Impact of strong selection for the PrP major gene on genetic variability of four French sheep breeds (Open Access publication)

PubMed Central

Palhiere, Isabelle; Brochard, Mickaël; Moazami-Goudarzi, Katayoun; Laloë, Denis; Amigues, Yves; Bed'hom, Bertrand; Neuts, Étienne; Leymarie, Cyril; Pantano, Thais; Cribiu, Edmond Paul; Bibé, Bernard; Verrier, Étienne

2008-01-01

Effective selection on the PrP gene has been implemented since October 2001 in all French sheep breeds. After four years, the ARR "resistant" allele frequency increased by about 35% in young males. The aim of this study was to evaluate the impact of this strong selection on genetic variability. It is focussed on four French sheep breeds and based on the comparison of two groups of 94 animals within each breed: the first group of animals was born before the selection began, and the second, 3–4 years later. Genetic variability was assessed using genealogical and molecular data (29 microsatellite markers). The expected loss of genetic variability on the PrP gene was confirmed. Moreover, among the five markers located in the PrP region, only the three closest ones were affected. The evolution of the number of alleles, heterozygote deficiency within population, expected heterozygosity and the Reynolds distances agreed with the criteria from pedigree and pointed out that neutral genetic variability was not much affected. This trend depended on breed, i.e. on their initial states (population size, PrP frequencies) and on the selection strategies for improving scrapie resistance while carrying out selection for production traits. PMID:18990357

NLSCIDNT user's guide maximum likehood parameter identification computer program with nonlinear rotorcraft model

NASA Technical Reports Server (NTRS)

1979-01-01

A nonlinear, maximum likelihood, parameter identification computer program (NLSCIDNT) is described which evaluates rotorcraft stability and control coefficients from flight test data. The optimal estimates of the parameters (stability and control coefficients) are determined (identified) by minimizing the negative log likelihood cost function. The minimization technique is the Levenberg-Marquardt method, which behaves like the steepest descent method when it is far from the minimum and behaves like the modified Newton-Raphson method when it is nearer the minimum. Twenty-one states and 40 measurement variables are modeled, and any subset may be selected. States which are not integrated may be fixed at an input value, or time history data may be substituted for the state in the equations of motion. Any aerodynamic coefficient may be expressed as a nonlinear polynomial function of selected 'expansion variables'.

Effect of Selected Variables on Funding State Compensatory and Regular Education in Texas

ERIC Educational Resources Information Center

Wiesman, Karen Wheeler

2009-01-01

Funding public schools has been an ongoing struggle since the inception of the United States. Beginning with Jefferson's "A General Diffusion of Knowledge" that charged the states with properly funding public schools, to the current day legal battles that continue in states across the Union, America struggles with finding a solution to…

An Ensemble Successive Project Algorithm for Liquor Detection Using Near Infrared Sensor.

PubMed

Qu, Fangfang; Ren, Dong; Wang, Jihua; Zhang, Zhong; Lu, Na; Meng, Lei

2016-01-11

Spectral analysis technique based on near infrared (NIR) sensor is a powerful tool for complex information processing and high precision recognition, and it has been widely applied to quality analysis and online inspection of agricultural products. This paper proposes a new method to address the instability of small sample sizes in the successive projections algorithm (SPA) as well as the lack of association between selected variables and the analyte. The proposed method is an evaluated bootstrap ensemble SPA method (EBSPA) based on a variable evaluation index (EI) for variable selection, and is applied to the quantitative prediction of alcohol concentrations in liquor using NIR sensor. In the experiment, the proposed EBSPA with three kinds of modeling methods are established to test their performance. In addition, the proposed EBSPA combined with partial least square is compared with other state-of-the-art variable selection methods. The results show that the proposed method can solve the defects of SPA and it has the best generalization performance and stability. Furthermore, the physical meaning of the selected variables from the near infrared sensor data is clear, which can effectively reduce the variables and improve their prediction accuracy.

Selection by Certification: A Neglected Variable in Stratification Research.

ERIC Educational Resources Information Center

Faia, Michael A.

1981-01-01

Reviews literature on status attainment, with emphasis on the relationship between status and education in the United States. Concludes that the status attainment process in the United States may depart substantially from the rational choice model favored by human capital theory. (DB)

User's instructions for the cardiovascular Walters model

NASA Technical Reports Server (NTRS)

Croston, R. C.

1973-01-01

The model is a combined, steady-state cardiovascular and thermal model. It was originally developed for interactive use, but was converted to batch mode simulation for the Sigma 3 computer. The model has the purpose to compute steady-state circulatory and thermal variables in response to exercise work loads and environmental factors. During a computer simulation run, several selected variables are printed at each time step. End conditions are also printed at the completion of the run.

Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.

USGS Publications Warehouse

Waite, Ian R.

2014-01-01

As part of the USGS study of nutrient enrichment of streams in agricultural regions throughout the United States, about 30 sites within each of eight study areas were selected to capture a gradient of nutrient conditions. The objective was to develop watershed disturbance predictive models for macroinvertebrate and algal metrics at national and three regional landscape scales to obtain a better understanding of important explanatory variables. Explanatory variables in models were generated from landscape data, habitat, and chemistry. Instream nutrient concentration and variables assessing the amount of disturbance to the riparian zone (e.g., percent row crops or percent agriculture) were selected as most important explanatory variable in almost all boosted regression tree models regardless of landscape scale or assemblage. Frequently, TN and TP concentration and riparian agricultural land use variables showed a threshold type response at relatively low values to biotic metrics modeled. Some measure of habitat condition was also commonly selected in the final invertebrate models, though the variable(s) varied across regions. Results suggest national models tended to account for more general landscape/climate differences, while regional models incorporated both broad landscape scale and more specific local-scale variables.

The Self-Perceived Leadership Styles of Chief State School Officers and Models of Educational Governance

ERIC Educational Resources Information Center

Wiggins, Lori A.

2013-01-01

This study examined the leadership styles of the chief state school officers of the United States and the District of Columbia. The entire population of 51 chief state school officers was surveyed and a response rate of 60% was obtained. The study examined the relationship between the leadership style, select demographic variables, and the…

Selected Factors Related to the Mathematics Academic Achievement of Eighth Grade English Language Learners

ERIC Educational Resources Information Center

Garza, Anthony

2012-01-01

The purpose of this study was to examine selected factors related to the 8th grade mathematics achievement levels of English Language Learner (ELL) students in selected South Texas middle schools. The dependent variable, ELL mathematics achievement, was measured by the ELL student's raw score on the State of Texas Assessment of Academic Readiness…

Automatic design of basin-specific drought indexes for highly regulated water systems

NASA Astrophysics Data System (ADS)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea Francesco; Pulido-Velazquez, Manuel

2018-04-01

Socio-economic costs of drought are progressively increasing worldwide due to undergoing alterations of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, traditional drought indexes often fail at detecting critical events in highly regulated systems, where natural water availability is conditioned by the operation of water infrastructures such as dams, diversions, and pumping wells. Here, ad hoc index formulations are usually adopted based on empirical combinations of several, supposed-to-be significant, hydro-meteorological variables. These customized formulations, however, while effective in the design basin, can hardly be generalized and transferred to different contexts. In this study, we contribute FRIDA (FRamework for Index-based Drought Analysis), a novel framework for the automatic design of basin-customized drought indexes. In contrast to ad hoc empirical approaches, FRIDA is fully automated, generalizable, and portable across different basins. FRIDA builds an index representing a surrogate of the drought conditions of the basin, computed by combining all the relevant available information about the water circulating in the system identified by means of a feature extraction algorithm. We used the Wrapper for Quasi-Equally Informative Subset Selection (W-QEISS), which features a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The preferred variable subset is selected among the efficient solutions and used to formulate the final index according to alternative model structures. We apply FRIDA to the case study of the Jucar river basin (Spain), a drought-prone and highly regulated Mediterranean water resource system, where an advanced drought management plan relying on the formulation of an ad hoc state index is used for triggering drought management measures. The state index was constructed empirically with a trial-and-error process begun in the 1980s and finalized in 2007, guided by the experts from the Confederación Hidrográfica del Júcar (CHJ). Our results show that the automated variable selection outcomes align with CHJ's 25-year-long empirical refinement. In addition, the resultant FRIDA index outperforms the official State Index in terms of accuracy in reproducing the target variable and cardinality of the selected inputs set.

Developing the formula for state subsidies for health care in Finland.

PubMed

Häkkinen, Unto; Järvelin, Jutta

2004-01-01

The aim was to generate a research-based proposal for a new subsidy formula for municipal healthcare services in Finland. Small-area data on potential need variables, supply of and access to services, and age-, sex- and case-mix-standardised service utilisation per capita were used. Utilisation was regressed in order to identify need variables and the cost weights for the selected need variables were subsequently derived using various multilevel models and structural equation methods. The variables selected for the subsidy formula were as follows: age- and sex-standardised mortality (age under 65 years) and income for outpatient primary health services; age- and sex-standardised mortality (all ages) and index of overcrowded housing for elderly care and long-term inpatient care; index of disability pensions for those aged 15-55 years and migration for specialised non-psychiatric care; and index of living alone and income for psychiatric care. Decisions on the amount of state subsidies can be divided into three stages, of which the first two are mainly political and the third is based on the results of this study.

Is There a Hole in the Bucket? Understanding SCHIP Retention. Assessing the New Federalism: An Urban Institute Program To Assess Changing Social Policies. Occasional Paper.

ERIC Educational Resources Information Center

Hill, Ian; Lutzky, Amy Westpfahl

This study examined states efforts to retain children in their State Childrens Health Insurance Program (SCHIP). Data were obtained during spring and summer of 2000 through telephone interviews with state program officials from eight states selected based on a variety of demographic and programmatic variables; the states were Alabama, California,…

Mating tactics determine patterns of condition dependence in a dimorphic horned beetle.

PubMed

Knell, Robert J; Simmons, Leigh W

2010-08-07

The persistence of genetic variability in performance traits such as strength is surprising given the directional selection that such traits experience, which should cause the fixation of the best genetic variants. One possible explanation is 'genic capture' which is usually considered as a candidate mechanism for the maintenance of high genetic variability in sexual signalling traits. This states that if a trait is 'condition dependent', with expression being strongly influenced by the bearer's overall viability, then genetic variability can be maintained via mutation-selection balance. Using a species of dimorphic beetle with males that gain matings either by fighting or by 'sneaking', we tested the prediction of strong condition dependence for strength, walking speed and testes mass. Strength was strongly condition dependent only in those beetles that fight for access to females. Walking speed, with less of an obvious selective advantage, showed no condition dependence, and testes mass was more condition dependent in sneaks, which engage in higher levels of sperm competition. Within a species, therefore, condition dependent expression varies between morphs, and corresponds to the specific selection pressures experienced by that morph. These results support genic capture as a general explanation for the maintenance of genetic variability in traits under directional selection.

Variable Selection for Regression Models of Percentile Flows

NASA Astrophysics Data System (ADS)

Fouad, G.

2017-12-01

Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high degree of multicollinearity, possibly illustrating the co-evolution of climatic and physiographic conditions. Given the ineffectiveness of many variables used here, future work should develop new variables that target specific processes associated with percentile flows.

ESTIMATED EFFECTIVE CHIMNEY HEIGHTS BASED ON RAWINSONDE OBSERVATIONS AT SELECTED SITES IN THE UNITED STATES

EPA Science Inventory

The plume rise equations of Briggs (1975) for variable vertical profiles of temperature and wind speed are described and applied for hypothetical small and very large chimneys at five NWS rawinsonde stations across the United States. From other available data additional informati...

Selection of single chain variable fragments (scFv) against Xylella fastidiosa subsp. pauca by phage display

USDA-ARS?s Scientific Manuscript database

Xylella fastidiosa is a gram-negative member of the gamma proteobacteria. Xylella fastidiosa subsp pauca causes citrus variegated chlorosis in Brazil and enjoys ‘select agent’ status in the United States. Antibody based detection assays are commercially available for Xylella fastidiosa, and are ef...

The Relationship between Attitudes toward Censorship and Selected Academic Variables.

ERIC Educational Resources Information Center

Dwyer, Edward J.; Summy, Mary K.

1989-01-01

To examine characteristics of subjects relative to their attitudes toward censorship, a study surveyed 98 college students selected from students in a public university in the southeastern United States. A 24-item Likert-style censorship scale was used to measure attitudes toward censorship. Strong agreement with affirmative items would suggest…

Psychosocial Variables as Predictors of School Adjustment of Gifted Students with Learning Disabilities in Nigeria

ERIC Educational Resources Information Center

Fakolade, O. A.; Oyedokun, S. O.

2015-01-01

The paper considered several psychosocial variables as predictors of school adjustment of 40 gifted students with learning disabilities in Junior Secondary School in Ikenne Local Government Council Area of Ogun State, Nigeria. Purposeful random sampling was employed to select four schools from 13 junior secondary schools in the area, six…

Continuous-variable quantum computing in optical time-frequency modes using quantum memories.

PubMed

Humphreys, Peter C; Kolthammer, W Steven; Nunn, Joshua; Barbieri, Marco; Datta, Animesh; Walmsley, Ian A

2014-09-26

We develop a scheme for time-frequency encoded continuous-variable cluster-state quantum computing using quantum memories. In particular, we propose a method to produce, manipulate, and measure two-dimensional cluster states in a single spatial mode by exploiting the intrinsic time-frequency selectivity of Raman quantum memories. Time-frequency encoding enables the scheme to be extremely compact, requiring a number of memories that are a linear function of only the number of different frequencies in which the computational state is encoded, independent of its temporal duration. We therefore show that quantum memories can be a powerful component for scalable photonic quantum information processing architectures.

Quantitative Analysis of Variables Affecting Nursing Program Completion at Arizona State University

ERIC Educational Resources Information Center

Herrera, Cheryl

2013-01-01

This study is designed to understand the patterns of selection, preparation, retention and graduation of undergraduate pre-licensure clinical nursing students in the College of Nursing and Health Innovation at Arizona State University enrolled in 2007 and 2008. The resulting patterns may guide policy decision making regarding future cohorts in…

Association of Selected Risk Factors with Variation in Child and Adolescent Firearm Mortality by State

ERIC Educational Resources Information Center

Murnan, Judy; Dake, Joseph A.; Price, James H.

2004-01-01

This study examined relationships between variation in child and adolescent firearm mortality by state and the following variables: childhood poverty rate, percent single parent families, percent population that is African American, percent population that is Hispanic. percent students carrying a gun, percent students carrying a weapon, percent…

Predictors of Placement Stability at the State Level: The Use of Logistic Regression to Inform Practice

ERIC Educational Resources Information Center

Courtney, Jon R.; Prophet, Retta

2011-01-01

Placement instability is often associated with a number of negative outcomes for children. To gain state level contextual knowledge of factors associated with placement stability/instability, logistic regression was applied to selected variables from the New Mexico Adoption and Foster Care Administrative Reporting System dataset. Predictors…

Counseling Racial and Ethnic Minorities in the United States.

ERIC Educational Resources Information Center

Vontress, Clemmont

The purpose of this paper is to discuss in brief six racial and ethnic minority groups in the United States, in order to demonstrate how selected cultural variables may intrude in the counseling relationship. American Indians present such problems as language difficulties, taciturnity, and suspiciousness. In working with Americans of African…

Variable Selection Strategies for Small-area Estimation Using FIA Plots and Remotely Sensed Data

Treesearch

Andrew Lister; Rachel Riemann; James Westfall; Mike Hoppus

2005-01-01

The USDA Forest Service's Forest Inventory and Analysis (FIA) unit maintains a network of tens of thousands of georeferenced forest inventory plots distributed across the United States. Data collected on these plots include direct measurements of tree diameter and height and other variables. We present a technique by which FIA plot data and coregistered...

Deprived Urban Youth: An Economic and Cross-Cultural Analysis of the United States, Colombia and Peru.

ERIC Educational Resources Information Center

Walter, John P.; And Others

This book analyzes in detail the various economic and socioeconomic factors that affect deprived urban youth in five cultures. Various possible hypotheses and variables that influence youth to enroll in school, participate in the labor force, or remain inactive are measured. Among the selected variables that are examined are: enrollment aspects;…

State funding for local public health: observations from six case studies.

PubMed

Potter, Margaret A; Fitzpatrick, Tiffany

2007-01-01

The purpose of this study is to describe state funding of local public health within the context of state public health system types. These types are based on administrative relationships, legal structures, and relative proportion of state funding in local public health budgets. We selected six states representing various types and geographic regions. A case study for each state summarized available information and was validated by state public health officials. An analysis of the case studies reveals that the variability of state public health systems--even within a given type--is matched by variability in approaches to funding local public health. Nevertheless, some meaningful associations appear. For example, higher proportions of state funding occur along with higher levels of state oversight and the existence of local service mandates in state law. These associations suggest topics for future research on public health financing in relation to local accountability, local input to state priority-setting, mandated local services, and the absence of state funds for public health services in some local jurisdictions.

The intraday variability in the radio-selected and X-ray-selected BL Lacertae objects

NASA Astrophysics Data System (ADS)

Bai, J. M.; Xie, G. Z.; Li, K. H.; Zhang, X.; Liu, W. W.

1998-10-01

Seven BL Lac objects have been photometrically observed in an effort to study the difference of optical intraday variability between the radio-selected BL Lac objects (RBLs) and X-ray-selected BL Lac objects (XBLs). The objects we observed are selected arbitrarily. They are four RBLs, PKS 0735+178, PKS 0754+101, OJ 287 and BL Lac, and three XBLs, H 0323+022, H 0548-322 and H 2154-304. During the observation all of them exhibited microvariation, and H 0323+022 and H 0548-322 sometimes showed brightness oscillation. PKS 0735+178 and BL Lac were in their faint states and not very active. It seems that RBLs do not show microvariability more frequently than XBLs. Table 2 is only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5)

Quantum key distribution using continuous-variable non-Gaussian states

NASA Astrophysics Data System (ADS)

Borelli, L. F. M.; Aguiar, L. S.; Roversi, J. A.; Vidiella-Barranco, A.

2016-02-01

In this work, we present a quantum key distribution protocol using continuous-variable non-Gaussian states, homodyne detection and post-selection. The employed signal states are the photon added then subtracted coherent states (PASCS) in which one photon is added and subsequently one photon is subtracted from the field. We analyze the performance of our protocol, compared with a coherent state-based protocol, for two different attacks that could be carried out by the eavesdropper (Eve). We calculate the secret key rate transmission in a lossy line for a superior channel (beam-splitter) attack, and we show that we may increase the secret key generation rate by using the non-Gaussian PASCS rather than coherent states. We also consider the simultaneous quadrature measurement (intercept-resend) attack, and we show that the efficiency of Eve's attack is substantially reduced if PASCS are used as signal states.

State observer for synchronous motors

DOEpatents

Lang, Jeffrey H.

1994-03-22

A state observer driven by measurements of phase voltages and currents for estimating the angular orientation of a rotor of a synchronous motor such as a variable reluctance motor (VRM). Phase voltages and currents are detected and serve as inputs to a state observer. The state observer includes a mathematical model of the electromechanical operation of the synchronous motor. The characteristics of the state observer are selected so that the observer estimates converge to the actual rotor angular orientation and velocity, winding phase flux linkages or currents.

Modulation Depth Estimation and Variable Selection in State-Space Models for Neural Interfaces

PubMed Central

Hochberg, Leigh R.; Donoghue, John P.; Brown, Emery N.

2015-01-01

Rapid developments in neural interface technology are making it possible to record increasingly large signal sets of neural activity. Various factors such as asymmetrical information distribution and across-channel redundancy may, however, limit the benefit of high-dimensional signal sets, and the increased computational complexity may not yield corresponding improvement in system performance. High-dimensional system models may also lead to overfitting and lack of generalizability. To address these issues, we present a generalized modulation depth measure using the state-space framework that quantifies the tuning of a neural signal channel to relevant behavioral covariates. For a dynamical system, we develop computationally efficient procedures for estimating modulation depth from multivariate data. We show that this measure can be used to rank neural signals and select an optimal channel subset for inclusion in the neural decoding algorithm. We present a scheme for choosing the optimal subset based on model order selection criteria. We apply this method to neuronal ensemble spike-rate decoding in neural interfaces, using our framework to relate motor cortical activity with intended movement kinematics. With offline analysis of intracortical motor imagery data obtained from individuals with tetraplegia using the BrainGate neural interface, we demonstrate that our variable selection scheme is useful for identifying and ranking the most information-rich neural signals. We demonstrate that our approach offers several orders of magnitude lower complexity but virtually identical decoding performance compared to greedy search and other selection schemes. Our statistical analysis shows that the modulation depth of human motor cortical single-unit signals is well characterized by the generalized Pareto distribution. Our variable selection scheme has wide applicability in problems involving multisensor signal modeling and estimation in biomedical engineering systems. PMID:25265627

Personality Variables as Correlates of Marital Adjustment among Married Persons in Delta State of Nigeria

ERIC Educational Resources Information Center

Ebenuwa-Okoh, E. E.

2008-01-01

This study examined the extent to which emotional expression, communication flow, financial management and work involvement predict marital adjustment among married persons in Delta State, Nigeria. One question was raised and one hypothesis was formulated to guide the study. 2561 married persons were selected through the use of purposive sampling…

A Design for a Multi-Use Object Editor with Connections

DTIC Science & Technology

1991-10-01

Variables of Class Select 14 3.6.2 Methods of Class Select 14 3.6.3 Application States 14 3.7 Class Clipboard 15 3.8 Class Crestore 15 3.9 Conclusions 15 4...this is not directly related to cutting and past- ing between applications. 3.8 CLASS CRESTORE Class crestore holds a connection until all the

A Comparative Study of the Patterns of Acculturation of Selected Puerto Rican, Protestant and Roman Catholic Families in an Urban Metropolitan Area.

ERIC Educational Resources Information Center

Lennon, John J.

This examines the existing state of acculturation of Puerto Rican migrants living in Chicago and the extent to which religion affects their acculturation. Six variables (age, prior urban or rural residence, sex, recency of migration, religion, and religiousness) and the relationship of these variables to acculturation are investigated. The sample…

Faithful entanglement transference from qubits to continuous variable systems

NASA Astrophysics Data System (ADS)

Blanco, P.; Mundarain, D.

2011-05-01

In this work, we study the transference of entanglement between atomic qubits and the fields of two separate optical cavities. We show that it is possible to transfer all the entanglement of two maximal entangled qubits to the fields of the cavities without post-selection. Initially, the qubit system is in a maximal entangled state and the cavities are in a pure separable state with each cavity in a coherent state. For high excitation levels in the coherent fields, at some characteristic time T, the state of the qubit system becomes separable and at this time all the entanglement is deposited on the mono-modal fields of the cavities. We also consider retrieval of entanglement and an alternative protocol using post-selection.

Identifying Slow Molecular Motions in Complex Chemical Reactions.

PubMed

Piccini, GiovanniMaria; Polino, Daniela; Parrinello, Michele

2017-09-07

We have studied the cyclization reaction of deprotonated 4-chloro-1-butanethiol to tetrahydrothiophene by means of well-tempered metadynamics. To properly select the collective variables, we used the recently proposed variational approach to conformational dynamics within the framework of metadyanmics. This allowed us to select the appropriate linear combinations from a set of collective variables representing the slow degrees of freedom that best describe the slow modes of the reaction. We performed our calculations at three different temperatures, namely, 300, 350, and 400 K. We show that the choice of such collective variables allows one to easily interpret the complex free-energy surface of such a reaction by univocal identification of the conformers belonging to reactants and product states playing a fundamental role in the reaction mechanism.

Utilizing multiple state variables to improve the dynamic range of analog switching in a memristor

NASA Astrophysics Data System (ADS)

Jeong, YeonJoo; Kim, Sungho; Lu, Wei D.

2015-10-01

Memristors and memristive systems have been extensively studied for data storage and computing applications such as neuromorphic systems. To act as synapses in neuromorphic systems, the memristor needs to exhibit analog resistive switching (RS) behavior with incremental conductance change. In this study, we show that the dynamic range of the analog RS behavior can be significantly enhanced in a tantalum-oxide-based memristor. By controlling different state variables enabled by different physical effects during the RS process, the gradual filament expansion stage can be selectively enhanced without strongly affecting the abrupt filament length growth stage. Detailed physics-based modeling further verified the observed experimental effects and revealed the roles of oxygen vacancy drift and diffusion processes, and how the diffusion process can be selectively enhanced during the filament expansion stage. These findings lead to more desirable and reliable memristor behaviors for analog computing applications. Additionally, the ability to selectively control different internal physical processes demonstrated in the current study provides guidance for continued device optimization of memristor devices in general.

Some Correlates of Risky Sexual Behavior among Secondary School Adolescents in Ogun State, Nigeria

ERIC Educational Resources Information Center

Adeyemo, D. A.; Williams, T. M.

2009-01-01

The purpose of the study is to examine factors associated with risky sexual behaviors among secondary school adolescents in Ogun State, Nigeria. Two hundred and fifty adolescents randomly selected from three schools participated in the study. The ages of the participants ranged from 13 to 18 years. Both the independent and dependent variables were…

Detection of drug active ingredients by chemometric processing of solid-state NMR spectrometry data -- the case of acetaminophen.

PubMed

Paradowska, Katarzyna; Jamróz, Marta Katarzyna; Kobyłka, Mariola; Gowin, Ewelina; Maczka, Paulina; Skibiński, Robert; Komsta, Łukasz

2012-01-01

This paper presents a preliminary study in building discriminant models from solid-state NMR spectrometry data to detect the presence of acetaminophen in over-the-counter pharmaceutical formulations. The dataset, containing 11 spectra of pure substances and 21 spectra of various formulations, was processed by partial least squares discriminant analysis (PLS-DA). The model found coped with the discrimination, and its quality parameters were acceptable. It was found that standard normal variate preprocessing had almost no influence on unsupervised investigation of the dataset. The influence of variable selection with the uninformative variable elimination by PLS method was studied, reducing the dataset from 7601 variables to around 300 informative variables, but not improving the model performance. The results showed the possibility to construct well-working PLS-DA models from such small datasets without a full experimental design.

Boosting multi-state models.

PubMed

Reulen, Holger; Kneib, Thomas

2016-04-01

One important goal in multi-state modelling is to explore information about conditional transition-type-specific hazard rate functions by estimating influencing effects of explanatory variables. This may be performed using single transition-type-specific models if these covariate effects are assumed to be different across transition-types. To investigate whether this assumption holds or whether one of the effects is equal across several transition-types (cross-transition-type effect), a combined model has to be applied, for instance with the use of a stratified partial likelihood formulation. Here, prior knowledge about the underlying covariate effect mechanisms is often sparse, especially about ineffectivenesses of transition-type-specific or cross-transition-type effects. As a consequence, data-driven variable selection is an important task: a large number of estimable effects has to be taken into account if joint modelling of all transition-types is performed. A related but subsequent task is model choice: is an effect satisfactory estimated assuming linearity, or is the true underlying nature strongly deviating from linearity? This article introduces component-wise Functional Gradient Descent Boosting (short boosting) for multi-state models, an approach performing unsupervised variable selection and model choice simultaneously within a single estimation run. We demonstrate that features and advantages in the application of boosting introduced and illustrated in classical regression scenarios remain present in the transfer to multi-state models. As a consequence, boosting provides an effective means to answer questions about ineffectiveness and non-linearity of single transition-type-specific or cross-transition-type effects.

Online Estimation of Model Parameters of Lithium-Ion Battery Using the Cubature Kalman Filter

NASA Astrophysics Data System (ADS)

Tian, Yong; Yan, Rusheng; Tian, Jindong; Zhou, Shijie; Hu, Chao

2017-11-01

Online estimation of state variables, including state-of-charge (SOC), state-of-energy (SOE) and state-of-health (SOH) is greatly crucial for the operation safety of lithium-ion battery. In order to improve estimation accuracy of these state variables, a precise battery model needs to be established. As the lithium-ion battery is a nonlinear time-varying system, the model parameters significantly vary with many factors, such as ambient temperature, discharge rate and depth of discharge, etc. This paper presents an online estimation method of model parameters for lithium-ion battery based on the cubature Kalman filter. The commonly used first-order resistor-capacitor equivalent circuit model is selected as the battery model, based on which the model parameters are estimated online. Experimental results show that the presented method can accurately track the parameters variation at different scenarios.

Reality of delusion: migrant perception of levels of living and opportunity in Venezuela, 1961-1971.

PubMed

Eastwood, D A

1983-07-01

To facilitate comparison of how well migrant perceptions may have accorded with reality and of the effects of that migration between 1961-71 may have had on relative regional development in Venezuela, a composite index based on state census data must be constructed by which the country's overall levels of living and social well being can be examined. The index constructed was loosely based on a range of variables suggested by Knox, but with the specific selected variables restricted by those data available in the Venezuelan censuses and other institutional reports. 20 variables were selected. Using these variables, a composite index of levels of living and social well being was constructed. The resultant index (S scores) for each state in 1971 appear in a table and a figure. These S scores demonstrated the relatively higher levels of living in the northern core area around Caracas, with S scores of over 200 in the Federal District and Miranda State. Ripple effects from the northern core also produced high scores in Aragua and Caraboba states. Secondary centers of relative prosperity were Zulia in the west and Bolivar in the east. The traditional Andean population centers in Tachira and Merida also scored positively. In contrast low S scores were found in a central belt of rural states. Lowest scores of all were in the states of Apure and Barinas, isolated on the southern margins of the central belt. Overall, the 1971 S scores decreased as distance from Caracas increased and clearly illustrated Venezuela's acute core/periphery imbalance. Despite the very substantial migration throughout the 1961-71 period, with only minor exceptions, the level of living pattern was essentially static, as a comparison of 1961 and 1971 reveals. Only the states of Bolivar (because of Guayanese industrial growth) and Nueva Esparata (because of its designation as a free port) showed significant 1961-71 improvement in state rankings; only Cojedes and Falcon (for unknown reasons) had significant decline. S scores clearly remained higher in the less rural states. In general, the majority of migration was toward those states with the higher S scores, and the high S scores correlated strongly and positively with net 1961-71 migration. The broad migrant perception of where potentially better overall conditions were likely to be found appeared to be largely accurate. When this overall picture was reduced to specific variables, the reality of migrant perception became less clear. Migrants tended to move not only to where wages were higher but also to where unemployment was higher.

Uniting statistical and individual-based approaches for animal movement modelling.

PubMed

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

Uniting Statistical and Individual-Based Approaches for Animal Movement Modelling

PubMed Central

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems. PMID:24979047

Determination of variables in the prediction of strontium distribution coefficients for selected sediments

USGS Publications Warehouse

Pace, M.N.; Rosentreter, J.J.; Bartholomay, R.C.

2001-01-01

Idaho State University and the US Geological Survey, in cooperation with the US Department of Energy, conducted a study to determine and evaluate strontium distribution coefficients (Kds) of subsurface materials at the Idaho National Engineering and Environmental Laboratory (INEEL). The Kds were determined to aid in assessing the variability of strontium Kds and their effects on chemical transport of strontium-90 in the Snake River Plain aquifer system. Data from batch experiments done to determine strontium Kds of five sediment-infill samples and six standard reference material samples were analyzed by using multiple linear regression analysis and the stepwise variable-selection method in the statistical program, Statistical Product and Service Solutions, to derive an equation of variables that can be used to predict strontium Kds of sediment-infill samples. The sediment-infill samples were from basalt vesicles and fractures from a selected core at the INEEL; strontium Kds ranged from ???201 to 356 ml g-1. The standard material samples consisted of clay minerals and calcite. The statistical analyses of the batch-experiment results showed that the amount of strontium in the initial solution, the amount of manganese oxide in the sample material, and the amount of potassium in the initial solution are the most important variables in predicting strontium Kds of sediment-infill samples.

Optimal information networks: Application for data-driven integrated health in populations

PubMed Central

Servadio, Joseph L.; Convertino, Matteo

2018-01-01

Development of composite indicators for integrated health in populations typically relies on a priori assumptions rather than model-free, data-driven evidence. Traditional variable selection processes tend not to consider relatedness and redundancy among variables, instead considering only individual correlations. In addition, a unified method for assessing integrated health statuses of populations is lacking, making systematic comparison among populations impossible. We propose the use of maximum entropy networks (MENets) that use transfer entropy to assess interrelatedness among selected variables considered for inclusion in a composite indicator. We also define optimal information networks (OINs) that are scale-invariant MENets, which use the information in constructed networks for optimal decision-making. Health outcome data from multiple cities in the United States are applied to this method to create a systemic health indicator, representing integrated health in a city. PMID:29423440

What Makes a Difference during the Last Two Years of High School: An Overview of Studies Based on High School and Beyond Data.

ERIC Educational Resources Information Center

Marsh, Herbert W.

Variables that influence growth and change in educational outcomes in the last 2 years of high school were studied using data from the High School and Beyond (HSB) study. The HSB study provided a database of thousands of variables for about 30 students from each of 1,000 randomly selected high schools in the United States in their sophomore and…

Continuous-variable measurement-device-independent quantum key distribution with virtual photon subtraction

NASA Astrophysics Data System (ADS)

Zhao, Yijia; Zhang, Yichen; Xu, Bingjie; Yu, Song; Guo, Hong

2018-04-01

The method of improving the performance of continuous-variable quantum key distribution protocols by postselection has been recently proposed and verified. In continuous-variable measurement-device-independent quantum key distribution (CV-MDI QKD) protocols, the measurement results are obtained from untrusted third party Charlie. There is still not an effective method of improving CV-MDI QKD by the postselection with untrusted measurement. We propose a method to improve the performance of coherent-state CV-MDI QKD protocol by virtual photon subtraction via non-Gaussian postselection. The non-Gaussian postselection of transmitted data is equivalent to an ideal photon subtraction on the two-mode squeezed vacuum state, which is favorable to enhance the performance of CV-MDI QKD. In CV-MDI QKD protocol with non-Gaussian postselection, two users select their own data independently. We demonstrate that the optimal performance of the renovated CV-MDI QKD protocol is obtained with the transmitted data only selected by Alice. By setting appropriate parameters of the virtual photon subtraction, the secret key rate and tolerable excess noise are both improved at long transmission distance. The method provides an effective optimization scheme for the application of CV-MDI QKD protocols.

Evolution of dispersal in spatially and temporally variable environments: The importance of life cycles.

PubMed

Massol, François; Débarre, Florence

2015-07-01

Spatiotemporal variability of the environment is bound to affect the evolution of dispersal, and yet model predictions strongly differ on this particular effect. Recent studies on the evolution of local adaptation have shown that the life cycle chosen to model the selective effects of spatiotemporal variability of the environment is a critical factor determining evolutionary outcomes. Here, we investigate the effect of the order of events in the life cycle on the evolution of unconditional dispersal in a spatially heterogeneous, temporally varying landscape. Our results show that the occurrence of intermediate singular strategies and disruptive selection are conditioned by the temporal autocorrelation of the environment and by the life cycle. Life cycles with dispersal of adults versus dispersal of juveniles, local versus global density regulation, give radically different evolutionary outcomes that include selection for total philopatry, evolutionary bistability, selection for intermediate stable states, and evolutionary branching points. Our results highlight the importance of accounting for life-cycle specifics when predicting the effects of the environment on evolutionarily selected trait values, such as dispersal, as well as the need to check the robustness of model conclusions against modifications of the life cycle. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

The relationship between employer health insurance characteristics and the provision of employee assistance programs.

PubMed

Zarkin, G A; Garfinkel, S A

1994-01-01

Workplace drug and alcohol abuse imposes substantial costs on employers. In response, employers have implemented a variety of programs to decrease substance abuse in the workplace, including drug testing, health and wellness programs, and employee assistance programs (EAPs). This paper focuses on the relationship between enterprises' organizational and health insurance characteristics and the firms' decisions to provide EAPs. Using data from the 1989 Survey of Health Insurance Plans (SHIP), sponsored by the Health Care Financing Administration (HCFA), we estimated the prevalence of EAPs by selected organizational and health insurance characteristics for those firms that offer health insurance to their workers. In addition, we estimated logistic models of the enterprises' decisions to provide EAPs as functions of the extent of state substance abuse and mental health insurance mandates, state-level demographic variables, and organizational and health insurance characteristics. Our results suggest that state mandates and demographic variables, as well as organizational and health insurance characteristics, are important explanatory variables of enterprises' decisions to provide EAPs.

An engineering economic assessment of whole-house residential wood heating in New York

EPA Science Inventory

Wood devices are being selected increasingly for residential space heating by households in New York State. Motivations for their use include energy independence, mitigating climate change, stimulating local economic development, and reducing exposure to high and variable fuel c...

The role of science self-efficacy, science career efficacy, science career interest, and intentions to enroll in nonrequired science courses in the future selection of science-related careers for high school students

NASA Astrophysics Data System (ADS)

Ballard, Sherri Patrice

1998-12-01

Underrepresentation of non-Asian minority groups and women in science and math related professions has been an area of concern for many years. The purpose of this study was to examine the role of career selection variables for African-American and European-American students on future aspirations of pursuing a science-related career. Other examined variables included gender, academic track and socioeconomic status. A survey was completed by 368 high school students in rural settings in the Southeastern portion of the United States. Gender, race, tracking, and socioeconomic differences in career selection variables and future aspirations of pursuing a science-related career were explored using a 2 x 2 x 2 x 2 MANOVA. Multiple regression was used to examine the predictiveness of career selection variables relative to future career aspirations of pursuing a science-related career. Results indicated that African-Americans reported higher total science career interest, and higher science career efficacy. European-American students reported higher levels of science self-efficacy relative to making a B or better in science courses and solving science-related problems. Also, European-Americans reported higher levels of interest in science-related tasks, a subscale on the science career interest variable. When the effect of gender was examined across the total sample, no differences were found. However, when gender was examined by race, European-American females reported higher levels of science career interest than European-American males. Students from high academic tracking groups reported greater efficacy for completing science-related technical skills. Science career interest was predictive of future career selection for this sample.

General Investigation of Tidal Inlets: Stability of Selected United States Tidal Inlets

DTIC Science & Technology

1991-09-01

characteristics in relation to the variability of the hydr; aulic parameters. An inlet can fall into any of four "stability" classes 48 Orientation Parameter 80...nlot he ~ :Ke(: t 93. If a fairly straight coast with uniform offshore slopes and a regionally homogeneous wave climate is considered, a reasonable...expectation is LhaL the longshore transport quantities and directions are homogeneous. Given a long-term variability in wave climate , a corresponding

Resonance dynamics of DCO (X ˜ '2A ) simulated with the dynamically pruned discrete variable representation (DP-DVR)

NASA Astrophysics Data System (ADS)

Larsson, Henrik R.; Riedel, Jens; Wei, Jie; Temps, Friedrich; Hartke, Bernd

2018-05-01

Selected resonance states of the deuterated formyl radical in the electronic ground state X ˜ '2A are computed using our recently introduced dynamically pruned discrete variable representation [H. R. Larsson, B. Hartke, and D. J. Tannor, J. Chem. Phys. 145, 204108 (2016)]. Their decay and asymptotic distributions are analyzed and, for selected resonances, compared to experimental results obtained by a combination of stimulated emission pumping and velocity-map imaging of the product D atoms. The theoretical results show good agreement with the experimental kinetic energy distributions. The intramolecular vibrational energy redistribution is analyzed and compared with previous results from an effective polyad Hamiltonian. Specifically, we analyzed the part of the wavefunction that remains in the interaction region during the decay. The results from the polyad Hamiltonian could mainly be confirmed. The C=O stretch quantum number is typically conserved, while the D—C=O bend quantum number decreases. Differences are due to strong anharmonic coupling such that all resonances have major contributions from several zero-order states. For some of the resonances, the coupling is so strong that no further zero-order states appear during the dynamics in the interaction region, even after propagating for 300 ps.

Zoonotic importance of canine scabies and dermatophytosis in relation to knowledge level of dog owners.

PubMed

Raval, Heli S; Nayak, J B; Patel, B M; Bhadesiya, C M

2015-06-01

The present study was undertaken to understand the zoonotic importance of canine scabies and dermatophytosis with special reference to the knowledge level of dog owners in urban areas of Gujarat. The study was carried out in randomly selected 120 dog owners of 3 urban cities (viz., Ahmedabad, Anand and Vadodara) of Gujarat state, India. Dog owners (i.e., respondents) were subjected to a detailed interview regarding the zoonotic importance of canine scabies and dermatophytosis in dogs. Ex-post-facto research design was selected because of the independent variables of the selected respondent population for the study. The crucial method used in collecting data was a field survey to generate null hypothesis (Ho1). Available data was subjected to statistical analysis. The three independent variables, viz., extension contact (r=0.522**), mass-media exposure (r=0.205*) and management orientation (r=0.264**) had significant relationship with knowledge of dog owners about zoonotic diseases. Other independent variables, viz., education, experience in dog keeping and housing space were observed to have negative and non-significant relationship with knowledge of dog owners about zoonotic diseases. Extension contact, exposure to extension mass-media, management orientation and innovation proneness among dog owners of 3 urban cities of Gujarat state had significant relationship with knowledge of dog owners on zoonotic aspects of canine scabies and dermatophytosis. Data provided new insights on the present status of zoonotic disease-awareness, which would be an aid to plan preventive measures.

Representativeness-based sampling network design for the State of Alaska

Treesearch

Forrest M. Hoffman; Jitendra Kumar; Richard T. Mills; William W. Hargrove

2013-01-01

Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. A quantitative methodology for stratifying sampling domains, informing site selection,...

Distributed Network and Multiprocessing Minicomputer State-of-the-Art Capabilities.

ERIC Educational Resources Information Center

Theis, Douglas J.

An examination of the capabilities of minicomputers and midicomputers now on the market reveals two basic items which users should evaluate when selecting computers for their own applications: distributed networking systems and multiprocessing architectures. Variables which should be considered in evaluating a distributed networking system…

A family of variable step-size affine projection adaptive filter algorithms using statistics of channel impulse response

NASA Astrophysics Data System (ADS)

Shams Esfand Abadi, Mohammad; AbbasZadeh Arani, Seyed Ali Asghar

2011-12-01

This paper extends the recently introduced variable step-size (VSS) approach to the family of adaptive filter algorithms. This method uses prior knowledge of the channel impulse response statistic. Accordingly, optimal step-size vector is obtained by minimizing the mean-square deviation (MSD). The presented algorithms are the VSS affine projection algorithm (VSS-APA), the VSS selective partial update NLMS (VSS-SPU-NLMS), the VSS-SPU-APA, and the VSS selective regressor APA (VSS-SR-APA). In VSS-SPU adaptive algorithms the filter coefficients are partially updated which reduce the computational complexity. In VSS-SR-APA, the optimal selection of input regressors is performed during the adaptation. The presented algorithms have good convergence speed, low steady state mean square error (MSE), and low computational complexity features. We demonstrate the good performance of the proposed algorithms through several simulations in system identification scenario.

Advanced colorectal neoplasia risk stratification by penalized logistic regression.

PubMed

Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F

2016-08-01

Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.

tICA-Metadynamics: Accelerating Metadynamics by Using Kinetically Selected Collective Variables.

PubMed

M Sultan, Mohammad; Pande, Vijay S

2017-06-13

Metadynamics is a powerful enhanced molecular dynamics sampling method that accelerates simulations by adding history-dependent multidimensional Gaussians along selective collective variables (CVs). In practice, choosing a small number of slow CVs remains challenging due to the inherent high dimensionality of biophysical systems. Here we show that time-structure based independent component analysis (tICA), a recent advance in Markov state model literature, can be used to identify a set of variationally optimal slow coordinates for use as CVs for Metadynamics. We show that linear and nonlinear tICA-Metadynamics can complement existing MD studies by explicitly sampling the system's slowest modes and can even drive transitions along the slowest modes even when no such transitions are observed in unbiased simulations.

A 24 km fiber-based discretely signaled continuous variable quantum key distribution system.

PubMed

Dinh Xuan, Quyen; Zhang, Zheshen; Voss, Paul L

2009-12-21

We report a continuous variable key distribution system that achieves a final secure key rate of 3.45 kilobits/s over a distance of 24.2 km of optical fiber. The protocol uses discrete signaling and post-selection to improve reconciliation speed and quantifies security by means of quantum state tomography. Polarization multiplexing and a frequency translation scheme permit transmission of a continuous wave local oscillator and suppression of noise from guided acoustic wave Brillouin scattering by more than 27 dB.

Deterministic quantum teleportation of photonic quantum bits by a hybrid technique.

PubMed

Takeda, Shuntaro; Mizuta, Takahiro; Fuwa, Maria; van Loock, Peter; Furusawa, Akira

2013-08-15

Quantum teleportation allows for the transfer of arbitrary unknown quantum states from a sender to a spatially distant receiver, provided that the two parties share an entangled state and can communicate classically. It is the essence of many sophisticated protocols for quantum communication and computation. Photons are an optimal choice for carrying information in the form of 'flying qubits', but the teleportation of photonic quantum bits (qubits) has been limited by experimental inefficiencies and restrictions. Main disadvantages include the fundamentally probabilistic nature of linear-optics Bell measurements, as well as the need either to destroy the teleported qubit or attenuate the input qubit when the detectors do not resolve photon numbers. Here we experimentally realize fully deterministic quantum teleportation of photonic qubits without post-selection. The key step is to make use of a hybrid technique involving continuous-variable teleportation of a discrete-variable, photonic qubit. When the receiver's feedforward gain is optimally tuned, the continuous-variable teleporter acts as a pure loss channel, and the input dual-rail-encoded qubit, based on a single photon, represents a quantum error detection code against photon loss and hence remains completely intact for most teleportation events. This allows for a faithful qubit transfer even with imperfect continuous-variable entangled states: for four qubits the overall transfer fidelities range from 0.79 to 0.82 and all of them exceed the classical limit of teleportation. Furthermore, even for a relatively low level of the entanglement, qubits are teleported much more efficiently than in previous experiments, albeit post-selectively (taking into account only the qubit subspaces), and with a fidelity comparable to the previously reported values.

Development of design guidelines for proper selection of graded aggregate base in Maryland state highways : [research summary].

DOT National Transportation Integrated Search

2015-01-01

Millions of tons of graded aggregate base (GAB) materials are used in construction of : highway base layers in Maryland due to their satisfactory mechanical properties. The : fines content of a GAB material is highly variable and is often related to ...

Instructional Objectives, Learner Personality and Prediction of Academic Achievement.

ERIC Educational Resources Information Center

Kelley, Russell Victor, Jr.

This study investigated three questions: the relationship between the use of stated instructional objectives and achievement in audio-tutorial (A-T) instruction, the relationship of learner personality and achievement under conditions of A-T, as well as determining the power of selected batteries of intellective and personality variables to…

Unemployment and mortality among Finnish men, 1981-5.

PubMed Central

Martikainen, P T

1990-01-01

OBJECTIVE--To ascertain whether, after controlling for several relevant background variables simultaneously, unemployment is related to mortality and to assess whether this relation is causal or whether unhealthy people are more likely to become unemployed. DESIGN--Prospective study of mortality in Finland during 1981-5 based on 1980 census data on 30-54 year old wage earner men and with particular attention to unemployment in the year before the census. SETTING--Research project at the University of Helsinki. SUBJECTS--All wage earner men in Finland aged 30-54 at the 1980 census. MAIN OUTCOME MEASURES--Causes of death during 1981-5 and duration of unemployment in the year before the census. Background variables controlled for were age, socioeconomic state, marital state, and health. The data were analysed by log linear regression models. RESULTS--During the study period 1981-5, which covered almost 2.7 million person years, there were 9810 deaths. After controlling for all background variables relative total mortality among unemployed versus employed men was 1.93 (95% confidence interval 1.82 to 2.05). The excess mortality was highest in accidental and violent causes of death (relative mortality 2.51; 95% confidence interval 2.28 to 2.76). For circulatory diseases the relative death rate was 1.54 (95% confidence interval 1.40 to 1.70), but among neoplasms only lung cancer was associated with excess mortality. Selection for unemployment based on age, socioeconomic state, and marital state was evident but no such selection was detected based on health. Effects of unemployment on mortality were more pronounced with increasing duration of unemployment. CONCLUSIONS--The relative excess mortality of unemployed men in Finland cannot fully be explained by demographic, social, and health variables preceding unemployment. Unemployment therefore seems to have an independent causal effect on male mortality. Further studies are needed to elucidate the mechanisms between unemployment and mortality. PMID:2282395

From the Digital Divide to Digital Inequality: A Secondary Research in the European Union

NASA Astrophysics Data System (ADS)

Stiakakis, Emmanouil; Kariotellis, Pavlos; Vlachopoulou, Maria

The digital divide is nowadays evolving to digital inequality, i.e., the socio-economic disparities inside the 'online population'. This paper examines two main dimensions of the digital inequality, namely 'skills' and 'autonomy' of Internet users. The level of formal education was selected as a representative variable of the skill dimension, as well as the density of population in different geographical areas as a representative variable of the autonomy dimension. The research was focused on the member states of the European Union (EU). The data, provided by Eurostat, included the daily use of computers for the last three months and the average use of the Internet at least once per week. The findings state that the EU already faces the problem of digital inequality to an extended rate, since there are significant disparities among the European countries with regard to the aforementioned variables.

Influence of precipitation and crop germination on resource selection by mule deer (Odocoileus hemionus) in southwest Colorado

USGS Publications Warehouse

Carrollo, Emily M.; Johnson, Heather E.; Fischer, Justin W.; Hammond, Matthew; Dorsey, Patricia D.; Anderson, Charles; Vercauteren, Kurt C.; Walter, W. David

2017-01-01

Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km2, and for two summer seasons that ranged between 5.51 and 6.24 km2. Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.

Influence of Precipitation and Crop Germination on Resource Selection by Mule Deer (Odocoileus hemionus) in Southwest Colorado.

PubMed

Carrollo, Emily M; Johnson, Heather E; Fischer, Justin W; Hammond, Matthew; Dorsey, Patricia D; Anderson, Charles; Vercauteren, Kurt C; Walter, W David

2017-11-09

Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km 2 , and for two summer seasons that ranged between 5.51 and 6.24 km 2 . Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.

Empirical Assessment of Spatial Prediction Methods for Location Cost Adjustment Factors

PubMed Central

Migliaccio, Giovanni C.; Guindani, Michele; D'Incognito, Maria; Zhang, Linlin

2014-01-01

In the feasibility stage, the correct prediction of construction costs ensures that budget requirements are met from the start of a project's lifecycle. A very common approach for performing quick-order-of-magnitude estimates is based on using Location Cost Adjustment Factors (LCAFs) that compute historically based costs by project location. Nowadays, numerous LCAF datasets are commercially available in North America, but, obviously, they do not include all locations. Hence, LCAFs for un-sampled locations need to be inferred through spatial interpolation or prediction methods. Currently, practitioners tend to select the value for a location using only one variable, namely the nearest linear-distance between two sites. However, construction costs could be affected by socio-economic variables as suggested by macroeconomic theories. Using a commonly used set of LCAFs, the City Cost Indexes (CCI) by RSMeans, and the socio-economic variables included in the ESRI Community Sourcebook, this article provides several contributions to the body of knowledge. First, the accuracy of various spatial prediction methods in estimating LCAF values for un-sampled locations was evaluated and assessed in respect to spatial interpolation methods. Two Regression-based prediction models were selected, a Global Regression Analysis and a Geographically-weighted regression analysis (GWR). Once these models were compared against interpolation methods, the results showed that GWR is the most appropriate way to model CCI as a function of multiple covariates. The outcome of GWR, for each covariate, was studied for all the 48 states in the contiguous US. As a direct consequence of spatial non-stationarity, it was possible to discuss the influence of each single covariate differently from state to state. In addition, the article includes a first attempt to determine if the observed variability in cost index values could be, at least partially explained by independent socio-economic variables. PMID:25018582

Double Photoionization of excited Lithium and Beryllium

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

Yip, Frank L.; McCurdy, C. William; Rescigno, Thomas N.

2010-05-20

We present total, energy-sharing and triple differential cross sections for one-photon, double ionization of lithium and beryllium starting from aligned, excited P states. We employ a recently developed hybrid atomic orbital/ numerical grid method based on the finite-element discrete-variable representation and exterior complex scaling. Comparisons with calculated results for the ground-state atoms, as well as analogous results for ground-state and excited helium, serve to highlight important selection rules and show some interesting effects that relate to differences between inter- and intra-shell electron correlation.

Power politics: National energy strategies of the nuclear newly independent states of Armenia, Lithuania and Ukraine

NASA Astrophysics Data System (ADS)

Sabonis-Chafee, Theresa Marie

The successor states of Armenia, Lithuania and Ukraine arrived at independence facing extraordinary challenges in their energy sectors. Each state was a net importer, heavily dependent on cheap energy supplies, mostly from Russia. Each state also inherited a nuclear power complex over which it had not previously exercised full control. In the time period 1991--1996, each state attempted to impose coherence on the energy sector, selecting a new course for the pieces it had inherited from a much larger, highly integrated energy structure. Each state attempted to craft national energy policies in the midst of severe supply shocks and price shocks. Each state developed institutions to govern its nuclear power sector. The states' challenges were made even greater by the fact that they had few political or economic structures necessary for energy management, and sought to create those structures at the same time. This dissertation is a systematic, non-quantitative examination of how each state's energy policies developed during the 1991--1996 time period. The theoretical premise of the analysis (drawn from Statist realism) is that systemic variables---regional climate and energy vulnerability---provide the best explanations for the resulting energy policy decisions. The dependent variable is defined as creation and reform of energy institutions. The independent variables include domestic climate, regional climate, energy vulnerability and transnational assistance. All three states adopted rhetoric and legislation declaring energy a strategic sector. The evidence suggests that two of the states, Armenia and Lithuania, which faced tense regional climates and high levels of energy vulnerability, succeeded in actually treating energy strategically, approaching energy as a matter of national security or "high politics." The third state, Ukraine, failed to do so. The evidence presented suggests that the systemic variables (regional climate and energy vulnerability) provided a more favorable environment for Ukraine, one in which the state attempted reform of the sector, but not as a concerted national security issue.

A System-Oriented Approach for the Optimal Control of Process Chains under Stochastic Influences

NASA Astrophysics Data System (ADS)

Senn, Melanie; Schäfer, Julian; Pollak, Jürgen; Link, Norbert

2011-09-01

Process chains in manufacturing consist of multiple connected processes in terms of dynamic systems. The properties of a product passing through such a process chain are influenced by the transformation of each single process. There exist various methods for the control of individual processes, such as classical state controllers from cybernetics or function mapping approaches realized by statistical learning. These controllers ensure that a desired state is obtained at process end despite of variations in the input and disturbances. The interactions between the single processes are thereby neglected, but play an important role in the optimization of the entire process chain. We divide the overall optimization into two phases: (1) the solution of the optimization problem by Dynamic Programming to find the optimal control variable values for each process for any encountered end state of its predecessor and (2) the application of the optimal control variables at runtime for the detected initial process state. The optimization problem is solved by selecting adequate control variables for each process in the chain backwards based on predefined quality requirements for the final product. For the demonstration of the proposed concept, we have chosen a process chain from sheet metal manufacturing with simplified transformation functions.

Intrafen and interfen variation of Indiana fens: water chemistry

USGS Publications Warehouse

Stewart, Paul M.; Kessler, Katrina; Dunbar, Richard

1993-01-01

This study establishes a baseline of water chemistry information for selected Indiana fens over the course of one year. Fens are peatlands fed by groundwater seepage and are characterized by their dominant plant communities. Most of the fens discussed in this paper are located on property controlled and protected by the State of Indiana or the Federal government. Comparisons were made of variability in water chemistry data between fens located in the same area and those located some distance away. This survey indicated extensive variability in fen water chemistry with greater variability in water chemistry between fens in separate locations than in yearly variation within individual fens.

VARIABILITY AND CHARACTER ASSOCIATION IN ROSE COLOURED LEADWORT (PLUMBAGO ROSEA Linn.)

PubMed Central

Kurian, Alice; Anitha, C.A.; Nybe, E.V.

2001-01-01

Forty five plumbago rosea accessions collected from different parts of Kerala state were evaluated for variability in morphological and yield related characters and plumbagin content. Highly significant variation was evident for all the characters studied except leaf size indicating wide variability in the accessions. Accessions PR 25 and PR 31 appear to be promising with respect to root yield and high plumbagin content. Character association revelated significant and positive correlation of all the characters except leaf size with yield. Hence, selection of high yielding types could easily be done based on visual characters expressing more vegetative growth but with reduced leaf size. PMID:22557037

Study of hadronic event-shape variables in multijet final states in pp collisions at √s = 7 TeV

DOE PAGES

Khachatryan, V.

2014-10-14

Event-shape variables, which are sensitive to perturbative and nonperturbative aspects of quantum chromodynamic (QCD) interactions, are studied in multijet events recorded in proton-proton collisions at √s = 7 TeV. Events are selected with at least one jet with transverse momentum p T > 110 GeV and pseudorapidity |η| < 2.4, in a data sample corresponding to integrated luminosities of up to 5 fb –1. As a result, the distributions of five event-shape variables in various leading jet p T ranges are compared to predictions from different QCD Monte Carlo event generators.

Knowledge of safe motherhood among women in rural communities in northern Nigeria: implications for maternal mortality reduction

PubMed Central

2013-01-01

Background Most developed countries have made considerable progress in addressing maternal mortality, but it appears that countries with high maternal mortality burdens like Nigeria have made little progress in improving maternal health outcomes despite emphasis by the Millennium Development Goals (MDGs). Knowledge about safe motherhood practices could help reduce pregnancy related health risks. This study examines knowledge of safe motherhood among women in selected rural communities in northern Nigeria. Methods This was a cross-sectional study carried out in two states (Kaduna and Kano States) within northern Nigeria. Pretested, interviewer-administered questionnaires were applied by female data collectors to 540 randomly selected women who had recently delivered within the study site. Chi-square tests were used to determine possible association between variables during bivariate analysis. Variables significant in the bivariate analysis were subsequently entered into a multivariate logistic regression analysis. The degree of association was estimated by odds ratio (OR) and 95% confidence interval (CI) between knowledge of maternal danger signs and independent socio-demographic as well as obstetric history variables which indicated significance at p< 0.05. Results Over 90% of respondents in both states showed poor knowledge of the benefits of health facility delivery by a skilled birth attendant. More than 80% of respondents in both states displayed poor knowledge of the benefits of ANC visits. More than half of the respondents across both states had poor knowledge of maternal danger signs. According to multivariate regression analysis, ever attending school by a respondent increased the likelihood of knowing maternal danger signs by threefold (OR 2.63, 95% CI: 1.2-5.8) among respondents in Kaduna State. While attendance at ANC visits during most recent pregnancy increased the likelihood of knowing maternal danger signs by twofold among respondents in Kano State (OR 2.05, 95% CI: 1.1-3.9) and threefold among respondents in Kaduna State (OR 3.33, 95% CI: 1.6-7.2). Conclusion This study found generally poor knowledge about safe motherhood practices among female respondents within selected rural communities in northern Nigeria. Knowledge of safe pregnancy practices among some women in rural communities is strongly associated with attendance at ANC visits, being employed or acquiring some level of education. Increasing knowledge about safe motherhood practices should translate into safer pregnancy outcomes and subsequently lead to lower maternal mortality across the developing world. PMID:24160692

A Quantitative Analysis of the Impact of the Summer Training Program on Midshipmen Service Selecting at the United States Naval Academy

DTIC Science & Technology

2005-06-01

Aldag, 1979; Eagly, 1981; Eagly, 1978; Gottfredson , 1981; O’Brien & Fassinger, 1993; Ryan, Tracey, & Rounds, 1996) personality characteristics...and intelligence are incorporated indirectly in the theory, Holland states “direct assessment of these variables are also required to secure more...Sell, & Aldag, 1979; Eagly, 1981; Eagly, 1978; 7 Gottfredson , 1981; Ryan, Tracey, & Rounds, 1996). Women have been perceived in the past to be

Enhanced production of lovastatin by Omphalotus olearius (DC.) Singer in solid state fermentation.

PubMed

Atlı, Burcu; Yamaç, Mustafa; Yıldız, Zeki; Isikhuemnen, Omoanghe S

2015-01-01

Although lovastatin production has been reported for different microorganism species, there is limited information about lovastatin production by basidiomycetes. The optimization of culture parameters that enhances lovastatin production by Omphalotus olearius OBCC 2002 was investigated, using statistically based experimental designs under solid state fermentation. The Plackett Burman design was used in the first step to test the relative importance of the variables affecting production of lovastatin. Amount and particle size of barley were identified as efficient variables. In the latter step, the interactive effects of selected efficient variables were studied with a full factorial design. A maximum lovastatin yield of 139.47mg/g substrate was achieved by the fermentation of 5g of barley, 1-2mm particle diam., at 28°C. This study showed that O. olearius OBCC 2002 has a high capacity for lovastatin production which could be enhanced by using solid state fermentation with novel and cost-effective substrates, such as barley. Copyright © 2013 Revista Iberoamericana de Micología. Published by Elsevier Espana. All rights reserved.

Zoonotic importance of canine scabies and dermatophytosis in relation to knowledge level of dog owners

PubMed Central

Raval, Heli S.; Nayak, J. B.; Patel, B. M.; Bhadesiya, C. M.

2015-01-01

Aim: The present study was undertaken to understand the zoonotic importance of canine scabies and dermatophytosis with special reference to the knowledge level of dog owners in urban areas of Gujarat. Materials and Methods: The study was carried out in randomly selected 120 dog owners of 3 urban cities (viz., Ahmedabad, Anand and Vadodara) of Gujarat state, India. Dog owners (i.e., respondents) were subjected to a detailed interview regarding the zoonotic importance of canine scabies and dermatophytosis in dogs. Ex-post-facto research design was selected because of the independent variables of the selected respondent population for the study. The crucial method used in collecting data was a field survey to generate null hypothesis (Ho1). Available data was subjected to statistical analysis. Results: The three independent variables, viz., extension contact (r=0.522**), mass-media exposure (r=0.205*) and management orientation (r=0.264**) had significant relationship with knowledge of dog owners about zoonotic diseases. Other independent variables, viz., education, experience in dog keeping and housing space were observed to have negative and non-significant relationship with knowledge of dog owners about zoonotic diseases. Conclusion: Extension contact, exposure to extension mass-media, management orientation and innovation proneness among dog owners of 3 urban cities of Gujarat state had significant relationship with knowledge of dog owners on zoonotic aspects of canine scabies and dermatophytosis. Data provided new insights on the present status of zoonotic disease-awareness, which would be an aid to plan preventive measures. PMID:27065644

Identifying public water facilities with low spatial variability of disinfection by-products for epidemiological investigations

PubMed Central

Hinckley, A; Bachand, A; Nuckols, J; Reif, J

2005-01-01

Background and Aims: Epidemiological studies of disinfection by-products (DBPs) and reproductive outcomes have been hampered by misclassification of exposure. In most epidemiological studies conducted to date, all persons living within the boundaries of a water distribution system have been assigned a common exposure value based on facility-wide averages of trihalomethane (THM) concentrations. Since THMs do not develop uniformly throughout a distribution system, assignment of facility-wide averages may be inappropriate. One approach to mitigate this potential for misclassification is to select communities for epidemiological investigations that are served by distribution systems with consistently low spatial variability of THMs. Methods and Results: A feasibility study was conducted to develop methods for community selection using the Information Collection Rule (ICR) database, assembled by the US Environmental Protection Agency. The ICR database contains quarterly DBP concentrations collected between 1997 and 1998 from the distribution systems of 198 public water facilities with minimum service populations of 100 000 persons. Facilities with low spatial variation of THMs were identified using two methods; 33 facilities were found with low spatial variability based on one or both methods. Because brominated THMs may be important predictors of risk for adverse reproductive outcomes, sites were categorised into three exposure profiles according to proportion of brominated THM species and average TTHM concentration. The correlation between THMs and haloacetic acids (HAAs) in these facilities was evaluated to see whether selection by total trihalomethanes (TTHMs) corresponds to low spatial variability for HAAs. TTHMs were only moderately correlated with HAAs (r = 0.623). Conclusions: Results provide a simple method for a priori selection of sites with low spatial variability from state or national public water facility datasets as a means to reduce exposure misclassification in epidemiological studies of DBPs. PMID:15961627

Multi-objective flexible job shop scheduling problem using variable neighborhood evolutionary algorithm

NASA Astrophysics Data System (ADS)

Wang, Chun; Ji, Zhicheng; Wang, Yan

2017-07-01

In this paper, multi-objective flexible job shop scheduling problem (MOFJSP) was studied with the objects to minimize makespan, total workload and critical workload. A variable neighborhood evolutionary algorithm (VNEA) was proposed to obtain a set of Pareto optimal solutions. First, two novel crowded operators in terms of the decision space and object space were proposed, and they were respectively used in mating selection and environmental selection. Then, two well-designed neighborhood structures were used in local search, which consider the problem characteristics and can hold fast convergence. Finally, extensive comparison was carried out with the state-of-the-art methods specially presented for solving MOFJSP on well-known benchmark instances. The results show that the proposed VNEA is more effective than other algorithms in solving MOFJSP.

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events

PubMed Central

Vincenzi, Simone

2014-01-01

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an ‘extinction window’ of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the ‘extinction window’, although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. PMID:24920116

Continuous Variable Cluster State Generation over the Optical Spatial Mode Comb

DOE PAGES

Pooser, Raphael C.; Jing, Jietai

2014-10-20

One way quantum computing uses single qubit projective measurements performed on a cluster state (a highly entangled state of multiple qubits) in order to enact quantum gates. The model is promising due to its potential scalability; the cluster state may be produced at the beginning of the computation and operated on over time. Continuous variables (CV) offer another potential benefit in the form of deterministic entanglement generation. This determinism can lead to robust cluster states and scalable quantum computation. Recent demonstrations of CV cluster states have made great strides on the path to scalability utilizing either time or frequency multiplexingmore » in optical parametric oscillators (OPO) both above and below threshold. The techniques relied on a combination of entangling operators and beam splitter transformations. Here we show that an analogous transformation exists for amplifiers with Gaussian inputs states operating on multiple spatial modes. By judicious selection of local oscillators (LOs), the spatial mode distribution is analogous to the optical frequency comb consisting of axial modes in an OPO cavity. We outline an experimental system that generates cluster states across the spatial frequency comb which can also scale the amount of quantum noise reduction to potentially larger than in other systems.« less

EVALUATION OF DIVERSION AND COSTS FOR SELECTED DROP-OFF RECYCLING PROGRAMS - A MITE PROGRAM EVALUATION

EPA Science Inventory

This analysis was undertaken in 1993-94 to examine a sample of drop-off recycling programs in the United States and Canada to determine the quantities of recyclable materials diverted, the cost of diverting those materials, and the impact of a wide range of independent variables ...

Effect of Age, Country, and Gender on Music Listening Preferences.

ERIC Educational Resources Information Center

LeBlanc, Albert; Jin, Young Chang; Stamou, Lelouda; McCrary, Jan

1999-01-01

Examines the music listening preferences of 2,042 students from Greece, South Korea, and the United States using a survey that listed selections from art music, traditional jazz, and rock music. Finds that age, gender, and country all exerted influence, but the variables did not perform the same way in each country. (CMK)

Further Studies in Achievement Testing, Hearing Impaired Students. United States: Spring 1971.

ERIC Educational Resources Information Center

Gallaudet Coll., Washington, DC. Office of Demographic Studies.

Reported are four studies resulting from achievement testing activities from 1971 to 1973 with approximately 17,000 hearing impaired students from under 6 to over 21 years of age. The first study reports the relationships between selected achievement test scores (Paragraph Meaning and Arithmetic Computation subtests) and the following variables:…

What Entering, Within-Program Variables Relate to Postrehabilitation "Success?"

ERIC Educational Resources Information Center

Force, Ronald C.; And Others

Adjudged offenders and predelinquent youths 12 to 18 years of age, from the United States, were selected for anticipated amenability to correctional change in this open-residential therapeutic environment. Each of four homes houses 26 youths. Each youth has a thorough assessment, explicit treatment plan, and primary counselor. All elements of the…

Canonical Measure of Correlation (CMC) and Canonical Measure of Distance (CMD) between sets of data. Part 3. Variable selection in classification.

PubMed

Ballabio, Davide; Consonni, Viviana; Mauri, Andrea; Todeschini, Roberto

2010-01-11

In multivariate regression and classification issues variable selection is an important procedure used to select an optimal subset of variables with the aim of producing more parsimonious and eventually more predictive models. Variable selection is often necessary when dealing with methodologies that produce thousands of variables, such as Quantitative Structure-Activity Relationships (QSARs) and highly dimensional analytical procedures. In this paper a novel method for variable selection for classification purposes is introduced. This method exploits the recently proposed Canonical Measure of Correlation between two sets of variables (CMC index). The CMC index is in this case calculated for two specific sets of variables, the former being comprised of the independent variables and the latter of the unfolded class matrix. The CMC values, calculated by considering one variable at a time, can be sorted and a ranking of the variables on the basis of their class discrimination capabilities results. Alternatively, CMC index can be calculated for all the possible combinations of variables and the variable subset with the maximal CMC can be selected, but this procedure is computationally more demanding and classification performance of the selected subset is not always the best one. The effectiveness of the CMC index in selecting variables with discriminative ability was compared with that of other well-known strategies for variable selection, such as the Wilks' Lambda, the VIP index based on the Partial Least Squares-Discriminant Analysis, and the selection provided by classification trees. A variable Forward Selection based on the CMC index was finally used in conjunction of Linear Discriminant Analysis. This approach was tested on several chemical data sets. Obtained results were encouraging.

Estimation of potential runoff-contributing areas in Kansas using topographic and soil information

USGS Publications Warehouse

Juracek, Kyle E.

1999-01-01

Digital topographic and soil information was used to estimate potential runoff-contributing areas throughout Kansas. The results then were used to compare 91 selected subbasins representing soil, slope, and runoff variability. Potential runoff-contributing areas were estimated collectively for the processes of infiltration-excess and saturation-excess overland flow using a set of environmental conditions that represented very high, high, moderate, low, very low, and extremely low potential runoff. For infiltration-excess overland flow, various rainfall-intensity and soil-permeability values were used. For saturation-excess overland flow, antecedent soil-moisture conditions and a topographic wetness index were used. Results indicated that very low potential-runoff conditions provided the best ability to distinguish the 91 selected subbasins as having relatively high or low potential runoff. The majority of the subbasins with relatively high potential runoff are located in the eastern half of the State where soil permeability generally is less and precipitation typically is greater. The ability to distinguish the subbasins as having relatively high or low potential runoff was possible mostly due to the variability of soil permeability across the State.

The Reactivity and Structure of Size Selected VxO y Clusters on a TiO2 (110)-(1 X 1) Surface of Variable Oxidation State

NASA Astrophysics Data System (ADS)

Neilson, Hunter L.

The Reactivity and Structure of Size Selected VxOy Clusters on a TiO2 (110) Surface of Variable Oxidation State by Hunter L Neilson The selective oxidative dehydrogenation of methanol by vanadium oxide/TiO2 model systems has received a great deal of interest in the surface science community. Previous studies using temperature programmed desorption and reaction (TPD/R) to probe the oxidation of methanol to formaldehyde by vanadia/TiO2 model catalysts have shown that the activity of these systems vary considerably based on the way in which the model system is prepared with formaldehyde desorption temperatures observed anywhere from room temperature to 660 K. The principle reason for this variation is that the preparation of sub-monolayer films of vanadia on TiO2 produces clusters with a multitude of VxOy structures and a mixture of vanadium oxidation states. As a result the stoichiometry of the active vanadium oxide catalyst as well as the oxidation state of vanadium in the active catalyst remain unknown. To better understand this system, our group has probed the reactivity and structure of size-selected Vx, VOy and VxOy clusters on a reduced TiO2 (110) support in ultra-high vacuum (UHV) via TPD/R and scanning tunneling microscopy (STM). Ex situ preparation of these clusters in the gas phase prior to deposition has allowed us to systematically vary the stoichiometry of the vanadia clusters; a layer of control not available via the usual routes to vanadium oxide. The most active catalysts are shown to have (VO3)n stoichiometry in agreement with the theoretical models of the Metiu group. We have shown that both the activity and selectivity of V2O6 and V3O9 cluster catalysts depend sensitively on the oxidation state of the TiO2 (110) support. For example, V2O6 on a reduced surface is selective for the oxidation of methanol to formaldehyde while the selectivity shifts to favor methyl formate as the surface becomes increasingly oxidized. STM studies show that the structure of size-selected V2O6 clusters, upon adsorption to the surface, varies considerably with the oxidation state of the support, in good agreement with our reactivity studies. V 3O9 was shown to catalyze the oxidation of methanol to both formaldehyde and methyl formate on a reduced surface while STM suggests that, unlike V2O6, these clusters are prone to decomposition upon adsorption to the surface. Furthermore, TPD/R of size selected V 2O5 and V2O7 on TiO2 suggests that altering the stoichiometry of the (VO3)n clusters by a single oxygen atom significantly inhibits the activity of these catalysts.

Variable Selection in the Presence of Missing Data: Imputation-based Methods.

PubMed

Zhao, Yize; Long, Qi

2017-01-01

Variable selection plays an essential role in regression analysis as it identifies important variables that associated with outcomes and is known to improve predictive accuracy of resulting models. Variable selection methods have been widely investigated for fully observed data. However, in the presence of missing data, methods for variable selection need to be carefully designed to account for missing data mechanisms and statistical techniques used for handling missing data. Since imputation is arguably the most popular method for handling missing data due to its ease of use, statistical methods for variable selection that are combined with imputation are of particular interest. These methods, valid used under the assumptions of missing at random (MAR) and missing completely at random (MCAR), largely fall into three general strategies. The first strategy applies existing variable selection methods to each imputed dataset and then combine variable selection results across all imputed datasets. The second strategy applies existing variable selection methods to stacked imputed datasets. The third variable selection strategy combines resampling techniques such as bootstrap with imputation. Despite recent advances, this area remains under-developed and offers fertile ground for further research.

[A meta-analysis of the variables related to depression in Korean patients with a stroke].

PubMed

Park, Eun Young; Shin, In Soo; Kim, Jung Hee

2012-08-01

The purpose of this study was to use meta-analysis to evaluate the variables related to depression in patients who have had a stroke. The materials of this study were based on 16 variables obtained from 26 recent studies over a span of 10 years which were selected from doctoral dissertations, master's thesis and published articles. Related variables were categorized into sixteen variables and six variable groups which included general characteristics of the patients, disease characteristics, psychological state, physical function, basic needs, and social variables. Also, the classification of six defensive and three risk variables group was based on the negative or positive effect of depression. The quality of life (ES=-.79) and acceptance of disability (ES=-.64) were highly correlated with depression in terms of defensive variables. For risk variables, anxiety (ES=.66), stress (ES=.53) showed high correlation effect size among the risk variables. These findings showed that defensive and risk variables were related to depression among stroke patients. Psychological interventions and improvement in physical functions should be effective in decreasing depression among stroke patients.

The Assessment of Climatological Impacts on Agricultural Production and Residential Energy Demand

NASA Astrophysics Data System (ADS)

Cooter, Ellen Jean

The assessment of climatological impacts on selected economic activities is presented as a multi-step, inter -disciplinary problem. The assessment process which is addressed explicitly in this report focuses on (1) user identification, (2) direct impact model selection, (3) methodological development, (4) product development and (5) product communication. Two user groups of major economic importance were selected for study; agriculture and gas utilities. The broad agricultural sector is further defined as U.S.A. corn production. The general category of utilities is narrowed to Oklahoma residential gas heating demand. The CERES physiological growth model was selected as the process model for corn production. The statistical analysis for corn production suggests that (1) although this is a statistically complex model, it can yield useful impact information, (2) as a result of output distributional biases, traditional statistical techniques are not adequate analytical tools, (3) the model yield distribution as a whole is probably non-Gausian, particularly in the tails and (4) there appears to be identifiable weekly patterns of forecasted yields throughout the growing season. Agricultural quantities developed include point yield impact estimates and distributional characteristics, geographic corn weather distributions, return period estimates, decision making criteria (confidence limits) and time series of indices. These products were communicated in economic terms through the use of a Bayesian decision example and an econometric model. The NBSLD energy load model was selected to represent residential gas heating consumption. A cursory statistical analysis suggests relationships among weather variables across the Oklahoma study sites. No linear trend in "technology -free" modeled energy demand or input weather variables which would correspond to that contained in observed state -level residential energy use was detected. It is suggested that this trend is largely the result of non-weather factors such as population and home usage patterns rather than regional climate change. Year-to-year changes in modeled residential heating demand on the order of 10('6) Btu's per household were determined and later related to state -level components of the Oklahoma economy. Products developed include the definition of regional forecast areas, likelihood estimates of extreme seasonal conditions and an energy/climate index. This information is communicated in economic terms through an input/output model which is used to estimate changes in Gross State Product and Household income attributable to weather variability.

Selecting sagebrush seed sources for restoration in a variable climate: ecophysiological variation among genotypes

USGS Publications Warehouse

Germino, Matthew J.

2012-01-01

Big sagebrush (Artemisia tridentata) communities dominate a large fraction of the United States and provide critical habitat for a number of wildlife species of concern. Loss of big sagebrush due to fire followed by poor restoration success continues to reduce ecological potential of this ecosystem type, particularly in the Great Basin. Choice of appropriate seed sources for restoration efforts is currently unguided due to knowledge gaps on genetic variation and local adaptation as they relate to a changing landscape. We are assessing ecophysiological responses of big sagebrush to climate variation, comparing plants that germinated from ~20 geographically distinct populations of each of the three subspecies of big sagebrush. Seedlings were previously planted into common gardens by US Forest Service collaborators Drs. B. Richardson and N. Shaw, (USFS Rocky Mountain Research Station, Provo, Utah and Boise, Idaho) as part of the Great Basin Native Plant Selection and Increase Project. Seed sources spanned all states in the conterminous Western United States. Germination, establishment, growth and ecophysiological responses are being linked to genomics and foliar palatability. New information is being produced to aid choice of appropriate seed sources by Bureau of Land Management and USFS field offices when they are planning seed acquisitions for emergency post-fire rehabilitation projects while considering climate variability and wildlife needs.

Socioeconomic Collapse of Rural Areas, Atlantic Forest Transition and Sustainability

NASA Astrophysics Data System (ADS)

Silva, R. F. B. D.; Batistella, M.; Moran, E. F.

2017-12-01

Centuries of human pressure over the Atlantic Forest has led the biome to encompass only 11.7 percent of forest remnants. On the other hand, natural regeneration has explained forest cover increase in specific regions since the 1960s as an outcome of land use policies, environmental legislation, agricultural modernization, economic development, and landscape biophysical conditions. We analyze Forest Transition (FT) pathways for the Paraíba Valley region, São Paulo State, Brazil looking for more sustainable relationships between land use and natural land cover. During the 18th and 19th centuries, the Valley's farms were responsible for providing the largest portion of the state's wealth. Nowadays, the Valley contributes with only 6% to the state's gross product and the share of rural activities is now insignificant. Between 1962 and 2011, forest cover area increased from 225 to 446 thousand hectares. Rural household survey was conducted in three municipalities (n=90, thirty in each municipality). To select the municipalities among the thirty-four present in the Paraíba Valley, we applied the modified Thompson Tau technique to detect outlier values for three selected variables: natural forest cover, eucalyptus plantation cover, and municipal revenue. The outliers were discharged and the municipality with the best performance (maximum value) for each variable was selected. Based on the rural household surveys and GIS analysis of satellite imagery classifications, topography and hydrology variables, we conclude that the diminished land use pressure in the Paraíba Valley is allowing the regeneration of forest cover. Over the observed period, the FT was strongly influenced by the unsuitable topography for agriculture (steep slopes) and the economic urban development since the 1960s. However, more recently (2000s), FT is more affected by the vicinity of eucalyptus plantations, the active role of local communities denouncing illegal environmental threats (e.g., deforestation), and voluntary afforestation practices, which we call the collective action pathways.

Nonparametric variational optimization of reaction coordinates

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

Banushkina, Polina V.; Krivov, Sergei V., E-mail: s.krivov@leeds.ac.uk

State of the art realistic simulations of complex atomic processes commonly produce trajectories of large size, making the development of automated analysis tools very important. A popular approach aimed at extracting dynamical information consists of projecting these trajectories into optimally selected reaction coordinates or collective variables. For equilibrium dynamics between any two boundary states, the committor function also known as the folding probability in protein folding studies is often considered as the optimal coordinate. To determine it, one selects a functional form with many parameters and trains it on the trajectories using various criteria. A major problem with such anmore » approach is that a poor initial choice of the functional form may lead to sub-optimal results. Here, we describe an approach which allows one to optimize the reaction coordinate without selecting its functional form and thus avoiding this source of error.« less

Finite Adaptation and Multistep Moves in the Metropolis-Hastings Algorithm for Variable Selection in Genome-Wide Association Analysis

PubMed Central

Peltola, Tomi; Marttinen, Pekka; Vehtari, Aki

2012-01-01

High-dimensional datasets with large amounts of redundant information are nowadays available for hypothesis-free exploration of scientific questions. A particular case is genome-wide association analysis, where variations in the genome are searched for effects on disease or other traits. Bayesian variable selection has been demonstrated as a possible analysis approach, which can account for the multifactorial nature of the genetic effects in a linear regression model. Yet, the computation presents a challenge and application to large-scale data is not routine. Here, we study aspects of the computation using the Metropolis-Hastings algorithm for the variable selection: finite adaptation of the proposal distributions, multistep moves for changing the inclusion state of multiple variables in a single proposal and multistep move size adaptation. We also experiment with a delayed rejection step for the multistep moves. Results on simulated and real data show increase in the sampling efficiency. We also demonstrate that with application specific proposals, the approach can overcome a specific mixing problem in real data with 3822 individuals and 1,051,811 single nucleotide polymorphisms and uncover a variant pair with synergistic effect on the studied trait. Moreover, we illustrate multimodality in the real dataset related to a restrictive prior distribution on the genetic effect sizes and advocate a more flexible alternative. PMID:23166669

Caloric and Selected Nutrient Values for Persons 1-74 Years of Age: First Health and Nutrition Examination Survey, United States, 1971-1974. Vital and Health Statistics, Data from the National Health Survey, Series ll, Number 209.

ERIC Educational Resources Information Center

Abraham, Sidney; And Others

This report presents data on dietary intake obtained to assess the nutritional status of the United States population, aged 1-74 years. Age, sex, race, and income level differences in dietary intake are among the variables considered. Data are analyzed for certain groups at high risk of malnutrition (e.g., the poor, preschool children, women of…

User's manual for LINEAR, a FORTRAN program to derive linear aircraft models

NASA Technical Reports Server (NTRS)

Duke, Eugene L.; Patterson, Brian P.; Antoniewicz, Robert F.

1987-01-01

This report documents a FORTRAN program that provides a powerful and flexible tool for the linearization of aircraft models. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied nonlinear aerodynamic model. The system model determined by LINEAR consists of matrices for both state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.

Wetland selection by breeding and foraging black terns in the Prairie Pothole Region of the United States

USGS Publications Warehouse

Steen, Valerie A.; Powell, Abby N.

2012-01-01

We examined wetland selection by the Black Tern (Chlidonias niger), a species that breeds primarily in the prairie pothole region, has experienced population declines, and is difficult to manage because of low site fidelity. To characterize its selection of wetlands in this region, we surveyed 589 wetlands throughout North and South Dakota. We documented breeding at 5% and foraging at 17% of wetlands. We created predictive habitat models with a machine-learning algorithm, Random Forests, to explore the relative role of local wetland characteristics and those of the surrounding landscape and to evaluate which characteristics were important to predicting breeding versus foraging. We also examined area-dependent wetland selection while addressing the passive sampling bias by replacing occurrence of terns in the models with an index of density. Local wetland variables were more important than landscape variables in predictions of occurrence of breeding and foraging. Wetland size was more important to prediction of foraging than of breeding locations, while floating matted vegetation was more important to prediction of breeding than of foraging locations. The amount of seasonal wetland in the landscape was the only landscape variable important to prediction of both foraging and breeding. Models based on a density index indicated that wetland selection by foraging terns may be more area dependent than that by breeding terns. Our study provides some of the first evidence for differential breeding and foraging wetland selection by Black Terns and for a more limited role of landscape effects and area sensitivity than has been previously shown.

Elimination of Neglected Diseases in Latin America and the Caribbean: A Mapping of Selected Diseases

PubMed Central

Schneider, Maria Cristina; Aguilera, Ximena Paz; Barbosa da Silva Junior, Jarbas; Ault, Steven Kenyon; Najera, Patricia; Martinez, Julio; Requejo, Raquel; Nicholls, Ruben Santiago; Yadon, Zaida; Silva, Juan Carlos; Leanes, Luis Fernando; Periago, Mirta Roses

2011-01-01

In Latin America and the Caribbean, around 195 million people live in poverty, a situation that increases the burden of some infectious diseases. Neglected diseases, in particular, are often restricted to poor, marginalized sections of the population. Tools exist to combat these diseases, making it imperative to work towards their elimination. In 2009, the Pan American Health Organization (PAHO) received a mandate to support the countries in the Region in eliminating neglected diseases and other poverty-related infections. The objective of this study is to analyze the presence of selected diseases using geo-processing techniques. Five diseases with information available at the first sub-national level (states) were mapped, showing the presence of the disease (“hotspots”) and overlap of diseases (“major hotspots”). In the 45 countries/territories (approximately 570 states) of the Region, there is: lymphatic filariasis in four countries (29 states), onchocerciasis in six countries (25 states), schistosomiasis in four countries (39 states), trachoma in three countries (29 states), and human rabies transmitted by dogs in ten countries (20 states). Of the 108 states with one or more of the selected diseases, 36 states present the diseases in overlapping areas (“major hotspots”). Additional information about soil-transmitted helminths was included. The analysis suggests a majority of the selected diseases are not widespread and can be considered part of an unfinished agenda with elimination as a goal. Integrated plans and a comprehensive approach, ensuring access to existing diagnostic and treatment methods, and establishing a multi-sectoral agenda that addresses social determinants, including access to adequate water and sanitation, are required. Future studies can include additional diseases, socio-economic and environmental variables. PMID:21358810

Efficient Variable Selection Method for Exposure Variables on Binary Data

NASA Astrophysics Data System (ADS)

Ohno, Manabu; Tarumi, Tomoyuki

In this paper, we propose a new variable selection method for "robust" exposure variables. We define "robust" as property that the same variable can select among original data and perturbed data. There are few studies of effective for the selection method. The problem that selects exposure variables is almost the same as a problem that extracts correlation rules without robustness. [Brin 97] is suggested that correlation rules are possible to extract efficiently using chi-squared statistic of contingency table having monotone property on binary data. But the chi-squared value does not have monotone property, so it's is easy to judge the method to be not independent with an increase in the dimension though the variable set is completely independent, and the method is not usable in variable selection for robust exposure variables. We assume anti-monotone property for independent variables to select robust independent variables and use the apriori algorithm for it. The apriori algorithm is one of the algorithms which find association rules from the market basket data. The algorithm use anti-monotone property on the support which is defined by association rules. But independent property does not completely have anti-monotone property on the AIC of independent probability model, but the tendency to have anti-monotone property is strong. Therefore, selected variables with anti-monotone property on the AIC have robustness. Our method judges whether a certain variable is exposure variable for the independent variable using previous comparison of the AIC. Our numerical experiments show that our method can select robust exposure variables efficiently and precisely.

Students' daily emotions in the classroom: intra-individual variability and appraisal correlates.

PubMed

Ahmed, Wondimu; van der Werf, Greetje; Minnaert, Alexander; Kuyper, Hans

2010-12-01

Recent literature on emotions in education has shown that competence- and value-related beliefs are important sources of students' emotions; nevertheless, the role of these antecedents in students' daily functioning in the classroom is not yet well-known. More importantly, to date we know little about intra-individual variability in students' daily emotions. The objectives of the study were (1) to examine within-student variability in emotional experiences and (2) to investigate how competence and value appraisals are associated with emotions. It was hypothesized that emotions would show substantial within-student variability and that there would be within-person associations between competence and value appraisals and the emotions. (s) The sample consisted of 120 grade 7 students (52%, girls) in 5 randomly selected classrooms in a secondary school. A diary method was used to acquire daily process variables of emotions and appraisals. Daily emotions and daily appraisals were assessed using items adapted from existing measures. Multi-level modelling was used to test the hypotheses. As predicted, the within-person variability in emotional states accounted for between 41% (for pride) and 70% (for anxiety) of total variability in the emotional states. Also as hypothesized, the appraisals were generally associated with the emotions. The within-student variability in emotions and appraisals clearly demonstrates the adaptability of students with respect to situational affordances and constraints in their everyday classroom experiences. The significant covariations between the appraisals and emotions suggest that within-student variability in emotions is systematic.

Neural correlates of the divergence of instrumental probability distributions.

PubMed

Liljeholm, Mimi; Wang, Shuo; Zhang, June; O'Doherty, John P

2013-07-24

Flexible action selection requires knowledge about how alternative actions impact the environment: a "cognitive map" of instrumental contingencies. Reinforcement learning theories formalize this map as a set of stochastic relationships between actions and states, such that for any given action considered in a current state, a probability distribution is specified over possible outcome states. Here, we show that activity in the human inferior parietal lobule correlates with the divergence of such outcome distributions-a measure that reflects whether discrimination between alternative actions increases the controllability of the future-and, further, that this effect is dissociable from those of other information theoretic and motivational variables, such as outcome entropy, action values, and outcome utilities. Our results suggest that, although ultimately combined with reward estimates to generate action values, outcome probability distributions associated with alternative actions may be contrasted independently of valence computations, to narrow the scope of the action selection problem.

Neural Correlates of the Divergence of Instrumental Probability Distributions

PubMed Central

Wang, Shuo; Zhang, June; O'Doherty, John P.

2013-01-01

Flexible action selection requires knowledge about how alternative actions impact the environment: a “cognitive map” of instrumental contingencies. Reinforcement learning theories formalize this map as a set of stochastic relationships between actions and states, such that for any given action considered in a current state, a probability distribution is specified over possible outcome states. Here, we show that activity in the human inferior parietal lobule correlates with the divergence of such outcome distributions–a measure that reflects whether discrimination between alternative actions increases the controllability of the future–and, further, that this effect is dissociable from those of other information theoretic and motivational variables, such as outcome entropy, action values, and outcome utilities. Our results suggest that, although ultimately combined with reward estimates to generate action values, outcome probability distributions associated with alternative actions may be contrasted independently of valence computations, to narrow the scope of the action selection problem. PMID:23884955

Exploring Student Characteristics of Retention That Lead to Graduation in Higher Education Using Data Mining Models

ERIC Educational Resources Information Center

Raju, Dheeraj; Schumacker, Randall

2015-01-01

The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…

Selected Influences on Solo and Small-Ensemble Festival Ratings: Replication and Extension

ERIC Educational Resources Information Center

Bergee, Martin J.; McWhirter, Jamila L.

2005-01-01

Festival performance is no trivial endeavor. At one midwestern state festival alone, 10,938 events received a rating over a 3-year period (2001-2003). Such an extensive level of participation justifies sustained study. To learn more about variables that may underlie success at solo and small ensemble evaluative festivals, Bergee and Platt (2003)…

The Application of Synoptic Weather Forecasting Rules to Selected Weather Situations in the United States.

ERIC Educational Resources Information Center

Kohler, Fred E.

The document describes the use of weather maps and data in teaching introductory college courses in synoptic meteorology. Students examine weather changes at three-hour intervals from data obtained from the "Monthly Summary of Local Climatological Data." Weather variables in the local summary include sky cover, air temperature, dew point, relative…

Poverty and Algebra Performance: A Comparative Spatial Analysis of a Border South State

ERIC Educational Resources Information Center

Tate, William F.; Hogrebe, Mark C.

2015-01-01

This research uses two measures of poverty, as well as mobility and selected education variables to study how their relationships vary across 543 Missouri high school districts. Using Missouri and U.S. Census American Community Survey (ACS) data, local R[superscript 2]'s from geographically weighted regressions are spatially mapped to demonstrate…

Economic values for growth and grade changes of sugar maple in the Lake States.

Treesearch

Richard M. Godman; Joseph J. Mendel

1978-01-01

Current and expected rates of value increase over a 10-year period were developed for sawtimber-size sugar maple based on variable growth rates, expected merchantable height changes, and butt log grade improvement. These economic guides, along with silvicultural considerations, provide a value basis for selecting trees during thinning and determining final harvest...

The Support System of the Hispanic Elderly and the Use of Formal Social Services.

ERIC Educational Resources Information Center

Starrett, Richard A.; And Others

The study examined the role played by informal (i.e., family, kin, neighbors, friends) and quasiformal (i.e., church-sponsored) support systems in predicting, enhancing, or inhibiting use of social services by Hispanic elderly. Thirty-seven variables and data selected from a 1979-1980 15-state survey of 1,805 noninstitutionalized Hispanic…

Individual and contextual factors influencing dental health care utilization by preschool children: a multilevel analysis

PubMed

Piovesan, Chaiana; Ardenghi, Thiago Machado; Mendes, Fausto Medeiros; Agostini, Bernardo Antonio; Michel-Crosato, Edgard

2017-03-30

The effect of contextual factors on dental care utilization was evaluated after adjustment for individual characteristics of Brazilian preschool children. This cross-sectional study assessed 639 preschool children aged 1 to 5 years from Santa Maria, a town in Rio Grande do Sul State, located in southern Brazil. Participants were randomly selected from children attending the National Children's Vaccination Day and 15 health centers were selected for this research. Visual examinations followed the ICDAS criteria. Parents answered a questionnaire about demographic and socioeconomic characteristics. Contextual influences on children's dental care utilization were obtained from two community-related variables: presence of dentists and presence of workers' associations in the neighborhood. Unadjusted and adjusted multilevel logistic regression models were used to describe the association between outcome and predictor variables. A prevalence of 21.6% was found for regular use of dental services. The unadjusted assessment of the associations of dental health care utilization with individual and contextual factors included children's ages, family income, parents' schooling, mothers' participation in their children's school activities, dental caries, and presence of workers' associations in the neighborhood as the main outcome covariates. Individual variables remained associated with the outcome after adding contextual variables in the model. In conclusion, individual and contextual variables were associated with dental health care utilization by preschool children.

The end-state comfort effect in bimanual grip selection.

PubMed

Fischman, Mark G; Stodden, David F; Lehman, Davana M

2003-03-01

During a unimanual grip selection task in which people pick up a lightweight dowel and place one end against targets at variable heights, the choice of hand grip (overhand vs. underhand) typically depends on the perception of how comfortable the arm will be at the end of the movement: an end-state comfort effect. The two experiments reported here extend this work to bimanual tasks. In each experiment, 26 right-handed participants used their left and right hands to simultaneously pick up two wooden dowels and place either the right or left end against a series of 14 targets ranging from 14 to 210 cm above the floor. These tasks were performed in systematic ascending and descending orders in Experiment 1 and in random order in Expiment 2. Results were generally consistent with predictions of end-state comfort in that, for the extreme highest and lowest targets, participants tended to select opposite grips with each hand. Taken together, our findings are consistent with the concept of constraint hierarchies within a posture-based motion-planning model.

Comparative levels of creative ability in black and white college students.

PubMed

Glover, J A

1976-03-01

Eighty-seven black, educational psychology students from three intact, randomly selected classes at Tennessee State University were compared to ninety-four white, educational phychology students from three intact, randomly selected classes at the University of Tennessee on Torrance's Unusual Uses and Ask and Guess activities. No differences were found on the frequency of flexibility measures of either activity. No attempt was made to examine the results on this "Level II" mental ability measure on any variable except race. There were no differences based on race.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Seasonal Habitat Use by Greater Sage-Grouse (Centrocercus urophasianus) on a Landscape with Low Density Oil and Gas Development.

PubMed

Rice, Mindy B; Rossi, Liza G; Apa, Anthony D

2016-01-01

Fragmentation of the sagebrush (Artemisia spp.) ecosystem has led to concern about a variety of sagebrush obligates including the greater sage-grouse (Centrocercus urophasianus). Given the increase of energy development within greater sage-grouse habitats, mapping seasonal habitats in pre-development populations is critical. The North Park population in Colorado is one of the largest and most stable in the state and provides a unique case study for investigating resource selection at a relatively low level of energy development compared to other populations both within and outside the state. We used locations from 117 radio-marked female greater sage-grouse in North Park, Colorado to develop seasonal resource selection models. We then added energy development variables to the base models at both a landscape and local scale to determine if energy variables improved the fit of the seasonal models. The base models for breeding and winter resource selection predicted greater use in large expanses of sagebrush whereas the base summer model predicted greater use along the edge of riparian areas. Energy development variables did not improve the winter or the summer models at either scale of analysis, but distance to oil/gas roads slightly improved model fit at both scales in the breeding season, albeit in opposite ways. At the landscape scale, greater sage-grouse were closer to oil/gas roads whereas they were further from oil/gas roads at the local scale during the breeding season. Although we found limited effects from low level energy development in the breeding season, the scale of analysis can influence the interpretation of effects. The lack of strong effects from energy development may be indicative that energy development at current levels are not impacting greater sage-grouse in North Park. Our baseline seasonal resource selection maps can be used for conservation to help identify ways of minimizing the effects of energy development.

Evaluating Washington State's immunization information system as a research tool.

PubMed

Jackson, Michael L; Henrikson, Nora B; Grossman, David C

2014-01-01

Immunization information systems (IISs) are powerful public health tools for vaccination activities. To date, however, their use for public health research has been limited, in part as a result of insufficient understanding on accuracy and quality of IIS data. We evaluated the completeness and accuracy of Washington State IIS (WAIIS) data, with particular attention to data elements of research interest. We analyzed all WAIIS records on all children born between 2006 and 2010 with at least 1 vaccination recorded in WAIIS between 2006 and 2010. We assessed all variables for completeness and tested selected variables for internal validity. To assess external validity, we matched WAIIS data to records from Group Health, a large integrated health care organization in Washington State. On these children, we compared vaccination data in WAIIS with vaccination data from Group Health's immunization registry. The WAIIS data included 486,265 children and 8,670,234 unique vaccinations. Variables required by WAIIS (such as date of vaccination) were highly complete, but optional variables were often missing. For example, most records were missing data on route (80.7%) and anatomic site (81.7%) of vaccination. WAIIS data, when complete, were highly accurate relative to the Group Health immunization registry, with 96% to 99% agreement between fields such as vaccination code and anatomic site. Required data elements in WAIIS are highly complete and have both internal and external validity, suggesting that these variables are useful for research. Research requiring nonrequired variables should use additional validity checks before proceeding. Copyright © 2014 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events.

PubMed

Vincenzi, Simone

2014-08-06

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an 'extinction window' of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the 'extinction window', although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Stability analysis of BWR nuclear-coupled thermal-hyraulics using a simple model

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

Karve, A.A.; Rizwan-uddin; Dorning, J.J.

1995-09-01

A simple mathematical model is developed to describe the dynamics of the nuclear-coupled thermal-hydraulics in a boiling water reactor (BWR) core. The model, which incorporates the essential features of neutron kinetics, and single-phase and two-phase thermal-hydraulics, leads to simple dynamical system comprised of a set of nonlinear ordinary differential equations (ODEs). The stability boundary is determined and plotted in the inlet-subcooling-number (enthalpy)/external-reactivity operating parameter plane. The eigenvalues of the Jacobian matrix of the dynamical system also are calculated at various steady-states (fixed points); the results are consistent with those of the direct stability analysis and indicate that a Hopf bifurcationmore » occurs as the stability boundary in the operating parameter plane is crossed. Numerical simulations of the time-dependent, nonlinear ODEs are carried out for selected points in the operating parameter plane to obtain the actual damped and growing oscillations in the neutron number density, the channel inlet flow velocity, and the other phase variables. These indicate that the Hopf bifurcation is subcritical, hence, density wave oscillations with growing amplitude could result from a finite perturbation of the system even where the steady-state is stable. The power-flow map, frequently used by reactor operators during start-up and shut-down operation of a BWR, is mapped to the inlet-subcooling-number/neutron-density (operating-parameter/phase-variable) plane, and then related to the stability boundaries for different fixed inlet velocities corresponding to selected points on the flow-control line. The stability boundaries for different fixed inlet subcooling numbers corresponding to those selected points, are plotted in the neutron-density/inlet-velocity phase variable plane and then the points on the flow-control line are related to their respective stability boundaries in this plane.« less

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

Kim, J.; Moon, T.J.; Howell, J.R.

This paper presents an analysis of the heat transfer occurring during an in-situ curing process for which infrared energy is provided on the surface of polymer composite during winding. The material system is Hercules prepreg AS4/3501-6. Thermoset composites have an exothermic chemical reaction during the curing process. An Eulerian thermochemical model is developed for the heat transfer analysis of helical winding. The model incorporates heat generation due to the chemical reaction. Several assumptions are made leading to a two-dimensional, thermochemical model. For simplicity, 360{degree} heating around the mandrel is considered. In order to generate the appropriate process windows, the developedmore » heat transfer model is combined with a simple winding time model. The process windows allow for a proper selection of process variables such as infrared energy input and winding velocity to give a desired end-product state. Steady-state temperatures are found for each combination of the process variables. A regression analysis is carried out to relate the process variables to the resulting steady-state temperatures. Using regression equations, process windows for a wide range of cylinder diameters are found. A general procedure to find process windows for Hercules AS4/3501-6 prepreg tape is coded in a FORTRAN program.« less

Design and Application of Drought Indexes in Highly Regulated Mediterranean Water Systems

NASA Astrophysics Data System (ADS)

Castelletti, A.; Zaniolo, M.; Giuliani, M.

2017-12-01

Costs of drought are progressively increasing due to the undergoing alteration of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, most of the traditional drought indexes fail in detecting critical events in highly regulated systems, which generally rely on ad-hoc formulations and cannot be generalized to different context. In this study, we contribute a novel framework for the design of a basin-customized drought index. This index represents a surrogate of the state of the basin and is computed by combining the available information about the water available in the system to reproduce a representative target variable for the drought condition of the basin (e.g., water deficit). To select the relevant variables and combinatione thereof, we use an advanced feature extraction algorithm called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS). W-QEISS relies on a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The accuracy objective is evaluated trough the calibration of an extreme learning machine of the water deficit for each candidate subset of variables, with the index selected from the resulting solutions identifying a suitable compromise between accuracy, cardinality, relevance, and redundancy. The approach is tested on Lake Como, Italy, a regulated lake mainly operated for irrigation supply. In the absence of an institutional drought monitoring system, we constructed the combined index using all the hydrological variables from the existing monitoring system as well as common drought indicators at multiple time aggregations. The soil moisture deficit in the root zone computed by a distributed-parameter water balance model of the agricultural districts is used as target variable. Numerical results show that our combined drought index succesfully reproduces the deficit. The index represents a valuable information for supporting appropriate drought management strategies, including the possibility of directly informing the lake operations about the drought conditions and improve the overall reliability of the irrigation supply system.

New opportunities for quasielastic and inelastic neutron scattering at steady-state sources using mechanical selection of the incident and final neutron energy

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

Mamantov, Eugene

2015-06-12

We propose a modification of the neutron wide-angle velocity selector (WAVES) device that enables inelastic (in particular, quasielastic) scattering measurements not relying on the neutron time-of-flight. The proposed device is highly suitable for a steady-state neutron source, somewhat similar to a triple-axis spectrometer, but with simultaneous selection of the incident and final neutron energy over a broad range of scattering momentum transfer. Both the incident and final neutron velocities are defined by the WAVES geometry and rotation frequency. The variable energy transfer is achieved through the natural variation of the velocity of the transmitted neutrons as a function of themore » scattering angle component out of the equatorial plane.« less

Analysis of Binary Multivariate Longitudinal Data via 2-Dimensional Orbits: An Application to the Agincourt Health and Socio-Demographic Surveillance System in South Africa

PubMed Central

Visaya, Maria Vivien; Sherwell, David; Sartorius, Benn; Cromieres, Fabien

2015-01-01

We analyse demographic longitudinal survey data of South African (SA) and Mozambican (MOZ) rural households from the Agincourt Health and Socio-Demographic Surveillance System in South Africa. In particular, we determine whether absolute poverty status (APS) is associated with selected household variables pertaining to socio-economic determination, namely household head age, household size, cumulative death, adults to minor ratio, and influx. For comparative purposes, households are classified according to household head nationality (SA or MOZ) and APS (rich or poor). The longitudinal data of each of the four subpopulations (SA rich, SA poor, MOZ rich, and MOZ poor) is a five-dimensional space defined by binary variables (questions), subjects, and time. We use the orbit method to represent binary multivariate longitudinal data (BMLD) of each household as a two-dimensional orbit and to visualise dynamics and behaviour of the population. At each time step, a point (x, y) from the orbit of a household corresponds to the observation of the household, where x is a binary sequence of responses and y is an ordering of variables. The ordering of variables is dynamically rearranged such that clusters and holes associated to least and frequently changing variables in the state space respectively, are exposed. Analysis of orbits reveals information of change at both individual- and population-level, change patterns in the data, capacity of states in the state space, and density of state transitions in the orbits. Analysis of household orbits of the four subpopulations show association between (i) households headed by older adults and rich households, (ii) large household size and poor households, and (iii) households with more minors than adults and poor households. Our results are compared to other methods of BMLD analysis. PMID:25919116

Sensitivity of solar-cell performance to atmospheric variables. 2: Dissimilar cells at several locations

NASA Technical Reports Server (NTRS)

Klucher, T. M.; Hart, R. E.

1976-01-01

Several solar cells having dissimilar spectral response curves and cell construction were measured at various locations in the United States to determine sensitivity of cell performance to atmospheric water vapor and turbidity. The locations selected represent a broad range of summer atmospheric conditions, from clear and dry to turbid and humid. Cell short circuit current under direct normal incidence sunlight, the intensity, water vapor and turbidity were measured. Regression equations were developed from the limited data base in order to provide a single method of prediction of cell current sensitivity to the atmospheric variables.

Global Diffusion Pattern and Hot SPOT Analysis of Vaccine-Preventable Diseases

NASA Astrophysics Data System (ADS)

Jiang, Y.; Fan, F.; Zanoni, I. Holly; Li, Y.

2017-10-01

Spatial characteristics reveal the concentration of vaccine-preventable disease in Africa and the Near East and that disease dispersion is variable depending on disease. The exception is whooping cough, which has a highly variable center of concentration from year to year. Measles exhibited the only statistically significant spatial autocorrelation among all the diseases under investigation. Hottest spots of measles are in Africa and coldest spots are in United States, warm spots are in Near East and cool spots are in Western Europe. Finally, cases of measles could not be explained by the independent variables, including Gini index, health expenditure, or rate of immunization. Since the literature confirms that each of the selected variables is considered determinants of disease dissemination, it is anticipated that the global dataset of disease cases was influenced by reporting bias.

The State and Level of Involvement among Jordanian Kindergarten Parents and Its Relationship to Teachers' Efforts of Outreach

ERIC Educational Resources Information Center

Fayez, Merfat; Sabah, Saed A.; Rudwan, Enaam Abu

2011-01-01

This study explored both the school- and home-based involvement practices of parents of children attending kindergarten in the city of Zarqa, Jordan. The study also examined the effect of some selected parental demographic variables (i.e. socioeconomic levels and levels of education) on parent involvement and the relationship between kindergarten…

The Utilization of Social Services by the Mexican-American Elderly.

ERIC Educational Resources Information Center

Starrett, Richard A.; Decker, James T.

The study tested the Andersen-Newman causal model of social service use as a means of determining patterns for social service use by Mexican American elderly. The model was shown to have applicability for identifying common and unique determinants of service use. Thirty-seven variables and data from a 1979-80 15-state survey were selected to form…

Design sensitivity analysis of rotorcraft airframe structures for vibration reduction

NASA Technical Reports Server (NTRS)

Murthy, T. Sreekanta

1987-01-01

Optimization of rotorcraft structures for vibration reduction was studied. The objective of this study is to develop practical computational procedures for structural optimization of airframes subject to steady-state vibration response constraints. One of the key elements of any such computational procedure is design sensitivity analysis. A method for design sensitivity analysis of airframes under vibration response constraints is presented. The mathematical formulation of the method and its implementation as a new solution sequence in MSC/NASTRAN are described. The results of the application of the method to a simple finite element stick model of the AH-1G helicopter airframe are presented and discussed. Selection of design variables that are most likely to bring about changes in the response at specified locations in the airframe is based on consideration of forced response strain energy. Sensitivity coefficients are determined for the selected design variable set. Constraints on the natural frequencies are also included in addition to the constraints on the steady-state response. Sensitivity coefficients for these constraints are determined. Results of the analysis and insights gained in applying the method to the airframe model are discussed. The general nature of future work to be conducted is described.

Reprogrammable read only variable threshold transistor memory with isolated addressing buffer

DOEpatents

Lodi, Robert J.

1976-01-01

A monolithic integrated circuit, fully decoded memory comprises a rectangular array of variable threshold field effect transistors organized into a plurality of multi-bit words. Binary address inputs to the memory are decoded by a field effect transistor decoder into a plurality of word selection lines each of which activates an address buffer circuit. Each address buffer circuit, in turn, drives a word line of the memory array. In accordance with the word line selected by the decoder the activated buffer circuit directs reading or writing voltages to the transistors comprising the memory words. All of the buffer circuits additionally are connected to a common terminal for clearing all of the memory transistors to a predetermined state by the application to the common terminal of a large magnitude voltage of a predetermined polarity. The address decoder, the buffer and the memory array, as well as control and input/output control and buffer field effect transistor circuits, are fabricated on a common substrate with means provided to isolate the substrate of the address buffer transistors from the remainder of the substrate so that the bulk clearing function of simultaneously placing all of the memory transistors into a predetermined state can be performed.

Age-related change in renal corticomedullary differentiation: evaluation with noncontrast-enhanced steady-state free precession (SSFP) MRI with spatially selective inversion pulse using variable inversion time.

PubMed

Noda, Yasufumi; Kanki, Akihiko; Yamamoto, Akira; Higashi, Hiroki; Tanimoto, Daigo; Sato, Tomohiro; Higaki, Atsushi; Tamada, Tsutomu; Ito, Katsuyoshi

2014-07-01

To evaluate age-related change in renal corticomedullary differentiation and renal cortical thickness by means of noncontrast-enhanced steady-state free precession (SSFP) magnetic resonance imaging (MRI) with spatially selective inversion recovery (IR) pulse. The Institutional Review Board of our hospital approved this retrospective study and patient informed consent was waived. This study included 48 patients without renal diseases who underwent noncontrast-enhanced SSFP MRI with spatially selective IR pulse using variable inversion times (TIs) (700-1500 msec). The signal intensity of renal cortex and medulla were measured to calculate renal corticomedullary contrast ratio. Additionally, renal cortical thickness was measured. The renal corticomedullary junction was clearly depicted in all patients. The mean cortical thickness was 3.9 ± 0.83 mm. The mean corticomedullary contrast ratio was 4.7 ± 1.4. There was a negative correlation between optimal TI for the best visualization of renal corticomedullary differentiation and age (r = -0.378; P = 0.001). However, there was no significant correlation between renal corticomedullary contrast ratio and age (r = 0.187; P = 0.20). Similarly, no significant correlation was observed between renal cortical thickness and age (r = 0.054; P = 0.712). In the normal kidney, noncontrast-enhanced SSFP MRI with spatially selective IR pulse can be used to assess renal corticomedullary differentiation and cortical thickness without the influence of aging, although optimal TI values for the best visualization of renal corticomedullary junction were shortened with aging. © 2013 Wiley Periodicals, Inc.

Spatiotemporal variability of snow depletion curves derived from SNODAS for the conterminous United States, 2004-2013

USGS Publications Warehouse

Driscoll, Jessica; Hay, Lauren E.; Bock, Andrew R.

2017-01-01

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental-scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental-extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1-km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed-scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed-scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national-scale categorization of snowmelt processes.

Application of recurrence quantification analysis to automatically estimate infant sleep states using a single channel of respiratory data.

PubMed

Terrill, Philip I; Wilson, Stephen J; Suresh, Sadasivam; Cooper, David M; Dakin, Carolyn

2012-08-01

Previous work has identified that non-linear variables calculated from respiratory data vary between sleep states, and that variables derived from the non-linear analytical tool recurrence quantification analysis (RQA) are accurate infant sleep state discriminators. This study aims to apply these discriminators to automatically classify 30 s epochs of infant sleep as REM, non-REM and wake. Polysomnograms were obtained from 25 healthy infants at 2 weeks, 3, 6 and 12 months of age, and manually sleep staged as wake, REM and non-REM. Inter-breath interval data were extracted from the respiratory inductive plethysmograph, and RQA applied to calculate radius, determinism and laminarity. Time-series statistic and spectral analysis variables were also calculated. A nested cross-validation method was used to identify the optimal feature subset, and to train and evaluate a linear discriminant analysis-based classifier. The RQA features radius and laminarity and were reliably selected. Mean agreement was 79.7, 84.9, 84.0 and 79.2 % at 2 weeks, 3, 6 and 12 months, and the classifier performed better than a comparison classifier not including RQA variables. The performance of this sleep-staging tool compares favourably with inter-human agreement rates, and improves upon previous systems using only respiratory data. Applications include diagnostic screening and population-based sleep research.

Selectivity of physiotherapist programs in the United States does not differ by institutional funding source or research activity level.

PubMed

Riley, Sean P; Covington, Kyle; Landry, Michel D; McCallum, Christine; Engelhard, Chalee; Cook, Chad E

2016-01-01

This study aimed to compare selectivity characteristics among institution characteristics to determine differences by institutional funding source (public vs. private) or research activity level (research vs. non-research). This study included information provided by the Commission on Accreditation in Physical Therapy Education (CAPTE) and the Federation of State Boards of Physical Therapy. Data were extracted from all students who graduated in 2011 from accredited physical therapy programs in the United States. The public and private designations of the institutions were extracted directly from the classifications from the 'CAPTE annual accreditation report,' and high and low research activity was determined based on Carnegie classifications. The institutions were classified into four groups: public/research intensive, public/non-research intensive, private/research intensive, and private/non-research intensive. Descriptive and comparison analyses with post hoc testing were performed to determine whether there were statistically significant differences among the four groups. Although there were statistically significant baseline grade point average differences among the four categorized groups, there were no significant differences in licensure pass rates or for any of the selectivity variables of interest. Selectivity characteristics did not differ by institutional funding source (public vs. private) or research activity level (research vs. non-research). This suggests that the concerns about reduced selectivity among physiotherapy programs, specifically the types that are experiencing the largest proliferation, appear less warranted.

Quantifying Variability of Avian Colours: Are Signalling Traits More Variable?

PubMed Central

Delhey, Kaspar; Peters, Anne

2008-01-01

Background Increased variability in sexually selected ornaments, a key assumption of evolutionary theory, is thought to be maintained through condition-dependence. Condition-dependent handicap models of sexual selection predict that (a) sexually selected traits show amplified variability compared to equivalent non-sexually selected traits, and since males are usually the sexually selected sex, that (b) males are more variable than females, and (c) sexually dimorphic traits more variable than monomorphic ones. So far these predictions have only been tested for metric traits. Surprisingly, they have not been examined for bright coloration, one of the most prominent sexual traits. This omission stems from computational difficulties: different types of colours are quantified on different scales precluding the use of coefficients of variation. Methodology/Principal Findings Based on physiological models of avian colour vision we develop an index to quantify the degree of discriminable colour variation as it can be perceived by conspecifics. A comparison of variability in ornamental and non-ornamental colours in six bird species confirmed (a) that those coloured patches that are sexually selected or act as indicators of quality show increased chromatic variability. However, we found no support for (b) that males generally show higher levels of variability than females, or (c) that sexual dichromatism per se is associated with increased variability. Conclusions/Significance We show that it is currently possible to realistically estimate variability of animal colours as perceived by them, something difficult to achieve with other traits. Increased variability of known sexually-selected/quality-indicating colours in the studied species, provides support to the predictions borne from sexual selection theory but the lack of increased overall variability in males or dimorphic colours in general indicates that sexual differences might not always be shaped by similar selective forces. PMID:18301766

A Robust Decision-Making Technique for Water Management under Decadal Scale Climate Variability

NASA Astrophysics Data System (ADS)

Callihan, L.; Zagona, E. A.; Rajagopalan, B.

2013-12-01

Robust decision making, a flexible and dynamic approach to managing water resources in light of deep uncertainties associated with climate variability at inter-annual to decadal time scales, is an analytical framework that detects when a system is in or approaching a vulnerable state. It provides decision makers the opportunity to implement strategies that both address the vulnerabilities and perform well over a wide range of plausible future scenarios. A strategy that performs acceptably over a wide range of possible future states is not likely to be optimal with respect to the actual future state. The degree of success--the ability to avoid vulnerable states and operate efficiently--thus depends on the skill in projecting future states and the ability to select the most efficient strategies to address vulnerabilities. This research develops a robust decision making framework that incorporates new methods of decadal scale projections with selection of efficient strategies. Previous approaches to water resources planning under inter-annual climate variability combining skillful seasonal flow forecasts with climatology for subsequent years are not skillful for medium term (i.e. decadal scale) projections as decision makers are not able to plan adequately to avoid vulnerabilities. We address this need by integrating skillful decadal scale streamflow projections into the robust decision making framework and making the probability distribution of this projection available to the decision making logic. The range of possible future hydrologic scenarios can be defined using a variety of nonparametric methods. Once defined, an ensemble projection of decadal flow scenarios are generated from a wavelet-based spectral K-nearest-neighbor resampling approach using historical and paleo-reconstructed data. This method has been shown to generate skillful medium term projections with a rich variety of natural variability. The current state of the system in combination with the probability distribution of the projected flow ensembles enables the selection of appropriate decision options. This process is repeated for each year of the planning horizon--resulting in system outcomes that can be evaluated on their performance and resiliency. The research utilizes the RiverSMART suite of software modeling and analysis tools developed under the Bureau of Reclamation's WaterSMART initiative and built around the RiverWare modeling environment. A case study is developed for the Gunnison and Upper Colorado River Basins. The ability to mitigate vulnerability using the framework is gauged by system performance indicators that measure the ability of the system to meet various water demands (i.e. agriculture, environmental flows, hydropower etc.). Options and strategies for addressing vulnerabilities include measures such as conservation, reallocation and adjustments to operational policy. In addition to being able to mitigate vulnerabilities, options and strategies are evaluated based on benefits, costs and reliability. Flow ensembles are also simulated to incorporate mean and variance from climate change projections for the planning horizon and the above robust decision-making framework is applied to evaluate its performance under changing climate.

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Continuous operation of four-state continuous-variable quantum key distribution system

NASA Astrophysics Data System (ADS)

Matsubara, Takuto; Ono, Motoharu; Oguri, Yusuke; Ichikawa, Tsubasa; Hirano, Takuya; Kasai, Kenta; Matsumoto, Ryutaroh; Tsurumaru, Toyohiro

2016-10-01

We report on the development of continuous-variable quantum key distribution (CV-QKD) system that are based on discrete quadrature amplitude modulation (QAM) and homodyne detection of coherent states of light. We use a pulsed light source whose wavelength is 1550 nm and repetition rate is 10 MHz. The CV-QKD system can continuously generate secret key which is secure against entangling cloner attack. Key generation rate is 50 kbps when the quantum channel is a 10 km optical fiber. The CV-QKD system we have developed utilizes the four-state and post-selection protocol [T. Hirano, et al., Phys. Rev. A 68, 042331 (2003).]; Alice randomly sends one of four states {|+/-α⟩,|+/-𝑖α⟩}, and Bob randomly performs x- or p- measurement by homodyne detection. A commercially available balanced receiver is used to realize shot-noise-limited pulsed homodyne detection. GPU cards are used to accelerate the software-based post-processing. We use a non-binary LDPC code for error correction (reverse reconciliation) and the Toeplitz matrix multiplication for privacy amplification.

BSL-3 laboratory practices in the United States: comparison of select agent and non-select agent facilities.

PubMed

Richards, Stephanie L; Pompei, Victoria C; Anderson, Alice

2014-01-01

New construction of biosafety level 3 (BSL-3) laboratories in the United States has increased in the past decade to facilitate research on potential bioterrorism agents. The Centers for Disease Control and Prevention inspect BSL-3 facilities and review commissioning documentation, but no single agency has oversight over all BSL-3 facilities. This article explores the extent to which standard operating procedures in US BSL-3 facilities vary between laboratories with select agent or non-select agent status. Comparisons are made for the following variables: personnel training, decontamination, personal protective equipment (PPE), medical surveillance, security access, laboratory structure and maintenance, funding, and pest management. Facilities working with select agents had more complex training programs and decontamination procedures than non-select agent facilities. Personnel working in select agent laboratories were likely to use powered air purifying respirators, while non-select agent laboratories primarily used N95 respirators. More rigorous medical surveillance was carried out in select agent workers (although not required by the select agent program) and a higher level of restrictive access to laboratories was found. Most select agent and non-select agent laboratories reported adequate structural integrity in facilities; however, differences were observed in personnel perception of funding for repairs. Pest management was carried out by select agent personnel more frequently than non-select agent personnel. Our findings support the need to promote high quality biosafety training and standard operating procedures in both select agent and non-select agent laboratories to improve occupational health and safety.

BSL-3 Laboratory Practices in the United States: Comparison of Select Agent and Non–Select Agent Facilities

PubMed Central

Pompei, Victoria C.; Anderson, Alice

2014-01-01

New construction of biosafety level 3 (BSL-3) laboratories in the United States has increased in the past decade to facilitate research on potential bioterrorism agents. The Centers for Disease Control and Prevention inspect BSL-3 facilities and review commissioning documentation, but no single agency has oversight over all BSL-3 facilities. This article explores the extent to which standard operating procedures in US BSL-3 facilities vary between laboratories with select agent or non–select agent status. Comparisons are made for the following variables: personnel training, decontamination, personal protective equipment (PPE), medical surveillance, security access, laboratory structure and maintenance, funding, and pest management. Facilities working with select agents had more complex training programs and decontamination procedures than non–select agent facilities. Personnel working in select agent laboratories were likely to use powered air purifying respirators, while non–select agent laboratories primarily used N95 respirators. More rigorous medical surveillance was carried out in select agent workers (although not required by the select agent program) and a higher level of restrictive access to laboratories was found. Most select agent and non–select agent laboratories reported adequate structural integrity in facilities; however, differences were observed in personnel perception of funding for repairs. Pest management was carried out by select agent personnel more frequently than non–select agent personnel. Our findings support the need to promote high quality biosafety training and standard operating procedures in both select agent and non–select agent laboratories to improve occupational health and safety. PMID:24552359

Implementation of continuous-variable quantum key distribution with discrete modulation

NASA Astrophysics Data System (ADS)

Hirano, Takuya; Ichikawa, Tsubasa; Matsubara, Takuto; Ono, Motoharu; Oguri, Yusuke; Namiki, Ryo; Kasai, Kenta; Matsumoto, Ryutaroh; Tsurumaru, Toyohiro

2017-06-01

We have developed a continuous-variable quantum key distribution (CV-QKD) system that employs discrete quadrature-amplitude modulation and homodyne detection of coherent states of light. We experimentally demonstrated automated secure key generation with a rate of 50 kbps when a quantum channel is a 10 km optical fibre. The CV-QKD system utilises a four-state and post-selection protocol and generates a secure key against the entangling cloner attack. We used a pulsed light source of 1550 nm wavelength with a repetition rate of 10 MHz. A commercially available balanced receiver is used to realise shot-noise-limited pulsed homodyne detection. We used a non-binary LDPC code for error correction (reverse reconciliation) and the Toeplitz matrix multiplication for privacy amplification. A graphical processing unit card is used to accelerate the software-based post-processing.

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

Aaboud, M.; Aad, G.; Abbott, B.

A measurement of the inclusive p p → tmore » $$\\bar{t}$$ + X production cross section in the τ + jets final state using only the hadronic decays of the τ lepton is presented. The measurement is performed using 20.2 fb -1 of proton-proton collision data recorded at a center-of-mass energy of √ s = 8 TeV with the ATLAS detector at the Large Hadron Collider. The cross section is measured via a counting experiment by imposing a set of selection criteria on the identification and kinematic variables of the reconstructed particles and jets, and on event kinematic variables and characteristics. The production cross section is measured to be σ t $$\\bar{t}$$ = 239 ± 29 pb , which is in agreement with the measurements in other final states and the theoretical predictions at this center-of-mass energy.« less

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

Aaboud, M.; Aad, G.; Abbott, B.

A measurement of the inclusive pp →more » $$t\\bar{t}$$ + X production cross section in the τ+jets final state using only the hadronic decays of the τ lepton is presented. The measurement is performed using 20.2 fb –1 of proton-proton collision data recorded at a center-of-mass energy of √s = 8 TeV with the ATLAS detector at the Large Hadron Collider. The cross section is measured via a counting experiment by imposing a set of selection criteria on the identification and kinematic variables of the reconstructed particles and jets, and on event kinematic variables and characteristics. Here, the production cross section is measured to be σ $$t\\bar{t}$$ = 239 ± 29 pb, which is in agreement with the measurements in other final states and the theoretical predictions at this center-of-mass energy.« less

Reactibodies generated by kinetic selection couple chemical reactivity with favorable protein dynamics

PubMed Central

Smirnov, Ivan; Carletti, Eugénie; Kurkova, Inna; Nachon, Florian; Nicolet, Yvain; Mitkevich, Vladimir A.; Débat, Hélène; Avalle, Bérangère; Belogurov, Alexey A.; Kuznetsov, Nikita; Reshetnyak, Andrey; Masson, Patrick; Tonevitsky, Alexander G.; Ponomarenko, Natalia; Makarov, Alexander A.; Friboulet, Alain; Tramontano, Alfonso; Gabibov, Alexander

2011-01-01

Igs offer a versatile template for combinatorial and rational design approaches to the de novo creation of catalytically active proteins. We have used a covalent capture selection strategy to identify biocatalysts from within a human semisynthetic antibody variable fragment library that uses a nucleophilic mechanism. Specific phosphonylation at a single tyrosine within the variable light-chain framework was confirmed in a recombinant IgG construct. High-resolution crystallographic structures of unmodified and phosphonylated Fabs display a 15-Å-deep two-chamber cavity at the interface of variable light (VL) and variable heavy (VH) fragments having a nucleophilic tyrosine at the base of the site. The depth and structure of the pocket are atypical of antibodies in general but can be compared qualitatively with the catalytic site of cholinesterases. A structurally disordered heavy chain complementary determining region 3 loop, constituting a wall of the cleft, is stabilized after covalent modification by hydrogen bonding to the phosphonate tropinol moiety. These features and presteady state kinetics analysis indicate that an induced fit mechanism operates in this reaction. Mutations of residues located in this stabilized loop do not interfere with direct contacts to the organophosphate ligand but can interrogate second shell interactions, because the H3 loop has a conformation adjusted for binding. Kinetic and thermodynamic parameters along with computational docking support the active site model, including plasticity and simple catalytic components. Although relatively uncomplicated, this catalytic machinery displays both stereo- and chemical selectivity. The organophosphate pesticide paraoxon is hydrolyzed by covalent catalysis with rate-limiting dephosphorylation. This reactibody is, therefore, a kinetically selected protein template that has enzyme-like catalytic attributes. PMID:21896761

Quantifying human disturbance in watersheds: Variable selection and performance of a GIS-based disturbance index for predicting the biological condition of perennial streams

USGS Publications Warehouse

Falcone, James A.; Carlisle, Daren M.; Weber, Lisa C.

2010-01-01

Characterizing the relative severity of human disturbance in watersheds is often part of stream assessments and is frequently done with the aid of Geographic Information System (GIS)-derived data. However, the choice of variables and how they are used to quantify disturbance are often subjective. In this study, we developed a number of disturbance indices by testing sets of variables, scoring methods, and weightings of 33 potential disturbance factors derived from readily available GIS data. The indices were calibrated using 770 watersheds located in the western United States for which the severity of disturbance had previously been classified from detailed local data by the United States Environmental Protection Agency (USEPA) Environmental Monitoring and Assessment Program (EMAP). The indices were calibrated by determining which variable or variable combinations and aggregation method best differentiated between least- and most-disturbed sites. Indices composed of several variables performed better than any individual variable, and best results came from a threshold method of scoring using six uncorrelated variables: housing unit density, road density, pesticide application, dam storage, land cover along a mainstem buffer, and distance to nearest canal/pipeline. The final index was validated with 192 withheld watersheds and correctly classified about two-thirds (68%) of least- and most-disturbed sites. These results provide information about the potential for using a disturbance index as a screening tool for a priori ranking of watersheds at a regional/national scale, and which landscape variables and methods of combination may be most helpful in doing so.

Measurement of the t t ¯ production cross section in the τ + jets final state in p p collisions at s = 8 TeV using the ATLAS detector

DOE PAGES

Aaboud, M.; Aad, G.; Abbott, B.; ...

2017-04-07

A measurement of the inclusive pp →more » $$t\\bar{t}$$ + X production cross section in the τ+jets final state using only the hadronic decays of the τ lepton is presented. The measurement is performed using 20.2 fb –1 of proton-proton collision data recorded at a center-of-mass energy of √s = 8 TeV with the ATLAS detector at the Large Hadron Collider. The cross section is measured via a counting experiment by imposing a set of selection criteria on the identification and kinematic variables of the reconstructed particles and jets, and on event kinematic variables and characteristics. Here, the production cross section is measured to be σ $$t\\bar{t}$$ = 239 ± 29 pb, which is in agreement with the measurements in other final states and the theoretical predictions at this center-of-mass energy.« less

Design of state-feedback controllers including sensitivity reduction, with applications to precision pointing

NASA Technical Reports Server (NTRS)

Hadass, Z.

1974-01-01

The design procedure of feedback controllers was described and the considerations for the selection of the design parameters were given. The frequency domain properties of single-input single-output systems using state feedback controllers are analyzed, and desirable phase and gain margin properties are demonstrated. Special consideration is given to the design of controllers for tracking systems, especially those designed to track polynomial commands. As an example, a controller was designed for a tracking telescope with a polynomial tracking requirement and some special features such as actuator saturation and multiple measurements, one of which is sampled. The resulting system has a tracking performance comparing favorably with a much more complicated digital aided tracker. The parameter sensitivity reduction was treated by considering the variable parameters as random variables. A performance index is defined as a weighted sum of the state and control convariances that sum from both the random system disturbances and the parameter uncertainties, and is minimized numerically by adjusting a set of free parameters.

Measurement of the t t ¯ production cross section in the τ +jets final state in p p collisions at √{s }=8 TeV using the ATLAS detector

NASA Astrophysics Data System (ADS)

Aaboud, M.; Aad, G.; Abbott, B.; Abdallah, J.; Abdinov, O.; Abeloos, B.; Abouzeid, O. S.; Abraham, N. L.; Abramowicz, H.; Abreu, H.; Abreu, R.; Abulaiti, Y.; Acharya, B. S.; Adachi, S.; Adamczyk, L.; Adams, D. L.; Adelman, J.; Adomeit, S.; Adye, T.; Affolder, A. A.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Akerstedt, H.; Åkesson, T. P. A.; Akimov, A. V.; Alberghi, G. L.; Albert, J.; Albrand, S.; Alconada Verzini, M. J.; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexopoulos, T.; Alhroob, M.; Ali, B.; Aliev, M.; Alimonti, G.; Alison, J.; Alkire, S. P.; Allbrooke, B. M. M.; Allen, B. W.; Allport, P. P.; Aloisio, A.; Alonso, A.; Alonso, F.; Alpigiani, C.; Alshehri, A. A.; Alstaty, M.; Alvarez Gonzalez, B.; Álvarez Piqueras, D.; Alviggi, M. G.; Amadio, B. T.; Amaral Coutinho, Y.; Amelung, C.; Amidei, D.; Amor Dos Santos, S. P.; Amorim, A.; Amoroso, S.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, J. K.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Angelidakis, S.; Angelozzi, I.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antel, C.; Antonelli, M.; Antonov, A.; Antrim, D. J.; Anulli, F.; Aoki, M.; Aperio Bella, L.; Arabidze, G.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arduh, F. A.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Armitage, L. J.; Arnaez, O.; Arnold, H.; Arratia, M.; Arslan, O.; Artamonov, A.; Artoni, G.; Artz, S.; Asai, S.; Asbah, N.; Ashkenazi, A.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Augsten, K.; Avolio, G.; Axen, B.; Ayoub, M. K.; Azuelos, G.; Baak, M. A.; Baas, A. E.; Baca, M. J.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Baines, J. T.; Bajic, M.; Baker, O. K.; Baldin, E. M.; Balek, P.; Balestri, T.; Balli, F.; Balunas, W. K.; Banas, E.; Banerjee, Sw.; Bannoura, A. A. E.; Barak, L.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisits, M.-S.; Barklow, T.; Barlow, N.; Barnes, S. L.; Barnett, B. M.; Barnett, R. M.; Barnovska-Blenessy, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barranco Navarro, L.; Barreiro, F.; Barreiro Guimarães da Costa, J.; Bartoldus, R.; Barton, A. E.; Bartos, P.; Basalaev, A.; Bassalat, A.; Bates, R. L.; Batista, S. J.; Batley, J. R.; Battaglia, M.; Bauce, M.; Bauer, F.; Bawa, H. S.; Beacham, J. B.; Beattie, M. D.; Beau, T.; Beauchemin, P. H.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, M.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bednyakov, V. A.; Bedognetti, M.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, J. K.; Bell, A. S.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belotskiy, K.; Beltramello, O.; Belyaev, N. L.; Benary, O.; Benchekroun, D.; Bender, M.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Benhar Noccioli, E.; Benitez, J.; Benjamin, D. P.; Bensinger, J. R.; Bentvelsen, S.; Beresford, L.; Beretta, M.; Berge, D.; Bergeaas Kuutmann, E.; Berger, N.; Beringer, J.; Berlendis, S.; Bernard, N. R.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertoli, G.; Bertolucci, F.; Bertram, I. A.; Bertsche, C.; Bertsche, D.; Besjes, G. J.; Bessidskaia Bylund, O.; Bessner, M.; Besson, N.; Betancourt, C.; Bethani, A.; Bethke, S.; Bevan, A. J.; Bianchi, R. M.; Bianco, M.; Biebel, O.; Biedermann, D.; Bielski, R.; Biesuz, N. V.; Biglietti, M.; Bilbao de Mendizabal, J.; Billoud, T. R. V.; Bilokon, H.; Bindi, M.; Bingul, A.; Bini, C.; Biondi, S.; Bisanz, T.; Bjergaard, D. M.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blazek, T.; Bloch, I.; Blocker, C.; Blue, A.; Blum, W.; Blumenschein, U.; Blunier, S.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. S.; Bocci, A.; Bock, C.; Boehler, M.; Boerner, D.; Bogaerts, J. A.; Bogavac, D.; Bogdanchikov, A. G.; Bohm, C.; Boisvert, V.; Bokan, P.; Bold, T.; Boldyrev, A. S.; Bomben, M.; Bona, M.; Boonekamp, M.; Borisov, A.; Borissov, G.; Bortfeldt, J.; Bortoletto, D.; Bortolotto, V.; Bos, K.; Boscherini, D.; Bosman, M.; Bossio Sola, J. D.; Boudreau, J.; Bouffard, J.; Bouhova-Thacker, E. V.; Boumediene, D.; Bourdarios, C.; Boutle, S. K.; Boveia, A.; Boyd, J.; Boyko, I. R.; Bracinik, J.; Brandt, A.; Brandt, G.; Brandt, O.; Bratzler, U.; Brau, B.; Brau, J. E.; Breaden Madden, W. D.; Brendlinger, K.; Brennan, A. J.; Brenner, L.; Brenner, R.; Bressler, S.; Bristow, T. M.; Britton, D.; Britzger, D.; Brochu, F. M.; Brock, I.; Brock, R.; Brooijmans, G.; Brooks, T.; Brooks, W. K.; Brosamer, J.; Brost, E.; Broughton, J. H.; Bruckman de Renstrom, P. A.; Bruncko, D.; Bruneliere, R.; Bruni, A.; Bruni, G.; Bruni, L. S.; Brunt, Bh; Bruschi, M.; Bruscino, N.; Bryant, P.; Bryngemark, L.; Buanes, T.; Buat, Q.; Buchholz, P.; Buckley, A. G.; Budagov, I. A.; Buehrer, F.; Bugge, M. K.; Bulekov, O.; Bullock, D.; Burckhart, H.; Burdin, S.; Burgard, C. D.; Burger, A. 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A.; Timoshenko, S.; Tipton, P.; Tisserant, S.; Todome, K.; Todorov, T.; Todorova-Nova, S.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tolley, E.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Tong, B.; Tornambe, P.; Torrence, E.; Torres, H.; Torró Pastor, E.; Toth, J.; Touchard, F.; Tovey, D. R.; Trefzger, T.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Trischuk, W.; Trocmé, B.; Trofymov, A.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; Truong, L.; Trzebinski, M.; Trzupek, A.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsui, K. M.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tu, Y.; Tudorache, A.; Tudorache, V.; Tulbure, T. T.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turgeman, D.; Turk Cakir, I.; Turra, R.; Tuts, P. M.; Ucchielli, G.; Ueda, I.; Ughetto, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Unverdorben, C.; Urban, J.; Urquijo, P.; Urrejola, P.; Usai, G.; Usui, J.; Vacavant, L.; Vacek, V.; Vachon, B.; Valderanis, C.; Valdes Santurio, E.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Valls Ferrer, J. A.; van den Wollenberg, W.; van der Deijl, P. C.; van der Graaf, H.; van Eldik, N.; van Gemmeren, P.; van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vanguri, R.; Vaniachine, A.; Vankov, P.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vasquez, J. G.; Vasquez, G. A.; Vazeille, F.; Vazquez Schroeder, T.; Veatch, J.; Veeraraghavan, V.; Veloce, L. M.; Veloso, F.; Veneziano, S.; Ventura, A.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Vickey Boeriu, O. E.; Viehhauser, G. H. A.; Viel, S.; Vigani, L.; Villa, M.; Villaplana Perez, M.; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Vittori, C.; Vivarelli, I.; Vlachos, S.; Vlasak, M.; Vogel, M.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; von Toerne, E.; Vorobel, V.; Vorobev, K.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Vranjes Milosavljevic, M.; Vrba, V.; Vreeswijk, M.; Vuillermet, R.; Vukotic, I.; Wagner, P.; Wagner, W.; Wahlberg, H.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wallangen, V.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, W.; Wanotayaroj, C.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Washbrook, A.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Weber, S. A.; Webster, J. S.; Weidberg, A. R.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M. D.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; Whallon, N. L.; Wharton, A. M.; White, A.; White, M. J.; White, R.; Whiteson, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wildauer, A.; Wilk, F.; Wilkens, H. G.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, J. A.; Wingerter-Seez, I.; Winklmeier, F.; Winston, O. J.; Winter, B. T.; Wittgen, M.; Wobisch, M.; Wolf, T. M. H.; Wolff, R.; Wolter, M. W.; Wolters, H.; Worm, S. D.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wu, M.; Wu, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xi, Z.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamaguchi, D.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, S.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, Y.; Yang, Z.; Yao, W.-M.; Yap, Y. C.; Yasu, Y.; Yatsenko, E.; Yau Wong, K. H.; Ye, J.; Ye, S.; Yeletskikh, I.; Yildirim, E.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yuen, S. P. Y.; Yusuff, I.; Zabinski, B.; Zacharis, G.; Zaidan, R.; Zaitsev, A. M.; Zakharchuk, N.; Zalieckas, J.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zeng, J. C.; Zeng, Q.; Zenin, O.; Ženiš, T.; Zerwas, D.; Zhang, D.; Zhang, F.; Zhang, G.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, L.; Zhang, M.; Zhang, R.; Zhang, R.; Zhang, X.; Zhang, Y.; Zhang, Z.; Zhao, X.; Zhao, Y.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, C.; Zhou, L.; Zhou, L.; Zhou, M.; Zhou, M.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zhukov, K.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, S.; Zinonos, Z.; Zinser, M.; Ziolkowski, M.; Živković, L.; Zobernig, G.; Zoccoli, A.; Zur Nedden, M.; Zwalinski, L.; Atlas Collaboration

2017-04-01

A measurement of the inclusive p p →t t ¯+X production cross section in the τ +jets final state using only the hadronic decays of the τ lepton is presented. The measurement is performed using 20.2 fb-1 of proton-proton collision data recorded at a center-of-mass energy of √{s }=8 TeV with the ATLAS detector at the Large Hadron Collider. The cross section is measured via a counting experiment by imposing a set of selection criteria on the identification and kinematic variables of the reconstructed particles and jets, and on event kinematic variables and characteristics. The production cross section is measured to be σt t ¯=239 ±29 pb , which is in agreement with the measurements in other final states and the theoretical predictions at this center-of-mass energy.

Environmental diversity as a surrogate for species representation.

PubMed

Beier, Paul; de Albuquerque, Fábio Suzart

2015-10-01

Because many species have not been described and most species ranges have not been mapped, conservation planners often use surrogates for conservation planning, but evidence for surrogate effectiveness is weak. Surrogates are well-mapped features such as soil types, landforms, occurrences of an easily observed taxon (discrete surrogates), and well-mapped environmental conditions (continuous surrogate). In the context of reserve selection, the idea is that a set of sites selected to span diversity in the surrogate will efficiently represent most species. Environmental diversity (ED) is a rarely used surrogate that selects sites to efficiently span multivariate ordination space. Because it selects across continuous environmental space, ED should perform better than discrete surrogates (which necessarily ignore within-bin and between-bin heterogeneity). Despite this theoretical advantage, ED appears to have performed poorly in previous tests of its ability to identify 50 × 50 km cells that represented vertebrates in Western Europe. Using an improved implementation of ED, we retested ED on Western European birds, mammals, reptiles, amphibians, and combined terrestrial vertebrates. We also tested ED on data sets for plants of Zimbabwe, birds of Spain, and birds of Arizona (United States). Sites selected using ED represented European mammals no better than randomly selected cells, but they represented species in the other 7 data sets with 20% to 84% effectiveness. This far exceeds the performance in previous tests of ED, and exceeds the performance of most discrete surrogates. We believe ED performed poorly in previous tests because those tests considered only a few candidate explanatory variables and used suboptimal forms of ED's selection algorithm. We suggest future work on ED focus on analyses at finer grain sizes more relevant to conservation decisions, explore the effect of selecting the explanatory variables most associated with species turnover, and investigate whether nonclimate abiotic variables can provide useful surrogates in an ED framework. © 2015 Society for Conservation Biology.

Resolving the Conflict Between Associative Overdominance and Background Selection

PubMed Central

Zhao, Lei; Charlesworth, Brian

2016-01-01

In small populations, genetic linkage between a polymorphic neutral locus and loci subject to selection, either against partially recessive mutations or in favor of heterozygotes, may result in an apparent selective advantage to heterozygotes at the neutral locus (associative overdominance) and a retardation of the rate of loss of variability by genetic drift at this locus. In large populations, selection against deleterious mutations has previously been shown to reduce variability at linked neutral loci (background selection). We describe analytical, numerical, and simulation studies that shed light on the conditions under which retardation vs. acceleration of loss of variability occurs at a neutral locus linked to a locus under selection. We consider a finite, randomly mating population initiated from an infinite population in equilibrium at a locus under selection. With mutation and selection, retardation occurs only when S, the product of twice the effective population size and the selection coefficient, is of order 1. With S >> 1, background selection always causes an acceleration of loss of variability. Apparent heterozygote advantage at the neutral locus is, however, always observed when mutations are partially recessive, even if there is an accelerated rate of loss of variability. With heterozygote advantage at the selected locus, loss of variability is nearly always retarded. The results shed light on experiments on the loss of variability at marker loci in laboratory populations and on the results of computer simulations of the effects of multiple selected loci on neutral variability. PMID:27182952

Relationships among selected physical science misconceptions held by preservice elementary teachers and four variables: Formal reasoning ability, working memory capacity, verbal intelligence, and field dependence/independence

NASA Astrophysics Data System (ADS)

Griffin, Leslie Little

The purpose of this study was to determine the relationship of selected cognitive abilities and physical science misconceptions held by preservice elementary teachers. The cognitive abilities under investigation were: formal reasoning ability as measured by the Lawson Classroom Test of Formal Reasoning (Lawson, 1978); working memory capacity as measured by the Figural Intersection Test (Burtis & Pascual-Leone, 1974); verbal intelligence as measured by the Acorn National Academic Aptitude Test: Verbal Intelligence (Kobal, Wrightstone, & Kunze, 1944); and field dependence/independence as measured by the Group Embedded Figures Test (Witkin, Oltman, & Raskin, 1971). The number of physical science misconceptions held by preservice elementary teachers was measured by the Misconceptions in Science Questionnaire (Franklin, 1992). The data utilized in this investigation were obtained from 36 preservice elementary teachers enrolled in two sections of a science methods course at a small regional university in the southeastern United States. Multiple regression techniques were used to analyze the collected data. The following conclusions were reached following an analysis of the data. The variables of formal reasoning ability and verbal intelligence were identified as having significant relationships, both individually and in combination, to the dependent variable of selected physical science misconceptions. Though the correlations were not high enough to yield strong predictors of physical science misconceptions or strong relationships, they were of sufficient magnitude to warrant further investigation. It is recommended that further investigation be conducted replicating this study with a larger sample size. In addition, experimental research should be implemented to explore the relationships suggested in this study between the cognitive variables of formal reasoning ability and verbal intelligence and the dependent variable of selected physical science misconceptions. Further research should also focus on the detection of a broad range of science misconceptions among preservice elementary teachers.

Factors related to choosing an academic career track among spine fellowship applicants.

PubMed

Park, Daniel K; Rhee, John M; Wu, Baohua; Easley, Kirk

2013-03-01

Retrospective review. To identify factors associated with the likelihood of spine surgery fellowship applicants choosing an academic job upon fellowship completion. Training academic spine surgeons is an important goal of many spine fellowships. However, there are no established criteria associated with academic job choice to guide selection committees. Two hundred three consecutive applications of candidates who were granted an interview to a single spine surgical fellowship from 2005 to 2010 were analyzed. Factors investigated included the following: membership in honor societies; number of publications, presentations, and book chapters; age; completion of an additional degree; completion of a research fellowship; teaching experience; marital status; graduation from a top-20 school; attendance in a residency with a spine fellowship; and comments made in personal statements and letters of recommendation. The job taken upon graduation from fellowship was determined. The χ2 test or Fisher exact test was used to estimate the strength of the association between the covariates and response. Significant variables were selected for further multivariate analysis. The following were significantly associated in a univariable analysis with academia: 5 or more national presentations; completion of a research fellowship; attendance in a top-20 medical school; stated desire in the personal statement to become an academic surgeon; and letters of reference stating likelihood of pursuing academics on hiring the applicant. When significant variables were selected for multivariable analysis, completion of a research fellowship, graduation from a top-20 medical school, and stated desire in the personal statement to become an academic surgeon were most strongly associated with choice of academia. Although job choice is multifactorial, the present study demonstrates that there are objective factors listed on spine fellowship applications associated with a significantly higher likelihood of academic job choice. Analyzing these factors may help selection committees evaluate spine fellowship applicants consistent with the academic missions of their programs.

Virtual Machine Language 2.1

NASA Technical Reports Server (NTRS)

Riedel, Joseph E.; Grasso, Christopher A.

2012-01-01

VML (Virtual Machine Language) is an advanced computing environment that allows spacecraft to operate using mechanisms ranging from simple, time-oriented sequencing to advanced, multicomponent reactive systems. VML has developed in four evolutionary stages. VML 0 is a core execution capability providing multi-threaded command execution, integer data types, and rudimentary branching. VML 1 added named parameterized procedures, extensive polymorphism, data typing, branching, looping issuance of commands using run-time parameters, and named global variables. VML 2 added for loops, data verification, telemetry reaction, and an open flight adaptation architecture. VML 2.1 contains major advances in control flow capabilities for executable state machines. On the resource requirements front, VML 2.1 features a reduced memory footprint in order to fit more capability into modestly sized flight processors, and endian-neutral data access for compatibility with Intel little-endian processors. Sequence packaging has been improved with object-oriented programming constructs and the use of implicit (rather than explicit) time tags on statements. Sequence event detection has been significantly enhanced with multi-variable waiting, which allows a sequence to detect and react to conditions defined by complex expressions with multiple global variables. This multi-variable waiting serves as the basis for implementing parallel rule checking, which in turn, makes possible executable state machines. The new state machine feature in VML 2.1 allows the creation of sophisticated autonomous reactive systems without the need to develop expensive flight software. Users specify named states and transitions, along with the truth conditions required, before taking transitions. Transitions with the same signal name allow separate state machines to coordinate actions: the conditions distributed across all state machines necessary to arm a particular signal are evaluated, and once found true, that signal is raised. The selected signal then causes all identically named transitions in all present state machines to be taken simultaneously. VML 2.1 has relevance to all potential space missions, both manned and unmanned. It was under consideration for use on Orion.

Effects of non-neuronal components for functional connectivity analysis from resting-state functional MRI toward automated diagnosis of schizophrenia

NASA Astrophysics Data System (ADS)

Kim, Junghoe; Lee, Jong-Hwan

2014-03-01

A functional connectivity (FC) analysis from resting-state functional MRI (rsfMRI) is gaining its popularity toward the clinical application such as diagnosis of neuropsychiatric disease. To delineate the brain networks from rsfMRI data, non-neuronal components including head motions and physiological artifacts mainly observed in cerebrospinal fluid (CSF), white matter (WM) along with a global brain signal have been regarded as nuisance variables in calculating the FC level. However, it is still unclear how the non-neuronal components can affect the performance toward diagnosis of neuropsychiatric disease. In this study, a systematic comparison of classification performance of schizophrenia patients was provided employing the partial correlation coefficients (CCs) as feature elements. Pair-wise partial CCs were calculated between brain regions, in which six combinatorial sets of nuisance variables were considered. The partial CCs were used as candidate feature elements followed by feature selection based on the statistical significance test between two groups in the training set. Once a linear support vector machine was trained using the selected features from the training set, the classification performance was evaluated using the features from the test set (i.e. leaveone- out cross validation scheme). From the results, the error rate using all non-neuronal components as nuisance variables (12.4%) was significantly lower than those using remaining combination of non-neuronal components as nuisance variables (13.8 ~ 20.0%). In conclusion, the non-neuronal components substantially degraded the automated diagnosis performance, which supports our hypothesis that the non-neuronal components are crucial in controlling the automated diagnosis performance of the neuropsychiatric disease using an fMRI modality.

Interactive FORTRAN IV computer programs for the thermodynamic and transport properties of selected cryogens (fluids pack)

NASA Technical Reports Server (NTRS)

Mccarty, R. D.

1980-01-01

The thermodynamic and transport properties of selected cryogens had programmed into a series of computer routines. Input variables are any two of P, rho or T in the single phase regions and either P or T for the saturated liquid or vapor state. The output is pressure, density, temperature, entropy, enthalpy for all of the fluids and in most cases specific heat capacity and speed of sound. Viscosity and thermal conductivity are also given for most of the fluids. The programs are designed for access by remote terminal; however, they have been written in a modular form to allow the user to select either specific fluids or specific properties for particular needs. The program includes properties for hydrogen, helium, neon, nitrogen, oxygen, argon, and methane. The programs include properties for gaseous and liquid states usually from the triple point to some upper limit of pressure and temperature which varies from fluid to fluid.

An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States

USGS Publications Warehouse

Wendel, Jochen; Buttenfield, Barbara P.; Stanislawski, Larry V.

2016-01-01

Knowledge of landscape type can inform cartographic generalization of hydrographic features, because landscape characteristics provide an important geographic context that affects variation in channel geometry, flow pattern, and network configuration. Landscape types are characterized by expansive spatial gradients, lacking abrupt changes between adjacent classes; and as having a limited number of outliers that might confound classification. The US Geological Survey (USGS) is exploring methods to automate generalization of features in the National Hydrography Data set (NHD), to associate specific sequences of processing operations and parameters with specific landscape characteristics, thus obviating manual selection of a unique processing strategy for every NHD watershed unit. A chronology of methods to delineate physiographic regions for the United States is described, including a recent maximum likelihood classification based on seven input variables. This research compares unsupervised and supervised algorithms applied to these seven input variables, to evaluate and possibly refine the recent classification. Evaluation metrics for unsupervised methods include the Davies–Bouldin index, the Silhouette index, and the Dunn index as well as quantization and topographic error metrics. Cross validation and misclassification rate analysis are used to evaluate supervised classification methods. The paper reports the comparative analysis and its impact on the selection of landscape regions. The compared solutions show problems in areas of high landscape diversity. There is some indication that additional input variables, additional classes, or more sophisticated methods can refine the existing classification.

Balancing aggregation and smoothing errors in inverse models

DOE PAGES

Turner, A. J.; Jacob, D. J.

2015-06-30

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function ofmore » state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.« less

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D. J.

2015-01-01

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D. J.

2015-06-01

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.

Linear and nonlinear pattern selection in Rayleigh-Benard stability problems

NASA Technical Reports Server (NTRS)

Davis, Sanford S.

1993-01-01

A new algorithm is introduced to compute finite-amplitude states using primitive variables for Rayleigh-Benard convection on relatively coarse meshes. The algorithm is based on a finite-difference matrix-splitting approach that separates all physical and dimensional effects into one-dimensional subsets. The nonlinear pattern selection process for steady convection in an air-filled square cavity with insulated side walls is investigated for Rayleigh numbers up to 20,000. The internalization of disturbances that evolve into coherent patterns is investigated and transient solutions from linear perturbation theory are compared with and contrasted to the full numerical simulations.

Job Satisfaction Facets as Predictors of Commitment to or Withdrawal from the Work Organization among Selected Community College Faculty in New York State.

ERIC Educational Resources Information Center

Hill, Earl A.

1986-01-01

Examines the differential effects of five job satisfaction variables (i.e., work, supervision, co-workers, pay, and promotion) on community college developmental educators in New York. Satisfaction with the work itself, promotion opportunities, and co-workers had the greatest influence on teachers' commitment to the college and propensity to leave…

Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach

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

Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com

We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.

Entanglement and Wigner Function Negativity of Multimode Non-Gaussian States

NASA Astrophysics Data System (ADS)

Walschaers, Mattia; Fabre, Claude; Parigi, Valentina; Treps, Nicolas

2017-11-01

Non-Gaussian operations are essential to exploit the quantum advantages in optical continuous variable quantum information protocols. We focus on mode-selective photon addition and subtraction as experimentally promising processes to create multimode non-Gaussian states. Our approach is based on correlation functions, as is common in quantum statistical mechanics and condensed matter physics, mixed with quantum optics tools. We formulate an analytical expression of the Wigner function after the subtraction or addition of a single photon, for arbitrarily many modes. It is used to demonstrate entanglement properties specific to non-Gaussian states and also leads to a practical and elegant condition for Wigner function negativity. Finally, we analyze the potential of photon addition and subtraction for an experimentally generated multimode Gaussian state.

Entanglement and Wigner Function Negativity of Multimode Non-Gaussian States.

PubMed

Walschaers, Mattia; Fabre, Claude; Parigi, Valentina; Treps, Nicolas

2017-11-03

Non-Gaussian operations are essential to exploit the quantum advantages in optical continuous variable quantum information protocols. We focus on mode-selective photon addition and subtraction as experimentally promising processes to create multimode non-Gaussian states. Our approach is based on correlation functions, as is common in quantum statistical mechanics and condensed matter physics, mixed with quantum optics tools. We formulate an analytical expression of the Wigner function after the subtraction or addition of a single photon, for arbitrarily many modes. It is used to demonstrate entanglement properties specific to non-Gaussian states and also leads to a practical and elegant condition for Wigner function negativity. Finally, we analyze the potential of photon addition and subtraction for an experimentally generated multimode Gaussian state.

Relationships between wintering waterbirds and invertebrates, sediments and hydrology of coastal marsh ponds

USGS Publications Warehouse

Bolduc, F.; Afton, A.D.

2004-01-01

We studied relationships among sediment variables (carbon content, C:N, hardness, oxygen penetration, silt-clay fraction), hydrologic variables (dissolved oxygen, salinity, temperature, transparency, water depth), sizes and biomass of common invertebrate classes, and densities of 15 common waterbird species in ponds of impounded freshwater, oligohaline, mesohaline, and unimpounded mesohaline marshes during winters 1997-98 to 1999-2000 on Rockefeller State Wildlife Refuge, Louisiana, USA. Canonical correspondence analysis and forward selection was used to analyze the above variables. Water depth and oxygen penetration were the variables that best segregated habitat characteristics that resulted in maximum densities of common waterbird species. Most common waterbird species were associated with specific marsh types, except Green-winged Teal (Anas crecca) and Northern Shoveler (Anas clypeata). We concluded that hydrologic manipulation of marsh ponds is the best way to manage habitats for these birds, if the hydrology can be controlled adequately.

A comparative approach to the principal mechanisms of different memory systems

NASA Astrophysics Data System (ADS)

Rensing, Ludger; Koch, Michael; Becker, Annette

2009-12-01

The term “memory” applies not only to the preservation of information in neuronal and immune systems but also to phenomena observed for example in plants, single cells, and RNA viruses. We here compare the different forms of information storage with respect to possible common features. The latter may be characterized by (1) selection of pre-existing information, (2) activation of memory systems often including transcriptional, and translational, as well as epigenetic and genetic mechanisms, (3) subsequent consolidation of the activated state in a latent form ( standby mode), and (4) reactivation of the latent state of memory systems when the organism is exposed to the same (or conditioned) signal or to previous selective constraints. These features apparently also exist in the “evolutionary memory,” i.e., in evolving populations which have highly variable mutant spectra.

Near-Ideal Xylene Selectivity in Adaptive Molecular Pillar[ n]arene Crystals.

PubMed

Jie, Kecheng; Liu, Ming; Zhou, Yujuan; Little, Marc A; Pulido, Angeles; Chong, Samantha Y; Stephenson, Andrew; Hughes, Ashlea R; Sakakibara, Fumiyasu; Ogoshi, Tomoki; Blanc, Frédéric; Day, Graeme M; Huang, Feihe; Cooper, Andrew I

2018-06-06

The energy-efficient separation of alkylaromatic compounds is a major industrial sustainability challenge. The use of selectively porous extended frameworks, such as zeolites or metal-organic frameworks, is one solution to this problem. Here, we studied a flexible molecular material, perethylated pillar[ n]arene crystals ( n = 5, 6), which can be used to separate C8 alkylaromatic compounds. Pillar[6]arene is shown to separate para-xylene from its structural isomers, meta-xylene and ortho-xylene, with 90% specificity in the solid state. Selectivity is an intrinsic property of the pillar[6]arene host, with the flexible pillar[6]arene cavities adapting during adsorption thus enabling preferential adsorption of para-xylene in the solid state. The flexibility of pillar[6]arene as a solid sorbent is rationalized using molecular conformer searches and crystal structure prediction (CSP) combined with comprehensive characterization by X-ray diffraction and 13 C solid-state NMR spectroscopy. The CSP study, which takes into account the structural variability of pillar[6]arene, breaks new ground in its own right and showcases the feasibility of applying CSP methods to understand and ultimately to predict the behavior of soft, adaptive molecular crystals.

Variable Selection through Correlation Sifting

NASA Astrophysics Data System (ADS)

Huang, Jim C.; Jojic, Nebojsa

Many applications of computational biology require a variable selection procedure to sift through a large number of input variables and select some smaller number that influence a target variable of interest. For example, in virology, only some small number of viral protein fragments influence the nature of the immune response during viral infection. Due to the large number of variables to be considered, a brute-force search for the subset of variables is in general intractable. To approximate this, methods based on ℓ1-regularized linear regression have been proposed and have been found to be particularly successful. It is well understood however that such methods fail to choose the correct subset of variables if these are highly correlated with other "decoy" variables. We present a method for sifting through sets of highly correlated variables which leads to higher accuracy in selecting the correct variables. The main innovation is a filtering step that reduces correlations among variables to be selected, making the ℓ1-regularization effective for datasets on which many methods for variable selection fail. The filtering step changes both the values of the predictor variables and output values by projections onto components obtained through a computationally-inexpensive principal components analysis. In this paper we demonstrate the usefulness of our method on synthetic datasets and on novel applications in virology. These include HIV viral load analysis based on patients' HIV sequences and immune types, as well as the analysis of seasonal variation in influenza death rates based on the regions of the influenza genome that undergo diversifying selection in the previous season.

A review of covariate selection for non-experimental comparative effectiveness research.

PubMed

Sauer, Brian C; Brookhart, M Alan; Roy, Jason; VanderWeele, Tyler

2013-11-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for a common cause pathway between treatment and outcome can remove confounding, whereas adjustment for other structural types may increase bias. For this reason, variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely known. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher's knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. Copyright © 2013 John Wiley & Sons, Ltd.

A Review of Covariate Selection for Nonexperimental Comparative Effectiveness Research

PubMed Central

Sauer, Brian C.; Brookhart, Alan; Roy, Jason; Vanderweele, Tyler

2014-01-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for on a common cause pathway between treatment and outcome can remove confounding, while adjustment for other structural types may increase bias. For this reason variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely know. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses the high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher’s knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically-derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. PMID:24006330

Rethinking Medicaid Coverage and Payment Policy to Promote High Value Care: The Case of Long-Acting Reversible Contraception.

PubMed

Vela, Veronica X; Patton, Elizabeth W; Sanghavi, Darshak; Wood, Susan F; Shin, Peter; Rosenbaum, Sara

Long-acting reversible contraception (LARC) is the most effective reversible method to prevent unplanned pregnancies. Variability in state-level policies and the high cost of LARC could create substantial inconsistencies in Medicaid coverage, despite federal guidance aimed at enhancing broad access. This study surveyed state Medicaid payment policies and outreach activities related to LARC to explore the scope of services covered. Using publicly available information, we performed a content analysis of state Medicaid family planning and LARC payment policies. Purposeful sampling led to a selection of nine states with diverse geographic locations, political climates, Medicaid expansion status, and the number of women covered by Medicaid. All nine states' Medicaid programs covered some aspects of LARC. However, only a single state's payment structure incorporated all core aspects of high-quality LARC service delivery, including counseling, device, insertion, removal, and follow-up care. Most states did not explicitly address counseling, device removal, or follow-up care. Some states had strategies to enhance access, including policies to increase device reimbursement, stocking and delivery programs to remove cost barriers, and covering devices and insertion after an abortion. Although Medicaid policy encourages LARC methods, state payment policies frequently fail to address key aspects of care, including counseling, follow-up care, and removal, resulting in highly variable state-level practices. Although some states include payment policy innovations to support LARC access, significant opportunities remain. Published by Elsevier Inc.

Power steering: The politics of utility privatization in India

NASA Astrophysics Data System (ADS)

Kale, Sunila Sharatkumar

In this dissertation I offer an explanation for why Indian states are undertaking economic liberalization at different rates, focusing on reforms to the electricity sector. In the period between 1991 and 2003, India's states restructured their electricity systems to vastly different degrees. The dissertation evaluates three variables that feature prominently in the literature on economic policy change: ideological predilections of governing elites, external pressures like those coming from international financial institutions, and state-society interactions. I argue that it is the last explanation, focusing on the degree to which the potential "losers" from reform dominate state politics---that most compellingly accounts for the unevenness in state-level reforms. In my work, I lay greater analytic weight on the role of rural actors than much of the existing literature on the political economy of market reforms. The primary independent variable that explains this variation in reform outcomes is the organization and political strength of societal actors in each state, particularly rural and industrial constituencies, and middle class interests. In some parts of India, the advent of Green Revolution technologies in the late 1960s meant that farmers---chiefly larger landowners---became the primary beneficiaries of extensive development subsidies, including those for electricity. During India's period of economic liberalization in the 1990s, these beneficiaries constituted the main opponents of privatization, which today threatens to change the rules of the game by allocating resources according to market logics. Given these dynamics, where farm sectors are large or well-organized, reform has not proceeded. In the absence of rural political clout, state elites elected to privatize in order to satisfy industrial and urban constituents and signal the state's openness to private capital inflows. By comparing outcomes across states within the single country of India, the research design can control for some variables that are proposed as determinative of government policy, like electoral institutions and macroeconomic shock. I have selected cases to both capture variation of the dependent variable and control for other plausible explanations, such as ideology, financial crisis, and external pressure.

A multi-criteria index for ecological evaluation of tropical agriculture in southeastern Mexico.

PubMed

Huerta, Esperanza; Kampichler, Christian; Ochoa-Gaona, Susana; De Jong, Ben; Hernandez-Daumas, Salvador; Geissen, Violette

2014-01-01

The aim of this study was to generate an easy to use index to evaluate the ecological state of agricultural land from a sustainability perspective. We selected environmental indicators, such as the use of organic soil amendments (green manure) versus chemical fertilizers, plant biodiversity (including crop associations), variables which characterize soil conservation of conventional agricultural systems, pesticide use, method and frequency of tillage. We monitored the ecological state of 52 agricultural plots to test the performance of the index. The variables were hierarchically aggregated with simple mathematical algorithms, if-then rules, and rule-based fuzzy models, yielding the final multi-criteria index with values from 0 (worst) to 1 (best conditions). We validated the model through independent evaluation by experts, and we obtained a linear regression with an r2 = 0.61 (p = 2.4e-06, d.f. = 49) between index output and the experts' evaluation.

A Multi-Criteria Index for Ecological Evaluation of Tropical Agriculture in Southeastern Mexico

PubMed Central

Huerta, Esperanza; Kampichler, Christian; Ochoa-Gaona, Susana; De Jong, Ben; Hernandez-Daumas, Salvador; Geissen, Violette

2014-01-01

The aim of this study was to generate an easy to use index to evaluate the ecological state of agricultural land from a sustainability perspective. We selected environmental indicators, such as the use of organic soil amendments (green manure) versus chemical fertilizers, plant biodiversity (including crop associations), variables which characterize soil conservation of conventional agricultural systems, pesticide use, method and frequency of tillage. We monitored the ecological state of 52 agricultural plots to test the performance of the index. The variables were hierarchically aggregated with simple mathematical algorithms, if-then rules, and rule-based fuzzy models, yielding the final multi-criteria index with values from 0 (worst) to 1 (best conditions). We validated the model through independent evaluation by experts, and we obtained a linear regression with an r2 = 0.61 (p = 2.4e-06, d.f. = 49) between index output and the experts’ evaluation. PMID:25405980

Epigallocatechin-3-gallate preferentially induces aggregation of amyloidogenic immunoglobulin light chains

PubMed Central

Hora, Manuel; Carballo-Pacheco, Martin; Weber, Benedikt; Morris, Vanessa K.; Wittkopf, Antje; Buchner, Johannes; Strodel, Birgit; Reif, Bernd

2017-01-01

Antibody light chain amyloidosis is a rare disease caused by fibril formation of secreted immunoglobulin light chains (LCs). The huge variety of antibody sequences puts a serious challenge to drug discovery. The green tea polyphenol epigallocatechin-3-gallate (EGCG) is known to interfere with fibril formation in general. Here we present solution- and solid-state NMR studies as well as MD simulations to characterise the interaction of EGCG with LC variable domains. We identified two distinct EGCG binding sites, both of which include a proline as an important recognition element. The binding sites were confirmed by site-directed mutagenesis and solid-state NMR analysis. The EGCG-induced protein complexes are unstructured. We propose a general mechanistic model for EGCG binding to a conserved site in LCs. We find that EGCG reacts selectively with amyloidogenic mutants. This makes this compound a promising lead structure, that can handle the immense sequence variability of antibody LCs. PMID:28128355

Using maximum entropy modeling for optimal selection of sampling sites for monitoring networks

USGS Publications Warehouse

Stohlgren, Thomas J.; Kumar, Sunil; Barnett, David T.; Evangelista, Paul H.

2011-01-01

Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.

Fluctuation relation based continuum model for thermoviscoplasticity in metals

NASA Astrophysics Data System (ADS)

Roy Chowdhury, Shubhankar; Roy, Debasish; Reddy, J. N.; Srinivasa, Arun

2016-11-01

A continuum plasticity model for metals is presented from considerations of non-equilibrium thermodynamics. Of specific interest is the application of a fluctuation relation that subsumes the second law of thermodynamics en route to deriving the evolution equations for the internal state variables. The modelling itself is accomplished in a two-temperature framework that appears naturally by considering the thermodynamic system to be composed of two weakly interacting subsystems, viz. a kinetic vibrational subsystem corresponding to the atomic lattice vibrations and a configurational subsystem of the slower degrees of freedom describing the motion of defects in a plastically deforming metal. An apparently physical nature of the present model derives upon considering the dislocation density, which characterizes the configurational subsystem, as a state variable. Unlike the usual constitutive modelling aided by the second law of thermodynamics that merely provides a guideline to select the admissible (though possibly non-unique) processes, the present formalism strictly determines the process or the evolution equations for the thermodynamic states while including the effect of fluctuations. The continuum model accommodates finite deformation and describes plastic deformation in a yield-free setup. The theory here is essentially limited to face-centered cubic metals modelled with a single dislocation density as the internal variable. Limited numerical simulations are presented with validation against relevant experimental data.

Least-rattling feedback from strong time-scale separation

NASA Astrophysics Data System (ADS)

Chvykov, Pavel; England, Jeremy

2018-03-01

In most interacting many-body systems associated with some "emergent phenomena," we can identify subgroups of degrees of freedom that relax on dramatically different time scales. Time-scale separation of this kind is particularly helpful in nonequilibrium systems where only the fast variables are subjected to external driving; in such a case, it may be shown through elimination of fast variables that the slow coordinates effectively experience a thermal bath of spatially varying temperature. In this paper, we investigate how such a temperature landscape arises according to how the slow variables affect the character of the driven quasisteady state reached by the fast variables. Brownian motion in the presence of spatial temperature gradients is known to lead to the accumulation of probability density in low-temperature regions. Here, we focus on the implications of attraction to low effective temperature for the long-term evolution of slow variables. After quantitatively deriving the temperature landscape for a general class of overdamped systems using a path-integral technique, we then illustrate in a simple dynamical system how the attraction to low effective temperature has a fine-tuning effect on the slow variable, selecting configurations that bring about exceptionally low force fluctuation in the fast-variable steady state. We furthermore demonstrate that a particularly strong effect of this kind can take place when the slow variable is tuned to bring about orderly, integrable motion in the fast dynamics that avoids thermalizing energy absorbed from the drive. We thus point to a potentially general feedback mechanism in multi-time-scale active systems, that leads to the exploration of slow variable space, as if in search of fine tuning for a "least-rattling" response in the fast coordinates.

Spool-type control valve assembly with reduced spool stroke for hydraulic belt-and-pulley type continuously variable transmission

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

Itoh, H.; Akashi, T.; Takada, M.

1987-03-31

This patent describes a hydraulic control system for controlling a speed ratio of a hydraulically-operated continuously variable transmission of belt-and-pulley type having a variable-diameter pulley and a hydraulic cylinder for changing an effective diameter of the variable diameter-pulley of the transmission. The hydraulic control system includes a speed-ratio control valve assembly for controlling the supply and discharge of a pressurized fluid to and from the hydraulic cylinder to thereby change the speed ratio of the transmission. The speed-ratio control valve assembly comprises: a shift-direction switching valve unit disposed in fluid supply and discharge conduits communicating with the hydraulic cylinder, formore » controlling a direction in which the speed ratio of the transmission is varied; a shift-speed control valve unit of spool-valve type connected to the shift-direction switching valve unit. The shift-speed control valve unit is selectively placed in a first state in which the fluid supply and discharge flows to and from the hydraulic cylinder through the conduits are permitted, or in a second state in which the fluid supply flow is restricted while the fluid discharge flow is inhibited; an actuator means for placing the shift speed control valve unit alternately in the first and second states to control a rate of variation in the speed ratio of the transmission in the direction established by the shift-direction switching valve unit.« less

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

System and method for optimal load and source scheduling in context aware homes

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

Shetty, Pradeep; Foslien Graber, Wendy; Mangsuli, Purnaprajna R.

A controller for controlling energy consumption in a home includes a constraints engine to define variables for multiple appliances in the home corresponding to various home modes and persona of an occupant of the home. A modeling engine models multiple paths of energy utilization of the multiple appliances to place the home into a desired state from a current context. An optimal scheduler receives the multiple paths of energy utilization and generates a schedule as a function of the multiple paths and a selected persona to place the home in a desired state.

Computing Linear Mathematical Models Of Aircraft

NASA Technical Reports Server (NTRS)

Duke, Eugene L.; Antoniewicz, Robert F.; Krambeer, Keith D.

1991-01-01

Derivation and Definition of Linear Aircraft Model (LINEAR) computer program provides user with powerful, and flexible, standard, documented, and verified software tool for linearization of mathematical models of aerodynamics of aircraft. Intended for use in software tool to drive linear analysis of stability and design of control laws for aircraft. Capable of both extracting such linearized engine effects as net thrust, torque, and gyroscopic effects, and including these effects in linear model of system. Designed to provide easy selection of state, control, and observation variables used in particular model. Also provides flexibility of allowing alternate formulations of both state and observation equations. Written in FORTRAN.

Temporal variability of selected air toxics in the United States

NASA Astrophysics Data System (ADS)

McCarthy, Michael C.; Hafner, Hilary R.; Chinkin, Lyle R.; Charrier, Jessica G.

Ambient measurements of hazardous air pollutants (HAPs, air toxics) collected in the United States from 1990 to 2005 were analyzed for diurnal, seasonal, and/or annual variability and trends. Visual and statistical analyses were used to identify and quantify temporal variations in air toxics at national and regional levels. Sufficient data were available to analyze diurnal variability for 14 air toxics, seasonal variability for 24 air toxics, and annual trends for 26 air toxics. Four diurnal variation patterns were identified and labeled invariant, nighttime peak, morning peak, and daytime peak. Three distinct seasonal patterns were identified and labeled invariant, cool, and warm. Multiple air toxics showed consistent decreasing trends over three trend periods, 1990-2005, 1995-2005, and 2000-2005. Trends appeared to be relatively consistent within chemically similar pollutant groups. Hydrocarbons such as benzene, 1,3-butadiene, styrene, xylene, and toluene decreased by approximately 5% or more per year at more than half of all monitoring sites. Concentrations of carbonyl compounds such as formaldehyde, acetaldehyde, and propionaldehyde were equally likely to have increased or decreased at monitoring sites. Chlorinated volatile organic compounds (VOCs) such as tetrachloroethylene, dichloromethane, and methyl chloroform decreased at more than half of all monitoring sites, but decreases among these species were much more variable than among the hydrocarbons. Lead particles decreased in concentration at most monitoring sites, but trends in other metals were not consistent over time.

Demographic risk factors of self-immolation: a case-control study.

PubMed

Ahmadi, Alireza; Mohammadi, Reza; Schwebel, David C; Khazaie, Habibolah; Yeganeh, Naser; Almasi, Afshin

2009-06-01

To investigate demographic risk factors for self-immolation patients. In a case-control study, 30 consecutive cases of deliberate self-inflicted burns admitted to the regional Burn centre (Imam Khomeini hospital in Kermanshah province, Iran) were compared with 30 controls who were selected from the community and matched by gender, age, and living area. All cases and controls were reviewed for demographic variables, including: age, gender, living area, family size, marital status, bearing and number of children, Body Mass Index (BMI), birth order, employment state, educational status, early school drop-out, and parent/guardian employment status. Two variables emerged as related to risk of self-immolation. Being the first or last child in family birth order was associated with increased risk of self-immolation. Moreover, among the married participants, having children was associated with decreased risk of self-immolation. The comparisons of other variables were not statistically significant. In multivariate analyses, none of the variables predicted risk for self-immolation. This study suggests that being the first or last child of a family might be a risk factor for self-immolation. For married persons, having children might serve as a protective factor from self-immolation. Other variables such as family size, marital status, number of children, BMI, employment state, educational status, early school drop-out, and parent/guardian employment status did not play a role as individually protective or risk factors for self-immolation.

Designing basin-customized combined drought indices via feature extraction

NASA Astrophysics Data System (ADS)

Zaniolo, Marta; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

The socio-economic costs of drought are progressively increasing worldwide due to the undergoing alteration of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, most of the traditional drought indexes fail in detecting critical events in highly regulated systems, which generally rely on ad-hoc formulations and cannot be generalized to different context. In this study, we contribute a novel framework for the design of a basin-customized drought index. This index represents a surrogate of the state of the basin and is computed by combining the available information about the water available in the system to reproduce a representative target variable for the drought condition of the basin (e.g., water deficit). To select the relevant variables and how to combine them, we use an advanced feature extraction algorithm called Wrapper for Quasi Equally Informative Subset Selection (W-QEISS). The W-QEISS algorithm relies on a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables (cardinality) and optimizing relevance and redundancy of the subset. The accuracy objective is evaluated trough the calibration of a pre-defined model (i.e., an extreme learning machine) of the water deficit for each candidate subset of variables, with the index selected from the resulting solutions identifying a suitable compromise between accuracy, cardinality, relevance, and redundancy. The proposed methodology is tested in the case study of Lake Como in northern Italy, a regulated lake mainly operated for irrigation supply to four downstream agricultural districts. In the absence of an institutional drought monitoring system, we constructed the combined index using all the hydrological variables from the existing monitoring system as well as the most common drought indicators at multiple time aggregations. The soil moisture deficit in the root zone computed by a distributed-parameter water balance model of the agricultural districts is used as target variable. Numerical results show that our framework succeeds in constructing a combined drought index that reproduces the soil moisture deficit. Moreover, this index represents a valuable information for supporting appropriate drought management strategies, including the possibility of directly informing the lake operations about the drought conditions and improve the overall reliability of the irrigation supply system.

Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Singh, Renu; Steinley, Douglas

2009-01-01

The selection of a subset of variables from a pool of candidates is an important problem in several areas of multivariate statistics. Within the context of principal component analysis (PCA), a number of authors have argued that subset selection is crucial for identifying those variables that are required for correct interpretation of the…

Development and Application of a Decision Support System for Water Management Investigations in the Upper Yakima River, Washington

USGS Publications Warehouse

Bovee, Ken D.; Waddle, Terry J.; Talbert, Colin; Hatten, James R.; Batt, Thomas R.

2008-01-01

The Yakima River Decision Support System (YRDSS) was designed to quantify and display the consequences of different water management scenarios for a variety of state variables in the upper Yakima River Basin, located in central Washington. The impetus for the YRDSS was the Yakima River Basin Water Storage Feasibility Study, which investigated alternatives for providing additional water in the basin for threatened and endangered fish, irrigated agriculture, and municipal water supply. The additional water supplies would be provided by combinations of water exchanges, pumping stations, and off-channel storage facilities, each of which could affect the operations of the Bureau of Reclamation's (BOR) five headwaters reservoirs in the basin. The driver for the YRDSS is RiverWare, a systems-operations model used by BOR to calculate reservoir storage, irrigation deliveries, and streamflow at downstream locations resulting from changes in water supply and reservoir operations. The YRDSS uses output from RiverWare to calculate and summarize changes at 5 important flood plain reaches in the basin to 14 state variables: (1) habitat availability for selected life stages of four salmonid species, (2) spawning-incubation habitat persistence, (3) potential redd scour, (4) maximum water temperatures, (5) outmigration for bull trout (Salvelinus confluentus) from headwaters reservoirs, (6) outmigration of salmon smolts from Cle Elum Reservoir, (7) frequency of beneficial overbank flooding, (8) frequency of damaging flood events, (9) total deliverable water supply, (10) total water supply deliverable to junior water rights holders, (11) end-of-year reservoir carryover, (12) potential fine sediment transport rates, (13) frequency of events capable of armor layer disruption, and (14) geomorphic work performed during each water year. Output of the YRDSS consists of a series of conditionally formatted scoring tables, wherein the changes to a state variable resulting from an operational scenario are compiled and summarized. Increases in the values for state variables result in their respective backgrounds to turn green in the scoring matrix, whereas decreases in the values for state variables result in their respective backgrounds turning red. This convention was designed to provide decision makers with a quick visual assessment of the overall results of an operating scenario. An evaluation matrix and a variety of weighting strategies to reflect the relative importance of different state variables are also presented as options for further distillation of YRDSS results during the decision-making process.

Model selection bias and Freedman's paradox

USGS Publications Warehouse

Lukacs, P.M.; Burnham, K.P.; Anderson, D.R.

2010-01-01

In situations where limited knowledge of a system exists and the ratio of data points to variables is small, variable selection methods can often be misleading. Freedman (Am Stat 37:152-155, 1983) demonstrated how common it is to select completely unrelated variables as highly "significant" when the number of data points is similar in magnitude to the number of variables. A new type of model averaging estimator based on model selection with Akaike's AIC is used with linear regression to investigate the problems of likely inclusion of spurious effects and model selection bias, the bias introduced while using the data to select a single seemingly "best" model from a (often large) set of models employing many predictor variables. The new model averaging estimator helps reduce these problems and provides confidence interval coverage at the nominal level while traditional stepwise selection has poor inferential properties. ?? The Institute of Statistical Mathematics, Tokyo 2009.

The Cramér-Rao Bounds and Sensor Selection for Nonlinear Systems with Uncertain Observations.

PubMed

Wang, Zhiguo; Shen, Xiaojing; Wang, Ping; Zhu, Yunmin

2018-04-05

This paper considers the problems of the posterior Cramér-Rao bound and sensor selection for multi-sensor nonlinear systems with uncertain observations. In order to effectively overcome the difficulties caused by uncertainty, we investigate two methods to derive the posterior Cramér-Rao bound. The first method is based on the recursive formula of the Cramér-Rao bound and the Gaussian mixture model. Nevertheless, it needs to compute a complex integral based on the joint probability density function of the sensor measurements and the target state. The computation burden of this method is relatively high, especially in large sensor networks. Inspired by the idea of the expectation maximization algorithm, the second method is to introduce some 0-1 latent variables to deal with the Gaussian mixture model. Since the regular condition of the posterior Cramér-Rao bound is unsatisfied for the discrete uncertain system, we use some continuous variables to approximate the discrete latent variables. Then, a new Cramér-Rao bound can be achieved by a limiting process of the Cramér-Rao bound of the continuous system. It avoids the complex integral, which can reduce the computation burden. Based on the new posterior Cramér-Rao bound, the optimal solution of the sensor selection problem can be derived analytically. Thus, it can be used to deal with the sensor selection of a large-scale sensor networks. Two typical numerical examples verify the effectiveness of the proposed methods.

Variables selection methods in near-infrared spectroscopy.

PubMed

Xiaobo, Zou; Jiewen, Zhao; Povey, Malcolm J W; Holmes, Mel; Hanpin, Mao

2010-05-14

Near-infrared (NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields, such as the petrochemical, pharmaceutical, environmental, clinical, agricultural, food and biomedical sectors during the past 15 years. A NIR spectrum of a sample is typically measured by modern scanning instruments at hundreds of equally spaced wavelengths. The large number of spectral variables in most data sets encountered in NIR spectral chemometrics often renders the prediction of a dependent variable unreliable. Recently, considerable effort has been directed towards developing and evaluating different procedures that objectively identify variables which contribute useful information and/or eliminate variables containing mostly noise. This review focuses on the variable selection methods in NIR spectroscopy. Selection methods include some classical approaches, such as manual approach (knowledge based selection), "Univariate" and "Sequential" selection methods; sophisticated methods such as successive projections algorithm (SPA) and uninformative variable elimination (UVE), elaborate search-based strategies such as simulated annealing (SA), artificial neural networks (ANN) and genetic algorithms (GAs) and interval base algorithms such as interval partial least squares (iPLS), windows PLS and iterative PLS. Wavelength selection with B-spline, Kalman filtering, Fisher's weights and Bayesian are also mentioned. Finally, the websites of some variable selection software and toolboxes for non-commercial use are given. Copyright 2010 Elsevier B.V. All rights reserved.

An Assessment of Farmers' Willingness to Pay for Extension Services Using the Contingent Valuation Method (CVM): The Case of Oyo State, Nigeria

ERIC Educational Resources Information Center

Ajayi, A. O.

2006-01-01

This study assessed farmers' willingness to pay (WTP) for extension services. The Contingent Valuation Method (CVM) was used to assess the amount which farmers are willing to pay. Primary data on the demographic, socio-economic variables of farmers and their WTP were collected from 228 farmers selected randomly in a stage-wise sampling procedure…

Robust Integration Schemes for Generalized Viscoplasticity with Internal-State Variables

NASA Technical Reports Server (NTRS)

Saleeb, Atef F.; Li, W.; Wilt, Thomas E.

1997-01-01

The scope of the work in this presentation focuses on the development of algorithms for the integration of rate dependent constitutive equations. In view of their robustness; i.e., their superior stability and convergence properties for isotropic and anisotropic coupled viscoplastic-damage models, implicit integration schemes have been selected. This is the simplest in its class and is one of the most widely used implicit integrators at present.

Stratifying FIA Ground Plots Using A 3-Year Old MRLC Forest Cover Map and Current TM Derived Variables Selected By "Decision Tree" Classification

Treesearch

Michael Hoppus; Stan Arner; Andrew Lister

2001-01-01

A reduction in variance for estimates of forest area and volume in the state of Connecticut was accomplished by stratifying FIA ground plots using raw, transformed and classified Landsat Thematic Mapper (TM) imagery. A US Geological Survey (USGS) Multi-Resolution Landscape Characterization (MRLC) vegetation cover map for Connecticut was used to produce a forest/non-...

The Information Processing Role of the Informal and Quasi-Formal Support Systems among the Hispanic Elderly: Implications for the Delivery of Formal Social Services.

ERIC Educational Resources Information Center

Starrett, Richard A.; And Others

The study examined relationships among factors influencing utilization of social services by Hispanic elderly, particularly factors categorized as: (1) informal, such as support groups of family, kin, neighbors, friends, and (2) quasi-formal, such as church groups. Thirty-seven variables and data selected from a 1979-80 15-state survey of 1,805…

A comparison of recharge rates in aquifers of the United States based on groundwater-age data

USGS Publications Warehouse

McMahon, P.B.; Plummer, Niel; Böhlke, J.K.; Shapiro, S.D.; Hinkle, S.R.

2011-01-01

An overview is presented of existing groundwater-age data and their implications for assessing rates and timescales of recharge in selected unconfined aquifer systems of the United States. Apparent age distributions in aquifers determined from chlorofluorocarbon, sulfur hexafluoride, tritium/helium-3, and radiocarbon measurements from 565 wells in 45 networks were used to calculate groundwater recharge rates. Timescales of recharge were defined by 1,873 distributed tritium measurements and 102 radiocarbon measurements from 27 well networks. Recharge rates ranged from < 10 to 1,200 mm/yr in selected aquifers on the basis of measured vertical age distributions and assuming exponential age gradients. On a regional basis, recharge rates based on tracers of young groundwater exhibited a significant inverse correlation with mean annual air temperature and a significant positive correlation with mean annual precipitation. Comparison of recharge derived from groundwater ages with recharge derived from stream base-flow evaluation showed similar overall patterns but substantial local differences. Results from this compilation demonstrate that age-based recharge estimates can provide useful insights into spatial and temporal variability in recharge at a national scale and factors controlling that variability. Local age-based recharge estimates provide empirical data and process information that are needed for testing and improving more spatially complete model-based methods.

Evaluating the effectiveness of Washington state repeated job search services on the employment rate of prime-age female welfare recipients☆

PubMed Central

Hsiao, Cheng; Shen, Yan; Wang, Boqing; Weeks, Greg

2014-01-01

This paper uses an unbalanced panel dataset to evaluate how repeated job search services (JSS) and personal characteristics affect the employment rate of the prime-age female welfare recipients in the State of Washington. We propose a transition probability model to take into account issues of sample attrition, sample refreshment and duration dependence. We also generalize Honoré and Kyriazidou’s [Honoré, B.E., Kyriazidou, E., 2000. Panel data discrete choice models with lagged dependent variables. Econometrica 68 (4), 839–874] conditional maximum likelihood estimator to allow for the presence of individual-specific effects. A limited information test is suggested to test for selection issues in non-experimental data. The specification tests indicate that the (conditional on the set of the confounding variables considered) assumptions of no selection due to unobservables and/or no unobserved individual-specific effects are not violated. Our findings indicate that the first job search service does have positive and significant impacts on the employment rate. However, providing repeated JSS to the same client has no significant impact. Further, we find that there are significant experience-enhancing effects. These findings suggest that providing one job search services training to individuals may have a lasting impact on raising their employment rates. PMID:26052178

Evaluating the effectiveness of Washington state repeated job search services on the employment rate of prime-age female welfare recipients.

PubMed

Hsiao, Cheng; Shen, Yan; Wang, Boqing; Weeks, Greg

2008-07-01

This paper uses an unbalanced panel dataset to evaluate how repeated job search services (JSS) and personal characteristics affect the employment rate of the prime-age female welfare recipients in the State of Washington. We propose a transition probability model to take into account issues of sample attrition, sample refreshment and duration dependence. We also generalize Honoré and Kyriazidou's [Honoré, B.E., Kyriazidou, E., 2000. Panel data discrete choice models with lagged dependent variables. Econometrica 68 (4), 839-874] conditional maximum likelihood estimator to allow for the presence of individual-specific effects. A limited information test is suggested to test for selection issues in non-experimental data. The specification tests indicate that the (conditional on the set of the confounding variables considered) assumptions of no selection due to unobservables and/or no unobserved individual-specific effects are not violated. Our findings indicate that the first job search service does have positive and significant impacts on the employment rate. However, providing repeated JSS to the same client has no significant impact. Further, we find that there are significant experience-enhancing effects. These findings suggest that providing one job search services training to individuals may have a lasting impact on raising their employment rates.

Educational Pathways and Change in Crime Between Adolescence and Early Adulthood

PubMed Central

Swisher, Raymond R.; Dennison, Christopher R.

2016-01-01

Objectives This article examines the relationship between intergenerational educational pathways and change in crime. Moreover, it examines the potential mediating roles of family and employment transitions, economic stressors, and social psychological factors. Method Data from the National Longitudinal Study of Adolescent to Adult Health (N = 14,742) and negative binomial models are used to assess associations between educational pathways (i.e., upward, downward, and stable) and change in crime between adolescence and early adulthood. Selection effects are assessed with lagged dependent variables and controls for self-control, grades, and the Add Health Picture Vocabulary Test. Results Intergenerational educational pathways are significantly associated with changes in crime. Downward educational pathways were predictive of increases in crime, whereas upward pathways were associated with decreases in crime. These associations were partly mediated by family transitions, and more strongly by economic stressors. These results were robust to controls for selection related variables. Conclusions This study is among the first to examine the relationship between intergenerational educational pathways and crime in the United States. Both upward and downward changes in educational attainments were found to be significant for crime. These findings are notable given the continuing expansion of higher education as well as concerns regarding increasing stratification and downward mobility in the United States. PMID:28348441

Roosting habitat use and selection by northern spotted owls during natal dispersal

USGS Publications Warehouse

Sovern, Stan G.; Forsman, Eric D.; Dugger, Catherine M.; Taylor, Margaret

2015-01-01

We studied habitat selection by northern spotted owls (Strix occidentalis caurina) during natal dispersal in Washington State, USA, at both the roost site and landscape scales. We used logistic regression to obtain parameters for an exponential resource selection function based on vegetation attributes in roost and random plots in 76 forest stands that were used for roosting. We used a similar analysis to evaluate selection of landscape habitat attributes based on 301 radio-telemetry relocations and random points within our study area. We found no evidence of within-stand selection for any of the variables examined, but 78% of roosts were in stands with at least some large (>50 cm dbh) trees. At the landscape scale, owls selected for stands with high canopy cover (>70%). Dispersing owls selected vegetation types that were more similar to habitat selected by adult owls than habitat that would result from following guidelines previously proposed to maintain dispersal habitat. Our analysis indicates that juvenile owls select stands for roosting that have greater canopy cover than is recommended in current agency guidelines.

The effect of energy reserves on social foraging: hungry sparrows scrounge more.

PubMed

Lendvai, Adám Z; Barta, Zoltán; Liker, András; Bókony, Veronika

2004-12-07

Animals often use alternative strategies when they compete for resources, but it is unclear in most cases what factors determine the actual tactic followed by individuals. Although recent models suggest that the internal state of animals may be particularly important in tactic choice, the effects of state variables on the use of alternative behavioural forms have rarely been demonstrated. In this study, using experimental wind exposure to increase overnight energy expenditure, we show that flock-feeding house sparrows (Passer domesticus) with lowered energy reserves increase their use of scrounging (exploiting others' food findings) during their first feed of the day. This result is in accordance with the prediction of a state-dependent model of use of social foraging tactics. We also show that scrounging provides less variable feeding rates and patch finding times than the alternative tactic. These latter results support the theoretical assumption that scrounging is a risk-averse tactic, i.e. it reduces the risk of immediate starvation. As the level of energy reserves predicts the use of social foraging tactics, we propose that selection should favour individuals that monitor the internal state of flock mates and use this information to adjust their own tactic choice.

HiMoP: A three-component architecture to create more human-acceptable social-assistive robots : Motivational architecture for assistive robots.

PubMed

Rodríguez-Lera, Francisco J; Matellán-Olivera, Vicente; Conde-González, Miguel Á; Martín-Rico, Francisco

2018-05-01

Generation of autonomous behavior for robots is a general unsolved problem. Users perceive robots as repetitive tools that do not respond to dynamic situations. This research deals with the generation of natural behaviors in assistive service robots for dynamic domestic environments, particularly, a motivational-oriented cognitive architecture to generate more natural behaviors in autonomous robots. The proposed architecture, called HiMoP, is based on three elements: a Hierarchy of needs to define robot drives; a set of Motivational variables connected to robot needs; and a Pool of finite-state machines to run robot behaviors. The first element is inspired in Alderfer's hierarchy of needs, which specifies the variables defined in the motivational component. The pool of finite-state machine implements the available robot actions, and those actions are dynamically selected taking into account the motivational variables and the external stimuli. Thus, the robot is able to exhibit different behaviors even under similar conditions. A customized version of the "Speech Recognition and Audio Detection Test," proposed by the RoboCup Federation, has been used to illustrate how the architecture works and how it dynamically adapts and activates robots behaviors taking into account internal variables and external stimuli.

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems

PubMed Central

de Paula, Lauro C. M.; Soares, Anderson S.; de Lima, Telma W.; Delbem, Alexandre C. B.; Coelho, Clarimar J.; Filho, Arlindo R. G.

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation. PMID:25493625

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems.

PubMed

de Paula, Lauro C M; Soares, Anderson S; de Lima, Telma W; Delbem, Alexandre C B; Coelho, Clarimar J; Filho, Arlindo R G

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation.

Selection Practices of Group Leaders: A National Survey.

ERIC Educational Resources Information Center

Riva, Maria T.; Lippert, Laurel; Tackett, M. Jan

2000-01-01

Study surveys the selection practices of group leaders. Explores methods of selection, variables used to make selection decisions, and the types of selection errors that leaders have experienced. Results suggest that group leaders use clinical judgment to make selection decisions and endorse using some specific variables in selection. (Contains 22…

A comparative modeling analysis of multiscale temporal variability of rainfall in Australia

NASA Astrophysics Data System (ADS)

Samuel, Jos M.; Sivapalan, Murugesu

2008-07-01

The effects of long-term natural climate variability and human-induced climate change on rainfall variability have become the focus of much concern and recent research efforts. In this paper, we present the results of a comparative analysis of observed multiscale temporal variability of rainfall in the Perth, Newcastle, and Darwin regions of Australia. This empirical and stochastic modeling analysis explores multiscale rainfall variability, i.e., ranging from short to long term, including within-storm patterns, and intra-annual, interannual, and interdecadal variabilities, using data taken from each of these regions. The analyses investigated how storm durations, interstorm periods, and average storm rainfall intensities differ for different climate states and demonstrated significant differences in this regard between the three selected regions. In Perth, the average storm intensity is stronger during La Niña years than during El Niño years, whereas in Newcastle and Darwin storm duration is longer during La Niña years. Increase of either storm duration or average storm intensity is the cause of higher average annual rainfall during La Niña years as compared to El Niño years. On the other hand, within-storm variability does not differ significantly between different ENSO states in all three locations. In the case of long-term rainfall variability, the statistical analyses indicated that in Newcastle the long-term rainfall pattern reflects the variability of the Interdecadal Pacific Oscillation (IPO) index, whereas in Perth and Darwin the long-term variability exhibits a step change in average annual rainfall (up in Darwin and down in Perth) which occurred around 1970. The step changes in Perth and Darwin and the switch in IPO states in Newcastle manifested differently in the three study regions in terms of changes in the annual number of rainy days or the average daily rainfall intensity or both. On the basis of these empirical data analyses, a stochastic rainfall time series model was developed that incorporates the entire range of multiscale variabilities observed in each region, including within-storm, intra-annual, interannual, and interdecadal variability. Such ability to characterize, model, and synthetically generate realistic time series of rainfall intensities is essential for addressing many hydrological problems, including estimation of flood and drought frequencies, pesticide risk assessment, and landslide frequencies.

Model predictive controller design for boost DC-DC converter using T-S fuzzy cost function

NASA Astrophysics Data System (ADS)

Seo, Sang-Wha; Kim, Yong; Choi, Han Ho

2017-11-01

This paper proposes a Takagi-Sugeno (T-S) fuzzy method to select cost function weights of finite control set model predictive DC-DC converter control algorithms. The proposed method updates the cost function weights at every sample time by using T-S type fuzzy rules derived from the common optimal control engineering knowledge that a state or input variable with an excessively large magnitude can be penalised by increasing the weight corresponding to the variable. The best control input is determined via the online optimisation of the T-S fuzzy cost function for all the possible control input sequences. This paper implements the proposed model predictive control algorithm in real time on a Texas Instruments TMS320F28335 floating-point Digital Signal Processor (DSP). Some experimental results are given to illuminate the practicality and effectiveness of the proposed control system under several operating conditions. The results verify that our method can yield not only good transient and steady-state responses (fast recovery time, small overshoot, zero steady-state error, etc.) but also insensitiveness to abrupt load or input voltage parameter variations.

Unbiased split variable selection for random survival forests using maximally selected rank statistics.

PubMed

Wright, Marvin N; Dankowski, Theresa; Ziegler, Andreas

2017-04-15

The most popular approach for analyzing survival data is the Cox regression model. The Cox model may, however, be misspecified, and its proportionality assumption may not always be fulfilled. An alternative approach for survival prediction is random forests for survival outcomes. The standard split criterion for random survival forests is the log-rank test statistic, which favors splitting variables with many possible split points. Conditional inference forests avoid this split variable selection bias. However, linear rank statistics are utilized by default in conditional inference forests to select the optimal splitting variable, which cannot detect non-linear effects in the independent variables. An alternative is to use maximally selected rank statistics for the split point selection. As in conditional inference forests, splitting variables are compared on the p-value scale. However, instead of the conditional Monte-Carlo approach used in conditional inference forests, p-value approximations are employed. We describe several p-value approximations and the implementation of the proposed random forest approach. A simulation study demonstrates that unbiased split variable selection is possible. However, there is a trade-off between unbiased split variable selection and runtime. In benchmark studies of prediction performance on simulated and real datasets, the new method performs better than random survival forests if informative dichotomous variables are combined with uninformative variables with more categories and better than conditional inference forests if non-linear covariate effects are included. In a runtime comparison, the method proves to be computationally faster than both alternatives, if a simple p-value approximation is used. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Exploratory Spectroscopy of Magnetic Cataclysmic Variables Candidates and Other Variable Objects

NASA Astrophysics Data System (ADS)

Oliveira, A. S.; Rodrigues, C. V.; Cieslinski, D.; Jablonski, F. J.; Silva, K. M. G.; Almeida, L. A.; Rodríguez-Ardila, A.; Palhares, M. S.

2017-04-01

The increasing number of synoptic surveys made by small robotic telescopes, such as the photometric Catalina Real-Time Transient Survey (CRTS), provides a unique opportunity to discover variable sources and improves the statistical samples of such classes of objects. Our goal is the discovery of magnetic Cataclysmic Variables (mCVs). These are rare objects that probe interesting accretion scenarios controlled by the white-dwarf magnetic field. In particular, improved statistics of mCVs would help to address open questions on their formation and evolution. We performed an optical spectroscopy survey to search for signatures of magnetic accretion in 45 variable objects selected mostly from the CRTS. In this sample, we found 32 CVs, 22 being mCV candidates, 13 of which were previously unreported as such. If the proposed classifications are confirmed, it would represent an increase of 4% in the number of known polars and 12% in the number of known IPs. A fraction of our initial sample was classified as extragalactic sources or other types of variable stars by the inspection of the identification spectra. Despite the inherent complexity in identifying a source as an mCV, variability-based selection, followed by spectroscopic snapshot observations, has proved to be an efficient strategy for their discoveries, being a relatively inexpensive approach in terms of telescope time. Based on observations obtained at the Observatório do Pico dos Dias/LNA, and at the Southern Astrophysical Research (SOAR) telescope, which is a joint project of the Ministério da Ciência, Tecnologia, e Inovação (MCTI) da República Federativa do Brasil, the U.S. National Optical Astronomy Observatory (NOAO), the University of North Carolina at Chapel Hill (UNC), and Michigan State University (MSU).

Rocky Mountain spotted fever in Georgia, 1961-75: analysis of social and environmental factors affecting occurrence.

PubMed Central

Newhouse, V F; Choi, K; Holman, R C; Thacker, S B; D'Angelo, L J; Smith, J D

1986-01-01

For the period of 1961 through 1975, 10 geographic and sociologic variables in each of the 159 counties of Georgia were analyzed to determine how they were correlated with the occurrence of Rocky Mountain spotted fever (RMSF). Combinations of variables were transformed into a smaller number of factors using principal-component analysis. Based upon the relative values of these factors, geographic areas of similarity were delineated by cluster analysis. It was found by use of these analyses that the counties of the State formed four similarity clusters, which we called south, central, lower north and upper north. When the incidence of RMSF was subsequently calculated for each of these regions of similarity, the regions had differing RMSF incidence; low in the south and upper north, moderate in the central, and high in the lower north. The four similarity clusters agreed closely with the incidence of RMSF when both were plotted on a map. Thus, when analyzed simultaneously, the 10 variables selected could be used to predict the occurrence of RMSF. The most important variables were those of climate and geography. Of secondary, but still major importance, were the changes over the 15-year period in variables associated with humans and their environmental alterations. Detailed examination of these factors has permitted quantitative evaluation of the simultaneous impacts of the geographic and sociologic variables on the occurrence of RMSF in Georgia. These analyses could be updated to reflect changes in the relevant variables and tested as a means of identifying new high risk areas for RMSF in the State. More generally, this method might be adapted to clarify our understanding of the relative importance of individual variables in the ecology of other diseases or environmental health problems. PMID:3090609

Screening analysis and selection of emission reduction concepts for intermittent combustion aircraft engines

NASA Technical Reports Server (NTRS)

Rezy, B. J.; Meyers, J. E.; Tucker, J. R.; Stuckas, S. J.

1976-01-01

An analysis was conducted to screen, evaluate, and select three engine exhaust emission reduction concepts from a group of 14 candidate alternatives. A comprehensive literature search was conducted to survey the emission reduction technology state-of-the-art and establish contact with firms working on intermittent combustion engine development and pollution reduction problems. Concept development, advantages, disadvantages, and expected emission reduction responses are stated. A set of cost effectiveness criteria was developed, appraised for relative importance, and traded off against each concept so that its merit could be determined. A decision model was used to aid the evaluators in managing the criteria, making consistent judgements, calculating merit scores, and ranking the concepts. An Improved Fuel Injection System, Improved Cooling Combustion Chamber, and a Variable Timing Ignition System were recommended to NASA for approval and further concept development. An alternate concept, Air Injection, was also recommended.

CORRELATION PURSUIT: FORWARD STEPWISE VARIABLE SELECTION FOR INDEX MODELS

PubMed Central

Zhong, Wenxuan; Zhang, Tingting; Zhu, Yu; Liu, Jun S.

2012-01-01

In this article, a stepwise procedure, correlation pursuit (COP), is developed for variable selection under the sufficient dimension reduction framework, in which the response variable Y is influenced by the predictors X1, X2, …, Xp through an unknown function of a few linear combinations of them. Unlike linear stepwise regression, COP does not impose a special form of relationship (such as linear) between the response variable and the predictor variables. The COP procedure selects variables that attain the maximum correlation between the transformed response and the linear combination of the variables. Various asymptotic properties of the COP procedure are established, and in particular, its variable selection performance under diverging number of predictors and sample size has been investigated. The excellent empirical performance of the COP procedure in comparison with existing methods are demonstrated by both extensive simulation studies and a real example in functional genomics. PMID:23243388

Input variable selection and calibration data selection for storm water quality regression models.

PubMed

Sun, Siao; Bertrand-Krajewski, Jean-Luc

2013-01-01

Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.

Group Variable Selection Via Convex Log-Exp-Sum Penalty with Application to a Breast Cancer Survivor Study

PubMed Central

Geng, Zhigeng; Wang, Sijian; Yu, Menggang; Monahan, Patrick O.; Champion, Victoria; Wahba, Grace

2017-01-01

Summary In many scientific and engineering applications, covariates are naturally grouped. When the group structures are available among covariates, people are usually interested in identifying both important groups and important variables within the selected groups. Among existing successful group variable selection methods, some methods fail to conduct the within group selection. Some methods are able to conduct both group and within group selection, but the corresponding objective functions are non-convex. Such a non-convexity may require extra numerical effort. In this article, we propose a novel Log-Exp-Sum(LES) penalty for group variable selection. The LES penalty is strictly convex. It can identify important groups as well as select important variables within the group. We develop an efficient group-level coordinate descent algorithm to fit the model. We also derive non-asymptotic error bounds and asymptotic group selection consistency for our method in the high-dimensional setting where the number of covariates can be much larger than the sample size. Numerical results demonstrate the good performance of our method in both variable selection and prediction. We applied the proposed method to an American Cancer Society breast cancer survivor dataset. The findings are clinically meaningful and may help design intervention programs to improve the qualify of life for breast cancer survivors. PMID:25257196

State Size and Government Level Matter Most: A Structural Equation Model of Local Health Department Policy Behaviors.

PubMed

Meyerson, Beth E; Sayegh, M Aaron

2016-01-01

To explore relationships between local health department policy behaviors, levels of government activity, policy focus areas, and selected health department characteristics. Cross-sectional analysis of secondary data from the 2013 National Association of County & City Health Officials (NACCHO) Profile Survey. Local health departments throughout the United States. A total of 2000 local health departments responding to the 2013 Profile Survey of Local Health Departments. Survey data were gathered by the NACCHO. Secondary analysis of reported policy behaviors for the 2013 NACCHO Profile Survey. A structural equation model tested effects on and between state population size, rurality, census region and policy focus, and the latent variables of policy behavior formed from a confirmatory factor analysis. Policy behaviors, levels of government activity (local, state, and federal), policy focus areas, and selected local health department characteristics. The majority (85.1%) of health departments reported at least one of the possible policy behaviors. State population size increased the probability of local policy behavior, and local behavior increased the probability of state policy behavior. State size increased the likelihood of federal policy behavior and the focus on tobacco, emergency preparedness, and obesity/chronic disease. However, the more rural a state was, the more likely policy behavior was at the state and federal levels and not at local levels. Specific policy behaviors mattered less than the level of government activity. Size of state and rurality of health departments influence the government level of policy behavior.

Temporal-spatial distribution of American bison (Bison bison) in a tallgrass prairie fire mosaic

USGS Publications Warehouse

Schuler, K.L.; Leslie, David M.; Shaw, J.H.; Maichak, E.J.

2006-01-01

Fire and bison (Bison bison) are thought to be historically responsible for shaping prairie vegetation in North America. Interactions between temporal-spatial distributions of bison and prescribed burning protocols are important in current restoration of tallgrass prairies. We examined dynamics of bison distribution in a patch-burned tallgrass prairie in the south-central United States relative to bison group size and composition, and burn age and temporal distribution. Bison formed larger mixed groups during summer and smaller sexually segregated groups the rest of the year, and bison selected dormant-season burn patches in the 1st posture growing season most often during spring and summer. Large bison herds selecting recently burned areas resulted in seasonally variable and concentrated grazing pressure that may substantially alter site-specific vegetation. These dynamics must be considered when reintroducing bison and fire into tallgrass prairie because variable outcomes of floral richness and structural complexity are likely depending on temporal-spatial distribution of bison. ?? 2006 American Society of Mammalogists.

Response of lake chemistry to atmospheric deposition and climate in selected Class I wilderness areas in the western United States, 1993-2009

USGS Publications Warehouse

Mast, M. Alisa

2011-01-01

The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Forest Service, Air Resource Management, conducted a study to evaluate long-term trends in lake-water chemistry for 64 high-elevation lakes in selected Class I wilderness areas in Colorado, Idaho, Utah, and Wyoming during 1993 to 2009. Understanding how and why lake chemistry is changing in mountain areas is essential for effectively managing and protecting high-elevation aquatic ecosystems. Trends in emissions, atmospheric deposition, and climate variables (air temperature and precipitation amount) were evaluated over a similar period of record. A main objective of the study was to determine if changes in atmospheric deposition of contaminants in the Rocky Mountain region have resulted in measurable changes in the chemistry of high-elevation lakes. A second objective was to investigate linkages between lake chemistry and air temperature and precipitation to improve understanding of the sensitivity of mountain lakes to climate variability.

Identification of phreatophytic groundwater dependent ecosystems using geospatial technologies

NASA Astrophysics Data System (ADS)

Perez Hoyos, Isabel Cristina

The protection of groundwater dependent ecosystems (GDEs) is increasingly being recognized as an essential aspect for the sustainable management and allocation of water resources. Ecosystem services are crucial for human well-being and for a variety of flora and fauna. However, the conservation of GDEs is only possible if knowledge about their location and extent is available. Several studies have focused on the identification of GDEs at specific locations using ground-based measurements. However, recent progress in technologies such as remote sensing and their integration with geographic information systems (GIS) has provided alternative ways to map GDEs at much larger spatial extents. This study is concerned with the discovery of patterns in geospatial data sets using data mining techniques for mapping phreatophytic GDEs in the United States at 1 km spatial resolution. A methodology to identify the probability of an ecosystem to be groundwater dependent is developed. Probabilities are obtained by modeling the relationship between the known locations of GDEs and main factors influencing groundwater dependency, namely water table depth (WTD) and aridity index (AI). A methodology is proposed to predict WTD at 1 km spatial resolution using relevant geospatial data sets calibrated with WTD observations. An ensemble learning algorithm called random forest (RF) is used in order to model the distribution of groundwater in three study areas: Nevada, California, and Washington, as well as in the entire United States. RF regression performance is compared with a single regression tree (RT). The comparison is based on contrasting training error, true prediction error, and variable importance estimates of both methods. Additionally, remote sensing variables are omitted from the process of fitting the RF model to the data to evaluate the deterioration in the model performance when these variables are not used as an input. Research results suggest that although the prediction accuracy of a single RT is reduced in comparison with RFs, single trees can still be used to understand the interactions that might be taking place between predictor variables and the response variable. Regarding RF, there is a great potential in using the power of an ensemble of trees for prediction of WTD. The superior capability of RF to accurately map water table position in Nevada, California, and Washington demonstrate that this technique can be applied at scales larger than regional levels. It is also shown that the removal of remote sensing variables from the RF training process degrades the performance of the model. Using the predicted WTD, the probability of an ecosystem to be groundwater dependent (GDE probability) is estimated at 1 km spatial resolution. The modeling technique is evaluated in the state of Nevada, USA to develop a systematic approach for the identification of GDEs and it is then applied in the United States. The modeling approach selected for the development of the GDE probability map results from a comparison of the performance of classification trees (CT) and classification forests (CF). Predictive performance evaluation for the selection of the most accurate model is achieved using a threshold independent technique, and the prediction accuracy of both models is assessed in greater detail using threshold-dependent measures. The resulting GDE probability map can potentially be used for the definition of conservation areas since it can be translated into a binary classification map with two classes: GDE and NON-GDE. These maps are created by selecting a probability threshold. It is demonstrated that the choice of this threshold has dramatic effects on deterministic model performance measures.

Report of the Paris consensus meeting on expanded criteria donors in liver transplantation.

PubMed

Durand, François; Renz, John F; Alkofer, Barbara; Burra, Patrizia; Clavien, Pierre-Alain; Porte, Robert J; Freeman, Richard B; Belghiti, Jacques

2008-12-01

Because of organ shortage and a constant imbalance between available organs and candidates for liver transplantation, expanded criteria donors are needed. Experience shows that there are wide variations in the definitions, selection criteria, and use of expanded criteria donors according to different geographic areas and different centers. Overall, selection criteria for donors have tended to be relaxed in recent years. Consensus recommendations are needed. This article reports the conclusions of a consensus meeting held in Paris in March 2007 with the contribution of experts from Europe, the United States, and Asia. Definitions of expanded criteria donors with respect to donor variables (including age, liver function tests, steatosis, infections, malignancies, and heart-beating versus non-heart-beating, among others) are proposed. It is emphasized that donor quality represents a continuum of risk rather than "good or bad." A distinction is made between donor factors that generate increased risk of graft failure and factors independent of graft function, such as transmissible infectious disease or donor-derived malignancy, that may preclude a good outcome. Updated data concerning the risks associated with different donor variables in different recipient populations are given. Recommendations on how to safely expand donor selection criteria are proposed.

Optimized tuner selection for engine performance estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

2013-01-01

A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

From Metaphors to Formalism: A Heuristic Approach to Holistic Assessments of Ecosystem Health.

PubMed

Fock, Heino O; Kraus, Gerd

2016-01-01

Environmental policies employ metaphoric objectives such as ecosystem health, resilience and sustainable provision of ecosystem services, which influence corresponding sustainability assessments by means of normative settings such as assumptions on system description, indicator selection, aggregation of information and target setting. A heuristic approach is developed for sustainability assessments to avoid ambiguity and applications to the EU Marine Strategy Framework Directive (MSFD) and OSPAR assessments are presented. For MSFD, nineteen different assessment procedures have been proposed, but at present no agreed assessment procedure is available. The heuristic assessment framework is a functional-holistic approach comprising an ex-ante/ex-post assessment framework with specifically defined normative and systemic dimensions (EAEPNS). The outer normative dimension defines the ex-ante/ex-post framework, of which the latter branch delivers one measure of ecosystem health based on indicators and the former allows to account for the multi-dimensional nature of sustainability (social, economic, ecological) in terms of modeling approaches. For MSFD, the ex-ante/ex-post framework replaces the current distinction between assessments based on pressure and state descriptors. The ex-ante and the ex-post branch each comprise an inner normative and a systemic dimension. The inner normative dimension in the ex-post branch considers additive utility models and likelihood functions to standardize variables normalized with Bayesian modeling. Likelihood functions allow precautionary target setting. The ex-post systemic dimension considers a posteriori indicator selection by means of analysis of indicator space to avoid redundant indicator information as opposed to a priori indicator selection in deconstructive-structural approaches. Indicator information is expressed in terms of ecosystem variability by means of multivariate analysis procedures. The application to the OSPAR assessment for the southern North Sea showed, that with the selected 36 indicators 48% of ecosystem variability could be explained. Tools for the ex-ante branch are risk and ecosystem models with the capability to analyze trade-offs, generating model output for each of the pressure chains to allow for a phasing-out of human pressures. The Bayesian measure of ecosystem health is sensitive to trends in environmental features, but robust to ecosystem variability in line with state space models. The combination of the ex-ante and ex-post branch is essential to evaluate ecosystem resilience and to adopt adaptive management. Based on requirements of the heuristic approach, three possible developments of this concept can be envisioned, i.e. a governance driven approach built upon participatory processes, a science driven functional-holistic approach requiring extensive monitoring to analyze complete ecosystem variability, and an approach with emphasis on ex-ante modeling and ex-post assessment of well-studied subsystems.

From Metaphors to Formalism: A Heuristic Approach to Holistic Assessments of Ecosystem Health

PubMed Central

Kraus, Gerd

2016-01-01

Environmental policies employ metaphoric objectives such as ecosystem health, resilience and sustainable provision of ecosystem services, which influence corresponding sustainability assessments by means of normative settings such as assumptions on system description, indicator selection, aggregation of information and target setting. A heuristic approach is developed for sustainability assessments to avoid ambiguity and applications to the EU Marine Strategy Framework Directive (MSFD) and OSPAR assessments are presented. For MSFD, nineteen different assessment procedures have been proposed, but at present no agreed assessment procedure is available. The heuristic assessment framework is a functional-holistic approach comprising an ex-ante/ex-post assessment framework with specifically defined normative and systemic dimensions (EAEPNS). The outer normative dimension defines the ex-ante/ex-post framework, of which the latter branch delivers one measure of ecosystem health based on indicators and the former allows to account for the multi-dimensional nature of sustainability (social, economic, ecological) in terms of modeling approaches. For MSFD, the ex-ante/ex-post framework replaces the current distinction between assessments based on pressure and state descriptors. The ex-ante and the ex-post branch each comprise an inner normative and a systemic dimension. The inner normative dimension in the ex-post branch considers additive utility models and likelihood functions to standardize variables normalized with Bayesian modeling. Likelihood functions allow precautionary target setting. The ex-post systemic dimension considers a posteriori indicator selection by means of analysis of indicator space to avoid redundant indicator information as opposed to a priori indicator selection in deconstructive-structural approaches. Indicator information is expressed in terms of ecosystem variability by means of multivariate analysis procedures. The application to the OSPAR assessment for the southern North Sea showed, that with the selected 36 indicators 48% of ecosystem variability could be explained. Tools for the ex-ante branch are risk and ecosystem models with the capability to analyze trade-offs, generating model output for each of the pressure chains to allow for a phasing-out of human pressures. The Bayesian measure of ecosystem health is sensitive to trends in environmental features, but robust to ecosystem variability in line with state space models. The combination of the ex-ante and ex-post branch is essential to evaluate ecosystem resilience and to adopt adaptive management. Based on requirements of the heuristic approach, three possible developments of this concept can be envisioned, i.e. a governance driven approach built upon participatory processes, a science driven functional-holistic approach requiring extensive monitoring to analyze complete ecosystem variability, and an approach with emphasis on ex-ante modeling and ex-post assessment of well-studied subsystems. PMID:27509185

Evaluation of the Botanical Authenticity and Phytochemical Profile of Black Cohosh Products by High-Performance Liquid Chromatography with Selected Ion Monitoring Liquid Chromatography–Mass Spectrometry

PubMed Central

Jiang, Bei; Kronenberg, Fredi; Nuntanakorn, Paiboon; Qiu, Ming-Hua; Kennelly, Edward J.

2011-01-01

Black cohosh (Actaea racemosa L., syn. Cimicifuga racemosa L.) has become increasingly popular as a dietary supplement in the United States for the treatment of symptoms related to menopause, but the botanical authenticity of most products containing black cohosh has not been evaluated, nor is manufacturing highly regulated in the United States. In this study, 11 black cohosh products were analyzed for triterpene glycosides, phenolic constituents, and formononetin by high-performance liquid chromatography–photodiode array detection and a new selected ion monitoring liquid chromatography–mass spectrometry method. Three of the 11 products were found to contain the marker compound cimifugin and not cimiracemoside C, thereby indicating that these plants contain Asian Actaea instead of black cohosh. One product contained both black cohosh and an Asian Actaea species. For the products containing only black cohosh, there was significant product-to-product variability in the amounts of the selected triterpene glycosides and phenolic constituents, and as expected, no formononetin was detected. PMID:16637680

Optical hybrid quantum teleportation and its applications

NASA Astrophysics Data System (ADS)

Takeda, Shuntaro; Okada, Masanori; Furusawa, Akira

2017-08-01

Quantum teleportation, a transfer protocol of quantum states, is the essence of many sophisticated quantum information protocols. There have been two complementary approaches to optical quantum teleportation: discrete variables (DVs) and continuous variables (CVs). However, both approaches have pros and cons. Here we take a "hybrid" approach to overcome the current limitations: CV quantum teleportation of DVs. This approach enabled the first realization of deterministic quantum teleportation of photonic qubits without post-selection. We also applied the hybrid scheme to several experiments, including entanglement swapping between DVs and CVs, conditional CV teleportation of single photons, and CV teleportation of qutrits. We are now aiming at universal, scalable, and fault-tolerant quantum computing based on these hybrid technologies.

Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area.

PubMed

Ye, Qing; Gu, Peishi; Li, Hugh Z; Robinson, Ellis S; Lipsky, Eric; Kaltsonoudis, Christos; Lee, Alex K Y; Apte, Joshua S; Robinson, Allen L; Sullivan, Ryan C; Presto, Albert A; Donahue, Neil M

2018-05-30

Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km 2 . Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.

Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

PubMed

Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

2017-07-01

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in using RF to develop predictive models with large environmental data sets.

The concept of the set to objectification of LLLT exposure

NASA Astrophysics Data System (ADS)

Gryko, Lukasz; Gilewski, Marian; Szymanska, Justyna; Zajac, Andrzej; Rosc, Danuta

2013-01-01

In this article authors present the developed optoelectronic set for controlled, repeatable exposure by electromagnetic radiation of biological structures in the spectral band of tissue transmission window 600-1000 nm. The set allows for an objective selection and control of exposure parameters and comparison of results for variable energetic, spectral and polarization parameters of radiation beam. Possibility of objective diagnostics of tissue state during laser treatment was provided in the presented optoelectronic set.

A Model of Human Variability in Viable Ship Design

DTIC Science & Technology

2014-02-21

when an organization is in a state of change. For example, an alternative to screening out individuals for a new job role is the self -selection of...being done and group members little care what happens beyond their self -imposed borders. The proposed extension addresses team decay with regard to the...these, the paygrade of team members probably reflects qualities of most interest from the authors’ point of 22 view. Paygrade is highly

Perceptions of preparedness of LBS I teachers in the state of Illinois and graduates of Illinois State University's LBS I program to collaborate in teaching grade 7--12 math, science, and social science

NASA Astrophysics Data System (ADS)

Caldwell, Janet E.

The expectations for no child to be left behind are leading to increased emphasis on teaching math, science, and social science effectively to students with disabilities. This study utilized information collected from online surveys to examine how current LBS I teachers and individuals graduating from the Illinois State University teacher certification program in LBS I perceive their preparedness to teach these subjects. Participants provided information about coursework and life experiences, and they made suggestions about teacher preparation and professional development programs. Six key items forming the composite variable focused on level of preparation in (a) best practices, (b) selecting materials, (c) selecting objectives, (d) adapting instructional strategies, (e) planning lessons, and (f) and evaluating outcomes. Only 30 LBS I teachers of the 282 contacted by e-mail completed surveys. Of 115 graduates contacted, 71 participated in the original survey and 23 participated in a follow-up survey. Data were analyzed to learn more about the teachers' self-perceptions regarding preparedness to teach math, science, or social science. There was a correlation between perceived level of knowledge and the composite preparation variable for all subjects, but no correlation with length of teaching. Both groups indicated high school content courses were important in preparation to teach. Teachers also indicated collaboration and graduates indicated grade school learning. The most frequent recommendation for both teacher preparation and professional development was additional methods courses. A survey distributed to math, science, and social science teachers of Grades 7--12 asked about their perceptions of the preparedness of LBS I teachers to teach their area of content. Few surveys were completed for each subject so they were examined qualitatively. There was variability among participants, but generally the content area teachers rated themselves as more prepared than the LBS I teachers.

Robust check loss-based variable selection of high-dimensional single-index varying-coefficient model

NASA Astrophysics Data System (ADS)

Song, Yunquan; Lin, Lu; Jian, Ling

2016-07-01

Single-index varying-coefficient model is an important mathematical modeling method to model nonlinear phenomena in science and engineering. In this paper, we develop a variable selection method for high-dimensional single-index varying-coefficient models using a shrinkage idea. The proposed procedure can simultaneously select significant nonparametric components and parametric components. Under defined regularity conditions, with appropriate selection of tuning parameters, the consistency of the variable selection procedure and the oracle property of the estimators are established. Moreover, due to the robustness of the check loss function to outliers in the finite samples, our proposed variable selection method is more robust than the ones based on the least squares criterion. Finally, the method is illustrated with numerical simulations.

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

PubMed

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.

Assessing the accuracy and stability of variable selection ...

EPA Pesticide Factsheets

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used, or stepwise procedures are employed which iteratively add/remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating dataset consists of the good/poor condition of n=1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p=212) of landscape features from the StreamCat dataset. Two types of RF models are compared: a full variable set model with all 212 predictors, and a reduced variable set model selected using a backwards elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors, and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substanti

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

PubMed

Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

2014-10-07

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

Punishment induced behavioural and neurophysiological variability reveals dopamine-dependent selection of kinematic movement parameters

PubMed Central

Galea, Joseph M.; Ruge, Diane; Buijink, Arthur; Bestmann, Sven; Rothwell, John C.

2013-01-01

Action selection describes the high-level process which selects between competing movements. In animals, behavioural variability is critical for the motor exploration required to select the action which optimizes reward and minimizes cost/punishment, and is guided by dopamine (DA). The aim of this study was to test in humans whether low-level movement parameters are affected by punishment and reward in ways similar to high-level action selection. Moreover, we addressed the proposed dependence of behavioural and neurophysiological variability on DA, and whether this may underpin the exploration of kinematic parameters. Participants performed an out-and-back index finger movement and were instructed that monetary reward and punishment were based on its maximal acceleration (MA). In fact, the feedback was not contingent on the participant’s behaviour but pre-determined. Blocks highly-biased towards punishment were associated with increased MA variability relative to blocks with either reward or without feedback. This increase in behavioural variability was positively correlated with neurophysiological variability, as measured by changes in cortico-spinal excitability with transcranial magnetic stimulation over the primary motor cortex. Following the administration of a DA-antagonist, the variability associated with punishment diminished and the correlation between behavioural and neurophysiological variability no longer existed. Similar changes in variability were not observed when participants executed a pre-determined MA, nor did DA influence resting neurophysiological variability. Thus, under conditions of punishment, DA-dependent processes influence the selection of low-level movement parameters. We propose that the enhanced behavioural variability reflects the exploration of kinematic parameters for less punishing, or conversely more rewarding, outcomes. PMID:23447607

A New Variable Weighting and Selection Procedure for K-Means Cluster Analysis

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

A variance-to-range ratio variable weighting procedure is proposed. We show how this weighting method is theoretically grounded in the inherent variability found in data exhibiting cluster structure. In addition, a variable selection procedure is proposed to operate in conjunction with the variable weighting technique. The performances of these…

A survey of variable selection methods in two Chinese epidemiology journals

PubMed Central

2010-01-01

Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163) via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44%) used stepwise procedures, 89 (41%) tested individual regression coefficients, but 33 (15%) did not mention how variables were selected. Sixty percent (58/97) of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals. PMID:20920252

Methodological development for selection of significant predictors explaining fatal road accidents.

PubMed

Dadashova, Bahar; Arenas-Ramírez, Blanca; Mira-McWilliams, José; Aparicio-Izquierdo, Francisco

2016-05-01

Identification of the most relevant factors for explaining road accident occurrence is an important issue in road safety research, particularly for future decision-making processes in transport policy. However model selection for this particular purpose is still an ongoing research. In this paper we propose a methodological development for model selection which addresses both explanatory variable and adequate model selection issues. A variable selection procedure, TIM (two-input model) method is carried out by combining neural network design and statistical approaches. The error structure of the fitted model is assumed to follow an autoregressive process. All models are estimated using Markov Chain Monte Carlo method where the model parameters are assigned non-informative prior distributions. The final model is built using the results of the variable selection. For the application of the proposed methodology the number of fatal accidents in Spain during 2000-2011 was used. This indicator has experienced the maximum reduction internationally during the indicated years thus making it an interesting time series from a road safety policy perspective. Hence the identification of the variables that have affected this reduction is of particular interest for future decision making. The results of the variable selection process show that the selected variables are main subjects of road safety policy measures. Published by Elsevier Ltd.

Development of a Robust Identifier for NPPs Transients Combining ARIMA Model and EBP Algorithm

NASA Astrophysics Data System (ADS)

Moshkbar-Bakhshayesh, Khalil; Ghofrani, Mohammad B.

2014-08-01

This study introduces a novel identification method for recognition of nuclear power plants (NPPs) transients by combining the autoregressive integrated moving-average (ARIMA) model and the neural network with error backpropagation (EBP) learning algorithm. The proposed method consists of three steps. First, an EBP based identifier is adopted to distinguish the plant normal states from the faulty ones. In the second step, ARIMA models use integrated (I) process to convert non-stationary data of the selected variables into stationary ones. Subsequently, ARIMA processes, including autoregressive (AR), moving-average (MA), or autoregressive moving-average (ARMA) are used to forecast time series of the selected plant variables. In the third step, for identification the type of transients, the forecasted time series are fed to the modular identifier which has been developed using the latest advances of EBP learning algorithm. Bushehr nuclear power plant (BNPP) transients are probed to analyze the ability of the proposed identifier. Recognition of transient is based on similarity of its statistical properties to the reference one, rather than the values of input patterns. More robustness against noisy data and improvement balance between memorization and generalization are salient advantages of the proposed identifier. Reduction of false identification, sole dependency of identification on the sign of each output signal, selection of the plant variables for transients training independent of each other, and extendibility for identification of more transients without unfavorable effects are other merits of the proposed identifier.

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

Smith, Braeton J.; Shaneyfelt, Calvin R.

A NISAC study on the economic effects of a hypothetical H1N1 pandemic was done in order to assess the differential impacts at the state and industry levels given changes in absenteeism, mortality, and consumer spending rates. Part of the analysis was to determine if there were any direct relationships between pandemic impacts and gross domestic product (GDP) losses. Multiple regression analysis was used because it shows very clearly which predictors are significant in their impact on GDP. GDP impact data taken from the REMI PI+ (Regional Economic Models, Inc., Policy Insight +) model was used to serve as the responsemore » variable. NISAC economists selected the average absenteeism rate, mortality rate, and consumer spending categories as the predictor variables. Two outliers were found in the data: Nevada and Washington, DC. The analysis was done twice, with the outliers removed for the second analysis. The second set of regressions yielded a cleaner model, but for the purposes of this study, the analysts deemed it not as useful because particular interest was placed on determining the differential impacts to states. Hospitals and accommodation were found to be the most important predictors of percentage change in GDP among the consumer spending variables.« less

Far-Ultraviolet Spectroscopy of Three Long-Period Novalike Variables

NASA Astrophysics Data System (ADS)

Bisol, Alexandra C.; Godon, Patrick; Sion, Edward M.

2012-02-01

We have selected three novalike variables at the long-period extreme of novalike orbital periods: V363 Aur, RZ Gru, and AC Cnc, all with IUE archival far-ultraviolet spectra. All are UX UMa-type novalike variables and all have Porb > 7 hr. V363 Aur is a bona fide SW Sex star, and AC Cnc is a probable one, while RZ Gru has not proven to be a member of the SW Sex subclass. We have carried out the first synthetic spectral analysis of far-ultraviolet spectra of the three systems using state-of-the-art models of both accretion disks and white dwarf photospheres. We find that the FUV spectral energy distribution of both V363 Aur and RZ Gru are in agreement with optically thick steady-state accretion disk models in which the luminous disk accounts for 100% of the FUV light. We present accretion rates and model-derived distances for V363 Aur and RZ Gru. For AC Cnc, we find that a hot accreting white dwarf accounts for ˜60% of the FUV light, with an accretion disk providing the rest. We compare our accretion rates and model-derived distances with estimates in the literature.

Socioeconomic determinants of fertility: selected Mexican regions, 1976-1977.

PubMed

Pick, J B; Butler, E W; Pavgi, S

1988-01-01

Cumulative fertility is analyzed for 4 regions of Mexico, based on World Fertility Survey data of 1976-77; the state of Baja California, the Northwest region, the State of Jalisco, and the Northeast region. Based on stepwise regression methodology, the study compares results for 12 subsamples of married respondents, 3 age categories by 4 regions. The dependent variables are children ever born and children ever born in the last 5 years. Migration, urban, educational, and occupational variables are included as independent variables. Regression results reveal level of education is the major, and negative, influence on fertility. Other results include specific negative effects for prior occupation, size of place of residence, and childhood place of residence. Fertility effects appear different for migration origin and destination regions, but more similar for younger ages. Effects of migration on fertility are small. Mean fertility as measured by children ever born was 4.34 for the 1976-77 World Fertility Survey samples versus 3.69 for the Mexican census of 1980. Fertility varied somewhat by region with the highest and lowest values in Jalisco and the Northeast, respectively. Expected age-related changes in fertility were noted.

Development and validation of a general purpose linearization program for rigid aircraft models

NASA Technical Reports Server (NTRS)

Duke, E. L.; Antoniewicz, R. F.

1985-01-01

A FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft models is discussed. The program LINEAR numerically determines a linear systems model using nonlinear equations of motion and a user-supplied, nonlinear aerodynamic model. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model. Also, included in the report is a comparison of linear and nonlinear models for a high performance aircraft.

The relationship of document and quantitative literacy with learning styles and selected personal variables for aerospace technology students at Indiana State University

NASA Astrophysics Data System (ADS)

Martin, Royce Ann

The purpose of this study was to determine the extent that student scores on a researcher-constructed quantitative and document literacy test, the Aviation Documents Delineator (ADD), were associated with (a) learning styles (imaginative, analytic, common sense, dynamic, and undetermined), as identified by the Learning Type Measure, (b) program curriculum (aerospace administration, professional pilot, both aerospace administration and professional pilot, other, or undeclared), (c) overall cumulative grade point average at Indiana State University, and (d) year in school (freshman, sophomore, junior, or senior). The Aviation Documents Delineator (ADD) was a three-part, 35 question survey that required students to interpret graphs, tables, and maps. Tasks assessed in the ADD included (a) locating, interpreting, and describing specific data displayed in the document, (b) determining data for a specified point on the table through interpolation, (c) comparing data for a string of variables representing one aspect of aircraft performance to another string of variables representing a different aspect of aircraft performance, (d) interpreting the documents to make decisions regarding emergency situations, and (e) performing single and/or sequential mathematical operations on a specified set of data. The Learning Type Measure (LTM) was a 15 item self-report survey developed by Bernice McCarthy (1995) to profile an individual's processing and perception tendencies in order to reveal different individual approaches to learning. The sample used in this study included 143 students enrolled in Aerospace Technology Department courses at Indiana State University in the fall of 1996. The ADD and the LTM were administered to each subject. Data collected in this investigation were analyzed using a stepwise multiple regression analysis technique. Results of the study revealed that the variables, year in school and GPA, were significant predictors of the criterion variables, document, quantitative, and total literacy, when utilizing the ADD. The variables learning style and program of study were found not to be significant predictors of literacy scores on the ADD instrument.

Differential sea-state bias: A case study using TOPEX/POSEIDON data

NASA Technical Reports Server (NTRS)

Stewart, Robert H.; Devalla, B.

1994-01-01

We used selected data from the NASA altimeter TOPEX/POSEIDON to calculate differences in range measured by the C and Ku-band altimeters when the satellite overflew 5 to 15 m waves late at night. The range difference is due to free electrons in the ionosphere and to errors in sea-state bias. For the selected data the ionospheric influence on Ku range is less than 2 cm. Any difference in range over short horizontal distances is due only to a small along-track variability of the ionosphere and to errors in calculating the differential sea-state bias. We find that there is a barely detectable error in the bias in the geophysical data records. The wave-induced error in the ionospheric correction is less than 0.2% of significant wave height. The equivalent error in differential range is less than 1% of wave height. Errors in the differential sea-state bias calculations appear to be small even for extreme wave heights that greatly exceed the conditions on which the bias is based. The results also improved our confidence in the sea-state bias correction used for calculating the geophysical data records. Any error in the correction must influence Ku and C-band ranges almost equally.

Post-Wildfire Potential for Carbon and Nitrogen Sequestration in the Southwestern United States in Restored Ephemeral and Intermittent Stream Channels

NASA Astrophysics Data System (ADS)

Callegary, J. B.; Norman, L.; Eastoe, C. J.; Sankey, J. B.; Youberg, A.

2016-12-01

The Kemp's ridley sea turtle (Lepidochelys kempii) is the most endangered sea turtle in the world, largely due to the limited geographic range of its nesting habitat. In the U.S., the majority of nesting occurs along Padre Island National Seashore (PAIS) in Texas. There has been limited research regarding the connection between beach geomorphology and Kemp's ridley nesting patterns, but studies concerning other sea turtle species suggest that certain beach geomorphology variables, such as beach slope and width, influence nest site selection. This research investigates terrestrial habitat variability of the Kemp's ridley sea turtle and quantifies the connection between beach geomorphology and Kemp's ridley nest site selection on PAIS and South Padre Island, Texas. Airborne topographic lidar data collected annually along the Texas coast from 2009 through 2012 was utilized to extract beach geomorphology characteristics, such as beach slope and width, dune height, and surface roughness, among others. The coordinates of observed Kemp's ridley nests from corresponding years were integrated with the aforementioned data in statistical models, which analyzed the influence of both general trends in geomorphology and individual morphologic variables on nest site selection. This research identified the terrestrial habitat variability of the Kemp's ridley and quantified the range of geomorphic characteristics of nesting beaches. Initial results indicate that dune width, beach width, and wind speed are significant variables in relation to nest presence, using an alpha of 0.1. Higher wind speeds and narrower beaches and foredunes favor nest presence. The average nest elevation is 1.13 m above mean sea level, which corresponds to the area directly below the potential vegetation line, and the majority of nesting occurs between the elevations of 0.68 m and 1.4 m above mean sea level. The results of this study include new information regarding Kemp's ridley beach habitat and its influence on nesting patterns that could be useful for the conservation and management of the species.

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

PubMed

Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

A non-linear data mining parameter selection algorithm for continuous variables

PubMed Central

Razavi, Marianne; Brady, Sean

2017-01-01

In this article, we propose a new data mining algorithm, by which one can both capture the non-linearity in data and also find the best subset model. To produce an enhanced subset of the original variables, a preferred selection method should have the potential of adding a supplementary level of regression analysis that would capture complex relationships in the data via mathematical transformation of the predictors and exploration of synergistic effects of combined variables. The method that we present here has the potential to produce an optimal subset of variables, rendering the overall process of model selection more efficient. This algorithm introduces interpretable parameters by transforming the original inputs and also a faithful fit to the data. The core objective of this paper is to introduce a new estimation technique for the classical least square regression framework. This new automatic variable transformation and model selection method could offer an optimal and stable model that minimizes the mean square error and variability, while combining all possible subset selection methodology with the inclusion variable transformations and interactions. Moreover, this method controls multicollinearity, leading to an optimal set of explanatory variables. PMID:29131829

Optimal Sampling to Provide User-Specific Climate Information.

NASA Astrophysics Data System (ADS)

Panturat, Suwanna

The types of weather-related world problems which are of socio-economic importance selected in this study as representative of three different levels of user groups include: (i) a regional problem concerned with air pollution plumes which lead to acid rain in the north eastern United States, (ii) a state-level problem in the form of winter wheat production in Oklahoma, and (iii) an individual-level problem involving reservoir management given errors in rainfall estimation at Lake Ellsworth, upstream from Lawton, Oklahoma. The study is aimed at designing optimal sampling networks which are based on customer value systems and also abstracting from data sets that information which is most cost-effective in reducing the climate-sensitive aspects of a given user problem. Three process models being used in this study to interpret climate variability in terms of the variables of importance to the user comprise: (i) the HEFFTER-SAMSON diffusion model as the climate transfer function for acid rain, (ii) the CERES-MAIZE plant process model for winter wheat production and (iii) the AGEHYD streamflow model selected as "a black box" for reservoir management. A state-of-the-art Non Linear Program (NLP) algorithm for minimizing an objective function is employed to determine the optimal number and location of various sensors. Statistical quantities considered in determining sensor locations including Bayes Risk, the chi-squared value, the probability of the Type I error (alpha) and the probability of the Type II error (beta) and the noncentrality parameter delta^2. Moreover, the number of years required to detect a climate change resulting in a given bushel per acre change in mean wheat production is determined; the number of seasons of observations required to reduce the standard deviation of the error variance of the ambient sulfur dioxide to less than a certain percent of the mean is found; and finally the policy of maintaining pre-storm flood pools at selected levels is examined given information from the optimal sampling network as defined by the study.

Serotonin Decreases the Gain of Visual Responses in Awake Macaque V1.

PubMed

Seillier, Lenka; Lorenz, Corinna; Kawaguchi, Katsuhisa; Ott, Torben; Nieder, Andreas; Pourriahi, Paria; Nienborg, Hendrikje

2017-11-22

Serotonin, an important neuromodulator in the brain, is implicated in affective and cognitive functions. However, its role even for basic cortical processes is controversial. For example, in the mammalian primary visual cortex (V1), heterogenous serotonergic modulation has been observed in anesthetized animals. Here, we combined extracellular single-unit recordings with iontophoresis in awake animals. We examined the role of serotonin on well-defined tuning properties (orientation, spatial frequency, contrast, and size) in V1 of two male macaque monkeys. We find that in the awake macaque the modulatory effect of serotonin is surprisingly uniform: it causes a mainly multiplicative decrease of the visual responses and a slight increase in the stimulus-selective response latency. Moreover, serotonin neither systematically changes the selectivity or variability of the response, nor the interneuronal correlation unexplained by the stimulus ("noise-correlation"). The modulation by serotonin has qualitative similarities with that for a decrease in stimulus contrast, but differs quantitatively from decreasing contrast. It can be captured by a simple additive change to a threshold-linear spiking nonlinearity. Together, our results show that serotonin is well suited to control the response gain of neurons in V1 depending on the animal's behavioral or motivational context, complementing other known state-dependent gain-control mechanisms. SIGNIFICANCE STATEMENT Serotonin is an important neuromodulator in the brain and a major target for drugs used to treat psychiatric disorders. Nonetheless, surprisingly little is known about how it shapes information processing in sensory areas. Here we examined the serotonergic modulation of visual processing in the primary visual cortex of awake behaving macaque monkeys. We found that serotonin mainly decreased the gain of the visual responses, without systematically changing their selectivity, variability, or covariability. This identifies a simple computational function of serotonin for state-dependent sensory processing, depending on the animal's affective or motivational state. Copyright © 2017 Seillier, Lorenz et al.

Serotonin Decreases the Gain of Visual Responses in Awake Macaque V1

PubMed Central

Seillier, Lenka; Lorenz, Corinna; Kawaguchi, Katsuhisa; Ott, Torben; Pourriahi, Paria

2017-01-01

Serotonin, an important neuromodulator in the brain, is implicated in affective and cognitive functions. However, its role even for basic cortical processes is controversial. For example, in the mammalian primary visual cortex (V1), heterogenous serotonergic modulation has been observed in anesthetized animals. Here, we combined extracellular single-unit recordings with iontophoresis in awake animals. We examined the role of serotonin on well-defined tuning properties (orientation, spatial frequency, contrast, and size) in V1 of two male macaque monkeys. We find that in the awake macaque the modulatory effect of serotonin is surprisingly uniform: it causes a mainly multiplicative decrease of the visual responses and a slight increase in the stimulus-selective response latency. Moreover, serotonin neither systematically changes the selectivity or variability of the response, nor the interneuronal correlation unexplained by the stimulus (“noise-correlation”). The modulation by serotonin has qualitative similarities with that for a decrease in stimulus contrast, but differs quantitatively from decreasing contrast. It can be captured by a simple additive change to a threshold-linear spiking nonlinearity. Together, our results show that serotonin is well suited to control the response gain of neurons in V1 depending on the animal's behavioral or motivational context, complementing other known state-dependent gain-control mechanisms. SIGNIFICANCE STATEMENT Serotonin is an important neuromodulator in the brain and a major target for drugs used to treat psychiatric disorders. Nonetheless, surprisingly little is known about how it shapes information processing in sensory areas. Here we examined the serotonergic modulation of visual processing in the primary visual cortex of awake behaving macaque monkeys. We found that serotonin mainly decreased the gain of the visual responses, without systematically changing their selectivity, variability, or covariability. This identifies a simple computational function of serotonin for state-dependent sensory processing, depending on the animal's affective or motivational state. PMID:29042433

[Variability patterns of nest construction, physiological state, and morphometric traits in honey bee].

PubMed

Es'kov, E K; Es'kova, M D

2014-01-01

High variability of cells size is used selectively for reproduction of working bees and drones. A decrease in both distance between cells and cells size themselves causes similar effects to body mass and morphometric traits of developing individuals. Adaptation of honey bees to living in shelters has led to their becoming tolerant to hypoxia. Improvement of ethological and physiological mechanisms of thermal regulation is associated with limitation of ecological valence and acquiring of stenothermic features by breed. Optimal thermal conditions for breed are limited by the interval 33-34.5 degrees C. Deviations of temperature by 3-4 degrees C beyond this range have minimum lethal effect at embryonic stage of development and medium effect at the stage of pre-pupa and pupa. Developing at the low bound of the vital range leads to increasing, while developing at the upper bound--to decreasing of body mass, mandibular and hypopharyngeal glands, as well as other organs, which, later, affects the variability of these traits during the adult stage of development. Eliminative and teratogenic efficiency of ecological factors that affect a breed is most often manifested in underdevelopment of wings. However, their size (in case of wing laminas formation). is characterized by relatively low variability and size-dependent asymmetry. Asymmetry variability of wings and other pair organs is expressed through realignment of size excess from right- to left-side one with respect to their increase. Selective elimination by those traits whose emerging probability increases as developmental conditions deviate from the optimal ones promotes restrictions on individual variability. Physiological mechanisms that facilitate adaptability enhancement under conditions of increasing anthropogenic contamination of eivironment and trophic substrates consumed by honey bees, arrear to be toxicants accumulation in rectum and crops' ability to absorb contaminants from nectar in course of its processing to honey.

Multistate λ-local-elevation umbrella-sampling (MS-λ-LEUS): method and application to the complexation of cations by crown ethers.

PubMed

Bieler, Noah S; Tschopp, Jan P; Hünenberger, Philippe H

2015-06-09

An extension of the λ-local-elevation umbrella-sampling (λ-LEUS) scheme [ Bieler et al. J. Chem. Theory Comput. 2014 , 10 , 3006 ] is proposed to handle the multistate (MS) situation, i.e. the calculation of the relative free energies of multiple physical states based on a single simulation. The key element of the MS-λ-LEUS approach is to use a single coupling variable Λ controlling successive pairwise mutations between the states of interest in a cyclic fashion. The Λ variable is propagated dynamically as an extended-system variable, using a coordinate transformation with plateaus and a memory-based biasing potential as in λ-LEUS. Compared to other available MS schemes (one-step perturbation, enveloping distribution sampling and conventional λ-dynamics) the proposed method presents a number of important advantages, namely: (i) the physical states are visited explicitly and over finite time periods; (ii) the extent of unphysical space required to ensure transitions is kept minimal and, in particular, one-dimensional; (iii) the setup protocol solely requires the topologies of the physical states; and (iv) the method only requires limited modifications in a simulation code capable of handling two-state mutations. As an initial application, the absolute binding free energies of five alkali cations to three crown ethers in three different solvents are calculated. The results are found to reproduce qualitatively the main experimental trends and, in particular, the experimental selectivity of 18C6 for K(+) in water and methanol, which is interpreted in terms of opposing trends along the cation series between the solvation free energy of the cation and the direct electrostatic interactions within the complex.

Bacterial Microcolonies in Gel Beads for High-Throughput Screening of Libraries in Synthetic Biology.

PubMed

Duarte, José M; Barbier, Içvara; Schaerli, Yolanda

2017-11-17

Synthetic biologists increasingly rely on directed evolution to optimize engineered biological systems. Applying an appropriate screening or selection method for identifying the potentially rare library members with the desired properties is a crucial step for success in these experiments. Special challenges include substantial cell-to-cell variability and the requirement to check multiple states (e.g., being ON or OFF depending on the input). Here, we present a high-throughput screening method that addresses these challenges. First, we encapsulate single bacteria into microfluidic agarose gel beads. After incubation, they harbor monoclonal bacterial microcolonies (e.g., expressing a synthetic construct) and can be sorted according their fluorescence by fluorescence activated cell sorting (FACS). We determine enrichment rates and demonstrate that we can measure the average fluorescent signals of microcolonies containing phenotypically heterogeneous cells, obviating the problem of cell-to-cell variability. Finally, we apply this method to sort a pBAD promoter library at ON and OFF states.

Correlation of HIV/AIDS prevalence with social, economic and demographic measures in Andhra Pradesh, India.

PubMed

Kandwal, R; Garg, P K; Garg, R D

2012-09-01

In this study, the spatial distribution of HIV/AIDS is investigated with several socioeconomic variables. Results of exploratory analysis of correlations have been reported between the prevalence of HIV/AIDS as it is the dependent variable against a range of socioeconomic and demographic measures in Andhra Pradesh, India. The state ranks among the top six states for HIV prevalence in the country. This study offers an insight to the distribution of HIV prevalence and the potential impacts of the epidemic on the high-, medium- and low-risk groups determined through cluster analyses of population and cumulative HIV infections. The impacts have been addressed through selective social and economic measures as HIV/AIDS is considered more of a social epidemic. These results help in identifying factors that are contributing more towards the spread of HIV and so guide policies to counteract dominant factors in order to control the disease. Future investigations are necessary to elucidate characterization of the rates of infection according to gender, age groups and regions.

Large Engine Technology (LET) Short Haul Civil Tiltrotor Contingency Power Materials Knowledge and Lifing Methodologies

NASA Technical Reports Server (NTRS)

Spring, Samuel D.

2006-01-01

This report documents the results of an experimental program conducted on two advanced metallic alloy systems (Rene' 142 directionally solidified alloy (DS) and Rene' N6 single crystal alloy) and the characterization of two distinct internal state variable inelastic constitutive models. The long term objective of the study was to develop a computational life prediction methodology that can integrate the obtained material data. A specialized test matrix for characterizing advanced unified viscoplastic models was specified and conducted. This matrix included strain controlled tensile tests with intermittent relaxtion test with 2 hr hold times, constant stress creep tests, stepped creep tests, mixed creep and plasticity tests, cyclic temperature creep tests and tests in which temperature overloads were present to simulate actual operation conditions for validation of the models. The selected internal state variable models where shown to be capable of representing the material behavior exhibited by the experimental results; however the program ended prior to final validation of the models.

Evaluation of variable selection methods for random forests and omics data sets.

PubMed

Degenhardt, Frauke; Seifert, Stephan; Szymczak, Silke

2017-10-16

Machine learning methods and in particular random forests are promising approaches for prediction based on high dimensional omics data sets. They provide variable importance measures to rank predictors according to their predictive power. If building a prediction model is the main goal of a study, often a minimal set of variables with good prediction performance is selected. However, if the objective is the identification of involved variables to find active networks and pathways, approaches that aim to select all relevant variables should be preferred. We evaluated several variable selection procedures based on simulated data as well as publicly available experimental methylation and gene expression data. Our comparison included the Boruta algorithm, the Vita method, recurrent relative variable importance, a permutation approach and its parametric variant (Altmann) as well as recursive feature elimination (RFE). In our simulation studies, Boruta was the most powerful approach, followed closely by the Vita method. Both approaches demonstrated similar stability in variable selection, while Vita was the most robust approach under a pure null model without any predictor variables related to the outcome. In the analysis of the different experimental data sets, Vita demonstrated slightly better stability in variable selection and was less computationally intensive than Boruta.In conclusion, we recommend the Boruta and Vita approaches for the analysis of high-dimensional data sets. Vita is considerably faster than Boruta and thus more suitable for large data sets, but only Boruta can also be applied in low-dimensional settings. © The Author 2017. Published by Oxford University Press.

Comparisons of Selected Student and Teacher Variables in All-Girls and Coeducational Physical Education Environments

ERIC Educational Resources Information Center

Derry, Julie A.; Phillips, D. Allen

2004-01-01

The purpose of this study was to investigate selected student and teacher variables and compare the differences between these variables for female students and female teachers in coeducation and single-sex physical education classes. Eighteen female teachers and intact classes were selected; 9 teachers from coeducation and 9 teachers from…

Petroleomics by electrospray ionization FT-ICR mass spectrometry coupled to partial least squares with variable selection methods: prediction of the total acid number of crude oils.

PubMed

Terra, Luciana A; Filgueiras, Paulo R; Tose, Lílian V; Romão, Wanderson; de Souza, Douglas D; de Castro, Eustáquio V R; de Oliveira, Mirela S L; Dias, Júlio C M; Poppi, Ronei J

2014-10-07

Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.

A Selective Overview of Variable Selection in High Dimensional Feature Space

PubMed Central

Fan, Jianqing

2010-01-01

High dimensional statistical problems arise from diverse fields of scientific research and technological development. Variable selection plays a pivotal role in contemporary statistical learning and scientific discoveries. The traditional idea of best subset selection methods, which can be regarded as a specific form of penalized likelihood, is computationally too expensive for many modern statistical applications. Other forms of penalized likelihood methods have been successfully developed over the last decade to cope with high dimensionality. They have been widely applied for simultaneously selecting important variables and estimating their effects in high dimensional statistical inference. In this article, we present a brief account of the recent developments of theory, methods, and implementations for high dimensional variable selection. What limits of the dimensionality such methods can handle, what the role of penalty functions is, and what the statistical properties are rapidly drive the advances of the field. The properties of non-concave penalized likelihood and its roles in high dimensional statistical modeling are emphasized. We also review some recent advances in ultra-high dimensional variable selection, with emphasis on independence screening and two-scale methods. PMID:21572976

Perceived individual, social, and environmental factors for physical activity and walking.

PubMed

Granner, Michelle L; Sharpe, Patricia A; Hutto, Brent; Wilcox, Sara; Addy, Cheryl L

2007-07-01

Few studies have explored associations of individual, social, and environmental factors with physical activity and walking behavior. A random-digit-dial questionnaire, which included selected individual, social, and environmental variables, was administered to 2025 adults, age 18 y and older, in two adjacent counties in a southeastern state. Logistic regressions were conducted adjusting for age, race, sex, education, and employment. In multivariate models, somewhat different variables were associated with physical activity versus regular walking. Self-efficacy (OR = 19.19), having an exercise partner (OR = 1.47), recreation facilities (OR = 1.54), and safety of trails from crime (OR = 0.72) were associated with physical activity level; while self-efficacy (OR = 4.22), known walking routes (OR = 1.54), recreation facilities (OR = 1.57-1.59), and safety of trails from crime (OR = 0.69) were associated with regular walking behavior. Physical activity and walking behaviors were associated with similar variables in this study.

Gas engine heat pump cycle analysis. Volume 1: Model description and generic analysis

NASA Astrophysics Data System (ADS)

Fischer, R. D.

1986-10-01

The task has prepared performance and cost information to assist in evaluating the selection of high voltage alternating current components, values for component design variables, and system configurations and operating strategy. A steady-state computer model for performance simulation of engine-driven and electrically driven heat pumps was prepared and effectively used for parametric and seasonal performance analyses. Parametric analysis showed the effect of variables associated with design of recuperators, brine coils, domestic hot water heat exchanger, compressor size, engine efficiency, insulation on exhaust and brine piping. Seasonal performance data were prepared for residential and commercial units in six cities with system configurations closely related to existing or contemplated hardware of the five GRI engine contractors. Similar data were prepared for an advanced variable-speed electric unit for comparison purposes. The effect of domestic hot water production on operating costs was determined. Four fan-operating strategies and two brine loop configurations were explored.

Spatial vs. individual variability with inheritance in a stochastic Lotka-Volterra system

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Tauber, Uwe C.

2012-02-01

We investigate a stochastic spatial Lotka-Volterra predator-prey model with randomized interaction rates that are either affixed to the lattice sites and quenched, and / or specific to individuals in either population. In the latter situation, we include rate inheritance with mutations from the particles' progenitors. Thus we arrive at a simple model for competitive evolution with environmental variability and selection pressure. We employ Monte Carlo simulations in zero and two dimensions to study the time evolution of both species' densities and their interaction rate distributions. The predator and prey concentrations in the ensuing steady states depend crucially on the environmental variability, whereas the temporal evolution of the individualized rate distributions leads to largely neutral optimization. Contrary to, e.g., linear gene expression models, this system does not experience fixation at extreme values. An approximate description of the resulting data is achieved by means of an effective master equation approach for the interaction rate distribution.

Improvement of two-way continuous-variable quantum key distribution with virtual photon subtraction

NASA Astrophysics Data System (ADS)

Zhao, Yijia; Zhang, Yichen; Li, Zhengyu; Yu, Song; Guo, Hong

2017-08-01

We propose a method to improve the performance of two-way continuous-variable quantum key distribution protocol by virtual photon subtraction. The virtual photon subtraction implemented via non-Gaussian post-selection not only enhances the entanglement of two-mode squeezed vacuum state but also has advantages in simplifying physical operation and promoting efficiency. In two-way protocol, virtual photon subtraction could be applied on two sources independently. Numerical simulations show that the optimal performance of renovated two-way protocol is obtained with photon subtraction only used by Alice. The transmission distance and tolerable excess noise are improved by using the virtual photon subtraction with appropriate parameters. Moreover, the tolerable excess noise maintains a high value with the increase in distance so that the robustness of two-way continuous-variable quantum key distribution system is significantly improved, especially at long transmission distance.

Development of toughened epoxy polymers for high performance composite and ablative applications

NASA Technical Reports Server (NTRS)

Allen, V. R.

1982-01-01

A survey of current procedures for the assessment of state of cure in epoxy polymers and for the evaluation of polymer toughness as related to nature of the crosslinking agent was made to facilitate a cause-effect study of the chemical modification of epoxy polymers. Various conformations of sample morphology were examined to identify testing variables and to establish optimum conditions for the selected physical test methods. Dynamic viscoelasticity testing was examined in conjunction with chemical analyses to allow observation of the extent of the curing reaction with size of the crosslinking agent the primary variable. Specifically the aims of the project were twofold: (1) to consider the experimental variables associated with development of "extent of cure" analysis, and (2) to assess methodology of fracture energy determination and to prescribe a meaningful and reproducible procedure. The following is separated into two categories for ease of presentation.

A technique for pole-zero placement for dual-input control systems. [computer simulation of CH-47 helicopter longitudinal dynamics

NASA Technical Reports Server (NTRS)

Reid, G. F.

1976-01-01

A technique is presented for determining state variable feedback gains that will place both the poles and zeros of a selected transfer function of a dual-input control system at pre-determined locations in the s-plane. Leverrier's algorithm is used to determine the numerator and denominator coefficients of the closed-loop transfer function as functions of the feedback gains. The values of gain that match these coefficients to those of a pre-selected model are found by solving two systems of linear simultaneous equations. The algorithm has been used in a computer simulation of the CH-47 helicopter to control longitudinal dynamics.

Mitigating Insider Sabotage and Espionage: A Review of the United States Air Force’s Current Posture

DTIC Science & Technology

2009-03-01

published on ins ider threat, to include the variables that come into play and historical case studies. Existing insider threat models are discussed ...problem, including the initial development of a logical da ta mod el and a system dynamics model. This chapter also discusses the selection of the...Finally, Chapter V provides a summary of the research along with a discussion of its conclusions and impact. Recommendations for future research

Identification of spectral regions for the quantification of red wine tannins with fourier transform mid-infrared spectroscopy.

PubMed

Jensen, Jacob S; Egebo, Max; Meyer, Anne S

2008-05-28

Accomplishment of fast tannin measurements is receiving increased interest as tannins are important for the mouthfeel and color properties of red wines. Fourier transform mid-infrared spectroscopy allows fast measurement of different wine components, but quantification of tannins is difficult due to interferences from spectral responses of other wine components. Four different variable selection tools were investigated for the identification of the most important spectral regions which would allow quantification of tannins from the spectra using partial least-squares regression. The study included the development of a new variable selection tool, iterative backward elimination of changeable size intervals PLS. The spectral regions identified by the different variable selection methods were not identical, but all included two regions (1485-1425 and 1060-995 cm(-1)), which therefore were concluded to be particularly important for tannin quantification. The spectral regions identified from the variable selection methods were used to develop calibration models. All four variable selection methods identified regions that allowed an improved quantitative prediction of tannins (RMSEP = 69-79 mg of CE/L; r = 0.93-0.94) as compared to a calibration model developed using all variables (RMSEP = 115 mg of CE/L; r = 0.87). Only minor differences in the performance of the variable selection methods were observed.

A prospective cohort study to evaluate peridomestic infection as a determinant of dengue transmission: Protocol

PubMed Central

2012-01-01

Background Vector control programs, which have focused mainly on the patient house and peridomestic areas around dengue cases, have not produced the expected impact on transmission. This project will evaluate the assumption that the endemic/epidemic transmission of dengue begins around peridomestic vicinities of the primary cases. Its objective is to assess the relationship between symptomatic dengue case exposure and peridomestic infection incidence. Methods/Design A prospective cohort study will be conducted (in Tepalcingo and Axochiapan, in the state of Morelos, Mexico), using the state surveillance system for the detection of incident cases. Paired blood specimens will be collected from both the individuals who live with the incident cases and a sample of subjects residing within a 25-meter radius of such cases (exposed cohort), in order to measure dengue-specific antibodies. Other subjects will be selected from areas which have not presented any incident cases within 200 meters, during the two months preceding the sampling (non-exposed cohort). Symptomatic/asymptomatic incident infection will be considered as the dependent variable, exposure to confirmed dengue cases, as the principal variable, and the socio-demographic, environmental and socio-cultural conditions of the subjects, as additional explanatory variables. Discussion Results indicating a high infection rate among the exposed subjects would justify the application of peridomestic control measures and call for an evaluation of alternate causes for insufficient program impact. On the other hand, a low incidence of peridomestic-infected subjects would support the hypothesis that infection occurs outside the domicile, and would thus explain why the vector control measures applied in the past have exerted such a limited impact on cases incidence rates. The results of the present study may therefore serve to reassess site selection for interventions of this type. PMID:22471857

Techniques for estimating flood-peak discharges from urban basins in Missouri

USGS Publications Warehouse

Becker, L.D.

1986-01-01

Techniques are defined for estimating the magnitude and frequency of future flood peak discharges of rainfall-induced runoff from small urban basins in Missouri. These techniques were developed from an initial analysis of flood records of 96 gaged sites in Missouri and adjacent states. Final regression equations are based on a balanced, representative sampling of 37 gaged sites in Missouri. This sample included 9 statewide urban study sites, 18 urban sites in St. Louis County, and 10 predominantly rural sites statewide. Short-term records were extended on the basis of long-term climatic records and use of a rainfall-runoff model. Linear least-squares regression analyses were used with log-transformed variables to relate flood magnitudes of selected recurrence intervals (dependent variables) to selected drainage basin indexes (independent variables). For gaged urban study sites within the State, the flood peak estimates are from the frequency curves defined from the synthesized long-term discharge records. Flood frequency estimates are made for ungaged sites by using regression equations that require determination of the drainage basin size and either the percentage of impervious area or a basin development factor. Alternative sets of equations are given for the 2-, 5-, 10-, 25-, 50-, and 100-yr recurrence interval floods. The average standard errors of estimate range from about 33% for the 2-yr flood to 26% for the 100-yr flood. The techniques for estimation are applicable to flood flows that are not significantly affected by storage caused by manmade activities. Flood peak discharge estimating equations are considered applicable for sites on basins draining approximately 0.25 to 40 sq mi. (Author 's abstract)

Collective feature selection to identify crucial epistatic variants.

PubMed

Verma, Shefali S; Lucas, Anastasia; Zhang, Xinyuan; Veturi, Yogasudha; Dudek, Scott; Li, Binglan; Li, Ruowang; Urbanowicz, Ryan; Moore, Jason H; Kim, Dokyoon; Ritchie, Marylyn D

2018-01-01

Machine learning methods have gained popularity and practicality in identifying linear and non-linear effects of variants associated with complex disease/traits. Detection of epistatic interactions still remains a challenge due to the large number of features and relatively small sample size as input, thus leading to the so-called "short fat data" problem. The efficiency of machine learning methods can be increased by limiting the number of input features. Thus, it is very important to perform variable selection before searching for epistasis. Many methods have been evaluated and proposed to perform feature selection, but no single method works best in all scenarios. We demonstrate this by conducting two separate simulation analyses to evaluate the proposed collective feature selection approach. Through our simulation study we propose a collective feature selection approach to select features that are in the "union" of the best performing methods. We explored various parametric, non-parametric, and data mining approaches to perform feature selection. We choose our top performing methods to select the union of the resulting variables based on a user-defined percentage of variants selected from each method to take to downstream analysis. Our simulation analysis shows that non-parametric data mining approaches, such as MDR, may work best under one simulation criteria for the high effect size (penetrance) datasets, while non-parametric methods designed for feature selection, such as Ranger and Gradient boosting, work best under other simulation criteria. Thus, using a collective approach proves to be more beneficial for selecting variables with epistatic effects also in low effect size datasets and different genetic architectures. Following this, we applied our proposed collective feature selection approach to select the top 1% of variables to identify potential interacting variables associated with Body Mass Index (BMI) in ~ 44,000 samples obtained from Geisinger's MyCode Community Health Initiative (on behalf of DiscovEHR collaboration). In this study, we were able to show that selecting variables using a collective feature selection approach could help in selecting true positive epistatic variables more frequently than applying any single method for feature selection via simulation studies. We were able to demonstrate the effectiveness of collective feature selection along with a comparison of many methods in our simulation analysis. We also applied our method to identify non-linear networks associated with obesity.

No difference in variability of unique hue selections and binary hue selections.

PubMed

Bosten, J M; Lawrance-Owen, A J

2014-04-01

If unique hues have special status in phenomenological experience as perceptually pure, it seems reasonable to assume that they are represented more precisely by the visual system than are other colors. Following the method of Malkoc et al. (J. Opt. Soc. Am. A22, 2154 [2005]), we gathered unique and binary hue selections from 50 subjects. For these subjects we repeated the measurements in two separate sessions, allowing us to measure test-retest reliabilities (0.52≤ρ≤0.78; p≪0.01). We quantified the within-individual variability for selections of each hue. Adjusting for the differences in variability intrinsic to different regions of chromaticity space, we compared the within-individual variability for unique hues to that for binary hues. Surprisingly, we found that selections of unique hues did not show consistently lower variability than selections of binary hues. We repeated hue measurements in a single session for an independent sample of 58 subjects, using a different relative scaling of the cardinal axes of MacLeod-Boynton chromaticity space. Again, we found no consistent difference in adjusted within-individual variability for selections of unique and binary hues. Our finding does not depend on the particular scaling chosen for the Y axis of MacLeod-Boynton chromaticity space.

Using variable rate models to identify genes under selection in sequence pairs: their validity and limitations for EST sequences.

PubMed

Church, Sheri A; Livingstone, Kevin; Lai, Zhao; Kozik, Alexander; Knapp, Steven J; Michelmore, Richard W; Rieseberg, Loren H

2007-02-01

Using likelihood-based variable selection models, we determined if positive selection was acting on 523 EST sequence pairs from two lineages of sunflower and lettuce. Variable rate models are generally not used for comparisons of sequence pairs due to the limited information and the inaccuracy of estimates of specific substitution rates. However, previous studies have shown that the likelihood ratio test (LRT) is reliable for detecting positive selection, even with low numbers of sequences. These analyses identified 56 genes that show a signature of selection, of which 75% were not identified by simpler models that average selection across codons. Subsequent mapping studies in sunflower show four of five of the positively selected genes identified by these methods mapped to domestication QTLs. We discuss the validity and limitations of using variable rate models for comparisons of sequence pairs, as well as the limitations of using ESTs for identification of positively selected genes.

Variable screening via quantile partial correlation

PubMed Central

Ma, Shujie; Tsai, Chih-Ling

2016-01-01

In quantile linear regression with ultra-high dimensional data, we propose an algorithm for screening all candidate variables and subsequently selecting relevant predictors. Specifically, we first employ quantile partial correlation for screening, and then we apply the extended Bayesian information criterion (EBIC) for best subset selection. Our proposed method can successfully select predictors when the variables are highly correlated, and it can also identify variables that make a contribution to the conditional quantiles but are marginally uncorrelated or weakly correlated with the response. Theoretical results show that the proposed algorithm can yield the sure screening set. By controlling the false selection rate, model selection consistency can be achieved theoretically. In practice, we proposed using EBIC for best subset selection so that the resulting model is screening consistent. Simulation studies demonstrate that the proposed algorithm performs well, and an empirical example is presented. PMID:28943683

Selection of key ambient particulate variables for epidemiological studies - applying cluster and heatmap analyses as tools for data reduction.

PubMed

Gu, Jianwei; Pitz, Mike; Breitner, Susanne; Birmili, Wolfram; von Klot, Stephanie; Schneider, Alexandra; Soentgen, Jens; Reller, Armin; Peters, Annette; Cyrys, Josef

2012-10-01

The success of epidemiological studies depends on the use of appropriate exposure variables. The purpose of this study is to extract a relatively small selection of variables characterizing ambient particulate matter from a large measurement data set. The original data set comprised a total of 96 particulate matter variables that have been continuously measured since 2004 at an urban background aerosol monitoring site in the city of Augsburg, Germany. Many of the original variables were derived from measured particle size distribution (PSD) across the particle diameter range 3 nm to 10 μm, including size-segregated particle number concentration, particle length concentration, particle surface concentration and particle mass concentration. The data set was complemented by integral aerosol variables. These variables were measured by independent instruments, including black carbon, sulfate, particle active surface concentration and particle length concentration. It is obvious that such a large number of measured variables cannot be used in health effect analyses simultaneously. The aim of this study is a pre-screening and a selection of the key variables that will be used as input in forthcoming epidemiological studies. In this study, we present two methods of parameter selection and apply them to data from a two-year period from 2007 to 2008. We used the agglomerative hierarchical cluster method to find groups of similar variables. In total, we selected 15 key variables from 9 clusters which are recommended for epidemiological analyses. We also applied a two-dimensional visualization technique called "heatmap" analysis to the Spearman correlation matrix. 12 key variables were selected using this method. Moreover, the positive matrix factorization (PMF) method was applied to the PSD data to characterize the possible particle sources. Correlations between the variables and PMF factors were used to interpret the meaning of the cluster and the heatmap analyses. Copyright © 2012 Elsevier B.V. All rights reserved.

Modelling the flaring activity of the high-z, hard X-ray-selected blazar IGR J22517+2217: Flaring activity of IGR J22517+2217

DOE PAGES

Lanzuisi, G.; De Rosa, A.; Ghisellini, G.; ...

2012-03-21

We present new Suzaku and Fermi data and re-analysed archival hard X-ray data from the INTErnational Gamma-Ray Astrophysics Laboratory (INTEGRAL) and Swift–Burst Alert Telescope (BAT) surveys to investigate the physical properties of the luminous, high-redshift, hard X-ray-selected blazar IGR J22517+2217, through the modelling of its broad-band spectral energy distribution (SED) in two different activity states. Through analysis of new Suzaku data and flux-selected data from archival hard X-ray observations, we build the source SED in two different states, one for the newly discovered flare that occurred in 2005 and one for the following quiescent period. Both SEDs are strongly dominatedmore » by the high-energy hump peaked at 10 20–10 22 Hz, which is at least two orders of magnitude higher than the low-energy (synchrotron) one at 10 11–10 14 Hz and varies by a factor of 10 between the two states. In both states the high-energy hump is modelled as inverse Compton emission between relativistic electrons and seed photons produced externally to the jet, while the synchrotron self-Compton component is found to be negligible. In our model the observed variability can be accounted for by a variation of the total number of emitting electrons and by a dissipation region radius changing from inside to outside the broad-line region as the luminosity increases. In its flaring activity, IGR J22517+2217 is revealed as one of the most powerful jets among the population of extreme, hard X-ray-selected, high-redshift blazars observed so far.« less

Bayesian Group Bridge for Bi-level Variable Selection.

PubMed

Mallick, Himel; Yi, Nengjun

2017-06-01

A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.

Usage of machine learning for the separation of electroweak and strong Zγ production at the LHC experiments

NASA Astrophysics Data System (ADS)

Petukhov, A. M.; Soldatov, E. Yu

2017-12-01

Separation of electroweak component from strong component of associated Zγ production on hadron colliders is a very challenging task due to identical final states of such processes. The only difference is the origin of two leading jets in these two processes. Rectangular cuts on jet kinematic variables from ATLAS/CMS 8 TeV Zγ experimental analyses were improved using machine learning techniques. New selection variables were also tested. The expected significance of separation for LHC experiments conditions at the second datataking period (Run2) and 120 fb-1 amount of data reaches more than 5σ. Future experimental observation of electroweak Zγ production can also lead to the observation physics beyond Standard Model.

Encke-Beta Predictor for Orion Burn Targeting and Guidance

NASA Technical Reports Server (NTRS)

Robinson, Shane; Scarritt, Sara; Goodman, John L.

2016-01-01

The state vector prediction algorithm selected for Orion on-board targeting and guidance is known as the Encke-Beta method. Encke-Beta uses a universal anomaly (beta) as the independent variable, valid for circular, elliptical, parabolic, and hyperbolic orbits. The variable, related to the change in eccentric anomaly, results in integration steps that cover smaller arcs of the trajectory at or near perigee, when velocity is higher. Some burns in the EM-1 and EM-2 mission plans are much longer than burns executed with the Apollo and Space Shuttle vehicles. Burn length, as well as hyperbolic trajectories, has driven the use of the Encke-Beta numerical predictor by the predictor/corrector guidance algorithm in place of legacy analytic thrust and gravity integrals.

Environmental variability and acoustic signals: a multi-level approach in songbirds.

PubMed

Medina, Iliana; Francis, Clinton D

2012-12-23

Among songbirds, growing evidence suggests that acoustic adaptation of song traits occurs in response to habitat features. Despite extensive study, most research supporting acoustic adaptation has only considered acoustic traits averaged for species or populations, overlooking intraindividual variation of song traits, which may facilitate effective communication in heterogeneous and variable environments. Fewer studies have explicitly incorporated sexual selection, which, if strong, may favour variation across environments. Here, we evaluate the prevalence of acoustic adaptation among 44 species of songbirds by determining how environmental variability and sexual selection intensity are associated with song variability (intraindividual and intraspecific) and short-term song complexity. We show that variability in precipitation can explain short-term song complexity among taxonomically diverse songbirds, and that precipitation seasonality and the intensity of sexual selection are related to intraindividual song variation. Our results link song complexity to environmental variability, something previously found for mockingbirds (Family Mimidae). Perhaps more importantly, our results illustrate that individual variation in song traits may be shaped by both environmental variability and strength of sexual selection.

A novel framework to simulating non-stationary, non-linear, non-Normal hydrological time series using Markov Switching Autoregressive Models

NASA Astrophysics Data System (ADS)

Birkel, C.; Paroli, R.; Spezia, L.; Tetzlaff, D.; Soulsby, C.

2012-12-01

In this paper we present a novel model framework using the class of Markov Switching Autoregressive Models (MSARMs) to examine catchments as complex stochastic systems that exhibit non-stationary, non-linear and non-Normal rainfall-runoff and solute dynamics. Hereby, MSARMs are pairs of stochastic processes, one observed and one unobserved, or hidden. We model the unobserved process as a finite state Markov chain and assume that the observed process, given the hidden Markov chain, is conditionally autoregressive, which means that the current observation depends on its recent past (system memory). The model is fully embedded in a Bayesian analysis based on Markov Chain Monte Carlo (MCMC) algorithms for model selection and uncertainty assessment. Hereby, the autoregressive order and the dimension of the hidden Markov chain state-space are essentially self-selected. The hidden states of the Markov chain represent unobserved levels of variability in the observed process that may result from complex interactions of hydroclimatic variability on the one hand and catchment characteristics affecting water and solute storage on the other. To deal with non-stationarity, additional meteorological and hydrological time series along with a periodic component can be included in the MSARMs as covariates. This extension allows identification of potential underlying drivers of temporal rainfall-runoff and solute dynamics. We applied the MSAR model framework to streamflow and conservative tracer (deuterium and oxygen-18) time series from an intensively monitored 2.3 km2 experimental catchment in eastern Scotland. Statistical time series analysis, in the form of MSARMs, suggested that the streamflow and isotope tracer time series are not controlled by simple linear rules. MSARMs showed that the dependence of current observations on past inputs observed by transport models often in form of the long-tailing of travel time and residence time distributions can be efficiently explained by non-stationarity either of the system input (climatic variability) and/or the complexity of catchment storage characteristics. The statistical model is also capable of reproducing short (event) and longer-term (inter-event) and wet and dry dynamical "hydrological states". These reflect the non-linear transport mechanisms of flow pathways induced by transient climatic and hydrological variables and modified by catchment characteristics. We conclude that MSARMs are a powerful tool to analyze the temporal dynamics of hydrological data, allowing for explicit integration of non-stationary, non-linear and non-Normal characteristics.

The XMM deep survey in the CDF-S. X. X-ray variability of bright sources

NASA Astrophysics Data System (ADS)

Falocco, S.; Paolillo, M.; Comastri, A.; Carrera, F. J.; Ranalli, P.; Iwasawa, K.; Georgantopoulos, I.; Vignali, C.; Gilli, R.

2017-12-01

Aims: We aim to study the variability properties of bright hard X-ray selected active galactic nuclei (AGN) in the redshift range between 0.3 and 1.6 detected in the Chandra Deep Field South (XMM-CDFS) by a long ( 3 Ms) XMM observation. Methods: Taking advantage of the good count statistics in the XMM CDFS, we search for flux and spectral variability using the hardness ratio (HR) techniques. We also investigate the spectral variability of different spectral components (photon index of the power law, column density of the local absorber, and reflection intensity). The spectra were merged in six epochs (defined as adjacent observations) and in high and low flux states to understand whether the flux transitions are accompanied by spectral changes. Results: The flux variability is significant in all the sources investigated. The HRs in general are not as variable as the fluxes, in line with previous results on deep fields. Only one source displays a variable HR, anti-correlated with the flux (source 337). The spectral analysis in the available epochs confirms the steeper when brighter trend consistent with Comptonisation models only in this source at 99% confidence level. Finding this trend in one out of seven unabsorbed sources is consistent, within the statistical limits, with the 15% of unabsorbed AGN in previous deep surveys. No significant variability in the column densities, nor in the Compton reflection component, has been detected across the epochs considered. The high and low states display in general different normalisations but consistent spectral properties. Conclusions: X-ray flux fluctuations are ubiquitous in AGN, though in some cases the data quality does not allow for their detection. In general, the significant flux variations are not associated with spectral variability: photon index and column densities are not significantly variable in nine out of the ten AGN over long timescales (from three to six and a half years). Photon index variability is found only in one source (which is steeper when brighter) out of seven unabsorbed AGN. The percentage of spectrally variable objects is consistent, within the limited statistics of sources studied here, with previous deep samples.

Automatic classifier based on heart rate variability to identify fallers among hypertensive subjects.

PubMed

Melillo, Paolo; Jovic, Alan; De Luca, Nicola; Pecchia, Leandro

2015-08-01

Accidental falls are a major problem of later life. Different technologies to predict falls have been investigated, but with limited success, mainly because of low specificity due to a high false positive rate. This Letter presents an automatic classifier based on heart rate variability (HRV) analysis with the goal to identify fallers automatically. HRV was used in this study as it is considered a good estimator of autonomic nervous system (ANS) states, which are responsible, among other things, for human balance control. Nominal 24 h electrocardiogram recordings from 168 cardiac patients (age 72 ± 8 years, 60 female), of which 47 were fallers, were investigated. Linear and nonlinear HRV properties were analysed in 30 min excerpts. Different data mining approaches were adopted and their performances were compared with a subject-based receiver operating characteristic analysis. The best performance was achieved by a hybrid algorithm, RUSBoost, integrated with feature selection method based on principal component analysis, which achieved satisfactory specificity and accuracy (80 and 72%, respectively), but low sensitivity (51%). These results suggested that ANS states causing falls could be reliably detected, but also that not all the falls were due to ANS states.

State-Space Estimation of Soil Organic Carbon Stock

NASA Astrophysics Data System (ADS)

Ogunwole, Joshua O.; Timm, Luis C.; Obidike-Ugwu, Evelyn O.; Gabriels, Donald M.

2014-04-01

Understanding soil spatial variability and identifying soil parameters most determinant to soil organic carbon stock is pivotal to precision in ecological modelling, prediction, estimation and management of soil within a landscape. This study investigates and describes field soil variability and its structural pattern for agricultural management decisions. The main aim was to relate variation in soil organic carbon stock to soil properties and to estimate soil organic carbon stock from the soil properties. A transect sampling of 100 points at 3 m intervals was carried out. Soils were sampled and analyzed for soil organic carbon and other selected soil properties along with determination of dry aggregate and water-stable aggregate fractions. Principal component analysis, geostatistics, and state-space analysis were conducted on the analyzed soil properties. The first three principal components explained 53.2% of the total variation; Principal Component 1 was dominated by soil exchange complex and dry sieved macroaggregates clusters. Exponential semivariogram model described the structure of soil organic carbon stock with a strong dependence indicating that soil organic carbon values were correlated up to 10.8m.Neighbouring values of soil organic carbon stock, all waterstable aggregate fractions, and dithionite and pyrophosphate iron gave reliable estimate of soil organic carbon stock by state-space.

Fecundity selection on ornamental plumage colour differs between ages and sexes and varies over small spatial scales.

PubMed

Parker, T H; Wilkin, T A; Barr, I R; Sheldon, B C; Rowe, L; Griffith, S C

2011-07-01

Avian plumage colours are some of the most conspicuous sexual ornaments, and yet standardized selection gradients for plumage colour have rarely been quantified. We examined patterns of fecundity selection on plumage colour in blue tits (Cyanistes caeruleus L.). When not accounting for environmental heterogeneity, we detected relatively few cases of selection. We found significant disruptive selection on adult male crown colour and yearling female chest colour and marginally nonsignificant positive linear selection on adult female crown colour. We discovered no new significant selection gradients with canonical rotation of the matrix of nonlinear selection. Next, using a long-term data set, we identified territory-level environmental variables that predicted fecundity to determine whether these variables influenced patterns of plumage selection. The first of these variables, the density of oaks within 50 m of the nest, influenced selection gradients only for yearling males. The second variable, an inverse function of nesting density, interacted with a subset of plumage selection gradients for yearling males and adult females, although the strength and direction of selection did not vary predictably with population density across these analyses. Overall, fecundity selection on plumage colour in blue tits appeared rare and inconsistent among sexes and age classes. © 2011 The Authors. Journal of Evolutionary Biology © 2011 European Society For Evolutionary Biology.

Application of Spaceborne Scatterometer for Mapping Freeze-Thaw State in Northern Landscapes as a Measure of Ecological and Hydrological Processes

NASA Technical Reports Server (NTRS)

McDonald, Kyle; Kimball, John; Zimmermann, Reiner; Way, JoBea; Frolking, Steve; Running, Steve

1999-01-01

Landscape freeze/thaw transitions coincide with marked shifts in albedo, surface energy and mass exchange, and associated snow dynamics. Monitoring landscape freeze/thaw dynamics would improve our ability to quantify the interannual variability of boreal hydrology and river runoff/flood dynamics. The annual duration of frost-free period also bounds the period of photosynthetic activity in boreal and arctic regions thus affecting the annual carbon budget and the interannual variability of regional carbon fluxes. In this study, we use the NASA scatterometer (NSCAT) to monitor the temporal change in the radar backscatter signature across selected ecoregions of the boreal zone. We have measured vegetation tissue temperatures, soil temperature profiles, and micrometeorological parameters in situ at selected sites along a north-south transect extending across Alaska from Prudhoe Bay to the Kenai Peninsula and in Siberia near the Yenisey River. Data from these stations have been used to quantify the scatterometer's sensitivity to freeze/thaw state under a variety of terrain and landcover conditions. Analysis of the NSCAT temporal response over the 1997 spring thaw cycle shows a 3 to 5 dB change in measured backscatter that is well correlated with the landscape springtime thaw process. Having verified the instrument's capability to monitor freeze/thaw transitions, regional scale mosaicked data are applied to derive temporal series of freeze/thaw transition maps for selected circumpolar high latitude regions. These maps are applied to derive areal extent of frozen and thawed landscape and demonstrate the utility of spaceborne radar for operational monitoring of seasonal freeze-thaw dynamics and associated biophysical processes for the circumpolar high latitudes.

Region-to-area screening methodology for the Crystalline Repository Project

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

None

1985-04-01

The purpose of this document is to describe the Crystalline Repository Project's (CRP) process for region-to-area screening of exposed and near-surface crystalline rock bodies in the three regions of the conterminous United States where crystalline rock is being evaluated as a potential host for the second nuclear waste repository (i.e., in the North Central, Northeastern, and Southeastern Regions). This document indicates how the US Department of Energy's (DOE) General Guidelines for the Recommendation of Sites for Nuclear Waste Repositories (10 CFR 960) were used to select and apply factors and variables for the region-to-area screening, explains how these factors andmore » variable are to be applied in the region-to-area screening, and indicates how this methodology relates to the decision process leading to the selection of candidate areas. A brief general discussion of the screening process from the national survey through area screening and site recommendation is presented. This discussion sets the scene for detailed discussions which follow concerning the region-to-area screening process, the guidance provided by the DOE Siting Guidelines for establishing disqualifying factors and variables for screening, and application of the disqualifying factors and variables in the screening process. This document is complementary to the regional geologic and environmental characterization reports to be issued in the summer of 1985 as final documents. These reports will contain the geologic and environmental data base that will be used in conjunction with the methodology to conduct region-to-area screening.« less

Effects of Music Interventions on Emotional States and Running Performance

PubMed Central

Lane, Andrew M.; Davis, Paul A.; Devonport, Tracey J.

2011-01-01

The present study compared the effects of two different music interventions on changes in emotional states before and during running, and also explored effects of music interventions upon performance outcome. Volunteer participants (n = 65) who regularly listened to music when running registered online to participate in a three-stage study. Participants attempted to attain a personally important running goal to establish baseline performance. Thereafter, participants were randomly assigned to either a self-selected music group or an Audiofuel music group. Audiofuel produce pieces of music designed to assist synchronous running. The self-selected music group followed guidelines for selecting motivating playlists. In both experimental groups, participants used the Brunel Music Rating Inventory-2 (BMRI-2) to facilitate selection of motivational music. Participants again completed the BMRI-2 post- intervention to assess the motivational qualities of Audiofuel music or the music they selected for use during the study. Results revealed no significant differences between self-selected music and Audiofuel music on all variables analyzed. Participants in both music groups reported increased pleasant emotions and decreased unpleasant emotions following intervention. Significant performance improvements were demonstrated post-intervention with participants reporting a belief that emotional states related to performance. Further analysis indicated that enhanced performance was significantly greater among participants reporting music to be motivational as indicated by high scores on the BMRI-2. Findings suggest that both individual athletes and practitioners should consider using the BMRI-2 when selecting music for running. Key points Listening to music with a high motivational quotient as indicated by scores on the BMRI-2 was associated with enhanced running performance and meta-emotional beliefs that emotions experienced during running helped performance. Beliefs on the effectiveness of music intended to alter emotions were associated with high scores on the BMRI-2. Runners seeking to use music as an emotion regulating strategy should consider using the BMRI-2 as an effective means by which to identify potentially motivating tracks. PMID:24149889

Data driven model generation based on computational intelligence

NASA Astrophysics Data System (ADS)

Gemmar, Peter; Gronz, Oliver; Faust, Christophe; Casper, Markus

2010-05-01

The simulation of discharges at a local gauge or the modeling of large scale river catchments are effectively involved in estimation and decision tasks of hydrological research and practical applications like flood prediction or water resource management. However, modeling such processes using analytical or conceptual approaches is made difficult by both complexity of process relations and heterogeneity of processes. It was shown manifold that unknown or assumed process relations can principally be described by computational methods, and that system models can automatically be derived from observed behavior or measured process data. This study describes the development of hydrological process models using computational methods including Fuzzy logic and artificial neural networks (ANN) in a comprehensive and automated manner. Methods We consider a closed concept for data driven development of hydrological models based on measured (experimental) data. The concept is centered on a Fuzzy system using rules of Takagi-Sugeno-Kang type which formulate the input-output relation in a generic structure like Ri : IFq(t) = lowAND...THENq(t+Δt) = ai0 +ai1q(t)+ai2p(t-Δti1)+ai3p(t+Δti2)+.... The rule's premise part (IF) describes process states involving available process information, e.g. actual outlet q(t) is low where low is one of several Fuzzy sets defined over variable q(t). The rule's conclusion (THEN) estimates expected outlet q(t + Δt) by a linear function over selected system variables, e.g. actual outlet q(t), previous and/or forecasted precipitation p(t ?Δtik). In case of river catchment modeling we use head gauges, tributary and upriver gauges in the conclusion part as well. In addition, we consider temperature and temporal (season) information in the premise part. By creating a set of rules R = {Ri|(i = 1,...,N)} the space of process states can be covered as concise as necessary. Model adaptation is achieved by finding on optimal set A = (aij) of conclusion parameters with respect to a defined rating function and experimental data. To find A, we use for example a linear equation solver and RMSE-function. In practical process models, the number of Fuzzy sets and the according number of rules is fairly low. Nevertheless, creating the optimal model requires some experience. Therefore, we improved this development step by methods for automatic generation of Fuzzy sets, rules, and conclusions. Basically, the model achievement depends to a great extend on the selection of the conclusion variables. It is the aim that variables having most influence on the system reaction being considered and superfluous ones being neglected. At first, we use Kohonen maps, a specialized ANN, to identify relevant input variables from the large set of available system variables. A greedy algorithm selects a comprehensive set of dominant and uncorrelated variables. Next, the premise variables are analyzed with clustering methods (e.g. Fuzzy-C-means) and Fuzzy sets are then derived from cluster centers and outlines. The rule base is automatically constructed by permutation of the Fuzzy sets of the premise variables. Finally, the conclusion parameters are calculated and the total coverage of the input space is iteratively tested with experimental data, rarely firing rules are combined and coarse coverage of sensitive process states results in refined Fuzzy sets and rules. Results The described methods were implemented and integrated in a development system for process models. A series of models has already been built e.g. for rainfall-runoff modeling or for flood prediction (up to 72 hours) in river catchments. The models required significantly less development effort and showed advanced simulation results compared to conventional models. The models can be used operationally and simulation takes only some minutes on a standard PC e.g. for a gauge forecast (up to 72 hours) for the whole Mosel (Germany) river catchment.

The joy of heartfelt music: An examination of emotional and physiological responses.

PubMed

Lynar, Emily; Cvejic, Erin; Schubert, Emery; Vollmer-Conna, Ute

2017-10-01

Music-listening can be a powerful therapeutic tool for mood rehabilitation, yet quality evidence for its validity as a singular treatment is scarce. Specifically, the relationship between music-induced mood improvement and meaningful physiological change, as well as the influence of music- and person-related covariates on these outcomes are yet to be comprehensively explored. Ninety-four healthy participants completed questionnaires probing demographics, personal information, and musical background. Participants listened to two prescribed musical pieces (one classical, one jazz), an "uplifting" piece of their own choice, and an acoustic control stimulus (white noise) in randomised order. Physiological responses (heart rate, respiration, galvanic skin response) were recorded throughout. After each piece, participants rated their subjective responses on a series of Likert scales. Subjectively, the self-selected pieces induced the most joy, and the classical piece was perceived as most relaxing, consistent with the arousal ratings proposed by a music selection panel. These two stimuli led to the greatest overall improvement in composite emotional state from baseline. Psycho-physiologically, self-selected pieces often elicited a "eustress" response ("positive arousal"), whereas classical music was associated with the highest heart rate variability. Very few person-related covariates appeared to affect responses, and music-related covariates (besides self-selection) appeared arbitrary. These data provide strong evidence that optimal music for therapy varies between individuals. Our findings additionally suggest that the self-selected music was most effective for inducing a joyous state; while low arousal classical music was most likely to shift the participant into a state of relaxation. Therapy should attempt to find the most effective and "heartfelt" music for each listener, according to therapeutic goals. Copyright © 2017 Elsevier B.V. All rights reserved.

How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

NASA Astrophysics Data System (ADS)

Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

2013-02-01

SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.

A parametric study of motor starting for a 2- to 10-kilowatt Brayton power system

NASA Technical Reports Server (NTRS)

Cantoni, D. A.

1971-01-01

A study of the motor starting of a Brayton cycle power system was conducted to provide estimates of system sensitivity to several controllable parameters. These sensitivity estimates were used as a basis for selection of an optimum motor-start scheme to be implemented on the 2- to 10-kilowatt Brayton power system designed and presently under test. The studies were conducted with an analog simulation of the Brayton power system and covered a range of frequencies from 400 Hz (33 percent design) to 1200 Hz (design), voltage-to-frequency ratios of 0.050 (50 percent design) to 0.100 (design), turbine-inlet temperatures of 800 K (1440 R, 70 percent design) to 1140 K (2060 deg R, design), and prestart pressure levels of 14.5 psia to 29.0 psia. These studies have shown the effect of selected system variables on motor starting. The final selection of motor-start variables can therefore be made on the basis of motor-start inverter complexity, battery size and weight, desired steady-state pressure level after startup, and other operational limitations. In general, the study showed the time required for motor starting to be inversely proportional to motor frequency, voltage, turbine-inlet temperature, and pressure level. An increase in any of these parameters decreases startup time.

Aeroservoelastic modeling and applications using minimum-state approximations of the unsteady aerodynamics

NASA Technical Reports Server (NTRS)

Tiffany, Sherwood H.; Karpel, Mordechay

1989-01-01

Various control analysis, design, and simulation techniques for aeroelastic applications require the equations of motion to be cast in a linear time-invariant state-space form. Unsteady aerodynamics forces have to be approximated as rational functions of the Laplace variable in order to put them in this framework. For the minimum-state method, the number of denominator roots in the rational approximation. Results are shown of applying various approximation enhancements (including optimization, frequency dependent weighting of the tabular data, and constraint selection) with the minimum-state formulation to the active flexible wing wind-tunnel model. The results demonstrate that good models can be developed which have an order of magnitude fewer augmenting aerodynamic equations more than traditional approaches. This reduction facilitates the design of lower order control systems, analysis of control system performance, and near real-time simulation of aeroservoelastic phenomena.

Extending Quantum Chemistry of Bound States to Electronic Resonances

NASA Astrophysics Data System (ADS)

Jagau, Thomas-C.; Bravaya, Ksenia B.; Krylov, Anna I.

2017-05-01

Electronic resonances are metastable states with finite lifetime embedded in the ionization or detachment continuum. They are ubiquitous in chemistry, physics, and biology. Resonances play a central role in processes as diverse as DNA radiolysis, plasmonic catalysis, and attosecond spectroscopy. This review describes novel equation-of-motion coupled-cluster (EOM-CC) methods designed to treat resonances and bound states on an equal footing. Built on complex-variable techniques such as complex scaling and complex absorbing potentials that allow resonances to be associated with a single eigenstate of the molecular Hamiltonian rather than several continuum eigenstates, these methods extend electronic-structure tools developed for bound states to electronic resonances. Selected examples emphasize the formal advantages as well as the numerical accuracy of EOM-CC in the treatment of electronic resonances. Connections to experimental observables such as spectra and cross sections, as well as practical aspects of implementing complex-valued approaches, are also discussed.

U.S. utilities' experiences with the implementation of energy efficiency programs

NASA Astrophysics Data System (ADS)

Goss, Courtney

In the U.S., many electric utility companies are offering demand-side management (DSM) programs to their customers as ways to save money and energy. However, it is challenging to compare these programs between utility companies throughout the U.S. because of the variability of state energy policies. For example, some states in the U.S. have deregulated electricity markets and others do not. In addition, utility companies within a state differ depending on ownership and size. This study examines 12 utilities' experiences with DSM programs and compares the programs' annual energy savings results that the selected utilities reported to the Energy Information Administration (EIA). The 2009 EIA data suggests that DSM program effectiveness is not significantly affected by electricity market deregulation or utility ownership. However, DSM programs seem to generally be more effective when administered by utilities located in states with energy savings requirements and DSM program mandates.

Fitness variables and the lipid profile in United States astronauts

NASA Technical Reports Server (NTRS)

Berry, M. A.; Squires, W. G.; Jackson, A. S.

1980-01-01

The study examines the relationship between several measures of fitness and the lipid profile in United States astronauts. Data were collected on 89 astronauts, previously selected (PSA) and newly selected (NSA), during their annual physical examinations. Several similarities were seen in the two groups. The PSA (mean age of 46.1) had a lower maximum oxygen capacity (41.7 ml kg/min vs. 47.5 ml kg/min); when adjusted for age, it was no different from the NSA (mean age 33.5). The PSA had similar body composition with 15.7% - lower than expected for age. The lipid profiles of the two groups were basically the same with the differences being a function of age. Compared to a normative population, the astronauts had similar cholesterols, lower triglycerides, and higher HDLs. The astronaut profiles were generally more favorable than the age-matched controls, which is felt to be a result of the self-supervised conditioning program and annual preventive medicine consultation and education.

Variable Selection for Nonparametric Quantile Regression via Smoothing Spline AN OVA

PubMed Central

Lin, Chen-Yen; Bondell, Howard; Zhang, Hao Helen; Zou, Hui

2014-01-01

Quantile regression provides a more thorough view of the effect of covariates on a response. Nonparametric quantile regression has become a viable alternative to avoid restrictive parametric assumption. The problem of variable selection for quantile regression is challenging, since important variables can influence various quantiles in different ways. We tackle the problem via regularization in the context of smoothing spline ANOVA models. The proposed sparse nonparametric quantile regression (SNQR) can identify important variables and provide flexible estimates for quantiles. Our numerical study suggests the promising performance of the new procedure in variable selection and function estimation. Supplementary materials for this article are available online. PMID:24554792

The Use of Electrophysiological and Cognitive Variables in the Assessment of Degradation During Periods of Sustained Wakefulness

DTIC Science & Technology

1992-12-01

spectral components. Spectral components were selected on the basis of their relation to states of alertness. In normal human adults , diffuse low...deterioration of handwriting , and ultimately, loss of consciousness. Belyavin and Wright (1987) reported that while EEG changes could not predict vigilance in...a function of alertness level. In human adults , two independent laboratories have shown that MLR components Pa (30 to 35 ms) and Nb (40 to 50 ms

Regional flood-frequency relations for streams with many years of no flow

USGS Publications Warehouse

Hjalmarson, Hjalmar W.; Thomas, Blakemore E.; ,

1990-01-01

In the southwestern United States, flood-frequency relations for streams that drain small arid basins are difficult to estimate, largely because of the extreme temporal and spatial variability of floods and the many years of no flow. A method is proposed that is based on the station-year method. The new method produces regional flood-frequency relations using all available annual peak-discharge data. The prediction errors for the relations are directly assessed using randomly selected subsamples of the annual peak discharges.

Locating CVBEM collocation points for steady state heat transfer problems

USGS Publications Warehouse

Hromadka, T.V.

1985-01-01

The Complex Variable Boundary Element Method or CVBEM provides a highly accurate means of developing numerical solutions to steady state two-dimensional heat transfer problems. The numerical approach exactly solves the Laplace equation and satisfies the boundary conditions at specified points on the boundary by means of collocation. The accuracy of the approximation depends upon the nodal point distribution specified by the numerical analyst. In order to develop subsequent, refined approximation functions, four techniques for selecting additional collocation points are presented. The techniques are compared as to the governing theory, representation of the error of approximation on the problem boundary, the computational costs, and the ease of use by the numerical analyst. ?? 1985.

User's manual for interactive LINEAR: A FORTRAN program to derive linear aircraft models

NASA Technical Reports Server (NTRS)

Antoniewicz, Robert F.; Duke, Eugene L.; Patterson, Brian P.

1988-01-01

An interactive FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models is documented in this report. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.

Face-Likeness and Image Variability Drive Responses in Human Face-Selective Ventral Regions

PubMed Central

Davidenko, Nicolas; Remus, David A.; Grill-Spector, Kalanit

2012-01-01

The human ventral visual stream contains regions that respond selectively to faces over objects. However, it is unknown whether responses in these regions correlate with how face-like stimuli appear. Here, we use parameterized face silhouettes to manipulate the perceived face-likeness of stimuli and measure responses in face- and object-selective ventral regions with high-resolution fMRI. We first use “concentric hyper-sphere” (CH) sampling to define face silhouettes at different distances from the prototype face. Observers rate the stimuli as progressively more face-like the closer they are to the prototype face. Paradoxically, responses in both face- and object-selective regions decrease as face-likeness ratings increase. Because CH sampling produces blocks of stimuli whose variability is negatively correlated with face-likeness, this effect may be driven by more adaptation during high face-likeness (low-variability) blocks than during low face-likeness (high-variability) blocks. We tested this hypothesis by measuring responses to matched-variability (MV) blocks of stimuli with similar face-likeness ratings as with CH sampling. Critically, under MV sampling, we find a face-specific effect: responses in face-selective regions gradually increase with perceived face-likeness, but responses in object-selective regions are unchanged. Our studies provide novel evidence that face-selective responses correlate with the perceived face-likeness of stimuli, but this effect is revealed only when image variability is controlled across conditions. Finally, our data show that variability is a powerful factor that drives responses across the ventral stream. This indicates that controlling variability across conditions should be a critical tool in future neuroimaging studies of face and object representation. PMID:21823208

[Research on fast detecting tomato seedlings nitrogen content based on NIR characteristic spectrum selection].

PubMed

Wu, Jing-zhu; Wang, Feng-zhu; Wang, Li-li; Zhang, Xiao-chao; Mao, Wen-hua

2015-01-01

In order to improve the accuracy and robustness of detecting tomato seedlings nitrogen content based on near-infrared spectroscopy (NIR), 4 kinds of characteristic spectrum selecting methods were studied in the present paper, i. e. competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variables elimination (MCUVE), backward interval partial least squares (BiPLS) and synergy interval partial least squares (SiPLS). There were totally 60 tomato seedlings cultivated at 10 different nitrogen-treatment levels (urea concentration from 0 to 120 mg . L-1), with 6 samples at each nitrogen-treatment level. They are in different degrees of over nitrogen, moderate nitrogen, lack of nitrogen and no nitrogen status. Each sample leaves were collected to scan near-infrared spectroscopy from 12 500 to 3 600 cm-1. The quantitative models based on the above 4 methods were established. According to the experimental result, the calibration model based on CARS and MCUVE selecting methods show better performance than those based on BiPLS and SiPLS selecting methods, but their prediction ability is much lower than that of the latter. Among them, the model built by BiPLS has the best prediction performance. The correlation coefficient (r), root mean square error of prediction (RMSEP) and ratio of performance to standard derivate (RPD) is 0. 952 7, 0. 118 3 and 3. 291, respectively. Therefore, NIR technology combined with characteristic spectrum selecting methods can improve the model performance. But the characteristic spectrum selecting methods are not universal. For the built model based or single wavelength variables selection is more sensitive, it is more suitable for the uniform object. While the anti-interference ability of the model built based on wavelength interval selection is much stronger, it is more suitable for the uneven and poor reproducibility object. Therefore, the characteristic spectrum selection will only play a better role in building model, combined with the consideration of sample state and the model indexes.

Genetic gains in the UENF-14 popcorn population with recurrent selection.

PubMed

Freitas, I L J; do Amaral Júnior, A T; Freitas, S P; Cabral, P D S; Ribeiro, R M; Gonçalves, L S A

2014-01-21

The popcorn breeding program of Universidade Estadual do Norte Fluminense Darcy Ribeiro aims to provide farmers a cultivar with desirable agronomic traits, particularly with respect to grain yield (GY) and popping expansion (PE). We evaluated full-sib families from the seventh cycle of recurrent selection and estimated the genetic progress with respect to GY and PE. Eight traits were evaluated in 200 full-sib families that were randomized into blocks with two replicates per set in two contrasting environments, Campos dos Goytacazes and Itaocara, located in north and northwest Rio de Janeiro State, respectively. There were significant differences between sets in families with respect to all traits evaluated, which indicates genetic variability that may be explored in future cycles. Using random economic weights in the selection of superior progenies, the Mulamba and Mock index showed gains for PE and GY of 5.11 and 7.78%, respectively. Significant PE and GY increases were found when comparing the evolution of mean values of these two parameters that were assessed at cycles C₀-C₆ and predicted for C₇. Thus, an advanced-cycle popcorn cultivar with genotypic superiority for the main traits of economic interest can be made available to farmers in Rio de Janeiro State.

Selection criteria for internal medicine residency applicants and professionalism ratings during internship.

PubMed

Cullen, Michael W; Reed, Darcy A; Halvorsen, Andrew J; Wittich, Christopher M; Kreuziger, Lisa M Baumann; Keddis, Mira T; McDonald, Furman S; Beckman, Thomas J

2011-03-01

To determine whether standardized admissions data in residents' Electronic Residency Application Service (ERAS) submissions were associated with multisource assessments of professionalism during internship. ERAS applications for all internal medicine interns (N=191) at Mayo Clinic entering training between July 1, 2005, and July 1, 2008, were reviewed by 6 raters. Extracted data included United States Medical Licensing Examination scores, medicine clerkship grades, class rank, Alpha Omega Alpha membership, advanced degrees, awards, volunteer activities, research experiences, first author publications, career choice, and red flags in performance evaluations. Medical school reputation was quantified using U.S. News & World Report rankings. Strength of comparative statements in recommendation letters (0 = no comparative statement, 1 = equal to peers, 2 = top 20%, 3 = top 10% or "best") were also recorded. Validated multisource professionalism scores (5-point scales) were obtained for each intern. Associations between application variables and professionalism scores were examined using linear regression. The mean ± SD (minimum-maximum) professionalism score was 4.09 ± 0.31 (2.13-4.56). In multivariate analysis, professionalism scores were positively associated with mean strength of comparative statements in recommendation letters (β = 0.13; P = .002). No other associations between ERAS application variables and professionalism scores were found. Comparative statements in recommendation letters for internal medicine residency applicants were associated with professionalism scores during internship. Other variables traditionally examined when selecting residents were not associated with professionalism. These findings suggest that faculty physicians' direct observations, as reflected in letters of recommendation, are useful indicators of what constitutes a best student. Residency selection committees should scrutinize applicants' letters for strongly favorable comparative statements.

Locomotor-respiratory coupling patterns and oxygen consumption during walking above and below preferred stride frequency.

PubMed

O'Halloran, Joseph; Hamill, Joseph; McDermott, William J; Remelius, Jebb G; Van Emmerik, Richard E A

2012-03-01

Locomotor respiratory coupling patterns in humans have been assessed on the basis of the interaction between different physiological and motor subsystems; these interactions have implications for movement economy. A complex and dynamical systems framework may provide more insight than entrainment into the variability and adaptability of these rhythms and their coupling. The purpose of this study was to investigate the relationship between steady state locomotor-respiratory coordination dynamics and oxygen consumption [Formula: see text] of the movement by varying walking stride frequency from preferred. Twelve male participants walked on a treadmill at a self-selected speed. Stride frequency was varied from -20 to +20% of preferred stride frequency (PSF) while respiratory airflow, gas exchange variables, and stride kinematics were recorded. Discrete relative phase and return map techniques were used to evaluate the strength, stability, and variability of both frequency and phase couplings. Analysis of [Formula: see text] during steady-state walking showed a U-shaped response (P = 0.002) with a minimum at PSF and PSF - 10%. Locomotor-respiratory frequency coupling strength was not greater (P = 0.375) at PSF than any other stride frequency condition. The dominant coupling across all conditions was 2:1 with greater occurrences at the lower stride frequencies. Variability in coupling was the greatest during PSF, indicating an exploration of coupling strategies to search for the coupling frequency strategy with the least oxygen consumption. Contrary to the belief that increased strength of frequency coupling would decrease oxygen consumption; these results conclude that it is the increased variability of frequency coupling that results in lower oxygen consumption.

Variability in interhospital trauma data coding and scoring: A challenge to the accuracy of aggregated trauma registries.

PubMed

Arabian, Sandra S; Marcus, Michael; Captain, Kevin; Pomphrey, Michelle; Breeze, Janis; Wolfe, Jennefer; Bugaev, Nikolay; Rabinovici, Reuven

2015-09-01

Analyses of data aggregated in state and national trauma registries provide the platform for clinical, research, development, and quality improvement efforts in trauma systems. However, the interhospital variability and accuracy in data abstraction and coding have not yet been directly evaluated. This multi-institutional, Web-based, anonymous study examines interhospital variability and accuracy in data coding and scoring by registrars. Eighty-two American College of Surgeons (ACS)/state-verified Level I and II trauma centers were invited to determine different data elements including diagnostic, procedure, and Abbreviated Injury Scale (AIS) coding as well as selected National Trauma Data Bank definitions for the same fictitious case. Variability and accuracy in data entries were assessed by the maximal percent agreement among the registrars for the tested data elements, and 95% confidence intervals were computed to compare this level of agreement to the ideal value of 100%. Variability and accuracy in all elements were compared (χ testing) based on Trauma Quality Improvement Program (TQIP) membership, level of trauma center, ACS verification, and registrar's certifications. Fifty registrars (61%) completed the survey. The overall accuracy for all tested elements was 64%. Variability was noted in all examined parameters except for the place of occurrence code in all groups and the lower extremity AIS code in Level II trauma centers and in the Certified Specialist in Trauma Registry- and Certified Abbreviated Injury Scale Specialist-certified registrar groups. No differences in variability were noted when groups were compared based on TQIP membership, level of center, ACS verification, and registrar's certifications, except for prehospital Glasgow Coma Scale (GCS), where TQIP respondents agreed more than non-TQIP centers (p = 0.004). There is variability and inaccuracy in interhospital data coding and scoring of injury information. This finding casts doubt on the validity of registry data used in all aspects of trauma care and injury surveillance.

Cloud cover estimation: Use of GOES imagery in development of cloud cover data base for insolation assessment

NASA Technical Reports Server (NTRS)

Huning, J. R.; Logan, T. L.; Smith, J. H.

1982-01-01

The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics.

Advanced propulsion system for hybrid vehicles

NASA Technical Reports Server (NTRS)

Norrup, L. V.; Lintz, A. T.

1980-01-01

A number of hybrid propulsion systems were evaluated for application in several different vehicle sizes. A conceptual design was prepared for the most promising configuration. Various system configurations were parametrically evaluated and compared, design tradeoffs performed, and a conceptual design produced. Fifteen vehicle/propulsion systems concepts were parametrically evaluated to select two systems and one vehicle for detailed design tradeoff studies. A single hybrid propulsion system concept and vehicle (five passenger family sedan)were selected for optimization based on the results of the tradeoff studies. The final propulsion system consists of a 65 kW spark-ignition heat engine, a mechanical continuously variable traction transmission, a 20 kW permanent magnet axial-gap traction motor, a variable frequency inverter, a 386 kg lead-acid improved state-of-the-art battery, and a transaxle. The system was configured with a parallel power path between the heat engine and battery. It has two automatic operational modes: electric mode and heat engine mode. Power is always shared between the heat engine and battery during acceleration periods. In both modes, regenerative braking energy is absorbed by the battery.

CLINICAL APPLICATIONS OF CRYOTHERAPY AMONG SPORTS PHYSICAL THERAPISTS.

PubMed

Hawkins, Shawn W; Hawkins, Jeremy R

2016-02-01

Therapeutic modalities (TM) are used by sports physical therapists (SPT) but how they are used is unknown. To identify the current clinical use patterns for cryotherapy among SPT. Cross-sectional survey. All members (7283) of the Sports Physical Therapy Section of the APTA were recruited. A scenario-based survey using pre-participation management of an acute or sub-acute ankle sprain was developed. A Select Survey link was distributed via email to participants. Respondents selected a treatment approach based upon options provided. Follow-up questions were asked. The survey was available for two weeks with a follow-up email sent after one week. Question answers were the main outcome measures. Reliability: Cronbach's alpha=>0.9. The SPT response rate = 6.9% (503); responses came from 48 states. Survey results indicated great variability in respondents' approaches to the treatment of an acute and sub-acute ankle sprain. SPT applied cryotherapy with great variability and not always in accordance to the limited research on the TM. Continuing education, application of current research, and additional outcomes based research needs to remain a focus for clinicians. 3.

Identifying overarching excipient properties towards an in-depth understanding of process and product performance for continuous twin-screw wet granulation.

PubMed

Willecke, N; Szepes, A; Wunderlich, M; Remon, J P; Vervaet, C; De Beer, T

2017-04-30

The overall objective of this work is to understand how excipient characteristics influence the process and product performance for a continuous twin-screw wet granulation process. The knowledge gained through this study is intended to be used for a Quality by Design (QbD)-based formulation design approach and formulation optimization. A total of 9 preferred fillers and 9 preferred binders were selected for this study. The selected fillers and binders were extensively characterized regarding their physico-chemical and solid state properties using 21 material characterization techniques. Subsequently, principal component analysis (PCA) was performed on the data sets of filler and binder characteristics in order to reduce the variety of single characteristics to a limited number of overarching properties. Four principal components (PC) explained 98.4% of the overall variability in the fillers data set, while three principal components explained 93.4% of the overall variability in the data set of binders. Both PCA models allowed in-depth evaluation of similarities and differences in the excipient properties. Copyright © 2017. Published by Elsevier B.V.

Correlations and path analysis among agronomic and technological traits of upland cotton.

PubMed

Farias, F J C; Carvalho, L P; Silva Filho, J L; Teodoro, P E

2016-08-12

To date, path analysis has been used with the aim of breeding different cultures. However, for cotton, there have been few studies using this analysis, and all of these have used fiber productivity as the primary dependent variable. Therefore, the aim of the present study was to identify agronomic and technological properties that can be used as criteria for direct and indirect phenotypes in selecting cotton genotypes with better fibers. We evaluated 16 upland cotton genotypes in eight trials conducted during the harvest 2008/2009 in the State of Mato Grosso, using a randomized block design with four replicates. The evaluated traits were: plant height, average boll weight, percentage of fiber, cotton seed yield, fiber length, uniformity of fiber, short fiber index, fiber strength, elongation, maturity of the fibers, micronaire, reflectance, and the degree of yellowing. Phenotypic correlations between the traits and cotton fiber yield (main dependent variable) were unfolded in direct and indirect effects through path analysis. Fiber strength, uniformity of fiber, and reflectance were found to influence fiber length, and therefore, these traits are recommended for both direct and indirect selection of cotton genotypes.

Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

2018-05-01

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

Improve projections of changes in southern African summer rainfall through comprehensive multi-timescale empirical statistical downscaling

NASA Astrophysics Data System (ADS)

Dieppois, B.; Pohl, B.; Eden, J.; Crétat, J.; Rouault, M.; Keenlyside, N.; New, M. G.

2017-12-01

The water management community has hitherto neglected or underestimated many of the uncertainties in climate impact scenarios, in particular, uncertainties associated with decadal climate variability. Uncertainty in the state-of-the-art global climate models (GCMs) is time-scale-dependant, e.g. stronger at decadal than at interannual timescales, in response to the different parameterizations and to internal climate variability. In addition, non-stationarity in statistical downscaling is widely recognized as a key problem, in which time-scale dependency of predictors plays an important role. As with global climate modelling, therefore, the selection of downscaling methods must proceed with caution to avoid unintended consequences of over-correcting the noise in GCMs (e.g. interpreting internal climate variability as a model bias). GCM outputs from the Coupled Model Intercomparison Project 5 (CMIP5) have therefore first been selected based on their ability to reproduce southern African summer rainfall variability and their teleconnections with Pacific sea-surface temperature across the dominant timescales. In observations, southern African summer rainfall has recently been shown to exhibit significant periodicities at the interannual timescale (2-8 years), quasi-decadal (8-13 years) and inter-decadal (15-28 years) timescales, which can be interpret as the signature of ENSO, the IPO, and the PDO over the region. Most of CMIP5 GCMs underestimate southern African summer rainfall variability and their teleconnections with Pacific SSTs at these three timescales. In addition, according to a more in-depth analysis of historical and pi-control runs, this bias is might result from internal climate variability in some of the CMIP5 GCMs, suggesting potential for bias-corrected prediction based empirical statistical downscaling. A multi-timescale regression based downscaling procedure, which determines the predictors across the different timescales, has thus been used to simulate southern African summer rainfall. This multi-timescale procedure shows much better skills in simulating decadal timescales of variability compared to commonly used statistical downscaling approaches.

VARIABLE SELECTION FOR REGRESSION MODELS WITH MISSING DATA

PubMed Central

Garcia, Ramon I.; Ibrahim, Joseph G.; Zhu, Hongtu

2009-01-01

We consider the variable selection problem for a class of statistical models with missing data, including missing covariate and/or response data. We investigate the smoothly clipped absolute deviation penalty (SCAD) and adaptive LASSO and propose a unified model selection and estimation procedure for use in the presence of missing data. We develop a computationally attractive algorithm for simultaneously optimizing the penalized likelihood function and estimating the penalty parameters. Particularly, we propose to use a model selection criterion, called the ICQ statistic, for selecting the penalty parameters. We show that the variable selection procedure based on ICQ automatically and consistently selects the important covariates and leads to efficient estimates with oracle properties. The methodology is very general and can be applied to numerous situations involving missing data, from covariates missing at random in arbitrary regression models to nonignorably missing longitudinal responses and/or covariates. Simulations are given to demonstrate the methodology and examine the finite sample performance of the variable selection procedures. Melanoma data from a cancer clinical trial is presented to illustrate the proposed methodology. PMID:20336190

DETERMINANTS OF SPECIALTY CHOICE OF RESIDENT DOCTORS; CASE STUDY--AMONG RESIDENT DOCTORS IN NIGERIA.

PubMed

Osuoji, Roland I; Adebanji, Atinuke; Abdulsalam, Moruf A; Oludara, Mobolaji A; Abolarinwa, Abimbola A

2015-01-01

This study examined medical specialty selection by Nigerian resident doctors using a marketing research approach to determine the selection criteria and the role of perceptions, expected remuneration, and job placement prospects of various specialties in the selection process. Data were from the Community of residents from April 2014 to July 2014. The cohort included 200 residents, but only 171 had complete information. Data were obtained from a cross section of resident doctors in the Lagos State University Teaching Hospital and at the 2014 Ordinary General Meeting of the National Association of Resident Doctors(NARD) where representatives from over 50 Teaching hospitals in Nigeria attended. Using a client behaviour model as a framework, a tripartite questionnaire was designed and administered to residents to deduce information on their knowledge about and interests in various specialties, their opinions of sixteen specialties, and the criteria they used in specialty selection. A total of 171 (85.5%) questionnaires were returned. ln many instances, consistency between selection criteria and perceptions of a specialty were accompanied by interest in pursuing the specialty. Job security, job availability on completion of programme, duration of training and qualifying examinations were highly correlated with p value < 0.05. Results of the Principal Component Analysis show two components (with Eigen values greater than one) explaining 65.3% of the total variance. The first component had placement and training and practice related variables loaded on it while the second component was loaded with job security and financial remuneration related variables. Using marketing research concepts for medical specialty selection (Weissmanet al 2012) stipulates that choice of speciality is influenced by criteria and perception. This study shows that job security expected financial remuneration, and examination requirements for qualification are major determinants of the choice of speciality for residents.

Functional molecular markers (EST-SSR) in the full-sib reciprocal recurrent selection program of maize (Zea mays L.).

PubMed

Galvão, K S C; Ramos, H C C; Santos, P H A D; Entringer, G C; Vettorazzi, J C F; Pereira, M G

2015-07-03

This study aimed to improve grain yield in the full-sib reciprocal recurrent selection program of maize from the North Fluminense State University. In the current phase of the program, the goal is to maintain, or even increase, the genetic variability within and among populations, in order to increase heterosis of the 13th cycle of reciprocal recurrent selection. Microsatellite expressed sequence tags (EST-SSRs) were used as a tool to assist the maximization step of genetic variability, targeting the functional genome. Eighty S1 progenies of the 13th recur-rent selection cycle, 40 from each population (CIMMYT and Piranão), were analyzed using 20 EST-SSR loci. Genetic diversity, observed heterozygosity, information content of polymorphism, and inbreeding co-efficient were estimated. Subsequently, analysis of genetic dissimilarity, molecular variance, and a graphical dispersion of genotypes were conducted. The number of alleles in the CIMMYT population ranged from 1 to 6, while in the Piranão population the range was from 2 to 8, with a mean of 3.65 and 4.35, respectively. As evidenced by the number of alleles, the Shannon index showed greater diversity for the Piranão population (1.04) in relation to the CIMMYT population (0.89). The genic SSR markers were effective in clustering genotypes into their respective populations before selection and an increase in the variation between populations after selection was observed. The results indicate that the study populations have expressive genetic diversity, which cor-responds to the functional genome, indicating that this strategy may contribute to genetic gain, especially in association with the grain yield of future hybrids.

An efficient swarm intelligence approach to feature selection based on invasive weed optimization: Application to multivariate calibration and classification using spectroscopic data

NASA Astrophysics Data System (ADS)

Sheykhizadeh, Saheleh; Naseri, Abdolhossein

2018-04-01

Variable selection plays a key role in classification and multivariate calibration. Variable selection methods are aimed at choosing a set of variables, from a large pool of available predictors, relevant to the analyte concentrations estimation, or to achieve better classification results. Many variable selection techniques have now been introduced among which, those which are based on the methodologies of swarm intelligence optimization have been more respected during a few last decades since they are mainly inspired by nature. In this work, a simple and new variable selection algorithm is proposed according to the invasive weed optimization (IWO) concept. IWO is considered a bio-inspired metaheuristic mimicking the weeds ecological behavior in colonizing as well as finding an appropriate place for growth and reproduction; it has been shown to be very adaptive and powerful to environmental changes. In this paper, the first application of IWO, as a very simple and powerful method, to variable selection is reported using different experimental datasets including FTIR and NIR data, so as to undertake classification and multivariate calibration tasks. Accordingly, invasive weed optimization - linear discrimination analysis (IWO-LDA) and invasive weed optimization- partial least squares (IWO-PLS) are introduced for multivariate classification and calibration, respectively.

An efficient swarm intelligence approach to feature selection based on invasive weed optimization: Application to multivariate calibration and classification using spectroscopic data.

PubMed

Sheykhizadeh, Saheleh; Naseri, Abdolhossein

2018-04-05

Variable selection plays a key role in classification and multivariate calibration. Variable selection methods are aimed at choosing a set of variables, from a large pool of available predictors, relevant to the analyte concentrations estimation, or to achieve better classification results. Many variable selection techniques have now been introduced among which, those which are based on the methodologies of swarm intelligence optimization have been more respected during a few last decades since they are mainly inspired by nature. In this work, a simple and new variable selection algorithm is proposed according to the invasive weed optimization (IWO) concept. IWO is considered a bio-inspired metaheuristic mimicking the weeds ecological behavior in colonizing as well as finding an appropriate place for growth and reproduction; it has been shown to be very adaptive and powerful to environmental changes. In this paper, the first application of IWO, as a very simple and powerful method, to variable selection is reported using different experimental datasets including FTIR and NIR data, so as to undertake classification and multivariate calibration tasks. Accordingly, invasive weed optimization - linear discrimination analysis (IWO-LDA) and invasive weed optimization- partial least squares (IWO-PLS) are introduced for multivariate classification and calibration, respectively. Copyright © 2018 Elsevier B.V. All rights reserved.

Selection of housekeeping genes for gene expression studies in the adult rat submandibular gland under normal, inflamed, atrophic and regenerative states

PubMed Central

Silver, Nicholas; Cotroneo, Emanuele; Proctor, Gordon; Osailan, Samira; Paterson, Katherine L; Carpenter, Guy H

2008-01-01

Background Real-time PCR is a reliable tool with which to measure mRNA transcripts, and provides valuable information on gene expression profiles. Endogenous controls such as housekeeping genes are used to normalise mRNA levels between samples for sensitive comparisons of mRNA transcription. Selection of the most stable control gene(s) is therefore critical for the reliable interpretation of gene expression data. For the purpose of this study, 7 commonly used housekeeping genes were investigated in salivary submandibular glands under normal, inflamed, atrophic and regenerative states. Results The program NormFinder identified the suitability of HPRT to use as a single gene for normalisation within the normal, inflamed and regenerative states, and GAPDH in the atrophic state. For normalisation to multiple housekeeping genes, for each individual state, the optimal number of housekeeping genes as given by geNorm was: ACTB/UBC in the normal, ACTB/YWHAZ in the inflamed, ACTB/HPRT in the atrophic and ACTB/GAPDH in the regenerative state. The most stable housekeeping gene identified between states (compared to normal) was UBC. However, ACTB, identified as one of the most stably expressed genes within states, was found to be one of the most variable between states. Furthermore we demonstrated that normalising between states to ACTB, rather than UBC, introduced an approximately 3 fold magnitude of error. Conclusion Using NormFinder, our studies demonstrated the suitability of HPRT to use as a single gene for normalisation within the normal, inflamed and regenerative groups and GAPDH in the atrophic group. However, if normalising to multiple housekeeping genes, we recommend normalising to those identified by geNorm. For normalisation across the physiological states, we recommend the use of UBC. PMID:18637167

Unliganded HIV-1 gp120 core structures assume the CD4-bound conformation with regulation by quaternary interactions and variable loops

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

Kwon, Young Do; Finzi, Andrés; Wu, Xueling

2013-03-04

The HIV-1 envelope (Env) spike (gp120{sub 3}/gp41{sub 3}) undergoes considerable structural rearrangements to mediate virus entry into cells and to evade the host immune response. Engagement of CD4, the primary human receptor, fixes a particular conformation and primes Env for entry. The CD4-bound state, however, is prone to spontaneous inactivation and susceptible to antibody neutralization. How does unliganded HIV-1 maintain CD4-binding capacity and regulate transitions to the CD4-bound state? To define this mechanistically, we determined crystal structures of unliganded core gp120 from HIV-1 clades B, C, and E. Notably, all of these unliganded HIV-1 structures resembled the CD4-bound state. Conformationalmore » fixation with ligand selection and thermodynamic analysis of full-length and core gp120 interactions revealed that the tendency of HIV-1 gp120 to adopt the CD4-bound conformation was restrained by the V1/V2- and V3-variable loops. In parallel, we determined the structure of core gp120 in complex with the small molecule, NBD-556, which specifically recognizes the CD4-bound conformation of gp120. Neutralization by NBD-556 indicated that Env spikes on primary isolates rarely assume the CD4-bound conformation spontaneously, although they could do so when quaternary restraints were loosened. Together, the results suggest that the CD4-bound conformation represents a 'ground state' for the gp120 core, with variable loop and quaternary interactions restraining unliganded gp120 from 'snapping' into this conformation. A mechanism of control involving deformations in unliganded structure from a functionally critical state (e.g., the CD4-bound state) provides advantages in terms of HIV-1 Env structural diversity and resistance to antibodies and inhibitors, while maintaining elements essential for entry.« less

How well can body size represent effects of the environment on demographic rates? Disentangling correlated explanatory variables.

PubMed

Brooks, Mollie E; Mugabo, Marianne; Rodgers, Gwendolen M; Benton, Timothy G; Ozgul, Arpat

2016-03-01

Demographic rates are shaped by the interaction of past and current environments that individuals in a population experience. Past environments shape individual states via selection and plasticity, and fitness-related traits (e.g. individual size) are commonly used in demographic analyses to represent the effect of past environments on demographic rates. We quantified how well the size of individuals captures the effects of a population's past and current environments on demographic rates in a well-studied experimental system of soil mites. We decomposed these interrelated sources of variation with a novel method of multiple regression that is useful for understanding nonlinear relationships between responses and multicollinear explanatory variables. We graphically present the results using area-proportional Venn diagrams. Our novel method was developed by combining existing methods and expanding upon them. We showed that the strength of size as a proxy for the past environment varied widely among vital rates. For instance, in this organism with an income breeding life history, the environment had more effect on reproduction than individual size, but with substantial overlap indicating that size encompassed some of the effects of the past environment on fecundity. This demonstrates that the strength of size as a proxy for the past environment can vary widely among life-history processes within a species, and this variation should be taken into consideration in trait-based demographic or individual-based approaches that focus on phenotypic traits as state variables. Furthermore, the strength of a proxy will depend on what state variable(s) and what demographic rate is being examined; that is, different measures of body size (e.g. length, volume, mass, fat stores) will be better or worse proxies for various life-history processes. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

TIMSS 2011 Student and Teacher Predictors for Mathematics Achievement Explored and Identified via Elastic Net.

PubMed

Yoo, Jin Eun

2018-01-01

A substantial body of research has been conducted on variables relating to students' mathematics achievement with TIMSS. However, most studies have employed conventional statistical methods, and have focused on selected few indicators instead of utilizing hundreds of variables TIMSS provides. This study aimed to find a prediction model for students' mathematics achievement using as many TIMSS student and teacher variables as possible. Elastic net, the selected machine learning technique in this study, takes advantage of both LASSO and ridge in terms of variable selection and multicollinearity, respectively. A logistic regression model was also employed to predict TIMSS 2011 Korean 4th graders' mathematics achievement. Ten-fold cross-validation with mean squared error was employed to determine the elastic net regularization parameter. Among 162 TIMSS variables explored, 12 student and 5 teacher variables were selected in the elastic net model, and the prediction accuracy, sensitivity, and specificity were 76.06, 70.23, and 80.34%, respectively. This study showed that the elastic net method can be successfully applied to educational large-scale data by selecting a subset of variables with reasonable prediction accuracy and finding new variables to predict students' mathematics achievement. Newly found variables via machine learning can shed light on the existing theories from a totally different perspective, which in turn propagates creation of a new theory or complement of existing ones. This study also examined the current scale development convention from a machine learning perspective.

TIMSS 2011 Student and Teacher Predictors for Mathematics Achievement Explored and Identified via Elastic Net

PubMed Central

Yoo, Jin Eun

2018-01-01

A substantial body of research has been conducted on variables relating to students' mathematics achievement with TIMSS. However, most studies have employed conventional statistical methods, and have focused on selected few indicators instead of utilizing hundreds of variables TIMSS provides. This study aimed to find a prediction model for students' mathematics achievement using as many TIMSS student and teacher variables as possible. Elastic net, the selected machine learning technique in this study, takes advantage of both LASSO and ridge in terms of variable selection and multicollinearity, respectively. A logistic regression model was also employed to predict TIMSS 2011 Korean 4th graders' mathematics achievement. Ten-fold cross-validation with mean squared error was employed to determine the elastic net regularization parameter. Among 162 TIMSS variables explored, 12 student and 5 teacher variables were selected in the elastic net model, and the prediction accuracy, sensitivity, and specificity were 76.06, 70.23, and 80.34%, respectively. This study showed that the elastic net method can be successfully applied to educational large-scale data by selecting a subset of variables with reasonable prediction accuracy and finding new variables to predict students' mathematics achievement. Newly found variables via machine learning can shed light on the existing theories from a totally different perspective, which in turn propagates creation of a new theory or complement of existing ones. This study also examined the current scale development convention from a machine learning perspective. PMID:29599736

Novel harmonic regularization approach for variable selection in Cox's proportional hazards model.

PubMed

Chu, Ge-Jin; Liang, Yong; Wang, Jia-Xuan

2014-01-01

Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq  (1/2 < q < 1) regularizations, to select key risk factors in the Cox's proportional hazards model using microarray gene expression data. The harmonic regularization method can be efficiently solved using our proposed direct path seeking approach, which can produce solutions that closely approximate those for the convex loss function and the nonconvex regularization. Simulation results based on the artificial datasets and four real microarray gene expression datasets, such as real diffuse large B-cell lymphoma (DCBCL), the lung cancer, and the AML datasets, show that the harmonic regularization method can be more accurate for variable selection than existing Lasso series methods.

Emotional state and psychological flexibility in breast cancer survivors.

PubMed

González-Fernández, Sonia; Fernández-Rodríguez, Concepción; Mota-Alonso, María Jesús; García-Teijido, Paula; Pedrosa, Ignacio; Pérez-Álvarez, Marino

2017-10-01

This study analyses the premise that less time spent carrying out valuable activities and inflexible avoidance of thoughts, feelings and memories related to the oncological process may play an important role in the emotional problems of cancer survivors. Emotional state was evaluated, as was quality of life and psychological flexibility in a sample of 122 breast cancer survivors (M age  = 52.40; SD age  = 7.26). The analysis was carried out using a cross-sectional predictive study. Approximately half of those in the sample suffered from clinically significant emotional distress. The predictor variables selected explained a high percentage of the variability in emotional problems and quality of life (51.10-77.10%). Avoidance explained a high percentage of the variance in anxiety, depression and general distress. A lower degree of participation in valuable activities contributed, more specifically, to explaining variability in depression. The quantity and availability of environmental reinforcement was closely related to quality of life. A decisive contribution towards promoting emotional well-being and quality of life can be made by nursing action aimed at diminishing those avoidance strategies related to the oncological experience which may distance patients from daily activities which are gratifying and congruent with their values. Copyright © 2017 Elsevier Ltd. All rights reserved.

Firmness prediction in Prunus persica 'Calrico' peaches by visible/short-wave near infrared spectroscopy and acoustic measurements using optimised linear and non-linear chemometric models.

PubMed

Lafuente, Victoria; Herrera, Luis J; Pérez, María del Mar; Val, Jesús; Negueruela, Ignacio

2015-08-15

In this work, near infrared spectroscopy (NIR) and an acoustic measure (AWETA) (two non-destructive methods) were applied in Prunus persica fruit 'Calrico' (n = 260) to predict Magness-Taylor (MT) firmness. Separate and combined use of these measures was evaluated and compared using partial least squares (PLS) and least squares support vector machine (LS-SVM) regression methods. Also, a mutual-information-based variable selection method, seeking to find the most significant variables to produce optimal accuracy of the regression models, was applied to a joint set of variables (NIR wavelengths and AWETA measure). The newly proposed combined NIR-AWETA model gave good values of the determination coefficient (R(2)) for PLS and LS-SVM methods (0.77 and 0.78, respectively), improving the reliability of MT firmness prediction in comparison with separate NIR and AWETA predictions. The three variables selected by the variable selection method (AWETA measure plus NIR wavelengths 675 and 697 nm) achieved R(2) values 0.76 and 0.77, PLS and LS-SVM. These results indicated that the proposed mutual-information-based variable selection algorithm was a powerful tool for the selection of the most relevant variables. © 2014 Society of Chemical Industry.

Structure Activity Relationship Studies of Flavonoids as Potent Inhibitors of Human Platelet 12-hLO, Reticulocyte 15-hLO-1 and Prostate Epithelial 15-hLO-2

PubMed Central

Vasquez-Martinez, Yesseny; Ohri, Rachana V.; Kenyon, Victor; Holman, Theodore R.; Sepúlveda-Boza, Silvia

2007-01-01

Human lipoxygenase (hLO) isozymes have been implicated in a number of disease states and have attracted much attention with respect to their inhibition. One class of inhibitors, the flavonoids, have been shown to be potent lipoxygenase inhibitors but their study has been restricted to those compounds found in nature, which have limited structural variability. We have therefore carried out a comprehensive study to determine the structural requirements for flavonoid potency and selectivity against platelet 12-hLO, reticulocyte 15-hLO-1 and prostate epithelial 15-hLO-2. We conclude from this study that catechols are essential for high potency, that isoflavones and isoflavanones tend to select against 12-hLO, that isoflavans tend to select against 15-hLO-1, but few flavonoids target 15-hLO-2. PMID:17869117

Evaluation of Maryland abutment scour equation through selected threshold velocity methods

USGS Publications Warehouse

Benedict, S.T.

2010-01-01

The U.S. Geological Survey, in cooperation with the Maryland State Highway Administration, used field measurements of scour to evaluate the sensitivity of the Maryland abutment scour equation to the critical (or threshold) velocity variable. Four selected methods for estimating threshold velocity were applied to the Maryland abutment scour equation, and the predicted scour to the field measurements were compared. Results indicated that performance of the Maryland abutment scour equation was sensitive to the threshold velocity with some threshold velocity methods producing better estimates of predicted scour than did others. In addition, results indicated that regional stream characteristics can affect the performance of the Maryland abutment scour equation with moderate-gradient streams performing differently from low-gradient streams. On the basis of the findings of the investigation, guidance for selecting threshold velocity methods for application to the Maryland abutment scour equation are provided, and limitations are noted.

Talent identification and selection in elite youth football: An Australian context.

PubMed

O'Connor, Donna; Larkin, Paul; Mark Williams, A

2016-10-01

We identified the perceptual-cognitive skills and player history variables that differentiate players selected or not selected into an elite youth football (i.e. soccer) programme in Australia. A sample of elite youth male football players (n = 127) completed an adapted participation history questionnaire and video-based assessments of perceptual-cognitive skills. Following data collection, 22 of these players were offered a full-time scholarship for enrolment at an elite player residential programme. Participants selected for the scholarship programme recorded superior performance on the combined perceptual-cognitive skills tests compared to the non-selected group. There were no significant between group differences on the player history variables. Stepwise discriminant function analysis identified four predictor variables that resulted in the best categorization of selected and non-selected players (i.e. recent match-play performance, region, number of other sports participated, combined perceptual-cognitive performance). The effectiveness of the discriminant function is reflected by 93.7% of players being correctly classified, with the four variables accounting for 57.6% of the variance. Our discriminating model for selection may provide a greater understanding of the factors that influence elite youth talent selection and identification.

Application of Probabilistic Methods for the Determination of an Economically Robust HSCT Configuration

NASA Technical Reports Server (NTRS)

Mavris, Dimitri N.; Bandte, Oliver; Schrage, Daniel P.

1996-01-01

This paper outlines an approach for the determination of economically viable robust design solutions using the High Speed Civil Transport (HSCT) as a case study. Furthermore, the paper states the advantages of a probability based aircraft design over the traditional point design approach. It also proposes a new methodology called Robust Design Simulation (RDS) which treats customer satisfaction as the ultimate design objective. RDS is based on a probabilistic approach to aerospace systems design, which views the chosen objective as a distribution function introduced by so called noise or uncertainty variables. Since the designer has no control over these variables, a variability distribution is defined for each one of them. The cumulative effect of all these distributions causes the overall variability of the objective function. For cases where the selected objective function depends heavily on these noise variables, it may be desirable to obtain a design solution that minimizes this dependence. The paper outlines a step by step approach on how to achieve such a solution for the HSCT case study and introduces an evaluation criterion which guarantees the highest customer satisfaction. This customer satisfaction is expressed by the probability of achieving objective function values less than a desired target value.

Relationship between health services, socioeconomic variables and inadequate weight gain among Brazilian children.

PubMed Central

de Souza, A. C.; Peterson, K. E.; Cufino, E.; Gardner, J.; Craveiro, M. V.; Ascherio, A.

1999-01-01

This ecological analysis assessed the relative contribution of behavioural, health services and socioeconomic variables to inadequate weight gain in infants (0-11 months) and children (12-23 months) in 140 municipalities in the State of Ceara, north-east Brazil. To assess the total effect of selected variables, we fitted three unique sets of multivariate linear regression models to the prevalence of inadequate weight gain in infants and in children. The final predictive models included variables from the three sets. Findings showed that participation in growth monitoring and urbanization were inversely and significantly associated with the prevalence of inadequate weight gain in infants, accounting for 38.3% of the variation. Female illiteracy rate, participation in growth monitoring and degree of urbanization were all positively associated with prevalence of inadequate weight gain in children. Together, these factors explained 25.6% of the variation. Our results suggest that efforts to reduce the average municipality-specific female illiteracy rate, in combination with participation in growth monitoring, may be effective in reducing municipality-level prevalence of inadequate weight gain in infants and children in Ceara. PMID:10612885

Variable stiffness mechanisms with SMA actuators

NASA Astrophysics Data System (ADS)

Siler, Damin J.; Demoret, Kimberly B. J.

1996-05-01

Variable stiffness is a new branch of smart structures development with several applications related to aircraft. Previous research indicates that temporarily reducing the stiffness of an airplane wing can decrease control actuator sizing and improve aeroelastic roll performance. Some smart materials like shape memory alloys (SMA) can change their material stiffness properties, but they tend to gain stiffness in their `power on' state. An alternative is to integrate mechanisms into a structure and change stiffness by altering boundary conditions and structural load paths. An innovative concept for an axial strut mechanism was discovered as part of research into variable stiffness. It employs SMA springs (specifically Ni-Ti) in a way that reduces overall stiffness when the SMA springs gain stiffness. A simplified mathematical model for static analysis was developed, and a 70% reduction in stiffness was obtained for a particular selection of springs. The small force capacity of commercially available SMA springs limits the practicality of this concept for large load applications. However, smart material technology is still immature, and future advances may permit development of a heavy-duty, variable stiffness strut that is small and light enough for use in aircraft structures.

Relationship between health services, socioeconomic variables and inadequate weight gain among Brazilian children.

PubMed

de Souza, A C; Peterson, K E; Cufino, E; Gardner, J; Craveiro, M V; Ascherio, A

1999-01-01

This ecological analysis assessed the relative contribution of behavioural, health services and socioeconomic variables to inadequate weight gain in infants (0-11 months) and children (12-23 months) in 140 municipalities in the State of Ceara, north-east Brazil. To assess the total effect of selected variables, we fitted three unique sets of multivariate linear regression models to the prevalence of inadequate weight gain in infants and in children. The final predictive models included variables from the three sets. Findings showed that participation in growth monitoring and urbanization were inversely and significantly associated with the prevalence of inadequate weight gain in infants, accounting for 38.3% of the variation. Female illiteracy rate, participation in growth monitoring and degree of urbanization were all positively associated with prevalence of inadequate weight gain in children. Together, these factors explained 25.6% of the variation. Our results suggest that efforts to reduce the average municipality-specific female illiteracy rate, in combination with participation in growth monitoring, may be effective in reducing municipality-level prevalence of inadequate weight gain in infants and children in Ceara.

LINEAR - DERIVATION AND DEFINITION OF A LINEAR AIRCRAFT MODEL

NASA Technical Reports Server (NTRS)

Duke, E. L.

1994-01-01

The Derivation and Definition of a Linear Model program, LINEAR, provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models. LINEAR was developed to provide a standard, documented, and verified tool to derive linear models for aircraft stability analysis and control law design. Linear system models define the aircraft system in the neighborhood of an analysis point and are determined by the linearization of the nonlinear equations defining vehicle dynamics and sensors. LINEAR numerically determines a linear system model using nonlinear equations of motion and a user supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. LINEAR is capable of extracting both linearized engine effects, such as net thrust, torque, and gyroscopic effects and including these effects in the linear system model. The point at which this linear model is defined is determined either by completely specifying the state and control variables, or by specifying an analysis point on a trajectory and directing the program to determine the control variables and the remaining state variables. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to provide easy selection of state, control, and observation variables to be used in a particular model. Thus, the order of the system model is completely under user control. Further, the program provides the flexibility of allowing alternate formulations of both the state and observation equations. Data describing the aircraft and the test case is input to the program through a terminal or formatted data files. All data can be modified interactively from case to case. The aerodynamic model can be defined in two ways: a set of nondimensional stability and control derivatives for the flight point of interest, or a full non-linear aerodynamic model as used in simulations. LINEAR is written in FORTRAN and has been implemented on a DEC VAX computer operating under VMS with a virtual memory requirement of approximately 296K of 8 bit bytes. Both an interactive and batch version are included. LINEAR was developed in 1988.

Advances in variable selection methods II: Effect of variable selection method on classification of hydrologically similar watersheds in three Mid-Atlantic ecoregions

EPA Science Inventory

Hydrological flow predictions in ungauged and sparsely gauged watersheds use regionalization or classification of hydrologically similar watersheds to develop empirical relationships between hydrologic, climatic, and watershed variables. The watershed classifications may be based...

A Variable-Selection Heuristic for K-Means Clustering.

ERIC Educational Resources Information Center

Brusco, Michael J.; Cradit, J. Dennis

2001-01-01

Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

Genetic progress in the UNB-2U population of popcorn under recurrent selection in Rio de Janeiro, Brazil.

PubMed

Ribeiro, R M; do Amaral Júnior, A T; Gonçalves, L S A; Candido, L S; Silva, T R C; Pena, G F

2012-05-15

As part of the Universidade Estadual do Norte Fluminense recurrent selection program of popcorn, we evaluated full-sib families of the sixth cycle of recurrent selection and estimated genetic progress for grain yield and expansion capacity. We assessed 200 full-sib families for 10 agronomic traits, in a randomized block design, with two replications within sets in two environments: Campos dos Goytacazes and Itaocara, in the State of Rio de Janeiro, Brazil. There were significant differences for families/"sets" for all traits, indicating genetic variability that could be exploited in future cycles. In the selection of superior progenies, the Mulamba and Mock index gave the best gains for popping expansion (PE) and grain yield (GY), with values of 10.97 and 15.30%, respectively, using random economic weights. By comparing the evolution of the means obtained for PE and GY in the cycles C(0), C(1), C(2), C(3), C(4), C(5), and predicted for C(6), a steady increase was observed for both PE and GY, with the addition of 1.71 mL/g (R(2) = 0.93) and 192.87 kg/ha (R(2) = 0.88), respectively, in each cycle. Given the good performance of this popcorn population in successive cycles of intrapopulation recurrent selection, we expect that a productive variety with high expansion capacity will soon be available for producers in the north and northwest regions of Rio de Janeiro State, Brazil.

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 2: Structure Design for State Estimation with Secondary Measurements

PubMed Central

2017-01-01

This work investigates the design of alternative monitoring tools based on state estimators for industrial crystallization systems with nucleation, growth, and agglomeration kinetics. The estimation problem is regarded as a structure design problem where the estimation model and the set of innovated states have to be chosen; the estimator is driven by the available measurements of secondary variables. On the basis of Robust Exponential estimability arguments, it is found that the concentration is distinguishable with temperature and solid fraction measurements while the crystal size distribution (CSD) is not. Accordingly, a state estimator structure is selected such that (i) the concentration (and other distinguishable states) are innovated by means of the secondary measurements processed with the geometric estimator (GE), and (ii) the CSD is estimated by means of a rigorous model in open loop mode. The proposed estimator has been tested through simulations showing good performance in the case of mismatch in the initial conditions, parametric plant-model mismatch, and noisy measurements. PMID:28890604

Monitoring of Batch Industrial Crystallization with Growth, Nucleation, and Agglomeration. Part 2: Structure Design for State Estimation with Secondary Measurements.

PubMed

Porru, Marcella; Özkan, Leyla

2017-08-30

This work investigates the design of alternative monitoring tools based on state estimators for industrial crystallization systems with nucleation, growth, and agglomeration kinetics. The estimation problem is regarded as a structure design problem where the estimation model and the set of innovated states have to be chosen; the estimator is driven by the available measurements of secondary variables. On the basis of Robust Exponential estimability arguments, it is found that the concentration is distinguishable with temperature and solid fraction measurements while the crystal size distribution (CSD) is not. Accordingly, a state estimator structure is selected such that (i) the concentration (and other distinguishable states) are innovated by means of the secondary measurements processed with the geometric estimator (GE), and (ii) the CSD is estimated by means of a rigorous model in open loop mode. The proposed estimator has been tested through simulations showing good performance in the case of mismatch in the initial conditions, parametric plant-model mismatch, and noisy measurements.

Sustained State-Independent Quantum Contextual Correlations from a Single Ion

NASA Astrophysics Data System (ADS)

Leupold, F. M.; Malinowski, M.; Zhang, C.; Negnevitsky, V.; Alonso, J.; Home, J. P.; Cabello, A.

2018-05-01

We use a single trapped-ion qutrit to demonstrate the quantum-state-independent violation of noncontextuality inequalities using a sequence of randomly chosen quantum nondemolition projective measurements. We concatenate 53 ×106 sequential measurements of 13 observables, and unambiguously violate an optimal noncontextual bound. We use the same data set to characterize imperfections including signaling and repeatability of the measurements. The experimental sequence was generated in real time with a quantum random number generator integrated into our control system to select the subsequent observable with a latency below 50 μ s , which can be used to constrain contextual hidden-variable models that might describe our results. The state-recycling experimental procedure is resilient to noise and independent of the qutrit state, substantiating the fact that the contextual nature of quantum physics is connected to measurements and not necessarily to designated states. The use of extended sequences of quantum nondemolition measurements finds applications in the fields of sensing and quantum information.

Preliminary power train design for a state-of-the-art electric vehicle

NASA Technical Reports Server (NTRS)

Mighdoll, P.; Hahn, W. F.

1978-01-01

Power train designs which can be implemented within the current state-of-the-art were identified by means of a review of existing electric vehicles and suitable off-the-shelf components. The affect of various motor/transmission combinations on vehicle range over the SAE J227a schedule D cycle was evaluated. The selected, state-of-the-art power train employs a dc series wound motor, SCR controller, variable speed transmission, regenerative braking, drum brakes and radial ply tires. Vehicle range over the SAE cycle can be extended by approximately 20% by the further development of separately excited, shunt wound DC motors and electrical controllers. Approaches which could improve overall power train efficiency, such as AC motor systems, are identified. However, future emphasis should remain on batteries, tires and lightweight structures if substantial range improvements are to be achieved.

Procedures for generation and reduction of linear models of a turbofan engine

NASA Technical Reports Server (NTRS)

Seldner, K.; Cwynar, D. S.

1978-01-01

A real time hybrid simulation of the Pratt & Whitney F100-PW-F100 turbofan engine was used for linear-model generation. The linear models were used to analyze the effect of disturbances about an operating point on the dynamic performance of the engine. A procedure that disturbs, samples, and records the state and control variables was developed. For large systems, such as the F100 engine, the state vector is large and may contain high-frequency information not required for control. This, reducing the full-state to a reduced-order model may be a practicable approach to simplifying the control design. A reduction technique was developed to generate reduced-order models. Selected linear and nonlinear output responses to exhaust-nozzle area and main-burner fuel flow disturbances are presented for comparison.

Determinants of customer satisfaction with hospitals: a managerial model.

PubMed

Andaleeb, S S

1998-01-01

States that rapid changes in the environment have exerted significant pressures on hospitals to incorporate patient satisfaction in their strategic stance and quest for market share and long-term viability. This study proposes and tests a five-factor model that explains considerable variation in customer satisfaction with hospitals. These factors include communication with patients, competence of the staff, their demeanour, quality of the facilities, and perceived costs; they also represent strategic concepts that managers can address in their bid to remain competitive. A probability sample was selected and a multiple regression model used to test the hypotheses. The results indicate that all five variables were significant in the model and explained 62 per cent of the variation in the dependent variable. Managerial implications of the proposed model are discussed.

An evolving effective stress approach to anisotropic distortional hardening

DOE PAGES

Lester, B. T.; Scherzinger, W. M.

2018-03-11

A new yield surface with an evolving effective stress definition is proposed for consistently and efficiently describing anisotropic distortional hardening. Specifically, a new internal state variable is introduced to capture the thermodynamic evolution between different effective stress definitions. The corresponding yield surface and evolution equations of the internal variables are derived from thermodynamic considerations enabling satisfaction of the second law. A closest point projection return mapping algorithm for the proposed model is formulated and implemented for use in finite element analyses. Finally, select constitutive and larger scale boundary value problems are solved to explore the capabilities of the model andmore » examine the impact of distortional hardening on constitutive and structural responses. Importantly, these simulations demonstrate the tractability of the proposed formulation in investigating large-scale problems of interest.« less

An evolving effective stress approach to anisotropic distortional hardening

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

Lester, B. T.; Scherzinger, W. M.

A new yield surface with an evolving effective stress definition is proposed for consistently and efficiently describing anisotropic distortional hardening. Specifically, a new internal state variable is introduced to capture the thermodynamic evolution between different effective stress definitions. The corresponding yield surface and evolution equations of the internal variables are derived from thermodynamic considerations enabling satisfaction of the second law. A closest point projection return mapping algorithm for the proposed model is formulated and implemented for use in finite element analyses. Finally, select constitutive and larger scale boundary value problems are solved to explore the capabilities of the model andmore » examine the impact of distortional hardening on constitutive and structural responses. Importantly, these simulations demonstrate the tractability of the proposed formulation in investigating large-scale problems of interest.« less

Photoswitchable carbohydrate-based fluorosurfactants as tuneable ice recrystallization inhibitors.

PubMed

Adam, Madeleine K; Hu, Yingxue; Poisson, Jessica S; Pottage, Matthew J; Ben, Robert N; Wilkinson, Brendan L

2017-02-01

Cryopreservation is an important technique employed for the storage and preservation of biological tissues and cells. The limited effectiveness and significant toxicity of conventionally-used cryoprotectants, such as DMSO, have prompted efforts toward the rational design of less toxic alternatives, including carbohydrate-based surfactants. In this paper, we report the modular synthesis and ice recrystallization inhibition (IRI) activity of a library of variably substituted, carbohydrate-based fluorosurfactants. Carbohydrate-based fluorosurfactants possessed a variable mono- or disaccharide head group appended to a hydrophobic fluoroalkyl-substituted azobenzene tail group. Light-addressable fluorosurfactants displayed weak-to-moderate IRI activity that could be tuned through selection of carbohydrate head group, position of the trifluoroalkyl group on the azobenzene ring, and isomeric state of the azobenzene tail fragment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

The upper bound of Pier Scour defined by selected laboratory and field data

USGS Publications Warehouse

Benedict, Stephen; Caldwell, Andral W.

2015-01-01

The U.S. Geological Survey, in cooperation with the South Carolina Department of Transportation, conducted several field investigations of pier scour in South Carolina (Benedict and Caldwell, 2006; Benedict and Caldwell, 2009) and used that data to develop envelope curves defining the upper bound of pier scour. To expand upon this previous work, an additional cooperative investigation was initiated to combine the South Carolina data with pier-scour data from other sources and evaluate the upper bound of pier scour with this larger data set. To facilitate this analysis, a literature review was made to identify potential sources of published pier-scour data, and selected data were compiled into a digital spreadsheet consisting of approximately 570 laboratory and 1,880 field measurements. These data encompass a wide range of laboratory and field conditions and represent field data from 24 states within the United States and six other countries. This extensive database was used to define the upper bound of pier-scour depth with respect to pier width encompassing the laboratory and field data. Pier width is a primary variable that influences pier-scour depth (Laursen and Toch, 1956; Melville and Coleman, 2000; Mueller and Wagner, 2005, Ettema et al. 2011, Arneson et al. 2012) and therefore, was used as the primary explanatory variable in developing the upper-bound envelope curve. The envelope curve provides a simple but useful tool for assessing the potential maximum pier-scour depth for pier widths of about 30 feet or less.

Confirmatory and quantitative analysis of fatty acid esters of hydroxy fatty acids in serum by solid phase extraction coupled to liquid chromatography tandem mass spectrometry.

PubMed

López-Bascón, María Asunción; Calderón-Santiago, Mónica; Priego-Capote, Feliciano

2016-11-02

A novel class of endogenous mammalian lipids endowed with antidiabetic and anti-inflammatory properties has been recently discovered. These are fatty acid esters of hydroxy fatty acids (FAHFAs) formed by condensation between a hydroxy fatty acid and a fatty acid. FAHFAs are present in human serum and tissues at low nanomolar concentrations. Therefore, high sensitivity and selectivity profiling analysis of these compounds in clinical samples is demanded. An automated qualitative and quantitative method based on on-line coupling between solid phase extraction and liquid chromatography-tandem mass spectrometry has been here developed for determination of FAHFAs in serum with the required sensitivity and selectivity. Matrix effects were evaluated by preparation of calibration models in serum and methanol. Recovery factors ranged between 73.8 and 100% in serum. The within-day variability ranged from 7.1 to 13.8%, and the between-days variability varied from 9.3 to 21.6%, which are quite acceptable values taking into account the low concentration levels at which the target analytes are found. The method has been applied to a cohort of human serum samples to estimate the concentrations profiles as a function of the glycaemic state and obesity. Statistical analysis revealed three FAHFAs with levels significantly different depending on the glycaemic state or the body mass index. This automated method could be implemented in high-throughput analysis with minimum user assistance. Copyright © 2016 Elsevier B.V. All rights reserved.

Novel Harmonic Regularization Approach for Variable Selection in Cox's Proportional Hazards Model

PubMed Central

Chu, Ge-Jin; Liang, Yong; Wang, Jia-Xuan

2014-01-01

Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq  (1/2 < q < 1) regularizations, to select key risk factors in the Cox's proportional hazards model using microarray gene expression data. The harmonic regularization method can be efficiently solved using our proposed direct path seeking approach, which can produce solutions that closely approximate those for the convex loss function and the nonconvex regularization. Simulation results based on the artificial datasets and four real microarray gene expression datasets, such as real diffuse large B-cell lymphoma (DCBCL), the lung cancer, and the AML datasets, show that the harmonic regularization method can be more accurate for variable selection than existing Lasso series methods. PMID:25506389

Covariate Selection for Multilevel Models with Missing Data

PubMed Central

Marino, Miguel; Buxton, Orfeu M.; Li, Yi

2017-01-01

Missing covariate data hampers variable selection in multilevel regression settings. Current variable selection techniques for multiply-imputed data commonly address missingness in the predictors through list-wise deletion and stepwise-selection methods which are problematic. Moreover, most variable selection methods are developed for independent linear regression models and do not accommodate multilevel mixed effects regression models with incomplete covariate data. We develop a novel methodology that is able to perform covariate selection across multiply-imputed data for multilevel random effects models when missing data is present. Specifically, we propose to stack the multiply-imputed data sets from a multiple imputation procedure and to apply a group variable selection procedure through group lasso regularization to assess the overall impact of each predictor on the outcome across the imputed data sets. Simulations confirm the advantageous performance of the proposed method compared with the competing methods. We applied the method to reanalyze the Healthy Directions-Small Business cancer prevention study, which evaluated a behavioral intervention program targeting multiple risk-related behaviors in a working-class, multi-ethnic population. PMID:28239457

Analysis and Design of High-Order Parallel Resonant Converters

NASA Astrophysics Data System (ADS)

Batarseh, Issa Eid

1990-01-01

In this thesis, a special state variable transformation technique has been derived for the analysis of high order dc-to-dc resonant converters. Converters comprised of high order resonant tanks have the advantage of utilizing the parasitic elements by making them part of the resonant tank. A new set of state variables is defined in order to make use of two-dimensional state-plane diagrams in the analysis of high order converters. Such a method has been successfully used for the analysis of the conventional Parallel Resonant Converters (PRC). Consequently, two -dimensional state-plane diagrams are used to analyze the steady state response for third and fourth order PRC's when these converters are operated in the continuous conduction mode. Based on this analysis, a set of control characteristic curves for the LCC-, LLC- and LLCC-type PRC are presented from which various converter design parameters are obtained. Various design curves for component value selections and device ratings are given. This analysis of high order resonant converters shows that the addition of the reactive components to the resonant tank results in converters with better performance characteristics when compared with the conventional second order PRC. Complete design procedure along with design examples for 2nd, 3rd and 4th order converters are presented. Practical power supply units, normally used for computer applications, were built and tested by using the LCC-, LLC- and LLCC-type commutation schemes. In addition, computer simulation results are presented for these converters in order to verify the theoretical results.

Frequency ranges of heart rate variability related to autonomic nerve activity in the mouse.

PubMed

Tsai, Meng-Li; Chen, Chien-Chang; Yeh, Chang-Jyi; Chou, Li-Ming; Cheng, Chiung-Hsiang

2012-01-01

Mice have gained more and more attention in recent years and been widely used in transgenic experiments. Although the number of researches on the heart rate variability (HRV) of mice has been gradually increasing, a consensus on the frequency ranges of autonomic modulation has not been established. Therefore, the main purpose of this study was to find a HRV "prototype" for conscious mice in the state of being motionless and breathing regularly (called "genuinely resting"), and to determine the frequency ranges corresponding to the autonomic modulation. Further, whether these frequencies will change when the mice move freely was studied to evaluate the feasibility of the HRV spectrum as an index of the autonomic modulation of mice. The recording sites were specially arranged to simultaneously obtain the electrocardiography and electromyography data to be provided for the use of HRV analysis and motion monitoring, respectively. The states of being motionless and breathing regularly as judged from the electromyography results were selected as a genuine resting state of a conscious mouse. The frequencies related to autonomic modulation of HRV were determined by comparing the spectrum changes before and after blockades of the autonomic tone by different pharmaceutical agents in both the genuine resting state and freely moving states. Our results showed that the HRV of mice is not suitable for indexing sympathetic modulation; however, it is possible to use the spectral power in the frequency range between 0.1 and 1 Hz as an index of parasympathetic modulation.

The Role of Trait and State Absorption in the Enjoyment of Music

PubMed Central

2016-01-01

Little is known about the role of state versus trait characteristics on our enjoyment of music. The aim of this study was to investigate the influence of state and trait absorption upon preference for music, particularly preference for music that evokes negative emotions. The sample consisted of 128 participants who were asked to listen to two pieces of self-selected music and rate the music on variables including preference and felt and expressed emotions. Participants completed a brief measure of state absorption after listening to each piece, and a trait absorption inventory. State absorption was strongly positively correlated with music preference, whereas trait absorption was not. Trait absorption was related to preference for negative emotions in music, with chi-square analyses demonstrating greater enjoyment of negative emotions in music among individuals with high trait absorption. This is the first study to show that state and trait absorption have separable and distinct effects on a listener’s music experience, with state characteristics impacting music enjoyment in the moment, and trait characteristics influencing music preference based on its emotional content. PMID:27828970

The Role of Trait and State Absorption in the Enjoyment of Music.

PubMed

Hall, Sarah E; Schubert, Emery; Wilson, Sarah J

2016-01-01

Little is known about the role of state versus trait characteristics on our enjoyment of music. The aim of this study was to investigate the influence of state and trait absorption upon preference for music, particularly preference for music that evokes negative emotions. The sample consisted of 128 participants who were asked to listen to two pieces of self-selected music and rate the music on variables including preference and felt and expressed emotions. Participants completed a brief measure of state absorption after listening to each piece, and a trait absorption inventory. State absorption was strongly positively correlated with music preference, whereas trait absorption was not. Trait absorption was related to preference for negative emotions in music, with chi-square analyses demonstrating greater enjoyment of negative emotions in music among individuals with high trait absorption. This is the first study to show that state and trait absorption have separable and distinct effects on a listener's music experience, with state characteristics impacting music enjoyment in the moment, and trait characteristics influencing music preference based on its emotional content.

Highlights of Odessa Branch of AN in 2017

NASA Astrophysics Data System (ADS)

Andronov, I. L.

2017-12-01

An annual report with a list of publications. Our group works on the variable star research within the international campaign "Inter-Longitude Astronomy" (ILA) based on temporarily working groups in collaboration with Poland, Slovakia, Korea, USA and other countries. A recent self-review on highlights was published in 2017. Our group continues the scientific school of Prof. Vladymir P. Tsesevich (1907 - 1983). Another project we participate is "AstroInformatics". The unprecedented photo-polarimetric monitoring of a group of AM Her - type magnetic cataclysmic variable stars was carried out since 1989 (photometry in our group - since 1978). A photometric monitoring of the intermediate polars (MU Cam, V1343 Her, V2306 Cyg et al.) was continued to study rotational evolution of magnetic white dwarfs. The super-low luminosity state was discovered in the outbursting intermediate polar = magnetic dwarf nova DO Dra. Previously typical low state was some times interrupted by outbursts, which are narrower than usual dwarf nova outbursts. Once there were detected TPO - "Transient Periodic Oscillations". The orbital and quasi-periodic variability was recently studied. Such super-low states are characteristic for nova-like variables (e.g. MV Lyr, TT Ari) or intermediate polars, but unusual for the dwarf novae. The electronic "Catalogue of Characteristics and Atlas of the Light Curves of Newly-Discovered Eclipsing Binary Stars" was compiled and is being prepared for publication. The software NAV ("New Algol Variable") with specially developed algorithms was used. It allows to determine the begin and end of the eclipses even in EB and EW - type stars, whereas the current classification (GCVS, VSX) claims that the begin and end of eclipses only in the EA - type objects. The further improvements of the NAV algorithm were comparatively studied. The "Wall-Supported Polynomial" (WSP) algoritms were implemented in the software MAVKA for statistically optimal modeling of flat eclipses and exoplanet transitions. MAVKA was used for studies of effects of the mass transfer and presence of the third components in close binary stellar systems and analysis of the poorly studied eclipsing binary 2MASS J20355082+5242136. Atlas of the Light Curves and Phase Plane Portraits of Selected Long-Period Variables was compiled.

Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs

DOE PAGES

Chipman, Hugh A.; Hamada, Michael S.

2016-06-02

Regular two-level fractional factorial designs have complete aliasing in which the associated columns of multiple effects are identical. Here, we show how Bayesian variable selection can be used to analyze experiments that use such designs. In addition to sparsity and hierarchy, Bayesian variable selection naturally incorporates heredity . This prior information is used to identify the most likely combinations of active terms. We also demonstrate the method on simulated and real experiments.

Variable Selection in Logistic Regression.

DTIC Science & Technology

1987-06-01

23 %. AUTIOR(.) S. CONTRACT OR GRANT NUMBE Rf.i %Z. D. Bai, P. R. Krishnaiah and . C. Zhao F49620-85- C-0008 " PERFORMING ORGANIZATION NAME AND AOORESS...d I7 IOK-TK- d 7 -I0 7’ VARIABLE SELECTION IN LOGISTIC REGRESSION Z. D. Bai, P. R. Krishnaiah and L. C. Zhao Center for Multivariate Analysis...University of Pittsburgh Center for Multivariate Analysis University of Pittsburgh Y !I VARIABLE SELECTION IN LOGISTIC REGRESSION Z- 0. Bai, P. R. Krishnaiah

Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs

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

Chipman, Hugh A.; Hamada, Michael S.

Regular two-level fractional factorial designs have complete aliasing in which the associated columns of multiple effects are identical. Here, we show how Bayesian variable selection can be used to analyze experiments that use such designs. In addition to sparsity and hierarchy, Bayesian variable selection naturally incorporates heredity . This prior information is used to identify the most likely combinations of active terms. We also demonstrate the method on simulated and real experiments.

Variable selection under multiple imputation using the bootstrap in a prognostic study

PubMed Central

Heymans, Martijn W; van Buuren, Stef; Knol, Dirk L; van Mechelen, Willem; de Vet, Henrica CW

2007-01-01

Background Missing data is a challenging problem in many prognostic studies. Multiple imputation (MI) accounts for imputation uncertainty that allows for adequate statistical testing. We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection. Method In our prospective cohort study we merged data from three different randomized controlled trials (RCTs) to assess prognostic variables for chronicity of low back pain. Among the outcome and prognostic variables data were missing in the range of 0 and 48.1%. We used four methods to investigate the influence of respectively sampling and imputation variation: MI only, bootstrap only, and two methods that combine MI and bootstrapping. Variables were selected based on the inclusion frequency of each prognostic variable, i.e. the proportion of times that the variable appeared in the model. The discriminative and calibrative abilities of prognostic models developed by the four methods were assessed at different inclusion levels. Results We found that the effect of imputation variation on the inclusion frequency was larger than the effect of sampling variation. When MI and bootstrapping were combined at the range of 0% (full model) to 90% of variable selection, bootstrap corrected c-index values of 0.70 to 0.71 and slope values of 0.64 to 0.86 were found. Conclusion We recommend to account for both imputation and sampling variation in sets of missing data. The new procedure of combining MI with bootstrapping for variable selection, results in multivariable prognostic models with good performance and is therefore attractive to apply on data sets with missing values. PMID:17629912

Maintenance of Genetic Variability under Strong Stabilizing Selection: A Two-Locus Model

PubMed Central

Gavrilets, S.; Hastings, A.

1993-01-01

We study a two locus model with additive contributions to the phenotype to explore the relationship between stabilizing selection and recombination. We show that if the double heterozygote has the optimum phenotype and the contributions of the loci to the trait are different, then any symmetric stabilizing selection fitness function can maintain genetic variability provided selection is sufficiently strong relative to linkage. We present results of a detailed analysis of the quadratic fitness function which show that selection need not be extremely strong relative to recombination for the polymorphic equilibria to be stable. At these polymorphic equilibria the mean value of the trait, in general, is not equal to the optimum phenotype, there exists a large level of negative linkage disequilibrium which ``hides'' additive genetic variance, and different equilibria can be stable simultaneously. We analyze dependence of different characteristics of these equilibria on the location of optimum phenotype, on the difference in allelic effect, and on the strength of selection relative to recombination. Our overall result that stabilizing selection does not necessarily eliminate genetic variability is compatible with some experimental results where the lines subject to strong stabilizing selection did not have significant reductions in genetic variability. PMID:8514145

Do bioclimate variables improve performance of climate envelope models?

USGS Publications Warehouse

Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

2012-01-01

Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

Bayesian inference for the genetic control of water deficit tolerance in spring wheat by stochastic search variable selection.

PubMed

Safari, Parviz; Danyali, Syyedeh Fatemeh; Rahimi, Mehdi

2018-06-02

Drought is the main abiotic stress seriously influencing wheat production. Information about the inheritance of drought tolerance is necessary to determine the most appropriate strategy to develop tolerant cultivars and populations. In this study, generation means analysis to identify the genetic effects controlling grain yield inheritance in water deficit and normal conditions was considered as a model selection problem in a Bayesian framework. Stochastic search variable selection (SSVS) was applied to identify the most important genetic effects and the best fitted models using different generations obtained from two crosses applying two water regimes in two growing seasons. The SSVS is used to evaluate the effect of each variable on the dependent variable via posterior variable inclusion probabilities. The model with the highest posterior probability is selected as the best model. In this study, the grain yield was controlled by the main effects (additive and non-additive effects) and epistatic. The results demonstrate that breeding methods such as recurrent selection and subsequent pedigree method and hybrid production can be useful to improve grain yield.

Theorems and application of local activity of CNN with five state variables and one port.

PubMed

Xiong, Gang; Dong, Xisong; Xie, Li; Yang, Thomas

2012-01-01

Coupled nonlinear dynamical systems have been widely studied recently. However, the dynamical properties of these systems are difficult to deal with. The local activity of cellular neural network (CNN) has provided a powerful tool for studying the emergence of complex patterns in a homogeneous lattice, which is composed of coupled cells. In this paper, the analytical criteria for the local activity in reaction-diffusion CNN with five state variables and one port are presented, which consists of four theorems, including a serial of inequalities involving CNN parameters. These theorems can be used for calculating the bifurcation diagram to determine or analyze the emergence of complex dynamic patterns, such as chaos. As a case study, a reaction-diffusion CNN of hepatitis B Virus (HBV) mutation-selection model is analyzed and simulated, the bifurcation diagram is calculated. Using the diagram, numerical simulations of this CNN model provide reasonable explanations of complex mutant phenomena during therapy. Therefore, it is demonstrated that the local activity of CNN provides a practical tool for the complex dynamics study of some coupled nonlinear systems.

Safety Early Warning Research for Highway Construction Based on Case-Based Reasoning and Variable Fuzzy Sets

PubMed Central

Liu, Yan; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established. PMID:24191134

Safety early warning research for highway construction based on case-based reasoning and variable fuzzy sets.

PubMed

Liu, Yan; Yi, Ting-Hua; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

A Neuron-Based Screening Platform for Optimizing Genetically-Encoded Calcium Indicators

PubMed Central

Schreiter, Eric R.; Hasseman, Jeremy P.; Tsegaye, Getahun; Fosque, Benjamin F.; Behnam, Reza; Shields, Brenda C.; Ramirez, Melissa; Kimmel, Bruce E.; Kerr, Rex A.; Jayaraman, Vivek; Looger, Loren L.; Svoboda, Karel; Kim, Douglas S.

2013-01-01

Fluorescent protein-based sensors for detecting neuronal activity have been developed largely based on non-neuronal screening systems. However, the dynamics of neuronal state variables (e.g., voltage, calcium, etc.) are typically very rapid compared to those of non-excitable cells. We developed an electrical stimulation and fluorescence imaging platform based on dissociated rat primary neuronal cultures. We describe its use in testing genetically-encoded calcium indicators (GECIs). Efficient neuronal GECI expression was achieved using lentiviruses containing a neuronal-selective gene promoter. Action potentials (APs) and thus neuronal calcium levels were quantitatively controlled by electrical field stimulation, and fluorescence images were recorded. Images were segmented to extract fluorescence signals corresponding to individual GECI-expressing neurons, which improved sensitivity over full-field measurements. We demonstrate the superiority of screening GECIs in neurons compared with solution measurements. Neuronal screening was useful for efficient identification of variants with both improved response kinetics and high signal amplitudes. This platform can be used to screen many types of sensors with cellular resolution under realistic conditions where neuronal state variables are in relevant ranges with respect to timing and amplitude. PMID:24155972

Evaluating the underlying factors behind variable rate debt.

PubMed

McCue, Michael J; Kim, Tae Hyun Tanny

2007-01-01

Recent trends show a greater usage of variable rate debt among health care bond issues. In 2004, 63.4% of the total health care bonds issued were variable rate compared with 30.6% in 1995 (Fitch Ratings, 2005). The purpose of this study is to gain a better understanding of the underlying factors, credit spread, issue characteristics, and issuer factors behind why hospitals and health system borrowers select variable rate debt compared with fixed rate debt. From 2000 to 2004, this study sampled 230 newly issued tax-exempt bonds issued by acute care hospitals and health care systems that included both variable and fixed rate debt issues. Using a logistic regression model, hospitals with variable rate debt issues were assigned a value of 1, whereas hospitals with fixed rate debt issues were assigned a value of 0. This study found a positive association between bond insurance and variable rate debt and a negative association between callable feature and variable rate debt. Facilities located in certificate-of-need states that possessed higher case mix acuity, earned higher profit margins, generated higher debt service coverage, and held less debt were more likely to issue variable rate debt. Overall, hospital managers and board members of hospitals possessing a strong financial performance have an interest in utilizing variable rate debt to lower their cost of capital. In addition, this outcome may also reflect that investment bankers are doing a better job in educating senior hospital management about the interest rate savings benefit of variable rate compared with fixed rate debt.

Shared Decision Making and Other Variables as Correlates of Satisfaction with Health Care Decisions in a United States National Survey

PubMed Central

Wills, Celia E.; Holloman, Christopher; Olson, Jacklyn; Hechmer, Catherine; Miller, Carla K.; Duchemin, Anne-Marie

2012-01-01

Objective The purpose of this study was to examine the relationship between shared decision-making (SDM) and satisfaction with decision (SWD) within a larger survey of patient decision-making in health care consultations. Methods A randomly selected age-proportionate national sample of adults (aged 21–70 years) stratified on race, ethnicity, and gender (N = 488) was recruited from a health research volunteer registry and completed an online survey with reference to a recent health consultation. Measures included the Shared Decision Making-9 questionnaire (SDM-Q-9), Satisfaction With Decision (SWD) scale, sociodemographic, health, and other standardized decision-making measures. Forward selection weighted multiple regression analysis was used to model correlates of SWD. Results After controlling for sociodemographic variables, SDM-Q-9 total score was associated with SWD, adjusted R2 = .368, p < .001. Three of nine SDM-Q-9 items accounted for significant proportions of variance in SWD. Conclusion SDM was positively associated with SWD and was strongest for three areas of SDM: patients being helped in a health care consultation with understanding information, with treatment preference elicitation, and with weighing options thoroughly. Practice Implications By identifying variables such as SDM that are associated with SWD, health care interventions can better target modifiable factors to enhance satisfaction and other outcomes. PMID:22410642

Research article: Watershed management councils and scientific models: Using diffusion literature to explain adoption

USGS Publications Warehouse

King, M.D.; Burkardt, N.; Clark, B.T.

2006-01-01

Recent literature on the diffusion of innovations concentrates either specifically on public adoption of policy, where social or environmental conditions are the dependent variables for adoption, or on private adoption of an innovation, where emphasis is placed on the characteristics of the innovation itself. This article uses both the policy diffusion literature and the diffusion of innovation literature to assess watershed management councils' decisions to adopt, or not adopt, scientific models. Watershed management councils are a relevant case study because they possess both public and private attributes. We report on a survey of councils in the United States that was conducted to determine the criteria used when selecting scientific models for studying watershed conditions. We found that specific variables from each body of literature play a role in explaining the choice to adopt scientific models by these quasi-public organizations. The diffusion of innovation literature contributes to an understanding of how organizations select models by confirming the importance of a model's ability to provide better data. Variables from the policy diffusion literature showed that watershed management councils that employ consultants are more likely to use scientific models. We found a gap between those who create scientific models and those who use these models. We recommend shrinking this gap through more communication between these actors and advancing the need for developers to provide more technical assistance.

Shared decision making and other variables as correlates of satisfaction with health care decisions in a United States national survey.

PubMed

Glass, Katherine Elizabeth; Wills, Celia E; Holloman, Christopher; Olson, Jacklyn; Hechmer, Catherine; Miller, Carla K; Duchemin, Anne-Marie

2012-07-01

The purpose of this study was to examine the relationship between shared decision-making (SDM) and satisfaction with decision (SWD) within a larger survey of patient decision-making in health care consultations. A randomly selected age-proportionate national sample of adults (aged 21-70 years) stratified on race, ethnicity, and gender (N=488) was recruited from a health research volunteer registry and completed an online survey with reference to a recent health consultation. Measures included the shared decision making-9 questionnaire (SDM-Q-9), Satisfaction With Decision (SWD) scale, sociodemographic, health, and other standardized decision-making measures. Forward selection weighted multiple regression analysis was used to model correlates of SWD. After controlling for sociodemographic variables, SDM-Q-9 total score was associated with SWD, adjusted R(2)=.368, p<.001. Three of nine SDM-Q-9 items accounted for significant proportions of variance in SWD. SDM was positively associated with SWD and was strongest for three areas of SDM: patients being helped in a health care consultation with understanding information, with treatment preference elicitation, and with weighing options thoroughly. By identifying variables such as SDM that are associated with SWD, health care interventions can better target modifiable factors to enhance satisfaction and other outcomes. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Spatial variability in acoustic backscatter as an indicator of tissue homogenate production in pulsed cavitational ultrasound therapy.

PubMed

Parsons, Jessica E; Cain, Charles A; Fowlkes, J Brian

2007-03-01

Spatial variability in acoustic backscatter is investigated as a potential feedback metric for assessment of lesion morphology during cavitation-mediated mechanical tissue disruption ("histotripsy"). A 750-kHz annular array was aligned confocally with a 4.5 MHz passive backscatter receiver during ex vivo insonation of porcine myocardium. Various exposure conditions were used to elicit a range of damage morphologies and backscatter characteristics [pulse duration = 14 micros, pulse repetition frequency (PRF) = 0.07-3.1 kHz, average I(SPPA) = 22-44 kW/cm2]. Variability in backscatter spatial localization was quantified by tracking the lag required to achieve peak correlation between sequential RF A-lines received. Mean spatial variability was observed to be significantly higher when damage morphology consisted of mechanically disrupted tissue homogenate versus mechanically intact coagulation necrosis (2.35 +/- 1.59 mm versus 0.067 +/- 0.054 mm, p < 0.025). Statistics from these variability distributions were used as the basis for selecting a threshold variability level to identify the onset of homogenate formation via an abrupt, sustained increase in spatially dynamic backscatter activity. Specific indices indicative of the state of the homogenization process were quantified as a function of acoustic input conditions. The prevalence of backscatter spatial variability was observed to scale with the amount of homogenate produced for various PRFs and acoustic intensities.

Body temperature variability (Part 1): a review of the history of body temperature and its variability due to site selection, biological rhythms, fitness, and aging.

PubMed

Kelly, Greg

2006-12-01

Body temperature is a complex, non-linear data point, subject to many sources of internal and external variation. While these sources of variation significantly complicate interpretation of temperature data, disregarding knowledge in favor of oversimplifying complex issues would represent a significant departure from practicing evidence-based medicine. Part 1 of this review outlines the historical work of Wunderlich on temperature and the origins of the concept that a healthy normal temperature is 98.6 degrees F (37.0 degrees C). Wunderlich's findings and methodology are reviewed and his results are contrasted with findings from modern clinical thermometry. Endogenous sources of temperature variability, including variations caused by site of measurement, circadian, menstrual, and annual biological rhythms, fitness, and aging are discussed. Part 2 will review the effects of exogenous masking agents - external factors in the environment, diet, or lifestyle that can influence body temperature, as well as temperature findings in disease states.

An entropy-variables-based formulation of residual distribution schemes for non-equilibrium flows

NASA Astrophysics Data System (ADS)

Garicano-Mena, Jesús; Lani, Andrea; Degrez, Gérard

2018-06-01

In this paper we present an extension of Residual Distribution techniques for the simulation of compressible flows in non-equilibrium conditions. The latter are modeled by means of a state-of-the-art multi-species and two-temperature model. An entropy-based variable transformation that symmetrizes the projected advective Jacobian for such a thermophysical model is introduced. Moreover, the transformed advection Jacobian matrix presents a block diagonal structure, with mass-species and electronic-vibrational energy being completely decoupled from the momentum and total energy sub-system. The advantageous structure of the transformed advective Jacobian can be exploited by contour-integration-based Residual Distribution techniques: established schemes that operate on dense matrices can be substituted by the same scheme operating on the momentum-energy subsystem matrix and repeated application of scalar scheme to the mass-species and electronic-vibrational energy terms. Finally, the performance gain of the symmetrizing-variables formulation is quantified on a selection of representative testcases, ranging from subsonic to hypersonic, in inviscid or viscous conditions.

The Estrada Real project and endemic diseases: the case of schistosomiasis, geoprocessing and tourism.

PubMed

Carvalho, Omar S; Scholte, Ronaldo G C; Guimarães, Ricardo J P S; Freitas, Corina C; Drummond, Sandra C; Amaral, Ronaldo S; Dutra, Luciano V; Oliveira, Guilherme; Massara, Cristiano L; Enk, Martin J

2010-07-01

Geographical Information System (GIS) is a tool that has recently been applied to better understand spatial disease distributions. Using meteorological, social, sanitation, mollusc distribution data and remote sensing variables, this study aimed to further develop the GIS technology by creating a model for the spatial distribution of schistosomiasis and to apply this model to an area with rural tourism in the Brazilian state of Minas Gerais (MG). The Estrada Real, covering about 1,400 km, is the largest and most important Brazilian tourism project, involving 163 cities in MG with different schistosomiasis prevalence rates. The model with three variables showed a R(2) = 0.34, with a standard deviation of risk estimated adequate for public health needs. The main variables selected for modelling were summer vegetation, summer minimal temperature and winter minimal temperature. The results confirmed the importance of Remote Sensing data and the valuable contribution of GIS in identifying priority areas for intervention in tourism regions which are endemic to schistosomiasis.

Selection of a Geostatistical Method to Interpolate Soil Properties of the State Crop Testing Fields using Attributes of a Digital Terrain Model

NASA Astrophysics Data System (ADS)

Sahabiev, I. A.; Ryazanov, S. S.; Kolcova, T. G.; Grigoryan, B. R.

2018-03-01

The three most common techniques to interpolate soil properties at a field scale—ordinary kriging (OK), regression kriging with multiple linear regression drift model (RK + MLR), and regression kriging with principal component regression drift model (RK + PCR)—were examined. The results of the performed study were compiled into an algorithm of choosing the most appropriate soil mapping technique. Relief attributes were used as the auxiliary variables. When spatial dependence of a target variable was strong, the OK method showed more accurate interpolation results, and the inclusion of the auxiliary data resulted in an insignificant improvement in prediction accuracy. According to the algorithm, the RK + PCR method effectively eliminates multicollinearity of explanatory variables. However, if the number of predictors is less than ten, the probability of multicollinearity is reduced, and application of the PCR becomes irrational. In that case, the multiple linear regression should be used instead.

Apparatus and method for microwave processing of materials

DOEpatents

Johnson, A.C.; Lauf, R.J.; Bible, D.W.; Markunas, R.J.

1996-05-28

Disclosed is a variable frequency microwave heating apparatus designed to allow modulation of the frequency of the microwaves introduced into a furnace cavity for testing or other selected applications. The variable frequency heating apparatus is used in the method of the present invention to monitor the resonant processing frequency within the furnace cavity depending upon the material, including the state thereof, from which the workpiece is fabricated. The variable frequency microwave heating apparatus includes a microwave signal generator and a high-power microwave amplifier or a microwave voltage-controlled oscillator. A power supply is provided for operation of the high-power microwave oscillator or microwave amplifier. A directional coupler is provided for detecting the direction and amplitude of signals incident upon and reflected from the microwave cavity. A first power meter is provided for measuring the power delivered to the microwave furnace. A second power meter detects the magnitude of reflected power. Reflected power is dissipated in the reflected power load. 10 figs.

Long term variability of B supergiant winds

NASA Technical Reports Server (NTRS)

Massa, Derck L.

1995-01-01

The object of this observing proposal was to sample wind variability in B supergiants on a daily basis over a period of several days in order to determine the time scale with which density variability occurs in their winds. Three stars were selected for this project: 69 Cyg (B0 Ib), HD 164402 (B0 Ib), and HD 47240 (B1 Ib). Three grey scale representations of the Si IV lambda lambda 1400 doublet in each star are attached. In these figures, time (in days) increases upward, and the wavelength (in terms of velocity relative to the rest wavelength of the violet component of the doublet) is the abscissa. The spectra are normalized by a minimum absorption (maximum flux) template, so that all changes appear as absorptions. As a result of these observations, we can now state with some certainty that typical B supergiants develop significant wind inhomogeneities with recurrence times of a few days, and that some of these events show signs of strong temporal coherence.

A Sustained Dietary Change Increases Epigenetic Variation in Isogenic Mice

PubMed Central

Cowley, Mark J.; Preiss, Thomas; Martin, David I. K.; Suter, Catherine M.

2011-01-01

Epigenetic changes can be induced by adverse environmental exposures, such as nutritional imbalance, but little is known about the nature or extent of these changes. Here we have explored the epigenomic effects of a sustained nutritional change, excess dietary methyl donors, by assessing genomic CpG methylation patterns in isogenic mice exposed for one or six generations. We find stochastic variation in methylation levels at many loci; exposure to methyl donors increases the magnitude of this variation and the number of variable loci. Several gene ontology categories are significantly overrepresented in genes proximal to these methylation-variable loci, suggesting that certain pathways are susceptible to environmental influence on their epigenetic states. Long-term exposure to the diet (six generations) results in a larger number of loci exhibiting epigenetic variability, suggesting that some of the induced changes are heritable. This finding presents the possibility that epigenetic variation within populations can be induced by environmental change, providing a vehicle for disease predisposition and possibly a substrate for natural selection. PMID:21541011

Projecting climate effects on birds and reptiles of the Southwestern United States

USGS Publications Warehouse

van Riper, Charles; Hatten, James R.; Giermakowski, J. Tomasz; Mattson, David; Holmes, Jennifer A.; Johnson, Matthew J.; Nowak, Erika M.; Ironside, Kirsten; Peters, Michael; Heinrich, Paul; Cole, K.L.; Truettner, C.; Schwalbe, Cecil R.

2014-01-01

We modeled the current and future breeding ranges of seven bird and five reptile species in the Southwestern United States with sets of landscape, biotic (plant), and climatic global circulation model (GCM) variables. For modeling purposes, we used PRISM data to characterize the climate of the Western United States between 1980 and 2009 (baseline for birds) and between 1940 and 2009 (baseline for reptiles). In contrast, we used a pre-selected set of GCMs that are known to be good predictors of southwestern climate (five individual and one ensemble GCM), for the A1B emission scenario, to characterize future climatic conditions in three time periods (2010–39; 2040–69; and, 2070–99). Our modeling approach relied on conceptual models for each target species to inform selection of candidate explanatory variables and to interpret the ecological meaning of developed probabilistic distribution models. We employed logistic regression and maximum entropy modeling techniques to create a set of probabilistic models for each target species. We considered climatic, landscape, and plant variables when developing and testing our probabilistic models. Climatic variables included the maximum and minimum mean monthly and seasonal temperature and precipitation for three time periods. Landscape features included terrain ruggedness and insolation. We also considered plant species distributions as candidate explanatory variables where prior ecological knowledge implicated a strong association between a plant and animal species. Projected changes in range varied widely among species, from major losses to major gains. Breeding bird ranges exhibited greater expansions and contractions than did reptile species. We project range losses for Williamson’s sapsucker and pygmy nuthatch of a magnitude that could move these two species close to extinction within the next century. Although both species currently have a relatively limited distribution, they can be locally common, and neither are presently considered candidates for prospective endangerment. We project range losses of over 40 percent, from its current extent of occurrence, for the plateau striped whiptail, Arizona black rattlesnake, and common lesser earless lizard. Currently, these reptile species are thought to be common or at least locally abundant throughout their ranges. The total contribution of plants in each distribution model was very small, but models that contained at least one plant always outperformed models with only physical variables (climatic or landscape). The magnitude of change in projected range increased further into the future, especially when a plant was in the model. Among bird species, those that had the strongest association with a landscape feature during the breeding season, such as terrain ruggedness and insolation, exhibited the smallest contractions in projected breeding range in the future. In contrast, bird species that had weak associations with landscape features, but strong climatic associations, suffered the greatest breeding range contractions. Thus, landscape effects appeared to buffer some of the negative effects of climate change for some species. Among bird species, magnitude of change in projected breeding range was positively related to the annual average temperature of their baseline distribution, thus species with the warmest breeding ranges exhibited the greatest changes in future breeding ranges. This pattern was not evident for reptiles, but might exist if additional species were included in the model. Our results provide managers with a series of projected range maps that will enable scientists, concerned citizens, and wildlife managers to identify what the potential effects of climate change will be on bird and reptile distributions in the Western United States. We hope that our results can be used in proactive ways to mitigate some of the potential effects of climate change on selected species.

Jury Selection in Child Sex Abuse Trials: A Case Analysis

ERIC Educational Resources Information Center

Cramer, Robert J.; Adams, Desiree D.; Brodsky, Stanley L.

2009-01-01

Child sex abuse cases have been the target of considerable psycho-legal research. The present paper offers an analysis of psychological constructs for jury selection in child sex abuse cases from the defense perspective. The authors specifically delineate general and case-specific jury selection variables. General variables include…

The Effects of Variability and Risk in Selection Utility Analysis: An Empirical Comparison.

ERIC Educational Resources Information Center

Rich, Joseph R.; Boudreau, John W.

1987-01-01

Investigated utility estimate variability for the selection utility of using the Programmer Aptitude Test to select computer programmers. Comparison of Monte Carlo results to other risk assessment approaches (sensitivity analysis, break-even analysis, algebraic derivation of the distribtion) suggests that distribution information provided by Monte…

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

USGS Publications Warehouse

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 (<40%) between the two methods Despite these differences in variable sets (expert versus statistical), models had high performance metrics (>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 selection is a useful first step, especially when there is a need to model a large number of species or expert knowledge of the species is limited. Expert input can then be used to refine models that seem unrealistic or for species that experts believe are particularly sensitive to change. It also emphasizes the importance of using multiple models to reduce uncertainty and improve map outputs for conservation planning. Where outputs overlap or show the same direction of change there is greater certainty in the predictions. Areas of disagreement can be used for learning by asking why the models do not agree, and may highlight areas where additional on-the-ground data collection could improve the models.

Developing a spatial-statistical model and map of historical malaria prevalence in Botswana using a staged variable selection procedure

PubMed Central

Craig, Marlies H; Sharp, Brian L; Mabaso, Musawenkosi LH; Kleinschmidt, Immo

2007-01-01

Background Several malaria risk maps have been developed in recent years, many from the prevalence of infection data collated by the MARA (Mapping Malaria Risk in Africa) project, and using various environmental data sets as predictors. Variable selection is a major obstacle due to analytical problems caused by over-fitting, confounding and non-independence in the data. Testing and comparing every combination of explanatory variables in a Bayesian spatial framework remains unfeasible for most researchers. The aim of this study was to develop a malaria risk map using a systematic and practicable variable selection process for spatial analysis and mapping of historical malaria risk in Botswana. Results Of 50 potential explanatory variables from eight environmental data themes, 42 were significantly associated with malaria prevalence in univariate logistic regression and were ranked by the Akaike Information Criterion. Those correlated with higher-ranking relatives of the same environmental theme, were temporarily excluded. The remaining 14 candidates were ranked by selection frequency after running automated step-wise selection procedures on 1000 bootstrap samples drawn from the data. A non-spatial multiple-variable model was developed through step-wise inclusion in order of selection frequency. Previously excluded variables were then re-evaluated for inclusion, using further step-wise bootstrap procedures, resulting in the exclusion of another variable. Finally a Bayesian geo-statistical model using Markov Chain Monte Carlo simulation was fitted to the data, resulting in a final model of three predictor variables, namely summer rainfall, mean annual temperature and altitude. Each was independently and significantly associated with malaria prevalence after allowing for spatial correlation. This model was used to predict malaria prevalence at unobserved locations, producing a smooth risk map for the whole country. Conclusion We have produced a highly plausible and parsimonious model of historical malaria risk for Botswana from point-referenced data from a 1961/2 prevalence survey of malaria infection in 1–14 year old children. After starting with a list of 50 potential variables we ended with three highly plausible predictors, by applying a systematic and repeatable staged variable selection procedure that included a spatial analysis, which has application for other environmentally determined infectious diseases. All this was accomplished using general-purpose statistical software. PMID:17892584

A method for simplifying the analysis of traffic accidents injury severity on two-lane highways using Bayesian networks.

PubMed

Mujalli, Randa Oqab; de Oña, Juan

2011-10-01

This study describes a method for reducing the number of variables frequently considered in modeling the severity of traffic accidents. The method's efficiency is assessed by constructing Bayesian networks (BN). It is based on a two stage selection process. Several variable selection algorithms, commonly used in data mining, are applied in order to select subsets of variables. BNs are built using the selected subsets and their performance is compared with the original BN (with all the variables) using five indicators. The BNs that improve the indicators' values are further analyzed for identifying the most significant variables (accident type, age, atmospheric factors, gender, lighting, number of injured, and occupant involved). A new BN is built using these variables, where the results of the indicators indicate, in most of the cases, a statistically significant improvement with respect to the original BN. It is possible to reduce the number of variables used to model traffic accidents injury severity through BNs without reducing the performance of the model. The study provides the safety analysts a methodology that could be used to minimize the number of variables used in order to determine efficiently the injury severity of traffic accidents without reducing the performance of the model. Copyright © 2011 Elsevier Ltd. All rights reserved.

Humidity: A review and primer on atmospheric moisture and human health.

PubMed

Davis, Robert E; McGregor, Glenn R; Enfield, Kyle B

2016-01-01

Research examining associations between weather and human health frequently includes the effects of atmospheric humidity. A large number of humidity variables have been developed for numerous purposes, but little guidance is available to health researchers regarding appropriate variable selection. We examine a suite of commonly used humidity variables and summarize both the medical and biometeorological literature on associations between humidity and human health. As an example of the importance of humidity variable selection, we correlate numerous hourly humidity variables to daily respiratory syncytial virus isolates in Singapore from 1992 to 1994. Most water-vapor mass based variables (specific humidity, absolute humidity, mixing ratio, dewpoint temperature, vapor pressure) exhibit comparable correlations. Variables that include a thermal component (relative humidity, dewpoint depression, saturation vapor pressure) exhibit strong diurnality and seasonality. Humidity variable selection must be dictated by the underlying research question. Despite being the most commonly used humidity variable, relative humidity should be used sparingly and avoided in cases when the proximity to saturation is not medically relevant. Care must be taken in averaging certain humidity variables daily or seasonally to avoid statistical biasing associated with variables that are inherently diurnal through their relationship to temperature. Copyright © 2015 Elsevier Inc. All rights reserved.

[Methodological design for the National Survey Violence Against Women in Mexico].

PubMed

Olaiz, Gustavo; Franco, Aurora; Palma, Oswaldo; Echarri, Carlos; Valdez, Rosario; Herrera, Cristina

2006-01-01

To describe the methodology, the research designs used, the estimation and sample selection, variable definitions, collection instruments, and operative design and analytical procedures for the National Survey Violence Against Women in Mexico. A complex (two-step) cross-sectional study was designed and the qualitative design was carried out using in-depth interviews and participant observation in health care units. We obtained for the quantitative study a total of 26 240 interviews in women users of health services and 2 636 questionnaires for health workers; the survey is representative of the 32 Mexican states. For the qualitative study 26 in-depth interviews were conducted with female users and 60 interviews with health workers in the States of Quintana Roo, Coahuila and the Federal District.

Prediction of Baseflow Index of Catchments using Machine Learning Algorithms

NASA Astrophysics Data System (ADS)

Yadav, B.; Hatfield, K.

2017-12-01

We present the results of eight machine learning techniques for predicting the baseflow index (BFI) of ungauged basins using a surrogate of catchment scale climate and physiographic data. The tested algorithms include ordinary least squares, ridge regression, least absolute shrinkage and selection operator (lasso), elasticnet, support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Our work seeks to identify the dominant controls of BFI that can be readily obtained from ancillary geospatial databases and remote sensing measurements, such that the developed techniques can be extended to ungauged catchments. More than 800 gauged catchments spanning the continental United States were selected to develop the general methodology. The BFI calculation was based on the baseflow separated from daily streamflow hydrograph using HYSEP filter. The surrogate catchment attributes were compiled from multiple sources including digital elevation model, soil, landuse, climate data, other publicly available ancillary and geospatial data. 80% catchments were used to train the ML algorithms, and the remaining 20% of the catchments were used as an independent test set to measure the generalization performance of fitted models. A k-fold cross-validation using exhaustive grid search was used to fit the hyperparameters of each model. Initial model development was based on 19 independent variables, but after variable selection and feature ranking, we generated revised sparse models of BFI prediction that are based on only six catchment attributes. These key predictive variables selected after the careful evaluation of bias-variance tradeoff include average catchment elevation, slope, fraction of sand, permeability, temperature, and precipitation. The most promising algorithms exceeding an accuracy score (r-square) of 0.7 on test data include support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Considering both the accuracy and the computational complexity of these algorithms, we identify the extremely randomized trees as the best performing algorithm for BFI prediction in ungauged basins.

An Investigation of Selected Readiness Variables As Predictors of Reading Achievement at Second Grade Level.

ERIC Educational Resources Information Center

Seals, Caryl Neman

This study was designed to determine the relationship of selected readiness variables to achievement in reading at the second grade level. The readiness variables were environment, mathematics, letters and sounds, aural comprehension, visual perception, auditory perception, vocabulary and concepts, word meaning, listening, matching, alphabet,…

Curve fitting and modeling with splines using statistical variable selection techniques

NASA Technical Reports Server (NTRS)

Smith, P. L.

1982-01-01

The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Fitting multidimensional splines using statistical variable selection techniques

NASA Technical Reports Server (NTRS)

Smith, P. L.

1982-01-01

This report demonstrates the successful application of statistical variable selection techniques to fit splines. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs using the B-spline basis were developed, and the one for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Detection of Nitrogen Content in Rubber Leaves Using Near-Infrared (NIR) Spectroscopy with Correlation-Based Successive Projections Algorithm (SPA).

PubMed

Tang, Rongnian; Chen, Xupeng; Li, Chuang

2018-05-01

Near-infrared spectroscopy is an efficient, low-cost technology that has potential as an accurate method in detecting the nitrogen content of natural rubber leaves. Successive projections algorithm (SPA) is a widely used variable selection method for multivariate calibration, which uses projection operations to select a variable subset with minimum multi-collinearity. However, due to the fluctuation of correlation between variables, high collinearity may still exist in non-adjacent variables of subset obtained by basic SPA. Based on analysis to the correlation matrix of the spectra data, this paper proposed a correlation-based SPA (CB-SPA) to apply the successive projections algorithm in regions with consistent correlation. The result shows that CB-SPA can select variable subsets with more valuable variables and less multi-collinearity. Meanwhile, models established by the CB-SPA subset outperform basic SPA subsets in predicting nitrogen content in terms of both cross-validation and external prediction. Moreover, CB-SPA is assured to be more efficient, for the time cost in its selection procedure is one-twelfth that of the basic SPA.

Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: STATSGO Soil Characteristics

USGS Publications Warehouse

Wieczorek, Michael; LaMotte, Andrew E.

2010-01-01

This tabular data set represents estimated soil variables compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The variables included are cation exchange capacity, percent calcium carbonate, slope, water-table depth, soil thickness, hydrologic soil group, soil erodibility (k-factor), permeability, average water capacity, bulk density, percent organic material, percent clay, percent sand, and percent silt. The source data set is the State Soil ( STATSGO ) Geographic Database (Wolock, 1997). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).

Second order sliding mode control for a quadrotor UAV.

PubMed

Zheng, En-Hui; Xiong, Jing-Jing; Luo, Ji-Liang

2014-07-01

A method based on second order sliding mode control (2-SMC) is proposed to design controllers for a small quadrotor UAV. For the switching sliding manifold design, the selection of the coefficients of the switching sliding manifold is in general a sophisticated issue because the coefficients are nonlinear. In this work, in order to perform the position and attitude tracking control of the quadrotor perfectly, the dynamical model of the quadrotor is divided into two subsystems, i.e., a fully actuated subsystem and an underactuated subsystem. For the former, a sliding manifold is defined by combining the position and velocity tracking errors of one state variable, i.e., the sliding manifold has two coefficients. For the latter, a sliding manifold is constructed via a linear combination of position and velocity tracking errors of two state variables, i.e., the sliding manifold has four coefficients. In order to further obtain the nonlinear coefficients of the sliding manifold, Hurwitz stability analysis is used to the solving process. In addition, the flight controllers are derived by using Lyapunov theory, which guarantees that all system state trajectories reach and stay on the sliding surfaces. Extensive simulation results are given to illustrate the effectiveness of the proposed control method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Predictors of self-reported negative mood following a depressive mood induction procedure across previously depressed, currently anxious, and control individuals.

PubMed

Scherrer, Martin C; Dobson, Keith S; Quigley, Leanne

2014-09-01

This study identified and examined a set of potential predictors of self-reported negative mood following a depressive mood induction procedure (MIP) in a sample of previously depressed, clinically anxious, and control participants. The examined predictor variables were selected on the basis of previous research and theories of depression, and included symptoms of depression and anxiety, negative and positive affect, negative and positive automatic thoughts, dysfunctional beliefs, rumination, self-concept, and occurrence and perceived unpleasantness of recent negative events. The sample consisted of 33 previously depressed, 22 currently anxious, and 26 non-clinical control participants, recruited from community sources. Participant group status was confirmed through structured diagnostic interviews. Participants completed the Velten negative self-statement MIP as well as self-report questionnaires of affective, cognitive, and psychosocial variables selected as potential predictors of mood change. Symptoms of anxiety were associated with increased self-reported negative mood shift following the MIP in previously depressed participants, but not clinically anxious or control participants. Increased occurrence of recent negative events was a marginally significant predictor of negative mood shift for the previously depressed participants only. None of the other examined variables was significant predictors of MIP response for any of the participant groups. These results identify factors that may increase susceptibility to negative mood states in previously depressed individuals, with implications for theory and prevention of relapse to depression. The findings also identify a number of affective, cognitive, and psychosocial variables that do not appear to influence mood change following a depressive MIP in previously depressed, currently anxious, and control individuals. Limitations of the study and directions for future research are discussed. Current anxiety symptomatology was a significant predictor and occurrence of recent negative events was a marginally significant predictor of greater negative mood shift following the depressive mood induction for previously depressed individuals. None of the examined variables predicted change in mood following the depressive mood induction for currently anxious or control individuals. These results suggest that anxiety symptoms and experience with negative events may increase risk for experiencing depressive mood states among individuals with a vulnerability to depression. The generalizability of the present results to individuals with comorbid depression and anxiety is limited. Future research employing appropriate statistical approaches for confirmatory research is needed to test and confirm the present results. © 2014 The British Psychological Society.

The relationship between vertical teaming in science and student achievement as reported in the Academic Excellence Indicator System (AEIS) at selected public schools in Bexar County, Texas

NASA Astrophysics Data System (ADS)

Arteaga, Veronica Hernandez

The purpose of this study was to examine the relationship between vertical teaming in science and student achievement. This study compared student achievement of campuses implementing vertical teaming with schools that do not practice vertical teaming. In addition, this study explored the relationship between selected demographic variables and vertical teaming using Grade 5 Science TAKS results in the Academic Excellence Indicator System (AEIS). Campus demographic variables such as economically disadvantaged, minority students, English language learners, student mobility, and experienced teachers were researched. A call-out yielded 168 responses. With the exclusion of the 12 campuses, a total of 156 participating campuses from 18 traditional school districts remained. Campuses employing vertical teaming were self-identified on the basis of having implemented the process for two or more years. The gain in percent mastered for Science TAKS scores from 2004 to 2007 was used as the Science TAKS score variable. Results indicated that there was no significant difference in student achievement in science for campuses practicing vertical teaming and campuses that did not. The two-way ANOVA was used to measure the relationship between the independent variables (vertical teaming and campus demographic variables) on the dependent variable (student achievement on Science TAKS). The results suggested that campuses having low percentages of economically disadvantaged students statistically gained more on the Science TAKS than campuses that have high percentages of economically disadvantaged students irrespective of vertical teaming practices. In addition, campuses that have low percentages of minority students statistically gained more on the Science TAKS than campuses that have high percentages of minority students despite vertical teaming participation. Recommendations include districts, state, and federal agencies providing campuses with a high percent of economically disadvantaged students with more resources and more flexibility in using those resources. Recommendations for further study included a replication of the study that takes into account the degree of implementation of vertical teaming.

Selection Criteria for Internal Medicine Residency Applicants and Professionalism Ratings During Internship

PubMed Central

Cullen, Michael W.; Reed, Darcy A.; Halvorsen, Andrew J.; Wittich, Christopher M.; Kreuziger, Lisa M. Baumann; Keddis, Mira T.; McDonald, Furman S.; Beckman, Thomas J.

2011-01-01

OBJECTIVE: To determine whether standardized admissions data in residents' Electronic Residency Application Service (ERAS) submissions were associated with multisource assessments of professionalism during internship. PARTICIPANTS AND METHODS: ERAS applications for all internal medicine interns (N=191) at Mayo Clinic entering training between July 1, 2005, and July 1, 2008, were reviewed by 6 raters. Extracted data included United States Medical Licensing Examination scores, medicine clerkship grades, class rank, Alpha Omega Alpha membership, advanced degrees, awards, volunteer activities, research experiences, first author publications, career choice, and red flags in performance evaluations. Medical school reputation was quantified using U.S. News & World Report rankings. Strength of comparative statements in recommendation letters (0 = no comparative statement, 1 = equal to peers, 2 = top 20%, 3 = top 10% or “best”) were also recorded. Validated multisource professionalism scores (5-point scales) were obtained for each intern. Associations between application variables and professionalism scores were examined using linear regression. RESULTS: The mean ± SD (minimum-maximum) professionalism score was 4.09±0.31 (2.13-4.56). In multivariate analysis, professionalism scores were positively associated with mean strength of comparative statements in recommendation letters (β=0.13; P=.002). No other associations between ERAS application variables and professionalism scores were found. CONCLUSION: Comparative statements in recommendation letters for internal medicine residency applicants were associated with professionalism scores during internship. Other variables traditionally examined when selecting residents were not associated with professionalism. These findings suggest that faculty physicians' direct observations, as reflected in letters of recommendation, are useful indicators of what constitutes a best student. Residency selection committees should scrutinize applicants' letters for strongly favorable comparative statements. PMID:21364111

GWASinlps: Nonlocal prior based iterative SNP selection tool for genome-wide association studies.

PubMed

Sanyal, Nilotpal; Lo, Min-Tzu; Kauppi, Karolina; Djurovic, Srdjan; Andreassen, Ole A; Johnson, Valen E; Chen, Chi-Hua

2018-06-19

Multiple marker analysis of the genome-wide association study (GWAS) data has gained ample attention in recent years. However, because of the ultra high-dimensionality of GWAS data, such analysis is challenging. Frequently used penalized regression methods often lead to large number of false positives, whereas Bayesian methods are computationally very expensive. Motivated to ameliorate these issues simultaneously, we consider the novel approach of using nonlocal priors in an iterative variable selection framework. We develop a variable selection method, named, iterative nonlocal prior based selection for GWAS, or GWASinlps, that combines, in an iterative variable selection framework, the computational efficiency of the screen-and-select approach based on some association learning and the parsimonious uncertainty quantification provided by the use of nonlocal priors. The hallmark of our method is the introduction of 'structured screen-and-select' strategy, that considers hierarchical screening, which is not only based on response-predictor associations, but also based on response-response associations, and concatenates variable selection within that hierarchy. Extensive simulation studies with SNPs having realistic linkage disequilibrium structures demonstrate the advantages of our computationally efficient method compared to several frequentist and Bayesian variable selection methods, in terms of true positive rate, false discovery rate, mean squared error, and effect size estimation error. Further, we provide empirical power analysis useful for study design. Finally, a real GWAS data application was considered with human height as phenotype. An R-package for implementing the GWASinlps method is available at https://cran.r-project.org/web/packages/GWASinlps/index.html. Supplementary data are available at Bioinformatics online.

Decision-support tools for Extreme Weather and Climate Events in the Northeast United States

NASA Astrophysics Data System (ADS)

Kumar, S.; Lowery, M.; Whelchel, A.

2013-12-01

Decision-support tools were assessed for the 2013 National Climate Assessment technical input document, "Climate Change in the Northeast, A Sourcebook". The assessment included tools designed to generate and deliver actionable information to assist states and highly populated urban and other communities in assessment of climate change vulnerability and risk, quantification of effects, and identification of adaptive strategies in the context of adaptation planning across inter-annual, seasonal and multi-decadal time scales. State-level adaptation planning in the Northeast has generally relied on qualitative vulnerability assessments by expert panels and stakeholders, although some states have undertaken initiatives to develop statewide databases to support vulnerability assessments by urban and local governments, and state agencies. The devastation caused by Superstorm Sandy in October 2012 has raised awareness of the potential for extreme weather events to unprecedented levels and created urgency for action, especially in coastal urban and suburban communities that experienced pronounced impacts - especially in New Jersey, New York and Connecticut. Planning approaches vary, but any adaptation and resiliency planning process must include the following: - Knowledge of the probable change in a climate variable (e.g., precipitation, temperature, sea-level rise) over time or that the climate variable will attain a certain threshold deemed to be significant; - Knowledge of intensity and frequency of climate hazards (past, current or future events or conditions with potential to cause harm) and their relationship with climate variables; - Assessment of climate vulnerabilities (sensitive resources, infrastructure or populations exposed to climate-related hazards); - Assessment of relative risks to vulnerable resources; - Identification and prioritization of adaptive strategies to address risks. Many organizations are developing decision-support tools to assist in the urban planning process by addressing some of these needs. In this paper we highlight the decision tools available today, discuss their application in selected case studies, and present a gap analysis with opportunities for innovation and future work.

Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleoclimate data

NASA Astrophysics Data System (ADS)

Henley, B. J.; Thyer, M. A.; Kuczera, G. A.

2012-12-01

A hierarchical framework for incorporating modes of climate variability into stochastic simulations of hydrological data is developed, termed the climate-informed multi-time scale stochastic (CIMSS) framework. To characterize long-term variability for the first level of the hierarchy, paleoclimate and instrumental data describing the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO) are analyzed. A new paleo IPO-PDO time series dating back 440 yrs is produced, combining seven IPO-PDO paleo sources using an objective smoothing procedure to fit low-pass filters to individual records. The paleo data analysis indicates that wet/dry IPO-PDO states have a broad range of run-lengths, with 90% between 3 and 33 yr and a mean of 15 yr. Model selection techniques were used to determine a suitable stochastic model to simulate these run-lengths. The Markov chain model, previously used to simulate oscillating wet/dry climate states, was found to underestimate the probability of wet/dry periods >5 yr, and was rejected in favor of a gamma distribution. For the second level of the hierarchy, a seasonal rainfall model is conditioned on the simulated IPO-PDO state. Application to two high-quality rainfall sites close to water supply reservoirs found that mean seasonal rainfall in the IPO-PDO dry state was 15%-28% lower than the wet state. The model was able to replicate observed statistics such as seasonal and multi-year accumulated rainfall distributions and interannual autocorrelations for the case study sites. In comparison, an annual lag-one autoregressive AR(1) model was unable to adequately capture the observed rainfall distribution within separate IPO-PDO states. Furthermore, analysis of the impact of the CIMSS framework on drought risk analysis found that short-term drought risks conditional on IPO/PDO state were considerably higher than the traditional AR(1) model.hort-term conditional water supply drought risks for the CIMSS and AR(1) models for the dry IPO-PDO scenario with a range of initial storage levels expressed as a proportion of the annual demand (yield).

Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective

NASA Astrophysics Data System (ADS)

Wen, Shaobo; An, Haizhong; Chen, Zhihua; Liu, Xueyong

2017-08-01

In traditional econometrics, a time series must be in a stationary sequence. However, it usually shows time-varying fluctuations, and it remains a challenge to execute a multiscale analysis of the data and discover the topological characteristics of conduction in different scales. Wavelet analysis and complex networks in physical statistics have special advantages in solving these problems. We select the exchange rate variable from the Chinese market and the commodity price index variable from the world market as the time series of our study. We explore the driving factors behind the behavior of the two markets and their topological characteristics in three steps. First, we use the Kalman filter to find the optimal estimation of the relationship between the two markets. Second, wavelet analysis is used to extract the scales of the relationship that are driven by different frequency wavelets. Meanwhile, we search for the actual economic variables corresponding to different frequency wavelets. Finally, a complex network is used to search for the transfer characteristics of the combination of states driven by different frequency wavelets. The results show that statistical physics have a unique advantage over traditional econometrics. The Chinese market has time-varying impacts on the world market: it has greater influence when the world economy is stable and less influence in times of turmoil. The process of forming the state combination is random. Transitions between state combinations have a clustering feature. Based on these characteristics, we can effectively reduce the information burden on investors and correctly respond to the government's policy mix.

Determination of interfacial states in solid heterostructures using a variable-energy positron beam

DOEpatents

Asoka kumar, Palakkal P. V.; Lynn, Kelvin G.

1993-01-01

A method and means is provided for characterizing interfacial electron states in solid heterostructures using a variable energy positron beam to probe the solid heterostructure. The method includes the steps of directing a positron beam having a selected energy level at a point on the solid heterostructure so that the positron beam penetrates into the solid heterostructure and causes positrons to collide with the electrons at an interface of the solid heterostructure. The number and energy of gamma rays emitted from the solid heterostructure as a result of the annihilation of positrons with electrons at the interface are detected. The data is quantified as a function of the Doppler broadening of the photopeak about the 511 keV line created by the annihilation of the positrons and electrons at the interface, preferably, as an S-parameter function; and a normalized S-parameter function of the data is obtained. The function of data obtained is compared with a corresponding function of the Doppler broadening of the annihilation photopeak about 511 keV for a positron beam having a second energy level directed at the same material making up a portion of the solid heterostructure. The comparison of these functions facilitates characterization of the interfacial states of electrons in the solid heterostructure at points corresponding to the penetration of positrons having the particular energy levels into the interface of the solid heterostructure. Accordingly, the invention provides a variable-energy non-destructive probe of solid heterostructures, such as SiO.sub.2 /Si, MOS or other semiconductor devices.

Determination of interfacial states in solid heterostructures using a variable-energy positron beam

DOEpatents

Asokakumar, P.P.V.; Lynn, K.G.

1993-04-06

A method and means is provided for characterizing interfacial electron states in solid heterostructures using a variable energy positron beam to probe the solid heterostructure. The method includes the steps of directing a positron beam having a selected energy level at a point on the solid heterostructure so that the positron beam penetrates into the solid heterostructure and causes positrons to collide with the electrons at an interface of the solid heterostructure. The number and energy of gamma rays emitted from the solid heterostructure as a result of the annihilation of positrons with electrons at the interface are detected. The data is quantified as a function of the Doppler broadening of the photopeak about the 511 keV line created by the annihilation of the positrons and electrons at the interface, preferably, as an S-parameter function; and a normalized S-parameter function of the data is obtained. The function of data obtained is compared with a corresponding function of the Doppler broadening of the annihilation photopeak about 511 keV for a positron beam having a second energy level directed at the same material making up a portion of the solid heterostructure. The comparison of these functions facilitates characterization of the interfacial states of electrons in the solid heterostructure at points corresponding to the penetration of positrons having the particular energy levels into the interface of the solid heterostructure. Accordingly, the invention provides a variable-energy non-destructive probe of solid heterostructures, such as SiO[sub 2]/Si, MOS or other semiconductor devices.

Fuzzy logic applied to prospecting for areas for installation of wood panel industries.

PubMed

Dos Santos, Alexandre Rosa; Paterlini, Ewerthon Mattos; Fiedler, Nilton Cesar; Ribeiro, Carlos Antonio Alvares Soares; Lorenzon, Alexandre Simões; Domingues, Getulio Fonseca; Marcatti, Gustavo Eduardo; de Castro, Nero Lemos Martins; Teixeira, Thaisa Ribeiro; Dos Santos, Gleissy Mary Amaral Dino Alves; Juvanhol, Ronie Silva; Branco, Elvis Ricardo Figueira; Mota, Pedro Henrique Santos; da Silva, Lilianne Gomes; Pirovani, Daiani Bernardo; de Jesus, Waldir Cintra; Santos, Ana Carolina de Albuquerque; Leite, Helio Garcia; Iwakiri, Setsuo

2017-05-15

Prospecting for suitable areas for forestry operations, where the objective is a reduction in production and transportation costs, as well as the maximization of profits and available resources, constitutes an optimization problem. However, fuzzy logic is an alternative method for solving this problem. In the context of prospecting for suitable areas for the installation of wood panel industries, we propose applying fuzzy logic analysis for simulating the planting of different species and eucalyptus hybrids in Espírito Santo State, Brazil. The necessary methodological steps for this study are as follows: a) agriclimatological zoning of different species and eucalyptus hybrids; b) the selection of the vector variables; c) the application of the Euclidean distance to the vector variables; d) the application of fuzzy logic to matrix variables of the Euclidean distance; and e) the application of overlap fuzzy logic to locate areas for installation of wood panel industries. Among all the species and hybrids, Corymbia citriodora showed the highest percentage values for the combined very good and good classes, with 8.60%, followed by Eucalyptus grandis with 8.52%, Eucalyptus urophylla with 8.35% and Urograndis with 8.34%. The fuzzy logic analysis afforded flexibility in prospecting for suitable areas for the installation of wood panel industries in the Espírito Santo State can bring great economic and social benefits to the local population with the generation of jobs, income, tax revenues and GDP increase for the State and municipalities involved. The proposed methodology can be adapted to other areas and agricultural crops. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Selective Review of Group Selection in High-Dimensional Models

PubMed Central

Huang, Jian; Breheny, Patrick; Ma, Shuangge

2013-01-01

Grouping structures arise naturally in many statistical modeling problems. Several methods have been proposed for variable selection that respect grouping structure in variables. Examples include the group LASSO and several concave group selection methods. In this article, we give a selective review of group selection concerning methodological developments, theoretical properties and computational algorithms. We pay particular attention to group selection methods involving concave penalties. We address both group selection and bi-level selection methods. We describe several applications of these methods in nonparametric additive models, semiparametric regression, seemingly unrelated regressions, genomic data analysis and genome wide association studies. We also highlight some issues that require further study. PMID:24174707

Left Atrial Appendage Closure for Stroke Prevention: Devices, Techniques, and Efficacy.

PubMed

Iskandar, Sandia; Vacek, James; Lavu, Madhav; Lakkireddy, Dhanunjaya

2016-05-01

Left atrial appendage closure can be performed either surgically or percutaneously. Surgical approaches include direct suture, excision and suture, stapling, and clipping. Percutaneous approaches include endocardial, epicardial, and hybrid endocardial-epicardial techniques. Left atrial appendage anatomy is highly variable and complex; therefore, preprocedural imaging is crucial to determine device selection and sizing, which contribute to procedural success and reduction of complications. Currently, the WATCHMAN is the only device that is approved for left atrial appendage closure in the United States. Copyright © 2016 Elsevier Inc. All rights reserved.

Security of coherent-state quantum cryptography in the presence of Gaussian noise

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

Heid, Matthias; Luetkenhaus, Norbert

2007-08-15

We investigate the security against collective attacks of a continuous variable quantum key distribution scheme in the asymptotic key limit for a realistic setting. The quantum channel connecting the two honest parties is assumed to be lossy and imposes Gaussian noise on the observed quadrature distributions. Secret key rates are given for direct and reverse reconciliation schemes including post-selection in the collective attack scenario. The effect of a nonideal error correction and two-way communication in the classical post-processing step is also taken into account.

Impact of petrophysical uncertainty on Bayesian hydrogeophysical inversion and model selection

NASA Astrophysics Data System (ADS)

Brunetti, Carlotta; Linde, Niklas

2018-01-01

Quantitative hydrogeophysical studies rely heavily on petrophysical relationships that link geophysical properties to hydrogeological properties and state variables. Coupled inversion studies are frequently based on the questionable assumption that these relationships are perfect (i.e., no scatter). Using synthetic examples and crosshole ground-penetrating radar (GPR) data from the South Oyster Bacterial Transport Site in Virginia, USA, we investigate the impact of spatially-correlated petrophysical uncertainty on inferred posterior porosity and hydraulic conductivity distributions and on Bayes factors used in Bayesian model selection. Our study shows that accounting for petrophysical uncertainty in the inversion (I) decreases bias of the inferred variance of hydrogeological subsurface properties, (II) provides more realistic uncertainty assessment and (III) reduces the overconfidence in the ability of geophysical data to falsify conceptual hydrogeological models.

Normalised subband adaptive filtering with extended adaptiveness on degree of subband filters

NASA Astrophysics Data System (ADS)

Samuyelu, Bommu; Rajesh Kumar, Pullakura

2017-12-01

This paper proposes an adaptive normalised subband adaptive filtering (NSAF) to accomplish the betterment of NSAF performance. In the proposed NSAF, an extended adaptiveness is introduced from its variants in two ways. In the first way, the step-size is set adaptive, and in the second way, the selection of subbands is set adaptive. Hence, the proposed NSAF is termed here as variable step-size-based NSAF with selected subbands (VS-SNSAF). Experimental investigations are carried out to demonstrate the performance (in terms of convergence) of the VS-SNSAF against the conventional NSAF and its state-of-the-art adaptive variants. The results report the superior performance of VS-SNSAF over the traditional NSAF and its variants. It is also proved for its stability, robustness against noise and substantial computing complexity.

Final-state QED multipole radiation in antenna parton showers

NASA Astrophysics Data System (ADS)

Kleiss, Ronald; Verheyen, Rob

2017-11-01

We present a formalism for a fully coherent QED parton shower. The complete multipole structure of photonic radiation is incorporated in a single branching kernel. The regular on-shell 2 → 3 kinematic picture is kept intact by dividing the radiative phase space into sectors, allowing for a definition of the ordering variable that is similar to QCD antenna showers. A modified version of the Sudakov veto algorithm is discussed that increases performance at the cost of the introduction of weighted events. Due to the absence of a soft singularity, the formalism for photon splitting is very similar to the QCD analogon of gluon splitting. However, since no color structure is available to guide the selection of a spectator, a weighted selection procedure from all available spectators is introduced.

Applications of Genomic Selection in Breeding Wheat for Rust Resistance.

PubMed

Ornella, Leonardo; González-Camacho, Juan Manuel; Dreisigacker, Susanne; Crossa, Jose

2017-01-01

There are a lot of methods developed to predict untested phenotypes in schemes commonly used in genomic selection (GS) breeding. The use of GS for predicting disease resistance has its own particularities: (a) most populations shows additivity in quantitative adult plant resistance (APR); (b) resistance needs effective combinations of major and minor genes; and (c) phenotype is commonly expressed in ordinal categorical traits, whereas most parametric applications assume that the response variable is continuous and normally distributed. Machine learning methods (MLM) can take advantage of examples (data) that capture characteristics of interest from an unknown underlying probability distribution (i.e., data-driven). We introduce some state-of-the-art MLM capable to predict rust resistance in wheat. We also present two parametric R packages for the reader to be able to compare.

Selecting the process variables for filament winding

NASA Technical Reports Server (NTRS)

Calius, E.; Springer, G. S.

1986-01-01

A model is described which can be used to determine the appropriate values of the process variables for filament winding cylinders. The process variables which can be selected by the model include the winding speed, fiber tension, initial resin degree of cure, and the temperatures applied during winding, curing, and post-curing. The effects of these process variables on the properties of the cylinder during and after manufacture are illustrated by a numerical example.

SVM-RFE based feature selection and Taguchi parameters optimization for multiclass SVM classifier.

PubMed

Huang, Mei-Ling; Hung, Yung-Hsiang; Lee, W M; Li, R K; Jiang, Bo-Ru

2014-01-01

Recently, support vector machine (SVM) has excellent performance on classification and prediction and is widely used on disease diagnosis or medical assistance. However, SVM only functions well on two-group classification problems. This study combines feature selection and SVM recursive feature elimination (SVM-RFE) to investigate the classification accuracy of multiclass problems for Dermatology and Zoo databases. Dermatology dataset contains 33 feature variables, 1 class variable, and 366 testing instances; and the Zoo dataset contains 16 feature variables, 1 class variable, and 101 testing instances. The feature variables in the two datasets were sorted in descending order by explanatory power, and different feature sets were selected by SVM-RFE to explore classification accuracy. Meanwhile, Taguchi method was jointly combined with SVM classifier in order to optimize parameters C and γ to increase classification accuracy for multiclass classification. The experimental results show that the classification accuracy can be more than 95% after SVM-RFE feature selection and Taguchi parameter optimization for Dermatology and Zoo databases.

SVM-RFE Based Feature Selection and Taguchi Parameters Optimization for Multiclass SVM Classifier

PubMed Central

Huang, Mei-Ling; Hung, Yung-Hsiang; Lee, W. M.; Li, R. K.; Jiang, Bo-Ru

2014-01-01

Recently, support vector machine (SVM) has excellent performance on classification and prediction and is widely used on disease diagnosis or medical assistance. However, SVM only functions well on two-group classification problems. This study combines feature selection and SVM recursive feature elimination (SVM-RFE) to investigate the classification accuracy of multiclass problems for Dermatology and Zoo databases. Dermatology dataset contains 33 feature variables, 1 class variable, and 366 testing instances; and the Zoo dataset contains 16 feature variables, 1 class variable, and 101 testing instances. The feature variables in the two datasets were sorted in descending order by explanatory power, and different feature sets were selected by SVM-RFE to explore classification accuracy. Meanwhile, Taguchi method was jointly combined with SVM classifier in order to optimize parameters C and γ to increase classification accuracy for multiclass classification. The experimental results show that the classification accuracy can be more than 95% after SVM-RFE feature selection and Taguchi parameter optimization for Dermatology and Zoo databases. PMID:25295306

IRAS variables as galactic structure tracers - Classification of the bright variables

NASA Technical Reports Server (NTRS)

Allen, L. E.; Kleinmann, S. G.; Weinberg, M. D.

1993-01-01

The characteristics of the 'bright infrared variables' (BIRVs), a sample consisting of the 300 brightest stars in the IRAS Point Source Catalog with IRAS variability index VAR of 98 or greater, are investigated with the purpose of establishing which of IRAS variables are AGB stars (e.g., oxygen-rich Miras and carbon stars, as was assumed by Weinberg (1992)). Results of the analysis of optical, infrared, and microwave spectroscopy of these stars indicate that, out of 88 stars in the BIRV sample identified with cataloged variables, 86 can be classified as Miras. Results of a similar analysis performed for a color-selected sample of stars, using the color limits employed by Habing (1988) to select AGB stars, showed that, out of 52 percent of classified stars, 38 percent are non-AGB stars, including H II regions, planetary nebulae, supergiants, and young stellar objects, indicating that studies using color-selected samples are subject to misinterpretation.

Superconducting fault current-limiter with variable shunt impedance

DOEpatents

Llambes, Juan Carlos H; Xiong, Xuming

2013-11-19

A superconducting fault current-limiter is provided, including a superconducting element configured to resistively or inductively limit a fault current, and one or more variable-impedance shunts electrically coupled in parallel with the superconducting element. The variable-impedance shunt(s) is configured to present a first impedance during a superconducting state of the superconducting element and a second impedance during a normal resistive state of the superconducting element. The superconducting element transitions from the superconducting state to the normal resistive state responsive to the fault current, and responsive thereto, the variable-impedance shunt(s) transitions from the first to the second impedance. The second impedance of the variable-impedance shunt(s) is a lower impedance than the first impedance, which facilitates current flow through the variable-impedance shunt(s) during a recovery transition of the superconducting element from the normal resistive state to the superconducting state, and thus, facilitates recovery of the superconducting element under load.

State of the art in marketing hospital foodservice departments.

PubMed

Pickens, C W; Shanklin, C W

1985-11-01

The purposes of this study were to identify the state of the art relative to the utilization of marketing techniques within hospital foodservice departments throughout the United States and to determine whether any relationships existed between the degree of utilization of marketing techniques and selected demographic characteristics of the foodservice administrators and/or operations. A validated questionnaire was mailed to 600 randomly selected hospital foodservice administrators requesting information related to marketing in their facilities. Forty-five percent of the questionnaires were returned and analyzed for frequency of response and significant relationship between variables. Chi-square was used for nominal data and Spearman rho for ranked data. Approximately 73% of the foodservice administrators stated that marketing was extremely important in the success of a hospital foodservice department. Respondents (79%) further indicated that marketing had become more important in their departments in the past 2 years. Departmental records, professional journals, foodservice suppliers, observation, and surveys were the sources most often used to obtain marketing data, a responsibility generally assumed by the foodservice director (86.2%). Merchandising, public relations, and word-of-mouth reputation were regarded as the most important aspects of marketing. Increased sales, participation, good will, departmental recognition, and employee satisfaction were used most frequently to evaluate the success of implemented marketing techniques. Marketing audits as a means of evaluating the success of marketing were used to a limited extent by the respondents.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

PubMed

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Ancestrality and evolution of trait syndromes in finches (Fringillidae).

PubMed

Ponge, Jean-François; Zuccon, Dario; Elias, Marianne; Pavoine, Sandrine; Henry, Pierre-Yves; Théry, Marc; Guilbert, Éric

2017-12-01

Species traits have been hypothesized by one of us (Ponge, 2013) to evolve in a correlated manner as species colonize stable, undisturbed habitats, shifting from "ancestral" to "derived" strategies. We predicted that generalism, r-selection, sexual monomorphism, and migration/gregariousness are the ancestral states (collectively called strategy A) and evolved correlatively toward specialism, K-selection, sexual dimorphism, and residence/territoriality as habitat stabilized (collectively called B strategy). We analyzed the correlated evolution of four syndromes, summarizing the covariation between 53 traits, respectively, involved in ecological specialization, r-K gradient, sexual selection, and dispersal/social behaviors in 81 species representative of Fringillidae, a bird family with available natural history information and that shows variability for all these traits. The ancestrality of strategy A was supported for three of the four syndromes, the ancestrality of generalism having a weaker support, except for the core group Carduelinae (69 species). It appeared that two different B-strategies evolved from the ancestral state A, both associated with highly predictable environments: one in poorly seasonal environments, called B1, with species living permanently in lowland tropics, with "slow pace of life" and weak sexual dimorphism, and one in highly seasonal environments, called B2, with species breeding out-of-the-tropics, migratory, with a "fast pace of life" and high sexual dimorphism.

Selection of Variables in Cluster Analysis: An Empirical Comparison of Eight Procedures

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

Eight different variable selection techniques for model-based and non-model-based clustering are evaluated across a wide range of cluster structures. It is shown that several methods have difficulties when non-informative variables (i.e., random noise) are included in the model. Furthermore, the distribution of the random noise greatly impacts the…

Physics of crypto-nonlocality

NASA Astrophysics Data System (ADS)

Navascués, Miguel

2014-02-01

In 2003, Leggett introduced his model of crypto-nonlocality based on considerations on the reality of photon polarization [A. J. Leggett, Found. Phys. 33, 1469 (2003), 10.1023/A:1026096313729]. In this paper, we prove that, contrary to hints in subsequent literature, crypto-nonlocality does not follow naturally from the postulate that polarization is a realistic variable. More explicitly, consider physical theories where (a) faster-than-light communication is impossible, (b) all physical photon states have a definite polarization, and (c) given two separate photons, if we measure one of them and post-select on the result, the measurement statistics of the remaining system correspond to a photon state. We show that the outcomes of any two-photon polarization experiment in these theories must follow the statistics generated by measuring a separable two-qubit quantum state. Consequently, in such experiments any instance of entanglement detection—and not necessarily a Leggett inequality violation—can be regarded as a refutation of this class of theories.

Influence of intrinsic decoherence on tripartite entanglement and bipartite fidelity of polar molecules in pendular states

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

Han, Jia-Xing; Hu, Yuan; Jin, Yu

An array of ultracold polar molecules trapped in an external electric field is regarded as a promising carrier of quantum information. Under the action of this field, molecules are compelled to undergo pendular oscillations by the Stark effect. Particular attention has been paid to the influence of intrinsic decoherence on the model of linear polar molecular pendular states, thereby we evaluate the tripartite entanglement with negativity, as well as fidelity of bipartite quantum systems for input and output signals using electric dipole moments of polar molecules as qubits. According to this study, we consider three typical initial states for bothmore » systems, respectively, and investigate the temporal evolution with variable values of the external field intensity, the intrinsic decoherence factor, and the dipole-dipole interaction. Thus, we demonstrate the sound selection of these three main parameters to obtain the best entanglement degree and fidelity.« less

Influence of intrinsic decoherence on tripartite entanglement and bipartite fidelity of polar molecules in pendular states.

PubMed

Han, Jia-Xing; Hu, Yuan; Jin, Yu; Zhang, Guo-Feng

2016-04-07

An array of ultracold polar molecules trapped in an external electric field is regarded as a promising carrier of quantum information. Under the action of this field, molecules are compelled to undergo pendular oscillations by the Stark effect. Particular attention has been paid to the influence of intrinsic decoherence on the model of linear polar molecular pendular states, thereby we evaluate the tripartite entanglement with negativity, as well as fidelity of bipartite quantum systems for input and output signals using electric dipole moments of polar molecules as qubits. According to this study, we consider three typical initial states for both systems, respectively, and investigate the temporal evolution with variable values of the external field intensity, the intrinsic decoherence factor, and the dipole-dipole interaction. Thus, we demonstrate the sound selection of these three main parameters to obtain the best entanglement degree and fidelity.

Determination of main fruits in adulterated nectars by ATR-FTIR spectroscopy combined with multivariate calibration and variable selection methods.

PubMed

Miaw, Carolina Sheng Whei; Assis, Camila; Silva, Alessandro Rangel Carolino Sales; Cunha, Maria Luísa; Sena, Marcelo Martins; de Souza, Scheilla Vitorino Carvalho

2018-07-15

Grape, orange, peach and passion fruit nectars were formulated and adulterated by dilution with syrup, apple and cashew juices at 10 levels for each adulterant. Attenuated total reflectance Fourier transform mid infrared (ATR-FTIR) spectra were obtained. Partial least squares (PLS) multivariate calibration models allied to different variable selection methods, such as interval partial least squares (iPLS), ordered predictors selection (OPS) and genetic algorithm (GA), were used to quantify the main fruits. PLS improved by iPLS-OPS variable selection showed the highest predictive capacity to quantify the main fruit contents. The selected variables in the final models varied from 72 to 100; the root mean square errors of prediction were estimated from 0.5 to 2.6%; the correlation coefficients of prediction ranged from 0.948 to 0.990; and, the mean relative errors of prediction varied from 3.0 to 6.7%. All of the developed models were validated. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effects of selected design variables on three ramp, external compression inlet performance. [boundary layer control bypasses, and mass flow rate

NASA Technical Reports Server (NTRS)

Kamman, J. H.; Hall, C. L.

1975-01-01

Two inlet performance tests and one inlet/airframe drag test were conducted in 1969 at the NASA-Ames Research Center. The basic inlet system was two-dimensional, three ramp (overhead), external compression, with variable capture area. The data from these tests were analyzed to show the effects of selected design variables on the performance of this type of inlet system. The inlet design variables investigated include inlet bleed, bypass, operating mass flow ratio, inlet geometry, and variable capture area.

Molecular Dynamics Simulations and Classical Multidimensional Scaling Unveil New Metastable States in the Conformational Landscape of CDK2

PubMed Central

Pisani, Pasquale; Rastelli, Giulio

2016-01-01

Protein kinases are key regulatory nodes in cellular networks and their function has been shown to be intimately coupled with their structural flexibility. However, understanding the key structural mechanisms of large conformational transitions remains a difficult task. CDK2 is a crucial regulator of cell cycle. Its activity is finely tuned by Cyclin E/A and the catalytic segment phosphorylation, whereas its deregulation occurs in many types of cancer. ATP competitive inhibitors have failed to be approved for clinical use due to toxicity issues raised by a lack of selectivity. However, in the last few years type III allosteric inhibitors have emerged as an alternative strategy to selectively modulate CDK2 activity. In this study we have investigated the conformational variability of CDK2. A low dimensional conformational landscape of CDK2 was modeled using classical multidimensional scaling on a set of 255 crystal structures. Microsecond-scale plain and accelerated MD simulations were used to populate this landscape by using an out-of-sample extension of multidimensional scaling. CDK2 was simulated in the apo-form and in complex with the allosteric inhibitor 8-anilino-1-napthalenesulfonic acid (ANS). The apo-CDK2 landscape analysis showed a conformational equilibrium between an Src-like inactive conformation and an active-like form. These two states are separated by different metastable states that share hybrid structural features with both forms of the kinase. In contrast, the CDK2/ANS complex landscape is compatible with a conformational selection picture where the binding of ANS in proximity of the αC helix causes a population shift toward the inactive conformation. Interestingly, the new metastable states could enlarge the pool of candidate structures for the development of selective allosteric CDK2 inhibitors. The method here presented should not be limited to the CDK2 case but could be used to systematically unmask similar mechanisms throughout the human kinome. PMID:27100206

Molecular Dynamics Simulations and Classical Multidimensional Scaling Unveil New Metastable States in the Conformational Landscape of CDK2.

PubMed

Pisani, Pasquale; Caporuscio, Fabiana; Carlino, Luca; Rastelli, Giulio

2016-01-01

Protein kinases are key regulatory nodes in cellular networks and their function has been shown to be intimately coupled with their structural flexibility. However, understanding the key structural mechanisms of large conformational transitions remains a difficult task. CDK2 is a crucial regulator of cell cycle. Its activity is finely tuned by Cyclin E/A and the catalytic segment phosphorylation, whereas its deregulation occurs in many types of cancer. ATP competitive inhibitors have failed to be approved for clinical use due to toxicity issues raised by a lack of selectivity. However, in the last few years type III allosteric inhibitors have emerged as an alternative strategy to selectively modulate CDK2 activity. In this study we have investigated the conformational variability of CDK2. A low dimensional conformational landscape of CDK2 was modeled using classical multidimensional scaling on a set of 255 crystal structures. Microsecond-scale plain and accelerated MD simulations were used to populate this landscape by using an out-of-sample extension of multidimensional scaling. CDK2 was simulated in the apo-form and in complex with the allosteric inhibitor 8-anilino-1-napthalenesulfonic acid (ANS). The apo-CDK2 landscape analysis showed a conformational equilibrium between an Src-like inactive conformation and an active-like form. These two states are separated by different metastable states that share hybrid structural features with both forms of the kinase. In contrast, the CDK2/ANS complex landscape is compatible with a conformational selection picture where the binding of ANS in proximity of the αC helix causes a population shift toward the inactive conformation. Interestingly, the new metastable states could enlarge the pool of candidate structures for the development of selective allosteric CDK2 inhibitors. The method here presented should not be limited to the CDK2 case but could be used to systematically unmask similar mechanisms throughout the human kinome.

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

NASA Astrophysics Data System (ADS)

Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

2018-01-01

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

Nowcasting of Low-Visibility Procedure States with Ordered Logistic Regression at Vienna International Airport

NASA Astrophysics Data System (ADS)

Kneringer, Philipp; Dietz, Sebastian; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Low-visibility conditions have a large impact on aviation safety and economic efficiency of airports and airlines. To support decision makers, we develop a statistical probabilistic nowcasting tool for the occurrence of capacity-reducing operations related to low visibility. The probabilities of four different low visibility classes are predicted with an ordered logistic regression model based on time series of meteorological point measurements. Potential predictor variables for the statistical models are visibility, humidity, temperature and wind measurements at several measurement sites. A stepwise variable selection method indicates that visibility and humidity measurements are the most important model inputs. The forecasts are tested with a 30 minute forecast interval up to two hours, which is a sufficient time span for tactical planning at Vienna Airport. The ordered logistic regression models outperform persistence and are competitive with human forecasters.

Atomistic mechanisms of ReRAM cell operation and reliability

NASA Astrophysics Data System (ADS)

Pandey, Sumeet C.

2018-01-01

We present results from first-principles-based modeling that captures functionally important physical phenomena critical to cell materials selection, operation, and reliability for resistance-switching memory technologies. An atomic-scale description of retention, the low- and high-resistance states (RS), and the sources of intrinsic cell-level variability in ReRAM is discussed. Through the results obtained from density functional theory, non-equilibrium Green’s function, molecular dynamics, and kinetic Monte Carlo simulations; the role of variable-charge vacancy defects and metal impurities in determining the RS, the LRS-stability, and electron-conduction in such RS is reported. Although, the statistical electrical characteristics of the oxygen-vacancy (Ox-ReRAM) and conductive-bridging RAM (M-ReRAM) are notably different, the underlying similar electrochemical phenomena describing retention and formation/dissolution of RS are being discussed.

Transcranial Magnetic Stimulation: Decomposing the Processes Underlying Action Preparation.

PubMed

Bestmann, Sven; Duque, Julie

2016-08-01

Preparing actions requires the operation of several cognitive control processes that influence the state of the motor system to ensure that the appropriate behavior is ultimately selected and executed. For example, some form of competition resolution ensures that the right action is chosen among alternatives, often in the presence of conflict; at the same time, impulse control ought to be deployed to prevent premature responses. Here we review how state-changes in the human motor system during action preparation can be studied through motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation over the contralateral primary motor cortex (M1). We discuss how the physiological fingerprints afforded by MEPs have helped to decompose some of the dynamic and effector-specific influences on the motor system during action preparation. We focus on competition resolution, conflict and impulse control, as well as on the influence of higher cognitive decision-related variables. The selected examples demonstrate the usefulness of MEPs as physiological readouts for decomposing the influence of distinct, but often overlapping, control processes on the human motor system during action preparation. © The Author(s) 2015.

Balanced excitation and inhibition are required for high-capacity, noise-robust neuronal selectivity

PubMed Central

Abbott, L. F.; Sompolinsky, Haim

2017-01-01

Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the robustness of single-neuron stimulus selective responses, as well as the robustness of attractor states of networks of neurons performing memory tasks. We find that robustness to output noise requires synaptic connections to be in a balanced regime in which excitation and inhibition are strong and largely cancel each other. We evaluate the conditions required for this regime to exist and determine the properties of networks operating within it. A plausible synaptic plasticity rule for learning that balances weight configurations is presented. Our theory predicts an optimal ratio of the number of excitatory and inhibitory synapses for maximizing the encoding capacity of balanced networks for given statistics of afferent activations. Previous work has shown that balanced networks amplify spatiotemporal variability and account for observed asynchronous irregular states. Here we present a distinct type of balanced network that amplifies small changes in the impinging signals and emerges automatically from learning to perform neuronal and network functions robustly. PMID:29042519

Go for broke: The role of somatic states when asked to lose in the Iowa Gambling Task.

PubMed

Wright, Rebecca J; Rakow, Tim; Russo, Riccardo

2017-02-01

The Somatic Marker Hypothesis (SMH) posits that somatic states develop and guide advantageous decision making by "marking" disadvantageous options (i.e., arousal increases when poor options are considered). This assumption was tested using the standard Iowa Gambling Task (IGT) in which participants win/lose money by selecting among four decks of cards, and an alternative version, identical in both structure and payoffs, but with the aim changed to lose as much money as possible. This "lose" version of the IGT reverses which decks are advantageous/disadvantageous; and so reverses which decks should be marked by somatic responses - which we assessed via skin conductance (SC). Participants learned to pick advantageously in the original (Win) IGT and in the (new) Lose IGT. Using multilevel regression, some variability in anticipatory SC across blocks was found but no consistent effect of anticipatory SC on disadvantageous deck selections. Thus, while we successfully developed a new way to test the central claims of the SMH, we did not find consistent support for the SMH. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Replication of Simulated Prebiotic Amphiphilic Vesicles in a Finite Environment Exhibits Complex Behavior That Includes High Progeny Variability and Competition

PubMed Central

Armstrong, Don L.; Lancet, Doron

2018-01-01

Abstract We studied the simulated replication and growth of prebiotic vesicles composed of 140 phospholipids and cholesterol using our R-GARD (Real Graded Autocatalysis Replication Domain) formalism that utilizes currently extant lipids that have known rate constants of lipid-vesicle interactions from published experimental data. R-GARD normally modifies kinetic parameters of lipid-vesicle interactions based on vesicle composition and properties. Our original R-GARD model tracked the growth and division of one vesicle at a time in an environment with unlimited lipids at a constant concentration. We explore here a modified model where vesicles compete for a finite supply of lipids. We observed that vesicles exhibit complex behavior including initial fast unrestricted growth, followed by intervesicle competition for diminishing resources, then a second growth burst driven by better-adapted vesicles, and ending with a final steady state. Furthermore, in simulations without kinetic parameter modifications (“invariant kinetics”), the initial replication was an order of magnitude slower, and vesicles' composition variability at the final steady state was much lower. The complex kinetic behavior was not observed either in the previously published R-GARD simulations or in additional simulations presented here with only one lipid component. This demonstrates that both a finite environment (inducing selection) and multiple components (providing variation for selection to act upon) are crucial for portraying evolution-like behavior. Such properties can improve survival in a changing environment by increasing the ability of early protocellular entities to respond to rapid environmental fluctuations likely present during abiogenesis both on Earth and possibly on other planets. This in silico simulation predicts that a relatively simple in vitro chemical system containing only lipid molecules might exhibit properties that are relevant to prebiotic processes. Key Words: Phospholipid vesicles—Prebiotic compartments—Prebiotic vesicle competition—Prebiotic vesicle variability. Astrobiology 18, 419–430. PMID:29634319

On the use of internal state variables in thermoviscoplastic constitutive equations

NASA Technical Reports Server (NTRS)

Allen, D. H.; Beek, J. M.

1985-01-01

The general theory of internal state variables are reviewed to apply it to inelastic metals in use in high temperature environments. In this process, certain constraints and clarifications will be made regarding internal state variables. It is shown that the Helmholtz free energy can be utilized to construct constitutive equations which are appropriate for metallic superalloys. Internal state variables are shown to represent locally averaged measures of dislocation arrangement, dislocation density, and intergranular fracture. The internal state variable model is demonstrated to be a suitable framework for comparison of several currently proposed models for metals and can therefore be used to exhibit history dependence, nonlinearity, and rate as well as temperature sensitivity.

Convergence analysis of sliding mode trajectories in multi-objective neural networks learning.

PubMed

Costa, Marcelo Azevedo; Braga, Antonio Padua; de Menezes, Benjamin Rodrigues

2012-09-01

The Pareto-optimality concept is used in this paper in order to represent a constrained set of solutions that are able to trade-off the two main objective functions involved in neural networks supervised learning: data-set error and network complexity. The neural network is described as a dynamic system having error and complexity as its state variables and learning is presented as a process of controlling a learning trajectory in the resulting state space. In order to control the trajectories, sliding mode dynamics is imposed to the network. It is shown that arbitrary learning trajectories can be achieved by maintaining the sliding mode gains within their convergence intervals. Formal proofs of convergence conditions are therefore presented. The concept of trajectory learning presented in this paper goes further beyond the selection of a final state in the Pareto set, since it can be reached through different trajectories and states in the trajectory can be assessed individually against an additional objective function. Copyright © 2012 Elsevier Ltd. All rights reserved.

Energy cost of walking: solving the paradox of steady state in the presence of variable walking speed.

PubMed

Plasschaert, Frank; Jones, Kim; Forward, Malcolm

2009-02-01

Measurement of the energy cost of walking in children with cerebral palsy is used for baseline and outcome assessment. However, such testing relies on the establishment of steady state that is deemed present when oxygen consumption is stable. This is often assumed when walking speed is constant but in practice, speed can and does vary naturally. Whilst constant speed is achievable on a treadmill, this is often impractical clinically, thus rendering an energy cost test to an element of subjectivity. This paper attempts to address this issue by presenting a new method for calculating energy cost of walking that automatically applies a mathematically defined threshold for steady state within a (non-treadmill) walking trial and then strips out all of the non-steady state events within that trial. The method is compared with a generic approach that does not remove non-steady state data but rather uses an average value over a complete walking trial as is often used in the clinical environment. Both methods were applied to the calculation of several energy cost of walking parameters of self-selected walking speed in a cohort of unimpaired subjects and children with cerebral palsy. The results revealed that both methods were strongly correlated for each parameter but showed systematic significant differences. It is suggested that these differences are introduced by the rejection of non-steady state data that would otherwise have incorrectly been incorporated into the calculation of the energy cost of walking indices during self-selected walking with its inherent speed variation.

Systematic Review of the profile of emergency contraception users

PubMed Central

Amengual, Maria de Lluc Bauzà; Canto, Magdalena Esteva; Berenguer, Inmaculada Pereiro; Pol, Maria Ingla

2016-01-01

Abastract Objective: to discern the profile of the Spanish Emergency Contraceptive users (EC). Design: systematic review of contraceptive use in the Spanish population. Data Source: Spanish and international databases, between January 2006 - March 2011. Keywords: Contraceptives, Postcoital pills, emergency contraception, levonorgestrel, data collection. Study selection: original papers, letters to the editor in which stated aims were the description, prediction or measurement of variables related to EC use. Twenty-two papers were retrieved and fourteen were finally selected, all of which were descriptive. Data extraction: manuscripts were evaluated by two independent reviewers. Results: Women requesting EC have ages between 21-24 years, mostly single and university students; declare that they have not previously used EC, and attend an Emergency department, at weekends and within 48 hours following unprotected sexual intercourse. The reason is condom rupture. None of the studies reviewed measured alcohol and other drug consumption, the number of sexual partners, nor any of the studies performed a comparison with a group not using EC. Conclusions: lack of homogeneity and comprehensiveness of studied variables resulted in a limited profile of Spanish EC users. Further studies are needed with a more comprehensive approach if sexual health interventions are to be carried out in possible users. PMID:27384470

Space-Time Joint Interference Cancellation Using Fuzzy-Inference-Based Adaptive Filtering Techniques in Frequency-Selective Multipath Channels

NASA Astrophysics Data System (ADS)

Hu, Chia-Chang; Lin, Hsuan-Yu; Chen, Yu-Fan; Wen, Jyh-Horng

2006-12-01

An adaptive minimum mean-square error (MMSE) array receiver based on the fuzzy-logic recursive least-squares (RLS) algorithm is developed for asynchronous DS-CDMA interference suppression in the presence of frequency-selective multipath fading. This receiver employs a fuzzy-logic control mechanism to perform the nonlinear mapping of the squared error and squared error variation, denoted by ([InlineEquation not available: see fulltext.],[InlineEquation not available: see fulltext.]), into a forgetting factor[InlineEquation not available: see fulltext.]. For the real-time applicability, a computationally efficient version of the proposed receiver is derived based on the least-mean-square (LMS) algorithm using the fuzzy-inference-controlled step-size[InlineEquation not available: see fulltext.]. This receiver is capable of providing both fast convergence/tracking capability as well as small steady-state misadjustment as compared with conventional LMS- and RLS-based MMSE DS-CDMA receivers. Simulations show that the fuzzy-logic LMS and RLS algorithms outperform, respectively, other variable step-size LMS (VSS-LMS) and variable forgetting factor RLS (VFF-RLS) algorithms at least 3 dB and 1.5 dB in bit-error-rate (BER) for multipath fading channels.

Emotional Experience Improves With Age: Evidence Based on Over 10 Years of Experience Sampling

PubMed Central

Carstensen, Laura L.; Turan, Bulent; Scheibe, Susanne; Ram, Nilam; Ersner-Hershfield, Hal; Samanez-Larkin, Gregory R.; Brooks, Kathryn P.; Nesselroade, John R.

2012-01-01

Recent evidence suggests that emotional well-being improves from early adulthood to old age. This study used experience-sampling to examine the developmental course of emotional experience in a representative sample of adults spanning early to very late adulthood. Participants (N = 184, Wave 1; N = 191, Wave 2; N = 178, Wave 3) reported their emotional states at five randomly selected times each day for a one week period. Using a measurement burst design, the one-week sampling procedure was repeated five and then ten years later. Cross-sectional and growth curve analyses indicate that aging is associated with more positive overall emotional well-being, with greater emotional stability and with more complexity (as evidenced by greater co-occurrence of positive and negative emotions). These findings remained robust after accounting for other variables that may be related to emotional experience (personality, verbal fluency, physical health, and demographic variables). Finally, emotional experience predicted mortality; controlling for age, sex, and ethnicity, individuals who experienced relatively more positive than negative emotions in everyday life were more likely to have survived over a 13 year period. Findings are discussed in the theoretical context of socioemotional selectivity theory. PMID:20973600

The Role of Body Size in Mate Selection among African American Young Adults

PubMed Central

Simons, Leslie G.; Simons, Ronald L.

2016-01-01

A profusion of studies have demonstrated that body size is a major factor in mate selection for both men and women. The particular role played by weight, however, has been subject to some debate, particularly with respect to the types of body sizes deemed most attractive, and scholars have questioned the degree to which body size preferences are constant across groups. In this paper, we drew from two perspectives on this issue, Sexual Strategies Theory and what we termed the cultural variability perspective, and used survey data to examine how body size was associated with both casual dating and serious romantic relationships. We used a United States sample of 386 African American adolescents and young adults between ages 16 and 21, living in the Midwest and Southeast, and who were enrolled in either high school or college. Results showed that overweight women were more likely to report casually dating than women in the thinnest weight category. Body size was not related to dating status among men. Among women, the results suggest stronger support for the cultural variability argument than for Sexual Strategies Theory. Potential explanations for these findings are discussed. PMID:26973377

Testing quantum contextuality of continuous-variable states

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

McKeown, Gerard; Paternostro, Mauro; Paris, Matteo G. A.

2011-06-15

We investigate the violation of noncontextuality by a class of continuous-variable states, including variations of entangled coherent states and a two-mode continuous superposition of coherent states. We generalize the Kochen-Specker (KS) inequality discussed by Cabello [A. Cabello, Phys. Rev. Lett. 101, 210401 (2008)] by using effective bidimensional observables implemented through physical operations acting on continuous-variable states, in a way similar to an approach to the falsification of Bell-Clauser-Horne-Shimony-Holt inequalities put forward recently. We test for state-independent violation of KS inequalities under variable degrees of state entanglement and mixedness. We then demonstrate theoretically the violation of a KS inequality for anymore » two-mode state by using pseudospin observables and a generalized quasiprobability function.« less

Demographic and health situation of children in conditions of economic destabilization in the Ukraine.

PubMed

Pantyley, Viktoriya

2014-01-01

In new conditions of socio-economic development in the Ukraine, the health of the population of children is considered as the most reliable indicator of socio-economic development of the country. The primary goal of the study was analysis of the effect of contemporary socio-economic transformations, their scope, and strength of effect on the demographic and social situation of children in various regions of the Ukraine. The methodological objectives of the study were as follows: development of a synthetic measure of the state of health of the population of children, based on the Hellwig's method, and selection of districts in the Ukraine according to the present health-demographic situation of children. The study was based on statistical data from the State Statistics Service of Ukraine, Centre of Medical Statistics in Kiev, Ukrainian Ministry of Defence, as well as Ministry of Education and Science, Youth and Sports of Ukraine. The following research methods were used: analysis of literature and Internet sources, selection and analysis of statistical materials, cartographic and statistical methods. Basic indices of the demographic and health situation of the population of children were analyzed, as well as factors of a socio-economic nature which affect this situation. A set of variables was developed for the synthetic evaluation of the state of health of the population of children. The typology of the Ukrainian districts was performed according to the state of health of the child population, based on the Hellwig's taxonomic method. Deterioration was observed of selected quality parameters, as well as a change in the strength and directions of effect of factors of organizational-institutional, socioeconomic, historical and cultural nature on the population of children potential.

Genetic potential of common bean progenies obtained by different breeding methods evaluated in various environments.

PubMed

Pontes Júnior, V A; Melo, P G S; Pereira, H S; Melo, L C

2016-09-02

Grain yield is strongly influenced by the environment, has polygenic and complex inheritance, and is a key trait in the selection and recommendation of cultivars. Breeding programs should efficiently explore the genetic variability resulting from crosses by selecting the most appropriate method for breeding in segregating populations. The goal of this study was to evaluate and compare the genetic potential of common bean progenies of carioca grain for grain yield, obtained by different breeding methods and evaluated in different environments. Progenies originating from crosses between lines and CNFC 7812 and CNFC 7829 were replanted up to the F 7 generation using three breeding methods in segregating populations: population (bulk), bulk within F 2 progenies, and single-seed descent (SSD). Fifteen F 8 progenies per method, two controls (BRS Estilo and Perola), and the parents were evaluated in a 7 x 7 simple lattice design, with plots of two 4-m rows. The tests were conducted in 10 environments in four States of Brazil and in three growing seasons in 2009 and 2010. Genetic parameters including genetic variance, heritability, variance of interaction, and expected selection gain were estimated. Genetic variability among progenies and the effect of progeny-environment interactions were determined for the three methods. The breeding methods differed significantly due to the effects of sampling procedures on the progenies and due to natural selection, which mainly affected the bulk method. The SSD and bulk methods provided populations with better estimates of genetic parameters and more stable progenies that were less affected by interaction with the environment.

Variable selection in discrete survival models including heterogeneity.

PubMed

Groll, Andreas; Tutz, Gerhard

2017-04-01

Several variable selection procedures are available for continuous time-to-event data. However, if time is measured in a discrete way and therefore many ties occur models for continuous time are inadequate. We propose penalized likelihood methods that perform efficient variable selection in discrete survival modeling with explicit modeling of the heterogeneity in the population. The method is based on a combination of ridge and lasso type penalties that are tailored to the case of discrete survival. The performance is studied in simulation studies and an application to the birth of the first child.

The resurgence of selective contracting restrictions.

PubMed

Marsteller, J A; Bovbjerg, R R; Nichols, L M; Verrilli, D K

1997-10-01

As managed care has spread, so has legislation to force plans to contract with any willing provider (AWP) and give patients freedom of choice (FOC). Managed care organizations' selective networks and provider integration reduce patient access to providers, along with provider access to paying patients, so many providers have lobbied for AWP-FOC laws. In opposition are managed care organizations (MCOs), which want full freedom to contract selectively to control prices and utilization. This article comprehensively describes laws in all fifty-one jurisdictions, classifies their relative strength, and assesses the implications of the laws. Most are relatively weak forms and all are limited in application by ERISA and the federal HMO Act. The article also uses an associative multivariate analysis to relate the selective contracting environments to HMO penetration rates, rural population, physician density, and other variables. States with weak laws also have higher HMO penetration and higher physician density, but smaller rural populations. We conclude that the strongest laws overly restrict the management of care, to the likely detriment of cost control. But where market power is rapidly concentrating, not restricting selective contracting could diminish long-term competition and patient access to care. In the face of uncertainty about the impact of these laws, an intermediate approach may be better than all or nothing. States should consider mandating that plans offer point-of-service options, for a separate premium. This option expands patient choice of plans at the time of enrollment and of providers at the time of care, yet maintains plans' ability to control core providers.

Altered trait variability in response to size-selective mortality.

PubMed

Uusi-Heikkilä, Silva; Lindström, Kai; Parre, Noora; Arlinghaus, Robert; Alós, Josep; Kuparinen, Anna

2016-09-01

Changes in trait variability owing to size-selective harvesting have received little attention in comparison with changes in mean trait values, perhaps because of the expectation that phenotypic variability should generally be eroded by directional selection typical for fishing and hunting. We show, however, that directional selection, in particular for large body size, leads to increased body-size variation in experimentally harvested zebrafish (Danio rerio) populations exposed to two alternative feeding environments: ad libitum and temporarily restricted food availability. Trait variation may influence population adaptivity, stability and resilience. Therefore, rather than exerting selection pressures that favour small individuals, our results stress the importance of protecting large ones, as they can harbour a great amount of variation within a population, to manage fish stocks sustainably. © 2016 The Author(s).

Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe

2016-11-01

Given the ever increasing number of climate change simulations being carried out, it has become impractical to use all of them to cover the uncertainty of climate change impacts. Various methods have been proposed to optimally select subsets of a large ensemble of climate simulations for impact studies. However, the behaviour of optimally-selected subsets of climate simulations for climate change impacts is unknown, since the transfer process from climate projections to the impact study world is usually highly non-linear. Consequently, this study investigates the transferability of optimally-selected subsets of climate simulations in the case of hydrological impacts. Two different methods were used for the optimal selection of subsets of climate scenarios, and both were found to be capable of adequately representing the spread of selected climate model variables contained in the original large ensemble. However, in both cases, the optimal subsets had limited transferability to hydrological impacts. To capture a similar variability in the impact model world, many more simulations have to be used than those that are needed to simply cover variability from the climate model variables' perspective. Overall, both optimal subset selection methods were better than random selection when small subsets were selected from a large ensemble for impact studies. However, as the number of selected simulations increased, random selection often performed better than the two optimal methods. To ensure adequate uncertainty coverage, the results of this study imply that selecting as many climate change simulations as possible is the best avenue. Where this was not possible, the two optimal methods were found to perform adequately.

Robustness of Two Formulas to Correct Pearson Correlation for Restriction of Range

ERIC Educational Resources Information Center

tran, minh

2011-01-01

Many research studies involving Pearson correlations are conducted in settings where one of the two variables has a restricted range in the sample. For example, this situation occurs when tests are used for selecting candidates for employment or university admission. Often after selection, there is interest in correlating the selection variable,…

Clustering Words to Match Conditions: An Algorithm for Stimuli Selection in Factorial Designs

ERIC Educational Resources Information Center

Guasch, Marc; Haro, Juan; Boada, Roger

2017-01-01

With the increasing refinement of language processing models and the new discoveries about which variables can modulate these processes, stimuli selection for experiments with a factorial design is becoming a tough task. Selecting sets of words that differ in one variable, while matching these same words into dozens of other confounding variables…

Selection of relevant input variables in storm water quality modeling by multiobjective evolutionary polynomial regression paradigm

NASA Astrophysics Data System (ADS)

Creaco, E.; Berardi, L.; Sun, Siao; Giustolisi, O.; Savic, D.

2016-04-01

The growing availability of field data, from information and communication technologies (ICTs) in "smart" urban infrastructures, allows data modeling to understand complex phenomena and to support management decisions. Among the analyzed phenomena, those related to storm water quality modeling have recently been gaining interest in the scientific literature. Nonetheless, the large amount of available data poses the problem of selecting relevant variables to describe a phenomenon and enable robust data modeling. This paper presents a procedure for the selection of relevant input variables using the multiobjective evolutionary polynomial regression (EPR-MOGA) paradigm. The procedure is based on scrutinizing the explanatory variables that appear inside the set of EPR-MOGA symbolic model expressions of increasing complexity and goodness of fit to target output. The strategy also enables the selection to be validated by engineering judgement. In such context, the multiple case study extension of EPR-MOGA, called MCS-EPR-MOGA, is adopted. The application of the proposed procedure to modeling storm water quality parameters in two French catchments shows that it was able to significantly reduce the number of explanatory variables for successive analyses. Finally, the EPR-MOGA models obtained after the input selection are compared with those obtained by using the same technique without benefitting from input selection and with those obtained in previous works where other data-modeling techniques were used on the same data. The comparison highlights the effectiveness of both EPR-MOGA and the input selection procedure.

Feature Selection for Nonstationary Data: Application to Human Recognition Using Medical Biometrics.

PubMed

Komeili, Majid; Louis, Wael; Armanfard, Narges; Hatzinakos, Dimitrios

2018-05-01

Electrocardiogram (ECG) and transient evoked otoacoustic emission (TEOAE) are among the physiological signals that have attracted significant interest in biometric community due to their inherent robustness to replay and falsification attacks. However, they are time-dependent signals and this makes them hard to deal with in across-session human recognition scenario where only one session is available for enrollment. This paper presents a novel feature selection method to address this issue. It is based on an auxiliary dataset with multiple sessions where it selects a subset of features that are more persistent across different sessions. It uses local information in terms of sample margins while enforcing an across-session measure. This makes it a perfect fit for aforementioned biometric recognition problem. Comprehensive experiments on ECG and TEOAE variability due to time lapse and body posture are done. Performance of the proposed method is compared against seven state-of-the-art feature selection algorithms as well as another six approaches in the area of ECG and TEOAE biometric recognition. Experimental results demonstrate that the proposed method performs noticeably better than other algorithms.

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Adaptability and stability of soybean cultivars for grain yield and seed quality.

PubMed

Silva, K B; Bruzi, A T; Zambiazzi, E V; Soares, I O; Pereira, J L A R; Carvalho, M L M

2017-05-10

This study aimed at verifying the adaptability and stability of soybean cultivars, considering the grain yield and quality of seeds, adopting univariate and multivariate approaches. The experiments were conducted in two crops, three environments, in 2013/2014 and 2014/2015 crop seasons, in the county of Inconfidentes, Lavras, and Patos de Minas, in the Minas Gerais State, Brazil. We evaluated 17 commercial soybean cultivars. For adaptability and stability evaluations, the Graphic and GGE biplot methods were employed. Previously, a selection index was estimated based on the sum of the standardized variables (Z index). The data relative to grain yield, mass of one thousand grain, uniformity test (sieve retention), and germination test were standardized (Z ij ) per cultivar. With the sum of Z ij , we obtained the selection index for the four traits evaluated together. In the Graphic method evaluation, cultivars NA 7200 RR and CD 2737 RR presented the highest values for selection index Z. By the GGE biplot method, we verified that cultivar NA 7200 RR presented greater stability in both univariate evaluations, for grain yield, and for selection index Z.

Implementation of Kalman filter algorithm on models reduced using singular pertubation approximation method and its application to measurement of water level

NASA Astrophysics Data System (ADS)

Rachmawati, Vimala; Khusnul Arif, Didik; Adzkiya, Dieky

2018-03-01

The systems contained in the universe often have a large order. Thus, the mathematical model has many state variables that affect the computation time. In addition, generally not all variables are known, so estimations are needed to measure the magnitude of the system that cannot be measured directly. In this paper, we discuss the model reduction and estimation of state variables in the river system to measure the water level. The model reduction of a system is an approximation method of a system with a lower order without significant errors but has a dynamic behaviour that is similar to the original system. The Singular Perturbation Approximation method is one of the model reduction methods where all state variables of the equilibrium system are partitioned into fast and slow modes. Then, The Kalman filter algorithm is used to estimate state variables of stochastic dynamic systems where estimations are computed by predicting state variables based on system dynamics and measurement data. Kalman filters are used to estimate state variables in the original system and reduced system. Then, we compare the estimation results of the state and computational time between the original and reduced system.

Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

2016-12-01

State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

Variable selection and model choice in geoadditive regression models.

PubMed

Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

2009-06-01

Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

Origin of the OFF state variability in ReRAM cells

NASA Astrophysics Data System (ADS)

Salaoru, Iulia; Khiat, Ali; Li, Qingjiang; Berdan, Radu; Papavassiliou, Christos; Prodromakis, Themistoklis

2014-04-01

This work exploits the switching dynamics of nanoscale resistive random access memory (ReRAM) cells with particular emphasis on the origin of the observed variability when cells are consecutively cycled/programmed at distinct memory states. It is demonstrated that this variance is a common feature of all ReRAM elements and is ascribed to the formation and rupture of conductive filaments that expand across the active core, independently of the material employed as the active switching core, the causal physical switching mechanism, the switching mode (bipolar/unipolar) or even the unit cells' dimensions. Our hypothesis is supported through both experimental and theoretical studies on TiO2 and In2O3 : SnO2 (ITO) based ReRAM cells programmed at three distinct resistive states. Our prototypes employed TiO2 or ITO active cores over 5 × 5 µm2 and 100 × 100 µm2 cell areas, with all tested devices demonstrating both unipolar and bipolar switching modalities. In the case of TiO2-based cells, the underlying switching mechanism is based on the non-uniform displacement of ionic species that foster the formation of conductive filaments. On the other hand, the resistive switching observed in the ITO-based devices is considered to be due to a phase change mechanism. The selected experimental parameters allowed us to demonstrate that the observed programming variance is a common feature of all ReRAM devices, proving that its origin is dependent upon randomly oriented local disorders within the active core that have a substantial impact on the overall state variance, particularly for high-resistive states.

Background concentrations of metals in soils from selected regions in the State of Washington

USGS Publications Warehouse

Ames, K.C.; Prych, E.A.

1995-01-01

Soil samples from 60 sites in the State of Washington were collected and analyzed to determine the magnitude and variability of background concen- trations of metals in soils of the State. Samples were collected in areas that were relatively undisturbed by human activity from the most pre- dominant soils in 12 different regions that are representative of large areas of Washington State. Concentrations of metals were determined by five different laboratory methods. Concentrations of mercury and nickel determined by both the total and total-recoverable methods displayed the greatest variability, followed by chromium and copper determined by the total-recoverable method. Concentrations of other metals, such as aluminum and barium determined by the total method, varied less. Most metals concentrations were found to be more nearly log-normally than normally distributed. Total metals concentrations were not significantly different among the different regions. However, total-recoverable metals concentrations were not as similar among different regions. Cluster analysis revealed that sampling sites in three regions encompassing the Puget Sound could be regrouped to form two new regions and sites in three regions in south-central and southeastern Washington State could also be regrouped into two new regions. Concentrations for 7 of 11 total-recoverable metals correlated with total metals concentrations. Concen- trations of six total metals also correlated positively with organic carbon. Total-recoverable metals concentrations did not correlate with either organic carbon or particle size. Concentrations of metals determined by the leaching methods did not correlate with total or total-recoverable metals concentrations, nor did they correlate with organic carbon or particle size.

A novel pixellated solid-state photon detector for enhancing the Everhart-Thornley detector.

PubMed

Chuah, Joon Huang; Holburn, David

2013-06-01

This article presents a pixellated solid-state photon detector designed specifically to improve certain aspects of the existing Everhart-Thornley detector. The photon detector was constructed and fabricated in an Austriamicrosystems 0.35 µm complementary metal-oxide-semiconductor process technology. This integrated circuit consists of an array of high-responsivity photodiodes coupled to corresponding low-noise transimpedance amplifiers, a selector-combiner circuit and a variable-gain postamplifier. Simulated and experimental results show that the photon detector can achieve a maximum transimpedance gain of 170 dBΩ and minimum bandwidth of 3.6 MHz. It is able to detect signals with optical power as low as 10 nW and produces a minimum signal-to-noise ratio (SNR) of 24 dB regardless of gain configuration. The detector has been proven to be able to effectively select and combine signals from different pixels. The key advantages of this detector are smaller dimensions, higher cost effectiveness, lower voltage and power requirements and better integration. The photon detector supports pixel-selection configurability which may improve overall SNR and also potentially generate images for different analyses. This work has contributed to the future research of system-level integration of a pixellated solid-state detector for secondary electron detection in the scanning electron microscope. Copyright © 2013 Wiley Periodicals, Inc.

Effects of low dose ibogaine on subjective mood state and psychological performance.

PubMed

Forsyth, Bridget; Machado, Liana; Jowett, Tim; Jakobi, Hannah; Garbe, Kira; Winter, Helen; Glue, Paul

2016-08-02

Root bark from Tabernanthe iboga has been used traditionally in West Africa as a psychoactive substance in religious rituals. In smaller doses it is reported anecdotally to have stimulant properties. To evaluate the influence of a single 20mg ibogaine dose on psychological variables reflecting subjective mood state and a range of cognitive functions. 21 healthy male volunteers received single 20mg doses of ibogaine after 6 days pretreatment with double-blind paroxetine or placebo. We compared responses to a battery of psychometric tests and subjective mood ratings performed before and 2h after ibogaine dosing, and assessed relationships between changes in test scores and concentrations of active moiety (the sum of molar noribogaine and ibogaine concentrations). Psychological tests were chosen based on responsiveness to opioid and serotonergic ligands. Ibogaine had minimal influence on psychological tests and mood ratings. The ability to selectively ignore distracting spatial information showed some evidence of modulation; however because this effect was limited to the less challenging condition calls into question the reliability of this result. We were unable to identify stimulant effects after single 20mg doses of ibogaine. Future research is needed to confirm whether active moiety concentrations impact selective attention abilities while leaving other cognitive functions and mood state unaffected. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Analytic Thermoelectric Couple Modeling: Variable Material Properties and Transient Operation

NASA Technical Reports Server (NTRS)

Mackey, Jonathan A.; Sehirlioglu, Alp; Dynys, Fred

2015-01-01

To gain a deeper understanding of the operation of a thermoelectric couple a set of analytic solutions have been derived for a variable material property couple and a transient couple. Using an analytic approach, as opposed to commonly used numerical techniques, results in a set of useful design guidelines. These guidelines can serve as useful starting conditions for further numerical studies, or can serve as design rules for lab built couples. The analytic modeling considers two cases and accounts for 1) material properties which vary with temperature and 2) transient operation of a couple. The variable material property case was handled by means of an asymptotic expansion, which allows for insight into the influence of temperature dependence on different material properties. The variable property work demonstrated the important fact that materials with identical average Figure of Merits can lead to different conversion efficiencies due to temperature dependence of the properties. The transient couple was investigated through a Greens function approach; several transient boundary conditions were investigated. The transient work introduces several new design considerations which are not captured by the classic steady state analysis. The work helps to assist in designing couples for optimal performance, and also helps assist in material selection.

Vulnerability and Tradeoffs of Dairy Farmers to the Impacts of Climate Variability and Change in India

NASA Astrophysics Data System (ADS)

Radhakrishnan, A.; Gupta, J.; R, D.

2016-12-01

In recent years climate variability has threatened the sustainability of dairy animals and dairy farming in India. The study aims at assessing the vulnerability and tradeoffs of Dairy Based Livelihoods to Climate Variability and Change in the Western Ghat ecosystem and for this purpose; data were aggregated to an overall Livelihood Vulnerability Index (LVI) to Climate Change underlying the principles of IPCC, using 28 indicators and trade-off between vulnerability and milk production was calculated. Data were collected through Participatory Rural Appraisal and personal interviews from 360 randomly selected dairy farmers of three states of Western Ghat region, complemented by thirty years of gridded weather data and livestock data. The index score of dairy based livelihoods of many regions were negative. Lanja taluka of Maharashtra has highest level of vulnerability with overall LVI value -4.17 with 48% farmers falling in highly vulnerable category. There is also significant tradeoff between milk production and components of LVI. Thus our research will provide an important basis for policy makers to develop appropriate adaptation strategies for alarming situation and decision making for farmers to minimize the risk of dairy sector to climate variability.

Postpartum fatigue in the active-duty military woman.

PubMed

Rychnovsky, Jacqueline D

2007-01-01

(a) To describe fatigue levels in military active-duty women, (b) to describe the relationship among selected predictor variables of fatigue, and (c) to examine the relationship between predictor variables, fatigue levels, and performance (as measured by functional status) after childbirth. Based on the Theory of Unpleasant Symptoms, a longitudinal, prospective design. A large military medical facility in the southwest United States. A convenience sample of 109 military active-duty women. Postpartum fatigue. Women were found to be moderately fatigued across time, with no change in fatigue levels from 2 to 6 weeks after delivery. All variables correlated with fatigue during hospitalization and at 2 weeks after delivery, and depression, anxiety, maternal sleep, and functional status correlated with fatigue at 6 weeks after delivery. Regression analyses indicated that maternal anxiety predicted fatigue at 6 weeks after delivery. Over half the women had not regained full functional status when they returned to work, and 40% still displayed symptoms of postpartum depression and anxiety. Military women continue to experiencing postpartum fatigue when they return to the workplace. Future research is needed to examine issues surrounding fatigue and its associated variables during the first year after delivery.

Latent variable method for automatic adaptation to background states in motor imagery BCI

NASA Astrophysics Data System (ADS)

Dagaev, Nikolay; Volkova, Ksenia; Ossadtchi, Alexei

2018-02-01

Objective. Brain-computer interface (BCI) systems are known to be vulnerable to variabilities in background states of a user. Usually, no detailed information on these states is available even during the training stage. Thus there is a need in a method which is capable of taking background states into account in an unsupervised way. Approach. We propose a latent variable method that is based on a probabilistic model with a discrete latent variable. In order to estimate the model’s parameters, we suggest to use the expectation maximization algorithm. The proposed method is aimed at assessing characteristics of background states without any corresponding data labeling. In the context of asynchronous motor imagery paradigm, we applied this method to the real data from twelve able-bodied subjects with open/closed eyes serving as background states. Main results. We found that the latent variable method improved classification of target states compared to the baseline method (in seven of twelve subjects). In addition, we found that our method was also capable of background states recognition (in six of twelve subjects). Significance. Without any supervised information on background states, the latent variable method provides a way to improve classification in BCI by taking background states into account at the training stage and then by making decisions on target states weighted by posterior probabilities of background states at the prediction stage.

Weather patterns as a downscaling tool - evaluating their skill in stratifying local climate variables

NASA Astrophysics Data System (ADS)

Murawski, Aline; Bürger, Gerd; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

The use of a weather pattern based approach for downscaling of coarse, gridded atmospheric data, as usually obtained from the output of general circulation models (GCM), allows for investigating the impact of anthropogenic greenhouse gas emissions on fluxes and state variables of the hydrological cycle such as e.g. on runoff in large river catchments. Here we aim at attributing changes in high flows in the Rhine catchment to anthropogenic climate change. Therefore we run an objective classification scheme (simulated annealing and diversified randomisation - SANDRA, available from the cost733 classification software) on ERA20C reanalyses data and apply the established classification to GCMs from the CMIP5 project. After deriving weather pattern time series from GCM runs using forcing from all greenhouse gases (All-Hist) and using natural greenhouse gas forcing only (Nat-Hist), a weather generator will be employed to obtain climate data time series for the hydrological model. The parameters of the weather pattern classification (i.e. spatial extent, number of patterns, classification variables) need to be selected in a way that allows for good stratification of the meteorological variables that are of interest for the hydrological modelling. We evaluate the skill of the classification in stratifying meteorological data using a multi-variable approach. This allows for estimating the stratification skill for all meteorological variables together, not separately as usually done in existing similar work. The advantage of the multi-variable approach is to properly account for situations where e.g. two patterns are associated with similar mean daily temperature, but one pattern is dry while the other one is related to considerable amounts of precipitation. Thus, the separation of these two patterns would not be justified when considering temperature only, but is perfectly reasonable when accounting for precipitation as well. Besides that, the weather patterns derived from reanalyses data should be well represented in the All-Hist GCM runs in terms of e.g. frequency, seasonality, and persistence. In this contribution we show how to select the most appropriate weather pattern classification and how the classes derived from it are reflected in the GCMs.

[Dating violence and associations with depression and risk behaviors: female students in Morelos, Mexico].

PubMed

Rivera-Rivera, Leonor; Allen, Betania; Rodríguez-Ortega, Graciela; Chávez-Ayala, Rubén; Lazcano-Ponce, Eduardo

2006-01-01

Determine the prevalence of dating violence and its association with depression and various risk behaviors in a sample of female students from the state of Morelos. This is a baseline cohort study of a sample of 13 293 students from 12 to 24 years of age who attended public schools in the state of Morelos during the 1998-1999 school year. The participants were selected from a random sample of 260 junior high schools, 92 high schools and one university. For the purpose of this analysis, a total of 4 587 female students who had a previous dating relationship were selected. To control for possible confounding variables, multiple logistic regression analysis was used. The total prevalence of dating violence in females who attended public schools in Morelos was 28%. The following variables were associated with dating violence: depression (OR = 1.92; 95% CI 1.61-2.28); tobacco smoking (OR = 1.31; 95% CI 1.06-1.60); alcohol abuse (OR = 1.30, 95% CI 1.12-1.51); poor academic performance (low grades) (OR = 1.25; 95% CI 1.03-1.52); a history of sexual relations (OR = 1.52; 95% CI 1.26-1.82). The results of this study clearly indicate that women experience partner violence beginning with dating during adolescence. Health and education professionals need to establish intervention strategies to prevent or treat dating violence among female students. Such strategies should take into account the association between depression and violence, as well as other related risk behaviors.

Analysis of Decentralized Variable Structure Control for Collective Search by Mobile Robots

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

Feddema, J.; Goldsmith, S.; Robinett, R.

1998-11-04

This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha-beta coordination strategy is a family of collective search algorithms that allow teams of communicating robots to implicitly coordinate their search activities through a division of labor based on self-selected roIes. In an alpha-beta team. alpha agents are motivated to improve their status by exploring new regions of the search space. Beta a~ents are conservative, and reiy on the alpha agents to provide advanced information on favorable regions of the search space. An agent selects its currentmore » role dynamically based on its current status value relative to the current status values of the other team members. Status is determined by some function of the agent's sensor readings, and is generally a measurement of source intensity at the agent's current location. Variations on the decision rules determining alpha and beta behavior produce different versions of the algorithm that lead to different global properties. The alpha-beta strategy is based on a simple finite-state machine that implements a form of Variable Structure Control (VSC). The VSC system changes the dynamics of the collective system by abruptly switching at defined states to alternative control laws . In VSC, Lyapunov's direct method is often used to design control surfaces which guide the system to a given goal. We introduce the alpha-beta aIgorithm and present an analysis of the equilibrium point and the global stability of the alpha-beta algorithm based on Lyapunov's method.« less

Analysis of decentralized variable structure control for collective search by mobile robots

NASA Astrophysics Data System (ADS)

Goldsmith, Steven Y.; Feddema, John T.; Robinett, Rush D., III

1998-10-01

This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha- beta coordination strategy is a family of collective search algorithms that allow teams of communicating robots to implicitly coordinate their search activities through a division of labor based on self-selected roles. In an alpha- beta team, alpha agents are motivated to improve their status by exploring new regions of the search space. Beta agents are conservative, and rely on the alpha agents to provide advanced information on favorable regions of the search space. An agent selects its current role dynamically based on its current status value relative to the current status values of the other team members. Status is determined by some function of the agent's sensor readings, and is generally a measurement of source intensity at the agent's current location. Variations on the decision rules determining alpha and beta behavior produce different versions of the algorithm that lead to different global properties. The alpha-beta strategy is based on a simple finite-state machine that implements a form of Variable Structure Control (VSC). The VSC system changes the dynamics of the collective system by abruptly switching at defined states to alternative control laws. In VSC, Lyapunov's direct method is often used to design control surfaces which guide the system to a given goal. We introduce the alpha- beta algorithm and present an analysis of the equilibrium point and the global stability of the alpha-beta algorithm based on Lyapunov's method.

Prevalence of physical inactivity and associated factors among high school students from state's public schools.

PubMed

Ceschini, Fabio L; Andrade, Douglas R; Oliveira, Luis C; Araújo Júnior, Jorge F; Matsudo, Victor K R

2009-01-01

To describe the prevalence of physical inactivity and associated factors among high school students from state's public schools in the city of São Paulo, state of São Paulo, Brazil. Sixteen state's public schools were randomly selected according to the geographic areas of the city (North, South, East, and West). The sample consisted of 3,845 high school students in 2006. Physical inactivity was measured using the International Physical Activity Questionnaire (short IPAQ) and was defined as practicing moderate and/or vigorous physical activity for a period of less than 300 minutes per week. The independent variables analyzed were: gender, age, socioeconomic level, geographic area of the city, awareness of the Agita São Paulo program, participation in physical education classes, smoking, alcohol intake and time spent per day watching television. Three-level Poisson regression was used for assessing the variables, with a significance level of p < 0.05. The general prevalence of physical inactivity among adolescents in São Paulo was 62.5% (95%CI 60.5-64.1). The factors associated with physical inactivity were gender, age, socioeconomic level, geographic area of the city, awareness of the Agita São Paulo program, non-participation in physical education classes, smoking, alcohol intake and time spent per day watching television. It was concluded that the prevalence of physical inactivity among adolescents in São Paulo was high in all the geographic areas evaluated, and that sociodemographic and behavioral factors contributed significantly to physical inactivity.

Music training relates to the development of neural mechanisms of selective auditory attention.

PubMed

Strait, Dana L; Slater, Jessica; O'Connell, Samantha; Kraus, Nina

2015-04-01

Selective attention decreases trial-to-trial variability in cortical auditory-evoked activity. This effect increases over the course of maturation, potentially reflecting the gradual development of selective attention and inhibitory control. Work in adults indicates that music training may alter the development of this neural response characteristic, especially over brain regions associated with executive control: in adult musicians, attention decreases variability in auditory-evoked responses recorded over prefrontal cortex to a greater extent than in nonmusicians. We aimed to determine whether this musician-associated effect emerges during childhood, when selective attention and inhibitory control are under development. We compared cortical auditory-evoked variability to attended and ignored speech streams in musicians and nonmusicians across three age groups: preschoolers, school-aged children and young adults. Results reveal that childhood music training is associated with reduced auditory-evoked response variability recorded over prefrontal cortex during selective auditory attention in school-aged child and adult musicians. Preschoolers, on the other hand, demonstrate no impact of selective attention on cortical response variability and no musician distinctions. This finding is consistent with the gradual emergence of attention during this period and may suggest no pre-existing differences in this attention-related cortical metric between children who undergo music training and those who do not. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Selecting minimum dataset soil variables using PLSR as a regressive multivariate method

NASA Astrophysics Data System (ADS)

Stellacci, Anna Maria; Armenise, Elena; Castellini, Mirko; Rossi, Roberta; Vitti, Carolina; Leogrande, Rita; De Benedetto, Daniela; Ferrara, Rossana M.; Vivaldi, Gaetano A.

2017-04-01

Long-term field experiments and science-based tools that characterize soil status (namely the soil quality indices, SQIs) assume a strategic role in assessing the effect of agronomic techniques and thus in improving soil management especially in marginal environments. Selecting key soil variables able to best represent soil status is a critical step for the calculation of SQIs. Current studies show the effectiveness of statistical methods for variable selection to extract relevant information deriving from multivariate datasets. Principal component analysis (PCA) has been mainly used, however supervised multivariate methods and regressive techniques are progressively being evaluated (Armenise et al., 2013; de Paul Obade et al., 2016; Pulido Moncada et al., 2014). The present study explores the effectiveness of partial least square regression (PLSR) in selecting critical soil variables, using a dataset comparing conventional tillage and sod-seeding on durum wheat. The results were compared to those obtained using PCA and stepwise discriminant analysis (SDA). The soil data derived from a long-term field experiment in Southern Italy. On samples collected in April 2015, the following set of variables was quantified: (i) chemical: total organic carbon and nitrogen (TOC and TN), alkali-extractable C (TEC and humic substances - HA-FA), water extractable N and organic C (WEN and WEOC), Olsen extractable P, exchangeable cations, pH and EC; (ii) physical: texture, dry bulk density (BD), macroporosity (Pmac), air capacity (AC), and relative field capacity (RFC); (iii) biological: carbon of the microbial biomass quantified with the fumigation-extraction method. PCA and SDA were previously applied to the multivariate dataset (Stellacci et al., 2016). PLSR was carried out on mean centered and variance scaled data of predictors (soil variables) and response (wheat yield) variables using the PLS procedure of SAS/STAT. In addition, variable importance for projection (VIP) statistics was used to quantitatively assess the predictors most relevant for response variable estimation and then for variable selection (Andersen and Bro, 2010). PCA and SDA returned TOC and RFC as influential variables both on the set of chemical and physical data analyzed separately as well as on the whole dataset (Stellacci et al., 2016). Highly weighted variables in PCA were also TEC, followed by K, and AC, followed by Pmac and BD, in the first PC (41.2% of total variance); Olsen P and HA-FA in the second PC (12.6%), Ca in the third (10.6%) component. Variables enabling maximum discrimination among treatments for SDA were WEOC, on the whole dataset, humic substances, followed by Olsen P, EC and clay, in the separate data analyses. The highest PLS-VIP statistics were recorded for Olsen P and Pmac, followed by TOC, TEC, pH and Mg for chemical variables and clay, RFC and AC for the physical variables. Results show that different methods may provide different ranking of the selected variables and the presence of a response variable, in regressive techniques, may affect variable selection. Further investigation with different response variables and with multi-year datasets would allow to better define advantages and limits of single or combined approaches. Acknowledgment The work was supported by the projects "BIOTILLAGE, approcci innovative per il miglioramento delle performances ambientali e produttive dei sistemi cerealicoli no-tillage", financed by PSR-Basilicata 2007-2013, and "DESERT, Low-cost water desalination and sensor technology compact module" financed by ERANET-WATERWORKS 2014. References Andersen C.M. and Bro R., 2010. Variable selection in regression - a tutorial. Journal of Chemometrics, 24 728-737. Armenise et al., 2013. Developing a soil quality index to compare soil fitness for agricultural use under different managements in the mediterranean environment. Soil and Tillage Research, 130:91-98. de Paul Obade et al., 2016. A standardized soil quality index for diverse field conditions. Sci. Total Env. 541:424-434. Pulido Moncada et al., 2014. Data-driven analysis of soil quality indicators using limited data. Geoderma, 235:271-278. Stellacci et al., 2016. Comparison of different multivariate methods to select key soil variables for soil quality indices computation. XLV Congress of the Italian Society of Agronomy (SIA), Sassari, 20-22 September 2016.

Classification of debtor credit status and determination amount of credit risk by using linier discriminant function

NASA Astrophysics Data System (ADS)

Aidi, Muhammad Nur; Sari, Resty Indah

2012-05-01

A decision of credit that given by bank or another creditur must have a risk and it called credit risk. Credit risk is an investor's risk of loss arising from a borrower who does not make payments as promised. The substantial of credit risk can lead to losses for the banks and the debtor. To minimize this problem need a further study to identify a potential new customer before the decision given. Identification of debtor can using various approaches analysis, one of them is by using discriminant analysis. Discriminant analysis in this study are used to classify whether belonging to the debtor's good credit or bad credit. The result of this study are two discriminant functions that can identify new debtor. Before step built the discriminant function, selection of explanatory variables should be done. Purpose of selection independent variable is to choose the variable that can discriminate the group maximally. Selection variables in this study using different test, for categoric variable selection of variable using proportion chi-square test, and stepwise discriminant for numeric variable. The result of this study are two discriminant functions that can identify new debtor. The selected variables that can discriminating two groups of debtor maximally are status of existing checking account, credit history, credit amount, installment rate in percentage of disposable income, sex, age in year, other installment plans, and number of people being liable to provide maintenance. This classification produce a classification accuracy rate is good enough, that is equal to 74,70%. Debtor classification using discriminant analysis has risk level that is small enough, and it ranged beetwen 14,992% and 17,608%. Based on that credit risk rate, using discriminant analysis on the classification of credit status can be used effectively.

Mesoscale Convective Complex versus Non-Mesoscale Convective Complex Thunderstorms: A Comparison of Selected Meteorological Variables.

DTIC Science & Technology

1986-08-01

mean square errors for selected variables . . 34 8. Variable range and mean value for MCC and non-MCC cases . . 36 9. Alpha ( a ) levels at which the...Table 9. For each variable, the a level is listed at which the two mean values are determined to be significantly 38 Table 9. Alpha ( a ) levels at...vorticity advection None 700 mb vertical velocity forecast .20 different. These a levels express the probability of erroneously con- cluding that the

Cervical spine injuries and helmet laws: a population-based study.

PubMed

Dao, Haisar; Lee, Justin; Kermani, Reza; Minshall, Christian; Eriksson, Evert A; Gross, Ronald; Doben, Andrew R

2012-03-01

To assess the incidence of cervical spine (C-spine) injuries in patients admitted after motorcycle crash in states with mandatory helmet laws (MHL) compared with states without helmet laws or selective helmet laws. The Nationwide Inpatient Sample from the Healthcare and Utilization Project for the year 2008 was analyzed. International Classification of Diseases and Health Related Problems, Ninth Edition codes were used to identify patients with a diagnosis of motorcycle crash and C-spine injuries. National estimates were generated based on weighted analysis of the data. Outcome variables investigated were as follows: length of stay (LOS), in-hospital mortality, hospital teaching status, and discharge disposition. States were then stratified into states with MHL or selective helmet laws. A total of 30,117 discharges were identified. Of these, 2,041 (6.7%) patients had a C-spine injury. Patients in MHL states had a lower incidence of C-spine injuries (5.6 vs. 6.4%; p = 0.003) and less in-hospital mortality (1.8 vs. 2.6%; p = 0.0001). Patients older than 55 years were less likely to be discharged home (57.5% vs. 72.5%; p = 0.0001), more likely to die in-hospital (3.0% vs. 2.1%; p = 0.0001), and more likely to have a hospital LOS more than 21 days (7.7% vs. 6.2%; p = 0.0001). Patients admitted to the hospital in states with MHLs have decreased rate of C-spine injuries than those patients admitted in states with more flexible helmet laws. Patients older than 55 years are more likely to die in the hospital, have a prolonged LOS, and require services after discharge. III.

Does Breast Cancer Drive the Building of Survival Probability Models among States? An Assessment of Goodness of Fit for Patient Data from SEER Registries

PubMed

Khan, Hafiz; Saxena, Anshul; Perisetti, Abhilash; Rafiq, Aamrin; Gabbidon, Kemesha; Mende, Sarah; Lyuksyutova, Maria; Quesada, Kandi; Blakely, Summre; Torres, Tiffany; Afesse, Mahlet

2016-12-01

Background: Breast cancer is a worldwide public health concern and is the most prevalent type of cancer in women in the United States. This study concerned the best fit of statistical probability models on the basis of survival times for nine state cancer registries: California, Connecticut, Georgia, Hawaii, Iowa, Michigan, New Mexico, Utah, and Washington. Materials and Methods: A probability random sampling method was applied to select and extract records of 2,000 breast cancer patients from the Surveillance Epidemiology and End Results (SEER) database for each of the nine state cancer registries used in this study. EasyFit software was utilized to identify the best probability models by using goodness of fit tests, and to estimate parameters for various statistical probability distributions that fit survival data. Results: Statistical analysis for the summary of statistics is reported for each of the states for the years 1973 to 2012. Kolmogorov-Smirnov, Anderson-Darling, and Chi-squared goodness of fit test values were used for survival data, the highest values of goodness of fit statistics being considered indicative of the best fit survival model for each state. Conclusions: It was found that California, Connecticut, Georgia, Iowa, New Mexico, and Washington followed the Burr probability distribution, while the Dagum probability distribution gave the best fit for Michigan and Utah, and Hawaii followed the Gamma probability distribution. These findings highlight differences between states through selected sociodemographic variables and also demonstrate probability modeling differences in breast cancer survival times. The results of this study can be used to guide healthcare providers and researchers for further investigations into social and environmental factors in order to reduce the occurrence of and mortality due to breast cancer. Creative Commons Attribution License

Simultaneous state-parameter estimation supports the evaluation of data assimilation performance and measurement design for soil-water-atmosphere-plant system

NASA Astrophysics Data System (ADS)

Hu, Shun; Shi, Liangsheng; Zha, Yuanyuan; Williams, Mathew; Lin, Lin

2017-12-01

Improvements to agricultural water and crop managements require detailed information on crop and soil states, and their evolution. Data assimilation provides an attractive way of obtaining these information by integrating measurements with model in a sequential manner. However, data assimilation for soil-water-atmosphere-plant (SWAP) system is still lack of comprehensive exploration due to a large number of variables and parameters in the system. In this study, simultaneous state-parameter estimation using ensemble Kalman filter (EnKF) was employed to evaluate the data assimilation performance and provide advice on measurement design for SWAP system. The results demonstrated that a proper selection of state vector is critical to effective data assimilation. Especially, updating the development stage was able to avoid the negative effect of ;phenological shift;, which was caused by the contrasted phenological stage in different ensemble members. Simultaneous state-parameter estimation (SSPE) assimilation strategy outperformed updating-state-only (USO) assimilation strategy because of its ability to alleviate the inconsistency between model variables and parameters. However, the performance of SSPE assimilation strategy could deteriorate with an increasing number of uncertain parameters as a result of soil stratification and limited knowledge on crop parameters. In addition to the most easily available surface soil moisture (SSM) and leaf area index (LAI) measurements, deep soil moisture, grain yield or other auxiliary data were required to provide sufficient constraints on parameter estimation and to assure the data assimilation performance. This study provides an insight into the response of soil moisture and grain yield to data assimilation in SWAP system and is helpful for soil moisture movement and crop growth modeling and measurement design in practice.

Predicting punching acceleration from selected strength and power variables in elite karate athletes: a multiple regression analysis.

PubMed

Loturco, Irineu; Artioli, Guilherme Giannini; Kobal, Ronaldo; Gil, Saulo; Franchini, Emerson

2014-07-01

This study investigated the relationship between punching acceleration and selected strength and power variables in 19 professional karate athletes from the Brazilian National Team (9 men and 10 women; age, 23 ± 3 years; height, 1.71 ± 0.09 m; and body mass [BM], 67.34 ± 13.44 kg). Punching acceleration was assessed under 4 different conditions in a randomized order: (a) fixed distance aiming to attain maximum speed (FS), (b) fixed distance aiming to attain maximum impact (FI), (c) self-selected distance aiming to attain maximum speed, and (d) self-selected distance aiming to attain maximum impact. The selected strength and power variables were as follows: maximal dynamic strength in bench press and squat-machine, squat and countermovement jump height, mean propulsive power in bench throw and jump squat, and mean propulsive velocity in jump squat with 40% of BM. Upper- and lower-body power and maximal dynamic strength variables were positively correlated to punch acceleration in all conditions. Multiple regression analysis also revealed predictive variables: relative mean propulsive power in squat jump (W·kg-1), and maximal dynamic strength 1 repetition maximum in both bench press and squat-machine exercises. An impact-oriented instruction and a self-selected distance to start the movement seem to be crucial to reach the highest acceleration during punching execution. This investigation, while demonstrating strong correlations between punching acceleration and strength-power variables, also provides important information for coaches, especially for designing better training strategies to improve punching speed.

Not accounting for interindividual variability can mask habitat selection patterns: a case study on black bears.

PubMed

Lesmerises, Rémi; St-Laurent, Martin-Hugues

2017-11-01

Habitat selection studies conducted at the population scale commonly aim to describe general patterns that could improve our understanding of the limiting factors in species-habitat relationships. Researchers often consider interindividual variation in selection patterns to control for its effects and avoid pseudoreplication by using mixed-effect models that include individuals as random factors. Here, we highlight common pitfalls and possible misinterpretations of this strategy by describing habitat selection of 21 black bears Ursus americanus. We used Bayesian mixed-effect models and compared results obtained when using random intercept (i.e., population level) versus calculating individual coefficients for each independent variable (i.e., individual level). We then related interindividual variability to individual characteristics (i.e., age, sex, reproductive status, body condition) in a multivariate analysis. The assumption of comparable behavior among individuals was verified only in 40% of the cases in our seasonal best models. Indeed, we found strong and opposite responses among sampled bears and individual coefficients were linked to individual characteristics. For some covariates, contrasted responses canceled each other out at the population level. In other cases, interindividual variability was concealed by the composition of our sample, with the majority of the bears (e.g., old individuals and bears in good physical condition) driving the population response (e.g., selection of young forest cuts). Our results stress the need to consider interindividual variability to avoid misinterpretation and uninformative results, especially for a flexible and opportunistic species. This study helps to identify some ecological drivers of interindividual variability in bear habitat selection patterns.

A Multivariate Test of an Expanded Andersen Health Care Utilization Model for Complementary and Alternative Medicine (CAM) Use in African Americans

PubMed Central

Barner, Jamie; Bohman, Tom; Richards, Kristin

2009-01-01

Abstract Objectives The objectives of this study were (1) to determine which Andersen Model variables [predisposing, enabling, and need (PEN)] are related to complementary and alternative medicine (CAM) use by African Americans in the past 12 months; and (2) to determine whether the addition of disease states to the Model will explain significant variation in CAM use in the past 12 months. Design The 2002 National Health Interview Survey was used with 4256 African American adults (n = 23,828,268 weighted) selected as the study population. The dependent variable, CAM Past 12 Months, represented participants' use of at least 1 of 17 CAM modalities during the past 12 months. The Andersen Model variables [predisposing (e.g., age); enabling (e.g., insurance); and need (e.g., medical conditions)] and prevalent disease states (≥10%) comprised the independent variables. Logistic regression analyses, incorporating the sampling weights, were employed. Results Among predisposing factors, CAM use was associated with middle-aged to older, more educated, and female African Americans. Region (Northeast less likely than South) was the only significant enabling factor. Need factors had the most frequent relationships, with more medical conditions, more physician visits, better health status, prescription and over-the-counter medication use, more frequent exercise, and having activities of daily living limitations being associated with CAM use. After adjusting for PEN factors, the disease states of pain/aching joints, recurring pain, and migraine were related to CAM use. Conclusions African American CAM users are middle-aged to older, female, educated, and have more medical conditions (especially pain-related). Users report higher utilization of “traditional” care (e.g., physician visits), indicating that CAM is likely a complement to conventional treatment in this population. Health care providers should use these factors as prompts for inquiring about CAM use in African American patients. PMID:19678783

A multivariate test of an expanded Andersen Health Care utilization model for complementary and alternative medicine (CAM) use in African Americans.

PubMed

Brown, Carolyn; Barner, Jamie; Bohman, Tom; Richards, Kristin

2009-08-01

The objectives of this study were (1) to determine which Andersen Model variables [predisposing, enabling, and need (PEN)] are related to complementary and alternative medicine (CAM) use by African Americans in the past 12 months; and (2) to determine whether the addition of disease states to the Model will explain significant variation in CAM use in the past 12 months. The 2002 National Health Interview Survey was used with 4256 African American adults (n = 23,828,268 weighted) selected as the study population. The dependent variable, CAM Past 12 Months, represented participants' use of at least 1 of 17 CAM modalities during the past 12 months. The Andersen Model variables [predisposing (e.g., age); enabling (e.g., insurance); and need (e.g., medical conditions)] and prevalent disease states (> or =10%) comprised the independent variables. Logistic regression analyses, incorporating the sampling weights, were employed. Among predisposing factors, CAM use was associated with middle-aged to older, more educated, and female African Americans. Region (Northeast less likely than South) was the only significant enabling factor. Need factors had the most frequent relationships, with more medical conditions, more physician visits, better health status, prescription and over-the-counter medication use, more frequent exercise, and having activities of daily living limitations being associated with CAM use. After adjusting for PEN factors, the disease states of pain/aching joints, recurring pain, and migraine were related to CAM use. African American CAM users are middle-aged to older, female, educated, and have more medical conditions (especially pain-related). Users report higher utilization of "traditional" care (e.g., physician visits), indicating that CAM is likely a complement to conventional treatment in this population. Health care providers should use these factors as prompts for inquiring about CAM use in African American patients.

Using Multigroup-Multiphase Latent State-Trait Models to Study Treatment-Induced Changes in Intra-Individual State Variability: An Application to Smokers' Affect.

PubMed

Geiser, Christian; Griffin, Daniel; Shiffman, Saul

2016-01-01

Sometimes, researchers are interested in whether an intervention, experimental manipulation, or other treatment causes changes in intra-individual state variability. The authors show how multigroup-multiphase latent state-trait (MG-MP-LST) models can be used to examine treatment effects with regard to both mean differences and differences in state variability. The approach is illustrated based on a randomized controlled trial in which N = 338 smokers were randomly assigned to nicotine replacement therapy (NRT) vs. placebo prior to quitting smoking. We found that post quitting, smokers in both the NRT and placebo group had significantly reduced intra-individual affect state variability with respect to the affect items calm and content relative to the pre-quitting phase. This reduction in state variability did not differ between the NRT and placebo groups, indicating that quitting smoking may lead to a stabilization of individuals' affect states regardless of whether or not individuals receive NRT.

Using Multigroup-Multiphase Latent State-Trait Models to Study Treatment-Induced Changes in Intra-Individual State Variability: An Application to Smokers' Affect

PubMed Central

Geiser, Christian; Griffin, Daniel; Shiffman, Saul

2016-01-01

Sometimes, researchers are interested in whether an intervention, experimental manipulation, or other treatment causes changes in intra-individual state variability. The authors show how multigroup-multiphase latent state-trait (MG-MP-LST) models can be used to examine treatment effects with regard to both mean differences and differences in state variability. The approach is illustrated based on a randomized controlled trial in which N = 338 smokers were randomly assigned to nicotine replacement therapy (NRT) vs. placebo prior to quitting smoking. We found that post quitting, smokers in both the NRT and placebo group had significantly reduced intra-individual affect state variability with respect to the affect items calm and content relative to the pre-quitting phase. This reduction in state variability did not differ between the NRT and placebo groups, indicating that quitting smoking may lead to a stabilization of individuals' affect states regardless of whether or not individuals receive NRT. PMID:27499744