classes of RCI and lithotypes that present the highest and the lowest correlation with the spatial distribution of springs, indicating its potential use as auxiliary variables to verify the map accuracy.

Statistical Analysis of Input Parameters Impact on the Modelling of Underground Structures

Directory of Open Access Journals (Sweden)

M. Hilar

2008-01-01

Full Text Available The behaviour of a geomechanical model and its final results are strongly affected by the input parameters. As the inherent variability of rock mass is difficult to model, engineers are frequently forced to face the question “Which input values should be used for analyses?” The correct answer to such a question requires a probabilistic approach, considering the uncertainty of site investigations and variation in the ground. This paper describes the statistical analysis of input parameters for FEM calculations of traffic tunnels in the city of Prague. At the beginning of the paper, the inaccuracy in the geotechnical modelling is discussed. In the following part the Fuzzy techniques are summarized, including information about an application of the Fuzzy arithmetic on the shotcrete parameters. The next part of the paper is focused on the stochastic simulation – Monte Carlo Simulation is briefly described, Latin Hypercubes method is described more in details. At the end several practical examples are described: statistical analysis of the input parameters on the numerical modelling of the completed Mrázovka tunnel (profile West Tunnel Tube km 5.160 and modelling of the constructed tunnel Špejchar – Pelc Tyrolka. 

Interleaved Boost-Half-Bridge Dual–Input DC-DC Converter with a PWM plus Phase-Shift Control for Fuel Cell Applications

DEFF Research Database (Denmark)

Zhang, Zhe; Andersen, Michael A. E.

2013-01-01

This paper presents an isolated dual-input DC-DC converter with a PWM plus phase-shift control for fuel cell hybrid energy systems. The power switches are controlled by phase shifted PWM signals with a variable duty cycle, and thus the two input voltages as well as the output voltage can...

Two-Stage Variable Sample-Rate Conversion System

Science.gov (United States)

Tkacenko, Andre

2009-01-01

A two-stage variable sample-rate conversion (SRC) system has been pro posed as part of a digital signal-processing system in a digital com munication radio receiver that utilizes a variety of data rates. The proposed system would be used as an interface between (1) an analog- todigital converter used in the front end of the receiver to sample an intermediatefrequency signal at a fixed input rate and (2) digita lly implemented tracking loops in subsequent stages that operate at v arious sample rates that are generally lower than the input sample r ate. This Two-Stage System would be capable of converting from an input sample rate to a desired lower output sample rate that could be var iable and not necessarily a rational fraction of the input rate.

Effect of the spatiotemporal variability of rainfall inputs in water quality integrated catchment modelling for dissolved oxygen concentrations

Science.gov (United States)

Moreno Ródenas, Antonio Manuel; Cecinati, Francesca; ten Veldhuis, Marie-Claire; Langeveld, Jeroen; Clemens, Francois

2016-04-01

Maintaining water quality standards in highly urbanised hydrological catchments is a worldwide challenge. Water management authorities struggle to cope with changing climate and an increase in pollution pressures. Water quality modelling has been used as a decision support tool for investment and regulatory developments. This approach led to the development of integrated catchment models (ICM), which account for the link between the urban/rural hydrology and the in-river pollutant dynamics. In the modelled system, rainfall triggers the drainage systems of urban areas scattered along a river. When flow exceeds the sewer infrastructure capacity, untreated wastewater enters the natural system by combined sewer overflows. This results in a degradation of the river water quality, depending on the magnitude of the emission and river conditions. Thus, being capable of representing these dynamics in the modelling process is key for a correct assessment of the water quality. In many urbanised hydrological systems the distances between draining sewer infrastructures go beyond the de-correlation length of rainfall processes, especially, for convective summer storms. Hence, spatial and temporal scales of selected rainfall inputs are expected to affect water quality dynamics. The objective of this work is to evaluate how the use of rainfall data from different sources and with different space-time characteristics affects modelled output concentrations of dissolved oxygen in a simplified ICM. The study area is located at the Dommel, a relatively small and sensitive river flowing through the city of Eindhoven (The Netherlands). This river stretch receives the discharge of the 750,000 p.e. WWTP of Eindhoven and from over 200 combined sewer overflows scattered along its length. A pseudo-distributed water quality model has been developed in WEST (mikedhi.com); this is a lumped-physically based model that accounts for urban drainage processes, WWTP and river dynamics for several

Eliciting conditional and unconditional rank correlations from conditional probabilities

International Nuclear Information System (INIS)

Morales, O.; Kurowicka, D.; Roelen, A.

2008-01-01

Causes of uncertainties may be interrelated and may introduce dependencies. Ignoring these dependencies may lead to large errors. A number of graphical models in probability theory such as dependence trees, vines and (continuous) Bayesian belief nets [Cooke RM. Markov and entropy properties of tree and vine-dependent variables. In: Proceedings of the ASA section on Bayesian statistical science, 1997; Kurowicka D, Cooke RM. Distribution-free continuous Bayesian belief nets. In: Proceedings of mathematical methods in reliability conference, 2004; Bedford TJ, Cooke RM. Vines-a new graphical model for dependent random variables. Ann Stat 2002; 30(4):1031-68; Kurowicka D, Cooke RM. Uncertainty analysis with high dimensional dependence modelling. New York: Wiley; 2006; Hanea AM, et al. Hybrid methods for quantifying and analyzing Bayesian belief nets. In: Proceedings of the 2005 ENBIS5 conference, 2005; Shachter RD, Kenley CR. Gaussian influence diagrams. Manage Sci 1998; 35(5) .] have been developed to capture dependencies between random variables. The input for these models are various marginal distributions and dependence information, usually in the form of conditional rank correlations. Often expert elicitation is required. This paper focuses on dependence representation, and dependence elicitation. The techniques presented are illustrated with an application from aviation safety

Correlation and simple linear regression.

Science.gov (United States)

Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

2003-06-01

In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

Isotope correlations for safeguards surveillance and accountancy methods

International Nuclear Information System (INIS)

Persiani, P.J.; Kalimullah.

1982-01-01

Isotope correlations corroborated by experiments, coupled with measurement methods for nuclear material in the fuel cycle have the potential as a safeguards surveillance and accountancy system. The ICT allows the verification of: fabricator's uranium and plutonium content specifications, shipper/receiver differences between fabricator output and reactor input, reactor plant inventory changes, reprocessing batch specifications and shipper/receiver differences between reactor output and reprocessing plant input. The investigation indicates that there exist predictable functional relationships (i.e. correlations) between isotopic concentrations over a range of burnup. Several cross-correlations serve to establish the initial fuel assembly-averaged compositions. The selection of the more effective correlations will depend not only on the level of reliability of ICT for verification, but also on the capability, accuracy and difficulty of developing measurement methods. The propagation of measurement errors through the correlations have been examined to identify the sensitivity of the isotope correlations to measurement errors, and to establish criteria for measurement accuracy in the development and selection of measurement methods. 6 figures, 3 tables

The variable Herbig Ae star HR 5999: VIII. Spectroscopic observations 1975 - 1985 and correlations with simulataneous photometry

International Nuclear Information System (INIS)

Tjin, A.; Djie, H.R.E.; The, P.S.; Andersen, J.; Nordstroem, B.; Finkenzeller, U.; Jankovics, I.

1989-01-01

Visual spectroscopy of the irregularly variable Herbig Ae star HR 5999 over the past 15 years is summarised. The general features of the spectrum indicate that HR 5999 is an A5-7 III-IVe star with an extended circumstellar atmosphere. Typical lines have a rotationally broadened photospheric component and one or two blue-shifted ''shell'' components. The average radial velocity of the photospheric components, together with the common proper motions of the stars strongly suggest that HR 5999 and the peculiar B6 star HR 6000 from a physical pair, with common age. In order to study the relation between variations in the spectrum and in the brightness of the star, three sequences of simultaneous spectroscopic and photometric observations have been obtained during the past decade. From these and other (isolated) simultaneous observations we concluded that: (a) the photospheric radial velocity component is variable, possibly with a period of about 14 days, which could point to the presence of a close companion, (b) occasionally, sudden variations may occur (within one night) either in the photospheric line components,or in the shell (absorption or emission) components or both; (c) a decreasing brightness is correlated with increasing Hα-emission flux and a decreasing wind velocity in the shell region. An interpretation of these correlations in terms of magnetic activity is proposed

Blood Pressure Variability and Cognitive Function Among Older African Americans: Introducing a New Blood Pressure Variability Measure.

Science.gov (United States)

Tsang, Siny; Sperling, Scott A; Park, Moon Ho; Helenius, Ira M; Williams, Ishan C; Manning, Carol

2017-09-01

Although blood pressure (BP) variability has been reported to be associated with cognitive impairment, whether this relationship affects African Americans has been unclear. We sought correlations between systolic and diastolic BP variability and cognitive function in community-dwelling older African Americans, and introduced a new BP variability measure that can be applied to BP data collected in clinical practice. We assessed cognitive function in 94 cognitively normal older African Americans using the Mini-Mental State Examination (MMSE) and the Computer Assessment of Mild Cognitive Impairment (CAMCI). We used BP measurements taken at the patients' three most recent primary care clinic visits to generate three traditional BP variability indices, range, standard deviation, and coefficient of variation, plus a new index, random slope, which accounts for unequal BP measurement intervals within and across patients. MMSE scores did not correlate with any of the BP variability indices. Patients with greater diastolic BP variability were less accurate on the CAMCI verbal memory and incidental memory tasks. Results were similar across the four BP variability indices. In a sample of cognitively intact older African American adults, BP variability did not correlate with global cognitive function, as measured by the MMSE. However, higher diastolic BP variability correlated with poorer verbal and incidental memory. By accounting for differences in BP measurement intervals, our new BP variability index may help alert primary care physicians to patients at particular risk for cognitive decline.

A latent low-dimensional common input drives a pool of motor neurons: a probabilistic latent state-space model.

Science.gov (United States)

Feeney, Daniel F; Meyer, François G; Noone, Nicholas; Enoka, Roger M

2017-10-01

Motor neurons appear to be activated with a common input signal that modulates the discharge activity of all neurons in the motor nucleus. It has proven difficult for neurophysiologists to quantify the variability in a common input signal, but characterization of such a signal may improve our understanding of how the activation signal varies across motor tasks. Contemporary methods of quantifying the common input to motor neurons rely on compiling discrete action potentials into continuous time series, assuming the motor pool acts as a linear filter, and requiring signals to be of sufficient duration for frequency analysis. We introduce a space-state model in which the discharge activity of motor neurons is modeled as inhomogeneous Poisson processes and propose a method to quantify an abstract latent trajectory that represents the common input received by motor neurons. The approach also approximates the variation in synaptic noise in the common input signal. The model is validated with four data sets: a simulation of 120 motor units, a pair of integrate-and-fire neurons with a Renshaw cell providing inhibitory feedback, the discharge activity of 10 integrate-and-fire neurons, and the discharge times of concurrently active motor units during an isometric voluntary contraction. The simulations revealed that a latent state-space model is able to quantify the trajectory and variability of the common input signal across all four conditions. When compared with the cumulative spike train method of characterizing common input, the state-space approach was more sensitive to the details of the common input current and was less influenced by the duration of the signal. The state-space approach appears to be capable of detecting rather modest changes in common input signals across conditions. NEW & NOTEWORTHY We propose a state-space model that explicitly delineates a common input signal sent to motor neurons and the physiological noise inherent in synaptic signal

ENSEMBLE VARIABILITY OF NEAR-INFRARED-SELECTED ACTIVE GALACTIC NUCLEI

International Nuclear Information System (INIS)

Kouzuma, S.; Yamaoka, H.

2012-01-01

We present the properties of the ensemble variability V for nearly 5000 near-infrared active galactic nuclei (AGNs) selected from the catalog of Quasars and Active Galactic Nuclei (13th Edition) and the SDSS-DR7 quasar catalog. From three near-infrared point source catalogs, namely, Two Micron All Sky Survey (2MASS), Deep Near Infrared Survey (DENIS), and UKIDSS/LAS catalogs, we extract 2MASS-DENIS and 2MASS-UKIDSS counterparts for cataloged AGNs by cross-identification between catalogs. We further select variable AGNs based on an optimal criterion for selecting the variable sources. The sample objects are divided into subsets according to whether near-infrared light originates by optical emission or by near-infrared emission in the rest frame; and we examine the correlations of the ensemble variability with the rest-frame wavelength, redshift, luminosity, and rest-frame time lag. In addition, we also examine the correlations of variability amplitude with optical variability, radio intensity, and radio-to-optical flux ratio. The rest-frame optical variability of our samples shows negative correlations with luminosity and positive correlations with rest-frame time lag (i.e., the structure function, SF), and this result is consistent with previous analyses. However, no well-known negative correlation exists between the rest-frame wavelength and optical variability. This inconsistency might be due to a biased sampling of high-redshift AGNs. Near-infrared variability in the rest frame is anticorrelated with the rest-frame wavelength, which is consistent with previous suggestions. However, correlations of near-infrared variability with luminosity and rest-frame time lag are the opposite of these correlations of the optical variability; that is, the near-infrared variability is positively correlated with luminosity but negatively correlated with the rest-frame time lag. Because these trends are qualitatively consistent with the properties of radio-loud quasars reported

Quantum mechanics and the theories of local hidden variables: an experimental test by measuring the spin correlation function in p-p scattering

International Nuclear Information System (INIS)

Lamehi-Rachti, Mohammad.

1976-01-01

The Einstein-Podolsky-Rosen paradox is briefly exposed with the Bell theorem on hidden variables and the locality principle. The conditions for an ideal experiment are discussed and the results from γ-γ correlation experiments are given. The principle of an experimental measurement of the spin correlation function predicted by the quantum mechanics theory is derived, new hypotheses to be introduced are discussed. The formula giving the dependence of the counting asymmetry on the spin correlation function, polarimeter analyzing power, and geometric correlation is developed. The principle of a Monte Carlo calculation is also exposed. The experimental device is described with the methods for measuring the subsidiary quantities and experimental results are analyzed [fr

Quantified carbon input for maintaining existing soil organic carbon stocks in global wheat systems

Science.gov (United States)

Wang, G.

2017-12-01

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1°× 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha-1 yr-1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

Critical carbon input to maintain current soil organic carbon stocks in global wheat systems.

Science.gov (United States)

Wang, Guocheng; Luo, Zhongkui; Han, Pengfei; Chen, Huansheng; Xu, Jingjing

2016-01-13

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1° × 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha(-1) yr(-1), with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

Multicollinearity in canonical correlation analysis in maize.

Science.gov (United States)

Alves, B M; Cargnelutti Filho, A; Burin, C

2017-03-30

The objective of this study was to evaluate the effects of multicollinearity under two methods of canonical correlation analysis (with and without elimination of variables) in maize (Zea mays L.) crop. Seventy-six maize genotypes were evaluated in three experiments, conducted in a randomized block design with three replications, during the 2009/2010 crop season. Eleven agronomic variables (number of days from sowing until female flowering, number of days from sowing until male flowering, plant height, ear insertion height, ear placement, number of plants, number of ears, ear index, ear weight, grain yield, and one thousand grain weight), 12 protein-nutritional variables (crude protein, lysine, methionine, cysteine, threonine, tryptophan, valine, isoleucine, leucine, phenylalanine, histidine, and arginine), and 6 energetic-nutritional variables (apparent metabolizable energy, apparent metabolizable energy corrected for nitrogen, ether extract, crude fiber, starch, and amylose) were measured. A phenotypic correlation matrix was first generated among the 29 variables for each of the experiments. A multicollinearity diagnosis was later performed within each group of variables using methodologies such as variance inflation factor and condition number. Canonical correlation analysis was then performed, with and without the elimination of variables, among groups of agronomic and protein-nutritional, and agronomic and energetic-nutritional variables. The canonical correlation analysis in the presence of multicollinearity (without elimination of variables) overestimates the variability of canonical coefficients. The elimination of variables is an efficient method to circumvent multicollinearity in canonical correlation analysis.

Input and execution

International Nuclear Information System (INIS)

Carr, S.; Lane, G.; Rowling, G.

1986-11-01

This document describes the input procedures, input data files and operating instructions for the SYVAC A/C 1.03 computer program. SYVAC A/C 1.03 simulates the groundwater mediated movement of radionuclides from underground facilities for the disposal of low and intermediate level wastes to the accessible environment, and provides an estimate of the subsequent radiological risk to man. (author)

Quantitative assessment of multiple sclerosis lesion load using CAD and expert input

Science.gov (United States)

Gertych, Arkadiusz; Wong, Alexis; Sangnil, Alan; Liu, Brent J.

2008-03-01

Multiple sclerosis (MS) is a frequently encountered neurological disease with a progressive but variable course affecting the central nervous system. Outline-based lesion quantification in the assessment of lesion load (LL) performed on magnetic resonance (MR) images is clinically useful and provides information about the development and change reflecting overall disease burden. Methods of LL assessment that rely on human input are tedious, have higher intra- and inter-observer variability and are more time-consuming than computerized automatic (CAD) techniques. At present it seems that methods based on human lesion identification preceded by non-interactive outlining by CAD are the best LL quantification strategies. We have developed a CAD that automatically quantifies MS lesions, displays 3-D lesion map and appends radiological findings to original images according to current DICOM standard. CAD is also capable to display and track changes and make comparison between patient's separate MRI studies to determine disease progression. The findings are exported to a separate imaging tool for review and final approval by expert. Capturing and standardized archiving of manual contours is also implemented. Similarity coefficients calculated from quantities of LL in collected exams show a good correlation of CAD-derived results vs. those incorporated as expert's reading. Combining the CAD approach with an expert interaction may impact to the diagnostic work-up of MS patients because of improved reproducibility in LL assessment and reduced time for single MR or comparative exams reading. Inclusion of CAD-generated outlines as DICOM-compliant overlays into the image data can serve as a better reference in MS progression tracking.

Mutual information against correlations in binary communication channels.

Science.gov (United States)

Pregowska, Agnieszka; Szczepanski, Janusz; Wajnryb, Eligiusz

2015-05-19

Explaining how the brain processing is so fast remains an open problem (van Hemmen JL, Sejnowski T., 2004). Thus, the analysis of neural transmission (Shannon CE, Weaver W., 1963) processes basically focuses on searching for effective encoding and decoding schemes. According to the Shannon fundamental theorem, mutual information plays a crucial role in characterizing the efficiency of communication channels. It is well known that this efficiency is determined by the channel capacity that is already the maximal mutual information between input and output signals. On the other hand, intuitively speaking, when input and output signals are more correlated, the transmission should be more efficient. A natural question arises about the relation between mutual information and correlation. We analyze the relation between these quantities using the binary representation of signals, which is the most common approach taken in studying neuronal processes of the brain. We present binary communication channels for which mutual information and correlation coefficients behave differently both quantitatively and qualitatively. Despite this difference in behavior, we show that the noncorrelation of binary signals implies their independence, in contrast to the case for general types of signals. Our research shows that the mutual information cannot be replaced by sheer correlations. Our results indicate that neuronal encoding has more complicated nature which cannot be captured by straightforward correlations between input and output signals once the mutual information takes into account the structure and patterns of the signals.

Noninvasive quantification of cerebral metabolic rate for glucose in rats using 18F-FDG PET and standard input function

Science.gov (United States)

Hori, Yuki; Ihara, Naoki; Teramoto, Noboru; Kunimi, Masako; Honda, Manabu; Kato, Koichi; Hanakawa, Takashi

2015-01-01

Measurement of arterial input function (AIF) for quantitative positron emission tomography (PET) studies is technically challenging. The present study aimed to develop a method based on a standard arterial input function (SIF) to estimate input function without blood sampling. We performed 18F-fluolodeoxyglucose studies accompanied by continuous blood sampling for measurement of AIF in 11 rats. Standard arterial input function was calculated by averaging AIFs from eight anesthetized rats, after normalization with body mass (BM) and injected dose (ID). Then, the individual input function was estimated using two types of SIF: (1) SIF calibrated by the individual's BM and ID (estimated individual input function, EIFNS) and (2) SIF calibrated by a single blood sampling as proposed previously (EIF1S). No significant differences in area under the curve (AUC) or cerebral metabolic rate for glucose (CMRGlc) were found across the AIF-, EIFNS-, and EIF1S-based methods using repeated measures analysis of variance. In the correlation analysis, AUC or CMRGlc derived from EIFNS was highly correlated with those derived from AIF and EIF1S. Preliminary comparison between AIF and EIFNS in three awake rats supported an idea that the method might be applicable to behaving animals. The present study suggests that EIFNS method might serve as a noninvasive substitute for individual AIF measurement. PMID:25966947

Gating of Long-Term Potentiation by Nicotinic Acetylcholine Receptors at the Cerebellum Input Stage

NARCIS (Netherlands)

F. Prestori (Francesca); C. Bonardi (Claudia); L. Mapelli (Lisa); P. Lombardo (Paola); R. Goselink (Rianne); M.E. de Stefano (Maria Egle); D. Gandolfi (Daniela); J. Mapelli (Jonathan); D. Bertrand (Daniel); M. Schonewille (Martijn); C.I. de Zeeuw (Chris); E. D'Angelo (Egidio)

2013-01-01

textabstractThe brain needs mechanisms able to correlate plastic changes with local circuit activity and internal functional states. At the cerebellum input stage, uncontrolled induction of long-term potentiation or depression (LTP or LTD) between mossy fibres and granule cells can saturate synaptic

PLEXOS Input Data Generator

Energy Technology Data Exchange (ETDEWEB)

2017-02-01

The PLEXOS Input Data Generator (PIDG) is a tool that enables PLEXOS users to better version their data, automate data processing, collaborate in developing inputs, and transfer data between different production cost modeling and other power systems analysis software. PIDG can process data that is in a generalized format from multiple input sources, including CSV files, PostgreSQL databases, and PSS/E .raw files and write it to an Excel file that can be imported into PLEXOS with only limited manual intervention.

A non-correlator-based digital communication system using interleaved chaotic differential peaks keying (I-CDPK) modulation and chaotic synchronization

International Nuclear Information System (INIS)

Chien, T.-I; Hung, Y.-C.; Liao, T.-L.

2006-01-01

This paper presents a novel non-correlator-based digital communication system with the application of interleaved chaotic differential peaks keying (I-CDPK) modulation technique. The proposed communication system consists of four major modules: I-CDPK modulator (ICM), frequency modulation (FM) transmitter, FM receiver and I-CDPK demodulator (ICDM). In the ICM module, there are four components: a chaotic circuit to generate the chaotic signals, A/D converter, D/A converter and a digital processing mechanism to control all signal flows and performs I-CDPK modulation corresponding to the input digital bits. For interleaving every input digital bit set, every state of the chaotic system is used to represent one portion of it, but only a scalar state variable (i.e. the system output) is sent to the ICDM's chaotic circuit through both FM transmitter and FM receiver. An observer-based chaotic synchronization scheme is designed to synchronize the chaotic circuits of the ICM and ICDM. Meanwhile, the bit detector in ICDM is devoted to recover the transmitted input digital bits. Some numerical simulations of an illustrative communication system are given to demonstrate its theoretical effectiveness. Furthermore, the performance of bit error rate of the proposed system is analyzed and compared with those of the correlator-based communication systems adopting coherent binary phase shift keying (BPSK) and coherent differential chaotic shift keying (DCSK) schemes

Spatio-temporal variability in accretion and erosion of coastal foredunes in the Netherlands: regional climate and local topography.

Science.gov (United States)

Keijsers, Joep G S; Poortinga, Ate; Riksen, Michel J P M; Maroulis, Jerry

2014-01-01

Depending on the amount of aeolian sediment input and dune erosion, dune size and morphology change over time. Since coastal foredunes play an important role in the Dutch coastal defence, it is important to have good insight in the main factors that control these changes. In this paper the temporal variations in foredune erosion and accretion were studied in relation to proxies for aeolian transport potential and storminess using yearly elevation measurements from 1965 to 2012 for six sections of the Dutch coast. Longshore differences in the relative impacts of erosion and accretion were examined in relation to local beach width. The results show that temporal variability in foredune accretion and erosion is highest in narrow beach sections. Here, dune erosion alternates with accretion, with variability displaying strong correlations with yearly values of storminess (maximum sea levels). In wider beach sections, dune erosion is less frequent, with lower temporal variability and stronger correlations with time series of transport potential. In erosion dominated years, eroded volumes decrease from narrow to wider beaches. When accretion dominates, dune-volume changes are relatively constant alongshore. Dune erosion is therefore suggested to control spatial variability in dune-volume changes. On a scale of decades, the volume of foredunes tends to increase more on wider beaches. However, where widths exceed 200 to 300 m, this trend is no longer observed.

On the significance of δ13C correlations in ancient sediments

Science.gov (United States)

Derry, Louis A.

2010-08-01

A graphical analysis of the correlations between δc and ɛTOC was introduced by Rothman et al. (2003) to obtain estimates of the carbon isotopic composition of inputs to the oceans and the organic carbon burial fraction. Applied to Cenozoic data, the method agrees with independent estimates, but with Neoproterozoic data the method yields results that cannot be accommodated with standard models of sedimentary carbon isotope mass balance. We explore the sensitivity of the graphical correlation method and find that the variance ratio between δc and δo is an important control on the correlation of δc and ɛ. If the variance ratio σc/ σo ≥ 1 highly correlated arrays very similar to those obtained from the data are produced from independent random variables. The Neoproterozoic data shows such variance patterns, and the regression parameters for the Neoproterozoic data are statistically indistinguishable from the randomized model at the 95% confidence interval. The projection of the data into δc- ɛ space cannot distinguish between signal and noise, such as post-depositional alteration, under these circumstances. There appears to be no need to invoke unusual carbon cycle dynamics to explain the Neoproterozoic δc- ɛ array. The Cenozoic data have σc/ σo vs. ɛ correlation is probably geologically significant, but the analyzed sample size is too small to yield statistically significant results.

Quantification of leptin in seminal plasma of buffalo bulls and its correlation with antioxidant status, conventional and computer-assisted sperm analysis (CASA) semen variables.

Science.gov (United States)

Kumar, Pradeep; Saini, Monika; Kumar, Dharmendra; Jan, M H; Swami, Dheer Singh; Sharma, R K

2016-03-01

The present study is the first to quantify leptin in seminal plasma of buffalo and investigate its relationship with seminal attributes. Ten ejaculates each from 10 Murrah buffalo bulls were collected. Semen quality variables such as semen volume, sperm concentration, sperm abnormalities, membrane integrity, antioxidant enzyme activities (superoxide dismutase, catalase and total antioxidant capacity), malondialdehyde (MDA) concentration, as well as sperm kinetics and motility variables were evaluated. The leptin concentration in serum and seminal plasma were estimated by the ELISA method. Bulls were classified in two groups on the basis of sperm concentration with Group I having >800 million sperm/mL and Group II <500 million sperm/mL. Greater (P<0.05) mean sperm abnormalities, seminal leptin concentrations and MDA concentrations were recorded in Group II than Group I. The seminal leptin was positively correlated with sperm abnormalities and MDA concentration while being negatively correlated with sperm concentration, but there was no correlation with sperm kinetic and motility variables, sperm membrane integrity and seminal plasma antioxidant enzyme activity. Thus, the data suggest that seminal leptin has a role in spermatogenesis and can be used as a marker for spermatogenesis to predict the capacity of buffalo bulls for semen production. Copyright © 2016 Elsevier B.V. All rights reserved.

Reactor protection system software test-case selection based on input-profile considering concurrent events and uncertainties

International Nuclear Information System (INIS)

Khalaquzzaman, M.; Lee, Seung Jun; Cho, Jaehyun; Jung, Wondea

2016-01-01

Recently, the input-profile-based testing for safety critical software has been proposed for determining the number of test cases and quantifying the failure probability of the software. Input-profile of a reactor protection system (RPS) software is the input which causes activation of the system for emergency shutdown of a reactor. This paper presents a method to determine the input-profile of a RPS software which considers concurrent events/transients. A deviation of a process parameter value begins through an event and increases owing to the concurrent multi-events depending on the correlation of process parameters and severity of incidents. A case of reactor trip caused by feedwater loss and main steam line break is simulated and analyzed to determine the RPS software input-profile and estimate the number of test cases. The different sizes of the main steam line breaks (e.g., small, medium, large break) with total loss of feedwater supply are considered in constructing the input-profile. The uncertainties of the simulation related to the input-profile-based software testing are also included. Our study is expected to provide an option to determine test cases and quantification of RPS software failure probability. (author)

Effect of Orifice Nozzle Design and Input Power on Two-Phase Flow and Mass Transfer Characteristics

Energy Technology Data Exchange (ETDEWEB)

Yang, Hei Cheon [Chonnam Nat’l Univ., Gwangju (Korea, Republic of)

2016-04-15

It is necessary to investigate the input power as well as the mass transfer characteristics of the aeration process in order to improve the energy efficiency of an aerobic water treatment. The objective of this study is to experimentally investigate the effect of orifice nozzle design and input power on the flow and mass transfer characteristics of a vertical two-phase flow. The mass ratio, input power, volumetric mass transfer coefficient, and mass transfer efficiency were calculated using the measured data. It was found that as the input power increases the volumetric mass transfer coefficient increases, while the mass ratio and mass transfer efficiency decrease. The mass ratio, volumetric mass transfer coefficient, and mass transfer efficiency were higher for the orifice configuration with a smaller orifice nozzle area ratio. An empirical correlation was proposed to estimate the effect of mass ratio, input power, and Froude number on the volumetric mass transfer coefficient.

Ground motion input in seismic evaluation studies

International Nuclear Information System (INIS)

Sewell, R.T.; Wu, S.C.

1996-07-01

This report documents research pertaining to conservatism and variability in seismic risk estimates. Specifically, it examines whether or not artificial motions produce unrealistic evaluation demands, i.e., demands significantly inconsistent with those expected from real earthquake motions. To study these issues, two types of artificial motions are considered: (a) motions with smooth response spectra, and (b) motions with realistic variations in spectral amplitude across vibration frequency. For both types of artificial motion, time histories are generated to match target spectral shapes. For comparison, empirical motions representative of those that might result from strong earthquakes in the Eastern U.S. are also considered. The study findings suggest that artificial motions resulting from typical simulation approaches (aimed at matching a given target spectrum) are generally adequate and appropriate in representing the peak-response demands that may be induced in linear structures and equipment responding to real earthquake motions. Also, given similar input Fourier energies at high-frequencies, levels of input Fourier energy at low frequencies observed for artificial motions are substantially similar to those levels noted in real earthquake motions. In addition, the study reveals specific problems resulting from the application of Western U.S. type motions for seismic evaluation of Eastern U.S. nuclear power plants

Sensitivity Analysis of Input Parameters for the Dose Assessment from Gaseous Effluents due to the Normal Operation of Jordan Research and Training Reactor

International Nuclear Information System (INIS)

Kim, Sukhoon; Lee, Seunghee; Kim, Juyoul; Kim, Juyub; Han, Moonhee

2015-01-01

In this study, therefore, the sensitivity analysis of input variables for the dose assessment was performed for reviewing the effect of each parameter on the result after determining the type and range of parameters that could affect the exposure dose of the public. (Since JRTR will be operated by the concept of 'no liquid discharge,' the input parameters used for calculation of dose due to liquid effluents are not considered in the sensitivity analysis.) In this paper, the sensitivity analysis of input parameters for the dose assessment in the vicinity of the site boundary due to gaseous effluents was performed for a total of thirty-five (35) cases. And, detailed results for the input variables that have an significant effect are shown in Figures 1 through 7, respectively. For preparing a R-ER for the operating license of the JRTR, these results will be updated by the additional information and could be applied to predicting the variation trend of the exposure dose in the process of updating the input parameters for the dose assessment reflecting the characteristics of the JRTR site

Quantitative assessment of drivers of recent global temperature variability: an information theoretic approach

Science.gov (United States)

Bhaskar, Ankush; Ramesh, Durbha Sai; Vichare, Geeta; Koganti, Triven; Gurubaran, S.

2017-12-01

Identification and quantification of possible drivers of recent global temperature variability remains a challenging task. This important issue is addressed adopting a non-parametric information theory technique, the Transfer Entropy and its normalized variant. It distinctly quantifies actual information exchanged along with the directional flow of information between any two variables with no bearing on their common history or inputs, unlike correlation, mutual information etc. Measurements of greenhouse gases: CO2, CH4 and N2O; volcanic aerosols; solar activity: UV radiation, total solar irradiance ( TSI) and cosmic ray flux ( CR); El Niño Southern Oscillation ( ENSO) and Global Mean Temperature Anomaly ( GMTA) made during 1984-2005 are utilized to distinguish driving and responding signals of global temperature variability. Estimates of their relative contributions reveal that CO2 ({˜ } 24 %), CH4 ({˜ } 19 %) and volcanic aerosols ({˜ }23 %) are the primary contributors to the observed variations in GMTA. While, UV ({˜ } 9 %) and ENSO ({˜ } 12 %) act as secondary drivers of variations in the GMTA, the remaining play a marginal role in the observed recent global temperature variability. Interestingly, ENSO and GMTA mutually drive each other at varied time lags. This study assists future modelling efforts in climate science.

Effective capacity of correlated MISO channels

KAUST Repository

Zhong, Caijun; Ratnarajah, Tharm; Wong, Kaikit; Alouini, Mohamed-Slim

2011-01-01

This paper presents an analytical performance investigation of the capacity limits of correlated multiple-input single-output (MISO) channels in the presence of quality-of-service (QoS) requirements. Exact closed-form expression for the effective

SSYST-3. Input description

International Nuclear Information System (INIS)

Meyder, R.

1983-12-01

The code system SSYST-3 is designed to analyse the thermal and mechanical behaviour of a fuel rod during a LOCA. The report contains a complete input-list for all modules and several tested inputs for a LOCA analysis. (orig.)

Impact of magnetic saturation on the input-output linearising tracking control of an induction motor

DEFF Research Database (Denmark)

Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd

2004-01-01

This paper deals with the tracking control design of an induction motor, based on input-output linearization with magnetic saturation included. Magnetic saturation is represented by the nonlinear magnetizing curve of the iron core and is used in the control design, the observer of state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances of the drive. It is based on the mixed ”stator current - rotor flux linkage” induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with the included saturation behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....

Material input of nuclear fuel

International Nuclear Information System (INIS)

Rissanen, S.; Tarjanne, R.

2001-01-01

The Material Input (MI) of nuclear fuel, expressed in terms of the total amount of natural material needed for manufacturing a product, is examined. The suitability of the MI method for assessing the environmental impacts of fuels is also discussed. Material input is expressed as a Material Input Coefficient (MIC), equalling to the total mass of natural material divided by the mass of the completed product. The material input coefficient is, however, only an intermediate result, which should not be used as such for the comparison of different fuels, because the energy contents of nuclear fuel is about 100 000-fold compared to the energy contents of fossil fuels. As a final result, the material input is expressed in proportion to the amount of generated electricity, which is called MIPS (Material Input Per Service unit). Material input is a simplified and commensurable indicator for the use of natural material, but because it does not take into account the harmfulness of materials or the way how the residual material is processed, it does not alone express the amount of environmental impacts. The examination of the mere amount does not differentiate between for example coal, natural gas or waste rock containing usually just sand. Natural gas is, however, substantially more harmful for the ecosystem than sand. Therefore, other methods should also be used to consider the environmental load of a product. The material input coefficient of nuclear fuel is calculated using data from different types of mines. The calculations are made among other things by using the data of an open pit mine (Key Lake, Canada), an underground mine (McArthur River, Canada) and a by-product mine (Olympic Dam, Australia). Furthermore, the coefficient is calculated for nuclear fuel corresponding to the nuclear fuel supply of Teollisuuden Voima (TVO) company in 2001. Because there is some uncertainty in the initial data, the inaccuracy of the final results can be even 20-50 per cent. The value

A default Bayesian hypothesis test for correlations and partial correlations

NARCIS (Netherlands)

Wetzels, R.; Wagenmakers, E.J.

2012-01-01

We propose a default Bayesian hypothesis test for the presence of a correlation or a partial correlation. The test is a direct application of Bayesian techniques for variable selection in regression models. The test is easy to apply and yields practical advantages that the standard frequentist tests

Suspension system vibration analysis with regard to variable type ability to smooth road irregularities

Science.gov (United States)

Rykov, S. P.; Rykova, O. A.; Koval, V. S.; Makhno, D. E.; Fedotov, K. V.

2018-03-01

The paper aims to analyze vibrations of the dynamic system equivalent of the suspension system with regard to tyre ability to smooth road irregularities. The research is based on static dynamics for linear systems of automated control, methods of correlation, spectral and numerical analysis. Input of new data on the smoothing effect of the pneumatic tyre reflecting changes of a contact area between the wheel and road under vibrations of the suspension makes the system non-linear which requires using numerical analysis methods. Taking into account the variable smoothing ability of the tyre when calculating suspension vibrations, one can approximate calculation and experimental results and improve the constant smoothing ability of the tyre.

Analysis on electronic control unit of continuously variable transmission

Science.gov (United States)

Cao, Shuanggui

Continuously variable transmission system can ensure that the engine work along the line of best fuel economy, improve fuel economy, save fuel and reduce harmful gas emissions. At the same time, continuously variable transmission allows the vehicle speed is more smooth and improves the ride comfort. Although the CVT technology has made great development, but there are many shortcomings in the CVT. The CVT system of ordinary vehicles now is still low efficiency, poor starting performance, low transmission power, and is not ideal controlling, high cost and other issues. Therefore, many scholars began to study some new type of continuously variable transmission. The transmission system with electronic systems control can achieve automatic control of power transmission, give full play to the characteristics of the engine to achieve optimal control of powertrain, so the vehicle is always traveling around the best condition. Electronic control unit is composed of the core processor, input and output circuit module and other auxiliary circuit module. Input module collects and process many signals sent by sensor and , such as throttle angle, brake signals, engine speed signal, speed signal of input and output shaft of transmission, manual shift signals, mode selection signals, gear position signal and the speed ratio signal, so as to provide its corresponding processing for the controller core.

Unitary input DEA model to identify beef cattle production systems typologies

Directory of Open Access Journals (Sweden)

Eliane Gonçalves Gomes

2012-08-01

Full Text Available The cow-calf beef production sector in Brazil has a wide variety of operating systems. This suggests the identification and the characterization of homogeneous regions of production, with consequent implementation of actions to achieve its sustainability. In this paper we attempted to measure the performance of 21 livestock modal production systems, in their cow-calf phase. We measured the performance of these systems, considering husbandry and production variables. The proposed approach is based on data envelopment analysis (DEA. We used unitary input DEA model, with apparent input orientation, together with the efficiency measurements generated by the inverted DEA frontier. We identified five modal production systems typologies, using the isoefficiency layers approach. The results showed that the knowledge and the processes management are the most important factors for improving the efficiency of beef cattle production systems.

Spatio-temporal environmental correlation and population variability in simple metacommunities.

Directory of Open Access Journals (Sweden)

Lasse Ruokolainen

Full Text Available Natural populations experience environmental conditions that vary across space and over time. This variation is often correlated between localities depending on the geographical separation between them, and different species can respond to local environmental fluctuations similarly or differently, depending on their adaptation. How this emerging structure in environmental correlation (between-patches and between-species affects spatial community dynamics is an open question. This paper aims at a general understanding of the interactions between the environmental correlation structure and population dynamics in spatial networks of local communities (metacommunities, by studying simple two-patch, two-species systems. Three different pairs of interspecific interactions are considered: competition, consumer-resource interaction, and host-parasitoid interaction. While the results paint a relatively complex picture of the effect of environmental correlation, the interaction between environmental forcing, dispersal, and local interactions can be understood via two mechanisms. While increasing between-patch environmental correlation couples immigration and local densities (destabilising effect, the coupling between local populations under increased between-species environmental correlation can either amplify or dampen population fluctuations, depending on the patterns in density dependence. This work provides a unifying framework for modelling stochastic metacommunities, and forms a foundation for a better understanding of population responses to environmental fluctuations in natural systems.

Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

Energy Technology Data Exchange (ETDEWEB)

Groen, E.A., E-mail: Evelyne.Groen@gmail.com [Wageningen University, P.O. Box 338, Wageningen 6700 AH (Netherlands); Heijungs, R. [Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV (Netherlands); Leiden University, Einsteinweg 2, Leiden 2333 CC (Netherlands)

2017-01-15

Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlations between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.

Chemical sensors are hybrid-input memristors

Science.gov (United States)

Sysoev, V. I.; Arkhipov, V. E.; Okotrub, A. V.; Pershin, Y. V.

2018-04-01

Memristors are two-terminal electronic devices whose resistance depends on the history of input signal (voltage or current). Here we demonstrate that the chemical gas sensors can be considered as memristors with a generalized (hybrid) input, namely, with the input consisting of the voltage, analyte concentrations and applied temperature. The concept of hybrid-input memristors is demonstrated experimentally using a single-walled carbon nanotubes chemical sensor. It is shown that with respect to the hybrid input, the sensor exhibits some features common with memristors such as the hysteretic input-output characteristics. This different perspective on chemical gas sensors may open new possibilities for smart sensor applications.

Bone densitometry in normal women of reproductive age: Correlation with reference values and anthropometric variables

International Nuclear Information System (INIS)

Lobo, G.; Palma, T.; Ladron de Guevara, D.

2002-01-01

Bone mass density measurements using X rays is considered to be the non-invasive reference method to measure bone mineral density. Even though the technology has reached a high level of development, precision and reproducibility must be optimised to assure that the observed variations are due solely to the variations in bone mineral content, and not to other associated variables, either technical or biological. The main factors affecting bone density measurements are those that depend on the technique used and those which depend on characteristics of the individuals. The variability associated with the technique can be minimised by an adequate standardisation and quality control. Among those characteristics of the individuals, which have been mentioned as a source of variability, the most important are related to the anthropomorphic characteristics such as size and depth of osseous structures, and thickness and characteristics of soft tissues. These factors may be especially important because the interpretation of bone mass density measurements depends on values obtained for reference normal populations, which are incorporated into the bone mass densitometers as reference value databases. Usually the anthropomorphic characteristics of this reference population are unknown and can be different from those of the local population, independently of genetic or ethnic factors. This situation leads to error both in the definition of basic concepts such as osteopenia and osteoporosis, and in the interpretation of individual results for population studies. The purpose of this study is to correlate bone density measurements of normal Chilean women with reference value databases and with parameters, which depend on body size

Genetic Variability, Correlation Studies and Path Coefficient Analysis in Gladiolus Alatus Cultivars

International Nuclear Information System (INIS)

Ramzan, A.; Nawab, N. N.; Tariq, M. S.; Ikram, S.; Ahad, A.

2016-01-01

A study was undertaken to find out the estimates of genetic variability, genetic parameters and character association among different flower traits between three gladiolus cultivars viz: Sancerre, Fado and Advanced Red. The experiment was repeated three times by using RCBD (Randomized complete block design) at Department of Horticulture, PMAS-UAAR, Rawalpindi. The highest genotypic coefficient variation (GCV) and phenotypic coefficient variation (PCV) magnitude was observed for spike length (16.00) and number of florets per spike (14.84) followed by number of leaves (10.00). Among the traits studied the highest heritability estimates was recorded in spike length (99.5 percent) followed by number of florets/spike (99.6 percent) and lowest in plant height (98.2 percent). The genetic advance as percent of mean was ranged from 2.8 percent to 24.75 percent. Genetic advance was highest for floret breadth (24.75 percent) and lowest for plant height (2.8 percent). High heritability combined with high genetic advance was noticed for number of florets per spike, spike length and floret breadth indicating additive gene action which suggested that improvement of these traits would be effective for further selection of superior genotypes. Plant height and number of florets per spike showed highly positive and significant association with spike length, number of leaves, leaf area, floret length and floret breadth while, spike length registered positive and significant correlation with number of leaves and floret breadth. The path coefficient analysis based on spike length, as responsible variable exposed that all of the traits exerted direct positive effect except leaf area and floret length. Spike length imparted maximum positive direct effect on the number of florets per spike. Hence, spike length and number of florets per spike may be considered for further improvement. However, Floret length and floret breadth may also be considered as a criterion for selection. (author)

Correlation and agreement: overview and clarification of competing concepts and measures.

Science.gov (United States)

Liu, Jinyuan; Tang, Wan; Chen, Guanqin; Lu, Yin; Feng, Changyong; Tu, Xin M

2016-04-25

Agreement and correlation are widely-used concepts that assess the association between variables. Although similar and related, they represent completely different notions of association. Assessing agreement between variables assumes that the variables measure the same construct, while correlation of variables can be assessed for variables that measure completely different constructs. This conceptual difference requires the use of different statistical methods, and when assessing agreement or correlation, the statistical method may vary depending on the distribution of the data and the interest of the investigator. For example, the Pearson correlation, a popular measure of correlation between continuous variables, is only informative when applied to variables that have linear relationships; it may be non-informative or even misleading when applied to variables that are not linearly related. Likewise, the intraclass correlation, a popular measure of agreement between continuous variables, may not provide sufficient information for investigators if the nature of poor agreement is of interest. This report reviews the concepts of agreement and correlation and discusses differences in the application of several commonly used measures.

A fast integrated discriminator with continuously variable width

International Nuclear Information System (INIS)

Borghesi, A.; Goggi, G.; Nardo, R.

1976-01-01

A simple dc-coupled discriminator with fast switching characteristics has been realized. Both input threshold and output width are continuously variable; the ECL design allows high speed and high density with ample fanout. (Auth.)

Sensitivity Analysis of Unsaturated Flow and Contaminant Transport with Correlated Parameters

Science.gov (United States)

Relative contributions from uncertainties in input parameters to the predictive uncertainties in unsaturated flow and contaminant transport are investigated in this study. The objectives are to: (1) examine the effects of input parameter correlations on the sensitivity of unsaturated flow and conta...

The relation between input-output transformation and gastrointestinal nematode infections on dairy farms.

Science.gov (United States)

van der Voort, M; Van Meensel, J; Lauwers, L; Van Huylenbroeck, G; Charlier, J

2016-02-01

Efficiency analysis is used for assessing links between technical efficiency (TE) of livestock farms and animal diseases. However, previous studies often do not make the link with the allocation of inputs and mainly present average effects that ignore the often huge differences among farms. In this paper, we studied the relationship between exposure to gastrointestinal (GI) nematode infections, the TE and the input allocation on dairy farms. Although the traditional cost allocative efficiency (CAE) indicator adequately measures how a given input allocation differs from the cost-minimising input allocation, they do not represent the unique input allocation of farms. Similar CAE scores may be obtained for farms with different input allocations. Therefore, we propose an adjusted allocative efficiency index (AAEI) to measure the unique input allocation of farms. Combining this AAEI with the TE score allows determining the unique input-output position of each farm. The method is illustrated by estimating efficiency scores using data envelopment analysis (DEA) on a sample of 152 dairy farms in Flanders for which both accountancy and parasitic monitoring data were available. Three groups of farms with a different input-output position can be distinguished based on cluster analysis: (1) technically inefficient farms, with a relatively low use of concentrates per 100 l milk and a high exposure to infection, (2) farms with an intermediate TE, relatively high use of concentrates per 100 l milk and a low exposure to infection, (3) farms with the highest TE, relatively low roughage use per 100 l milk and a relatively high exposure to infection. Correlation analysis indicates for each group how the level of exposure to GI nematodes is associated or not with improved economic performance. The results suggest that improving both the economic performance and exposure to infection seems only of interest for highly TE farms. The findings indicate that current farm recommendations

A Non-Simulation Based Method for Inducing Pearson’s Correlation Between Input Random Variables

Science.gov (United States)

2008-04-23

Systems 500 Auxillary Systems 600 Outfit & Furnishings 700 Weapons 800 Integration & Engineering 900 Ship Assembly & Support Total SWBS Description...Upside Probable Downside 000 Administration 100 Hull 200 Propulsion 300 Electric Plant 400 Electonics Systems 500 Auxillary Systems 600 Outfit

Variability of Cloud Cover and Its Relation to Snowmelt and Runoff in the Mountainous Western United States

Science.gov (United States)

Sumargo, E.; Cayan, D. R.; Iacobellis, S.

2014-12-01

Obtaining accurate solar radiation input to snowmelt runoff models remains a fundamental challenge for water supply forecasters in the mountainous western U.S. The variability of cloud cover is a primary source of uncertainty in estimating surface radiation, especially given that ground-based radiometer networks in mountain terrains are sparse. Thus, remote sensed cloud properties provide a way to extend in situ observations and more importantly, to understand cloud variability in montane environment. We utilize 17 years of NASA/NOAA GOES visible albedo product with 4 km spatial and half-hour temporal resolutions to investigate daytime cloud variability in the western U.S. at elevations above 800 m. REOF/PC analysis finds that the 5 leading modes account for about two-thirds of the total daily cloud albedo variability during the whole year (ALL) and snowmelt season (AMJJ). The AMJJ PCs are significantly correlated with de-seasonalized snowmelt derived from CDWR CDEC and NRCS SNOTEL SWE data and USGS stream discharge across the western conterminous states. The sum of R2 from 7 days prior to the day of snowmelt/discharge amounts to as much as ~52% on snowmelt and ~44% on discharge variation. Spatially, the correlation patterns take on broad footprints, with strongest signals in regions of highest REOF weightings. That the response of snowmelt and streamflow to cloud variation is spread across several days indicates the cumulative effect of cloud variation on the energy budget in mountain catchments.

QUANTUM AND CLASSICAL CORRELATIONS IN GAUSSIAN OPEN QUANTUM SYSTEMS

Directory of Open Access Journals (Sweden)

Aurelian ISAR

2015-01-01

Full Text Available In the framework of the theory of open systems based on completely positive quantum dynamical semigroups, we give a description of the continuous-variable quantum correlations (quantum entanglement and quantum discord for a system consisting of two noninteracting bosonic modes embedded in a thermal environment. We solve the Kossakowski-Lindblad master equation for the time evolution of the considered system and describe the entanglement and discord in terms of the covariance matrix for Gaussian input states. For all values of the temperature of the thermal reservoir, an initial separable Gaussian state remains separable for all times. We study the time evolution of logarithmic negativity, which characterizes the degree of entanglement, and show that in the case of an entangled initial squeezed thermal state, entanglement suppression takes place for all temperatures of the environment, including zero temperature. We analyze the time evolution of the Gaussian quantum discord, which is a measure of all quantum correlations in the bipartite state, including entanglement, and show that it decays asymptotically in time under the effect of the thermal bath. This is in contrast with the sudden death of entanglement. Before the suppression of the entanglement, the qualitative evolution of quantum discord is very similar to that of the entanglement. We describe also the time evolution of the degree of classical correlations and of quantum mutual information, which measures the total correlations of the quantum system.

Correlation Structures of Correlated Binomial Models and Implied Default Distribution

OpenAIRE

S. Mori; K. Kitsukawa; M. Hisakado

2006-01-01

We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution h...

Reliable Recognition of Partially Occluded Objects with Correlation Filters

Directory of Open Access Journals (Sweden)

Alexey Ruchay

2018-01-01

Full Text Available Design of conventional correlation filters requires explicit knowledge of the appearance and shape of a target object, so the performance of correlation filters is significantly affected by changes in the appearance of the object in the input scene. In particular, the performance of correlation filters worsens when objects to be recognized are partially occluded by other objects, and the input scene contains a cluttered background and noise. In this paper, we propose a new algorithm for the design of a system consisting of a set of adaptive correlation filters for recognition of partially occluded objects in noisy scenes. Since the input scene may contain different fragments of the target, false objects, and background to be rejected, the system is designed in such a manner to guarantee equally high correlation peaks corresponding to parts of the target in the scenes. The key points of the system are as follows: (i it consists of a bank of composite optimum filters, which yield the best performance for different parts of the target; (ii it includes a fragmentation of the target into a given number of parts in the training stage to provide equal intensity responses of the system for each part of the target. With the help of computer simulation, the performance of the proposed algorithm for recognition partially occluded objects is compared with that of common algorithms in terms of objective metrics.

A Model for Positively Correlated Count Variables

DEFF Research Database (Denmark)

Møller, Jesper; Rubak, Ege Holger

2010-01-01

An α-permanental random field is briefly speaking a model for a collection of non-negative integer valued random variables with positive associations. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of α-permanental random fields...... and their potential applications. The purpose of this paper is to summarize useful probabilistic results, study stochastic constructions and simulation techniques, and discuss some examples of α-permanental random fields. This should provide a useful basis for discussing the statistical aspects in future work....

The effect of long-term changes in plant inputs on soil carbon stocks

Science.gov (United States)

Georgiou, K.; Li, Z.; Torn, M. S.

2017-12-01

Soil organic carbon (SOC) is the largest actively-cycling terrestrial reservoir of C and an integral component of thriving natural and managed ecosystems. C input interventions (e.g., litter removal or organic amendments) are common in managed landscapes and present an important decision for maintaining healthy soils in sustainable agriculture and forestry. Furthermore, climate and land-cover change can also affect the amount of plant C inputs that enter the soil through changes in plant productivity, allocation, and rooting depth. Yet, the processes that dictate the response of SOC to such changes in C inputs are poorly understood and inadequately represented in predictive models. Long-term litter manipulations are an invaluable resource for exploring key controls of SOC storage and validating model representations. Here we explore the response of SOC to long-term changes in plant C inputs across a range of biomes and soil types. We synthesize and analyze data from long-term litter manipulation field experiments, and focus our meta-analysis on changes to total SOC stocks, microbial biomass carbon, and mineral-associated (`protected') carbon pools and explore the relative contribution of above- versus below-ground C inputs. Our cross-site data comparison reveals that divergent SOC responses are observed between forest sites, particularly for treatments that increase C inputs to the soil. We explore trends among key variables (e.g., microbial biomass to SOC ratios) that inform soil C model representations. The assembled dataset is an important benchmark for evaluating process-based hypotheses and validating divergent model formulations.

Analysis of the Variability of Epstein-Barr Virus Genes in Infectious Mononucleosis: Investigation of the Potential Correlation with Biochemical Parameters of Hepatic Involvement.

Science.gov (United States)

Banko, Ana; Lazarevic, Ivana; Stevanovic, Goran; Cirkovic, Andja; Karalic, Danijela; Cupic, Maja; Banko, Bojan; Milovanovic, Jovica; Jovanovic, Tanja

2016-09-01

Primary Epstein-Barr virus (EBV) infection is usually asymptomatic, although at times it results in the benign lymphoproliferative disease, infectious mononucleosis (IM), during which almost half of patients develop hepatitis. The aims of the present study are to evaluate polymorphisms of EBV genes circulating in IM isolates from this geographic region and to investigate the correlation of viral sequence patterns with the available IM biochemical parameters. The study included plasma samples from 128 IM patients. The genes EBNA2, LMP1 , and EBNA1 were amplified using nested-PCR. EBNA2 genotyping was performed by visualization of PCR products using gel electrophoresis. Investigation of LMP1 and EBNA1 included sequence, phylogenetic, and statistical analyses. The presence of EBV DNA in plasma samples showed correlation with patients' necessity for hospitalization (p=0.034). The majority of EBV isolates was genotype 1. LMP1 variability showed 4 known variants, and two new deletions (27-bp and 147-bp). Of the 3 analyzed attributes of LMP1 isolates, the number of 33-bp repeats less than the reference 4.5 was the only one that absolutely correlated with the elevated levels of transaminases. EBNA1 variability was presented by prototype subtypes. A particular combination of EBNA2, LMP1 , and EBNA1 polymorphisms, deleted LMP1/P-thr and non-deleted LMP1/P-ala , as well as genotype 1/ 4.5 33-bp LMP1 repeats or genotype 2/ 4.5 33-bp LMP1 repeats showed correlation with elevated AST (aspartate aminotransferase) and ALT (alanine transaminase). This is the first study which identified the association between EBV variability and biochemical parameters in IM patients. These results showed a possibility for the identification of hepatic related diagnostic EBV markers.

Heat rate variability and dyssomnia and their correlations to neurological defects in cerebral infarction patients complicated by insomnia A concurrent non-randomized case-control study

Institute of Scientific and Technical Information of China (English)

Jianping Chu; Xueli Shen; Jun Fan; Changhai Chen; Shuyang Lin

2008-01-01

BACKGROUND: Heart rate variability refers to the beat-to-beat alteration in heart rate. It is usually a slight periodic variation of R-R intervals. Much information of autonomic nerve system balance can be obtained by measuring the heart rate variability of patients. It remains to be shown whether heart rate variability can be used as an index for determining the severity of insomnia and cerebral infarction. OBJECTIVE: This study aimed to analyze the correlation for each frequency spectrum parameter of heart rate variability with an insomnia index, as well as the degree of neurological defects in patients with simple cerebral infarction and cerebral infarction complicated by insomnia. The goal was to verify the feasibility of frequency spectrum parameters for heart rate variability as a marker for insomnia and cerebral infarction. DESIGN: A case-control observation. SETTING: Department of Neurology, First Hospital Affiliated to China Medical University. PARTICIPANTS: Sixty inpatients, and/or outpatients, with cerebral infarction were admitted to the 202 Hospital of Chinese PLA between December 2005 and October 2006, confirmed by CT, and recruited to the study. According to the insomnia condition (insomnia is defined by a Pittsburgh Sleep Quality Index score > 7), the patients were assigned to a simple cerebral infarction group and a cerebral infarction complicated by insomnia group, with 30 subjects in each group. Thirty additional subjects, who concurrently received ex-aminations and were confirmed to not suffer from cerebral infarction and insomnia, were recruited into the control group. Written informed consent was obtained from each subject for laboratory specimens. The pro-tocol was approved by the Hospital's Ethics Committee. METHODS: Following admission, each subject's neurological impairment was assessed with the National Institutes of Health Stroke Scale and Pittsburgh Sleep Quality Index. Heart rate variability of each subject was measured with an

Prediction-Based Control for Nonlinear Systems with Input Delay

Directory of Open Access Journals (Sweden)

I. Estrada-Sánchez

2017-01-01

Full Text Available This work has two primary objectives. First, it presents a state prediction strategy for a class of nonlinear Lipschitz systems subject to constant time delay in the input signal. As a result of a suitable change of variable, the state predictor asymptotically provides the value of the state τ units of time ahead. Second, it proposes a solution to the stabilization and trajectory tracking problems for the considered class of systems using predicted states. The predictor-controller convergence is proved by considering a complete Lyapunov functional. The proposed predictor-based controller strategy is evaluated using numerical simulations.

Momentum, sensible heat and CO2 correlation coefficient variability: what can we learn from 20 years of continuous eddy covariance measurements?

Science.gov (United States)

Hurdebise, Quentin; Heinesch, Bernard; De Ligne, Anne; Vincke, Caroline; Aubinet, Marc

2017-04-01

Long-term data series of carbon dioxide and other gas exchanges between terrestrial ecosystems and atmosphere become more and more numerous. Long-term analyses of such exchanges require a good understanding of measurement conditions during the investigated period. Independently of climate drivers, measurements may indeed be influenced by measurement conditions themselves subjected to long-term variability due to vegetation growth or set-up changes. The present research refers to the Vielsalm Terrestrial Observatory (VTO) an ICOS candidate site located in a mixed forest (beech, silver fir, Douglas fir, Norway spruce) in the Belgian Ardenne. Fluxes of momentum, carbon dioxide and sensible heat have been continuously measured there by eddy covariance for more than 20 years. During this period, changes in canopy height and measurement height occurred. The correlation coefficients (for momemtum, sensible heat and CO2) and the normalized standard deviations measured for the past 20 years at the Vielsalm Terrestrial Observatory (VTO) were analysed in order to define how the fluxes, independently of climate conditions, were affected by the surrounding environment evolution, including tree growth, forest thinning and tower height change. A relationship between canopy aerodynamic distance and the momentum correlation coefficient was found which is characteristic of the roughness sublayer, and suggests that momentum transport processes were affected by z-d. In contrast, no relationship was found for sensible heat and CO2 correlation coefficients, suggesting that the z-d variability observed did not affect their turbulent transport. There were strong differences in these coefficients, however, between two wind sectors, characterized by contrasted stands (height differences, homogeneity) and different hypotheses were raised to explain it. This study highlighted the importance of taking the surrounding environment variability into account in order to ensure the spatio

Nitrogen input from residential lawn care practices in suburban watersheds in Baltimore county, MD

Science.gov (United States)

Neely L. Law; Lawrence E. Band; J. Morgan. Grove

2004-01-01

A residential lawn care survey was conducted as part of the Baltimore Ecosystem Study, a Long-term Ecological Research project funded by the National Science Foundation and collaborating agencies, to estimate the nitrogen input to urban watersheds from lawn care practices. The variability in the fertilizer N application rates and the factors affecting the application...

Macro-Finance Determinants of the Long-Run Stock-Bond Correlation

DEFF Research Database (Denmark)

Asgharian, Hossein; Christiansen, Charlotte; Hou, Ai Jun

itself. Macro-finance variables and the lagged realized correlation are simultaneously significant in forecasting the long-run stock-bond correlation. The behavior of the long-run stock-bond correlation is very different when estimated taking the macro-finance variables into account. Supporting......We investigate the long-run stock-bond correlation using a novel model that combines the dynamic conditional correlation model with the mixed-data sampling approach. The long-run correlation is affected by both macro-finance variables (historical and forecasts) and the lagged realized correlation...

Enhanced Input in LCTL Pedagogy

Directory of Open Access Journals (Sweden)

Marilyn S. Manley

2009-08-01

Full Text Available Language materials for the more-commonly-taught languages (MCTLs often include visual input enhancement (Sharwood Smith 1991, 1993 which makes use of typographical cues like bolding and underlining to enhance the saliency of targeted forms. For a variety of reasons, this paper argues that the use of enhanced input, both visual and oral, is especially important as a tool for the lesscommonly-taught languages (LCTLs. As there continues to be a scarcity of teaching resources for the LCTLs, individual teachers must take it upon themselves to incorporate enhanced input into their own self-made materials. Specific examples of how to incorporate both visual and oral enhanced input into language teaching are drawn from the author’s own experiences teaching Cuzco Quechua. Additionally, survey results are presented from the author’s Fall 2010 semester Cuzco Quechua language students, supporting the use of both visual and oral enhanced input.

Enhanced Input in LCTL Pedagogy

Directory of Open Access Journals (Sweden)

Marilyn S. Manley

2010-08-01

Full Text Available Language materials for the more-commonly-taught languages (MCTLs often include visual input enhancement (Sharwood Smith 1991, 1993 which makes use of typographical cues like bolding and underlining to enhance the saliency of targeted forms. For a variety of reasons, this paper argues that the use of enhanced input, both visual and oral, is especially important as a tool for the lesscommonly-taught languages (LCTLs. As there continues to be a scarcity of teaching resources for the LCTLs, individual teachers must take it upon themselves to incorporate enhanced input into their own self-made materials. Specific examples of how to incorporate both visual and oral enhanced input into language teaching are drawn from the author’s own experiences teaching Cuzco Quechua. Additionally, survey results are presented from the author’s Fall 2010 semester Cuzco Quechua language students, supporting the use of both visual and oral enhanced input.

GIS and correlation analysis of geo-environmental variables ...

African Journals Online (AJOL)

Key words: Correlation, GIS, malaria geography, malaria incidence ... problems, as it has created the possibility for geocoding, extracting and spatial analysis of health ...... Bulletin of the World Health Organization, 78(12), 1438–1444. Carter ...

A radial map of multi-whisker correlation selectivity in the rat barrel cortex.

Science.gov (United States)

Estebanez, Luc; Bertherat, Julien; Shulz, Daniel E; Bourdieu, Laurent; Léger, Jean-François

2016-11-21

In the barrel cortex, several features of single-whisker stimuli are organized in functional maps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whisker inputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown. Here we report that layer 2/3 of the rat barrel cortex contains an additional functional map based on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuron responses to uncorrelated multi-whisker stimulation are strongest above barrel centres, whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peak above the barrel-septal borders, forming rings of multi-whisker synchrony-preferring cells.

Analysis of biopsy outcome after three-dimensional conformal radiation therapy of prostate cancer using dose-distribution variables and tumor control probability models

International Nuclear Information System (INIS)

Levegruen, Sabine; Jackson, Andrew; Zelefsky, Michael J.; Venkatraman, Ennapadam S.; Skwarchuk, Mark W.; Schlegel, Wolfgang; Fuks, Zvi; Leibel, Steven A.; Ling, C. Clifton

2000-01-01

Purpose: To investigate tumor control following three-dimensional conformal radiation therapy (3D-CRT) of prostate cancer and to identify dose-distribution variables that correlate with local control assessed through posttreatment prostate biopsies. Methods and Material: Data from 132 patients, treated at Memorial Sloan-Kettering Cancer Center (MSKCC), who had a prostate biopsy 2.5 years or more after 3D-CRT for T1c-T3 prostate cancer with prescription doses of 64.8-81 Gy were analyzed. Variables derived from the dose distribution in the PTV included: minimum dose (Dmin), maximum dose (Dmax), mean dose (Dmean), dose to n% of the PTV (Dn), where n = 1%, ..., 99%. The concept of the equivalent uniform dose (EUD) was evaluated for different values of the surviving fraction at 2 Gy (SF 2 ). Four tumor control probability (TCP) models (one phenomenologic model using a logistic function and three Poisson cell kill models) were investigated using two sets of input parameters, one for low and one for high T-stage tumors. Application of both sets to all patients was also investigated. In addition, several tumor-related prognostic variables were examined (including T-stage, Gleason score). Univariate and multivariate logistic regression analyses were performed. The ability of the logistic regression models (univariate and multivariate) to predict the biopsy result correctly was tested by performing cross-validation analyses and evaluating the results in terms of receiver operating characteristic (ROC) curves. Results: In univariate analysis, prescription dose (Dprescr), Dmax, Dmean, dose to n% of the PTV with n of 70% or less correlate with outcome (p 2 : EUD correlates significantly with outcome for SF 2 of 0.4 or more, but not for lower SF 2 values. Using either of the two input parameters sets, all TCP models correlate with outcome (p 2 , is limited because the low dose region may not coincide with the tumor location. Instead, for MSKCC prostate cancer patients with their

Magnetic resonance observation of cartilage repair tissue (MOCART) for the evaluation of autologous chondrocyte transplantation: Determination of interobserver variability and correlation to clinical outcome after 2 years

International Nuclear Information System (INIS)

Marlovits, Stefan; Singer, Philipp; Zeller, Philip; Mandl, Irena; Haller, Joerg; Trattnig, Siegfried

2006-01-01

In an observational study, the validity and reliability of magnetic resonance imaging (MRI) for the assessment of autologous chondrocyte transplantation (ACT) in the knee joint was determined. Two years after implantation, high-resolution MRI was used to analyze the repair tissue with nine pertinent variables. A complete filling of the defect was found in 61.5%, and a complete integration of the border zone to the adjacent cartilage in 76.9%. An intact subchondral lamina was present in 84.6% and an intact subchondral bone was present in 61.5%. Isointense signal intensities of the repair tissue compared to the adjacent native cartilage were seen in 92.3%. To evaluate interobserver variability, a reliability analysis with the determination of the intraclass correlation coefficient (ICC) was calculated. An 'almost perfect' agreement, with an ICC value >0.81, was calculated in 8 of 9 variables. The clinical outcome after 2 years showed the visual analog score (VAS) at 2.62 (S.D. ±0.65). The values for the knee injury and osteoarthritis outcome score (KOOS) subgroups were 68.29 (±23.90) for pain, 62.09 (±14.62) for symptoms, 75.45 (±21.91) for ADL function, 52.69 (±28.77) for sport and 70.19 (±22.41) for knee-related quality of life. The clinical scores were correlated with the MRI variables. A statistically significant correlation was found for the variables 'filling of the defect,' 'structure of the repair tissue,' 'changes in the subchondral bone,' and 'signal intensities of the repair issue'. High resolution MRI and well-defined MRI variables are a reliable, reproducible and accurate tool for assessing cartilage repair tissue

Investigation of empirical correlations on the determination of condensation heat transfer characteristics during downward annular flow of R134a inside a vertical smooth tube using artificial intelligence algorithms

Energy Technology Data Exchange (ETDEWEB)

Balcilar, Muhammet; Dalkilic, Ahmet Selim; Bolat, Berna [Yildiz Technical University, Istanbul (Turkmenistan); Wongwises, Somchai [King Mongkut' s University of Technology Thonburi, Bangkok (Thailand)

2011-10-15

The heat transfer characteristics of R134a during downward condensation are investigated experimentally and numerically. While the convective heat transfer coefficient, two-phase multiplier and frictional pressure drop are considered to be the significant variables as output for the analysis, inputs of the computational numerical techniques include the important two-phase flow parameters such as equivalent Reynolds number, Prandtl number, Bond number, Froude number, Lockhart and Martinelli number. Genetic algorithm technique (GA), unconstrained nonlinear minimization algorithm-Nelder-Mead method (NM) and non-linear least squares error method (NLS) are applied for the optimization of these significant variables in this study. Regression analysis gave convincing correlations on the prediction of condensation heat transfer characteristics using {+-}30% deviation band for practical applications. The most suitable coefficients of the proposed correlations are depicted to be compatible with the large number of experimental data by means of the computational numerical methods. Validation process of the proposed correlations is accomplished by means of the comparison between the various correlations reported in the literature.

Modeling conditional correlations of asset returns

DEFF Research Database (Denmark)

Silvennoinen, Annastiina; Teräsvirta, Timo

2015-01-01

In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM-test is d......In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The time-varying conditional correlations change smoothly between two extreme states of constant correlations according to a predetermined or exogenous transition variable. An LM......-test is derived to test the constancy of correlations and LM- and Wald tests to test the hypothesis of partially constant correlations. Analytical expressions for the test statistics and the required derivatives are provided to make computations feasible. An empirical example based on daily return series of five...

Corrections for frequency domain transformations of Winfrith binary cross correlator responses

International Nuclear Information System (INIS)

Cummins, J.D.

1968-04-01

This report considers the corrections for frequency domain transformations of Winfrith binary cross correlator responses; (i) for the finite bandwidth of the equivalent input signal; (2) for the finite time required for the actuator to move between the two positions appropriate to the two levels of the periodic binary chain code input and (3) for the averaging of experimental determinations of the system frequency response and calculations of the standard deviations of the modulus and phase of the frequency responses determined from the cross correlator responses. (author)

Neural pulse frequency modulation of an exponentially correlated Gaussian process

Science.gov (United States)

Hutchinson, C. E.; Chon, Y.-T.

1976-01-01

The effect of NPFM (Neural Pulse Frequency Modulation) on a stationary Gaussian input, namely an exponentially correlated Gaussian input, is investigated with special emphasis on the determination of the average number of pulses in unit time, known also as the average frequency of pulse occurrence. For some classes of stationary input processes where the formulation of the appropriate multidimensional Markov diffusion model of the input-plus-NPFM system is possible, the average impulse frequency may be obtained by a generalization of the approach adopted. The results are approximate and numerical, but are in close agreement with Monte Carlo computer simulation results.

Stabilization of Networked Control Systems with Variable Delays and Saturating Inputs

Directory of Open Access Journals (Sweden)

M. Mahmodi Kaleybar

2014-06-01

Full Text Available In this paper, improved conditions for the synthesis of static state-feedback controller are derived to stabilize networked control systems (NCSs subject to actuator saturation. Both of the data packet latency and dropout which deteriorate the performance of the closed-loop system are considered in the NCS model via variable delays. Two different techniques are employed to incorporate actuator saturation in the system description. Utilizing Lyapunov-Krasovskii Theorem, delay-dependent conditions are obtained in terms of linear matrix inequalities (LMIs to determine the static feedback gain. Moreover, an optimization problem is formulated in order to find the less conservative estimate for the region of attraction corresponding to different maximum allowable delays. Numerical examples are introduced to demonstrate the effectiveness and advantages of the proposed schemes.

MDS MIC Catalog Inputs

Science.gov (United States)

Johnson-Throop, Kathy A.; Vowell, C. W.; Smith, Byron; Darcy, Jeannette

2006-01-01

This viewgraph presentation reviews the inputs to the MDS Medical Information Communique (MIC) catalog. The purpose of the group is to provide input for updating the MDS MIC Catalog and to request that MMOP assign Action Item to other working groups and FSs to support the MITWG Process for developing MIC-DDs.

Variability in Measured Space Temperatures in 60 Homes

Energy Technology Data Exchange (ETDEWEB)

Roberts, D.; Lay, K.

2013-03-01

This report discusses the observed variability in indoor space temperature in a set of 60 homes located in Florida, New York, Oregon, and Washington. Temperature data were collected at 15-minute intervals for an entire year, including living room, master bedroom, and outdoor air temperature (Arena, et. al). The data were examined to establish the average living room temperature for the set of homes for the heating and cooling seasons, the variability of living room temperature depending on climate, and the variability of indoor space temperature within the homes. The accuracy of software-based energy analysis depends on the accuracy of input values. Thermostat set point is one of the most influential inputs for building energy simulation. Several industry standards exist that recommend differing default thermostat settings for heating and cooling seasons. These standards were compared to the values calculated for this analysis. The data examined for this report show that there is a definite difference between the climates and that the data do not agree well with any particular standard.

Overcoming multicollinearity in multiple regression using correlation coefficient

Science.gov (United States)

Zainodin, H. J.; Yap, S. J.

2013-09-01

Multicollinearity happens when there are high correlations among independent variables. In this case, it would be difficult to distinguish between the contributions of these independent variables to that of the dependent variable as they may compete to explain much of the similar variance. Besides, the problem of multicollinearity also violates the assumption of multiple regression: that there is no collinearity among the possible independent variables. Thus, an alternative approach is introduced in overcoming the multicollinearity problem in achieving a well represented model eventually. This approach is accomplished by removing the multicollinearity source variables on the basis of the correlation coefficient values based on full correlation matrix. Using the full correlation matrix can facilitate the implementation of Excel function in removing the multicollinearity source variables. It is found that this procedure is easier and time-saving especially when dealing with greater number of independent variables in a model and a large number of all possible models. Hence, in this paper detailed insight of the procedure is shown, compared and implemented.

Simplified quantitative treatment of uncertainty and interindividual variability in health risk assessment

International Nuclear Information System (INIS)

Bogen, K.T.

1993-01-01

A distinction between uncertainty (or the extent of lack of knowledge) and interindividual variability (or the extent of person-to-person heterogeneity) regarding the values of input variates must be maintained if a quantitative characterization of uncertainty in population risk or in individual risk is sought. Here, some practical methods are presented that should facilitate implementation of the analytic framework for uncertainty and variability proposed by Bogen and Spear. (1,2) Two types of methodology are discussed: one that facilitates the distinction between uncertainty and variability per se, and another that may be used to simplify quantitative analysis of distributed inputs representing either uncertainty or variability. A simple and a complex form for modeled increased risk are presented and then used to illustrate methods facilitating the distinction between uncertainty and variability in reference to characterization of both population and individual risk. Finally, a simple form of discrete probability calculus is proposed as an easily implemented, practical altemative to Monte-Carlo based procedures to quantitative integration of uncertainty and variability in risk assessment

Reliable computation from contextual correlations

Science.gov (United States)

Oestereich, André L.; Galvão, Ernesto F.

2017-12-01

An operational approach to the study of computation based on correlations considers black boxes with one-bit inputs and outputs, controlled by a limited classical computer capable only of performing sums modulo-two. In this setting, it was shown that noncontextual correlations do not provide any extra computational power, while contextual correlations were found to be necessary for the deterministic evaluation of nonlinear Boolean functions. Here we investigate the requirements for reliable computation in this setting; that is, the evaluation of any Boolean function with success probability bounded away from 1 /2 . We show that bipartite CHSH quantum correlations suffice for reliable computation. We also prove that an arbitrarily small violation of a multipartite Greenberger-Horne-Zeilinger noncontextuality inequality also suffices for reliable computation.

Correlation Structures of Correlated Binomial Models and Implied Default Distribution

Science.gov (United States)

Mori, Shintaro; Kitsukawa, Kenji; Hisakado, Masato

2008-11-01

We show how to analyze and interpret the correlation structures, the conditional expectation values and correlation coefficients of exchangeable Bernoulli random variables. We study implied default distributions for the iTraxx-CJ tranches and some popular probabilistic models, including the Gaussian copula model, Beta binomial distribution model and long-range Ising model. We interpret the differences in their profiles in terms of the correlation structures. The implied default distribution has singular correlation structures, reflecting the credit market implications. We point out two possible origins of the singular behavior.

Respiratory variability preceding and following sighs: a resetter hypothesis.

Science.gov (United States)

Vlemincx, Elke; Van Diest, Ilse; Lehrer, Paul M; Aubert, André E; Van den Bergh, Omer

2010-04-01

Respiratory behavior is characterized by complex variability with structured and random components. Assuming that both a lack of variability and too much randomness represent suboptimal breathing regulation, we hypothesized that sighing acts as a resetter inducing structured variability. Spontaneous breathing was measured in healthy persons (N=42) during a 20min period of quiet sitting using the LifeShirt(®) System. Four blocks of 10 breaths with a 50% window overlap were determined before and after spontaneous sighs. Total respiratory variability of minute ventilation was measured using the coefficient of variation and structured (correlated) variability was quantified using autocorrelation. Towards a sigh, total variability gradually increased without concomittant changes in correlated variability, suggesting that randomness increased. After a sigh, correlated variability increased. No changes in variability were found in comparable epochs without intermediate sighs. We conclude that a sigh resets structured respiratory variability, enhancing information processing in the respiratory system. Copyright © 2009 Elsevier B.V. All rights reserved.

Lexical and phonological variability in preschool children with speech sound disorder.

Science.gov (United States)

Macrae, Toby; Tyler, Ann A; Lewis, Kerry E

2014-02-01

The authors of this study examined relationships between measures of word and speech error variability and between these and other speech and language measures in preschool children with speech sound disorder (SSD). In this correlational study, 18 preschool children with SSD, age-appropriate receptive vocabulary, and normal oral motor functioning and hearing were assessed across 2 sessions. Experimental measures included word and speech error variability, receptive vocabulary, nonword repetition (NWR), and expressive language. Pearson product–moment correlation coefficients were calculated among the experimental measures. The correlation between word and speech error variability was slight and nonsignificant. The correlation between word variability and receptive vocabulary was moderate and negative, although nonsignificant. High word variability was associated with small receptive vocabularies. The correlations between speech error variability and NWR and between speech error variability and the mean length of children's utterances were moderate and negative, although both were nonsignificant. High speech error variability was associated with poor NWR and language scores. High word variability may reflect unstable lexical representations, whereas high speech error variability may reflect indistinct phonological representations. Preschool children with SSD who show abnormally high levels of different types of speech variability may require slightly different approaches to intervention.

Variabilidade espacial de atributos químicos de um argissolo para aplicação de insumos à taxa variável em diferentes formas de relevo Spatial variability of chemical attributes in an alfisol for variable rates of inputs in different forms of relief

Directory of Open Access Journals (Sweden)

Diogo M. Barbieri

2008-12-01

Full Text Available A agricultura de precisão implica análise da variabilidade espacial de fatores de produção e a aplicação de insumos de forma localizada. Várias são as causas que condicionam a variabilidade espacial dos solos, sendo o relevo um dos fatores mais importantes. O presente estudo teve por objetivo analisar a variabilidade espacial dos atributos químicos do solo e a elaboração de mapas de necessidade de aplicação de insumos de forma localizada, em áreas com diferentes formas de relevo. Duas parcelas de 1 ha cada foram delimitadas em áreas com topografia côncava e convexa. Foram retiradas, em cada área, 242 amostras de solos em 121 pontos, nas profundidades de solo de 0,00-0,20 m e 0,20-0,40 m. Os resultados de análise química foram submetidos às análises da estatística descritiva, geoestatística e interpolação por krigagem. A área convexa apresentou maior variabilidade espacial do solo em relação a área côncava. A adoção da agricultura de precisão possibilitou economia de aproximadamente 25 kg ha-1 de P2O5 na área côncava.The precision agriculture implies an analysis of spatial variability of production factors and the inputs application of located form. There are several factors that cause spatial variability in soils; relief is one of the most important ones. The objective of this study was to analyze the spatial variability, the chemical attributes of the soil and the elaboration of maps necessity for input application of located form, in areas with different relief forms. Two parcels of one hectare each were delimited in areas with concave and convex shaped topography. A set of 242 samples were collected from each area at 121 points in depths of 0.00-0.20 m and 0.20-0.40 m. The data were submitted to the descriptive statistical analyses, geostatistics and interpolation for kriging. The convex area presented more spatial variability of the soil in relation the concave area. The adoption of precision agriculture

Modeling of heat transfer into a heat pipe for a localized heat input zone

International Nuclear Information System (INIS)

Rosenfeld, J.H.

1987-01-01

A general model is presented for heat transfer into a heat pipe using a localized heat input. Conduction in the wall of the heat pipe and boiling in the interior structure are treated simultaneously. The model is derived from circumferential heat transfer in a cylindrical heat pipe evaporator and for radial heat transfer in a circular disk with boiling from the interior surface. A comparison is made with data for a localized heat input zone. Agreement between the theory and the model is good. This model can be used for design purposes if a boiling correlation is available. The model can be extended to provide improved predictions of heat pipe performance

Role of updraft velocity in temporal variability of global cloud hydrometeor number

Science.gov (United States)

Sullivan, Sylvia C.; Lee, Dongmin; Oreopoulos, Lazaros; Nenes, Athanasios

2016-05-01

Understanding how dynamical and aerosol inputs affect the temporal variability of hydrometeor formation in climate models will help to explain sources of model diversity in cloud forcing, to provide robust comparisons with data, and, ultimately, to reduce the uncertainty in estimates of the aerosol indirect effect. This variability attribution can be done at various spatial and temporal resolutions with metrics derived from online adjoint sensitivities of droplet and crystal number to relevant inputs. Such metrics are defined and calculated from simulations using the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1 (CAM5.1). Input updraft velocity fluctuations can explain as much as 48% of temporal variability in output ice crystal number and 61% in droplet number in GEOS-5 and up to 89% of temporal variability in output ice crystal number in CAM5.1. In both models, this vertical velocity attribution depends strongly on altitude. Despite its importance for hydrometeor formation, simulated vertical velocity distributions are rarely evaluated against observations due to the sparsity of relevant data. Coordinated effort by the atmospheric community to develop more consistent, observationally based updraft treatments will help to close this knowledge gap.

[Application of characteristic NIR variables selection in portable detection of soluble solids content of apple by near infrared spectroscopy].

Science.gov (United States)

Fan, Shu-Xiang; Huang, Wen-Qian; Li, Jiang-Bo; Guo, Zhi-Ming; Zhaq, Chun-Jiang

2014-10-01

In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including unin- formative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were pro- posed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS- SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.

Role of correlation in the operation of quantum-dot cellular automata

International Nuclear Information System (INIS)

Toth, Geza; Lent, Craig S.

2001-01-01

Quantum-dot cellular automata (QCA) may offer a viable alternative of traditional transistor-based technology at the nanoscale. When modeling a QCA circuit, the number of degrees of freedom necessary to describe the quantum mechanical state increases exponentially making modeling even modest size cell arrays difficult. The intercellular Hartree approximation largely reduces the number of state variables and still gives good results especially when the system remains near ground state. This suggests that a large part of the correlation degrees of freedom are not essential from the point of view of the dynamics. In certain cases, however, such as, for example, the majority gate with unequal input legs, the Hartree approximation gives qualitatively wrong results. An intermediate model is constructed between the Hartree approximation and the exact model, based on the coherence vector formalism. By including correlation effects to a desired degree, it improves the results of the Hartree method and gives the approximate dynamics of the correlation terms. It also models the majority gate correctly. Beside QCA cell arrays, our findings are valid for Ising spin chains in transverse magnetic field, and can be straightforwardly generalized for coupled two-level systems with a more complicated Hamiltonian. [copyright] 2001 American Institute of Physics

Alternatives to Pearson's and Spearman's Correlation Coefficients

OpenAIRE

Smarandache, Florentin

2008-01-01

This article presents several alternatives to Pearson's correlation coefficient and many examples. In the samples where the rank in a discrete variable counts more than the variable values, the mixtures that we propose of Pearson's and Spearman's correlation coefficients give better results.

Distance correlation methods for discovering associations in large astrophysical databases

International Nuclear Information System (INIS)

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P.

2014-01-01

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient, which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension, can be used to determine smaller sets of variables that provide equivalent astrophysical information, is zero only when variables are independent, and is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated horseshoe- or V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.

State, Parameter, and Unknown Input Estimation Problems in Active Automotive Safety Applications

Science.gov (United States)

Phanomchoeng, Gridsada

A variety of driver assistance systems such as traction control, electronic stability control (ESC), rollover prevention and lane departure avoidance systems are being developed by automotive manufacturers to reduce driver burden, partially automate normal driving operations, and reduce accidents. The effectiveness of these driver assistance systems can be significant enhanced if the real-time values of several vehicle parameters and state variables, namely tire-road friction coefficient, slip angle, roll angle, and rollover index, can be known. Since there are no inexpensive sensors available to measure these variables, it is necessary to estimate them. However, due to the significant nonlinear dynamics in a vehicle, due to unknown and changing plant parameters, and due to the presence of unknown input disturbances, the design of estimation algorithms for this application is challenging. This dissertation develops a new approach to observer design for nonlinear systems in which the nonlinearity has a globally (or locally) bounded Jacobian. The developed approach utilizes a modified version of the mean value theorem to express the nonlinearity in the estimation error dynamics as a convex combination of known matrices with time varying coefficients. The observer gains are then obtained by solving linear matrix inequalities (LMIs). A number of illustrative examples are presented to show that the developed approach is less conservative and more useful than the standard Lipschitz assumption based nonlinear observer. The developed nonlinear observer is utilized for estimation of slip angle, longitudinal vehicle velocity, and vehicle roll angle. In order to predict and prevent vehicle rollovers in tripped situations, it is necessary to estimate the vertical tire forces in the presence of unknown road disturbance inputs. An approach to estimate unknown disturbance inputs in nonlinear systems using dynamic model inversion and a modified version of the mean value theorem is

Input filter compensation for switching regulators

Science.gov (United States)

Lee, F. C.; Kelkar, S. S.

1982-01-01

The problems caused by the interaction between the input filter, output filter, and the control loop are discussed. The input filter design is made more complicated because of the need to avoid performance degradation and also stay within the weight and loss limitations. Conventional input filter design techniques are then dicussed. The concept of pole zero cancellation is reviewed; this concept is the basis for an approach to control the peaking of the output impedance of the input filter and thus mitigate some of the problems caused by the input filter. The proposed approach for control of the peaking of the output impedance of the input filter is to use a feedforward loop working in conjunction with feedback loops, thus forming a total state control scheme. The design of the feedforward loop for a buck regulator is described. A possible implementation of the feedforward loop design is suggested.

ASSIST - a package of Fortran routines for handling input under specified syntax rules and for management of data structures

International Nuclear Information System (INIS)

Sinclair, J.E.

1991-02-01

The ASSIST package (A Structured Storage and Input Syntax Tool) provides for Fortran programs a means for handling data structures more general than those provided by the Fortran language, and for obtaining input to the program from a file or terminal according to specified syntax rules. The syntax-controlled input can be interactive, with automatic generation of prompts, and dialogue to correct any input errors. The range of syntax rules possible is sufficient to handle lists of numbers and character strings, keywords, commands with optional clauses, and many kinds of variable-format constructions, such as algebraic expressions. ASSIST was developed for use in two large programs for the analysis of safety of radioactive waste disposal facilities, but it should prove useful for a wide variety of applications. (author)

Magnetic resonance observation of cartilage repair tissue (MOCART) for the evaluation of autologous chondrocyte transplantation: Determination of interobserver variability and correlation to clinical outcome after 2 years

Energy Technology Data Exchange (ETDEWEB)

Marlovits, Stefan [Department of Traumatology, Center for Joint and Cartilage, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna (Austria)]. E-mail: stefan.marlovits@meduniwien.ac.at; Singer, Philipp [Department of Traumatology, Center for Joint and Cartilage, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna (Austria); Zeller, Philip [Department of Traumatology, Center for Joint and Cartilage, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna (Austria); Mandl, Irena [Department of Traumatology, Center for Joint and Cartilage, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna (Austria); Haller, Joerg [Department of Radiology, Hanusch Hospital, Heinrich-Collin-Strasse, A-1140 Vienna (Austria); Trattnig, Siegfried [Department of Radiology, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna (Austria)

2006-01-15

In an observational study, the validity and reliability of magnetic resonance imaging (MRI) for the assessment of autologous chondrocyte transplantation (ACT) in the knee joint was determined. Two years after implantation, high-resolution MRI was used to analyze the repair tissue with nine pertinent variables. A complete filling of the defect was found in 61.5%, and a complete integration of the border zone to the adjacent cartilage in 76.9%. An intact subchondral lamina was present in 84.6% and an intact subchondral bone was present in 61.5%. Isointense signal intensities of the repair tissue compared to the adjacent native cartilage were seen in 92.3%. To evaluate interobserver variability, a reliability analysis with the determination of the intraclass correlation coefficient (ICC) was calculated. An 'almost perfect' agreement, with an ICC value >0.81, was calculated in 8 of 9 variables. The clinical outcome after 2 years showed the visual analog score (VAS) at 2.62 (S.D. {+-}0.65). The values for the knee injury and osteoarthritis outcome score (KOOS) subgroups were 68.29 ({+-}23.90) for pain, 62.09 ({+-}14.62) for symptoms, 75.45 ({+-}21.91) for ADL function, 52.69 ({+-}28.77) for sport and 70.19 ({+-}22.41) for knee-related quality of life. The clinical scores were correlated with the MRI variables. A statistically significant correlation was found for the variables 'filling of the defect,' 'structure of the repair tissue,' 'changes in the subchondral bone,' and 'signal intensities of the repair issue'. High resolution MRI and well-defined MRI variables are a reliable, reproducible and accurate tool for assessing cartilage repair tissue.

Estimating the input function non-invasively for FDG-PET quantification with multiple linear regression analysis: simulation and verification with in vivo data

International Nuclear Information System (INIS)

Fang, Yu-Hua; Kao, Tsair; Liu, Ren-Shyan; Wu, Liang-Chih

2004-01-01

A novel statistical method, namely Regression-Estimated Input Function (REIF), is proposed in this study for the purpose of non-invasive estimation of the input function for fluorine-18 2-fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET) quantitative analysis. We collected 44 patients who had undergone a blood sampling procedure during their FDG-PET scans. First, we generated tissue time-activity curves of the grey matter and the whole brain with a segmentation technique for every subject. Summations of different intervals of these two curves were used as a feature vector, which also included the net injection dose. Multiple linear regression analysis was then applied to find the correlation between the input function and the feature vector. After a simulation study with in vivo data, the data of 29 patients were applied to calculate the regression coefficients, which were then used to estimate the input functions of the other 15 subjects. Comparing the estimated input functions with the corresponding real input functions, the averaged error percentages of the area under the curve and the cerebral metabolic rate of glucose (CMRGlc) were 12.13±8.85 and 16.60±9.61, respectively. Regression analysis of the CMRGlc values derived from the real and estimated input functions revealed a high correlation (r=0.91). No significant difference was found between the real CMRGlc and that derived from our regression-estimated input function (Student's t test, P>0.05). The proposed REIF method demonstrated good abilities for input function and CMRGlc estimation, and represents a reliable replacement for the blood sampling procedures in FDG-PET quantification. (orig.)

Mixed signal learning by spike correlation propagation in feedback inhibitory circuits.

Directory of Open Access Journals (Sweden)

Naoki Hiratani

2015-04-01

Full Text Available The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory.

7 CFR 3430.607 - Stakeholder input.

Science.gov (United States)

2010-01-01

... 7 Agriculture 15 2010-01-01 2010-01-01 false Stakeholder input. 3430.607 Section 3430.607 Agriculture Regulations of the Department of Agriculture (Continued) COOPERATIVE STATE RESEARCH, EDUCATION... § 3430.607 Stakeholder input. CSREES shall seek and obtain stakeholder input through a variety of forums...

Input Uncertainty and its Implications on Parameter Assessment in Hydrologic and Hydroclimatic Modelling Studies

Science.gov (United States)

Chowdhury, S.; Sharma, A.

2005-12-01

Hydrological model inputs are often derived from measurements at point locations taken at discrete time steps. The nature of uncertainty associated with such inputs is thus a function of the quality and number of measurements available in time. A change in these characteristics (such as a change in the number of rain-gauge inputs used to derive spatially averaged rainfall) results in inhomogeneity in the associated distributional profile. Ignoring such uncertainty can lead to models that aim to simulate based on the observed input variable instead of the true measurement, resulting in a biased representation of the underlying system dynamics as well as an increase in both bias and the predictive uncertainty in simulations. This is especially true of cases where the nature of uncertainty likely in the future is significantly different to that in the past. Possible examples include situations where the accuracy of the catchment averaged rainfall has increased substantially due to an increase in the rain-gauge density, or accuracy of climatic observations (such as sea surface temperatures) increased due to the use of more accurate remote sensing technologies. We introduce here a method to ascertain the true value of parameters in the presence of additive uncertainty in model inputs. This method, known as SIMulation EXtrapolation (SIMEX, [Cook, 1994]) operates on the basis of an empirical relationship between parameters and the level of additive input noise (or uncertainty). The method starts with generating a series of alternate realisations of model inputs by artificially adding white noise in increasing multiples of the known error variance. The alternate realisations lead to alternate sets of parameters that are increasingly biased with respect to the truth due to the increased variability in the inputs. Once several such realisations have been drawn, one is able to formulate an empirical relationship between the parameter values and the level of additive noise

On the Influence of Input Data Quality to Flood Damage Estimation: The Performance of the INSYDE Model

Directory of Open Access Journals (Sweden)

Daniela Molinari

2017-09-01

Full Text Available IN-depth SYnthetic Model for Flood Damage Estimation (INSYDE is a model for the estimation of flood damage to residential buildings at the micro-scale. This study investigates the sensitivity of INSYDE to the accuracy of input data. Starting from the knowledge of input parameters at the scale of individual buildings for a case study, the level of detail of input data is progressively downgraded until the condition in which a representative value is defined for all inputs at the census block scale. The analysis reveals that two conditions are required to limit the errors in damage estimation: the representativeness of representatives values with respect to micro-scale values and the local knowledge of the footprint area of the buildings, being the latter the main extensive variable adopted by INSYDE. Such a result allows for extending the usability of the model at the meso-scale, also in different countries, depending on the availability of aggregated building data.

World Input-Output Network.

Directory of Open Access Journals (Sweden)

Federica Cerina

Full Text Available Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD is one of the first efforts to construct the global multi-regional input-output (GMRIO tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

Bounding the conservatism in flaw-related variables for pressure vessel integrity analyses

International Nuclear Information System (INIS)

Foulds, J.R.; Kennedy, E.L.

1993-01-01

The fracture mechanics-based integrity analysis of a pressure vessel, whether performed deterministically or probabilistically, requires use of one or more flaw-related input variables, such as flaw size, number of flaws, flaw location, and flaw type. The specific values of these variables are generally selected with the intent to ensure conservative predictions of vessel integrity. These selected values, however, are largely independent of vessel-specific inspection results, or are, at best, deduced by ''conservative'' interpretation of vessel-specific inspection results without adequate consideration of the pertinent inspection system performance (reliability). In either case, the conservatism associated with the flaw-related variables chosen for analysis remains examination (NDE) technology and the recently formulated ASME Code procedures for qualifying NDE system capability and performance (as applied to selected nuclear power plant components) now provides a systematic means of bounding the conservatism in flaw-related input variables for pressure vessel integrity analyses. This is essentially achieved by establishing probabilistic (risk)-based limits on the assigned variable values, dependent upon the vessel inspection results and on the inspection system unreliability. Described herein is this probabilistic method and its potential application to: (i) defining a vessel-specific ''reference'' flaw for calculating pressure-temperature limit curves in the deterministic evaluation of pressurized water reactor (PWR) reactor vessels, and (ii) limiting the flaw distribution input to a PWR reactor vessel-specific, probabilistic integrity analysis for pressurized thermal shock loads

ACORNS, Covariance and Correlation Matrix Diagonalization

International Nuclear Information System (INIS)

Szondi, E.J.

1990-01-01

1 - Description of program or function: The program allows the user to verify the different types of covariance/correlation matrices used in the activation neutron spectrometry. 2 - Method of solution: The program performs the diagonalization of the input covariance/relative covariance/correlation matrices. The Eigen values are then analyzed to determine the rank of the matrices. If the Eigen vectors of the pertinent correlation matrix have also been calculated, the program can perform a complete factor analysis (generation of the factor matrix and its rotation in Kaiser's 'varimax' sense to select the origin of the correlations). 3 - Restrictions on the complexity of the problem: Matrix size is limited to 60 on PDP and to 100 on IBM PC/AT

7 CFR 3430.15 - Stakeholder input.

Science.gov (United States)

2010-01-01

... 7 Agriculture 15 2010-01-01 2010-01-01 false Stakeholder input. 3430.15 Section 3430.15... Stakeholder input. Section 103(c)(2) of the Agricultural Research, Extension, and Education Reform Act of 1998... RFAs for competitive programs. CSREES will provide instructions for submission of stakeholder input in...

147 - 154 Genetic Variability, Heritability and Correlation Coefficient

African Journals Online (AJOL)

USER

twelve upland rice genotypes during 2013 main cropping season. ... spikelet per panicle, number of filled grains per panicle and biomass yield had a positive and significant correlation ... fertilizers were applied at the rate of 100 kg per hectare. ..... ultimate effect for selecting superior varieties (Ali et al., .... (Brassica napus L.).

Coexistence of unlimited bipartite and genuine multipartite entanglement: Promiscuous quantum correlations arising from discrete to continuous-variable systems

International Nuclear Information System (INIS)

Adesso, Gerardo; Ericsson, Marie; Illuminati, Fabrizio

2007-01-01

Quantum mechanics imposes 'monogamy' constraints on the sharing of entanglement. We show that, despite these limitations, entanglement can be fully 'promiscuous', i.e., simultaneously present in unlimited two-body and many-body forms in states living in an infinite-dimensional Hilbert space. Monogamy just bounds the divergence rate of the various entanglement contributions. This is demonstrated in simple families of N-mode (N≥4) Gaussian states of light fields or atomic ensembles, which therefore enable infinitely more freedom in the distribution of information, as opposed to systems of individual qubits. Such a finding is of importance for the quantification, understanding, and potential exploitation of shared quantum correlations in continuous variable systems. We discuss how promiscuity gradually arises when considering simple families of discrete variable states, with increasing Hilbert space dimension towards the continuous variable limit. Such models are somehow analogous to Gaussian states with asymptotically diverging, but finite, squeezing. In this respect, we find that non-Gaussian states (which in general are more entangled than Gaussian states) exhibit also the interesting feature that their entanglement is more shareable: in the non-Gaussian multipartite arena, unlimited promiscuity can be already achieved among three entangled parties, while this is impossible for Gaussian, even infinitely squeezed states

Groundwater travel time uncertainty analysis: Sensitivity of results to model geometry, and correlations and cross correlations among input parameters

International Nuclear Information System (INIS)

Clifton, P.M.

1984-12-01

The deep basalt formations beneath the Hanford Site are being investigated for the Department of Energy (DOE) to assess their suitability as a host medium for a high level nuclear waste repository. Predicted performance of the proposed repository is an important part of the investigation. One of the performance measures being used to gauge the suitability of the host medium is pre-waste-emplacement groundwater travel times to the accessible environment. Many deterministic analyses of groundwater travel times have been completed by Rockwell and other independent organizations. Recently, Rockwell has completed a preliminary stochastic analysis of groundwater travel times. This document presents analyses that show the sensitivity of the results from the previous stochastic travel time study to: (1) scale of representation of model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross-correlation between transmissivity and effective thickness. 40 refs., 29 figs., 6 tabs

Input description for BIOPATH

International Nuclear Information System (INIS)

Marklund, J.E.; Bergstroem, U.; Edlund, O.

1980-01-01

The computer program BIOPATH describes the flow of radioactivity within a given ecosystem after a postulated release of radioactive material and the resulting dose for specified population groups. The present report accounts for the input data necessary to run BIOPATH. The report also contains descriptions of possible control cards and an input example as well as a short summary of the basic theory.(author)

A liquid lens switching-based motionless variable fiber-optic delay line

Science.gov (United States)

Khwaja, Tariq Shamim; Reza, Syed Azer; Sheikh, Mumtaz

2018-05-01

We present a Variable Fiber-Optic Delay Line (VFODL) module capable of imparting long variable delays by switching an input optical/RF signal between Single Mode Fiber (SMF) patch cords of different lengths through a pair of Electronically Controlled Tunable Lenses (ECTLs) resulting in a polarization-independent operation. Depending on intended application, the lengths of the SMFs can be chosen accordingly to achieve the desired VFODL operation dynamic range. If so desired, the state of the input signal polarization can be preserved with the use of commercially available polarization-independent ECTLs along with polarization-maintaining SMFs (PM-SMFs), resulting in an output polarization that is identical to the input. An ECTL-based design also improves power consumption and repeatability. The delay switching mechanism is electronically-controlled, involves no bulk moving parts, and can be fully-automated. The VFODL module is compact due to the use of small optical components and SMFs that can be packaged compactly.