Nonlinear time series modeling and forecasting the seismic data of the Hindu Kush region

NASA Astrophysics Data System (ADS)

Khan, Muhammad Yousaf; Mittnik, Stefan

2018-01-01

In this study, we extended the application of linear and nonlinear time models in the field of earthquake seismology and examined the out-of-sample forecast accuracy of linear Autoregressive (AR), Autoregressive Conditional Duration (ACD), Self-Exciting Threshold Autoregressive (SETAR), Threshold Autoregressive (TAR), Logistic Smooth Transition Autoregressive (LSTAR), Additive Autoregressive (AAR), and Artificial Neural Network (ANN) models for seismic data of the Hindu Kush region. We also extended the previous studies by using Vector Autoregressive (VAR) and Threshold Vector Autoregressive (TVAR) models and compared their forecasting accuracy with linear AR model. Unlike previous studies that typically consider the threshold model specifications by using internal threshold variable, we specified these models with external transition variables and compared their out-of-sample forecasting performance with the linear benchmark AR model. The modeling results show that time series models used in the present study are capable of capturing the dynamic structure present in the seismic data. The point forecast results indicate that the AR model generally outperforms the nonlinear models. However, in some cases, threshold models with external threshold variables specification produce more accurate forecasts, indicating that specification of threshold time series models is of crucial importance. For raw seismic data, the ACD model does not show an improved out-of-sample forecasting performance over the linear AR model. The results indicate that the AR model is the best forecasting device to model and forecast the raw seismic data of the Hindu Kush region.

A Four Dimensional Spatio-Temporal Analysis of an Agricultural Dataset

PubMed Central

Donald, Margaret R.; Mengersen, Kerrie L.; Young, Rick R.

2015-01-01

While a variety of statistical models now exist for the spatio-temporal analysis of two-dimensional (surface) data collected over time, there are few published examples of analogous models for the spatial analysis of data taken over four dimensions: latitude, longitude, height or depth, and time. When taking account of the autocorrelation of data within and between dimensions, the notion of closeness often differs for each of the dimensions. Here, we consider a number of approaches to the analysis of such a dataset, which arises from an agricultural experiment exploring the impact of different cropping systems on soil moisture. The proposed models vary in their representation of the spatial correlation in the data, the assumed temporal pattern and choice of conditional autoregressive (CAR) and other priors. In terms of the substantive question, we find that response cropping is generally more effective than long fallow cropping in reducing soil moisture at the depths considered (100 cm to 220 cm). Thus, if we wish to reduce the possibility of deep drainage and increased groundwater salinity, the recommended cropping system is response cropping. PMID:26513746

Mathematical model with autoregressive process for electrocardiogram signals

NASA Astrophysics Data System (ADS)

Evaristo, Ronaldo M.; Batista, Antonio M.; Viana, Ricardo L.; Iarosz, Kelly C.; Szezech, José D., Jr.; Godoy, Moacir F. de

2018-04-01

The cardiovascular system is composed of the heart, blood and blood vessels. Regarding the heart, cardiac conditions are determined by the electrocardiogram, that is a noninvasive medical procedure. In this work, we propose autoregressive process in a mathematical model based on coupled differential equations in order to obtain the tachograms and the electrocardiogram signals of young adults with normal heartbeats. Our results are compared with experimental tachogram by means of Poincaré plot and dentrended fluctuation analysis. We verify that the results from the model with autoregressive process show good agreement with experimental measures from tachogram generated by electrical activity of the heartbeat. With the tachogram we build the electrocardiogram by means of coupled differential equations.

A multivariate spatial mixture model for areal data: examining regional differences in standardized test scores

PubMed Central

Neelon, Brian; Gelfand, Alan E.; Miranda, Marie Lynn

2013-01-01

Summary Researchers in the health and social sciences often wish to examine joint spatial patterns for two or more related outcomes. Examples include infant birth weight and gestational length, psychosocial and behavioral indices, and educational test scores from different cognitive domains. We propose a multivariate spatial mixture model for the joint analysis of continuous individual-level outcomes that are referenced to areal units. The responses are modeled as a finite mixture of multivariate normals, which accommodates a wide range of marginal response distributions and allows investigators to examine covariate effects within subpopulations of interest. The model has a hierarchical structure built at the individual level (i.e., individuals are nested within areal units), and thus incorporates both individual- and areal-level predictors as well as spatial random effects for each mixture component. Conditional autoregressive (CAR) priors on the random effects provide spatial smoothing and allow the shape of the multivariate distribution to vary flexibly across geographic regions. We adopt a Bayesian modeling approach and develop an efficient Markov chain Monte Carlo model fitting algorithm that relies primarily on closed-form full conditionals. We use the model to explore geographic patterns in end-of-grade math and reading test scores among school-age children in North Carolina. PMID:26401059

Hierarchical additive modeling of nonlinear association with spatial correlations--an application to relate alcohol outlet density and neighborhood assault rates.

PubMed

Yu, Qingzhao; Li, Bin; Scribner, Richard Allen

2009-06-30

Previous studies have suggested a link between alcohol outlets and assaults. In this paper, we explore the effects of alcohol availability on assaults at the census tract level over time. In addition, we use a natural experiment to check whether a sudden loss of alcohol outlets is associated with deeper decreasing in assault violence. Several features of the data raise statistical challenges: (1) the association between covariates (for example, the alcohol outlet density of each census tract) and the assault rates may be complex and therefore cannot be described using a linear model without covariates transformation, (2) the covariates may be highly correlated with each other, (3) there are a number of observations that have missing inputs, and (4) there is spatial association in assault rates at the census tract level. We propose a hierarchical additive model, where the nonlinear correlations and the complex interaction effects are modeled using the multiple additive regression trees and the residual spatial association in the assault rates that cannot be explained in the model are smoothed using a conditional autoregressive (CAR) method. We develop a two-stage algorithm that connects the nonparametric trees with CAR to look for important covariates associated with the assault rates, while taking into account the spatial association of assault rates in adjacent census tracts. The proposed method is applied to the Los Angeles assault data (1990-1999). To assess the efficiency of the method, the results are compared with those obtained from a hierarchical linear model. Copyright (c) 2009 John Wiley & Sons, Ltd.

An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

PubMed Central

Wang, Shiyao; Deng, Zhidong; Yin, Gang

2016-01-01

A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

PubMed

Wang, Shiyao; Deng, Zhidong; Yin, Gang

2016-02-24

A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.

(Re)evaluating the Implications of the Autoregressive Latent Trajectory Model Through Likelihood Ratio Tests of Its Initial Conditions.

PubMed

Ou, Lu; Chow, Sy-Miin; Ji, Linying; Molenaar, Peter C M

2017-01-01

The autoregressive latent trajectory (ALT) model synthesizes the autoregressive model and the latent growth curve model. The ALT model is flexible enough to produce a variety of discrepant model-implied change trajectories. While some researchers consider this a virtue, others have cautioned that this may confound interpretations of the model's parameters. In this article, we show that some-but not all-of these interpretational difficulties may be clarified mathematically and tested explicitly via likelihood ratio tests (LRTs) imposed on the initial conditions of the model. We show analytically the nested relations among three variants of the ALT model and the constraints needed to establish equivalences. A Monte Carlo simulation study indicated that LRTs, particularly when used in combination with information criterion measures, can allow researchers to test targeted hypotheses about the functional forms of the change process under study. We further demonstrate when and how such tests may justifiably be used to facilitate our understanding of the underlying process of change using a subsample (N = 3,995) of longitudinal family income data from the National Longitudinal Survey of Youth.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

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

Lu, Fengbin, E-mail: fblu@amss.ac.cn

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relationsmore » evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.« less

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

PubMed

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright © 2016 Elsevier Ltd. All rights reserved.

An experimental investigation of tobacco smoke pollution in cars.

PubMed

Sendzik, Taryn; Fong, Geoffrey T; Travers, Mark J; Hyland, Andrew

2009-06-01

Tobacco smoke pollution (TSP) has been identified as a serious public health threat. Although the number of jurisdictions that prohibit smoking in public places has increased rapidly, just a few successful attempts have been made to pass similar laws prohibiting smoking in cars, where the cabin space may contribute to concentrated exposure. In particular, TSP constitutes a potentially serious health hazard to children because of prolonged exposure and their small size. The present study investigated the levels of TSP in 18 cars via the measurement of fine respirable particles (<2.5 microns in diameter or PM(2.5)) under a variety of in vivo conditions. Car owners smoked a single cigarette in their cars in each of five controlled air-sampling conditions. Each condition varied on movement of the car, presence of air conditioning, open windows, and combinations of these airflow influences. Smoking just a single cigarette in a car generated extremely high average levels of PM(2.5): more than 3,800 microg/m3 in the condition with the least airflow (motionless car, windows closed). In moderate ventilation conditions (air conditioning or having the smoking driver hold the cigarette next to a half-open window), the average levels of PM(2.5) were reduced but still at significantly high levels (air conditioning = 844 microg/m3; holding cigarette next to a half-open window = 223 microg/m3). This study demonstrates that TSP in cars reaches unhealthy levels, even under realistic ventilation conditions, lending support to efforts occurring across a growing number of jurisdictions to educate people and prohibit smoking in cars in the presence of children.

Numerical limitations in application of vector autoregressive modeling and Granger causality to analysis of EEG time series

NASA Astrophysics Data System (ADS)

Kammerdiner, Alla; Xanthopoulos, Petros; Pardalos, Panos M.

2007-11-01

In this chapter a potential problem with application of the Granger-causality based on the simple vector autoregressive (VAR) modeling to EEG data is investigated. Although some initial studies tested whether the data support the stationarity assumption of VAR, the stability of the estimated model is rarely (if ever) been verified. In fact, in cases when the stability condition is violated the process may exhibit a random walk like behavior or even be explosive. The problem is illustrated by an example.

Level shift two-components autoregressive conditional heteroscedasticity modelling for WTI crude oil market

NASA Astrophysics Data System (ADS)

Sin, Kuek Jia; Cheong, Chin Wen; Hooi, Tan Siow

2017-04-01

This study aims to investigate the crude oil volatility using a two components autoregressive conditional heteroscedasticity (ARCH) model with the inclusion of abrupt jump feature. The model is able to capture abrupt jumps, news impact, clustering volatility, long persistence volatility and heavy-tailed distributed error which are commonly observed in the crude oil time series. For the empirical study, we have selected the WTI crude oil index from year 2000 to 2016. The results found that by including the multiple-abrupt jumps in ARCH model, there are significant improvements of estimation evaluations as compared with the standard ARCH models. The outcomes of this study can provide useful information for risk management and portfolio analysis in the crude oil markets.

An experimental investigation of tobacco smoke pollution in cars

PubMed Central

Sendzik, Taryn; Travers, Mark J.; Hyland, Andrew

2009-01-01

Introduction Tobacco smoke pollution (TSP) has been identified as a serious public health threat. Although the number of jurisdictions that prohibit smoking in public places has increased rapidly, just a few successful attempts have been made to pass similar laws prohibiting smoking in cars, where the cabin space may contribute to concentrated exposure. In particular, TSP constitutes a potentially serious health hazard to children because of prolonged exposure and their small size. Methods The present study investigated the levels of TSP in 18 cars via the measurement of fine respirable particles (<2.5 microns in diameter or PM2.5) under a variety of in vivo conditions. Car owners smoked a single cigarette in their cars in each of five controlled air-sampling conditions. Each condition varied on movement of the car, presence of air conditioning, open windows, and combinations of these airflow influences. Results Smoking just a single cigarette in a car generated extremely high average levels of PM2.5: more than 3,800 μg/m3 in the condition with the least airflow (motionless car, windows closed). In moderate ventilation conditions (air conditioning or having the smoking driver hold the cigarette next to a half-open window), the average levels of PM2.5 were reduced but still at significantly high levels (air conditioning = 844 μg/m3; holding cigarette next to a half-open window = 223 μg/m3). Discussion This study demonstrates that TSP in cars reaches unhealthy levels, even under realistic ventilation conditions, lending support to efforts occurring across a growing number of jurisdictions to educate people and prohibit smoking in cars in the presence of children. PMID:19351785

Spatial analysis of ambulance response times related to prehospital cardiac arrests in the city-state of Singapore.

PubMed

Earnest, Arul; Hock Ong, Marcus Eng; Shahidah, Nur; Min Ng, Wen; Foo, Chuanyang; Nott, David John

2012-01-01

The main objective of this study was to establish the spatial variation in ambulance response times for out-of-hospital cardiac arrests (OHCAs) in the city-state of Singapore. The secondary objective involved studying the relationships between various covariates, such as traffic condition and time and day of collapse, and ambulance response times. The study design was observational and ecological in nature. Data on OHCAs were collected from a nationally representative database for the period October 2001 to October 2004. We used the conditional autoregressive (CAR) model to analyze the data. Within the Bayesian framework of analysis, we used a Weibull regression model that took into account spatial random effects. The regression model was used to study the independent effects of each covariate. Our results showed that there was spatial heterogeneity in the ambulance response times in Singapore. Generally, areas in the far outskirts (suburbs), such as Boon Lay (in the west) and Sembawang (in the north), fared badly in terms of ambulance response times. This improved when adjusted for key covariates, including distance from the nearest fire station. Ambulance response time was also associated with better traffic conditions, weekend OHCAs, distance from the nearest fire station, and OHCAs occurring during nonpeak driving hours. For instance, the hazard ratio for good ambulance response time was 2.35 (95% credible interval [CI] 1.97-2.81) when traffic conditions were light and 1.72 (95% CI 1.51-1.97) when traffic conditions were moderate, as compared with heavy traffic. We found a clear spatial gradient for ambulance response times, with far-outlying areas' exhibiting poorer response times. Our study highlights the utility of this novel approach, which may be helpful for planning emergency medical services and public emergency responses.

Vibration based condition monitoring of a multistage epicyclic gearbox in lifting cranes

NASA Astrophysics Data System (ADS)

Assaad, Bassel; Eltabach, Mario; Antoni, Jérôme

2014-01-01

This paper proposes a model-based technique for detecting wear in a multistage planetary gearbox used by lifting cranes. The proposed method establishes a vibration signal model which deals with cyclostationary and autoregressive models. First-order cyclostationarity is addressed by the analysis of the time synchronous average (TSA) of the angular resampled vibration signal. Then an autoregressive model (AR) is applied to the TSA part in order to extract a residual signal containing pertinent fault signatures. The paper also explores a number of methods commonly used in vibration monitoring of planetary gearboxes, in order to make comparisons. In the experimental part of this study, these techniques are applied to accelerated lifetime test bench data for the lifting winch. After processing raw signals recorded with an accelerometer mounted on the outside of the gearbox, a number of condition indicators (CIs) are derived from the TSA signal, the residual autoregressive signal and other signals derived using standard signal processing methods. The goal is to check the evolution of the CIs during the accelerated lifetime test (ALT). Clarity and fluctuation level of the historical trends are finally considered as a criteria for comparing between the extracted CIs.

A Spatial Poisson Hurdle Model for Exploring Geographic Variation in Emergency Department Visits

PubMed Central

Neelon, Brian; Ghosh, Pulak; Loebs, Patrick F.

2012-01-01

Summary We develop a spatial Poisson hurdle model to explore geographic variation in emergency department (ED) visits while accounting for zero inflation. The model consists of two components: a Bernoulli component that models the probability of any ED use (i.e., at least one ED visit per year), and a truncated Poisson component that models the number of ED visits given use. Together, these components address both the abundance of zeros and the right-skewed nature of the nonzero counts. The model has a hierarchical structure that incorporates patient- and area-level covariates, as well as spatially correlated random effects for each areal unit. Because regions with high rates of ED use are likely to have high expected counts among users, we model the spatial random effects via a bivariate conditionally autoregressive (CAR) prior, which introduces dependence between the components and provides spatial smoothing and sharing of information across neighboring regions. Using a simulation study, we show that modeling the between-component correlation reduces bias in parameter estimates. We adopt a Bayesian estimation approach, and the model can be fit using standard Bayesian software. We apply the model to a study of patient and neighborhood factors influencing emergency department use in Durham County, North Carolina. PMID:23543242

Kepler AutoRegressive Planet Search: Motivation & Methodology

NASA Astrophysics Data System (ADS)

Caceres, Gabriel; Feigelson, Eric; Jogesh Babu, G.; Bahamonde, Natalia; Bertin, Karine; Christen, Alejandra; Curé, Michel; Meza, Cristian

2015-08-01

The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Auto-Regressive Moving-Average (ARMA) models, Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH), and related models are flexible, phenomenological methods used with great success to model stochastic temporal behaviors in many fields of study, particularly econometrics. Powerful statistical methods are implemented in the public statistical software environment R and its many packages. Modeling involves maximum likelihood fitting, model selection, and residual analysis. These techniques provide a useful framework to model stellar variability and are used in KARPS with the objective of reducing stellar noise to enhance opportunities to find as-yet-undiscovered planets. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; ARMA-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. We apply the procedures to simulated Kepler-like time series with known stellar and planetary signals to evaluate the effectiveness of the KARPS procedures. The ARMA-type modeling is effective at reducing stellar noise, but also reduces and transforms the transit signal into ingress/egress spikes. A periodogram based on the TCF is constructed to concentrate the signal of these periodic spikes. When a periodic transit is found, the model is displayed on a standard period-folded averaged light curve. We also illustrate the efficient coding in R.

Water balance models in one-month-ahead streamflow forecasting

USGS Publications Warehouse

Alley, William M.

1985-01-01

Techniques are tested that incorporate information from water balance models in making 1-month-ahead streamflow forecasts in New Jersey. The results are compared to those based on simple autoregressive time series models. The relative performance of the models is dependent on the month of the year in question. The water balance models are most useful for forecasts of April and May flows. For the stations in northern New Jersey, the April and May forecasts were made in order of decreasing reliability using the water-balance-based approaches, using the historical monthly means, and using simple autoregressive models. The water balance models were useful to a lesser extent for forecasts during the fall months. For the rest of the year the improvements in forecasts over those obtained using the simpler autoregressive models were either very small or the simpler models provided better forecasts. When using the water balance models, monthly corrections for bias are found to improve minimum mean-square-error forecasts as well as to improve estimates of the forecast conditional distributions.

Fetal bovine serum and human constitutive androstane receptor: Evidence for activation of the SV23 splice variant by artemisinin, artemether, and arteether in a serum-free cell culture system

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

Lau, Aik Jiang; Chang, Thomas K.H., E-mail: thomas.chang@ubc.ca

The naturally occurring SV23 splice variant of human constitutive androstane receptor (hCAR-SV23) is activated by di-(2-ethylhexyl)phthalate (DEHP), which is detected as a contaminant in fetal bovine serum (FBS). In our initial experiment, we compared the effect of dialyzed FBS, charcoal-stripped, dextran-treated FBS (CS-FBS), and regular FBS on the basal activity and ligand-activation of hCAR-SV23 in a cell-based reporter gene assay. In transfected HepG2 cells cultured in medium supplemented with 10% FBS, basal hCAR-SV23 activity varied with the type of FBS (regular > dialyzed > CS). DEHP increased hCAR-SV23 activity when 10% CS-FBS, but not regular FBS or dialyzed FBS, wasmore » used. With increasing concentrations (1–10%) of regular FBS or CS-FBS, hCAR-SV23 basal activity increased, whereas in DEHP-treated cells, hCAR-SV23 activity remained similar (regular FBS) or slightly increased (CS-FBS). Subsequent experiments identified a serum-free culture condition to detect DEHP activation of hCAR-SV23. Under this condition, artemisinin, artemether, and arteether increased hCAR-SV23 activity, whereas they decreased it in cells cultured in medium supplemented with 10% regular FBS. By comparison, FBS increased the basal activity of the wild-type isoform of hCAR (hCAR-WT), whereas it did not affect the basal activity of the SV24 splice variant (hCAR-SV24) or ligand activation of hCAR-SV24 and hCAR-WT by 6-(4-chlorophenyl)imidazo[2,1-b][1,3]thiazole-5-carbaldehyde O-(3,4-dichlorobenzyl)oxime (CITCO). The use of serum-free culture condition was suitable for detecting CITCO activation of hCAR-WT and hCAR-SV24. In conclusion, FBS leads to erroneous classification of pharmacological ligands of hCAR-SV23 in cell-based assays, but investigations on functional ligands of hCAR isoforms can be conducted in serum-free culture condition. - Highlights: • FBS leads to erroneous pharmacological classification of hCAR-SV23 ligands. • Artemisinin, artemether, and arteether activate hCAR-SV23 in the absence of FBS. • Serum-free culture condition can be used for identifying ligands of hCAR isoforms.« less

Explanation of power law behavior of autoregressive conditional duration processes based on the random multiplicative process

NASA Astrophysics Data System (ADS)

Sato, Aki-Hiro

2004-04-01

Autoregressive conditional duration (ACD) processes, which have the potential to be applied to power law distributions of complex systems found in natural science, life science, and social science, are analyzed both numerically and theoretically. An ACD(1) process exhibits the singular second order moment, which suggests that its probability density function (PDF) has a power law tail. It is verified that the PDF of the ACD(1) has a power law tail with an arbitrary exponent depending on a model parameter. On the basis of theory of the random multiplicative process a relation between the model parameter and the power law exponent is theoretically derived. It is confirmed that the relation is valid from numerical simulations. An application of the ACD(1) to intervals between two successive transactions in a foreign currency market is shown.

Explanation of power law behavior of autoregressive conditional duration processes based on the random multiplicative process.

PubMed

Sato, Aki-Hiro

2004-04-01

Autoregressive conditional duration (ACD) processes, which have the potential to be applied to power law distributions of complex systems found in natural science, life science, and social science, are analyzed both numerically and theoretically. An ACD(1) process exhibits the singular second order moment, which suggests that its probability density function (PDF) has a power law tail. It is verified that the PDF of the ACD(1) has a power law tail with an arbitrary exponent depending on a model parameter. On the basis of theory of the random multiplicative process a relation between the model parameter and the power law exponent is theoretically derived. It is confirmed that the relation is valid from numerical simulations. An application of the ACD(1) to intervals between two successive transactions in a foreign currency market is shown.

49 CFR 172.330 - Tank cars and multi-unit tank car tanks.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 2 2013-10-01 2013-10-01 false Tank cars and multi-unit tank car tanks. 172.330..., TRAINING REQUIREMENTS, AND SECURITY PLANS Marking § 172.330 Tank cars and multi-unit tank car tanks. (a... material— (1) In a tank car unless the following conditions are met: (i) The tank car must be marked on...

49 CFR 172.330 - Tank cars and multi-unit tank car tanks.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 2 2012-10-01 2012-10-01 false Tank cars and multi-unit tank car tanks. 172.330..., TRAINING REQUIREMENTS, AND SECURITY PLANS Marking § 172.330 Tank cars and multi-unit tank car tanks. (a... material— (1) In a tank car unless the following conditions are met: (i) The tank car must be marked on...

49 CFR 172.330 - Tank cars and multi-unit tank car tanks.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 2 2014-10-01 2014-10-01 false Tank cars and multi-unit tank car tanks. 172.330..., TRAINING REQUIREMENTS, AND SECURITY PLANS Marking § 172.330 Tank cars and multi-unit tank car tanks. (a... material— (1) In a tank car unless the following conditions are met: (i) The tank car must be marked on...

Ultrafast Saturation of Electronic-Resonance-Enhanced Coherent Anti-Stokes Raman Scattering and Comparison for Pulse Durations in the Nanosecond to Femtosecond Regime

DTIC Science & Technology

2016-02-05

electronic-resonance-enhanced CARS (ERE- CARS ) configuration is calculated. We demonstrate that while underdamping condition is a suffi- cient condition for...saturation of ERE- CARS with the long-pulse excitations, a transient-gain must be achieved to saturate ERE- CARS signal for ultrafast probe regime. We...ultrafast ERE- CARS . From a simplified analytical solution and a detailed numerical calculation based on density-matrix equations, the saturation threshold

49 CFR 174.114 - Record to be made of change of seals on “Cars loaded with Division 1.1 or 1.2 (explosive...

Code of Federal Regulations, 2010 CFR

2010-10-01

... car to its destination: RailroadPlaceDate Car InitialsCar NumberNumber or description of seal broken Number or description of seal used to reseal car Reasons for opening car Condition of load Name and...

Selective binding of carotenoids with a shorter conjugated chain to the LH2 antenna complex and those with a longer conjugated chain to the reaction center from Rubrivivax gelatinosus.

PubMed

Kakitani, Yoshinori; Fujii, Ritsuko; Hayakawa, Yoshihiro; Kurahashi, Masahiro; Koyama, Yasushi; Harada, Jiro; Shimada, Keizo

2007-06-19

Rubrivivax gelatinosus having both the spheroidene and spirilloxanthin biosynthetic pathways produces carotenoids (Cars) with a variety of conjugated chains, which consist of different numbers of conjugated double bonds (n), including the C=C (m) and C=O (o) bonds. When grown under anaerobic conditions, the wild type produces Cars for which n = m = 9-13, whereas under semiaerobic conditions, it additionally produces Cars for which n = m + o = 10 + 1, 13 + 1, and 13 + 2. On the other hand, a mutant, in which the latter pathway is genetically blocked, produces only Cars for which n = 9 and 10 under anaerobic conditions and n = 9, 10, and 10 + 1 under semianaerobic conditions. Those Cars that were extracted from the LH2 complex (LH2) and the reaction center (RC), isolated from the wild-type and the mutant Rvi. gelatinosus, were analyzed by HPLC, and their structures were determined by mass spectrometry and 1H NMR spectroscopy. The selective binding of Cars to those pigment-protein complexes has been characterized as follows. (1) Cars with a shorter conjugated chain are selectively bound to LH2 whereas Cars with a longer conjugated chain to the RC. (2) Shorter chain Cars with a hydroxyl group are bound to LH2 almost exclusively. This rule holds either in the absence or in the presence of the keto group. The natural selection of shorter chain Cars by LH2 and longer chain Cars by the RC is discussed, on the basis of the results now available, in relation to the light-harvesting and photoprotective functions of Cars.

Measurements of car-body lateral vibration induced by high-speed trains negotiating complex terrain sections under strong wind conditions

NASA Astrophysics Data System (ADS)

Liu, Dongrun; Lu, Zhaijun; Zhong, Mu; Cao, Tianpei; Chen, Dong; Xiong, Yupu

2018-02-01

Assessment of the vibration of high-speed trains negotiating complex sections of terrain under strong wind conditions is very important for research into the operation safety and comfort of passengers on high-speed trains. To assess the vibration of high-speed trains negotiating complex sections of terrain under strong wind conditions, we performed a field measurement when the train passes through typical sections of complex terrain along the Lanzhou-Xinjiang high-speed railway in China. We selected the lateral vibration conditions, including the roll angle and lateral displacement of car-body gravity centre through two typical representative sections (embankment-tunnel-embankment and embankment-rectangular transition-cutting) for analysis. The results show that the severe car-swaying phenomenon occurs when the high-speed train moves through the test section, and the car-body lateral vibration characteristic is related significantly to the state of the terrain and topography along the railway. The main causes for this car-swaying phenomenon may be the transitions between different windproof structures, and the greater the scale of the transition region between different windproof structures or landform changes, the more obvious the car-swaying phenomenon becomes. The lateral vibration of the car-body is relatively steady when the train is running through terrain with minor changes in topography, such as the windbreak installed on the bridge and embankment, but the tail car sways more violently than the head car. When the vehicle runs from the windbreak installed on the embankment into the tunnel (or in the opposite direction), the tail car sways more intensely than the head car, and the head car runs relatively stable in the tunnel.

Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models

ERIC Educational Resources Information Center

Price, Larry R.

2012-01-01

The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…

Characteristics of the transmission of autoregressive sub-patterns in financial time series

NASA Astrophysics Data System (ADS)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong

2014-09-01

There are many types of autoregressive patterns in financial time series, and they form a transmission process. Here, we define autoregressive patterns quantitatively through an econometrical regression model. We present a computational algorithm that sets the autoregressive patterns as nodes and transmissions between patterns as edges, and then converts the transmission process of autoregressive patterns in a time series into a network. We utilised daily Shanghai (securities) composite index time series to study the transmission characteristics of autoregressive patterns. We found statistically significant evidence that the financial market is not random and that there are similar characteristics between parts and whole time series. A few types of autoregressive sub-patterns and transmission patterns drive the oscillations of the financial market. A clustering effect on fluctuations appears in the transmission process, and certain non-major autoregressive sub-patterns have high media capabilities in the financial time series. Different stock indexes exhibit similar characteristics in the transmission of fluctuation information. This work not only proposes a distinctive perspective for analysing financial time series but also provides important information for investors.

Characteristics of the transmission of autoregressive sub-patterns in financial time series

PubMed Central

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong

2014-01-01

There are many types of autoregressive patterns in financial time series, and they form a transmission process. Here, we define autoregressive patterns quantitatively through an econometrical regression model. We present a computational algorithm that sets the autoregressive patterns as nodes and transmissions between patterns as edges, and then converts the transmission process of autoregressive patterns in a time series into a network. We utilised daily Shanghai (securities) composite index time series to study the transmission characteristics of autoregressive patterns. We found statistically significant evidence that the financial market is not random and that there are similar characteristics between parts and whole time series. A few types of autoregressive sub-patterns and transmission patterns drive the oscillations of the financial market. A clustering effect on fluctuations appears in the transmission process, and certain non-major autoregressive sub-patterns have high media capabilities in the financial time series. Different stock indexes exhibit similar characteristics in the transmission of fluctuation information. This work not only proposes a distinctive perspective for analysing financial time series but also provides important information for investors. PMID:25189200

Myeloid Conditioning with c-kit-Targeted CAR-T Cells Enables Donor Stem Cell Engraftment.

PubMed

Arai, Yasuyuki; Choi, Uimook; Corsino, Cristina I; Koontz, Sherry M; Tajima, Masaki; Sweeney, Colin L; Black, Mary A; Feldman, Steven A; Dinauer, Mary C; Malech, Harry L

2018-05-02

We report a novel approach to bone marrow (BM) conditioning using c-kit-targeted chimeric antigen receptor T (c-kit CAR-T) cells in mice. Previous reports using anti-c-kit or anti-CD45 antibody linked to a toxin such as saporin have been promising. We developed a distinctly different approach using c-kit CAR-T cells. Initial studies demonstrated in vitro killing of hematopoietic stem cells by c-kit CAR-T cells but poor expansion in vivo and poor migration of CAR-T cells into BM. Pre-treatment of recipient mice with low-dose cyclophosphamide (125 mg/kg) together with CXCR4 transduction in the CAR-T cells enhanced trafficking to and expansion in BM (<1%-13.1%). This resulted in significant depletion of the BM c-kit + population (9.0%-0.1%). Because congenic Thy1.1 CAR-T cells were used in the Thy1.2-recipient mice, anti-Thy1.1 antibody could be used to deplete CAR-T cells in vivo before donor BM transplant. This achieved 20%-40% multilineage engraftment. We applied this conditioning to achieve an average of 28% correction of chronic granulomatous disease mice by wild-type BM transplant. Our findings provide a proof of concept that c-kit CAR-T cells can achieve effective BM conditioning without chemo-/radiotherapy. Our work also demonstrates that co-expression of a trafficking receptor can enhance targeting of CAR-T cells to a designated tissue. Published by Elsevier Inc.

The use of telemetry in testing in high performance racing engines

NASA Astrophysics Data System (ADS)

Hauser, E.

Telemetry measurement data in mobile application and under difficult environmental conditions were recorded. All relevant racing car and engine parameters were measured: pressure, stress, temperature, acceleration, ignition, number of revolutions, control of electronic injection, and flow measurements on the car body. The difficult measuring conditions due to high voltage ignition, mechanical loads and vibrations impose special requirements on a telemetry system built in racing cars. It has to be compact, flexible, light, and mechanically robust and has to fulfil special sheilding conditions. The measured data are transfered to a stationary measurement car via a radio line, involving RF communication problems. The measured data are directly displayed and evaluated in the measurement car.

Detection and classification of subject-generated artifacts in EEG signals using autoregressive models.

PubMed

Lawhern, Vernon; Hairston, W David; McDowell, Kaleb; Westerfield, Marissa; Robbins, Kay

2012-07-15

We examine the problem of accurate detection and classification of artifacts in continuous EEG recordings. Manual identification of artifacts, by means of an expert or panel of experts, can be tedious, time-consuming and infeasible for large datasets. We use autoregressive (AR) models for feature extraction and characterization of EEG signals containing several kinds of subject-generated artifacts. AR model parameters are scale-invariant features that can be used to develop models of artifacts across a population. We use a support vector machine (SVM) classifier to discriminate among artifact conditions using the AR model parameters as features. Results indicate reliable classification among several different artifact conditions across subjects (approximately 94%). These results suggest that AR modeling can be a useful tool for discriminating among artifact signals both within and across individuals. Copyright © 2012 Elsevier B.V. All rights reserved.

Asymptotically stable phase synchronization revealed by autoregressive circle maps

NASA Astrophysics Data System (ADS)

Drepper, F. R.

2000-11-01

A specially designed of nonlinear time series analysis is introduced based on phases, which are defined as polar angles in spaces spanned by a finite number of delayed coordinates. A canonical choice of the polar axis and a related implicit estimation scheme for the potentially underlying autoregressive circle map (next phase map) guarantee the invertibility of reconstructed phase space trajectories to the original coordinates. The resulting Fourier approximated, invertibility enforcing phase space map allows us to detect conditional asymptotic stability of coupled phases. This comparatively general synchronization criterion unites two existing generalizations of the old concept and can successfully be applied, e.g., to phases obtained from electrocardiogram and airflow recordings characterizing cardiorespiratory interaction.

Calibration of the heat balance model for prediction of car climate

NASA Astrophysics Data System (ADS)

Pokorný, Jan; Fišer, Jan; Jícha, Miroslav

2012-04-01

In the paper, the authors refer to development a heat balance model to predict car climate and power heat load. Model is developed in Modelica language using Dymola as interpreter. It is a dynamical system, which describes a heat exchange between car cabin and ambient. Inside a car cabin, there is considered heat exchange between air zone, interior and air-conditioning system. It is considered 1D heat transfer with a heat accumulation and a relative movement Sun respect to the car cabin, whilst car is moving. Measurements of the real operating conditions of gave us data for model calibration. The model was calibrated for Škoda Felicia parking-summer scenarios.

The microbiological quality of air improves when using air conditioning systems in cars.

PubMed

Vonberg, Ralf-Peter; Gastmeier, Petra; Kenneweg, Björn; Holdack-Janssen, Hinrich; Sohr, Dorit; Chaberny, Iris F

2010-06-01

Because of better comfort, air conditioning systems are a common feature in automobiles these days. However, its impact on the number of particles and microorganisms inside the vehicle--and by this its impact on the risk of an allergic reaction--is yet unknown. Over a time period of 30 months, the quality of air was investigated in three different types of cars (VW Passat, VW Polo FSI, Seat Alhambra) that were all equipped with a automatic air conditioning system. Operation modes using fresh air from outside the car as well as circulating air from inside the car were examined. The total number of microorganisms and the number of mold spores were measured by impaction in a high flow air sampler. Particles of 0.5 to 5.0 microm diameter were counted by a laser particle counter device. Overall 32 occasions of sampling were performed. The concentration of microorganisms outside the cars was always higher than it was inside the cars. Few minutes after starting the air conditioning system the total number of microorganisms was reduced by 81.7%, the number of mold spores was reduced by 83.3%, and the number of particles was reduced by 87.8%. There were no significant differences neither between the types of cars nor between the types of operation mode of the air conditioning system (fresh air vs. circulating air). All parameters that were looked for in this study improved during utilization of the car's air conditioning system. We believe that the risk of an allergic reaction will be reduced during use also. Nevertheless, we recommend regular maintenance of the system and replacement of older filters after defined changing intervals.

The microbiological quality of air improves when using air conditioning systems in cars

PubMed Central

2010-01-01

Background Because of better comfort, air conditioning systems are a common feature in automobiles these days. However, its impact on the number of particles and microorganisms inside the vehicle - and by this its impact on the risk of an allergic reaction - is yet unknown. Methods Over a time period of 30 months, the quality of air was investigated in three different types of cars (VW Passat, VW Polo FSI, Seat Alhambra) that were all equipped with a automatic air conditioning system. Operation modes using fresh air from outside the car as well as circulating air from inside the car were examined. The total number of microorganisms and the number of mold spores were measured by impaction in a high flow air sampler. Particles of 0.5 to 5.0 μm diameter were counted by a laser particle counter device. Results Overall 32 occasions of sampling were performed. The concentration of microorganisms outside the cars was always higher than it was inside the cars. Few minutes after starting the air conditioning system the total number of microorganisms was reduced by 81.7%, the number of mold spores was reduced by 83.3%, and the number of particles was reduced by 87.8%. There were no significant differences neither between the types of cars nor between the types of operation mode of the air conditioning system (fresh air vs. circulating air). All parameters that were looked for in this study improved during utilization of the car's air conditioning system. Conclusions We believe that the risk of an allergic reaction will be reduced during use also. Nevertheless, we recommend regular maintenance of the system and replacement of older filters after defined changing intervals. PMID:20515449

Chosen risk level during car-following in adverse weather conditions.

PubMed

Hjelkrem, Odd André; Ryeng, Eirin Olaussen

2016-10-01

This study examines how precipitation, light conditions and surface conditions affect the drivers' risk perception. An indicator CRI (Chosen Risk Index) is defined, which describes the chosen risk level for drivers in a car-following situation. The dataset contains about 70 000 observations of driver behaviour and weather status on a rural road. Based on the theory of risk homeostasis and an assumption that driving behaviour in situations with daylight, dry road and no precipitation reflects drivers' target level of risk, generalised linear models (GLM) were estimated for cars and trucks separately to reveal the effect of adverse weather conditions on risk perception. The analyses show that both car and truck drivers perceive the highest risk when driving on snow covered roads. For car drivers, a snow covered road in combination with moderate rain or light snow are the factors which lowers the CRI the most. For trucks, snow cover and partially covered roads significantly lowers the CRI, while precipitation did not seem to impose any higher risk. Interaction effects were found for car drivers only. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of Prototype Head Shield for Hazardous Material Tank Car

DOT National Transportation Integrated Search

1976-12-01

The structural integrity of a prototype tank car head shield for hazardous material railroad tank cars was evaluated under conditions of freight car coupling at moderate to high speeds. This is one of the most severe environments encountered in norma...

PIV Analysis Comparing Aerodynamic Downforce Devices on Race Car in Water Tunnel

NASA Astrophysics Data System (ADS)

Hellman, Sam; Tkacik, Peter; Uddin, Mesbah; Kelly, Scott

2010-11-01

There have been claims that the rear wing on the NASCAR Car of Tomorrow (COT) race car causes lift in the condition where the car spins during a crash and is traveling backwards down the track at a high rate of speed. When enough lift is generated, the race car can lose control and even fly off of the track surface completely. To address this concern, a new rear spoiler was designed by NASCAR to replace the wing and prevent this dangerous condition. Flow characteristics of both the rear wing and the new spoiler are qualitatively analyzed using particle image velocimetry (PIV). The experiment is done in a continuous flow water tunnel using a simplified 10% scale model COT. Flow structures are identified and compared for both the wing and spoiler. The same conditions are also reviewed when the car is traveling backwards as it might during a crash. The cause of the lift generated by the rear wing when in reverse is shown.

Two dynamic regimes in the human gut microbiome

PubMed Central

Smillie, Chris S.; Alm, Eric J.

2017-01-01

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)—a multivariate method developed for econometrics—to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes. PMID:28222117

Two dynamic regimes in the human gut microbiome.

PubMed

Gibbons, Sean M; Kearney, Sean M; Smillie, Chris S; Alm, Eric J

2017-02-01

The gut microbiome is a dynamic system that changes with host development, health, behavior, diet, and microbe-microbe interactions. Prior work on gut microbial time series has largely focused on autoregressive models (e.g. Lotka-Volterra). However, we show that most of the variance in microbial time series is non-autoregressive. In addition, we show how community state-clustering is flawed when it comes to characterizing within-host dynamics and that more continuous methods are required. Most organisms exhibited stable, mean-reverting behavior suggestive of fixed carrying capacities and abundant taxa were largely shared across individuals. This mean-reverting behavior allowed us to apply sparse vector autoregression (sVAR)-a multivariate method developed for econometrics-to model the autoregressive component of gut community dynamics. We find a strong phylogenetic signal in the non-autoregressive co-variance from our sVAR model residuals, which suggests niche filtering. We show how changes in diet are also non-autoregressive and that Operational Taxonomic Units strongly correlated with dietary variables have much less of an autoregressive component to their variance, which suggests that diet is a major driver of microbial dynamics. Autoregressive variance appears to be driven by multi-day recovery from frequent facultative anaerobe blooms, which may be driven by fluctuations in luminal redox. Overall, we identify two dynamic regimes within the human gut microbiota: one likely driven by external environmental fluctuations, and the other by internal processes.

Estimating time-varying conditional correlations between stock and foreign exchange markets

NASA Astrophysics Data System (ADS)

Tastan, Hüseyin

2006-02-01

This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.

Dual direction blower system powered by solar energy to reduce car cabin temperature in open parking condition

NASA Astrophysics Data System (ADS)

Hamdan, N. S.; Radzi, M. F. M.; Damanhuri, A. A. M.; Mokhtar, S. N.

2017-10-01

El-nino phenomenon that strikes Malaysia with temperature recorded more than 35°C can lead to extreme temperature rise in car cabin up to 80°C. Various problems will arise due to this extreme rising of temperature such as the occupant are vulnerable to heat stroke, emission of benzene gas that can cause cancer due to reaction of high temperature with interior compartments, and damage of compartments in the car. The current solution available to reduce car cabin temperature including tinted of window and portable heat rejection device that are available in the market. As an alternative to reduce car cabin temperature, this project modifies the car’s air conditioning blower motor into dual direction powered by solar energy and identifies its influence to temperature inside the car, parked under scorching sun. By reducing the car cabin temperature up to 10°C which equal to 14% of reduction in the car cabin temperature, this simple proposed system aims to provide comfort to users due to its capability in improving the quality of air and moisture in the car cabin.

Full Hybrid: Overview

Science.gov Websites

conditions. stage graphic: vertical blue rule Main stage: See through car with battery, engine, generator , power split device, and electric motor visible. The car is stopped at an intersection. Main stage: See through car with battery, engine, generator, power split device, and electric motor visible. The car is

A Global Genomic Screening Strategy Reveals Diverse Activators of Constitutive Activated Receptor (CAR)

EPA Science Inventory

A comprehensive survey of conditions that activate CAR in the mouse liver has not been carried out but would be useful in understanding their impact on CAR-dependent liver tumor induction. A gene signature dependent on CAR activation was identified by comparing the transcript pr...

Impact of global financial crisis on precious metals returns: An application of ARCH and GARCH methods

NASA Astrophysics Data System (ADS)

Ismail, Mohd Tahir; Abdullah, Nurul Ain; Abdul Karim, Samsul Ariffin

2013-04-01

This paper is focusing on seeing the resilient of precious metals returns in facing the global financial crisis and provides a new guide for the investors before making investment decisions on precious metals. Four types of precious metals returns which are the variables selected in this study. The precious metals are gold, silver, bronze and platinum. All the variables are transferred to natural logarithm (ln). Daily data over the period 2 January 1995 to 30 December 2011 is used. Unit root tests that involve Augmented Dickey-Fuller (ADF) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests have been employed in determining the stationarity of the variables. Autoregressive Conditional Heteroscedasticity (ARCH) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) methods have been applied in measuring the impact of global financial crisis on precious metals returns. The result shows that investing in platinum is less risky compared to the other precious metals because it is not influence by the crisis period.

Exploring the Mechanisms of Ecological Land Change Based on the Spatial Autoregressive Model: A Case Study of the Poyang Lake Eco-Economic Zone, China

PubMed Central

Xie, Hualin; Liu, Zhifei; Wang, Peng; Liu, Guiying; Lu, Fucai

2013-01-01

Ecological land is one of the key resources and conditions for the survival of humans because it can provide ecosystem services and is particularly important to public health and safety. It is extremely valuable for effective ecological management to explore the evolution mechanisms of ecological land. Based on spatial statistical analyses, we explored the spatial disparities and primary potential drivers of ecological land change in the Poyang Lake Eco-economic Zone of China. The results demonstrated that the global Moran’s I value is 0.1646 during the 1990 to 2005 time period and indicated significant positive spatial correlation (p < 0.05). The results also imply that the clustering trend of ecological land changes weakened in the study area. Some potential driving forces were identified by applying the spatial autoregressive model in this study. The results demonstrated that the higher economic development level and industrialization rate were the main drivers for the faster change of ecological land in the study area. This study also tested the superiority of the spatial autoregressive model to study the mechanisms of ecological land change by comparing it with the traditional linear regressive model. PMID:24384778

Comparison of six methods for the detection of causality in a bivariate time series

NASA Astrophysics Data System (ADS)

Krakovská, Anna; Jakubík, Jozef; Chvosteková, Martina; Coufal, David; Jajcay, Nikola; Paluš, Milan

2018-04-01

In this comparative study, six causality detection methods were compared, namely, the Granger vector autoregressive test, the extended Granger test, the kernel version of the Granger test, the conditional mutual information (transfer entropy), the evaluation of cross mappings between state spaces, and an assessment of predictability improvement due to the use of mixed predictions. Seven test data sets were analyzed: linear coupling of autoregressive models, a unidirectional connection of two Hénon systems, a unidirectional connection of chaotic systems of Rössler and Lorenz type and of two different Rössler systems, an example of bidirectionally connected two-species systems, a fishery model as an example of two correlated observables without a causal relationship, and an example of mediated causality. We tested not only 20 000 points long clean time series but also noisy and short variants of the data. The standard and the extended Granger tests worked only for the autoregressive models. The remaining methods were more successful with the more complex test examples, although they differed considerably in their capability to reveal the presence and the direction of coupling and to distinguish causality from mere correlation.

Methodology for the AutoRegressive Planet Search (ARPS) Project

NASA Astrophysics Data System (ADS)

Feigelson, Eric; Caceres, Gabriel; ARPS Collaboration

2018-01-01

The detection of periodic signals of transiting exoplanets is often impeded by the presence of aperiodic photometric variations. This variability is intrinsic to the host star in space-based observations (typically arising from magnetic activity) and from observational conditions in ground-based observations. The most common statistical procedures to remove stellar variations are nonparametric, such as wavelet decomposition or Gaussian Processes regression. However, many stars display variability with autoregressive properties, wherein later flux values are correlated with previous ones. Providing the time series is evenly spaced, parametric autoregressive models can prove very effective. Here we present the methodology of the Autoregessive Planet Search (ARPS) project which uses Autoregressive Integrated Moving Average (ARIMA) models to treat a wide variety of stochastic short-memory processes, as well as nonstationarity. Additionally, we introduce a planet-search algorithm to detect periodic transits in the time-series residuals after application of ARIMA models. Our matched-filter algorithm, the Transit Comb Filter (TCF), replaces the traditional box-fitting step. We construct a periodogram based on the TCF to concentrate the signal of these periodic spikes. Various features of the original light curves, the ARIMA fits, the TCF periodograms, and folded light curves at peaks of the TCF periodogram can then be collected to provide constraints for planet detection. These features provide input into a multivariate classifier when a training set is available. The ARPS procedure has been applied NASA's Kepler mission observations of ~200,000 stars (Caceres, Dissertation Talk, this meeting) and will be applied in the future to other datasets.

How do CARs work?

PubMed Central

Davila, Marco L.; Brentjens, Renier; Wang, Xiuyan; Rivière, Isabelle; Sadelain, Michel

2012-01-01

Second-generation chimeric antigen receptors (CARs) are powerful tools to redirect antigen-specific T cells independently of HLA-restriction. Recent clinical studies evaluating CD19-targeted T cells in patients with B-cell malignancies demonstrate the potency of CAR-engineered T cells. With results from 28 subjects enrolled by five centers conducting studies in patients with chronic lymphocytic leukemia (CLL) or lymphoma, some insights into the parameters that determine T-cell function and clinical outcome of CAR-based approaches are emerging. These parameters involve CAR design, T-cell production methods, conditioning chemotherapy as well as patient selection. Here, we discuss the potential relevance of these findings and in particular the interplay between the adoptive transfer of T cells and pre-transfer patient conditioning. PMID:23264903

Incorporating measurement error in n = 1 psychological autoregressive modeling.

PubMed

Schuurman, Noémi K; Houtveen, Jan H; Hamaker, Ellen L

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30-50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters.

Peroxisome proliferator-activated receptor (PPAR)-binding protein (PBP) but not PPAR-interacting protein (PRIP) is required for nuclear translocation of constitutive androstane receptor in mouse liver.

PubMed

Guo, Dongsheng; Sarkar, Joy; Ahmed, Mohamed R; Viswakarma, Navin; Jia, Yuzhi; Yu, Songtao; Sambasiva Rao, M; Reddy, Janardan K

2006-08-25

The constitutive androstane receptor (CAR) regulates transcription of phenobarbital-inducible genes that encode xenobiotic-metabolizing enzymes in liver. CAR is localized to the hepatocyte cytoplasm but to be functional, it translocates into the nucleus in the presence of phenobarbital-like CAR ligands. We now demonstrate that adenovirally driven EGFP-CAR, as expected, translocates into the nucleus of normal wild-type hepatocytes following phenobarbital treatment under both in vivo and in vitro conditions. Using this approach we investigated the role of transcription coactivators PBP and PRIP in the translocation of EGFP-CAR into the nucleus of PBP and PRIP liver conditional null mouse hepatocytes. We show that coactivator PBP is essential for nuclear translocation of CAR but not PRIP. Adenoviral expression of both PBP and EGFP-CAR restored phenobarbital-mediated nuclear translocation of exogenously expressed CAR in PBP null livers in vivo and in PBP null primary hepatocytes in vitro. CAR translocation into the nucleus of PRIP null livers resulted in the induction of CAR target genes such as CYP2B10, necessary for the conversion of acetaminophen to its hepatotoxic intermediate metabolite, N-acetyl-p-benzoquinone imine. As a consequence, PRIP-deficiency in liver did not protect from acetaminophen-induced hepatic necrosis, unlike that exerted by PBP deficiency. These results establish that transcription coactivator PBP plays a pivotal role in nuclear localization of CAR, that it is likely that PBP either enhances nuclear import or nuclear retention of CAR in hepatocytes, and that PRIP is redundant for CAR function.

Fouling resistance prediction using artificial neural network nonlinear auto-regressive with exogenous input model based on operating conditions and fluid properties correlations

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

Biyanto, Totok R.

Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO{sub 2} emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model aremore » flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.« less

Impact of smoking on in-vehicle fine particle exposure during driving

NASA Astrophysics Data System (ADS)

Sohn, Hongji; Lee, Kiyoung

2010-09-01

Indoor smoking ban in public places can reduce secondhand smoke (SHS) exposure. However, smoking in cars and homes has continued. The purpose of this study was to assess particulate matter less than 2.5 μm (PM 2.5) concentration in moving cars with different window opening conditions. The PM 2.5 level was measured by an aerosol spectrometer inside and outside moving cars simultaneously, along with ultrafine particle (UFP) number concentration, speed, temperature and humidity inside cars. Two sport utility vehicles were used. Three different ventilation conditions were evaluated by up to 20 repeated experiments. In the pre-smoking phase, average in-vehicle PM 2.5 concentrations were 16-17 μg m -3. Regardless of different window opening conditions, the PM 2.5 levels promptly increased when smoking occurred and decreased after cigarette was extinguished. Although only a single cigarette was smoked, the average PM 2.5 levels were 506-1307 μg m -3 with different window opening conditions. When smoking was ceased, the average PM 2.5 levels for 15 min were several times higher than the US National Ambient Air Quality Standard of 35 μg m -3. It took longer than 10 min to reach the level of the pre-smoking phase. Although UFP levels had a similar temporal profile of PM 2.5, the increased levels during the smoking phase were relatively small. This study demonstrated that the SHS exposure in cars with just a single cigarette being smoked could exceed the US EPA NAAQS under realistic window opening conditions. Therefore, the findings support the need for public education against smoking in cars and advocacy for a smoke-free car policy.

Characterization of extremely low frequency magnetic fields from diesel, gasoline and hybrid cars under controlled conditions.

PubMed

Hareuveny, Ronen; Sudan, Madhuri; Halgamuge, Malka N; Yaffe, Yoav; Tzabari, Yuval; Namir, Daniel; Kheifets, Leeka

2015-01-30

This study characterizes extremely low frequency (ELF) magnetic field (MF) levels in 10 car models. Extensive measurements were conducted in three diesel, four gasoline, and three hybrid cars, under similar controlled conditions and negligible background fields. Averaged over all four seats under various driving scenarios the fields were lowest in diesel cars (0.02 μT), higher for gasoline (0.04-0.05 μT) and highest in hybrids (0.06-0.09 μT), but all were in-line with daily exposures from other sources. Hybrid cars had the highest mean and 95th percentile MF levels, and an especially large percentage of measurements above 0.2 μT. These parameters were also higher for moving conditions compared to standing while idling or revving at 2500 RPM and higher still at 80 km/h compared to 40 km/h. Fields in non-hybrid cars were higher at the front seats, while in hybrid cars they were higher at the back seats, particularly the back right seat where 16%-69% of measurements were greater than 0.2 μT. As our results do not include low frequency fields (below 30 Hz) that might be generated by tire rotation, we suggest that net currents flowing through the cars' metallic chassis may be a possible source of MF. Larger surveys in standardized and well-described settings should be conducted with different types of vehicles and with spectral analysis of fields including lower frequencies due to magnetization of tires.

PROJECT REPORT : Alaska-Metro/Rural Deployment Project CARS/511 – Anchorage Integration

DOT National Transportation Integrated Search

2009-03-19

The Alaska Department of Transportation & Public Facilities (ADOT&PF) initiated the Alaska Travel Information System by joining the Condition Acquisition & Reporting System/511 (CARS/511) Pooled Fund in October 2002. CARS was jointly developed by the...

Causal conditionals and counterfactuals

PubMed Central

Frosch, Caren A.; Byrne, Ruth M.J.

2012-01-01

Causal counterfactuals e.g., ‘if the ignition key had been turned then the car would have started’ and causal conditionals e.g., ‘if the ignition key was turned then the car started’ are understood by thinking about multiple possibilities of different sorts, as shown in six experiments using converging evidence from three different types of measures. Experiments 1a and 1b showed that conditionals that comprise enabling causes, e.g., ‘if the ignition key was turned then the car started’ primed people to read quickly conjunctions referring to the possibility of the enabler occurring without the outcome, e.g., ‘the ignition key was turned and the car did not start’. Experiments 2a and 2b showed that people paraphrased causal conditionals by using causal or temporal connectives (because, when), whereas they paraphrased causal counterfactuals by using subjunctive constructions (had…would have). Experiments 3a and 3b showed that people made different inferences from counterfactuals presented with enabling conditions compared to none. The implications of the results for alternative theories of conditionals are discussed. PMID:22858874

Spatial analysis of paediatric swimming pool submersions by housing type.

PubMed

Shenoi, Rohit P; Levine, Ned; Jones, Jennifer L; Frost, Mary H; Koerner, Christine E; Fraser, John J

2015-08-01

Drowning is a major cause of unintentional childhood death. The relationship between childhood swimming pool submersions, neighbourhood sociodemographics, housing type and swimming pool location was examined in Harris County, Texas. Childhood pool submersion incidents were examined for spatial clustering using the Nearest Neighbor Hierarchical Cluster (Nnh) algorithm. To relate submersions to predictive factors, an Markov Chain Monte Carlo (MCMC) Poisson-Lognormal-Conditional Autoregressive (CAR) spatial regression model was tested at the census tract level. There were 260 submersions; 49 were fatal. Forty-two per cent occurred at single-family residences and 36% at multifamily residential buildings. The risk of a submersion was 2.7 times higher for a child at a multifamily than a single-family residence and 28 times more likely in a multifamily swimming pool than a single family pool. However, multifamily submersions were clustered because of the concentration of such buildings with pools. Spatial clustering did not occur in single-family residences. At the tract level, submersions in single-family and multifamily residences were best predicted by the number of pools by housing type and the number of children aged 0-17 by housing type. Paediatric swimming pool submersions in multifamily buildings are spatially clustered. The likelihood of submersions is higher for children who live in multifamily buildings with pools than those who live in single-family homes with pools. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Evaluation of service-induced residual stresses in railroad commuter car wheels

DOT National Transportation Integrated Search

1999-11-01

Analyses of the effects of service conditions on the distribution of : residual stresses in railroad commuter car wheels are presented. Novel : software has been applied to estimate the effects of service conditions : on the as-manufactured state of ...

Get Over It! A Multilevel Threshold Autoregressive Model for State-Dependent Affect Regulation.

PubMed

De Haan-Rietdijk, Silvia; Gottman, John M; Bergeman, Cindy S; Hamaker, Ellen L

2016-03-01

Intensive longitudinal data provide rich information, which is best captured when specialized models are used in the analysis. One of these models is the multilevel autoregressive model, which psychologists have applied successfully to study affect regulation as well as alcohol use. A limitation of this model is that the autoregressive parameter is treated as a fixed, trait-like property of a person. We argue that the autoregressive parameter may be state-dependent, for example, if the strength of affect regulation depends on the intensity of affect experienced. To allow such intra-individual variation, we propose a multilevel threshold autoregressive model. Using simulations, we show that this model can be used to detect state-dependent regulation with adequate power and Type I error. The potential of the new modeling approach is illustrated with two empirical applications that extend the basic model to address additional substantive research questions.

Small passenger car transmission test: Dodge Omni A-404 transmission

NASA Technical Reports Server (NTRS)

Bujold, M. P.

1980-01-01

The small passenger car transmission test was initiated to supply electric vehicle manufacturers with technical information regarding the performance of commercially available transmissions. This transmission was tested in accordance with a passenger car automatic transmission test code (SAE J65lb) which required drive performance, coast performance, and no load test conditions. Under these test conditions, the transmission attained maximum efficiencies in the mid eighty percent range for both drive performance test and coast performance tests.

Protein Activity of the Fusarium fujikuroi Rhodopsins CarO and OpsA and Their Relation to Fungus–Plant Interaction

PubMed Central

Adam, Alexander; Deimel, Stephan; Pardo-Medina, Javier; García-Martínez, Jorge; Konte, Tilen; Limón, M. Carmen; Avalos, Javier

2018-01-01

Fungi possess diverse photosensory proteins that allow them to perceive different light wavelengths and to adapt to changing light conditions in their environment. The biological and physiological roles of the green light-sensing rhodopsins in fungi are not yet resolved. The rice plant pathogen Fusarium fujikuroi exhibits two different rhodopsins, CarO and OpsA. CarO was previously characterized as a light-driven proton pump. We further analyzed the pumping behavior of CarO by patch-clamp experiments. Our data show that CarO pumping activity is strongly augmented in the presence of the plant hormone indole-3-acetic acid and in sodium acetate, in a dose-dependent manner under slightly acidic conditions. By contrast, under these and other tested conditions, the Neurospora rhodopsin (NR)-like rhodopsin OpsA did not exhibit any pump activity. Basic local alignment search tool (BLAST) searches in the genomes of ascomycetes revealed the occurrence of rhodopsin-encoding genes mainly in phyto-associated or phytopathogenic fungi, suggesting a possible correlation of the presence of rhodopsins with fungal ecology. In accordance, rice plants infected with a CarO-deficient F. fujikuroi strain showed more severe bakanae symptoms than the reference strain, indicating a potential role of the CarO rhodopsin in the regulation of plant infection by this fungus. PMID:29324661

Application of time-frequency analysis to the evaluation of the condition of car suspension

NASA Astrophysics Data System (ADS)

Szymański, G. M.; Josko, M.; Tomaszewski, F.; Filipiak, R.

2015-06-01

The article presents possibilities of use of vibration signal parameters for the evaluation of elements' clearance in the car suspension system. The time-spectrum analysis has been proposed to determine the frequency band connected with car body free vibration generated by impacts of suspension elements in case of clearance in suspension elements fixing to the car body. Diagnostic models allowing evaluation of shock absorber fastening to the car body are described in this work.

Stock-car racing makes intuitive physicists

NASA Astrophysics Data System (ADS)

Gwynne, Peter

2008-03-01

Formula One races involve cars festooned with gadgets and complex electronic devices, in which millions of dollars are spent refining a vehicle's aerodynamics and reducing its weight. But in events run by America's National Association of Stock Car Auto Racing (NASCAR), cars hurtle round an oval track at speeds of about 300 km h-1 without the help of the complex sensors that are employed in Formula One cars. To avoid crashing, drivers must make their own adjustments to track conditions, engine problems and the traffic around them.

Robust Semi-Active Ride Control under Stochastic Excitation

DTIC Science & Technology

2014-01-01

broad classes of time-series models which are of practical importance; the Auto-Regressive (AR) models, the Integrated (I) models, and the Moving...Average (MA) models [12]. Combinations of these models result in autoregressive moving average (ARMA) and autoregressive integrated moving average...Down Up 4) Down Down These four cases can be written in compact form as: (20) Where is the Heaviside

Random Process Simulation for stochastic fatigue analysis. Ph.D. Thesis - Rice Univ., Houston, Tex.

NASA Technical Reports Server (NTRS)

Larsen, Curtis E.

1988-01-01

A simulation technique is described which directly synthesizes the extrema of a random process and is more efficient than the Gaussian simulation method. Such a technique is particularly useful in stochastic fatigue analysis because the required stress range moment E(R sup m), is a function only of the extrema of the random stress process. The family of autoregressive moving average (ARMA) models is reviewed and an autoregressive model is presented for modeling the extrema of any random process which has a unimodal power spectral density (psd). The proposed autoregressive technique is found to produce rainflow stress range moments which compare favorably with those computed by the Gaussian technique and to average 11.7 times faster than the Gaussian technique. The autoregressive technique is also adapted for processes having bimodal psd's. The adaptation involves using two autoregressive processes to simulate the extrema due to each mode and the superposition of these two extrema sequences. The proposed autoregressive superposition technique is 9 to 13 times faster than the Gaussian technique and produces comparable values for E(R sup m) for bimodal psd's having the frequency of one mode at least 2.5 times that of the other mode.

Incorporating measurement error in n = 1 psychological autoregressive modeling

PubMed Central

Schuurman, Noémi K.; Houtveen, Jan H.; Hamaker, Ellen L.

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30–50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters. PMID:26283988

Large signal-to-noise ratio quantification in MLE for ARARMAX models

NASA Astrophysics Data System (ADS)

Zou, Yiqun; Tang, Xiafei

2014-06-01

It has been shown that closed-loop linear system identification by indirect method can be generally transferred to open-loop ARARMAX (AutoRegressive AutoRegressive Moving Average with eXogenous input) estimation. For such models, the gradient-related optimisation with large enough signal-to-noise ratio (SNR) can avoid the potential local convergence in maximum likelihood estimation. To ease the application of this condition, the threshold SNR needs to be quantified. In this paper, we build the amplitude coefficient which is an equivalence to the SNR and prove the finiteness of the threshold amplitude coefficient within the stability region. The quantification of threshold is achieved by the minimisation of an elaborately designed multi-variable cost function which unifies all the restrictions on the amplitude coefficient. The corresponding algorithm based on two sets of physically realisable system input-output data details the minimisation and also points out how to use the gradient-related method to estimate ARARMAX parameters when local minimum is present as the SNR is small. Then, the algorithm is tested on a theoretical AutoRegressive Moving Average with eXogenous input model for the derivation of the threshold and a gas turbine engine real system for model identification, respectively. Finally, the graphical validation of threshold on a two-dimensional plot is discussed.

Effects of service conditions on the as-manufactured residual stress distribution in commuter car wheels

DOT National Transportation Integrated Search

2001-09-01

The effects of simulated service conditions on the as-manufactured residual stress : distribution in commuter car wheels are investigated. The residual stresses, those : stresses which remain after all applied loads are removed, can encourage the for...

Spatial Distribution of Dengue in a Brazilian Urban Slum Setting: Role of Socioeconomic Gradient in Disease Risk.

PubMed

Kikuti, Mariana; Cunha, Geraldo M; Paploski, Igor A D; Kasper, Amelia M; Silva, Monaise M O; Tavares, Aline S; Cruz, Jaqueline S; Queiroz, Tássia L; Rodrigues, Moreno S; Santana, Perla M; Lima, Helena C A V; Calcagno, Juan; Takahashi, Daniele; Gonçalves, André H O; Araújo, Josélio M G; Gauthier, Kristine; Diuk-Wasser, Maria A; Kitron, Uriel; Ko, Albert I; Reis, Mitermayer G; Ribeiro, Guilherme S

2015-01-01

Few studies of dengue have shown group-level associations between demographic, socioeconomic, or geographic characteristics and the spatial distribution of dengue within small urban areas. This study aimed to examine whether specific characteristics of an urban slum community were associated with the risk of dengue disease. From 01/2009 to 12/2010, we conducted enhanced, community-based surveillance in the only public emergency unit in a slum in Salvador, Brazil to identify acute febrile illness (AFI) patients with laboratory evidence of dengue infection. Patient households were geocoded within census tracts (CTs). Demographic, socioeconomic, and geographical data were obtained from the 2010 national census. Associations between CTs characteristics and the spatial risk of both dengue and non-dengue AFI were assessed by Poisson log-normal and conditional auto-regressive models (CAR). We identified 651 (22.0%) dengue cases among 2,962 AFI patients. Estimated risk of symptomatic dengue was 21.3 and 70.2 cases per 10,000 inhabitants in 2009 and 2010, respectively. All the four dengue serotypes were identified, but DENV2 predominated (DENV1: 8.1%; DENV2: 90.7%; DENV3: 0.4%; DENV4: 0.8%). Multivariable CAR regression analysis showed increased dengue risk in CTs with poorer inhabitants (RR: 1.02 for each percent increase in the frequency of families earning ≤1 times the minimum wage; 95% CI: 1.01-1.04), and decreased risk in CTs located farther from the health unit (RR: 0.87 for each 100 meter increase; 95% CI: 0.80-0.94). The same CTs characteristics were also associated with non-dengue AFI risk. This study highlights the large burden of symptomatic dengue on individuals living in urban slums in Brazil. Lower neighborhood socioeconomic status was independently associated with increased risk of dengue, indicating that within slum communities with high levels of absolute poverty, factors associated with the social gradient influence dengue transmission. In addition, poor geographic access to health services may be a barrier to identifying both dengue and non-dengue AFI cases. Therefore, further spatial studies should account for this potential source of bias.

Side impact test and analyses of a DOT-111 tank car : final report.

DOT National Transportation Integrated Search

2015-10-01

Transportation Technology Center, Inc. conducted a side impact test on a DOT-111 tank car to evaluate the performance of the : tank car under dynamic impact conditions and to provide data for the verification and refinement of a computational model. ...

40 CFR 201.10 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Standards § 201.10 Applicability. The provisions of this subpart apply to all rail cars and all locomotives... level emitted by rail cars and locomotives operated under the conditions specified, including the sound... provisions of this subpart apply to all active retarders, all car coupling operations, all switcher...

40 CFR 201.10 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Standards § 201.10 Applicability. The provisions of this subpart apply to all rail cars and all locomotives... level emitted by rail cars and locomotives operated under the conditions specified, including the sound... provisions of this subpart apply to all active retarders, all car coupling operations, all switcher...

40 CFR 201.10 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Standards § 201.10 Applicability. The provisions of this subpart apply to all rail cars and all locomotives... level emitted by rail cars and locomotives operated under the conditions specified, including the sound... provisions of this subpart apply to all active retarders, all car coupling operations, all switcher...

40 CFR 201.10 - Applicability.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Standards § 201.10 Applicability. The provisions of this subpart apply to all rail cars and all locomotives... level emitted by rail cars and locomotives operated under the conditions specified, including the sound... provisions of this subpart apply to all active retarders, all car coupling operations, all switcher...

40 CFR 201.10 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Standards § 201.10 Applicability. The provisions of this subpart apply to all rail cars and all locomotives... level emitted by rail cars and locomotives operated under the conditions specified, including the sound... provisions of this subpart apply to all active retarders, all car coupling operations, all switcher...

The Autoregressive Method: A Method of Approximating and Estimating Positive Functions

DTIC Science & Technology

1976-08-01

in drawing the curves, thanks to computer graphics. A few people ha’ very imaginatively pro- posed - td developed new ways of visualizing the data...k= -= it turns out that , , 0ki < 0 is a sufficient condition for all our k= -cc ( operations to be valid. Ii_ _ _ _ _ _ __ __ _ _ _ _ -106- We will

Laccase mediated-synthesis of hydroxycinnamoyl-peptide from ferulic acid and carnosine.

PubMed

Aljawish, Abdulhadi; Chevalot, Isabelle; Madad, Nidal; Paris, Cédric; Muniglia, Lionel

2016-06-10

Carnosine (CAR) dipeptide was functionalized with ferulic acid (FA) as substrate using laccase from Myceliophtora thermophila as biocatalyst. The enzymatic reaction was performed in aqueous medium under mild conditions (pH 7.5, 30°C) as an eco-friendly procedure. Results showed that this enzymatic process led to the synthesis of two new derivatives (P1, P2), from the coupling between CAR and FA derived products. Conditions allowing a high production of P1, P2 derivatives were determined with an optimal ratio of (FA: CAR) of (1:1.6) at optimal time reaction of 8h. Under these optimal conditions, the coupling between CAR and FA-products was demonstrated, resulting in the decrease of -NH2 groups (almost 50%) as quantified via derivatization. Due to the presence of FA in the structure of these new derivatives, they exhibited higher hydrophobic property than carnosine. Structural analyses by mass spectrometry showed that P1 and P2 (FA-CAR) derivatives exhibited the same molecular mass (MM 770g/mol) containing one CAR-molecule and three FA-molecules but with different chemical structures. Furthermore, these derivatives presented improved antioxidant (almost 10 times) and anti-proliferative (almost 18 times) properties in comparison with CAR. Moreover, P1 derivative exhibited higher antioxidant and anti-proliferative activities than P2 derivative, which confirmed the different structures of P1 and P2. These results suggested that the oxidized phenols coupling with carnosine is a promising process to enhance the CAR-properties. Copyright © 2016 Elsevier B.V. All rights reserved.

Probabilistic Approach to Conditional Probability of Release of Hazardous Materials from Railroad Tank Cars during Accidents

DOT National Transportation Integrated Search

2009-10-13

This paper describes a probabilistic approach to estimate the conditional probability of release of hazardous materials from railroad tank cars during train accidents. Monte Carlo methods are used in developing a probabilistic model to simulate head ...

Side impact test and analysis of a DOT-112 tank car.

DOT National Transportation Integrated Search

2016-12-01

As part of a program to improve transportation safety for tank cars, Transportation Technology Center, Inc. (TTCI) has conducted a side impact test on a DOT-112 tank car to evaluate the performance of the DOT-112 under dynamic impact conditions and t...

Development of a computer model for prediction of collision response of a railroad passenger car

DOT National Transportation Integrated Search

2002-04-23

The paper describes the development of a detailed finite element model that is capable of predicting the response of a rail passenger car to collision conditions. This model was developed to predict the car crush, the three-dimensional gross motions ...

Selected topics in railroad tank car safety research. Volume 1 : fatigue evaluation of prototype tank car head shield

DOT National Transportation Integrated Search

1978-08-01

The characteristics of a prototype head shield for hazardous material tank cars were evaluated with respect to the maintenance of its structural integrity under normal service conditions. The primary concern was with the resistance to fatigue damage ...

Directional control-response compatibility of joystick steered shuttle cars.

PubMed

Burgess-Limerick, Robin; Zupanc, Christine M; Wallis, Guy

2012-01-01

Shuttle cars are an unusual class of vehicle operated in underground coal mines, sometimes in close proximity to pedestrians and steering errors may have very serious consequences. A directional control-response incompatibility has previously been described in shuttle cars which are controlled using a steering wheel oriented perpendicular to the direction of travel. Some other shuttle car operators are seated perpendicular to the direction of travel and steer the car via a seat mounted joystick. A virtual simulation was utilised to determine whether the steering arrangement in these vehicles maintains directional control-response compatibility. Twenty-four participants were randomly assigned to either a condition corresponding to this design (consistent direction), or a condition in which the directional steering response was reversed while driving in-bye (visual field compatible). Significantly less accurate steering performance was exhibited by the consistent direction group during the in-bye trials only. Shuttle cars which provide the joystick steering mechanism described here require operators to accommodate alternating compatible and incompatible directional control-response relationships with each change of car direction. A virtual simulation of an underground coal shuttle car demonstrates that the design incorporates a directional control-response incompatibility when driving the vehicle in one direction. This design increases the probability of operator error, with potential adverse safety and productivity consequences.

78 FR 25345 - Petition for Waiver of Compliance

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-30

... 223.11 and 223.15 for one locomotive, two cars, and one equipment/generator car. Specifically, CHS..., and equipment/generator car, is in good condition and has no history of glazing-related accidents or... Docket Operations Facility, 1200 New Jersey Avenue SE., W12-140, Washington, DC 20590. The Docket...

Car Travel-Related Thrombosis: Fact or Fiction?

PubMed

Lippi, Giuseppe; Favaloro, Emmanuel J

2018-06-01

The condition sometimes referred to as "economy class syndrome," and also known as "traveler's thrombosis," is a distinctive pathological condition characterized by occurrence of venous thromboembolism (VTE) in a patient who has recently experienced a long journey (i.e., ≥ 4 h). Typically, the identified travel is by airplane, but travel with other vehicles, such as trains, trucks, buses, or cars, could potentially qualify as contributing to VTE events. Although the enhanced risk of VTE after long haul flights is now widely acknowledged, albeit potentially overhyped, the risk of venous thrombosis after prolonged travel by other modes of transport, in particular, by cars, is less well appreciated. Current evidence, collected from some epidemiological studies, suggests that if any risk of VTE can be attributed to prolonged and uninterrupted car travels, and we give moderate credibility to such an association, the risk may be similar to that already proven for long haul flights. The risk is especially high in individuals undergoing uninterrupted car journeys lasting 4 hours or longer, in vehicles with a narrow seat-pitch, and in particularly would affect those with pre-existing acquired or inherited prothrombotic conditions. The putative biological mechanisms basically entail venous stasis and edema, which are often compounded by a certain degree of hypercoagulability. When these factors are combined with preexistent prothrombotic conditions, the risk may be substantially magnified. In this perspective, then, 'car thrombosis' may be regarded as a trigger rather than a risk factor for venous thrombosis. Although the current evidence is certainly not solid enough to endorse the use of general chemical prophylaxis for lowering the risk of car-related VTE, a set of possible precautionary measures, with no or very little side effects, may be suggested before planning prolonged car travels, especially for at risk individuals. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

CARs: Synthetic Immunoreceptors for Cancer Therapy and Beyond

PubMed Central

Chang, ZeNan L.; Chen, Yvonne Y.

2017-01-01

Chimeric antigen receptors (CARs) are versatile synthetic receptors that provide T cells with engineered specificity. Clinical success in treating B-cell malignancies has demonstrated the therapeutic potential of CAR-T cells against cancer, and efforts are underway to expand the use of engineered T cells to the treatment of diverse medical conditions, including infections and autoimmune diseases. Here, we review current understanding of the molecular properties of CARs, how this knowledge informs the rational design and characterization of novel receptors, successes and shortcomings of CAR-T cells in the clinic, and emerging solutions for the continued improvement of CAR-T cell therapy. PMID:28416139

To center or not to center? Investigating inertia with a multilevel autoregressive model.

PubMed

Hamaker, Ellen L; Grasman, Raoul P P P

2014-01-01

Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion), cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship). This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction), cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model.

To center or not to center? Investigating inertia with a multilevel autoregressive model

PubMed Central

Hamaker, Ellen L.; Grasman, Raoul P. P. P.

2015-01-01

Whether level 1 predictors should be centered per cluster has received considerable attention in the multilevel literature. While most agree that there is no one preferred approach, it has also been argued that cluster mean centering is desirable when the within-cluster slope and the between-cluster slope are expected to deviate, and the main interest is in the within-cluster slope. However, we show in a series of simulations that if one has a multilevel autoregressive model in which the level 1 predictor is the lagged outcome variable (i.e., the outcome variable at the previous occasion), cluster mean centering will in general lead to a downward bias in the parameter estimate of the within-cluster slope (i.e., the autoregressive relationship). This is particularly relevant if the main question is whether there is on average an autoregressive effect. Nonetheless, we show that if the main interest is in estimating the effect of a level 2 predictor on the autoregressive parameter (i.e., a cross-level interaction), cluster mean centering should be preferred over other forms of centering. Hence, researchers should be clear on what is considered the main goal of their study, and base their choice of centering method on this when using a multilevel autoregressive model. PMID:25688215

A comparative study of the elemental composition of the exhaust emissions of cars powered by liquefied petroleum gas and unleaded petrol

NASA Astrophysics Data System (ADS)

Lim, McKenzie C. H.; Ayoko, Godwin A.; Morawska, Lidia; Ristovski, Zoran D.; Jayaratne, E. Rohan; Kokot, Serge

Elements emitted from the exhausts of new Ford Falcon Forte cars powered by unleaded petrol (ULP) and liquefied petroleum gas (LPG) were measured on a chassis dynamometer. The measurements were carried out in February, June and August 2001, and at two steady state driving conditions (60 and 80 km h -1). Thirty seven elements were quantified in the exhaust samples by inductively coupled plasma mass spectrometry (ICPMS). The total emission factors of the elements from the exhausts of ULP cars were higher than those of LPG cars at both engine speeds even though high variability in the exhaust emissions from different cars was noted. The effect of the operating conditions such as mileage of the cars, engine speed, fuel and lubricating oil compositions on the emissions was studied. To investigate the effects of these conditions, multivariate data analysis methods were employed including exploratory principal component analysis (PCA), and the multi-criteria decision making methods (MCDM), preference ranking organization method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive aid (GAIA), for ranking the cars on the basis of the emission factors of the elements. PCA biplot of the complete data matrix showed a clear discrimination of the February, June and August emission test results. In addition, (i) platinum group elements (PGE) emissions were separated from each other in the three different clusters viz. Pt with February, Pd with June and Rh with August; (ii) the motor oil related elements, Zn and P, were particularly associated with the June and August tests (these vectors were also grouped with V, Al and Cu); and (iii) highest emissions of most major elements were associated with the August test after the cars have recorded their highest mileage. Extensive analysis with the aid of the MCDM ranking methods demonstrated clearly that cars powered by LPG outperform those powered by ULP. In general, cars tested in June perform better than those tested in August, which suggested that mileage was the key criterion of car performance on the basis of elemental emission factors.

Study of car-sharing diffusion criticality conditions based on human traveling network

NASA Astrophysics Data System (ADS)

Xu, Yan; Ji, Xuehong

Car-sharing program, like Car2go, is an innovative urban transportation mode where the car-sharing company provides a car fleet to offer people with the short-term access of car traveling. As a new traveling service, car-sharing platforms have been struggling hard to trigger initial users and speed up their diffusion process. Unlike new product spreading via geographical proximity people, car-sharing users usually drive sharing cars to different destinations and influence people there, and potential user decision also depends on previous user activity at all their destinations. Car-sharing user connections are mainly affected by their traveling behaviors. The influence of user traveling network on new service/product spreading process has been rarely studied before. Here, we find that the infective rate between users with the same destination is critical to the minimum user base of car-sharing diffusion. Moreover, a city with central user network is more appropriate for car-sharing. It leads to a small critical infective rate for diffusion, and a large stable market size of car-sharing service. Our study can impact car-sharing market strategies ranging from market expansion in one city to optimal market selection among different cities.

The Longitudinal Interplay of Adolescents' Self-Esteem and Body Image: A Conditional Autoregressive Latent Trajectory Analysis

ERIC Educational Resources Information Center

Morin, Alexandre J. S.; Maiano, Christophe; Marsh, Herbert W.; Janosz, Michel; Nagengast, Benjamin

2011-01-01

Self-esteem and body image are central to coping successfully with the developmental challenges of adolescence. However, the current knowledge surrounding self-esteem and body image is fraught with controversy. This study attempts to clarify some of them by addressing three questions: (1) Are the intraindividual developmental trajectories of…

Mean-variance portfolio optimization by using time series approaches based on logarithmic utility function

NASA Astrophysics Data System (ADS)

Soeryana, E.; Fadhlina, N.; Sukono; Rusyaman, E.; Supian, S.

2017-01-01

Investments in stocks investors are also faced with the issue of risk, due to daily price of stock also fluctuate. For minimize the level of risk, investors usually forming an investment portfolio. Establishment of a portfolio consisting of several stocks are intended to get the optimal composition of the investment portfolio. This paper discussed about optimizing investment portfolio of Mean-Variance to stocks by using mean and volatility is not constant based on logarithmic utility function. Non constant mean analysed using models Autoregressive Moving Average (ARMA), while non constant volatility models are analysed using the Generalized Autoregressive Conditional heteroscedastic (GARCH). Optimization process is performed by using the Lagrangian multiplier technique. As a numerical illustration, the method is used to analyse some Islamic stocks in Indonesia. The expected result is to get the proportion of investment in each Islamic stock analysed.

Mean-Variance portfolio optimization by using non constant mean and volatility based on the negative exponential utility function

NASA Astrophysics Data System (ADS)

Soeryana, Endang; Halim, Nurfadhlina Bt Abdul; Sukono, Rusyaman, Endang; Supian, Sudradjat

2017-03-01

Investments in stocks investors are also faced with the issue of risk, due to daily price of stock also fluctuate. For minimize the level of risk, investors usually forming an investment portfolio. Establishment of a portfolio consisting of several stocks are intended to get the optimal composition of the investment portfolio. This paper discussed about optimizing investment portfolio of Mean-Variance to stocks by using mean and volatility is not constant based on the Negative Exponential Utility Function. Non constant mean analyzed using models Autoregressive Moving Average (ARMA), while non constant volatility models are analyzed using the Generalized Autoregressive Conditional heteroscedastic (GARCH). Optimization process is performed by using the Lagrangian multiplier technique. As a numerical illustration, the method is used to analyze some stocks in Indonesia. The expected result is to get the proportion of investment in each stock analyzed

Directionality volatility in electroencephalogram time series

NASA Astrophysics Data System (ADS)

Mansor, Mahayaudin M.; Green, David A.; Metcalfe, Andrew V.

2016-06-01

We compare time series of electroencephalograms (EEGs) from healthy volunteers with EEGs from subjects diagnosed with epilepsy. The EEG time series from the healthy group are recorded during awake state with their eyes open and eyes closed, and the records from subjects with epilepsy are taken from three different recording regions of pre-surgical diagnosis: hippocampal, epileptogenic and seizure zone. The comparisons for these 5 categories are in terms of deviations from linear time series models with constant variance Gaussian white noise error inputs. One feature investigated is directionality, and how this can be modelled by either non-linear threshold autoregressive models or non-Gaussian errors. A second feature is volatility, which is modelled by Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) processes. Other features include the proportion of variability accounted for by time series models, and the skewness and the kurtosis of the residuals. The results suggest these comparisons may have diagnostic potential for epilepsy and provide early warning of seizures.

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

Nonlinear Autoregressive Exogenous modeling of a large anaerobic digester producing biogas from cattle waste.

PubMed

Dhussa, Anil K; Sambi, Surinder S; Kumar, Shashi; Kumar, Sandeep; Kumar, Surendra

2014-10-01

In waste-to-energy plants, there is every likelihood of variations in the quantity and characteristics of the feed. Although intermediate storage tanks are used, but many times these are of inadequate capacity to dampen the variations. In such situations an anaerobic digester treating waste slurry operates under dynamic conditions. In this work a special type of dynamic Artificial Neural Network model, called Nonlinear Autoregressive Exogenous model, is used to model the dynamics of anaerobic digesters by using about one year data collected on the operating digesters. The developed model consists of two hidden layers each having 10 neurons, and uses 18days delay. There are five neurons in input layer and one neuron in output layer for a day. Model predictions of biogas production rate are close to plant performance within ±8% deviation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Safety of the Japanese K-car in a real-world low-severity frontal collision.

PubMed

Hitosugi, Masahito; Matsui, Yasuhiro

2015-01-01

Kei-cars (K-cars), which are a tiny 660 cc mini-car class 3.4 m long or less, 1.48 m wide or less, and 2.00 m high or less, have become popular in Japan. To evaluate the safety of K-car drivers in frontal collisions, we retrospectively compared the severity of injuries suffered by drivers between K-cars and standard vehicles involved in frontal collisions in which at least one injury occurred. From in-depth data provided by the Institute for Traffic Accident Research and Data Analysis from 1993 to 2010, records for 1379 drivers aged 36.8 ± 15.6 years were collected for analysis. Of the 1379 drivers, 1115 subjects were in standard vehicles and 264 were in K-cars. The mean delta V of the struck vehicle was 28.6 ± 15.6 km/h. After classifying the subjects according to seat belt use and air bag deployment, the background of the drivers and delta V, the injury severity scores (ISSs) and Abbreviated Injury Scale (AIS) scores were compared for all body regions. Under similar conditions, no significant differences in severity of injuries of the drivers were found between K-cars and standard vehicles. Although we are generally concerned that drivers of small vehicles suffer more severe injuries, our results suggest that, for real-world accidents, K-cars provide similar safety for drivers involved in frontal collisions as standard vehicles in low delta V impact conditions.

Characterization of Extremely Low Frequency Magnetic Fields from Diesel, Gasoline and Hybrid Cars under Controlled Conditions

PubMed Central

Hareuveny, Ronen; Sudan, Madhuri; Halgamuge, Malka N.; Yaffe, Yoav; Tzabari, Yuval; Namir, Daniel; Kheifets, Leeka

2015-01-01

This study characterizes extremely low frequency (ELF) magnetic field (MF) levels in 10 car models. Extensive measurements were conducted in three diesel, four gasoline, and three hybrid cars, under similar controlled conditions and negligible background fields. Averaged over all four seats under various driving scenarios the fields were lowest in diesel cars (0.02 μT), higher for gasoline (0.04–0.05 μT) and highest in hybrids (0.06–0.09 μT), but all were in-line with daily exposures from other sources. Hybrid cars had the highest mean and 95th percentile MF levels, and an especially large percentage of measurements above 0.2 μT. These parameters were also higher for moving conditions compared to standing while idling or revving at 2500 RPM and higher still at 80 km/h compared to 40 km/h. Fields in non-hybrid cars were higher at the front seats, while in hybrid cars they were higher at the back seats, particularly the back right seat where 16%–69% of measurements were greater than 0.2 μT. As our results do not include low frequency fields (below 30 Hz) that might be generated by tire rotation, we suggest that net currents flowing through the cars’ metallic chassis may be a possible source of MF. Larger surveys in standardized and well-described settings should be conducted with different types of vehicles and with spectral analysis of fields including lower frequencies due to magnetization of tires. PMID:25647323

49 CFR 238.229 - Safety appliances-general.

Code of Federal Regulations, 2014 CFR

2014-10-01

... support meets all of the conditions contained in § 238.230(b)(1) for being considered part of the car body... disassembly of a car is necessary to visually inspect the involved safety appliance bracket or support, the... for a final determination. No car with a defect in the weld of a safety appliance or its attachment...

49 CFR 238.229 - Safety appliances-general.

Code of Federal Regulations, 2013 CFR

2013-10-01

... support meets all of the conditions contained in § 238.230(b)(1) for being considered part of the car body... disassembly of a car is necessary to visually inspect the involved safety appliance bracket or support, the... for a final determination. No car with a defect in the weld of a safety appliance or its attachment...

49 CFR 238.229 - Safety appliances-general.

Code of Federal Regulations, 2012 CFR

2012-10-01

... support meets all of the conditions contained in § 238.230(b)(1) for being considered part of the car body... disassembly of a car is necessary to visually inspect the involved safety appliance bracket or support, the... for a final determination. No car with a defect in the weld of a safety appliance or its attachment...

49 CFR 232.103 - General requirements for all train brake systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... pneumatic technology, the integrity of the train line shall be monitored by the brake control system. (c) A... train shall not move if less than 85 percent of the cars in that train have operative and effective brakes. (f) Each car in a train shall have its air brakes in effective operating condition unless the car...

Comparison of chirped-probe-pulse and hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering for combustion thermometry.

PubMed

Richardson, Daniel R; Stauffer, Hans U; Roy, Sukesh; Gord, James R

2017-04-10

A comparison is made between two ultrashort-pulse coherent anti-Stokes Raman scattering (CARS) thermometry techniques-hybrid femtosecond/picosecond (fs/ps) CARS and chirped-probe-pulse (CPP) fs-CARS-that have become standards for high-repetition-rate thermometry in the combustion diagnostics community. These two variants of fs-CARS differ only in the characteristics of the ps-duration probe pulse; in hybrid fs/ps CARS a spectrally narrow, time-asymmetric probe pulse is used, whereas a highly chirped, spectrally broad probe pulse is used in CPP fs-CARS. Temperature measurements were performed using both techniques in near-adiabatic flames in the temperature range 1600-2400 K and for probe time delays of 0-30 ps. Under these conditions, both techniques are shown to exhibit similar temperature measurement accuracies and precisions to previously reported values and to each other. However, it is observed that initial calibration fits to the spectrally broad CPP results require more fitting parameters and a more robust optimization algorithm and therefore significantly increased computational cost and complexity compared to the fitting of hybrid fs/ps CARS data. The optimized model parameters varied more for the CPP measurements than for the hybrid fs/ps measurements for different experimental conditions.

A collision model for safety evaluation of autonomous intelligent cruise control.

PubMed

Touran, A; Brackstone, M A; McDonald, M

1999-09-01

This paper describes a general framework for safety evaluation of autonomous intelligent cruise control in rear-end collisions. Using data and specifications from prototype devices, two collision models are developed. One model considers a train of four cars, one of which is equipped with autonomous intelligent cruise control. This model considers the car in front and two cars following the equipped car. In the second model, none of the cars is equipped with the device. Each model can predict the possibility of rear-end collision between cars under various conditions by calculating the remaining distance between cars after the front car brakes. Comparing the two collision models allows one to evaluate the effectiveness of autonomous intelligent cruise control in preventing collisions. The models are then subjected to Monte Carlo simulation to calculate the probability of collision. Based on crash probabilities, an expected value is calculated for the number of cars involved in any collision. It is found that given the model assumptions, while equipping a car with autonomous intelligent cruise control can significantly reduce the probability of the collision with the car ahead, it may adversely affect the situation for the following cars.

Full velocity difference car-following model considering desired inter-vehicle distance

NASA Astrophysics Data System (ADS)

Xin, Tong; Yi, Liu; Rongjun, Cheng; Hongxia, Ge

Based on the full velocity difference car-following model, an improved car-following model is put forward by considering the driver’s desired inter-vehicle distance. The stability conditions are obtained by applying the control method. The results of theoretical analysis are used to demonstrate the advantages of our model. Numerical simulations are used to show that traffic congestion can be improved as the desired inter-vehicle distance is considered in the full velocity difference car-following model.

Perceptual aspects of reproduced sound in car cabin acoustics.

PubMed

Kaplanis, Neofytos; Bech, Søren; Tervo, Sakari; Pätynen, Jukka; Lokki, Tapio; van Waterschoot, Toon; Jensen, Søren Holdt

2017-03-01

An experiment was conducted to determine the perceptual effects of car cabin acoustics on the reproduced sound field. In-car measurements were conducted whilst the cabin's interior was physically modified. The captured sound fields were recreated in the laboratory using a three-dimensional loudspeaker array. A panel of expert assessors followed a rapid sensory analysis protocol, the flash profile, to perceptually characterize and evaluate 12 acoustical conditions of the car cabin using individually elicited attributes. A multivariate analysis revealed the panel's consensus and the identified perceptual constructs. Six perceptual constructs characterize the differences between the acoustical conditions of the cabin, related to bass, ambience, transparency, width and envelopment, brightness, and image focus. The current results indicate the importance of several acoustical properties of a car's interior on the perceived sound qualities. Moreover, they signify the capacity of the applied methodology in assessing spectral and spatial properties of automotive environments in laboratory settings using a time-efficient and flexible protocol.

Sensor network based solar forecasting using a local vector autoregressive ridge framework

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

Xu, J.; Yoo, S.; Heiser, J.

2016-04-04

The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations duemore » to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.« less

Estimating long-run equilibrium real exchange rates: short-lived shocks with long-lived impacts on Pakistan.

PubMed

Zardad, Asma; Mohsin, Asma; Zaman, Khalid

2013-12-01

The purpose of this study is to investigate the factors that affect real exchange rate volatility for Pakistan through the co-integration and error correction model over a 30-year time period, i.e. between 1980 and 2010. The study employed the autoregressive conditional heteroskedasticity (ARCH), generalized autoregressive conditional heteroskedasticity (GARCH) and Vector Error Correction model (VECM) to estimate the changes in the volatility of real exchange rate series, while an error correction model was used to determine the short-run dynamics of the system. The study is limited to a few variables i.e., productivity differential (i.e., real GDP per capita relative to main trading partner); terms of trade; trade openness and government expenditures in order to manage robust data. The result indicates that real effective exchange rate (REER) has been volatile around its equilibrium level; while, the speed of adjustment is relatively slow. VECM results confirm long run convergence of real exchange rate towards its equilibrium level. Results from ARCH and GARCH estimation shows that real shocks volatility persists, so that shocks die out rather slowly, and lasting misalignment seems to have occurred.

Pavlovian drug-sickness pairings result in the conditioning of an antisickness response.

PubMed

Lett, B T

1983-10-01

After a drug conditioned stimulus (CS) has been injected prior to lithium chloride as the unconditioned stimulus (US) on five occasions, the drug CS becomes able to evoke a conditioned antisickness response (CAR). This CAR is implied by the finding that the CS drug mitigates the conditioned saccharin aversion produced by lithium when it is administered in the interval between saccharin consumption and lithium injection. The following drugs were tested and are listed in approximate order of their effectiveness in producing a conditioned antisickness effect: pentobarbital, ethanol, morphine, amphetamine, and chlordiazepoxide.

Design of two wheel self balancing car

NASA Astrophysics Data System (ADS)

He, Chun-hong; Ren, Bin

2018-02-01

This paper proposes a design scheme of the two-wheel self-balancing dolly, the integration of the gyroscope and accelerometer MPU6050 constitutes the car position detection device.System selects 32-bit MCU stmicroelectronics company as the control core, completed the processing of sensor signals, the realization of the filtering algorithm, motion control and human-computer interaction. Produced and debugging in the whole system is completed, the car can realize the independent balance under the condition of no intervention. The introduction of a suitable amount of interference, the car can adjust quickly to recover and steady state. Through remote control car bluetooth module complete forward, backward, turn left and other basic action..

77 FR 2437 - Special Conditions: Gulfstream Aerospace Corporation, Model GVI Airplane; Rechargeable Lithium...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-18

..., transport-category airplanes were derived from Civil Air Regulations (CAR) Part 4b.625(d) as part of the re-codification of CAR 4b that established 14 CFR part 25 in February 1965. The new battery requirements, Sec. 25.1353(c) (1) through (c)(4), basically reworded the CAR requirements. Increased use of nickel-cadmium...

Direct emission of nitrous acid (HONO) from gasoline cars in China determined by vehicle chassis dynamometer experiments

NASA Astrophysics Data System (ADS)

Liu, Yuhan; Lu, Keding; Ma, Yufang; Yang, Xinping; Zhang, Wenbin; Wu, Yusheng; Peng, Jianfei; Shuai, Shijin; Hu, Min; Zhang, Yuanhang

2017-11-01

HONO plays a key role in atmospheric chemistry, and while its importance is well-known, the sources of HONO are still not completely understood. As a component of ambient HONO sources, direct emission from vehicles is an area that should be extensively studied. In this study, we determined the HONO emission index for typical gasoline vehicles in the car population of China through a chassis dynamometer with different types of engines (PFI/GDI), starting conditions (cold/warm) and running styles (Beijing cycle). Emission ratios of HONO to nitrogen oxide (NOX) for the Chinese gasoline cars are determined to be in the range of (0.03-0.42) % and an averaged value is about 0.18%, which are comparable to those reported in the few studies available in Europe, the United States and Japan for gasoline cars while smaller for those of the diesel cars. The atmospheric impact of the direct HONO emission from gasoline cars was analyzed for a typical urban site in Beijing, significant contributions of the direct emission toward the HONO budget were found during morning rush hours or twilight conditions to be 8-12%.

Combined effects of inversion and feature removal on N170 responses elicited by faces and car fronts

PubMed Central

Kloth, Nadine; Itier, Roxane J.; Schweinberger, Stefan R.

2014-01-01

The face-sensitive N170 is typically enhanced for inverted compared to upright faces. Itier, Alain, Sedore, and McIntosh (2007) recently suggested that this N170 inversion effect is mainly driven by the eye region which becomes salient when the face configuration is disrupted. Here we tested whether similar effects could be observed with non-face objects that are structurally similar to faces in terms of possessing a homogeneous within-class first-order feature configuration. We presented upright and inverted pictures of intact car fronts, car fronts without lights, and isolated lights, in addition to analogous face conditions. Upright cars elicited substantial N170 responses of similar amplitude to those evoked by upright faces. In strong contrast to face conditions however, the car-elicited N170 was mainly driven by the global shape rather than the presence or absence of lights, and was dramatically reduced for isolated lights. Overall, our data confirm a differential influence of the eye region in upright and inverted faces. Results for car fronts do not suggest similar interactive encoding of eye-like features and configuration for non-face objects, even when these objects possess a similar feature configuration as faces. PMID:23485023

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada.

PubMed

Modarres, Reza; Ouarda, Taha B M J; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMAX-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56% of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada

NASA Astrophysics Data System (ADS)

Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

Assessing rear-end collision risk of cars and heavy vehicles on freeways using a surrogate safety measure.

PubMed

Zhao, Peibo; Lee, Chris

2018-04-01

This study analyzes rear-end collision risk of cars and heavy vehicles on freeways using a surrogate safety measure. The crash potential index (CPI) was modified to reflect driver's reaction time and estimated by types of lead and following vehicles (car or heavy vehicle). CPIs were estimated using the individual vehicle trajectory data from a segment of the US-101 freeway in Los Angeles, U.S.A. It was found that the CPI was generally higher for the following heavy vehicle than the following car due to heavy vehicle's lower braking capability. This study also validates the CPI using the simulated traffic data which replicate the observed traffic conditions a few minutes before the crash time upstream and downstream of the crash locations. The observed data were obtained from crash records and loop detectors on a section of the Gardiner Expressway in Toronto, Canada. The result shows that the values of CPI were consistently higher during the traffic conditions immediately before the crash time (crash case) than the normal traffic conditions (non-crash case). This demonstrates that the CPI can be used to capture rear-end collision risk during car-following maneuver on freeways. The result also shows that rear-end collision risk is lower for heavy vehicles than cars in the crash case due to their shorter reaction time and lower speed when spacing is shorter. Thus, it is important to reflect the differences in driver behavior and vehicle performance characteristics between cars and heavy vehicles in estimating surrogate safety measures. Lastly, it was found that the CPI-based crash prediction model can correctly identify the crash and non-crash cases at higher accuracy than the other crash prediction models based on detectors. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of high-resolution n(2) coherent anti-stokes Raman scattering for measuring pressure, temperature, and density in high-speed gas flows.

PubMed

Woodmansee, M A; Lucht, R P; Dutton, J C

2000-11-20

Mean and instantaneous measurements of pressure, temperature, and density have been acquired in an optically accessible gas cell and in the flow field of an underexpanded sonic jet by use of the high-resolution N(2) coherent anti-Stokes Raman scattering (CARS) technique. This nonintrusive method resolves the pressure- and temperature-sensitive rotational transitions of the nu = 0 ? 1 N(2) Q-branch to within Domega = 0.10 cm(-1). To extract thermodynamic information from the experimental spectra, theoretical spectra, generated by a N(2) spectral modeling program, are fit to the experimental spectra in a least-squares manner. In the gas cell, the CARS-measured pressures compare favorably with transducer-measured pressures. The precision and accuracy of the single-shot CARS pressure measurements increase at subatmospheric conditions. Along the centerline of the underexpanded jet, the agreement between the mean CARS P/T/rho measurements and similar quantities extracted from a Reynolds-averaged Navier-Stokes computational fluid dynamic simulation is generally excellent. This CARS technique is able to capture the low-pressure and low-temperature conditions of the M = 3.4 flow entering the Mach disk, as well as the subsonic conditions immediately downstream of this normal shock.

An adaptive ARX model to estimate the RUL of aluminum plates based on its crack growth

NASA Astrophysics Data System (ADS)

Barraza-Barraza, Diana; Tercero-Gómez, Víctor G.; Beruvides, Mario G.; Limón-Robles, Jorge

2017-01-01

A wide variety of Condition-Based Maintenance (CBM) techniques deal with the problem of predicting the time for an asset fault. Most statistical approaches rely on historical failure data that might not be available in several practical situations. To address this issue, practitioners might require the use of self-starting approaches that consider only the available knowledge about the current degradation process and the asset operating context to update the prognostic model. Some authors use Autoregressive (AR) models for this purpose that are adequate when the asset operating context is constant, however, if it is variable, the accuracy of the models can be affected. In this paper, three autoregressive models with exogenous variables (ARX) were constructed, and their capability to estimate the remaining useful life (RUL) of a process was evaluated following the case of the aluminum crack growth problem. An existing stochastic model of aluminum crack growth was implemented and used to assess RUL estimation performance of the proposed ARX models through extensive Monte Carlo simulations. Point and interval estimations were made based only on individual history, behavior, operating conditions and failure thresholds. Both analytic and bootstrapping techniques were used in the estimation process. Finally, by including recursive parameter estimation and a forgetting factor, the ARX methodology adapts to changing operating conditions and maintain the focus on the current degradation level of an asset.

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

NASA Astrophysics Data System (ADS)

Guo, A.; Wang, Y.

2017-12-01

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

Research on external flow field of a car based on reverse engineering

NASA Astrophysics Data System (ADS)

Hu, Shushan; Liu, Ronge

2018-05-01

In this paper, the point cloud data of FAW-VOLKSWAGEN car body shape is obtained by three coordinate measuring instrument and laser scanning method. The accurate three dimensional model of the car is obtained using CATIA software reverse modelling technology. The car body is gridded, the calculation field and boundary condition type of the car flow field are determined, and the numerical simulation is carried out in Hyper Mesh software. The pressure cloud diagram, velocity vector diagram, air resistance coefficient and lift coefficient of the car are obtained. The calculation results reflect the aerodynamic characteristics of the car's external flow field. The motion of the separation flow on the surface of the vehicle body is well simulated, and the area where the vortex motion is relatively intense has been determined. The results provide a theoretical basis for improving and optimizing the body shape.

Project report : Alaska travel information system

DOT National Transportation Integrated Search

2004-11-01

The Alaska Department of Transportation and Public Facilities (ADOT&PF) initiated the Alaska Travel Information System by joining the Condition Acquisition and Reporting System/511 (CARS/511) Pooled Fund in October 2002. CARS was jointly developed by...

Confirmation of heavy metal ions in used lubricating oil from a passenger car using chelating self-assembled monolayer.

PubMed

Ko, Young Gun; Kim, Choong Hyun

2006-09-01

In order to prevent engine failure, the oil must be changed before it loses its protective properties. It is necessary to monitor the actual physical and chemical condition of the oil to reliably determine the optimum oil-change interval. Our study focuses on the condition of the lubricating oil in an operated car engine. Shear stress curves and viscosity curves as a function of the shear rate for fresh and used lubricating oil were examined. Metal nitrate was detected in the lubricating oil from the operated car engine through the use of a chelating self-assembled monolayer.

Are car daytime running lights detrimental to motorcycle conspicuity?

PubMed

Cavallo, Viola; Pinto, Maria

2012-11-01

For a long time, motorcycles were the only vehicles with daytime running lights (DRLs), but this conspicuity advantage has been questioned due to the rapidly increasing introduction of DRLs on cars as well. The present experiment was designed to assess effects of car DRLs on motorcycle perception in a situation that specifically brought attentional conspicuity to bear. Photographs representing complex urban traffic scenes were displayed briefly (250 ms) to 24 participants who had to detect vulnerable road users (motorcyclists, cyclists, pedestrians) appearing at different locations and distances. Car DRLs hampered motorcycle perception compared to conditions where car lights were not on, especially when the motorcycle was at a greater distance from the observer and when it was located in the central part of the visual scene. Car DRLs also hampered the perception of cyclists and pedestrians. Although the globally positive safety effect of car DRLs is generally acknowledged, our study suggests that more attention should be paid to motorcyclists and other vulnerable road users when introducing car DRLs. Several means of improving motorcycle conspicuity in car DRL environments are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling of Engine Parameters for Condition-Based Maintenance of the MTU Series 2000 Diesel Engine

DTIC Science & Technology

2016-09-01

are suitable. To model the behavior of the engine, an autoregressive distributed lag (ARDL) time series model of engine speed and exhaust gas... time series model of engine speed and exhaust gas temperature is derived. The lag length for ARDL is determined by whitening of residuals using the...15 B. REGRESSION ANALYSIS ....................................................................15 1. Time Series Analysis

[Effects of exposure frequency and background information on preferences for photographs of cars in different locations].

PubMed

Matsuda, Ken; Kusumi, Takashi; Hosomi, Naohiro; Osa, Atsushi; Miike, Hidetoshi

2014-08-01

This study examined the influence of familiarity and novelty on the mere exposure effect while manipulating the presentation of background information. We selected presentation stimuli that integrated cars and backgrounds based on the results of pilot studies. During the exposure phase, we displayed the stimuli successively for 3 seconds, manipulating the background information (same or different backgrounds with each presentation) and exposure frequency (3, 6, and 9 times). In the judgment phase, 18 participants judged the cars in terms of preference, familiarity, and novelty on a 7-point scale. As the number of stimulus presentations increased, the preference for the cars increased during the different background condition and decreased during the same background condition. This increased preference may be due to the increase in familiarity caused by the higher exposure frequency and novelty resulting from the background changes per exposure session. The rise in preference judgments was not seen when cars and backgrounds were presented independently. Therefore, the addition of novel features to each exposure session facilitated the mere exposure effect.

Traction studies of piston ring wear using an external radiometric method with proton activation

NASA Astrophysics Data System (ADS)

Scharf, Waldemar; Niewczas, Andrzej

1987-04-01

A method and results are presented of traction studies of piston ring wear in a Polski Fiat 126p passenger car and Star 200 lorry. The rings sliding surface was activated with a beam of 9.6-MeV protons and the measurements were made using a collimated scintillation detector placed outside the engine, i.e. without interfering with the engine's operation. The cars were run under varying traction conditions, their mileages having ranged between 7000 and 12000 km. In stable wear conditions on the road the piston ring wear for the passenger car and the lorry was {0.28%}/{100} km and {0.045%}/{100} km, respectively. The method was found to be particularly suitable for traction studies because it is simple and cheap. It can be employed as early as after the first 100 km of the car mileage.

Analysis of a front suspension system for UniART FSAE car using FEA

NASA Astrophysics Data System (ADS)

Zaidie, M. N. A.; Hashim, M. S. M.; Tasyrif, M.; Basha, M. H.; Ibrahim, I.; Kamaruddin, N. S.; Shahriman, A. B.

2017-10-01

In recent years, many research works from institutions that participated in Formula SAE had highlighted on suspension systems. The aim is to improve the system in term of performance and robustness. However, every suspension system for a racing car is tailored to the car itself. Thus, this paper proposes a new design for front suspension system for UniART FSAE car. The new design was than being compared to the previous suspension system for enhancement. The analysis covered in this paper based on several conditions such as braking, cornering and bumping condition and was carried out using finite element analysis. Each main component for the suspension system such as lower arm, upper arm and knuckle has been analysed in term of strength and performance. From the results, the proposed new design of the suspension system has improved in term of strength and performance compared to the previous suspension system.

Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks

PubMed Central

2015-01-01

Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency. PMID:26539722

Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.

PubMed

Jin, Junghwan; Kim, Jinsoo

2015-01-01

Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency.

Combined effects of inversion and feature removal on N170 responses elicited by faces and car fronts.

PubMed

Kloth, Nadine; Itier, Roxane J; Schweinberger, Stefan R

2013-04-01

The face-sensitive N170 is typically enhanced for inverted compared to upright faces. Itier, Alain, Sedore, and McIntosh (2007) recently suggested that this N170 inversion effect is mainly driven by the eye region which becomes salient when the face configuration is disrupted. Here we tested whether similar effects could be observed with non-face objects that are structurally similar to faces in terms of possessing a homogeneous within-class first-order feature configuration. We presented upright and inverted pictures of intact car fronts, car fronts without lights, and isolated lights, in addition to analogous face conditions. Upright cars elicited substantial N170 responses of similar amplitude to those evoked by upright faces. In strong contrast to face conditions however, the car-elicited N170 was mainly driven by the global shape rather than the presence or absence of lights, and was dramatically reduced for isolated lights. Overall, our data confirm a differential influence of the eye region in upright and inverted faces. Results for car fronts do not suggest similar interactive encoding of eye-like features and configuration for non-face objects, even when these objects possess a similar feature configuration as faces. Copyright © 2013 Elsevier Inc. All rights reserved.

Formation of met-cars and face-centered cubic structures. Thermodynamically or kinetically controlled

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

Wei, S.; Guo, B.C.; Deng, H.T.

1994-05-18

On the basis of a series of experimental studies from our laboratory, it is well established that metallocarbohedrenes, or Met-Cars for short, are a stable class of cluster materials. To account for their exceptional stability, we initially proposed a pentagonal dodecahedron structure. This cage-like structure is consistent with all the experimental findings. In general, there are two possible structures that can be developed in these metal-carbon systems, i.e., Met-Cars and cubes. Since only one structural pattern is generally observed for one particular cluster system, it has been suggested that their thermodynamical stabilities might be responsible for the selective formation ofmore » specific structures, e.g., Met-Cars or fcc structures. Herein, we present new experimental results on the system of Nb[sub m]C[sub n] under various conditions. It is shown that the experimental conditions are extremely critical for the formation of either Met-Cars or cubic structures, as predicted by Reddy and Khanma. Moreover, the new data show that the cubic structures do not develop on top of Met-Cars, but rather, they grow independently. The experiments were performed by using both time-of-flight and quadrupole mass spectrometer techniques coupled with a laser vaporization source. 23 refs., 1 fig.« less

In-car particles and cardiovascular health: an air conditioning-based intervention study.

PubMed

Chuang, Hsiao-Chi; Lin, Lian-Yu; Hsu, Ya-Wen; Ma, Chih-Ming; Chuang, Kai-Jen

2013-05-01

Exposure to traffic-related particulate matter (PM) is considered a potential risk for cardiovascular events. Little is known about whether improving air quality in car can modify cardiovascular effects among human subjects during commuting. We recruited a panel of 60 healthy subjects to commute for 2 h by a car equipped with an air conditioning (AC) system during the morning rush hour in Taipei. Operation modes of AC system using outside air (OA-mode), circulating inside air (IA-mode) and turning off (Off-mode) were examined. Repeated measurements of heart rate variability (HRV) indices, PM≤2.5 μm in aerodynamic diameter (PM2.5) and noise level were conducted for each participant in different modes during the commute. We used linear mixed-effects models to associate HRV indices with in-car PM2.5. We found that decreases in HRV indices were associated with increased levels of in-car PM2.5. For Off-mode, an interquartile range (IQR) increase in in-car PM2.5 with 15-min moving average was associated with 2.7% and 4.1% decreases in standard deviation of NN intervals (SDNN) and the square root of the mean of the sum of the squares of differences between adjacent NN intervals (r-MSSD), respectively. During OA and IA modes, participants showed slight decreases in SDNN (OA mode: 0.1%; IA mode: 1.3%) and r-MSSD (OA mode: 1.1%; IA mode: 1.8%) by an IQR increase in in-car PM2.5 with 15-min moving average. We concluded that in-car PM2.5 is associated with autonomic alteration. Utilization of the car's AC system can improve air quality and modify the effects of in-car PM2.5 on HRV indices among human subjects during the commute. Copyright © 2013 Elsevier B.V. All rights reserved.

What Are Some Ways to Promote Infant Safety in a Car?

MedlinePlus

... NICHD Research Information Find a Study More Information Cerebral Palsy Condition Information NICHD Research Information Find a Study ... 6, 2012, from http://www.nhtsa.gov/Safety/CPS / American Academy of Pediatrics. (2012). Car seats: Information ...

Forecasting coconut production in the Philippines with ARIMA model

NASA Astrophysics Data System (ADS)

Lim, Cristina Teresa

2015-02-01

The study aimed to depict the situation of the coconut industry in the Philippines for the future years applying Autoregressive Integrated Moving Average (ARIMA) method. Data on coconut production, one of the major industrial crops of the country, for the period of 1990 to 2012 were analyzed using time-series methods. Autocorrelation (ACF) and partial autocorrelation functions (PACF) were calculated for the data. Appropriate Box-Jenkins autoregressive moving average model was fitted. Validity of the model was tested using standard statistical techniques. The forecasting power of autoregressive moving average (ARMA) model was used to forecast coconut production for the eight leading years.

How to compare cross-lagged associations in a multilevel autoregressive model.

PubMed

Schuurman, Noémi K; Ferrer, Emilio; de Boer-Sonnenschein, Mieke; Hamaker, Ellen L

2016-06-01

By modeling variables over time it is possible to investigate the Granger-causal cross-lagged associations between variables. By comparing the standardized cross-lagged coefficients, the relative strength of these associations can be evaluated in order to determine important driving forces in the dynamic system. The aim of this study was twofold: first, to illustrate the added value of a multilevel multivariate autoregressive modeling approach for investigating these associations over more traditional techniques; and second, to discuss how the coefficients of the multilevel autoregressive model should be standardized for comparing the strength of the cross-lagged associations. The hierarchical structure of multilevel multivariate autoregressive models complicates standardization, because subject-based statistics or group-based statistics can be used to standardize the coefficients, and each method may result in different conclusions. We argue that in order to make a meaningful comparison of the strength of the cross-lagged associations, the coefficients should be standardized within persons. We further illustrate the bivariate multilevel autoregressive model and the standardization of the coefficients, and we show that disregarding individual differences in dynamics can prove misleading, by means of an empirical example on experienced competence and exhaustion in persons diagnosed with burnout. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Influence of mobile air-conditioning on vehicle emissions and fuel consumption: a model approach for modern gasoline cars used in Europe.

PubMed

Weilenmann, Martin F; Vasic, Ana-Marija; Stettler, Peter; Novak, Philippe

2005-12-15

The influence of air-conditioning activity on the emissions and fuel consumption of passenger cars is an important issue, since fleet penetration and use of these systems have reached a high level. Apart from the MOBILE6 study in the United States, little data is available on the impact of air-conditioning devices (A/Cs). Since weather conditions and A/C technologies both differ from those in the U. S., a test series was designed for the European setting. A fleet of six modern gasoline passenger cars was tested in different weather conditions. Separate test series were carried out for the initial cooldown and for the stationary situation of keeping the interior of the vehicle cool. As assumed, CO2 emissions and fuel consumption rise with the thermal load. This also causes a notable rise in CO and hydrocarbons (HCs). Moreover, A/Cs do not stop automatically at low ambient temperatures; if necessary, they produce dry air to demist the windscreen. A model is proposed that shows a constant load for lower temperatures and a linear trend for higher temperatures. The initial cooldown tests highlight significant differences among cars but show that A/C operation for the initial cooling of an overheated passenger compartment does not result in any extra emissions for the fleet as a whole.

A Bayesian spatio-temporal model for forecasting the prevalence of antibodies to Borrelia burgdorferi, causative agent of Lyme disease, in domestic dogs within the contiguous United States.

PubMed

Watson, Stella C; Liu, Yan; Lund, Robert B; Gettings, Jenna R; Nordone, Shila K; McMahan, Christopher S; Yabsley, Michael J

2017-01-01

This paper models the prevalence of antibodies to Borrelia burgdorferi in domestic dogs in the United States using climate, geographic, and societal factors. We then use this model to forecast the prevalence of antibodies to B. burgdorferi in dogs for 2016. The data available for this study consists of 11,937,925 B. burgdorferi serologic test results collected at the county level within the 48 contiguous United States from 2011-2015. Using the serologic data, a baseline B. burgdorferi antibody prevalence map was constructed through the use of spatial smoothing techniques after temporal aggregation; i.e., head-banging and Kriging. In addition, several covariates purported to be associated with B. burgdorferi prevalence were collected on the same spatio-temporal granularity, and include forestation, elevation, water coverage, temperature, relative humidity, precipitation, population density, and median household income. A Bayesian spatio-temporal conditional autoregressive (CAR) model was used to analyze these data, for the purposes of identifying significant risk factors and for constructing disease forecasts. The fidelity of the forecasting technique was assessed using historical data, and a Lyme disease forecast for dogs in 2016 was constructed. The correlation between the county level model and baseline B. burgdorferi antibody prevalence estimates from 2011 to 2015 is 0.894, illustrating that the Bayesian spatio-temporal CAR model provides a good fit to these data. The fidelity of the forecasting technique was assessed in the usual fashion; i.e., the 2011-2014 data was used to forecast the 2015 county level prevalence, with comparisons between observed and predicted being made. The weighted (to acknowledge sample size) correlation between 2015 county level observed prevalence and 2015 forecasted prevalence is 0.978. A forecast for the prevalence of B. burgdorferi antibodies in domestic dogs in 2016 is also provided. The forecast presented from this model can be used to alert veterinarians in areas likely to see above average B. burgdorferi antibody prevalence in dogs in the upcoming year. In addition, because dogs and humans can be exposed to ticks in similar habitats, these data may ultimately prove useful in predicting areas where human Lyme disease risk may emerge.

A Bayesian spatio-temporal model for forecasting the prevalence of antibodies to Borrelia burgdorferi, causative agent of Lyme disease, in domestic dogs within the contiguous United States

PubMed Central

Watson, Stella C.; Liu, Yan; Lund, Robert B.; Gettings, Jenna R.; Nordone, Shila K.; McMahan, Christopher S.

2017-01-01

This paper models the prevalence of antibodies to Borrelia burgdorferi in domestic dogs in the United States using climate, geographic, and societal factors. We then use this model to forecast the prevalence of antibodies to B. burgdorferi in dogs for 2016. The data available for this study consists of 11,937,925 B. burgdorferi serologic test results collected at the county level within the 48 contiguous United States from 2011-2015. Using the serologic data, a baseline B. burgdorferi antibody prevalence map was constructed through the use of spatial smoothing techniques after temporal aggregation; i.e., head-banging and Kriging. In addition, several covariates purported to be associated with B. burgdorferi prevalence were collected on the same spatio-temporal granularity, and include forestation, elevation, water coverage, temperature, relative humidity, precipitation, population density, and median household income. A Bayesian spatio-temporal conditional autoregressive (CAR) model was used to analyze these data, for the purposes of identifying significant risk factors and for constructing disease forecasts. The fidelity of the forecasting technique was assessed using historical data, and a Lyme disease forecast for dogs in 2016 was constructed. The correlation between the county level model and baseline B. burgdorferi antibody prevalence estimates from 2011 to 2015 is 0.894, illustrating that the Bayesian spatio-temporal CAR model provides a good fit to these data. The fidelity of the forecasting technique was assessed in the usual fashion; i.e., the 2011-2014 data was used to forecast the 2015 county level prevalence, with comparisons between observed and predicted being made. The weighted (to acknowledge sample size) correlation between 2015 county level observed prevalence and 2015 forecasted prevalence is 0.978. A forecast for the prevalence of B. burgdorferi antibodies in domestic dogs in 2016 is also provided. The forecast presented from this model can be used to alert veterinarians in areas likely to see above average B. burgdorferi antibody prevalence in dogs in the upcoming year. In addition, because dogs and humans can be exposed to ticks in similar habitats, these data may ultimately prove useful in predicting areas where human Lyme disease risk may emerge. PMID:28472096

A Bayesian-Based Novel Methodology to Generate Reliable Site Response Mapping Sensitive to Data Uncertainties

NASA Astrophysics Data System (ADS)

Chakraborty, A.; Goto, H.

2017-12-01

The 2011 off the Pacific coast of Tohoku earthquake caused severe damage in many areas further inside the mainland because of site-amplification. Furukawa district in Miyagi Prefecture, Japan recorded significant spatial differences in ground motion even at sub-kilometer scales. The site responses in the damage zone far exceeded the levels in the hazard maps. A reason why the mismatch occurred is that mapping follow only the mean value at the measurement locations with no regard to the data uncertainties and thus are not always reliable. Our research objective is to develop a methodology to incorporate data uncertainties in mapping and propose a reliable map. The methodology is based on a hierarchical Bayesian modeling of normally-distributed site responses in space where the mean (μ), site-specific variance (σ2) and between-sites variance(s2) parameters are treated as unknowns with a prior distribution. The observation data is artificially created site responses with varying means and variances for 150 seismic events across 50 locations in one-dimensional space. Spatially auto-correlated random effects were added to the mean (μ) using a conditionally autoregressive (CAR) prior. The inferences on the unknown parameters are done using Markov Chain Monte Carlo methods from the posterior distribution. The goal is to find reliable estimates of μ sensitive to uncertainties. During initial trials, we observed that the tau (=1/s2) parameter of CAR prior controls the μ estimation. Using a constraint, s = 1/(k×σ), five spatial models with varying k-values were created. We define reliability to be measured by the model likelihood and propose the maximum likelihood model to be highly reliable. The model with maximum likelihood was selected using a 5-fold cross-validation technique. The results show that the maximum likelihood model (μ*) follows the site-specific mean at low uncertainties and converges to the model-mean at higher uncertainties (Fig.1). This result is highly significant as it successfully incorporates the effect of data uncertainties in mapping. This novel approach can be applied to any research field using mapping techniques. The methodology is now being applied to real records from a very dense seismic network in Furukawa district, Miyagi Prefecture, Japan to generate a reliable map of the site responses.

A systematic review of secondhand smoke exposure in a car: Attributable changes in atmospheric and biological markers.

PubMed

Raoof, Sana A; Agaku, Israel T; Vardavas, Constantine I

2015-05-01

Exposure to secondhand smoke (SHS) has been linked to disease, disability, and premature death. While several countries have enacted smoke-free legislations, exposure to SHS may still occur in unregulated private environments, such as in the family car. We performed a systematic review of peer-reviewed literature in PubMed and Web of Science up to May 2013. Articles were selected if they provided a quantitative measure of SHS exposure (biological or atmospheric markers); the study was conducted inside a car; and the assessed exposure was attributable to cigarette combustion. From 202 articles identified, 12 met the inclusion criteria. Among all studies that assessed smoking in cars with at least one window partially open, the particulate matter 2.5 μm or less in diameter (PM2.5) concentrations ranged from 47 μg/m(3) to 12,150 μg/m(3). For studies with all windows closed, PM2.5 ranged from 203.6 μg/m(3) to 13,150 μg/m(3). SHS concentration in a car was mediated by air-conditioning status, extent of airflow, and driving speed. Smoking in cars leads to extremely high exposure to SHS and increased concentration of atmospheric markers of exposure-even in the presence of air-conditioning or increased airflow from open windows. This clearly shows that the only way to protect nonsmokers, especially children, from SHS within cars is by eliminating tobacco smoking. © The Author(s) 2015.

Simulation of car movement along circular path

NASA Astrophysics Data System (ADS)

Fedotov, A. I.; Tikhov-Tinnikov, D. A.; Ovchinnikova, N. I.; Lysenko, A. V.

2017-10-01

Under operating conditions, suspension system performance changes which negatively affects vehicle stability and handling. The paper aims to simulate the impact of changes in suspension system performance on vehicle stability and handling. Methods. The paper describes monitoring of suspension system performance, testing of vehicle stability and handling, analyzes methods of suspension system performance monitoring under operating conditions. The mathematical model of a car movement along a circular path was developed. Mathematical tools describing a circular movement of a vehicle along a horizontal road were developed. Turning car movements were simulated. Calculation and experiment results were compared. Simulation proves the applicability of a mathematical model for assessment of the impact of suspension system performance on vehicle stability and handling.

Expansion of the visual angle of a car rear-view image via an image mosaic algorithm

NASA Astrophysics Data System (ADS)

Wu, Zhuangwen; Zhu, Liangrong; Sun, Xincheng

2015-05-01

The rear-view image system is one of the active safety devices in cars and is widely applied in all types of vehicles and traffic safety areas. However, studies made by both domestic and foreign researchers were based on a single image capture device while reversing, so a blind area still remained to drivers. Even if multiple cameras were used to expand the visual angle of the car's rear-view image in some studies, the blind area remained because different source images were not mosaicked together. To acquire an expanded visual angle of a car rear-view image, two charge-coupled device cameras with optical axes angled at 30 deg were mounted below the left and right fenders of a car in three light conditions-sunny outdoors, cloudy outdoors, and an underground garage-to capture rear-view heterologous images of the car. Then these rear-view heterologous images were rapidly registered through the scale invariant feature transform algorithm. Combined with the random sample consensus algorithm, the two heterologous images were finally mosaicked using the linear weighted gradated in-and-out fusion algorithm, and a seamless and visual-angle-expanded rear-view image was acquired. The four-index test results showed that the algorithms can mosaic rear-view images well in the underground garage condition, where the average rate of correct matching was the lowest among the three conditions. The rear-view image mosaic algorithm presented had the best information preservation, the shortest computation time and the most complete preservation of the image detail features compared to the mean value method (MVM) and segmental fusion method (SFM), and it was also able to perform better in real time and provided more comprehensive image details than MVM and SFM. In addition, it had the most complete image preservation from source images among the three algorithms. The method introduced by this paper provided the basis for researching the expansion of the visual angle of a car rear-view image in all-weather conditions.

Effect of the mileage of a passenger car on changes in its body geometry

NASA Astrophysics Data System (ADS)

Gonera, Jarosław; Napiórkowski, Jerzy

2018-04-01

This study analyses the effect of the mileage of a passenger car on changes in its body geometry in regards to its safety. Ninety-six passenger cars used in similar environmental conditions were examined. The required position of twelve base points was compared to their actual position. Those were the points responsible for the active and passive safety of a car on the left and right side of the floor panel. The geometry of the floor panel was measured with a GYSMETER device manufactured by GYS and Allvis Light software. Increasing mileage was found to result in increasing changes in the floor panel geometry, which take place mainly on the right side of a car and at points affecting passive safety.

Simultaneous observation of rotational coherent Stokes Raman scattering and coherent anti-Stokes Raman scattering in air and nitrogen

NASA Technical Reports Server (NTRS)

Snow, J. B.; Chang, R. K.; Zheng, J. B.; Leipertz, A.

1983-01-01

Rotational coherent Stokes Raman scattering (CSRS) and coherent anti-Stokes Raman scattering (CARS) in air and in nitrogen were observed simultaneously by using broadband generation and detection. In the broadband technique used, the entire CARS and CSRS spectrum was generated in a single laser pulse; the CSRS and CARS signals were dispersed by a spectrograph and detected simultaneously by an optical multichannel analyzer. A three-dimensional phase-matching geometry was used to achieve spatial resolution of the CSRS and CARS beams from the input beams. Under resonant conditions, similar experiments may provide a means of investigating the possible interaction between the CSRS and CARS processes in driving the rotational levels.

The comparison study among several data transformations in autoregressive modeling

NASA Astrophysics Data System (ADS)

Setiyowati, Susi; Waluyo, Ramdhani Try

2015-12-01

In finance, the adjusted close of stocks are used to observe the performance of a company. The extreme prices, which may increase or decrease drastically, are often become particular concerned since it can impact to bankruptcy. As preventing action, the investors have to observe the future (forecasting) stock prices comprehensively. For that purpose, time series analysis could be one of statistical methods that can be implemented, for both stationary and non-stationary processes. Since the variability process of stocks prices tend to large and also most of time the extreme values are always exist, then it is necessary to do data transformation so that the time series models, i.e. autoregressive model, could be applied appropriately. One of popular data transformation in finance is return model, in addition to ratio of logarithm and some others Tukey ladder transformation. In this paper these transformations are applied to AR stationary models and non-stationary ARCH and GARCH models through some simulations with varying parameters. As results, this work present the suggestion table that shows transformations behavior for some condition of parameters and models. It is confirmed that the better transformation is obtained, depends on type of data distributions. In other hands, the parameter conditions term give significant influence either.

Sinusoidal synthesis based adaptive tracking for rotating machinery fault detection

NASA Astrophysics Data System (ADS)

Li, Gang; McDonald, Geoff L.; Zhao, Qing

2017-01-01

This paper presents a novel Sinusoidal Synthesis Based Adaptive Tracking (SSBAT) technique for vibration-based rotating machinery fault detection. The proposed SSBAT algorithm is an adaptive time series technique that makes use of both frequency and time domain information of vibration signals. Such information is incorporated in a time varying dynamic model. Signal tracking is then realized by applying adaptive sinusoidal synthesis to the vibration signal. A modified Least-Squares (LS) method is adopted to estimate the model parameters. In addition to tracking, the proposed vibration synthesis model is mainly used as a linear time-varying predictor. The health condition of the rotating machine is monitored by checking the residual between the predicted and measured signal. The SSBAT method takes advantage of the sinusoidal nature of vibration signals and transfers the nonlinear problem into a linear adaptive problem in the time domain based on a state-space realization. It has low computation burden and does not need a priori knowledge of the machine under the no-fault condition which makes the algorithm ideal for on-line fault detection. The method is validated using both numerical simulation and practical application data. Meanwhile, the fault detection results are compared with the commonly adopted autoregressive (AR) and autoregressive Minimum Entropy Deconvolution (ARMED) method to verify the feasibility and performance of the SSBAT method.

Exploring the Specifications of Spatial Adjacencies and Weights in Bayesian Spatial Modeling with Intrinsic Conditional Autoregressive Priors in a Small-area Study of Fall Injuries

PubMed Central

Law, Jane

2016-01-01

Intrinsic conditional autoregressive modeling in a Bayeisan hierarchical framework has been increasingly applied in small-area ecological studies. This study explores the specifications of spatial structure in this Bayesian framework in two aspects: adjacency, i.e., the set of neighbor(s) for each area; and (spatial) weight for each pair of neighbors. Our analysis was based on a small-area study of falling injuries among people age 65 and older in Ontario, Canada, that was aimed to estimate risks and identify risk factors of such falls. In the case study, we observed incorrect adjacencies information caused by deficiencies in the digital map itself. Further, when equal weights was replaced by weights based on a variable of expected count, the range of estimated risks increased, the number of areas with probability of estimated risk greater than one at different probability thresholds increased, and model fit improved. More importantly, significance of a risk factor diminished. Further research to thoroughly investigate different methods of variable weights; quantify the influence of specifications of spatial weights; and develop strategies for better defining spatial structure of a map in small-area analysis in Bayesian hierarchical spatial modeling is recommended. PMID:29546147

CAR Suppresses Hepatic Gluconeogenesis by Facilitating the Ubiquitination and Degradation of PGC1α

PubMed Central

Gao, Jie; Yan, Jiong; Xu, Meishu; Ren, Songrong

2015-01-01

The constitutive androstane receptor (CAR) and peroxisome proliferator-activated receptor gamma coactivator-1α (PGC1α) are master regulators of drug metabolism and gluconeogenesis, respectively. In supporting the cross talk between drug metabolism and energy metabolism, activation of CAR has been shown to suppress hepatic gluconeogenesis and ameliorate hyperglycemia in vivo, but the underlying molecular mechanism remains elusive. In this study, we demonstrated that CAR suppressed hepatic gluconeogenic gene expression through posttranslational regulation of the subcellular localization and degradation of PGC1α. Activated CAR translocated into the nucleus and served as an adaptor protein to recruit PGC1α to the Cullin1 E3 ligase complex for ubiquitination. The interaction between CAR and PGC1α also led to their sequestration within the promyelocytic leukemia protein-nuclear bodies, where PGC1α and CAR subsequently underwent proteasomal degradation. Taken together, our findings revealed an unexpected function of CAR in recruiting an E3 ligase and targeting the gluconeogenic activity of PGC1α. Both drug metabolism and gluconeogenesis are energy-demanding processes. The negative regulation of PGC1α by CAR may represent a cellular adaptive mechanism to accommodate energy-restricted conditions. PMID:26407237

CAR Suppresses Hepatic Gluconeogenesis by Facilitating the Ubiquitination and Degradation of PGC1α.

PubMed

Gao, Jie; Yan, Jiong; Xu, Meishu; Ren, Songrong; Xie, Wen

2015-11-01

The constitutive androstane receptor (CAR) and peroxisome proliferator-activated receptor gamma coactivator-1α (PGC1α) are master regulators of drug metabolism and gluconeogenesis, respectively. In supporting the cross talk between drug metabolism and energy metabolism, activation of CAR has been shown to suppress hepatic gluconeogenesis and ameliorate hyperglycemia in vivo, but the underlying molecular mechanism remains elusive. In this study, we demonstrated that CAR suppressed hepatic gluconeogenic gene expression through posttranslational regulation of the subcellular localization and degradation of PGC1α. Activated CAR translocated into the nucleus and served as an adaptor protein to recruit PGC1α to the Cullin1 E3 ligase complex for ubiquitination. The interaction between CAR and PGC1α also led to their sequestration within the promyelocytic leukemia protein-nuclear bodies, where PGC1α and CAR subsequently underwent proteasomal degradation. Taken together, our findings revealed an unexpected function of CAR in recruiting an E3 ligase and targeting the gluconeogenic activity of PGC1α. Both drug metabolism and gluconeogenesis are energy-demanding processes. The negative regulation of PGC1α by CAR may represent a cellular adaptive mechanism to accommodate energy-restricted conditions.

49 CFR 210.3 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-10-01

... emitted by moving rail cars and locomotives (including the sound produced by refrigeration and air conditioning units that are an integral element of such equipment), active retarders, switcher locomotives, car... apply to— (1) Steam locomotives; (2) Street, suburban, or interurban electric railways unless operated...

49 CFR 210.3 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-10-01

... emitted by moving rail cars and locomotives (including the sound produced by refrigeration and air conditioning units that are an integral element of such equipment), active retarders, switcher locomotives, car... apply to— (1) Steam locomotives; (2) Street, suburban, or interurban electric railways unless operated...

49 CFR 210.3 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-10-01

... emitted by moving rail cars and locomotives (including the sound produced by refrigeration and air conditioning units that are an integral element of such equipment), active retarders, switcher locomotives, car... apply to— (1) Steam locomotives; (2) Street, suburban, or interurban electric railways unless operated...

49 CFR 210.3 - Applicability.

Code of Federal Regulations, 2010 CFR

2010-10-01

... emitted by moving rail cars and locomotives (including the sound produced by refrigeration and air conditioning units that are an integral element of such equipment), active retarders, switcher locomotives, car... apply to— (1) Steam locomotives; (2) Street, suburban, or interurban electric railways unless operated...

49 CFR 210.3 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-10-01

... emitted by moving rail cars and locomotives (including the sound produced by refrigeration and air conditioning units that are an integral element of such equipment), active retarders, switcher locomotives, car... apply to— (1) Steam locomotives; (2) Street, suburban, or interurban electric railways unless operated...

Generation of CAR T cells for adoptive therapy in the context of glioblastoma standard of care.

PubMed

Riccione, Katherine; Suryadevara, Carter M; Snyder, David; Cui, Xiuyu; Sampson, John H; Sanchez-Perez, Luis

2015-02-16

Adoptive T cell immunotherapy offers a promising strategy for specifically targeting and eliminating malignant gliomas. T cells can be engineered ex vivo to express chimeric antigen receptors specific for glioma antigens (CAR T cells). The expansion and function of adoptively transferred CAR T cells can be potentiated by the lymphodepletive and tumoricidal effects of standard of care chemotherapy and radiotherapy. We describe a method for generating CAR T cells targeting EGFRvIII, a glioma-specific antigen, and evaluating their efficacy when combined with a murine model of glioblastoma standard of care. T cells are engineered by transduction with a retroviral vector containing the anti-EGFRvIII CAR gene. Tumor-bearing animals are subjected to host conditioning by a course of temozolomide and whole brain irradiation at dose regimens designed to model clinical standard of care. CAR T cells are then delivered intravenously to primed hosts. This method can be used to evaluate the antitumor efficacy of CAR T cells in the context of standard of care.

Railroad Safety: DoD can Improve the Safety of On-Base Track and Equipment

DTIC Science & Technology

1991-06-01

explosives are secured on rail cars for on-base movement. Unless you publicly announce its contents earlier, we plan no further distribution of this report...and rail cars thatare used to haul ammunition, explosives, or other hazardous material . The safe transport of this material both on military...commercial operating conditions. When transporting haz- ardous materials , cars operating in commerce must also comply with safety requirements established

Know Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models

DTIC Science & Technology

2015-04-01

features/index.htm. Accessed: 2014-09-30. [3] Google self driving car . http://en.wikipedia.org/wiki/ Google driverless car . Accessed: 2014-10-11. [4...and outside the car , GPS, and speed information, with lane and driving maneuver annotations. II. RELATED WORK Assistive features for vehicles . Recent...made driving safer over the last decade. They prepare vehicles for unsafe road conditions and alert drivers if they perform a dangerous maneuver

Simulation And Forecasting of Daily Pm10 Concentrations Using Autoregressive Models In Kagithane Creek Valley, Istanbul

NASA Astrophysics Data System (ADS)

Ağaç, Kübra; Koçak, Kasım; Deniz, Ali

2015-04-01

A time series approach using autoregressive model (AR), moving average model (MA) and seasonal autoregressive integrated moving average model (SARIMA) were used in this study to simulate and forecast daily PM10 concentrations in Kagithane Creek Valley, Istanbul. Hourly PM10 concentrations have been measured in Kagithane Creek Valley between 2010 and 2014 periods. Bosphorus divides the city in two parts as European and Asian parts. The historical part of the city takes place in Golden Horn. Our study area Kagithane Creek Valley is connected with this historical part. The study area is highly polluted because of its topographical structure and industrial activities. Also population density is extremely high in this site. The dispersion conditions are highly poor in this creek valley so it is necessary to calculate PM10 levels for air quality and human health. For given period there were some missing PM10 concentration values so to make an accurate calculations and to obtain exact results gap filling method was applied by Singular Spectrum Analysis (SSA). SSA is a new and efficient method for gap filling and it is an state-of-art modeling. SSA-MTM Toolkit was used for our study. SSA is considered as a noise reduction algorithm because it decomposes an original time series to trend (if exists), oscillatory and noise components by way of a singular value decomposition. The basic SSA algorithm has stages of decomposition and reconstruction. For given period daily and monthly PM10 concentrations were calculated and episodic periods are determined. Long term and short term PM10 concentrations were analyzed according to European Union (EU) standards. For simulation and forecasting of high level PM10 concentrations, meteorological data (wind speed, pressure and temperature) were used to see the relationship between daily PM10 concentrations. Fast Fourier Transformation (FFT) was also applied to the data to see the periodicity and according to these periods models were built in MATLAB an Eviews programmes. Because of the seasonality of PM10 data SARIMA model was also used. The order of autoregression model was determined according to AIC and BIC criteria. The model performances were evaluated from Fractional Bias, Normalized Mean Square Error (NMSE) and Mean Absolute Percentage Error (MAPE). As expected, the results were encouraging. Keywords: PM10, Autoregression, Forecast Acknowledgement The authors would like to acknowledge the financial support by the Scientific and Technological Research Council of Turkey (TUBITAK, project no:112Y319).

Aromatherapy for travel-induced excitement in dogs.

PubMed

Wells, Deborah L

2006-09-15

To evaluate the efficacy of the ambient odor of lavender as a treatment for travel-induced excitement in dogs. Clinical trial. Animals-32 dogs with a history of travel-induced excitement in owners' cars. Each dog was studied during travel in the owner's car to a familiar walking site during 2 conditions of olfactory stimulation. The first condition was a control condition, during which dogs were exposed to no odor other than that arising naturally from the environment. The second condition was an experimental condition during which dogs were exposed to the ambient odor of lavender. Dogs' behavior was recorded during the car journey for 3 consecutive days under the control condition and for 3 consecutive days under the experimental condition. The percentage of time spent moving, standing, sitting, resting, and vocalizing in each condition of olfactory stimulation was quantified for each dog. Dogs spent significantly more time resting and sitting and less time moving and vocalizing during the experimental condition. There was no significant relationship between dogs' behavior and sex, castration status, day, or the order of exposure to each olfactory condition. Traditional treatments for travel-induced excitement in dogs may be time-consuming, expensive, or associated with adverse effects. Aromatherapy in the form of diffused lavender odor may offer a practical alternative treatment for travel-induced excitement in this species.

The dynamic conditional relationship between stock market returns and implied volatility

NASA Astrophysics Data System (ADS)

Park, Sung Y.; Ryu, Doojin; Song, Jeongseok

2017-09-01

Using the dynamic conditional correlation multivariate generalized autoregressive conditional heteroskedasticity (DCC-MGARCH) model, we empirically examine the dynamic relationship between stock market returns (KOSPI200 returns) and implied volatility (VKOSPI), as well as their statistical mechanics, in the Korean market, a representative and leading emerging market. We consider four macroeconomic variables (exchange rates, risk-free rates, term spreads, and credit spreads) as potential determinants of the dynamic conditional correlation between returns and volatility. Of these macroeconomic variables, the change in exchange rates has a significant impact on the dynamic correlation between KOSPI200 returns and the VKOSPI, especially during the recent financial crisis. We also find that the risk-free rate has a marginal effect on this dynamic conditional relationship.

Detailed puncture analyses tank cars : analysis of different impactor threats and impact conditions.

DOT National Transportation Integrated Search

2013-03-01

There has been significant research in recent years to analyze and improve the impact behavior and puncture resistance of railroad tank cars. Much of this research has been performed using detailed nonlinear finite element analyses supported by full ...

Optimization of autoregressive, exogenous inputs-based typhoon inundation forecasting models using a multi-objective genetic algorithm

NASA Astrophysics Data System (ADS)

Ouyang, Huei-Tau

2017-07-01

Three types of model for forecasting inundation levels during typhoons were optimized: the linear autoregressive model with exogenous inputs (LARX), the nonlinear autoregressive model with exogenous inputs with wavelet function (NLARX-W) and the nonlinear autoregressive model with exogenous inputs with sigmoid function (NLARX-S). The forecast performance was evaluated by three indices: coefficient of efficiency, error in peak water level and relative time shift. Historical typhoon data were used to establish water-level forecasting models that satisfy all three objectives. A multi-objective genetic algorithm was employed to search for the Pareto-optimal model set that satisfies all three objectives and select the ideal models for the three indices. Findings showed that the optimized nonlinear models (NLARX-W and NLARX-S) outperformed the linear model (LARX). Among the nonlinear models, the optimized NLARX-W model achieved a more balanced performance on the three indices than the NLARX-S models and is recommended for inundation forecasting during typhoons.

Embedding perseverative interest of a child with autism in text may result in improved reading comprehension: A pilot study.

PubMed

El Zein, Farah; Solis, Michael; Lang, Russell; Kim, Min Kyung

2016-06-01

We investigated the effects of embedding the perseverative interest (PI) of a child with autism (i.e. cars) within texts on reading comprehension. A PI text condition (text altered to include cars) was compared with a non-PI text condition (same story without cars inserted) in an alternating treatment design. Dependent variables were responses to reading comprehension questions and number of words uttered during an oral retell (i.e. curriculum-based measures [CBMs]). The reading level, instructional routines, and therapist where held constant across the randomly alternated conditions. Both CBMs suggested that reading comprehension was enhanced when the story included the child's PI. These preliminary findings suggest that embedding the PIs of students with autism spectrum disorder within readings may result in more accurate responses to reading comprehension questions and more detailed oral retelling. These findings are discussed in terms of potential directions for future research.

[MICROCLIMATE CONDITION IN SUBWAY CARS IN THE SUMMER PERIOD OF THE YEAR].

PubMed

Leksin, A G; Evlampieva, M N; Timoshenkova, E V; Morgunov, A V; Kaptsov, V A

2015-01-01

There are presented the results of the work, which aims to identify the relationship between the temperature of air in the salons of subway cars from the heat output of passengers in different people occupancy of cars during "peak hours", and to determine the efficacy offorced air handling regular ventilation or air conditioning system to remove the elevated heat load on passengers. In the work there was used the method of calculating the amount of heat output of 215 passengers (nominal fullness of the chamber) and the simulation method of heat and moisture output of the same number of passengers. The operating system of ventilation has been shown to fail to decline the average temperature of the air in the passenger compartment to the optimum values and most efficient approach for the reducing the heat load on the passengers is the use of air conditioning systems.

Two-dimensional statistical linear discriminant analysis for real-time robust vehicle-type recognition

NASA Astrophysics Data System (ADS)

Zafar, I.; Edirisinghe, E. A.; Acar, S.; Bez, H. E.

2007-02-01

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic License Plate Recognition (ALPR) systems. Several car MMR systems have been proposed in literature. However these approaches are based on feature detection algorithms that can perform sub-optimally under adverse lighting and/or occlusion conditions. In this paper we propose a real time, appearance based, car MMR approach using Two Dimensional Linear Discriminant Analysis that is capable of addressing this limitation. We provide experimental results to analyse the proposed algorithm's robustness under varying illumination and occlusions conditions. We have shown that the best performance with the proposed 2D-LDA based car MMR approach is obtained when the eigenvectors of lower significance are ignored. For the given database of 200 car images of 25 different make-model classifications, a best accuracy of 91% was obtained with the 2D-LDA approach. We use a direct Principle Component Analysis (PCA) based approach as a benchmark to compare and contrast the performance of the proposed 2D-LDA approach to car MMR. We conclude that in general the 2D-LDA based algorithm supersedes the performance of the PCA based approach.

Estimation of Snow Particle Model Suitable for a Complex and Forested Terrain: Lessons from SnowEx

NASA Astrophysics Data System (ADS)

Gatebe, C. K.; Li, W.; Stamnes, K. H.; Poudyal, R.; Fan, Y.; Chen, N.

2017-12-01

SnowEx 2017 obtained consistent and coordinated ground and airborne remote sensing measurements over Grand Mesa in Colorado, which feature sufficient forested stands to have a range of density and height (and other forest conditions); a range of snow depth/snow water equivalent (SWE) conditions; sufficiently flat snow-covered terrain of a size comparable to airborne instrument swath widths. The Cloud Absorption Radiometer (CAR) data from SnowEx are unique and can be used to assess the accuracy of Bidirectional Reflectance-Distribution Functions (BRDFs) calculated by different snow models. These measurements provide multiple angle and multiple wavelength data needed for accurate surface BRDF characterization. Such data cannot easily be obtained by current satellite remote sensors. Compared to ground-based snow field measurements, CAR measurements minimize the effect of self-shading, and are adaptable to a wide variety of field conditions. We plan to use the CAR measurements as the validation data source for our snow modeling effort. By comparing calculated BRDF results from different snow models to CAR measurements, we can determine which model best explains the snow BRDFs, and is therefore most suitable for application to satellite remote sensing of snow parameters and surface energy budget calculations.

Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach

USGS Publications Warehouse

Bled, Florent; Sauer, John R.; Pardieck, Keith L.; Doherty, Paul; Royle, J. Andy

2013-01-01

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.

Spatial and temporal patterns of dengue infections in Timor-Leste, 2005-2013.

PubMed

Wangdi, Kinley; Clements, Archie C A; Du, Tai; Nery, Susana Vaz

2018-01-04

Dengue remains an important public health problem in Timor-Leste, with several major epidemics occurring over the last 10 years. The aim of this study was to identify dengue clusters at high geographical resolution and to determine the association between local environmental characteristics and the distribution and transmission of the disease. Notifications of dengue cases that occurred from January 2005 to December 2013 were obtained from the Ministry of Health, Timor-Leste. The population of each suco (the third-level administrative subdivision) was obtained from the Population and Housing Census 2010. Spatial autocorrelation in dengue incidence was explored using Moran's I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate, Zero-Inflated, Poisson (ZIP) regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling. The analysis used data from 3206 cases. Dengue incidence was highly seasonal with a large peak in January. Patients ≥ 14 years were found to be 74% [95% credible interval (CrI): 72-76%] less likely to be infected than those < 14 years, and females were 12% (95% CrI: 4-21%) more likely to suffer from dengue as compared to males. Dengue incidence increased by 0.7% (95% CrI: 0.6-0.8%) for a 1 °C increase in mean temperature; and 47% (95% CrI: 29-59%) for a 1 mm increase in precipitation. There was no significant residual spatial clustering after accounting for climate and demographic variables. Dengue incidence was highly seasonal and spatially clustered, with positive associations with temperature, precipitation and demographic factors. These factors explained the observed spatial heterogeneity of infection.

Macro-level safety analysis of pedestrian crashes in Shanghai, China.

PubMed

Wang, Xuesong; Yang, Junguang; Lee, Chris; Ji, Zhuoran; You, Shikai

2016-11-01

Pedestrian safety has become one of the most important issues in the field of traffic safety. This study aims at investigating the association between pedestrian crash frequency and various predictor variables including roadway, socio-economic, and land-use features. The relationships were modeled using the data from 263 Traffic Analysis Zones (TAZs) within the urban area of Shanghai - the largest city in China. Since spatial correlation exists among the zonal-level data, Bayesian Conditional Autoregressive (CAR) models with seven different spatial weight features (i.e. (a) 0-1 first order, adjacency-based, (b) common boundary-length-based, (c) geometric centroid-distance-based, (d) crash-weighted centroid-distance-based, (e) land use type, adjacency-based, (f) land use intensity, adjacency-based, and (g) geometric centroid-distance-order) were developed to characterize the spatial correlations among TAZs. Model results indicated that the geometric centroid-distance-order spatial weight feature, which was introduced in macro-level safety analysis for the first time, outperformed all the other spatial weight features. Population was used as the surrogate for pedestrian exposure, and had a positive effect on pedestrian crashes. Other significant factors included length of major arterials, length of minor arterials, road density, average intersection spacing, percentage of 3-legged intersections, and area of TAZ. Pedestrian crashes were higher in TAZs with medium land use intensity than in TAZs with low and high land use intensity. Thus, higher priority should be given to TAZs with medium land use intensity to improve pedestrian safety. Overall, these findings can help transportation planners and managers understand the characteristics of pedestrian crashes and improve pedestrian safety. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prediction of car cabin environment by means of 1D and 3D cabin model

NASA Astrophysics Data System (ADS)

Fišer, J.; Pokorný, J.; Jícha, M.

2012-04-01

Thermal comfort and also reduction of energy requirements of air-conditioning system in vehicle cabins are currently very intensively investigated and up-to-date issues. The article deals with two approaches of modelling of car cabin environment; the first model was created in simulation language Modelica (typical 1D approach without cabin geometry) and the second one was created in specialized software Theseus-FE (3D approach with cabin geometry). Performance and capabilities of this tools are demonstrated on the example of the car cabin and the results from simulations are compared with the results from the real car cabin climate chamber measurements.

VIEW OF SEMIDISMANTLED HOPPER CAR ON THE ORE TRESTLE FACING ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

VIEW OF SEMI-DISMANTLED HOPPER CAR ON THE ORE TRESTLE FACING NORTHWEST WITH OPEN HEARTH BUILDING IN THE BACKGROUND AND THE INGOT MOLD CONDITIONING BUILDING TO THE RIGHT. - Pittsburgh Steel Company, Monessen Works, Open Hearth Plant, Donner Avenue, Monessen, Westmoreland County, PA

49 CFR 1039.11 - Miscellaneous commodities exemptions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... machinery or complete air-conditioning units. 36 ......do Electrical machinery, equipment or supplies except... regarding the use of equipment, whether shipper or railroad owned or leased, including car hire, per diem... car service regulations or mandatory interchange of equipment or to maintain and execute such...

Covert effects of "one drink" of alcohol on brain processes related to car driving: an event-related potential study.

PubMed

Ebe, Kazutoshi; Itoh, Kosuke; Kwee, Ingrid L; Nakada, Tsutomu

2015-04-23

The effects of a low dose of alcohol on car driving remain controversial. To address this issue, event-related potentials were recorded while subjects performed a simple car-following task in a driving simulator before and after consuming either "one drink" of beer (representing one standard alcoholic beverage containing 14 g of alcohol) or mineral water (control condition). Subjects who had consumed the determined amount of alcohol demonstrated no detectable outward behavioral signs of intoxication while performing the driving task, an observation in agreement with previous findings. However, the parietal P3 elicited by the brake lights of the preceding car was significantly reduced in amplitude, approximately 50% that observed under the control condition, likely indicating alteration of the neural processing of visual information critical for safe driving. The finding suggests that alcohol begins to affect neural processes for driving even at quantities too low to modify behavior. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Modeling mechanical restriction differences between car and heavy truck in two-lane cellular automata traffic flow model

NASA Astrophysics Data System (ADS)

Li, Xin; Li, Xingang; Xiao, Yao; Jia, Bin

2016-06-01

Real traffic is heterogeneous with car and truck. Due to mechanical restrictions, the car and the truck have different limited deceleration capabilities, which are important factors in safety driving. This paper extends the single lane safety driving (SD) model with limited deceleration capability to two-lane SD model, in which car-truck heterogeneous traffic is considered. A car has a larger limited deceleration capability while a heavy truck has a smaller limited deceleration capability as a result of loaded goods. Then the safety driving conditions are different as the types of the following and the leading vehicles vary. In order to eliminate the well-known plug in heterogeneous two-lane traffic, it is assumed that heavy truck has active deceleration behavior when the heavy truck perceives the forming plug. The lane-changing decisions are also determined by the safety driving conditions. The fundamental diagram, spatiotemporal diagram, and lane-changing frequency were investigated to show the effect of mechanical restriction on heterogeneous traffic flow. It was shown that there would be still three traffic phases in heterogeneous traffic condition; the active deceleration of the heavy truck could well eliminate the plug; the lane-changing frequency was low in synchronized flow; the flow and velocity would decrease as the proportion of heavy truck grows or the limited deceleration capability of heavy truck drops; and the flow could be improved with lane control measures.

Spatial Dynamics and Determinants of County-Level Education Expenditure in China

ERIC Educational Resources Information Center

Gu, Jiafeng

2012-01-01

In this paper, a multivariate spatial autoregressive model of local public education expenditure determination with autoregressive disturbance is developed and estimated. The existence of spatial interdependence is tested using Moran's I statistic and Lagrange multiplier test statistics for both the spatial error and spatial lag models. The full…

The Disparate Labor Market Impacts of Monetary Policy

ERIC Educational Resources Information Center

Carpenter, Seth B.; Rodgers, William M., III

2004-01-01

Employing two widely used approaches to identify the effects of monetary policy, this paper explores the differential impact of policy on the labor market outcomes of teenagers, minorities, out-of-school youth, and less-skilled individuals. Evidence from recursive vector autoregressions and autoregressive distributed lag models that use…

Spatial Autocorrelation And Autoregressive Models In Ecology

Treesearch

Jeremy W. Lichstein; Theodore R. Simons; Susan A. Shriner; Kathleen E. Franzreb

2003-01-01

Abstract. Recognition and analysis of spatial autocorrelation has defined a new paradigm in ecology. Attention to spatial pattern can lead to insights that would have been otherwise overlooked, while ignoring space may lead to false conclusions about ecological relationships. We used Gaussian spatial autoregressive models, fit with widely available...

Airborne Infectious Agents and Other Pollutants in Automobiles for Domestic Use: Potential Health Impacts and Approaches to Risk Mitigation

PubMed Central

Zargar, Bahram; Rubino, Joseph R.

2016-01-01

The world total of passenger cars is expected to go from the current one billion to >2.5 billion by 2050. Cars for domestic use account for ~74% of the world's yearly production of motorized vehicles. In North America, ~80% of the commuters use their own car with another 5.6% travelling as passengers. With the current life-expectancy of 78.6 years, the average North American spends 4.3 years driving a car! This equates to driving 101 minutes/day with a lifetime driving distance of nearly 1.3 million km inside the confined and often shared space of the car with exposure to a mix of potentially harmful pathogens, allergens, endotoxins, particulates, and volatile organics. Such risks may increase in proportion to the unprecedented upsurge in the numbers of family cars globally. Though new technologies may reduce the levels of air pollution from car exhausts and other sources, they are unlikely to impact our in-car exposure to pathogens. Can commercial in-car air decontamination devices reduce the risk from airborne infections and other pollutants? We lack scientifically rigorous protocols to verify the claims of such devices. Here we discuss the essentials of a customized aerobiology facility and test protocols to assess such devices under field-relevant conditions. PMID:28042302

Airborne Infectious Agents and Other Pollutants in Automobiles for Domestic Use: Potential Health Impacts and Approaches to Risk Mitigation.

PubMed

Sattar, Syed A; Wright, Kathryn E; Zargar, Bahram; Rubino, Joseph R; Ijaz, M Khalid

2016-01-01

The world total of passenger cars is expected to go from the current one billion to >2.5 billion by 2050. Cars for domestic use account for ~74% of the world's yearly production of motorized vehicles. In North America, ~80% of the commuters use their own car with another 5.6% travelling as passengers. With the current life-expectancy of 78.6 years, the average North American spends 4.3 years driving a car! This equates to driving 101 minutes/day with a lifetime driving distance of nearly 1.3 million km inside the confined and often shared space of the car with exposure to a mix of potentially harmful pathogens, allergens, endotoxins, particulates, and volatile organics. Such risks may increase in proportion to the unprecedented upsurge in the numbers of family cars globally. Though new technologies may reduce the levels of air pollution from car exhausts and other sources, they are unlikely to impact our in-car exposure to pathogens. Can commercial in-car air decontamination devices reduce the risk from airborne infections and other pollutants? We lack scientifically rigorous protocols to verify the claims of such devices. Here we discuss the essentials of a customized aerobiology facility and test protocols to assess such devices under field-relevant conditions.

Problem of the Used Cars Import on the Territory of the Russian Federation

NASA Astrophysics Data System (ADS)

Taskaev, Vladimir; Taskaeva, Natalia

2017-10-01

Authors completed the analysis of the accepted practice of classification of the sawn car bodies in Russia. They conclude that the tools of the Product Range of Foreign Economic Activity do not allow to classify the front and rear parts of the car as goods. Nowadays the participants of foreign economic activity sent the efforts to search for any new way to cut the customs payments. Meanwhile that is not incidental, that during car sale, the sellers specify in their offers not only purely technical characteristics but also the fact that “It is not a Sawn Car”. Thereby the sellers of cars agree that the car, obtained by joint of the sawn parts in the handicraft conditions, have an uncertainty of such important characteristic as safety, and that reduces the consumer properties of the purchase. Many buyers consider unsafe and even impossible to use the car in which such fundamental characteristic as safety is not provided. Therefore, the attempts of customs to carry out any classification of goods in the commodity position 8703 for the increase in collectable customs payments have a negative side as the matters of health and life of future owner of the car are concerned.

Characteristics of particulate matter emissions from toy cars with electric motors.

PubMed

Wang, Xiaofei; Williams, Brent J; Biswas, Pratim

2015-04-01

Aerosol emissions from toy cars with electric motors were characterized. Particle emission rates from the toy cars, as high as 7.47×10(7) particles/s, were measured. This emission rate is lower than other indoor sources such as smoking and cooking. The particles emitted from toy cars are generated from spark discharges inside the electric motors that power the toy cars. Size distribution measurements indicated that most particles were below 100 nm in diameter. Copper was the dominant inorganic species in these particles. By deploying aerosol mass spectrometers, high concentrations of particulate organic matter were also detected and characterized in detail. Several organic compounds were identified using a thermal desorption aerosol gas chromatography. The mass size distribution of particulate organic matter was bimodal. The formation mechanism of particulate organic matter from toy cars was elucidated. A possible new source of indoor air pollution, particles from electric motors in toy cars, was identified. This study characterized aerosol emissions from toy cars in detail. Most of these particles have a diameter less than 100 nm. Copper and some organics are the major components of these particles. Conditions that minimize these emissions were determined.

Carotenoids, versatile components of oxygenic photosynthesis.

PubMed

Domonkos, Ildikó; Kis, Mihály; Gombos, Zoltán; Ughy, Bettina

2013-10-01

Carotenoids (CARs) are a group of pigments that perform several important physiological functions in all kingdoms of living organisms. CARs serve as protective agents, which are essential structural components of photosynthetic complexes and membranes, and they play an important role in the light harvesting mechanism of photosynthesizing plants and cyanobacteria. The protection against reactive oxygen species, realized by quenching of singlet oxygen and the excited states of photosensitizing molecules, as well as by the scavenging of free radicals, is one of the main biological functions of CARs. X-ray crystallographic localization of CARs revealed that they are present at functionally and structurally important sites of both the PSI and PSII reaction centers. Characterization of a CAR-less cyanobacterial mutant revealed that while the absence of CARs prevents the formation of PSII complexes, it does not abolish the assembly and function of PSI. CAR molecules assist in the formation of protein subunits of the photosynthetic complexes by gluing together their protein components. In addition to their aforementioned indispensable functions, CARs have a substantial role in the formation and maintenance of proper cellular architecture, and potentially also in the protection of the translational machinery under stress conditions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Features of the Vision of Elderly Pedestrians when Crossing a Road.

PubMed

Matsui, Yasuhiro; Oikawa, Shoko; Aoki, Yoshio; Sekine, Michiaki; Mitobe, Kazutaka

2014-11-01

The present study clarifies the mechanism by which an accident occurs when an elderly pedestrian crosses a road in front of a car, focusing on features of the central and peripheral vision of elderly pedestrians who are judging when it is safe to cross the road. For the pedestrian's central visual field, we investigated the effect of age on the timing judgment using an actual car. The results for daytime conditions indicate that the elderly pedestrians tended to make later judgments of when they crossed the road from the right side of the driver's view at high car velocities. At night, for a car with its headlights on high beam, the average car-pedestrian distances of elderly pedestrians on the left side of the driver's view were significantly longer than those of young pedestrians at velocities of 20 and 40 km/h. The eyesight of the elderly pedestrians during the day did not affect the timing judgment of crossing a road. At night, for a car with its headlights on either high or low beam, the average car-pedestrian distances of elderly pedestrians having good eyesight were longer than those of elderly pedestrians having poor eyesight, for all car velocities. The color of the car body in the central visual field did not affect the timing judgment of elderly pedestrians crossing the road. Meanwhile, the car-body color in the elderly pedestrian's peripheral vision strongly affected the pedestrian's awareness of the car.

Health Monitoring System for Car Seat

NASA Technical Reports Server (NTRS)

Elrod, Susan Vinz (Inventor); Dabney, Richard W. (Inventor)

2004-01-01

A health monitoring system for use with a child car seat has sensors mounted in the seat to monitor one or more health conditions of the seat's occupant. A processor monitors the sensor's signals and generates status signals related to the monitored conditions. A transmitter wireless transmits the status signals to a remotely located receiver. A signaling device coupled to the receiver produces at least one sensory (e.g., visual, audible, tactile) output based on the status signals.

Effects of miles per gallon feedback on fuel efficiency in gas-powered cars.

DOT National Transportation Integrated Search

2009-10-01

This study tested the impact of continuous miles per gallon (MPG) feedback on driving : behavior and fuel efficiency in gas-powered cars. We compared an experimental condition, : where drivers received real-time MPG feedback and a tip sheet, to a con...

Forecasting typhoid fever incidence in the Cordillera administrative region in the Philippines using seasonal ARIMA models

NASA Astrophysics Data System (ADS)

Cawiding, Olive R.; Natividad, Gina May R.; Bato, Crisostomo V.; Addawe, Rizavel C.

2017-11-01

The prevalence of typhoid fever in developing countries such as the Philippines calls for a need for accurate forecasting of the disease. This will be of great assistance in strategic disease prevention. This paper presents a development of useful models that predict the behavior of typhoid fever incidence based on the monthly incidence in the provinces of the Cordillera Administrative Region from 2010 to 2015 using univariate time series analysis. The data used was obtained from the Cordillera Office of the Department of Health (DOH-CAR). Seasonal autoregressive moving average (SARIMA) models were used to incorporate the seasonality of the data. A comparison of the results of the obtained models revealed that the SARIMA (1,1,7)(0,0,1)12 with a fixed coefficient at the seventh lag produces the smallest root mean square error (RMSE), mean absolute error (MAE), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The model suggested that for the year 2016, the number of cases would increase from the months of July to September and have a drop in December. This was then validated using the data collected from January 2016 to December 2016.

Application of multivariate autoregressive spectrum estimation to ULF waves

NASA Technical Reports Server (NTRS)

Ioannidis, G. A.

1975-01-01

The estimation of the power spectrum of a time series by fitting a finite autoregressive model to the data has recently found widespread application in the physical sciences. The extension of this method to the analysis of vector time series is presented here through its application to ULF waves observed in the magnetosphere by the ATS 6 synchronous satellite. Autoregressive spectral estimates of the power and cross-power spectra of these waves are computed with computer programs developed by the author and are compared with the corresponding Blackman-Tukey spectral estimates. The resulting spectral density matrices are then analyzed to determine the direction of propagation and polarization of the observed waves.

Vector Autoregression, Structural Equation Modeling, and Their Synthesis in Neuroimaging Data Analysis

PubMed Central

Chen, Gang; Glen, Daniel R.; Saad, Ziad S.; Hamilton, J. Paul; Thomason, Moriah E.; Gotlib, Ian H.; Cox, Robert W.

2011-01-01

Vector autoregression (VAR) and structural equation modeling (SEM) are two popular brain-network modeling tools. VAR, which is a data-driven approach, assumes that connected regions exert time-lagged influences on one another. In contrast, the hypothesis-driven SEM is used to validate an existing connectivity model where connected regions have contemporaneous interactions among them. We present the two models in detail and discuss their applicability to FMRI data, and interpretational limits. We also propose a unified approach that models both lagged and contemporaneous effects. The unifying model, structural vector autoregression (SVAR), may improve statistical and explanatory power, and avoids some prevalent pitfalls that can occur when VAR and SEM are utilized separately. PMID:21975109

Prediction of energy balance and utilization for solar electric cars

NASA Astrophysics Data System (ADS)

Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

2017-11-01

Solar irradiation and ambient temperature are characterized by region, season and time-domain, which directly affects the performance of solar energy based car system. In this paper, the model of solar electric cars used was based in Xi’an. Firstly, the meteorological data are modelled to simulate the change of solar irradiation and ambient temperature, and then the temperature change of solar cell is calculated using the thermal equilibrium relation. The above work is based on the driving resistance and solar cell power generation model, which is simulated under the varying radiation conditions in a day. The daily power generation and solar electric car cruise mileage can be predicted by calculating solar cell efficiency and power. The above theoretical approach and research results can be used in the future for solar electric car program design and optimization for the future developments.

Chimeric Antigen Receptor-Redirected T cells return to the bench

PubMed Central

Geldres, Claudia; Savoldo, Barbara; Dotti, Gianpietro

2016-01-01

While the clinical progress of chimeric antigen receptor T cell (CAR-T) immunotherapy has garnered attention to the field, our understanding of the biology of these chimeric molecules is still emerging. Our aim within this review is to bring to light the mechanistic understanding of these multi-modular receptors and how these individual components confer particular properties to CAR-Ts. In addition, we will discuss extrinsic factors that can be manipulated to influence CAR-T performance such as choice of cellular population, culturing conditions and additional modifications that enhance their activity particularly in solid tumors. Finally, we will also consider the emerging toxicity associated with CAR-Ts. By breaking apart the CAR and examining the role of each piece, we can build a better functioning cellular vehicle for optimized treatment of cancer patients. PMID:26797495

Numerical analysis of air-flow and temperature field in a passenger car compartment

NASA Astrophysics Data System (ADS)

Kamar, Haslinda Mohamed; Kamsah, Nazri; Mohammad Nor, Ahmad Miski

2012-06-01

This paper presents a numerical study on the temperature field inside a passenger's compartment of a Proton Wira saloon car using computational fluid dynamics (CFD) method. The main goal is to investigate the effects of different glazing types applied onto the front and rear windscreens of the car on the distribution of air-temperature inside the passenger compartment in the steady-state conditions. The air-flow condition in the passenger's compartment is also investigated. Fluent CFD software was used to develop a three-dimensional symmetrical model of the passenger's compartment. Simplified representations of the driver and one rear passenger were incorporated into the CFD model of the passenger's compartment. Two types of glazing were considered namely clear insulated laminated tint (CIL) with a shading coefficient of 0.78 and green insulated laminate tint (GIL) with a shading coefficient of 0.5. Results of the CFD analysis were compared with those obtained when the windscreens are made up of clear glass having a shading coefficient of 0.86. Results of the CFD analysis show that for a given glazing material, the temperature of the air around the driver is slightly lower than the air around the rear passenger. Also, the use of GIL glazing material on both the front and rear windscreens significantly reduces the air temperature inside the passenger's compartment of the car. This contributes to a better thermal comfort condition to the occupants. Swirling air flow condition occurs in the passenger compartment. The air-flow intensity and velocity are higher along the side wall of the passenger's compartment compared to that along the middle section of the compartment. It was also found that the use of glazing materials on both the front and rear windscreen has no significant effects on the air-flow condition inside the passenger's compartment of the car.

Evaluation of temporary traffic signals in conjunction with pilot car operations at two-way long temporary work zones.

DOT National Transportation Integrated Search

2016-05-01

The primary objective of this study was to evaluate the use of Portable Traffic Signal (PTS) systems at long, rural : two-lane work zones and to compare three different conditions for controlling one-lane traffic in conjunction with pilot car : opera...

Results of Energy-Loss Measurements on Passenger Car Tires Operating in the Free-Rolling and Braking/Traction Modes

DOT National Transportation Integrated Search

1980-01-01

This report described the results of tests on twelve passenger car tires performed on Calspan's Tire Research Facility (CTRF). The tests were used to measure energy loss under three different test conditions: 1) with the tire in a straight, free-roll...

Track/train dynamics test procedure transfer function test

NASA Technical Reports Server (NTRS)

Vigil, R. A.

1975-01-01

A transfer function vibration test was made on an 80 ton open hopper freight car in an effort to obtain validation data on the car's nonlinear elastic model. Test configuration, handling, test facilities, test operations, and data acquisition/reduction activities necessary to meet the conditions of test requirements are given.

The new car following model considering vehicle dynamics influence and numerical simulation

NASA Astrophysics Data System (ADS)

Sun, Dihua; Liu, Hui; Zhang, Geng; Zhao, Min

2015-12-01

In this paper, the car following model is investigated by considering the vehicle dynamics in a cyber physical view. In fact, that driving is a typical cyber physical process which couples the cyber aspect of the vehicles' information and driving decision tightly with the dynamics and physics of the vehicles and traffic environment. However, the influence from the physical (vehicle) view was been ignored in the previous car following models. In order to describe the car following behavior more reasonably in real traffic, a new car following model by considering vehicle dynamics (for short, D-CFM) is proposed. In this paper, we take the full velocity difference (FVD) car following model as a case. The stability condition is given on the base of the control theory. The analytical method and numerical simulation results show that the new models can describe the evolution of traffic congestion. The simulations also show vehicles with a more actual acceleration of starting process than early models.

Temperature rise and Heat build up inside a parked Car

NASA Astrophysics Data System (ADS)

Coady, Rose; Maheswaranathan, Ponn

2001-11-01

We have studied the heat build up inside a parked car under the hot summer Sun. Inside and outside temperatures were monitored every ten seconds from 9 AM to about 4 PM for a 2000 Toyota Camry parked in a Winthrop University parking lot without any shades or trees. Two PASCO temperature sensors, one inside the car and the other outside the car, are used along with PASCO-750 interface to collect the data. Data were collected under the following conditions while keeping track of the outside weather: fully closed windows, slightly open windows, half way open windows, fully open windows, and with window shades inside and outside. Inside temperatures reached as high as 150 degrees Fahrenheit on a sunny day with outside high temperature of about 100 degrees Fahrenheit. These results will be presented along with results from car cover and window tint manufacturers and suggestions to keep your car cool next time you park it under the Sun.

Modelling of cayenne production in Central Java using ARIMA-GARCH

NASA Astrophysics Data System (ADS)

Tarno; Sudarno; Ispriyanti, Dwi; Suparti

2018-05-01

Some regencies/cities in Central Java Province are known as producers of horticultural crops in Indonesia, for example, Brebes which is the largest area of shallot producer in Central Java, while the others, such as Cilacap and Wonosobo are the areas of cayenne commodities production. Currently, cayenne is a strategic commodity and it has broad impact to Indonesian economic development. Modelling the cayenne production is necessary to predict about the commodity to meet the need for society. The needs fulfillment of society will affect stability of the concerned commodity price. Based on the reality, the decreasing of cayenne production will cause the increasing of society’s basic needs price, and finally it will affect the inflation level at that area. This research focused on autoregressive integrated moving average (ARIMA) modelling by considering the effect of autoregressive conditional heteroscedasticity (ARCH) to study about cayenne production in Central Java. The result of empirical study of ARIMA-GARCH modelling for cayenne production in Central Java from January 2003 to November 2015 is ARIMA([1,3],0,0)-GARCH(1,0) as the best model.

A time series model: First-order integer-valued autoregressive (INAR(1))

NASA Astrophysics Data System (ADS)

Simarmata, D. M.; Novkaniza, F.; Widyaningsih, Y.

2017-07-01

Nonnegative integer-valued time series arises in many applications. A time series model: first-order Integer-valued AutoRegressive (INAR(1)) is constructed by binomial thinning operator to model nonnegative integer-valued time series. INAR (1) depends on one period from the process before. The parameter of the model can be estimated by Conditional Least Squares (CLS). Specification of INAR(1) is following the specification of (AR(1)). Forecasting in INAR(1) uses median or Bayesian forecasting methodology. Median forecasting methodology obtains integer s, which is cumulative density function (CDF) until s, is more than or equal to 0.5. Bayesian forecasting methodology forecasts h-step-ahead of generating the parameter of the model and parameter of innovation term using Adaptive Rejection Metropolis Sampling within Gibbs sampling (ARMS), then finding the least integer s, where CDF until s is more than or equal to u . u is a value taken from the Uniform(0,1) distribution. INAR(1) is applied on pneumonia case in Penjaringan, Jakarta Utara, January 2008 until April 2016 monthly.

Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel

2016-01-01

Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.

Estimation of Value-at-Risk for Energy Commodities via CAViaR Model

NASA Astrophysics Data System (ADS)

Xiliang, Zhao; Xi, Zhu

This paper uses the Conditional Autoregressive Value at Risk model (CAViaR) proposed by Engle and Manganelli (2004) to evaluate the value-at-risk for daily spot prices of Brent crude oil and West Texas Intermediate crude oil covering the period May 21th, 1987 to Novermber 18th, 2008. Then the accuracy of the estimates of CAViaR model, Normal-GARCH, and GED-GARCH was compared. The results show that all the methods do good job for the low confidence level (95%), and GED-GARCH is the best for spot WTI price, Normal-GARCH and Adaptive-CAViaR are the best for spot Brent price. However, for the high confidence level (99%), Normal-GARCH do a good job for spot WTI, GED-GARCH and four kind of CAViaR specifications do well for spot Brent price. Normal-GARCH does badly for spot Brent price. The result seems suggest that CAViaR do well as well as GED-GARCH since CAViaR directly model the quantile autoregression, but it does not outperform GED-GARCH although it does outperform Normal-GARCH.

Projecting county pulpwood production with historical production and macro-economic variables

Treesearch

Consuelo Brandeis; Dayton M. Lambert

2014-01-01

We explored forecasting of county roundwood pulpwood produc-tion with county-vector autoregressive (CVAR) and spatial panelvector autoregressive (SPVAR) methods. The analysis used timberproducts output data for the state of Florida, together with a set ofmacro-economic variables. Overall, we found the SPVAR specifica-tion produced forecasts with lower error rates...

Functional MRI and Multivariate Autoregressive Models

PubMed Central

Rogers, Baxter P.; Katwal, Santosh B.; Morgan, Victoria L.; Asplund, Christopher L.; Gore, John C.

2010-01-01

Connectivity refers to the relationships that exist between different regions of the brain. In the context of functional magnetic resonance imaging (fMRI), it implies a quantifiable relationship between hemodynamic signals from different regions. One aspect of this relationship is the existence of small timing differences in the signals in different regions. Delays of 100 ms or less may be measured with fMRI, and these may reflect important aspects of the manner in which brain circuits respond as well as the overall functional organization of the brain. The multivariate autoregressive time series model has features to recommend it for measuring these delays, and is straightforward to apply to hemodynamic data. In this review, we describe the current usage of the multivariate autoregressive model for fMRI, discuss the issues that arise when it is applied to hemodynamic time series, and consider several extensions. Connectivity measures like Granger causality that are based on the autoregressive model do not always reflect true neuronal connectivity; however, we conclude that careful experimental design could make this methodology quite useful in extending the information obtainable using fMRI. PMID:20444566

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico.

PubMed

Johansson, Michael A; Reich, Nicholas G; Hota, Aditi; Brownstein, John S; Santillana, Mauricio

2016-09-26

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model.

Evaluating the performance of infectious disease forecasts: A comparison of climate-driven and seasonal dengue forecasts for Mexico

PubMed Central

Johansson, Michael A.; Reich, Nicholas G.; Hota, Aditi; Brownstein, John S.; Santillana, Mauricio

2016-01-01

Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model. PMID:27665707

The emission of BTEX compounds during movement of passenger car in accordance with the NEDC.

PubMed

Adamović, Dragan; Dorić, Jovan; Vojinović Miloradov, Mirjana; Adamović, Savka; Pap, Sabolč; Radonić, Jelena; Turk Sekulić, Maja

2018-05-20

The results of the research in the field of benzene, toluene, ethylbenzene and xylene isomers (BTEX) concentrations in exhaust gases of spark ignition engines under different operating conditions are presented in this paper. The aim of this paper is to gain a clearer insight into the impact of different engine working parameters on the concentrations of BTEX. The experimental investigation has been performed on the SCHENCK 230 W test stand with the controlled IC engine. The engine operating points have been chosen based on the results of a simulation and they are considered as the typical driving conditions according to the New European Driving Cycle. Concentration levels of BTEX compounds in exhaust gas mixtures have been determined by gas chromatography technique by using the combination of Supelcowax 10-Polyethylene glycol column and the PID detector. Based on the experimental research results, the emission model of BTEX compounds has been defined by the simulation of movement of a Fiat Punto Classic passenger car in accordance with the NEDC cycle. Using the results obtained within the simulation, the official statistics on the number of gasoline-powered cars on the territory of the Republic of Serbia and the European Commission data on the annual distance traveled by car, the amounts of BTEX compounds emitted annually per car have been estimated, as well as the emissions of the entire Serbian car fleet. Copyright © 2018 Elsevier B.V. All rights reserved.

Small passenger car transmission test; Chevrolet LUV transmission

NASA Technical Reports Server (NTRS)

Bujold, M. P.

1980-01-01

A 1978 Chevrolet LUV manual transmission tested per the applicable portions of a passenger car automatic transmission test code (SAE J65lb) which required drive performance, coast performance, and no load test conditions. Under these test conditions, the transmission attained maximum efficiencies in the upper ninety percent range for both drive performance tests and coast performance tests. The major results of this test (torque, speed, and efficiency curves) are presented. Graphs map the complete performance characteristics for the Chevrolet LUV transmission.

Small passenger car transmission test; Ford C4 transmission

NASA Technical Reports Server (NTRS)

Bujold, M. P.

1980-01-01

A 1979 Ford C4 automatic transmission was tested per a passenger car automatic transmission test code (SAE J651b) which required drive performance, coast performance, and no load test conditions. Under these test conditions, the transmission attained maximum efficiencies in the mid-eighty percent range for both drive performance tests and coast performance tests. The major results of this test (torque, speed, and efficiency curves) are presented. Graphs map the complete performance characteristics for the Ford C4 transmission.

Small passenger car transmission test: Mercury Lynx ATX transmission

NASA Technical Reports Server (NTRS)

Bujold, M. P.

1981-01-01

The testing of a Mercury Lynx automatic transmission is reported. The transmission was tested in accordance with a passenger car automatic transmission test code (SAE J65lb) which required drive performance, coast performance, and no load test conditions. Under these conditions, the transmission attained maximum efficiencies in the mid-ninety percent range both for drive performance test and coast performance tests. The torque, speed, and efficiency curves are presented, which provide the complete performance characteristics for the Mercury Lynx automatic transmission.

The Role of Evolutive Elastic Properties in the Performance of a Sheet Formed Spring Applied in Multimedia Car Industry

NASA Astrophysics Data System (ADS)

Faria, J.; Silva, J.; Bernardo, P.; Araújo, M.; Alves, J. L.

2016-08-01

The manufacturing process and the behaviour of a spring manufactured from an aluminium sheet is described and investigated in this work considering the specifications for the in-service conditions. The spring is intended to be applied in car multimedia industry to replace bolted connections. Among others, are investigated the roles of the constitutive parameters and the hypothesis of evolutive elastic properties with the plastic work in the multistep forming process and in working conditions.

Indoor to outdoor air quality associations with self-pollution implications inside passenger car cabins

NASA Astrophysics Data System (ADS)

Abi-Esber, L.; El-Fadel, M.

2013-12-01

In this study, in-vehicle and out-vehicle concentrations of fine particulate matter (PM2.5) and carbon monoxide (CO) are measured to assess commuter's exposure in a commercial residential area and on a highway, under three popular ventilation modes namely, one window half opened, air conditioning on fresh air intake, and air conditioning on recirculation and examine its relationship to scarcely studied parameters including self pollution, out-vehicle sample intake location and meteorological gradients. Self pollution is the intrusion of a vehicle's own engine fumes into the passenger's compartment. For this purpose, six car makes with different ages were instrumented to concomitantly monitor in- and out-vehicle PM2.5 and CO concentrations as well as meteorological parameters. Air pollution levels were unexpectedly higher in new cars compared to old cars, with in-cabin air quality most correlated to that of out-vehicle air near the front windshield. Self-pollution was observed at variable rates in three of the six tested cars. Significant correlations were identified between indoor to outdoor pressure difference and PM2.5 and CO In/Out (IO) ratios under air recirculation and window half opened ventilation modes whereas temperature and humidity difference affected CO IO ratios only under the air recirculation ventilation mode.

The influence of action on episodic memory: a virtual reality study.

PubMed

Plancher, Gaën; Barra, Julien; Orriols, Eric; Piolino, Pascale

2013-01-01

A range of empirical findings suggest that active learning is important for memory. However, few studies have focused on the mechanisms underlying this enactment effect in episodic memory using complex environments. Research using virtual reality has yielded inconsistent results. We postulated that the effect of action depends on the degree of interaction with the environment and freedom in the planning of an itinerary. To test these hypotheses, we disentangled the interaction and planning components of action to investigate whether each enhances factual and spatial memory. Seventy-two participants (36 male and 36 female) explored a virtual town in one of three experimental conditions: (a) a passive condition where participants were immersed as passenger of the car (no interaction, no planning); (b) a planning-only condition (the subject chose the itinerary but did not drive the car); (c) an interaction-only condition (the subject drove the car but the itinerary was fixed). We found that itinerary choice and motor control both enhanced spatial memory, while factual memory was impaired by online motor control. The role of action in memory is discussed.

Nonconformities in real-world fatal crashes--electronic stability control and seat belt reminders.

PubMed

Lie, Anders

2012-01-01

Many new safety systems are entering the market. Vision Zero is a safety strategy aiming at the elimination of fatalities and impairing injuries by the use of a holistic model for safe traffic to develop a safe system. The aim of this article is to analyze fatalities in modern cars with respect to the Vision Zero model with special respect to electronic stability control (ESC) systems and modern seat belt reminders (SBRs). The model is used to identify and understand cases where cars with ESC systems lost control and where occupants were unbelted in a seat with seat belt reminders under normal driving conditions. The model for safe traffic was used to analyze in-depth studies of fatal crashes with respect to seat belt use and loss of control. Vehicles from 2003 and later in crashes from January 2004 to mid-2010 were analyzed. The data were analyzed case by case. Cars that were equipped with ESC systems and lost control and occupants not using the seat belt in a seat with a seat belt reminder were considered as nonconformities. A total of 138 fatal crashes involving 152 fatally injured occupants were analyzed. Cars with ESC systems had fewer loss-of-control-relevant cases than cars without ESC systems. Thirteen percent of the ESC-equipped vehicles had loss-of-control-relevant crashes and 36 percent of the cars without ESC systems had loss-of-control-relevant crashes. The analysis indicates that only one car of the 9 equipped with ESC that lost control did it on a road surface with relevant friction when driving within the speed restriction of the road. In seats with seat belt reminders that are in accordance with the European New Car Assessment Programme's (Euro NCAP) protocol, 93 percent of the occupants were using a seat belt. In seats without reminders this number was 74 percent. This study shows that ESC systems result in a very significant reduction in fatal crashes, especially under normal driving conditions. Under extreme driving conditions such as speeding or extremely low friction (snow or on the side of the road), ESC systems can fail in keeping the car under control. Seat belt reminders result in higher seat belt use rates but the level of unbelted occupants is higher than roadside studies have indicated. The holistic Vision Zero approach helped in the analysis by identifying nonconformities and putting these into the safe systems perspective.

Relative risk for HIV in India - An estimate using conditional auto-regressive models with Bayesian approach.

PubMed

Kandhasamy, Chandrasekaran; Ghosh, Kaushik

2017-02-01

Indian states are currently classified into HIV-risk categories based on the observed prevalence counts, percentage of infected attendees in antenatal clinics, and percentage of infected high-risk individuals. This method, however, does not account for the spatial dependence among the states nor does it provide any measure of statistical uncertainty. We provide an alternative model-based approach to address these issues. Our method uses Poisson log-normal models having various conditional autoregressive structures with neighborhood-based and distance-based weight matrices and incorporates all available covariate information. We use R and WinBugs software to fit these models to the 2011 HIV data. Based on the Deviance Information Criterion, the convolution model using distance-based weight matrix and covariate information on female sex workers, literacy rate and intravenous drug users is found to have the best fit. The relative risk of HIV for the various states is estimated using the best model and the states are then classified into the risk categories based on these estimated values. An HIV risk map of India is constructed based on these results. The choice of the final model suggests that an HIV control strategy which focuses on the female sex workers, intravenous drug users and literacy rate would be most effective. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tumor-targeted T cells modified to secrete IL-12 eradicate systemic tumors without need for prior conditioning

PubMed Central

Pegram, Hollie J.; Lee, James C.; Hayman, Erik G.; Imperato, Gavin H.; Tedder, Thomas F.; Sadelain, Michel

2012-01-01

Adoptive cell therapy with tumor-targeted T cells is a promising approach to cancer therapy. Enhanced clinical outcome using this approach requires conditioning regimens with total body irradiation, lymphodepleting chemotherapy, and/or additional cytokine support. However, the need for prior conditioning precludes optimal application of this approach to a significant number of cancer patients intolerant to these regimens. Herein, we present preclinical studies demonstrating that treatment with CD19-specific, chimeric antigen receptor (CAR)–modified T cells that are further modified to constitutively secrete IL-12 are able to safely eradicate established disease in the absence of prior conditioning. We demonstrate in a novel syngeneic tumor model that tumor elimination requires both CD4+ and CD8+ T-cell subsets, autocrine IL-12 stimulation, and subsequent IFNγ secretion by the CAR+ T cells. Importantly, IL-12–secreting, tumor-targeted T cells acquire intrinsic resistance to T regulatory cell–mediated inhibition. Based on these preclinical data, we anticipate that adoptive therapy using CAR-targeted T cells modified to secrete IL-12 will obviate or reduce the need for potentially hazardous conditioning regimens to achieve optimal antitumor responses in cancer patients. PMID:22354001

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

Kearney, Sean Patrick

A hybrid fs/ps pure-rotational coherent anti-Stokes Raman scattering (CARS) scheme is systematically evaluated over a wide range of flame conditions in the product gases of two canonical flat-flame burners. Near-transform-limited, broadband femtosecond pump and Stokes pulses impulsively prepare a rotational Raman coherence, which is later probed using a high-energy, frequency-narrow picosecond beam generated by the second-harmonic bandwidth compression scheme that has recently been demonstrated for rotational CARS generation in H 2/air flat flames. The measured spectra are free of collision effects and nonresonant background and can be obtained on a single-shot basis at 1 kHz. The technique is evaluated formore » temperature/oxygen measurements in near-adiabatic H 2/air flames stabilized on the Hencken burner for equivalence ratios of φ = 0.20–1.20. Thermometry is demonstrated in hydrocarbon/air products for φ = 0.75–3.14 in premixed C 2H 4/air flat flames on the McKenna burner. Reliable spectral fitting is demonstrated for both shot-averaged and single-laser-shot data using a simple phenomenological model. Measurement accuracy is benchmarked by comparison to adiabatic-equilibrium calculations for the H 2/air flames, and by comparison with nanosecond CARS measurements for the C 2H 4/air flames. Quantitative accuracy comparable to nanosecond rotational CARS measurements is observed, while the observed precision in both the temperature and oxygen data is extraordinarily high, exceeding nanosecond CARS, and on par with the best published thermometric precision by femtosecond vibrational CARS in flames, and rotational femtosecond CARS at low temperature. Threshold levels of signal-to-noise ratio to achieve 1–2% precision in temperature and O 2/N 2 ratio are identified. Our results show that pure-rotational fs/ps CARS is a robust and quantitative tool when applied across a wide range of flame conditions spanning lean H 2/air combustion to fuel-rich sooting hydrocarbon flames.« less

Carbon accumulation in a permafrost polygon peatland: steady long-term rates in spite of shifts between dry and wet conditions.

PubMed

Gao, Yang; Couwenberg, John

2015-02-01

Ice-wedge polygon peatlands contain a substantial part of the carbon stored in permafrost soils. However, little is known about their long-term carbon accumulation rates (CAR) in relation to shifts in vegetation and climate. We collected four peat profiles from one single polygon in NE Yakutia and cut them into contiguous 0.5 cm slices. Pollen density interpolation between AMS (14)C dated levels provided the time span contained in each of the sample slices, which--in combination with the volumetric carbon content--allowed for the reconstruction of CAR over decadal and centennial timescales. Vegetation representing dry palaeo-ridges and wet depressions was reconstructed with detailed micro- and macrofossil analysis. We found repeated shifts between wet and dry conditions during the past millennium. Dry ridges with associated permafrost growth originated during phases of (relatively) warm summer temperature and collapsed during relatively cold phases, illustrating the important role of vegetation and peat as intermediaries between ambient air temperature and the permafrost. The average long-term CAR across the four profiles was 10.6 ± 5.5 g C m(-2) yr(-1). Time-weighted mean CAR did not differ significantly between wet depression and dry ridge/hummock phases (10.6 ± 5.2 g C m(-2) yr(-1) and 10.3 ± 5.7 g C m(-2) yr(-1), respectively). Although we observed increased CAR in relation to warm shifts, we also found changes in the opposite direction and the highest CAR actually occurred during the Little Ice Age. In fact, CAR rather seems to be governed by strong internal feedback mechanisms and has roughly remained stable on centennial time scales. The absence of significant differences in CAR between dry ridge and wet depression phases suggests that recent warming and associated expansion of shrubs will not affect long-term rates of carbon burial in ice-wedge polygon peatlands. © 2014 John Wiley & Sons Ltd.

Numerical study on wake characteristics of high-speed trains

NASA Astrophysics Data System (ADS)

Yao, Shuan-Bao; Sun, Zhen-Xu; Guo, Di-Long; Chen, Da-Wei; Yang, Guo-Wei

2013-12-01

Intensive turbulence exists in the wakes of high speed trains, and the aerodynamic performance of the trailing car could deteriorate rapidly due to complicated features of the vortices in the wake zone. As a result, the safety and amenity of high speed trains would face a great challenge. This paper considers mainly the mechanism of vortex formation and evolution in the train flow field. A real CRH2 model is studied, with a leading car, a middle car and a trailing car included. Different running speeds and cross wind conditions are considered, and the approaches of unsteady Reynold-averaged Navier-Stokes (URANS) and detached eddy simulation (DES) are utilized, respectively. Results reveal that DES has better capability of capturing small eddies compared to URANS. However, for large eddies, the effects of two approaches are almost the same. In conditions without cross winds, two large vortex streets stretch from the train nose and interact strongly with each other in the wake zone. With the reinforcement of the ground, a complicated wake vortex system generates and becomes strengthened as the running speed increases. However, the locations of flow separations on the train surface and the separation mechanism keep unchanged. In conditions with cross winds, three large vortices develop along the leeward side of the train, among which the weakest one has no obvious influence on the wake flow while the other two stretch to the tail of the train and combine with the helical vortices in the train wake. Thus, optimization of the aerodynamic performance of the trailing car should be aiming at reducing the intensity of the wake vortex system.

Performance of the Prognocean Plus system during the El Niño 2015/2016: predictions of sea level anomalies as tools for forecasting El Niño

NASA Astrophysics Data System (ADS)

Świerczyńska-Chlaściak, Małgorzata; Niedzielski, Tomasz; Miziński, Bartłomiej

2017-04-01

The aim of this paper is to present the performance of the Prognocean Plus system, which produces long-term predictions of sea level anomalies, during the El Niño 2015/2016. The main objective of work is to identify such ocean areas in which long-term forecasts of sea level anomalies during El Niño 2015/2016 reveal a considerable accuracy. At present, the system produces prognoses using four data-based models and their combinations: polynomial-harmonic model, autoregressive model, threshold autoregressive model and multivariate autoregressive model. The system offers weekly forecasts, with lead time up to 12 weeks. Several statistics that describe the efficiency of the available prediction models in four seasons used for estimating Oceanic Niño index (ONI) are calculated. The accuracies/skills of the predicting models were computed in the specific locations in the equatorial Pacific, namely the geometrically-determined central points of all Niño regions. For the said locations, we focused on the forecasts which targeted at the local maximum of sea level, driven by the El Niño 2015/2016. As a result, a series of the "spaghetti" graphs (for each point, season and model) as well as plots presenting the prognostic performance of every model - for all lead times, seasons and locations - were created. It is found that the Prognocean Plus system has a potential to become a new solution which may enhance the diagnostic discussions on the El Niño development. The forecasts produced by the threshold autoregressive model, for lead times of 5-6 weeks and 9 weeks, within the Niño1+2 region for the November-to-January (NDJ) season anticipated the culmination of the El Niño 2015/2016. The longest forecasts (8-12 weeks) were found to be the most accurate in the phase of transition from El Niño to normal conditions (the multivariate autoregressive model, central point of Niño1+2 region, the December-to-February season). The study was conducted to verify the ability and usefulness of sea level anomaly forecasts in predicting phenomena that are controlled by the ocean-atmosphere processes, such as El Niño Southern Oscillation or North Atlantic Oscillation. The results may support further investigations into long-term forecasting of the quantitative indices of these oscillations, solely based on prognoses of sea level change. In particular, comparing the accuracies of prognoses of the North Atlantic Oscillation index remains one of the tasks of the research project no. 2016/21/N/ST10/03231, financed by the National Science Center of Poland.

Within- and between-session reliability of the maximal voluntary knee extension torque and activation.

PubMed

Park, Jihong; Hopkins, J Ty

2013-01-01

A ratio between the torque generated by maximal voluntary isometric contraction (MVIC) and exogenous electrical stimulus, central activation ratio (CAR), has been widely used to assess quadriceps function. To date, no data exist regarding between-session reliability of this measurement. Thirteen neurologically sound volunteers underwent three testing sessions (three trials per session) with 48 hours between-session. Subjects performed MVICs of the quadriceps with the knee locked at 90° flexion and the hip at 85°. Once the MVIC reached a plateau, an electrical stimulation from superimposed burst technique (SIB: 125 V with peak output current 450 mA) was manually delivered and transmitted directly to the quadriceps via stimulating electrodes. CAR was calculated by using the following equation: CAR = MVIC torque/MVIC + SIB torque. Intraclass correlation coefficients (ICC) were calculated within- (ICC((2,1))) and between-session (ICC((2,k))) for MVIC torques and CAR values. Our data show that quadriceps MVIC and CAR are very reliable both within- (ICC((2,1)) = 0.99 for MVIC; 0.94 for CAR) and between-measurement sessions (ICC((2,k)) = 0.92 for MVIC; 0.86 for CAR) in healthy young adults. For clinical research, more data of the patients with pathological conditions are required to ensure reproducibility of calculation of CAR.

Time-resolved two-photon spectroscopy of photosystem I determines hidden carotenoid dark-state dynamics.

PubMed

Wehling, Axel; Walla, Peter J

2005-12-29

We present time-resolved fs two-photon pump-probe data measured with photosystem I (PS I) of Thermosynechococcus elongatus. Two-photon excitation (lambda(exc)/2 = 575 nm) in the spectral region of the optically forbidden first excited singlet state of the carotenoids, Car S1, gives rise to a 800 fs and a 9 ps decay component of the Car S1 --> S(n) excited-state absorption with an amplitude of about 47 +/- 16% and 53 +/- 10%, respectively. By measuring a solution of pure beta-carotene under exactly the same conditions, only a 9 ps decay component can be observed. Exciting PS I at exactly the same spectral region via one-photon excitation (lambda(exc) = 575 nm) also does not show any sub-ps component. We ascribe the observed constant of 800 fs to a portion of about 47 +/- 16% beta-carotene states that can potentially transfer their energy efficiently to chlorophyll pigments via the optically dark Car S1 state. We compared these data with conventional one-photon pump-probe data, exciting the optically allowed second excited state, Car S2. This comparison demonstrates that the fast dynamics of the optically forbidden state can hardly be unravelled via conventional one-photon excitation only because the corresponding Car S1 populations are too small after Car S2 --> Car S1 internal conversion. A direct comparison of the amplitudes of the Car S1 --> S(n) excited-state absorption of PS I and beta-carotene observed after Car S2 excitation allows determination of a quantum yield for the Car S1 formation in PS I of 44 +/- 5%. In conclusion, an overall Car S2 --> Chl energy-transfer efficiency of approximately 69 +/- 5% is observed at room temperature with 56 +/- 5% being transferred via Car S2 and probably very hot Car S1 states and 13 +/- 5% being transferred via hot and "cold" Car S1 states.

Evaluation of temporary traffic signals in conjunction with pilot car operations at two-way long temporary work zones : technical summary.

DOT National Transportation Integrated Search

2016-05-01

The primary objective of this study was to evaluate the use of Portable Traffic Signal (PTS) systems at long, rural two-lane work zones and to compare three different conditions for controlling one-lane traffic in conjunction with pilot car operation...

Equivalent Dynamic Models.

PubMed

Molenaar, Peter C M

2017-01-01

Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

Hybrid fs/ps rotational CARS temperature and oxygen measurements in the product gases of canonical flat flames

DOE PAGES

Kearney, Sean Patrick

2014-12-31

A hybrid fs/ps pure-rotational coherent anti-Stokes Raman scattering (CARS) scheme is systematically evaluated over a wide range of flame conditions in the product gases of two canonical flat-flame burners. Near-transform-limited, broadband femtosecond pump and Stokes pulses impulsively prepare a rotational Raman coherence, which is later probed using a high-energy, frequency-narrow picosecond beam generated by the second-harmonic bandwidth compression scheme that has recently been demonstrated for rotational CARS generation in H 2/air flat flames. The measured spectra are free of collision effects and nonresonant background and can be obtained on a single-shot basis at 1 kHz. The technique is evaluated formore » temperature/oxygen measurements in near-adiabatic H 2/air flames stabilized on the Hencken burner for equivalence ratios of φ = 0.20–1.20. Thermometry is demonstrated in hydrocarbon/air products for φ = 0.75–3.14 in premixed C 2H 4/air flat flames on the McKenna burner. Reliable spectral fitting is demonstrated for both shot-averaged and single-laser-shot data using a simple phenomenological model. Measurement accuracy is benchmarked by comparison to adiabatic-equilibrium calculations for the H 2/air flames, and by comparison with nanosecond CARS measurements for the C 2H 4/air flames. Quantitative accuracy comparable to nanosecond rotational CARS measurements is observed, while the observed precision in both the temperature and oxygen data is extraordinarily high, exceeding nanosecond CARS, and on par with the best published thermometric precision by femtosecond vibrational CARS in flames, and rotational femtosecond CARS at low temperature. Threshold levels of signal-to-noise ratio to achieve 1–2% precision in temperature and O 2/N 2 ratio are identified. Our results show that pure-rotational fs/ps CARS is a robust and quantitative tool when applied across a wide range of flame conditions spanning lean H 2/air combustion to fuel-rich sooting hydrocarbon flames.« less

Performance consequences of alternating directional control-response compatibility: evidence from a coal mine shuttle car simulator.

PubMed

Zupanc, Christine M; Burgess-Limerick, Robin J; Wallis, Guy

2007-08-01

To investigate error and reaction time consequences of alternating compatible and incompatible steering arrangements during a simulated obstacle avoidance task. Underground coal mine shuttle cars provide an example of a vehicle in which operators are required to alternate between compatible and incompatible steering configurations. This experiment examines the performance of 48 novice participants in a virtual analogy of an underground coal mine shuttle car. Participants were randomly assigned to a compatible condition, an incompatible condition, an alternating condition in which compatibility alternated within and between hands, or an alternating condition in which compatibility alternated between hands. Participants made fewer steering direction errors and made correct steering responses more quickly in the compatible condition. Error rate decreased over time in the incompatible condition. A compatibility effect for both errors and reaction time was also found when the control-response relationship alternated; however, performance improvements over time were not consistent. Isolating compatibility to a hand resulted in reduced error rate and faster reaction time than when compatibility alternated within and between hands. The consequences of alternating control-response relationships are higher error rates and slower responses, at least in the early stages of learning. This research highlights the importance of ensuring consistently compatible human-machine directional control-response relationships.

Three essays on price dynamics and causations among energy markets and macroeconomic information

NASA Astrophysics Data System (ADS)

Hong, Sung Wook

This dissertation examines three important issues in energy markets: price dynamics, information flow, and structural change. We discuss each issue in detail, building empirical time series models, analyzing the results, and interpreting the findings. First, we examine the contemporaneous interdependencies and information flows among crude oil, natural gas, and electricity prices in the United States (US) through the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model, Directed Acyclic Graph (DAG) for contemporaneous causal structures and Bernanke factorization for price dynamic processes. Test results show that the DAG from residuals of out-of-sample-forecast is consistent with the DAG from residuals of within-sample-fit. The result supports innovation accounting analysis based on DAGs using residuals of out-of-sample-forecast. Second, we look at the effects of the federal fund rate and/or WTI crude oil price shock on US macroeconomic and financial indicators by using a Factor Augmented Vector Autoregression (FAVAR) model and a graphical model without any deductive assumption. The results show that, in contemporaneous time, the federal fund rate shock is exogenous as the identifying assumption in the Vector Autoregression (VAR) framework of the monetary shock transmission mechanism, whereas the WTI crude oil price return is not exogenous. Third, we examine price dynamics and contemporaneous causality among the price returns of WTI crude oil, gasoline, corn, and the S&P 500. We look for structural break points and then build an econometric model to find the consistent sub-periods having stable parameters in a given VAR framework and to explain recent movements and interdependency among returns. We found strong evidence of two structural breaks and contemporaneous causal relationships among the residuals, but also significant differences between contemporaneous causal structures for each sub-period.

Channel Formation by CarO, the Carbapenem Resistance-Associated Outer Membrane Protein of Acinetobacter baumannii

PubMed Central

Siroy, Axel; Molle, Virginie; Lemaître-Guillier, Christelle; Vallenet, David; Pestel-Caron, Martine; Cozzone, Alain J.; Jouenne, Thierry; Dé, Emmanuelle

2005-01-01

It has been recently shown that resistance to both imipenem and meropenem in multidrug-resistant clinical strains of Acinetobacter baumannii is associated with the loss of a heat-modifiable 25/29-kDa outer membrane protein, called CarO. This study aimed to investigate the channel-forming properties of CarO. Mass spectrometry analyses of this protein band detected another 25-kDa protein (called Omp25), together with CarO. Both proteins presented similar physicochemical parameters (Mw and pI). We overproduced and purified the two polypeptides as His-tagged recombinant proteins. Circular dichroism analyses demonstrated that the secondary structure of these proteins was mainly a β-strand conformation with spectra typical of porins. We studied the channel-forming properties of proteins by reconstitution into artificial lipid bilayers. In these conditions, CarO induced ion channels with a conductance value of 110 pS in 1 M KCl, whereas the Omp25 protein did not form any channels, despite its suggested porin function. The pores formed by CarO showed a slight cationic selectivity and no voltage closure. No specific imipenem binding site was found in CarO, and this protein would rather form unspecific monomeric channels. PMID:16304148

Finite element prediction on the chassis design of UniART4 racing car

NASA Astrophysics Data System (ADS)

Zaman, Z. I.; Basaruddin, K. S.; Basha, M. H.; Rahman, M. T. Abd; Daud, R.

2017-09-01

This paper presents the analysis and evaluation of the chassis design for University Automotive Racing Team No. 4 (UniART4) car based on finite element analysis. The existing UniART4 car chassis was measured and modelled geometrically using Solidwork before analysed in FEA software (ANSYS). Four types of static structural analysis were used to predict the chassis design capability under four different loading conditions; vertical bending, lateral bending, lateral torsion and horizontal lozenging. The results showed the chassis subjected to the highest stress and strain under horizontal lozenging, whereas the minimum stress and strain response was obtained under lateral bending. The present analysis result could provide valuable information in predicting the sustainability of the current UniART car chassis design.

Choice of costimulatory domains and of cytokines determines CAR T-cell activity in neuroblastoma

PubMed Central

Quintarelli, Concetta; Orlando, Domenico; Boffa, Iolanda; Guercio, Marika; Petretto, Andrea; Lavarello, Chiara; Sinibaldi, Matilde; Weber, Gerrit; Del Bufalo, Francesca; Giorda, Ezio; Scarsella, Marco; Petrini, Stefania; Pagliara, Daria; Locatelli, Franco

2018-01-01

ABSTRACT Chimeric antigen receptor (CAR) T-cell therapy has been shown to be dramatically effective in the treatment of B-cell malignancies. However, there are still substantial obstacles to overcome, before similar responses can be achieved in patients with solid tumors. We evaluated both in vitro and in a preclinical murine model the efficacy of different 2nd and 3rd generation CAR constructs targeting GD2, a disial-ganglioside expressed on the surface of neuroblastoma (NB) tumor cells. In order to address potential safety concerns regarding clinical application, an inducible safety switch, namely inducible Caspase-9 (iC9), was also included in the vector constructs. Our data indicate that a 3rd generation CAR incorporating CD28.4-1BB costimulatory domains is associated with improved anti-tumor efficacy as compared with a CAR incorporating the combination of CD28.OX40 domains. We demonstrate that the choice of 4-1BB signaling results into significant amelioration of several CAR T-cell characteristics, including: 1) T-cell exhaustion, 2) basal T-cell activation, 3) in vivo tumor control and 4) T-cell persistence. The fine-tuning of T-cell culture conditions obtained using IL7 and IL15 was found to be synergic with the CAR.GD2 design in increasing the anti-tumor activity of CAR T cells. We also demonstrate that activation of the suicide gene iC9, included in our construct without significantly impairing neither CAR expression nor anti-tumor activity, leads to a prompt induction of apoptosis of GD2.CAR T cells. Altogether, these findings are instrumental in optimizing the function of CAR T-cell products to be employed in the treatment of children with NB. PMID:29872565

Activation of the Constitutive Androstane Receptor induces hepatic lipogenesis and regulates Pnpla3 gene expression in a LXR-independent way

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

Marmugi, Alice; Lukowicz, Céline; Lasserre, Freder

The Constitutive Androstane Receptor (CAR, NR1I3) has been newly described as a regulator of energy metabolism. A relevant number of studies using animal models of obesity suggest that CAR activation could be beneficial on the metabolic balance. However, this remains controversial and the underlying mechanisms are still unknown. This work aimed to investigate the effect of CAR activation on hepatic energy metabolism during physiological conditions, i.e. in mouse models not subjected to metabolic/nutritional stress. Gene expression profiling in the liver of CAR knockout and control mice on chow diet and treated with a CAR agonist highlighted CAR-mediated up-regulations of lipogenicmore » genes, concomitant with neutral lipid accumulation. A strong CAR-mediated up-regulation of the patatin-like phospholipase domain-containing protein 3 (Pnpla3) was demonstrated. Pnpla3 is a gene whose polymorphism is associated with the pathogenesis of nonalcoholic fatty liver disease (NAFLD) development. This observation was confirmed in human hepatocytes treated with the antiepileptic drug and CAR activator, phenobarbital and in immortalized human hepatocytes treated with CITCO. Studying the molecular mechanisms controlling Pnpla3 gene expression, we demonstrated that CAR does not act by a direct regulation of Pnpla3 transcription or via the Liver X Receptor but may rather involve the transcription factor Carbohydrate Responsive Element-binding protein. These data provide new insights into the regulation by CAR of glycolytic and lipogenic genes and on pathogenesis of steatosis. This also raises the question concerning the impact of drugs and environmental contaminants in lipid-associated metabolic diseases. - Highlights: • Induction of hepatic glycolytic and lipogenic genes upon CAR activation by TCPOBOP. • These effects are not mediated by the nuclear receptor LXR. • CAR activation resulted in hepatic lipid accumulation. • Pnpla3 expression is regulated by CAR in mouse liver and human hepatocytes.« less

EGFRvIII mCAR-modified T-cell therapy cures mice with established intracerebral glioma and generates host immunity against tumor-antigen loss.

PubMed

Sampson, John H; Choi, Bryan D; Sanchez-Perez, Luis; Suryadevara, Carter M; Snyder, David J; Flores, Catherine T; Schmittling, Robert J; Nair, Smita K; Reap, Elizabeth A; Norberg, Pamela K; Herndon, James E; Kuan, Chien-Tsun; Morgan, Richard A; Rosenberg, Steven A; Johnson, Laura A

2014-02-15

Chimeric antigen receptor (CAR) transduced T cells represent a promising immune therapy that has been shown to successfully treat cancers in mice and humans. However, CARs targeting antigens expressed in both tumors and normal tissues have led to significant toxicity. Preclinical studies have been limited by the use of xenograft models that do not adequately recapitulate the immune system of a clinically relevant host. A constitutively activated mutant of the naturally occurring epidermal growth factor receptor (EGFRvIII) is antigenically identical in both human and mouse glioma, but is also completely absent from any normal tissues. We developed a third-generation, EGFRvIII-specific murine CAR (mCAR), and performed tests to determine its efficacy in a fully immunocompetent mouse model of malignant glioma. At elevated doses, infusion with EGFRvIII mCAR T cells led to cures in all mice with brain tumors. In addition, antitumor efficacy was found to be dependent on lymphodepletive host conditioning. Selective blockade with EGFRvIII soluble peptide significantly abrogated the activity of EGFRvIII mCAR T cells in vitro and in vivo, and may offer a novel strategy to enhance the safety profile for CAR-based therapy. Finally, mCAR-treated, cured mice were resistant to rechallenge with EGFRvIII(NEG) tumors, suggesting generation of host immunity against additional tumor antigens. All together, these data support that third-generation, EGFRvIII-specific mCARs are effective against gliomas in the brain and highlight the importance of syngeneic, immunocompetent models in the preclinical evaluation of tumor immunotherapies. ©2013 AACR

Interference between face and non-face domains of perceptual expertise: a replication and extension

PubMed Central

Curby, Kim M.; Gauthier, Isabel

2014-01-01

As car expertise increases, so does interference between the visual processing of faces and that of cars; this suggests performance trade-offs across domains of real-world expertise. Such interference between expert domains has been previously revealed in a relatively complex design, interleaving 2-back part-judgment task with faces and cars (Gauthier et al., 2003). However, the basis of this interference is unclear. Experiment 1A replicated the finding of interference between faces and cars, as a function of car expertise. Experiments 1B and 2 investigated the mechanisms underlying this effect by (1) providing baseline measures of performance and (2) assessing the specificity of this interference effect. Our findings support the presence of expertise-dependent interference between face and non-face domains of expertise. However, surprisingly, it is in the condition where faces are processed among cars with a disrupted configuration where expertise has a greater influence on faces. This finding highlights how expertise-related processing changes also occur for transformed objects of expertise and that such changes can also drive interference across domains of expertise. PMID:25346702

Driving with Intuition: A Preregistered Study about the EEG Anticipation of Simulated Random Car Accidents

PubMed Central

Duma, Gian Marco; Mento, Giovanni; Manari, Tommaso; Martinelli, Massimiliano

2017-01-01

The study of neural pre-stimulus or “anticipatory” activity opened a new window for understanding how the brain actively constructs the forthcoming reality. Usually, experimental paradigms designed to study anticipatory activity make use of stimuli. The purpose of the present study is to expand the study of neural anticipatory activity upon the temporal occurrence of dichotomic, statistically unpredictable (random) stimuli within an ecological experimental paradigm. To this purpose, we used a simplified driving simulation including two possible, randomly-presented trial types: a car crash end trial and a no car crash end trial. Event Related Potentials (ERP) were extracted -3,000 ms before stimulus onset. We identified a fronto-central negativity starting around 1,000 ms before car crash presentation. By contrast, a whole-scalp distributed positivity characterized the anticipatory activity observed before the end of the trial in the no car crash end condition. The present data are in line with the hypothesis that the brain may also anticipate dichotomic, statistically unpredictable stimuli, relaying onto different pre-stimulus ERP activity. Possible integration with car-smart-systems is also suggested. PMID:28103303

Neural correlates of culturally familiar brands of car manufacturers.

PubMed

Schaefer, Michael; Berens, Harald; Heinze, Hans-Jochen; Rotte, Michael

2006-06-01

Brands have a high impact on people's economic decisions. People may prefer products of brands even among almost identical products. Brands can be defined as cultural-based symbols, which promise certain advantages of a product. Recent studies suggest that the prefrontal cortex may be crucial for the processing of brand knowledge. The aim of this study was to examine the neural correlates of culturally based brands. We confronted subjects with logos of car manufactures during an fMRI session and instructed them to imagine and use a car of these companies. As a control condition, we used graphically comparable logos of car manufacturers that were unfamiliar to the culture of the subjects participating in this study. If they did not know the logo of the brand, they were told to imagine and use a generic car. Results showed activation of a single region in the medial prefrontal cortex related to the logos of the culturally familiar brands. We discuss the results as self-relevant processing induced by the imagined use of cars of familiar brands and suggest that the prefrontal cortex plays a crucial role for processing culturally based brands.

The Performance of Multilevel Growth Curve Models under an Autoregressive Moving Average Process

ERIC Educational Resources Information Center

Murphy, Daniel L.; Pituch, Keenan A.

2009-01-01

The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…

Testing the Causal Links between School Climate, School Violence, and School Academic Performance: A Cross-Lagged Panel Autoregressive Model

ERIC Educational Resources Information Center

Benbenishty, Rami; Astor, Ron Avi; Roziner, Ilan; Wrabel, Stephani L.

2016-01-01

The present study explores the causal link between school climate, school violence, and a school's general academic performance over time using a school-level, cross-lagged panel autoregressive modeling design. We hypothesized that reductions in school violence and climate improvement would lead to schools' overall improved academic performance.…

Time to burn: Modeling wildland arson as an autoregressive crime function

Treesearch

Jeffrey P. Prestemon; David T. Butry

2005-01-01

Six Poisson autoregressive models of order p [PAR(p)] of daily wildland arson ignition counts are estimated for five locations in Florida (1994-2001). In addition, a fixed effects time-series Poisson model of annual arson counts is estimated for all Florida counties (1995-2001). PAR(p) model estimates reveal highly significant arson ignition autocorrelation, lasting up...

Towards immunotherapy with redirected T cells in a large animal model: Ex vivo activation, expansion, and genetic modification of canine T cells

PubMed Central

Mata, Melinda; Vera, Juan; Gerken, Claudia; Rooney, Cliona M.; Miller, Tasha; Pfent, Catherine; Wang, Lisa L.; Wilson-Robles, Heather M.; Gottschalk, Stephen

2014-01-01

Adoptive transfer of T cells expressing chimeric antigen receptors (CARs) has shown promising anti-tumor activity in early phase clinical studies, especially for hematological malignancies. However, most preclinical models do not reliably mimic human disease. We reasoned that developing an adoptive T-cell therapy approach for spontaneous osteosarcoma (OS) occurring in dogs would more closely reproduce the condition in human cancer. To generate CAR-expressing canine T cells we developed expansion and transduction protocols that allow for the generation of sufficient numbers of CAR-expressing canine T cells for future clinical studies in dogs within 2 weeks of ex vivo culture. To evaluate the functionality of CAR-expressing canine T cells we targeted HER2-positive OS. We demonstrate that canine OS is positive for HER2, and that canine T cells expressing a HER2-specific CAR with human-derived transmembrane and CD28.ζ signaling domains recognize and kill HER2-positive canine OS cell lines in an antigen-dependent manner. To reduce the potential immunogenicity of the CAR we evaluated a CAR with canine-derived transmembrane and signaling domains, and found no functional difference between human and canine CARs. Hence, we have successfully developed a strategy to generate CAR-expressing canine T cells for future preclinical studies in dogs. Testing T-cell therapies in an immunocompetent, outbred animal model may improve our ability to predict their safety and efficacy prior to conducting studies in humans. PMID:25198528

Medium- and Long-term Prediction of LOD Change with the Leap-step Autoregressive Model

NASA Astrophysics Data System (ADS)

Liu, Q. B.; Wang, Q. J.; Lei, M. F.

2015-09-01

It is known that the accuracies of medium- and long-term prediction of changes of length of day (LOD) based on the combined least-square and autoregressive (LS+AR) decrease gradually. The leap-step autoregressive (LSAR) model is more accurate and stable in medium- and long-term prediction, therefore it is used to forecast the LOD changes in this work. Then the LOD series from EOP 08 C04 provided by IERS (International Earth Rotation and Reference Systems Service) is used to compare the effectiveness of the LSAR and traditional AR methods. The predicted series resulted from the two models show that the prediction accuracy with the LSAR model is better than that from AR model in medium- and long-term prediction.

Trans-dimensional joint inversion of seabed scattering and reflection data.

PubMed

Steininger, Gavin; Dettmer, Jan; Dosso, Stan E; Holland, Charles W

2013-03-01

This paper examines joint inversion of acoustic scattering and reflection data to resolve seabed interface roughness parameters (spectral strength, exponent, and cutoff) and geoacoustic profiles. Trans-dimensional (trans-D) Bayesian sampling is applied with both the number of sediment layers and the order (zeroth or first) of auto-regressive parameters in the error model treated as unknowns. A prior distribution that allows fluid sediment layers over an elastic basement in a trans-D inversion is derived and implemented. Three cases are considered: Scattering-only inversion, joint scattering and reflection inversion, and joint inversion with the trans-D auto-regressive error model. Including reflection data improves the resolution of scattering and geoacoustic parameters. The trans-D auto-regressive model further improves scattering resolution and correctly differentiates between strongly and weakly correlated residual errors.

A novel solution for car traffic control based on radiometric microwave devices

NASA Astrophysics Data System (ADS)

Soldovieri, Francesco; Denisov, Alexander; Speziale, Victor

2014-05-01

The significant problem of traffic in big cities, connected with huge and building up quantity of automobile cars, demands for novel strategies, based on nonconventional solutions, in order to improve system traffic control, especially at crossroads. As well known, the usual solution is based on the time relay, which requires the installation of a fixed traffic interval (signal light switching) at a crossroad; this solution is low cost, but does not account for the actual traffic conditions. Therefore, in the recent years, attention is towards to new designs, where the monitoring of the and control of traffic is carried out by using various methods including, optical, the infrared, magnetic, radar tracking, acoustical ones. In this work, we discuss the deployment of high sensitivity radiometric systems and radiometers(sensor) in the microwave range [1, 2]. In fact, the radiometer as "sensor" can provide an always updated information about the car traffic in any weather condition and in absence or low visibility conditions. In fact, the radiometric sensor detects the cars thanks to the different behavior of the car roofs which reflect the cold sky whereas the road asphalt is visible as warm object (at around outside temperature). [1] A. G. Denisov, V. P. Gorishnyak, S. E. Kuzmin et al., "Some experiments concerning resolution of 32 sensors passive 8mm wave imaging system," in Proceedings of the International Symposium on Space Terahertz Technology (ISSTT '09), Charlottesville, Va, USA, April 2009. [2] F. Soldovieri, A. Natale, V. Gorishnyak, A. Pavluchenko, A. Denisov, and L. Chen, "Radiometric Imaging for Monitoring and Surveillance Issues," International Journal of Antennas and Propagation, vol. 2013, Article ID 272561, 8 pages, 2013. doi:10.1155/2013/272561.

Coxsackie- and adenovirus receptor (CAR) is expressed in lymphatic vessels in human skin and affects lymphatic endothelial cell function in vitro

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

Vigl, Benjamin; Zgraggen, Claudia; Rehman, Nadia

Lymphatic vessels play an important role in tissue fluid homeostasis, intestinal fat absorption and immunosurveillance. Furthermore, they are involved in pathologic conditions, such as tumor cell metastasis and chronic inflammation. In comparison to blood vessels, the molecular phenotype of lymphatic vessels is less well characterized. Performing comparative gene expression analysis we have recently found that coxsackie- and adenovirus receptor (CAR) is significantly more highly expressed in cultured human, skin-derived lymphatic endothelial cells (LECs), as compared to blood vascular endothelial cells. Here, we have confirmed these results at the protein level, using Western blot and FACS analysis. Immunofluorescence performed on humanmore » skin confirmed that CAR is expressed at detectable levels in lymphatic vessels, but not in blood vessels. To address the functional significance of CAR expression, we modulated CAR expression levels in cultured LECs in vitro by siRNA- and vector-based transfection approaches. Functional assays performed with the transfected cells revealed that CAR is involved in distinct cellular processes in LECs, such as cell adhesion, migration, tube formation and the control of vascular permeability. In contrast, no effect of CAR on LEC proliferation was observed. Overall, our data suggest that CAR stabilizes LEC-LEC interactions in the skin and may contribute to lymphatic vessel integrity.« less

Features of pedestrian behavior in car-to-pedestrian contact situations in near-miss incidents in Japan.

PubMed

Matsui, Yasuhiro; Hitosugi, Masahito; Doi, Tsutomu; Oikawa, Shoko; Takahashi, Kunio; Ando, Kenichi

2013-01-01

The objective of this study is to evaluate the severe conditions between car-to-pedestrian near-miss situations using pedestrian time-to-vehicle (pedestrian TTV) which is the time when the pedestrian would reach the forward moving car line. Since the information available from the real-world accidents was limited, the authors focused on the near-miss situations captured by driving recorders installed in passenger cars. In their previous study, the authors found there were some similarities between accidents and near-miss incidents. It was made clear that the situations in pedestrians' accidents could be estimated from the near-miss incident data which included motion pictures capturing pedestrian behaviors. In their previous study, the vehicle time-to-collision (vehicle TTC) was investigated from the near-miss incident data. The authors analyzed data for 101 near-miss car-to-pedestrian incident events in which pedestrians were crossing the roads in front of a forward-moving car at an intersection or on a straight road. Using a video of near-miss car-to-pedestrian incidents captured by drive recorders and collected by the Society of Automotive Engineers of Japan (J-SAE) from 2005 to 2009, the pedestrian TTV was calculated. Based on the calculated pedestrian TTV, one of the severe conditions between car-to-pedestrian near-miss situations was evaluated for pedestrians who emerged from behind an obstruction such as a building, a parked vehicle and a moving vehicle. Focusing on the cases of the pedestrians who emerged from behind an obstruction, the averages of the vehicle TTC and pedestrian TTV were 1.31 and 1.05 seconds, respectively, and did not demonstrate a significant difference. Since the averages of the vehicle TTC and pedestrian TTV were similar, there would be a higher possibility of the contact between a car and pedestrian if the driver and pedestrian were not paying any attention. The authors propose that a moving speed of a pedestrian surrogate "dummy" should be determined considering the near-miss incident situations for the evaluation of a CDMBS for pedestrian detection. The authors also propose that the time-to-collision of the dummy to the tested car during the evaluation of the performance of the CDMBS for pedestrian detection should be determined considering the time such as the vehicle TTC in this study. Additionally or alternatively, the pedestrian TTV should be considered, in which the worst situation was assumed for a car that was moving toward a pedestrian without braking due to the car driver's inattentiveness and the pedestrian not slowing down their walking speed or stopping.

Texture classification using autoregressive filtering

NASA Technical Reports Server (NTRS)

Lawton, W. M.; Lee, M.

1984-01-01

A general theory of image texture models is proposed and its applicability to the problem of scene segmentation using texture classification is discussed. An algorithm, based on half-plane autoregressive filtering, which optimally utilizes second order statistics to discriminate between texture classes represented by arbitrary wide sense stationary random fields is described. Empirical results of applying this algorithm to natural and sysnthesized scenes are presented and future research is outlined.

Fuel consumption and CO2/pollutant emissions of mobile air conditioning at fleet level - new data and model comparison.

PubMed

Weilenmann, Martin F; Alvarez, Robert; Keller, Mario

2010-07-01

Mobile air conditioning (MAC) systems are the second-largest energy consumers in cars after driving itself. While different measurement series are available to illustrate their behavior in hot ambient conditions, little data are available for lower temperatures. There are also no data available on diesel vehicles, despite these being quite common in Europe (up to 70% of the fleet in some countries). In the present study, six representative modern diesel passenger cars were tested. In combination with data from previous measurements on gasoline cars, a new model was developed - EEMAC = Empa Emission model for Mobile Air Conditioning systems - to predict emissions from air conditioning. The measurements obtained show that A/C activity still occurs at temperatures below the desired interior temperature. The EEMAC model was applied to the average meteorological year of a central European region and compared with the US EPA MOBILE6 model. As temperatures in central Europe are often below 20 degrees C (the point below which the two models differ), the overall results differ clearly. The estimated average annual CO(2) output according to EEMAC is six times higher than that of MOBILE6. EEMAC also indicates that around two-thirds of the fuel used for air conditioning could be saved by switching the MAC system off below 18 degrees C.

40 CFR 201.23 - Test site, weather conditions and background noise criteria for measurement at a 30 meter (100...

Code of Federal Regulations, 2010 CFR

2010-07-01

... rail car operations and locomotive load cell test stands. 201.23 Section 201.23 Protection of... locomotive and rail car operations and locomotive load cell test stands. (a) The standard test site shall be... contribution from the operation of the load cell, if any, including load cell contribution during test. (h...

The Effect of Delayed Responding on Stroop-Like Task Performance among Preschoolers

ERIC Educational Resources Information Center

Montgomery, Derek E.; Fosco, Whitney

2012-01-01

Forty-four preschoolers completed 2 conditions of a Stroop-like procedure (e.g., saying "boat" for car and "car" for boat) that differed in whether a 3-s delay was imposed before responding. The test card was visible during the delay period for half of the children and occluded for the other children. Preschoolers' interference control was…

Injury tolerance of tibia for the car-pedestrian impact.

PubMed

Mo, Fuhao; Arnoux, Pierre Jean; Jure, Jean Jaques; Masson, Catherine

2012-05-01

Lower limbs are normally the first contacted body region during car-pedestrian accidents, and easily suffer serious injuries. The previous tibia bending tolerances for pedestrian safety were mainly developed from three-point bending tests on tibia mid-shaft. The tibia tolerances of other locations are still not investigated enough. In addition, tibia loading condition under the car-pedestrian impact should be explored to compare with the three-point bending. This work aims to investigate the injury tolerance of tibia fracture with combined experimental data and numerical simulation. Eleven new reported quasi-static bending tests of tibia mid-shaft, and additional eleven dynamic mid-shaft bending test results in the previous literature were used to define injury risk functions. Furthermore, to investigate the influence of tibia locations on bending tolerance, finite element simulations with lower limb model were implemented according to three-point bending and pedestrian impact conditions. The regressive curve of tibia bending tolerance was obtained from the simulations on the different impact locations, and indicated that tibia fracture tolerance could vary largely due to the impact locations for the car-pedestrian crash. Copyright © 2011 Elsevier Ltd. All rights reserved.

Nitrogen dioxide in exhaust emissions from motor vehicles

NASA Astrophysics Data System (ADS)

Lenner, Magnus

NO 2/NO x (v/v) fractions and NO 2 exhaust emission rates were determined for diesel- and gasoline-powered passenger cars and a diesel truck, at several conditions of constant engine load and speed. Vehicles with various kinds of emission control equipment were investigated. Also, integrations of NO 2/NO x percentages during Federal Test Procedure driving cycles were made for six types of passenger car. High (> 30 %) NO 2 fractions were measured for gasoline cars with air injection, and for diesel vehicles. A gasoline car with a 3-way catalyst had low NO x totals with small (< 1 %) NO 2 fractions. A passenger diesel with particle trap yielded surprisingly small (0-2%) NO 2 fractions at moderate speeds. The results have implications for NO 2 concentration in the atmosphere of northern cities during wintertime inversions, in view of the increasing use of air injection systems for passenger cars to meet legal restrictions on vehicle emissions of hydrocarbons and CO.

Activation of the Constitutive Androstane Receptor induces hepatic lipogenesis and regulates Pnpla3 gene expression in a LXR-independent way.

PubMed

Marmugi, Alice; Lukowicz, Céline; Lasserre, Frederic; Montagner, Alexandra; Polizzi, Arnaud; Ducheix, Simon; Goron, Adeline; Gamet-Payrastre, Laurence; Gerbal-Chaloin, Sabine; Pascussi, Jean Marc; Moldes, Marthe; Pineau, Thierry; Guillou, Hervé; Mselli-Lakhal, Laila

2016-07-15

The Constitutive Androstane Receptor (CAR, NR1I3) has been newly described as a regulator of energy metabolism. A relevant number of studies using animal models of obesity suggest that CAR activation could be beneficial on the metabolic balance. However, this remains controversial and the underlying mechanisms are still unknown. This work aimed to investigate the effect of CAR activation on hepatic energy metabolism during physiological conditions, i.e. in mouse models not subjected to metabolic/nutritional stress. Gene expression profiling in the liver of CAR knockout and control mice on chow diet and treated with a CAR agonist highlighted CAR-mediated up-regulations of lipogenic genes, concomitant with neutral lipid accumulation. A strong CAR-mediated up-regulation of the patatin-like phospholipase domain-containing protein 3 (Pnpla3) was demonstrated. Pnpla3 is a gene whose polymorphism is associated with the pathogenesis of nonalcoholic fatty liver disease (NAFLD) development. This observation was confirmed in human hepatocytes treated with the antiepileptic drug and CAR activator, phenobarbital and in immortalized human hepatocytes treated with CITCO. Studying the molecular mechanisms controlling Pnpla3 gene expression, we demonstrated that CAR does not act by a direct regulation of Pnpla3 transcription or via the Liver X Receptor but may rather involve the transcription factor Carbohydrate Responsive Element-binding protein. These data provide new insights into the regulation by CAR of glycolytic and lipogenic genes and on pathogenesis of steatosis. This also raises the question concerning the impact of drugs and environmental contaminants in lipid-associated metabolic diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

The effectiveness of lane departure warning systems-A reduction in real-world passenger car injury crashes.

PubMed

Sternlund, Simon; Strandroth, Johan; Rizzi, Matteo; Lie, Anders; Tingvall, Claes

2017-02-17

The objective of this study was to estimate the safety benefits of in vehicle lane departure warning (LDW) and lane keeping aid (LKA) systems in reducing relevant real-world passenger car injury crashes. The study used an induced exposure method, where LDW/LKA-sensitive and nonsensitive crashes were compared for Volvo passenger cars equipped with and without LDW/LKA systems. These crashes were matched by car make, model, model year, and technical equipment; that is, low-speed autonomous emergency braking (AEB) called City Safety (CS). The data were extracted from the Swedish Traffic Accident Data Acquisition database (STRADA) and consisted of 1,853 driver injury crashes that involved 146 LDW-equipped cars, 11 LKA-equipped cars, and 1,696 cars without LDW/LKA systems. The analysis showed a positive effect of the LDW/LKA systems in reducing lane departure crashes. The LDW/LKA systems were estimated to reduce head-on and single-vehicle injury crashes on Swedish roads with speed limits between 70 and 120 km/h and with dry or wet road surfaces (i.e., not covered by ice or snow) by 53% with a lower limit of 11% (95% confidence interval [CI]). This reduction corresponded to a reduction of 30% with a lower limit of 6% (95% CI) for all head-on and single-vehicle driver injury crashes (including all speed limits and all road surface conditions). LDW/LKA systems were estimated to lower the driver injury risk in crash types that the systems are designed to prevent; that is, head-on and single-vehicle crashes. Though these are important findings, they were based on a small data set. Therefore, further research is desirable to evaluate the effectiveness of LDW/LKA systems under real-world conditions and to differentiate the effectiveness between technical solutions (i.e., LDW and LKA) proposed by different manufacturers.

Circulating levels of carbamylated protein and neutrophil extracellular traps are associated with periodontitis severity in patients with rheumatoid arthritis: A pilot case-control study.

PubMed

Kaneko, Chihiro; Kobayashi, Tetsuo; Ito, Satoshi; Sugita, Noriko; Murasawa, Akira; Nakazono, Kiyoshi; Yoshie, Hiromasa

2018-01-01

An interrelationship between rheumatoid arthritis (RA) and periodontitis has been suggested due to their common pathogenic mechanisms. Protein carbamylation and neutrophil extracellular traps (NETs) formation have been shown to be related to autoimmune conditions, including RA, but their association with periodontitis has not been elucidated. Therefore, we assessed whether or not circulating levels of carbamylated protein (CarP) and NETs are associated with periodontitis severity and influenced by periodontal treatment. We conducted a retrospective case-control study that included 40 patients with RA and periodontitis, 30 patients with periodontitis, and 43 systemically and periodontally healthy controls to assess the circulating levels of CarP and NETs and rheumatologic and periodontal conditions. The same assessments were also performed in 22 patients with RA and periodontitis after 2 months of periodontal treatment, including oral hygiene instruction and full-mouth supragingival scaling. Patients with RA and periodontitis showed significantly higher serum levels of CarP and NETs than the control group (P = 0.04 and P < 0.001, respectively). The serum levels of CarP and NETs were significantly correlated positively with the mean values of probing depth (P = 0.01 and P = 0.007, respectively) and clinical attachment level (P = 0.007 and P = 0.001, respectively) in the 40 patients with RA and periodontitis. Multiple logistic regression analyses also revealed significantly positive associations between the serum levels of CarP and NETs and moderate to severe periodontitis (P = 0.03 and P = 0.001, respectively). Furthermore, periodontal treatment significantly decreased the serum levels of CarP and NETs in patients with RA and periodontitis (P = 0.03 and P = 0.02). The circulating levels of CarP and NETs are associated with periodontitis severity and influenced by periodontal treatment in patients with RA.

Circulating levels of carbamylated protein and neutrophil extracellular traps are associated with periodontitis severity in patients with rheumatoid arthritis: A pilot case-control study

PubMed Central

Kaneko, Chihiro; Ito, Satoshi; Sugita, Noriko; Murasawa, Akira; Nakazono, Kiyoshi; Yoshie, Hiromasa

2018-01-01

Objectives An interrelationship between rheumatoid arthritis (RA) and periodontitis has been suggested due to their common pathogenic mechanisms. Protein carbamylation and neutrophil extracellular traps (NETs) formation have been shown to be related to autoimmune conditions, including RA, but their association with periodontitis has not been elucidated. Therefore, we assessed whether or not circulating levels of carbamylated protein (CarP) and NETs are associated with periodontitis severity and influenced by periodontal treatment. Methods We conducted a retrospective case-control study that included 40 patients with RA and periodontitis, 30 patients with periodontitis, and 43 systemically and periodontally healthy controls to assess the circulating levels of CarP and NETs and rheumatologic and periodontal conditions. The same assessments were also performed in 22 patients with RA and periodontitis after 2 months of periodontal treatment, including oral hygiene instruction and full-mouth supragingival scaling. Results Patients with RA and periodontitis showed significantly higher serum levels of CarP and NETs than the control group (P = 0.04 and P < 0.001, respectively). The serum levels of CarP and NETs were significantly correlated positively with the mean values of probing depth (P = 0.01 and P = 0.007, respectively) and clinical attachment level (P = 0.007 and P = 0.001, respectively) in the 40 patients with RA and periodontitis. Multiple logistic regression analyses also revealed significantly positive associations between the serum levels of CarP and NETs and moderate to severe periodontitis (P = 0.03 and P = 0.001, respectively). Furthermore, periodontal treatment significantly decreased the serum levels of CarP and NETs in patients with RA and periodontitis (P = 0.03 and P = 0.02). Conclusion The circulating levels of CarP and NETs are associated with periodontitis severity and influenced by periodontal treatment in patients with RA. PMID:29394286

Asymmetric statistical features of the Chinese domestic and international gold price fluctuation

NASA Astrophysics Data System (ADS)

Cao, Guangxi; Zhao, Yingchao; Han, Yan

2015-05-01

Analyzing the statistical features of fluctuation is remarkably significant for financial risk identification and measurement. In this study, the asymmetric detrended fluctuation analysis (A-DFA) method was applied to evaluate asymmetric multifractal scaling behaviors in the Shanghai and New York gold markets. Our findings showed that the multifractal features of the Chinese and international gold spot markets were asymmetric. The gold return series persisted longer in an increasing trend than in a decreasing trend. Moreover, the asymmetric degree of multifractals in the Chinese and international gold markets decreased with the increase in fluctuation range. In addition, the empirical analysis using sliding window technology indicated that multifractal asymmetry in the Chinese and international gold markets was characterized by its time-varying feature. However, the Shanghai and international gold markets basically shared a similar asymmetric degree evolution pattern. The American subprime mortgage crisis (2008) and the European debt crisis (2010) enhanced the asymmetric degree of the multifractal features of the Chinese and international gold markets. Furthermore, we also make statistical tests for the results of multifractatity and asymmetry, and discuss the origin of them. Finally, results of the empirical analysis using the threshold autoregressive conditional heteroskedasticity (TARCH) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models exhibited that good news had a more significant effect on the cyclical fluctuation of the gold market than bad news. Moreover, good news exerted a more significant effect on the Chinese gold market than on the international gold market.

Damage localization of marine risers using time series of vibration signals

NASA Astrophysics Data System (ADS)

Liu, Hao; Yang, Hezhen; Liu, Fushun

2014-10-01

Based on dynamic response signals a damage detection algorithm is developed for marine risers. Damage detection methods based on numerous modal properties have encountered issues in the researches in offshore oil community. For example, significant increase in structure mass due to marine plant/animal growth and changes in modal properties by equipment noise are not the result of damage for riser structures. In an attempt to eliminate the need to determine modal parameters, a data-based method is developed. The implementation of the method requires that vibration data are first standardized to remove the influence of different loading conditions and the autoregressive moving average (ARMA) model is used to fit vibration response signals. In addition, a damage feature factor is introduced based on the autoregressive (AR) parameters. After that, the Euclidean distance between ARMA models is subtracted as a damage indicator for damage detection and localization and a top tensioned riser simulation model with different damage scenarios is analyzed using the proposed method with dynamic acceleration responses of a marine riser as sensor data. Finally, the influence of measured noise is analyzed. According to the damage localization results, the proposed method provides accurate damage locations of risers and is robust to overcome noise effect.

Fuzzy neural network technique for system state forecasting.

PubMed

Li, Dezhi; Wang, Wilson; Ismail, Fathy

2013-10-01

In many system state forecasting applications, the prediction is performed based on multiple datasets, each corresponding to a distinct system condition. The traditional methods dealing with multiple datasets (e.g., vector autoregressive moving average models and neural networks) have some shortcomings, such as limited modeling capability and opaque reasoning operations. To tackle these problems, a novel fuzzy neural network (FNN) is proposed in this paper to effectively extract information from multiple datasets, so as to improve forecasting accuracy. The proposed predictor consists of both autoregressive (AR) nodes modeling and nonlinear nodes modeling; AR models/nodes are used to capture the linear correlation of the datasets, and the nonlinear correlation of the datasets are modeled with nonlinear neuron nodes. A novel particle swarm technique [i.e., Laplace particle swarm (LPS) method] is proposed to facilitate parameters estimation of the predictor and improve modeling accuracy. The effectiveness of the developed FNN predictor and the associated LPS method is verified by a series of tests related to Mackey-Glass data forecast, exchange rate data prediction, and gear system prognosis. Test results show that the developed FNN predictor and the LPS method can capture the dynamics of multiple datasets effectively and track system characteristics accurately.

Autoregressive model in the Lp norm space for EEG analysis.

PubMed

Li, Peiyang; Wang, Xurui; Li, Fali; Zhang, Rui; Ma, Teng; Peng, Yueheng; Lei, Xu; Tian, Yin; Guo, Daqing; Liu, Tiejun; Yao, Dezhong; Xu, Peng

2015-01-30

The autoregressive (AR) model is widely used in electroencephalogram (EEG) analyses such as waveform fitting, spectrum estimation, and system identification. In real applications, EEGs are inevitably contaminated with unexpected outlier artifacts, and this must be overcome. However, most of the current AR models are based on the L2 norm structure, which exaggerates the outlier effect due to the square property of the L2 norm. In this paper, a novel AR object function is constructed in the Lp (p≤1) norm space with the aim to compress the outlier effects on EEG analysis, and a fast iteration procedure is developed to solve this new AR model. The quantitative evaluation using simulated EEGs with outliers proves that the proposed Lp (p≤1) AR can estimate the AR parameters more robustly than the Yule-Walker, Burg and LS methods, under various simulated outlier conditions. The actual application to the resting EEG recording with ocular artifacts also demonstrates that Lp (p≤1) AR can effectively address the outliers and recover a resting EEG power spectrum that is more consistent with its physiological basis. Copyright © 2014 Elsevier B.V. All rights reserved.

Non-linear models for the detection of impaired cerebral blood flow autoregulation.

PubMed

Chacón, Max; Jara, José Luis; Miranda, Rodrigo; Katsogridakis, Emmanuel; Panerai, Ronney B

2018-01-01

The ability to discriminate between normal and impaired dynamic cerebral autoregulation (CA), based on measurements of spontaneous fluctuations in arterial blood pressure (BP) and cerebral blood flow (CBF), has considerable clinical relevance. We studied 45 normal subjects at rest and under hypercapnia induced by breathing a mixture of carbon dioxide and air. Non-linear models with BP as input and CBF velocity (CBFV) as output, were implemented with support vector machines (SVM) using separate recordings for learning and validation. Dynamic SVM implementations used either moving average or autoregressive structures. The efficiency of dynamic CA was estimated from the model's derived CBFV response to a step change in BP as an autoregulation index for both linear and non-linear models. Non-linear models with recurrences (autoregressive) showed the best results, with CA indexes of 5.9 ± 1.5 in normocapnia, and 2.5 ± 1.2 for hypercapnia with an area under the receiver-operator curve of 0.955. The high performance achieved by non-linear SVM models to detect deterioration of dynamic CA should encourage further assessment of its applicability to clinical conditions where CA might be impaired.

Non-linear models for the detection of impaired cerebral blood flow autoregulation

PubMed Central

Miranda, Rodrigo; Katsogridakis, Emmanuel

2018-01-01

The ability to discriminate between normal and impaired dynamic cerebral autoregulation (CA), based on measurements of spontaneous fluctuations in arterial blood pressure (BP) and cerebral blood flow (CBF), has considerable clinical relevance. We studied 45 normal subjects at rest and under hypercapnia induced by breathing a mixture of carbon dioxide and air. Non-linear models with BP as input and CBF velocity (CBFV) as output, were implemented with support vector machines (SVM) using separate recordings for learning and validation. Dynamic SVM implementations used either moving average or autoregressive structures. The efficiency of dynamic CA was estimated from the model’s derived CBFV response to a step change in BP as an autoregulation index for both linear and non-linear models. Non-linear models with recurrences (autoregressive) showed the best results, with CA indexes of 5.9 ± 1.5 in normocapnia, and 2.5 ± 1.2 for hypercapnia with an area under the receiver-operator curve of 0.955. The high performance achieved by non-linear SVM models to detect deterioration of dynamic CA should encourage further assessment of its applicability to clinical conditions where CA might be impaired. PMID:29381724

Autoregressive processes with exponentially decaying probability distribution functions: applications to daily variations of a stock market index.

PubMed

Porto, Markus; Roman, H Eduardo

2002-04-01

We consider autoregressive conditional heteroskedasticity (ARCH) processes in which the variance sigma(2)(y) depends linearly on the absolute value of the random variable y as sigma(2)(y) = a+b absolute value of y. While for the standard model, where sigma(2)(y) = a + b y(2), the corresponding probability distribution function (PDF) P(y) decays as a power law for absolute value of y-->infinity, in the linear case it decays exponentially as P(y) approximately exp(-alpha absolute value of y), with alpha = 2/b. We extend these results to the more general case sigma(2)(y) = a+b absolute value of y(q), with 0 < q < 2. We find stretched exponential decay for 1 < q < 2 and stretched Gaussian behavior for 0 < q < 1. As an application, we consider the case q=1 as our starting scheme for modeling the PDF of daily (logarithmic) variations in the Dow Jones stock market index. When the history of the ARCH process is taken into account, the resulting PDF becomes a stretched exponential even for q = 1, with a stretched exponent beta = 2/3, in a much better agreement with the empirical data.

Coherent anti-Stokes Raman scattering for quantitative temperature and concentration measurements in a high-pressure gas turbine combustor rig

NASA Astrophysics Data System (ADS)

Thariyan, Mathew Paul

Dual-pump coherent anti-Stokes Raman scattering (DP-CARS) temperature and major species (CO2/N2) concentration measurements have been performed in an optically-accessible high-pressure gas turbine combustor facility (GTCF) and for partially-premixed and non-premixed flames in a laminar counter-flow burner. A window assembly incorporating pairs of thin and thick fused silica windows on three sides was designed, fabricated, and assembled in the GTCF for advanced laser diagnostic studies. An injection-seeded optical parametric oscillator (OPO) was used as a narrowband pump laser source in the dual-pump CARS system. Large prisms on computer-controlled translation stages were used to direct the CARS beams either into the main optics leg for measurements in the GTCF or to a reference optics leg for measurements of the nonresonant CARS spectrum and for aligning the CARS system. Combusting flows were stabilized with liquid fuel injection only for the central injector of a 9-element lean direct injection (LDI) device developed at NASA Glenn Research Center. The combustor was operated using Jet A fuel at inlet air temperatures up to 725 K and combustor pressures up to 1.03 MPa. Single-shot DP-CARS spectra were analyzed using the Sandia CARSFT code in the batch operation mode to yield instantaneous temperature and CO2/N2 concentration ratio values. Spatial maps of mean and standard deviations of temperature and CO2/N2 concentrations were obtained in the high-pressure LDI flames by translating the CARS probe volume in axial and vertical directions inside the combustor rig. The mean temperature fields demonstrate the effect of the combustor conditions on the overall flame length and the average flame structure. The temperature relative standard deviation values indicate thermal fluctuations due to the presence of recirculation zones and/or flame brush fluctuations. The correlation between the temperature and relative CO 2 concentration data has been studied at various combustor conditions. The insight into the reacting flow structure provided by these measurements is discussed. Such measurements at conditions similar to those of aircraft gas turbine combustors are extremely useful for testing combustion models being used to predict performance of these systems.

Fractal and chaotic laws on seismic dissipated energy in an energy system of engineering structures

NASA Astrophysics Data System (ADS)

Cui, Yu-Hong; Nie, Yong-An; Yan, Zong-Da; Wu, Guo-You

1998-09-01

Fractal and chaotic laws of engineering structures are discussed in this paper, it means that the intrinsic essences and laws on dynamic systems which are made from seismic dissipated energy intensity E d and intensity of seismic dissipated energy moment I e are analyzed. Based on the intrinsic characters of chaotic and fractal dynamic system of E d and I e, three kinds of approximate dynamic models are rebuilt one by one: index autoregressive model, threshold autoregressive model and local-approximate autoregressive model. The innate laws, essences and systematic error of evolutional behavior I e are explained over all, the short-term behavior predictability and long-term behavior probability of which are analyzed in the end. That may be valuable for earthquake-resistant theory and analysis method in practical engineering structures.

Evaluation Of Statistical Models For Forecast Errors From The HBV-Model

NASA Astrophysics Data System (ADS)

Engeland, K.; Kolberg, S.; Renard, B.; Stensland, I.

2009-04-01

Three statistical models for the forecast errors for inflow to the Langvatn reservoir in Northern Norway have been constructed and tested according to how well the distribution and median values of the forecasts errors fit to the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order autoregressive model was constructed for the forecast errors. The parameters were conditioned on climatic conditions. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order autoregressive model was constructed for the forecast errors. For the last model positive and negative errors were modeled separately. The errors were first NQT-transformed before a model where the mean values were conditioned on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: We wanted a) the median values to be close to the observed values; b) the forecast intervals to be narrow; c) the distribution to be correct. The results showed that it is difficult to obtain a correct model for the forecast errors, and that the main challenge is to account for the auto-correlation in the errors. Model 1 and 2 gave similar results, and the main drawback is that the distributions are not correct. The 95% forecast intervals were well identified, but smaller forecast intervals were over-estimated, and larger intervals were under-estimated. Model 3 gave a distribution that fits better, but the median values do not fit well since the auto-correlation is not properly accounted for. If the 95% forecast interval is of interest, Model 2 is recommended. If the whole distribution is of interest, Model 3 is recommended.

Brillouin Scattering Spectrum Analysis Based on Auto-Regressive Spectral Estimation

NASA Astrophysics Data System (ADS)

Huang, Mengyun; Li, Wei; Liu, Zhangyun; Cheng, Linghao; Guan, Bai-Ou

2018-06-01

Auto-regressive (AR) spectral estimation technology is proposed to analyze the Brillouin scattering spectrum in Brillouin optical time-domain refelectometry. It shows that AR based method can reliably estimate the Brillouin frequency shift with an accuracy much better than fast Fourier transform (FFT) based methods provided the data length is not too short. It enables about 3 times improvement over FFT at a moderate spatial resolution.

Hedonic price models with omitted variables and measurement errors: a constrained autoregression-structural equation modeling approach with application to urban Indonesia

NASA Astrophysics Data System (ADS)

Suparman, Yusep; Folmer, Henk; Oud, Johan H. L.

2014-01-01

Omitted variables and measurement errors in explanatory variables frequently occur in hedonic price models. Ignoring these problems leads to biased estimators. In this paper, we develop a constrained autoregression-structural equation model (ASEM) to handle both types of problems. Standard panel data models to handle omitted variables bias are based on the assumption that the omitted variables are time-invariant. ASEM allows handling of both time-varying and time-invariant omitted variables by constrained autoregression. In the case of measurement error, standard approaches require additional external information which is usually difficult to obtain. ASEM exploits the fact that panel data are repeatedly measured which allows decomposing the variance of a variable into the true variance and the variance due to measurement error. We apply ASEM to estimate a hedonic housing model for urban Indonesia. To get insight into the consequences of measurement error and omitted variables, we compare the ASEM estimates with the outcomes of (1) a standard SEM, which does not account for omitted variables, (2) a constrained autoregression model, which does not account for measurement error, and (3) a fixed effects hedonic model, which ignores measurement error and time-varying omitted variables. The differences between the ASEM estimates and the outcomes of the three alternative approaches are substantial.

A two dimensional power spectral estimate for some nonstationary processes. M.S. Thesis

NASA Technical Reports Server (NTRS)

Smith, Gregory L.

1989-01-01

A two dimensional estimate for the power spectral density of a nonstationary process is being developed. The estimate will be applied to helicopter noise data which is clearly nonstationary. The acoustic pressure from the isolated main rotor and isolated tail rotor is known to be periodically correlated (PC) and the combined noise from the main and tail rotors is assumed to be correlation autoregressive (CAR). The results of this nonstationary analysis will be compared with the current method of assuming that the data is stationary and analyzing it as such. Another method of analysis is to introduce a random phase shift into the data as shown by Papoulis to produce a time history which can then be accurately modeled as stationary. This method will also be investigated for the helicopter data. A method used to determine the period of a PC process when the period is not know is discussed. The period of a PC process must be known in order to produce an accurate spectral representation for the process. The spectral estimate is developed. The bias and variability of the estimate are also discussed. Finally, the current method for analyzing nonstationary data is compared to that of using a two dimensional spectral representation. In addition, the method of phase shifting the data is examined.

Transformational Autonomy and Personal Transportation: Synergies and Differences Between Cars and Planes

NASA Technical Reports Server (NTRS)

Goodrich, Kenneth H.; Nickolaou, Jim; Moore, Mark D.

2016-01-01

Highly automated cars have undergone tremendous investment and progress over the past ten years with speculation about fully-driverless cars within the foreseeable, or even near future, becoming common. If a driverless future is realized, what might be the impact on personal aviation? Would self-piloting airplanes be a relatively simple spin-off, possibly making travel by personal aircraft also commonplace? What if the technology for completely removing human drivers turns out to be further in the future rather than sooner; would such a delay suggest that transformational personal aviation is also somewhere over the horizon or can transformation be achieved with less than full automation? This paper presents a preliminary exploration of these questions by comparing the operational, functional, and implementation requirements and constraints of cars and small aircraft for on-demand mobility. In general, we predict that the mission management and perception requirements of self-piloting aircraft differ significantly from self-driving cars and requires the development of aviation specific technologies. We also predict that the highly-reliable control and system automation technology developed for conditionally and highly automated cars can have a significant beneficial effect on personal aviation, even if full automation is not immediately feasible.

Is car use related with successful aging of older adults? Results from the multinational Mediterranean islands study.

PubMed

Tyrovolas, Stefanos; Polychronopoulos, Evangelos; Morena, Marianthi; Mariolis, Anargiros; Piscopo, Suzanne; Valacchi, Giuseppe; Bountziouka, Vassiliki; Anastasiou, Foteini; Zeimbekis, Akis; Tyrovola, Dimitra; Foscolou, Alexandra; Gotsis, Efthimios; Metallinos, George; Soulis, George; Tur, Josep-Antoni; Matalas, Antonia; Lionis, Christos; Sidossis, Labros S; Panagiotakos, Demosthenes

2017-03-01

The aim of the present work was to evaluate the relation between car use and the level of successful aging of a random sample of older adults living in the Mediterranean basin. During 2005-2011, 2749 older (aged 65-100 years) from 22 islands and the rural Mani region (Peloponnesus) of Greece were voluntarily enrolled in the Mediterranean islands cross-sectional study. Sociodemographics, medical conditions, and dietary and lifestyle habits were derived throughout standard procedures. Car use was recorded with a standard binary question. A successful aging index ranging from 0-10 was used. Older adults who used a car on regular basis had significantly higher levels of successful aging, as well as less prevalence of obesity and hypertension while were more physically active (P < .001). After adjusting for several confounders car use was still positively related with elderly islander's successful aging level (beta coefficient [95% confidence interval]: 0.65 [0.54-0.77]). In conclusion, the activity of car use seems to be an indicator of quality of life among older adults, as measured through successful aging. Copyright © 2017 Elsevier Inc. All rights reserved.

Resonance, criticality, and emergence in city traffic investigated in cellular automaton models.

PubMed

Varas, A; Cornejo, M D; Toledo, B A; Muñoz, V; Rogan, J; Zarama, R; Valdivia, J A

2009-11-01

The complex behavior that occurs when traffic lights are synchronized is studied for a row of interacting cars. The system is modeled through a cellular automaton. Two strategies are considered: all lights in phase and a "green wave" with a propagating green signal. It is found that the mean velocity near the resonant condition follows a critical scaling law. For the green wave, it is shown that the mean velocity scaling law holds even for random separation between traffic lights and is not dependent on the density. This independence on car density is broken when random perturbations are considered in the car velocity. Random velocity perturbations also have the effect of leading the system to an emergent state, where cars move in clusters, but with an average velocity which is independent of traffic light switching for large injection rates.

Talking about the Automobile Braking System

NASA Astrophysics Data System (ADS)

Xu, Zhiqiang

2017-12-01

With the continuous progress of society, the continuous development of the times, people’s living standards continue to improve, people continue to improve the pursuit. With the rapid development of automobile manufacturing, the car will be all over the tens of thousands of households, the increase in car traffic, a direct result of the incidence of traffic accidents. Brake system is the guarantee of the safety of the car, its technical condition is good or bad, directly affect the operational safety and transportation efficiency, so the brake system is absolutely reliable. The requirements of the car on the braking system is to have a certain braking force to ensure reliable work in all cases, light and flexible operation. Normal braking should be good performance, in addition to a foot sensitive, the emergency brake four rounds can not be too long, not partial, not ring.

Automatic processing of semantic relations in fMRI: neural activation during semantic priming of taxonomic and thematic categories.

PubMed

Sachs, Olga; Weis, Susanne; Zellagui, Nadia; Huber, Walter; Zvyagintsev, Mikhail; Mathiak, Klaus; Kircher, Tilo

2008-07-07

Most current models of knowledge organization are based on hierarchical or taxonomic categories (animals, tools). Another important organizational pattern is thematic categorization, i.e. categories held together by external relations, a unifying scene or event (car and garage). The goal of this study was to compare the neural correlates of these categories under automatic processing conditions that minimize strategic influences. We used fMRI to examine neural correlates of semantic priming for category members with a short stimulus onset asynchrony (SOA) of 200 ms as subjects performed a lexical decision task. Four experimental conditions were compared: thematically related words (car-garage); taxonomically related (car-bus); unrelated (car-spoon); non-word trials (car-derf). We found faster reaction times for related than for unrelated prime-target pairs for both thematic and taxonomic categories. However, the size of the thematic priming effect was greater than that of the taxonomic. The imaging data showed signal changes for the taxonomic priming effects in the right precuneus, postcentral gyrus, middle frontal and superior frontal gyri and thematic priming effects in the right middle frontal gyrus and anterior cingulate. The contrast of neural priming effects showed larger signal changes in the right precuneus associated with the taxonomic but not with thematic priming response. We suggest that the greater involvement of precuneus in the processing of taxonomic relations indicates their reduced salience in the knowledge structure compared to more prominent thematic relations.

Studies of the metastable decay of met-cars. The vanadium and niobium systems

NASA Astrophysics Data System (ADS)

Purnell, J.; Wei, S.; Castleman, A. W., Jr.

1994-10-01

The decay fractions and metastable decomposition channels were measured for V(m)C(n)(+) and Nb(m)C(n)(+) clusters using a reflectron time-of-flight mass spectrometer. These measurements for the V(m)C(n)(+) clusters reveal stable (8, 12) and (8, 13) met-car species. However, under the present experimental conditions, the Nb(m)C(n)(+) clusters display dominantly cubic structures, but the decay fraction and metastable decomposition measurements also show the presence of a stable (8, 12) species in the parent cluster spectrum. This evidence indicates that cubic structures and met-cars are being formed simultaneously for the niobium system.

Metallocarbohedrenes: Transmission Electron Microscopy of Mass Gated Deposits

NASA Astrophysics Data System (ADS)

Castleman, M. E. Lyn, Jr.

2002-03-01

Titanium and zirconium Met-Car cluster ions have been detected from the direct laser vaporization of metal-graphite mixtures using time-of-flight mass spectrometry. Optimization of the production conditions enabled sufficient intensities to mass select and deposit Met-Cars on surfaces. High-resolution transmission electron microscopy images of mass gated Met-Car species reveals deposited nanocrystals 2 nm in diameter. Diffraction patterns indicate the presence of multiple species and shows that the deposits have spatial orientation. Lattice parameters have been extracted. The implication of the findings will be discussed. Support for the work has been from the AFOSR F49620-01-1-0122.

Hands on what? The relative effectiveness of physical versus virtual materials in an engineering design project by middle school children

NASA Astrophysics Data System (ADS)

Klahr, David; Triona, Lara M.; Williams, Cameron

2007-01-01

Hands-on activities play an important, but controversial, role in early science education. In this study we attempt to clarify some of the issues surrounding the controversy by calling attention to distinctions between: (a) type of instruction (direct or discovery); (b) type of knowledge to be acquired (domain-general or domain-specific); and (c) type of materials that are used (physical or virtual). We then describe an empirical study that investigates the relative effectiveness of the physical-virtual dimension. In the present study, seventh and eighth grade students assembled and tested mousetrap cars with the goal of designing a car that would go the farthest. Children were assigned to four different conditions, depending on whether they manipulated physical or virtual materials, and whether they had a fixed number of cars they could construct or a fixed amount of time in which to construct them. All four conditions were equally effective in producing significant gains in learners' knowledge about causal factors, in their ability to design optimal cars, and in their confidence in their knowledge. Girls' performance, knowledge, and effort were equal to boys' in all conditions, but girls' confidence remained below boys' throughout. Given the fact that, on several different measures, children were able to learn as well with virtual as with physical materials, the inherent pragmatic advantages of virtual materials in science may make them the preferred instructional medium in many hands-on contexts.

Cooling performance and evaluation of automotive refrigeration system for a passenger car

NASA Astrophysics Data System (ADS)

Prajitno, Deendarlianto, Majid, Akmal Irfan; Mardani, Mahardeka Dhias; Wicaksono, Wendi; Kamal, Samsul; Purwanto, Teguh Pudji; Fauzun

2016-06-01

A new design of automotive refrigeration system for a passenger car was proposed. To ensure less energy consumption and optimal thermal comfort, the performance of the system were evaluated. This current research was aimed to evaluate the refrigeration characteristics of the system for several types of cooling load. In this present study, a four-passenger wagon car with 1500 cc gasoline engine that equipped by a belt driven compressor (BDC) was used as the tested vehicle. To represent the tropical condition, a set of lamps and wind sources are installed around the vehicle. The blower capacity inside a car is varied from 0.015 m/s to 0.027 m/s and the compressor speed is varied at variable 820, 1400, and 2100 rpm at a set temperature of 22°C. A set of thermocouples that combined by data logger were used to measure the temperature distribution. The system uses R-134a as the refrigerant. In order to determine the cooling capacity of the vehicle, two conditions were presented: without passengers and full load conditions. As the results, cooling capacity from any possible heating sources and transient characteristics of temperature in both systems for the cabin, engine, compressor, and condenser are presented in this work. As the load increases, the outlet temperature of evaporator also increases due to the increase of condensed air. This phenomenon also causes the increase of compressor work and compression ratio which associated to the addition of specific volume in compressor inlet.

Global carbon benefits of material substitution in passenger cars until 2050 and the impact on the steel and aluminum industries.

PubMed

Modaresi, Roja; Pauliuk, Stefan; Løvik, Amund N; Müller, Daniel B

2014-09-16

Light-weighting of passenger cars using high-strength steel or aluminum is a common emissions mitigation strategy. We provide a first estimate of the global impact of light-weighting by material substitution on GHG emissions from passenger cars and the steel and aluminum industries until 2050. We develop a dynamic stock model of the global car fleet and combine it with a dynamic MFA of the associated steel, aluminum, and energy supply industries. We propose four scenarios for substitution of conventional steel with high-strength steel and aluminum at different rates over the period 2010-2050. We show that light-weighting of passenger cars can become a "gigaton solution": Between 2010 and 2050, persistent light-weighting of passenger cars can, under optimal conditions, lead to cumulative GHG emissions savings of 9-18 gigatons CO2-eq compared to development business-as-usual. Annual savings can be up to 1 gigaton per year. After 2030, enhanced material recycling can lead to further reductions: closed-loop metal recycling in the automotive sector may reduce cumulative emissions by another 4-6 gigatons CO2-eq. The effectiveness of emissions mitigation by material substitution significantly depends on how the recycling system evolves. At present, policies focusing on tailpipe emissions and life cycle assessments of individual cars do not consider this important effect.

Expertise Effects in Face-Selective Areas are Robust to Clutter and Diverted Attention, but not to Competition

PubMed Central

McGugin, Rankin Williams; Van Gulick, Ana E.; Tamber-Rosenau, Benjamin J.; Ross, David A.; Gauthier, Isabel

2015-01-01

Expertise effects for nonface objects in face-selective brain areas may reflect stable aspects of neuronal selectivity that determine how observers perceive objects. However, bottom-up (e.g., clutter from irrelevant objects) and top-down manipulations (e.g., attentional selection) can influence activity, affecting the link between category selectivity and individual performance. We test the prediction that individual differences expressed as neural expertise effects for cars in face-selective areas are sufficiently stable to survive clutter and manipulations of attention. Additionally, behavioral work and work using event related potentials suggest that expertise effects may not survive competition; we investigate this using functional magnetic resonance imaging. Subjects varying in expertise with cars made 1-back decisions about cars, faces, and objects in displays containing one or 2 objects, with only one category attended. Univariate analyses suggest car expertise effects are robust to clutter, dampened by reducing attention to cars, but nonetheless more robust to manipulations of attention than competition. While univariate expertise effects are severely abolished by competition between cars and faces, multivariate analyses reveal new information related to car expertise. These results demonstrate that signals in face-selective areas predict expertise effects for nonface objects in a variety of conditions, although individual differences may be expressed in different dependent measures depending on task and instructions. PMID:24682187

Modified Confidence Intervals for the Mean of an Autoregressive Process.

DTIC Science & Technology

1985-08-01

Validity of the method 45 3.6 Theorem 47 4 Derivation of corrections 48 Introduction 48 The zero order pivot 50 4.1 Algorithm 50 CONTENTS The first...of standard confidence intervals. There are several standard methods of setting confidence intervals in simulations, including the regener- ative... method , batch means, and time series methods . We-will focus-s on improved confidence intervals for the mean of an autoregressive process, and as such our

Autoregressive Methods for Spectral Estimation from Interferograms.

DTIC Science & Technology

1986-09-19

RL83 6?6 AUTOREGRESSIVE METHODS FOR SPECTRAL. ESTIMTION FROM / SPACE ENGINEERING E N RICHARDS ET AL. 19 SEPINEFRGAS.()UA TT NV GNCNE O C: 31SSF...was AUG1085 performed under subcontract to . Center for Space Engineering Utah State University Logan, UT 84322-4140 4 4 Scientific Report No. 17 AFGL...MONITORING ORGANIZATION Center for Space Engineering (iapplicable) Air Force Geophysics Laboratory e. AORESS (City. State and ZIP Code) 7b. AOORESS (City

Foreign Exchange Value-at-Risk with Multiple Currency Exposure: A Multivariate and Copula Generalized Autoregressive Conditional Heteroskedasticity Approach

DTIC Science & Technology

2014-11-01

du taux de change, et les responsables de la gestion interne se voient donc pressés de trouver des ... mesurer les effets négatifs que peuvent avoir les fluctuations mo- nétaires sur le budget et la planification du MDN, il faut connaître le poids des ...qualités comparables et qu’ils permettent d’effectuer une meilleure évaluation du risque qu’avec la méthode courante. On obtient désormais des estimations de

Detecting P and S-wave of Mt. Rinjani seismic based on a locally stationary autoregressive (LSAR) model

NASA Astrophysics Data System (ADS)

Nurhaida, Subanar, Abdurakhman, Abadi, Agus Maman

2017-08-01

Seismic data is usually modelled using autoregressive processes. The aim of this paper is to find the arrival times of the seismic waves of Mt. Rinjani in Indonesia. Kitagawa algorithm's is used to detect the seismic P and S-wave. Householder transformation used in the algorithm made it effectively finding the number of change points and parameters of the autoregressive models. The results show that the use of Box-Cox transformation on the variable selection level makes the algorithm works well in detecting the change points. Furthermore, when the basic span of the subinterval is set 200 seconds and the maximum AR order is 20, there are 8 change points which occur at 1601, 2001, 7401, 7601,7801, 8001, 8201 and 9601. Finally, The P and S-wave arrival times are detected at time 1671 and 2045 respectively using a precise detection algorithm.

Gaussian Process Autoregression for Simultaneous Proportional Multi-Modal Prosthetic Control With Natural Hand Kinematics.

PubMed

Xiloyannis, Michele; Gavriel, Constantinos; Thomik, Andreas A C; Faisal, A Aldo

2017-10-01

Matching the dexterity, versatility, and robustness of the human hand is still an unachieved goal in bionics, robotics, and neural engineering. A major limitation for hand prosthetics lies in the challenges of reliably decoding user intention from muscle signals when controlling complex robotic hands. Most of the commercially available prosthetic hands use muscle-related signals to decode a finite number of predefined motions and some offer proportional control of open/close movements of the whole hand. Here, in contrast, we aim to offer users flexible control of individual joints of their artificial hand. We propose a novel framework for decoding neural information that enables a user to independently control 11 joints of the hand in a continuous manner-much like we control our natural hands. Toward this end, we instructed six able-bodied subjects to perform everyday object manipulation tasks combining both dynamic, free movements (e.g., grasping) and isometric force tasks (e.g., squeezing). We recorded the electromyographic and mechanomyographic activities of five extrinsic muscles of the hand in the forearm, while simultaneously monitoring 11 joints of hand and fingers using a sensorized data glove that tracked the joints of the hand. Instead of learning just a direct mapping from current muscle activity to intended hand movement, we formulated a novel autoregressive approach that combines the context of previous hand movements with instantaneous muscle activity to predict future hand movements. Specifically, we evaluated a linear vector autoregressive moving average model with exogenous inputs and a novel Gaussian process ( ) autoregressive framework to learn the continuous mapping from hand joint dynamics and muscle activity to decode intended hand movement. Our approach achieves high levels of performance (RMSE of 8°/s and ). Crucially, we use a small set of sensors that allows us to control a larger set of independently actuated degrees of freedom of a hand. This novel undersensored control is enabled through the combination of nonlinear autoregressive continuous mapping between muscle activity and joint angles. The system evaluates the muscle signals in the context of previous natural hand movements. This enables us to resolve ambiguities in situations, where muscle signals alone cannot determine the correct action as we evaluate the muscle signals in their context of natural hand movements. autoregression is a particularly powerful approach which makes not only a prediction based on the context but also represents the associated uncertainty of its predictions, thus enabling the novel notion of risk-based control in neuroprosthetics. Our results suggest that autoregressive approaches with exogenous inputs lend themselves for natural, intuitive, and continuous control in neurotechnology, with the particular focus on prosthetic restoration of natural limb function, where high dexterity is required for complex movements.

Secondhand smoke in cars: assessing children's potential exposure during typical journey conditions.

PubMed

Semple, Sean; Apsley, Andrew; Galea, Karen S; MacCalman, Laura; Friel, Brenda; Snelgrove, Vicki

2012-11-01

To measure levels of fine particulate matter in the rear passenger area of cars where smoking does and does not take place during typical real-life car journeys. Fine particulate matter (PM(2.5)) was used as a marker of secondhand smoke and was measured and logged every minute of each car journey undertaken by smoking and non-smoking study participants. The monitoring instrument was located at breathing zone height in the rear seating area of each car. Participants were asked to carry out their normal driving and smoking behaviours over a 3-day period. 17 subjects (14 smokers) completed a total of 104 journeys (63 smoking journeys). Journeys averaged 27 min (range 5-70 min). PM(2.5) levels averaged 85 and 7.4 μg/m(3) during smoking and non-smoking car journeys, respectively. During smoking journeys, peak PM(2.5) concentrations averaged 385 μg/m(3), with one journey measuring over 880 μg/m(3). PM(2.5) concentrations were strongly linked to rate of smoking (cigarettes per minute). Use of forced ventilation and opening of car windows were very common during smoking journeys, but PM(2.5) concentrations were still found to exceed WHO indoor air quality guidance (25 μg/m(3)) at some point in the measurement period during all smoking journeys. PM(2.5) concentrations in cars where smoking takes place are high and greatly exceed international indoor air quality guidance values. Children exposed to these levels of fine particulate are likely to suffer ill-health effects. There are increasing numbers of countries legislating against smoking in cars and such measures may be appropriate to prevent the exposure of children to these high levels of secondhand smoke.

Stabilization strategies of a general nonlinear car-following model with varying reaction-time delay of the drivers.

PubMed

Li, Shukai; Yang, Lixing; Gao, Ziyou; Li, Keping

2014-11-01

In this paper, the stabilization strategies of a general nonlinear car-following model with reaction-time delay of the drivers are investigated. The reaction-time delay of the driver is time varying and bounded. By using the Lyapunov stability theory, the sufficient condition for the existence of the state feedback control strategy for the stability of the car-following model is given in the form of linear matrix inequality, under which the traffic jam can be well suppressed with respect to the varying reaction-time delay. Moreover, by considering the external disturbance for the running cars, the robust state feedback control strategy is designed, which ensures robust stability and a smaller prescribed H∞ disturbance attenuation level for the traffic flow. Numerical examples are given to illustrate the effectiveness of the proposed methods. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Dual-pump CARS of Air in a Heated Pressure Vessel up to 55 Bar and 1300 K

NASA Technical Reports Server (NTRS)

Cantu, Luca; Gallo, Emanuela; Cutler, Andrew D.; Danehy, Paul M.

2014-01-01

Dual-pump Coherent anti-Stokes Raman scattering (CARS) measurements have been performed in a heated pressure vessel at NASA Langley Research Center. Each measurement, consisting of 500 single shot spectra, was recorded at a fixed location in dry air at various pressures and temperatures, in a range of 0.03-55×10(exp 5) Pa and 300-1373 K, where the temperature was varied using an electric heater. The maximum output power of the electric heater limited the combinations of pressures and temperatures that could be obtained. Charts of CARS signal versus temperature (at constant pressure) and signal versus pressure (at constant temperature) are presented and fit with an empirical model to validate the range of capability of the dual-pump CARS technique; averaged spectra at different conditions of pressure and temperature are also shown.

Car suspension system monitoring under road conditions

NASA Astrophysics Data System (ADS)

Fedotov, A. I.; Kuznetsov, N. Y.; Lysenko, A. V.; Vlasov, V. G.

2017-12-01

The paper describes an advanced gyro-based measuring system comprising a CGV-4K central vertical gyro and a G-3M gyrocompass. The advanced system provides additional functions that help measure unsprung mass rotation angles about a vertical axis, rolling angles, trim angles and movements of the unsprung masses of the front (ap and al) and rear b axes when a car wheel hits a single obstruction. The paper also describes the operation of the system, which measures movements of unsprung masses about the body of a car when it hits a single obstruction. The paper presents the dependency diagrams ap = f(t) and al = f(t) for front and rear wheels respectively, as well as b = f(t) for a rear left wheel, which were determined experimentally. Test results for a car equipped with an advanced gyro-based measuring system moving around a circle can form a basis for developing a mathematical model of the process.

Climate effects of non-compliant Volkswagen diesel cars

NASA Astrophysics Data System (ADS)

Tanaka, Katsumasa; Lund, Marianne T.; Aamaas, Borgar; Berntsen, Terje

2018-04-01

On-road operations of Volkswagen light-duty diesel vehicles equipped with defeat devices cause emissions of NOx up to 40 times above emission standards. Higher on-road NOx emissions are a widespread problem not limited to Volkswagen vehicles, but the Volkswagen violations brought this issue under the spotlight. While several studies investigated the health impacts of high NOx emissions, the climatic impacts have not been quantified. Here we show that such diesel cars generate a larger warming on the time scale of several years but a smaller warming on the decadal time scale during actual on-road operations than in vehicle certification tests. The difference in longer-term warming levels, however, depends on underlying driving conditions. Furthermore, in the presence of defeat devices, the climatic advantage of ‘clean diesel’ cars over gasoline cars, in terms of global-mean temperature change, is in our view not necessarily the case.

Nonintrusive biological signal monitoring in a car to evaluate a driver's stress and health state.

PubMed

Baek, Hyun Jae; Lee, Haet Bit; Kim, Jung Soo; Choi, Jong Min; Kim, Ko Keun; Park, Kwang Suk

2009-03-01

Nonintrusive monitoring of a driver's physiological signals was introduced and evaluated in a car as a test of extending the concept of ubiquitous healthcare to vehicles. Electrocardiogram, photoplethysmogram, galvanic skin response, and respiration were measured in the ubiquitous healthcare car (U-car) using nonintrusively installed sensors on the steering wheel, driver's seat, and seat belt. Measured signals were transmitted to the embedded computer via Bluetooth(R) communication and processed. We collected and analyzed physiological signals during driving in order to estimate a driver's stress state while using this system. In order to compare the effect of stress on physical and mental conditions, two categories of stresses were defined. Experimental results show that a driver's physiological signals were measured with acceptable quality for analysis without interrupting driving, and they were changed meaningfully due to elicited stress. This nonintrusive monitoring can be used to evaluate a driver's state of health and stress.

A conditional Granger causality model approach for group analysis in functional MRI

PubMed Central

Zhou, Zhenyu; Wang, Xunheng; Klahr, Nelson J.; Liu, Wei; Arias, Diana; Liu, Hongzhi; von Deneen, Karen M.; Wen, Ying; Lu, Zuhong; Xu, Dongrong; Liu, Yijun

2011-01-01

Granger causality model (GCM) derived from multivariate vector autoregressive models of data has been employed for identifying effective connectivity in the human brain with functional MR imaging (fMRI) and to reveal complex temporal and spatial dynamics underlying a variety of cognitive processes. In the most recent fMRI effective connectivity measures, pairwise GCM has commonly been applied based on single voxel values or average values from special brain areas at the group level. Although a few novel conditional GCM methods have been proposed to quantify the connections between brain areas, our study is the first to propose a viable standardized approach for group analysis of an fMRI data with GCM. To compare the effectiveness of our approach with traditional pairwise GCM models, we applied a well-established conditional GCM to pre-selected time series of brain regions resulting from general linear model (GLM) and group spatial kernel independent component analysis (ICA) of an fMRI dataset in the temporal domain. Datasets consisting of one task-related and one resting-state fMRI were used to investigate connections among brain areas with the conditional GCM method. With the GLM detected brain activation regions in the emotion related cortex during the block design paradigm, the conditional GCM method was proposed to study the causality of the habituation between the left amygdala and pregenual cingulate cortex during emotion processing. For the resting-state dataset, it is possible to calculate not only the effective connectivity between networks but also the heterogeneity within a single network. Our results have further shown a particular interacting pattern of default mode network (DMN) that can be characterized as both afferent and efferent influences on the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). These results suggest that the conditional GCM approach based on a linear multivariate vector autoregressive (MVAR) model can achieve greater accuracy in detecting network connectivity than the widely used pairwise GCM, and this group analysis methodology can be quite useful to extend the information obtainable in fMRI. PMID:21232892

Driver steering dynamics measured in car simulator under a range of visibility and roadmaking conditions

NASA Technical Reports Server (NTRS)

Allen, R. W.; Mcruer, D. T.

1977-01-01

A simulation experiment was conducted to determine the effect of reduced visibility on driver lateral (steering) control. The simulator included a real car cab and a single lane road image projected on a screen six feet in front of the driver. Simulated equations of motion controlled apparent car lane position in response to driver steering actions, wind gusts, and road curvature. Six drivers experienced a range of visibility conditions at various speeds with assorted roadmaking configurations (mark and gap lengths). Driver describing functions were measured and detailed parametric model fits were determined. A pursuit model employing a road curvature feedforward was very effective in explaining driver behavior in following randomly curving roads. Sampled-data concepts were also effective in explaining the combined effects of reduced visibility and intermittent road markings on the driver's dynamic time delay. The results indicate the relative importance of various perceptual variables as the visual input to the driver's steering control process is changed.

Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

NASA Astrophysics Data System (ADS)

Gu, Huaying; Liu, Zhixue; Weng, Yingliang

2017-04-01

The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

Does the New European Driving Cycle (NEDC) really fail to capture the NOX emissions of diesel cars in Europe?

PubMed

Degraeuwe, Bart; Weiss, Martin

2017-03-01

Tests with Portable Emissions Measurement Systems (PEMS) have demonstrated that diesel cars emit several times more NO X on the road than during certification on the New European Driving Cycle (NEDC). Policy makers and scientists have attributed the discrepancy to the unrealistically low dynamics and the narrow temperature range of NEDC testing. Although widely accepted, this assumption was never been put under scientific scrutiny. Here, we demonstrate that the narrow NEDC test conditions explain only a small part of the elevated on-road NO X emissions of diesel cars. For seven Euro 4-6 diesel cars, we filter from on-road driving those events that match the NEDC conditions in instantaneous speed, acceleration, CO 2 emissions, and ambient temperature. The resulting on-road NO X emissions exceed by 206% (median) those measured on the NEDC, whereas the NO X emissions of all unfiltered on-road measurements exceed the NEDC emissions by 266% (median). Moreover, when applying the same filtering of on-road data to two other driving cycles (WLTP and CADC), the resulting on-road NO X emissions exceed by only 13% (median) those measured over the respective cycles. This result demonstrates that our filtering method is accurate and robust. If neither the low dynamics nor the limited temperature range of NEDC testing can explain the elevated NO X emissions of diesel cars, emissions control strategies used during NEDC testing must be inactive or modulated on the road, even if vehicles are driven under certification-like conditions. This points to defeat strategies that warrant further investigations by type-approval authorities and, in turn, limitations in the enforcement of the European vehicle emissions legislation by EU Member States. We suggest applying our method as a simple yet effective tool to screen and select vehicles for in-depth analysis by the competent certification authorities. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Anomalous Fluctuations in Autoregressive Models with Long-Term Memory

NASA Astrophysics Data System (ADS)

Sakaguchi, Hidetsugu; Honjo, Haruo

2015-10-01

An autoregressive model with a power-law type memory kernel is studied as a stochastic process that exhibits a self-affine-fractal-like behavior for a small time scale. We find numerically that the root-mean-square displacement Δ(m) for the time interval m increases with a power law as mα with α < 1/2 for small m but saturates at sufficiently large m. The exponent α changes with the power exponent of the memory kernel.

On the Stationarity of Multiple Autoregressive Approximants: Theory and Algorithms

DTIC Science & Technology

1976-08-01

a I (3.4) Hannan and Terrell (1972) consider problems of a similar nature. Efficient estimates A(1),... , A(p) , and i of A(1)... ,A(p) and...34Autoregressive model fitting for control, Ann . Inst. Statist. Math., 23, 163-180. Hannan, E. J. (1970), Multiple Time Series, New York, John Wiley...Hannan, E. J. and Terrell , R. D. (1972), "Time series regression with linear constraints, " International Economic Review, 13, 189-200. Masani, P

Forecasting Instability Indicators in the Horn of Africa

DTIC Science & Technology

2008-03-01

further than 2 (Makridakis, et al, 1983, 359). 2-32 Autoregressive Integrated Moving Average ( ARIMA ) Model . Similar to the ARMA model except for...stationary process. ARIMA models are described as ARIMA (p,d,q), where p is the order of the autoregressive process, d is the degree of the...differential process, and q is the order of the moving average process. The ARMA (1,1) model shown above is equivalent to an ARIMA (1,0,1) model . An ARIMA

Equilibrium Policy Proposals with Abstentions.

DTIC Science & Technology

1981-05-01

David M. Kreps. 262. ’Autoregressive Modelling and Money Income (ajusality Detection." by (heng lisiao. 263. "Measurement IError in a Dynamiic...34Autoregressive Modeling of"Canadian Money and Income Data," by Cheng Ilsjao. 277. "We Can’t Disagree IForever," by John 1). Geanakoplos and Heraklis...34*Optimal & Voluntary Income Distribution," by K. J. Arrow. 289. "’Asymptotic Values mif Mixed Gaime,.," by Abraham Neymnan. 290. "Tinie Series Modelling

Time series models on analysing mortality rates and acute childhood lymphoid leukaemia.

PubMed

Kis, Maria

2005-01-01

In this paper we demonstrate applying time series models on medical research. The Hungarian mortality rates were analysed by autoregressive integrated moving average models and seasonal time series models examined the data of acute childhood lymphoid leukaemia.The mortality data may be analysed by time series methods such as autoregressive integrated moving average (ARIMA) modelling. This method is demonstrated by two examples: analysis of the mortality rates of ischemic heart diseases and analysis of the mortality rates of cancer of digestive system. Mathematical expressions are given for the results of analysis. The relationships between time series of mortality rates were studied with ARIMA models. Calculations of confidence intervals for autoregressive parameters by tree methods: standard normal distribution as estimation and estimation of the White's theory and the continuous time case estimation. Analysing the confidence intervals of the first order autoregressive parameters we may conclude that the confidence intervals were much smaller than other estimations by applying the continuous time estimation model.We present a new approach to analysing the occurrence of acute childhood lymphoid leukaemia. We decompose time series into components. The periodicity of acute childhood lymphoid leukaemia in Hungary was examined using seasonal decomposition time series method. The cyclic trend of the dates of diagnosis revealed that a higher percent of the peaks fell within the winter months than in the other seasons. This proves the seasonal occurrence of the childhood leukaemia in Hungary.

EEG data reduction by means of autoregressive representation and discriminant analysis procedures.

PubMed

Blinowska, K J; Czerwosz, L T; Drabik, W; Franaszczuk, P J; Ekiert, H

1981-06-01

A program for automatic evaluation of EEG spectra, providing considerable reduction of data, was devised. Artefacts were eliminated in two steps: first, the longer duration eye movement artefacts were removed by a fast and simple 'moving integral' methods, then occasional spikes were identified by means of a detection function defined in the formalism of the autoregressive (AR) model. The evaluation of power spectra was performed by means of an FFT and autoregressive representation, which made possible the comparison of both methods. The spectra obtained by means of the AR model had much smaller statistical fluctuations and better resolution, enabling us to follow the time changes of the EEG pattern. Another advantage of the autoregressive approach was the parametric description of the signal. This last property appeared to be essential in distinguishing the changes in the EEG pattern. In a drug study the application of the coefficients of the AR model as input parameters in the discriminant analysis, instead of arbitrary chosen frequency bands, brought a significant improvement in distinguishing the effects of the medication. The favourable properties of the AR model are connected with the fact that the above approach fulfils the maximum entropy principle. This means that the method describes in a maximally consistent way the available information and is free from additional assumptions, which is not the case for the FFT estimate.

Prediction of global ionospheric VTEC maps using an adaptive autoregressive model

NASA Astrophysics Data System (ADS)

Wang, Cheng; Xin, Shaoming; Liu, Xiaolu; Shi, Chuang; Fan, Lei

2018-02-01

In this contribution, an adaptive autoregressive model is proposed and developed to predict global ionospheric vertical total electron content maps (VTEC). Specifically, the spherical harmonic (SH) coefficients are predicted based on the autoregressive model, and the order of the autoregressive model is determined adaptively using the F-test method. To test our method, final CODE and IGS global ionospheric map (GIM) products, as well as altimeter TEC data during low and mid-to-high solar activity period collected by JASON, are used to evaluate the precision of our forecasting products. Results indicate that the predicted products derived from the model proposed in this paper have good consistency with the final GIMs in low solar activity, where the annual mean of the root-mean-square value is approximately 1.5 TECU. However, the performance of predicted vertical TEC in periods of mid-to-high solar activity has less accuracy than that during low solar activity periods, especially in the equatorial ionization anomaly region and the Southern Hemisphere. Additionally, in comparison with forecasting products, the final IGS GIMs have the best consistency with altimeter TEC data. Future work is needed to investigate the performance of forecasting products using the proposed method in an operational environment, rather than using the SH coefficients from the final CODE products, to understand the real-time applicability of the method.

Car crash and injury among young drivers: contribution of social, circumstantial and car attributes.

PubMed

Laflamme, L; Vaez, M

2007-03-01

The objective of the study was to assess the independent contribution of individual, car and circumstantial features in severe and fatal car crashes involving young drivers. A prospective longitudinal, register-based cohort study was conducted at national level (in Sweden), in which people born in the years 1970-1972 (n = 334070) were followed up for the period 1988-2000 (aged 16-18 years in 1988) for their first two-car crashes leading to severe or fatal injury. Ten variables descriptive of the driver (sociodemographics), the car (safety level) and the crash have been analysed using multiple logistic regressions for male and female drivers separately, compiling crude and adjusted odds ratios with 95% CI. When controlling for other features, none of the variables descriptive of male and female drivers' socio-demographic characteristics impacts significantly on the odds of being severely injured or dying in a car-to-car crash. After adjustment, significant excess risks are observed for speed limits higher than the lowest one, type of crash other than rear end collision and road and light conditions other than favourable (dry and daylight), for both male and female drivers. For males only, cars from all car safety levels have significantly higher odds than those from the safest category. Among male and female young drivers, class differences in the risk of being severely injured in a traffic injury are substantial. Yet, despite this imbalance, crash characteristics (for males and females) and safety level of the vehicle driven (for males) remain the most determinant factors of crash severity. Understanding the social patterning of road traffic injuries is a challenge for public health and it seems that qualitative and quantitative differences in crash exposure offer part of the explanation. Young drivers from all social groups need, however, to be sensitized to the risk factors.

The effects of velocity difference changes with memory on the dynamics characteristics and fuel economy of traffic flow

NASA Astrophysics Data System (ADS)

Yu, Shaowei; Zhao, Xiangmo; Xu, Zhigang; Zhang, Licheng

2016-11-01

To evaluate the effects of velocity difference changes with memory in the intelligent transportation environment on the dynamics and fuel consumptions of traffic flow, we first investigate the linkage between velocity difference changes with memory and car-following behaviors with the measured data in cities, and then propose an improved cooperative car-following model considering multiple velocity difference changes with memory in the cooperative adaptive cruise control strategy, finally carry out several numerical simulations under the periodic boundary condition and at signalized intersections to explore how velocity difference changes with memory affect car's velocity, velocity fluctuation, acceleration and fuel consumptions in the intelligent transportation environment. The results show that velocity difference changes with memory have obvious effects on car-following behaviors, that the improved cooperative car-following model can describe the phase transition of traffic flow and estimate the evolution of traffic congestion, that the stability and fuel economy of traffic flow simulated by the improved car-following model with velocity difference changes with memory is obviously superior to those without velocity difference changes, and that taking velocity difference changes with memory into account in designing the advanced adaptive cruise control strategy can significantly improve the stability and fuel economy of traffic flow.

Driver Mortality in Paired Side Impact Collisions Due to Incompatible Vehicle Types

PubMed Central

Crandall, C.S.

2003-01-01

Using a matched case control design, this study measured the mortality associated with paired passenger car-sport utility vehicle side impact (‘T-bone’) collisions using FARS data. Survival versus fatal outcome within the matched crash pairs was measured with matched pair odds ratios. Conditional logistic regression adjusted for multiple effects. Overall, passenger car drivers experienced greater mortality than did SUV drivers, regardless if they were in the struck or striking vehicle (odds ratio: 10.0; 95% confidence interval: 7.9, 12.5). Differential mortality persisted after adjustment for confounders. Efforts should be sought to improve passenger car side impact crashworthiness and to reduce SUV aggressivity. PMID:12941243

[Steady car engine noise does not affect the cognitive abilities of sleep apnea syndrome patients].

PubMed

Mayoralas, L R; Barbé, F; Muñoz, A; Agustí, A G N

2003-09-01

Traffic accidents are more frequent for sleep apnea syndrome (SAS) patients than in the population at large. The mechanisms that underlie this observation are poorly defined. Our working hypothesis was that in SAS patients the steady noise of a car engine might alter cognitive capacities that may be involved in driving, thus increasing the risk of traffic accidents. To test this hypothesis we designed a prospective randomized controlled trial. Eighteen SAS patients (apnea-hypopnea index [SEM] 62 [6] h1) and 18 healthy controls were studied. All the participants were evaluated in random order both in basal conditions and after exposure to the steady noise of a car engine recorded on a compact disc. Their level of vigilance was evaluated (Steer-Clear) as well as their reaction time (PVT 192). Attention, coordination, and memory were measured using the following tests: Wechsler Memory Scale (digit span), the Wechsler Intelligence Scale (digit symbol), and Lezack's Trail Making tests A and B. The SAS patients were slightly younger than the control group (mean 50 [7] vs 57 [11] years, respectively; P=.05). The patients showed a lower level of vigilance than the controls both in basal and engine noise conditions (P<.05). No differences between groups were found for the other variables studied. Exposure to steady car engine noise had no effect on the tests of either group. In conclusion, the results of our study do not support the hypothesis that steady car engine noise significantly alters the cognitive ability of SAS patients.

Parkinson's disease and driving ability

PubMed Central

Singh, Rajiv; Pentland, Brian; Hunter, John; Provan, Frances

2007-01-01

Objectives To explore the driving problems associated with Parkinson's disease (PD) and to ascertain whether any clinical features or tests predict driver safety. Methods The driving ability of 154 individuals with PD referred to a driving assessment centre was determined by a combination of clinical tests, reaction times on a test rig and an in‐car driving test. Results The majority of cases (104, 66%) were able to continue driving although 46 individuals required an automatic transmission and 10 others needed car modifications. Ability to drive was predicted by the severity of physical disease, age, presence of other associated medical conditions, particularly dementia, duration of disease, brake reaction, time on a test rig and score on a driving test (all p<0.001). The level of drug treatment and the length of driving history were not correlated. Discriminant analysis revealed that the most important features in distinguishing safety to drive were severe physical disease (Hoehn and Yahr stage 3), reaction time, moderate disease associated with another medical condition and high score on car testing. Conclusions Most individuals with PD are safe to drive, although many benefit from car modifications or from using an automatic transmission. A combination of clinical tests and in‐car driving assessment will establish safety to drive, and a number of clinical correlates can be shown to predict the likely outcome and may assist in the decision process. This is the largest series of consecutive patients seen at a driving assessment centre reported to date, and the first to devise a scoring system for on‐road driving assessment. PMID:17178820

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.

Measuring Treasury Bond Portfolio Risk and Portfolio Optimization with a Non-Gaussian Multivariate Model

NASA Astrophysics Data System (ADS)

Dong, Yijun

The research about measuring the risk of a bond portfolio and the portfolio optimization was relatively rare previously, because the risk factors of bond portfolios are not very volatile. However, this condition has changed recently. The 2008 financial crisis brought high volatility to the risk factors and the related bond securities, even if the highly rated U.S. treasury bonds. Moreover, the risk factors of bond portfolios show properties of fat-tailness and asymmetry like risk factors of equity portfolios. Therefore, we need to use advanced techniques to measure and manage risk of bond portfolios. In our paper, we first apply autoregressive moving average generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) model with multivariate normal tempered stable (MNTS) distribution innovations to predict risk factors of U.S. treasury bonds and statistically demonstrate that MNTS distribution has the ability to capture the properties of risk factors based on the goodness-of-fit tests. Then based on empirical evidence, we find that the VaR and AVaR estimated by assuming normal tempered stable distribution are more realistic and reliable than those estimated by assuming normal distribution, especially for the financial crisis period. Finally, we use the mean-risk portfolio optimization to minimize portfolios' potential risks. The empirical study indicates that the optimized bond portfolios have better risk-adjusted performances than the benchmark portfolios for some periods. Moreover, the optimized bond portfolios obtained by assuming normal tempered stable distribution have improved performances in comparison to the optimized bond portfolios obtained by assuming normal distribution.

Assessment of cardio-respiratory interactions in preterm infants by bivariate autoregressive modeling and surrogate data analysis.

PubMed

Indic, Premananda; Bloch-Salisbury, Elisabeth; Bednarek, Frank; Brown, Emery N; Paydarfar, David; Barbieri, Riccardo

2011-07-01

Cardio-respiratory interactions are weak at the earliest stages of human development, suggesting that assessment of their presence and integrity may be an important indicator of development in infants. Despite the valuable research devoted to infant development, there is still a need for specifically targeted standards and methods to assess cardiopulmonary functions in the early stages of life. We present a new methodological framework for the analysis of cardiovascular variables in preterm infants. Our approach is based on a set of mathematical tools that have been successful in quantifying important cardiovascular control mechanisms in adult humans, here specifically adapted to reflect the physiology of the developing cardiovascular system. We applied our methodology in a study of cardio-respiratory responses for 11 preterm infants. We quantified cardio-respiratory interactions using specifically tailored multivariate autoregressive analysis and calculated the coherence as well as gain using causal approaches. The significance of the interactions in each subject was determined by surrogate data analysis. The method was tested in control conditions as well as in two different experimental conditions; with and without use of mild mechanosensory intervention. Our multivariate analysis revealed a significantly higher coherence, as confirmed by surrogate data analysis, in the frequency range associated with eupneic breathing compared to the other ranges. Our analysis validates the models behind our new approaches, and our results confirm the presence of cardio-respiratory coupling in early stages of development, particularly during periods of mild mechanosensory intervention, thus encouraging further application of our approach. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Upscaling of a Batch De-Vulcanization Process for Ground Car Tire Rubber to a Continuous Process in a Twin Screw Extruder.

PubMed

Saiwari, Sitisaiyidah; van Hoek, Johannes W; Dierkes, Wilma K; Reuvekamp, Louis E A M; Heideman, Geert; Blume, Anke; Noordermeer, Jacques W M

2016-08-24

As a means to decrease the amount of waste tires and to re-use tire rubber for new tires, devulcanization of ground passenger car tires is a promising process. Being an established process for NR and EPDM, earlier work has shown that for ground passenger car tire rubber with a relatively high amount of SBR, a devulcanization process can be formulated, as well. This was proven for a laboratory-scale batch process in an internal mixer, using diphenyl disulfide as the devulcanization aid and powder-sized material. In this paper, the devulcanization process for passenger car tire rubber is upscaled from 15 g per batch and transformed into a continuous process in a co-rotating twin screw extruder with a capacity of 2 kg/h. As SBR is rather sensitive to devulcanization process conditions, such as thermal and mechanical energy input, the screw design was based on a low shear concept. A granulate with particle sizes from 1-3.5 mm was chosen for purity, as well as economic reasons. The devulcanization process conditions were fine-tuned in terms of: devulcanization conditions (time/temperature profile, concentration of devulcanization aid), extruder parameters (screw configuration, screw speed, fill factor) and ancillary equipment (pre-treatment, extrudate handling). The influence of these parameters on the devulcanization efficiency and the quality of the final product will be discussed. The ratio of random to crosslink scission as determined by a Horikx plot was taken for the evaluation of the process and material. A best practice for continuous devulcanization will be given.

Upscaling of a Batch De-Vulcanization Process for Ground Car Tire Rubber to a Continuous Process in a Twin Screw Extruder

PubMed Central

Saiwari, Sitisaiyidah; van Hoek, Johannes W.; Dierkes, Wilma K.; Reuvekamp, Louis E.A.M.; Heideman, Geert; Blume, Anke; Noordermeer, Jacques W.M.

2016-01-01

As a means to decrease the amount of waste tires and to re-use tire rubber for new tires, devulcanization of ground passenger car tires is a promising process. Being an established process for NR and EPDM, earlier work has shown that for ground passenger car tire rubber with a relatively high amount of SBR, a devulcanization process can be formulated, as well. This was proven for a laboratory-scale batch process in an internal mixer, using diphenyl disulfide as the devulcanization aid and powder-sized material. In this paper, the devulcanization process for passenger car tire rubber is upscaled from 15 g per batch and transformed into a continuous process in a co-rotating twin screw extruder with a capacity of 2 kg/h. As SBR is rather sensitive to devulcanization process conditions, such as thermal and mechanical energy input, the screw design was based on a low shear concept. A granulate with particle sizes from 1–3.5 mm was chosen for purity, as well as economic reasons. The devulcanization process conditions were fine-tuned in terms of: devulcanization conditions (time/temperature profile, concentration of devulcanization aid), extruder parameters (screw configuration, screw speed, fill factor) and ancillary equipment (pre-treatment, extrudate handling). The influence of these parameters on the devulcanization efficiency and the quality of the final product will be discussed. The ratio of random to crosslink scission as determined by a Horikx plot was taken for the evaluation of the process and material. A best practice for continuous devulcanization will be given. PMID:28773843

Predation and fragmentation portrayed in the statistical structure of prey time series

PubMed Central

Hendrichsen, Ditte K; Topping, Chris J; Forchhammer, Mads C

2009-01-01

Background Statistical autoregressive analyses of direct and delayed density dependence are widespread in ecological research. The models suggest that changes in ecological factors affecting density dependence, like predation and landscape heterogeneity are directly portrayed in the first and second order autoregressive parameters, and the models are therefore used to decipher complex biological patterns. However, independent tests of model predictions are complicated by the inherent variability of natural populations, where differences in landscape structure, climate or species composition prevent controlled repeated analyses. To circumvent this problem, we applied second-order autoregressive time series analyses to data generated by a realistic agent-based computer model. The model simulated life history decisions of individual field voles under controlled variations in predator pressure and landscape fragmentation. Analyses were made on three levels: comparisons between predated and non-predated populations, between populations exposed to different types of predators and between populations experiencing different degrees of habitat fragmentation. Results The results are unambiguous: Changes in landscape fragmentation and the numerical response of predators are clearly portrayed in the statistical time series structure as predicted by the autoregressive model. Populations without predators displayed significantly stronger negative direct density dependence than did those exposed to predators, where direct density dependence was only moderately negative. The effects of predation versus no predation had an even stronger effect on the delayed density dependence of the simulated prey populations. In non-predated prey populations, the coefficients of delayed density dependence were distinctly positive, whereas they were negative in predated populations. Similarly, increasing the degree of fragmentation of optimal habitat available to the prey was accompanied with a shift in the delayed density dependence, from strongly negative to gradually becoming less negative. Conclusion We conclude that statistical second-order autoregressive time series analyses are capable of deciphering interactions within and across trophic levels and their effect on direct and delayed density dependence. PMID:19419539

The dynamic correlation between policy uncertainty and stock market returns in China

NASA Astrophysics Data System (ADS)

Yang, Miao; Jiang, Zhi-Qiang

2016-11-01

The dynamic correlation is examined between government's policy uncertainty and Chinese stock market returns in the period from January 1995 to December 2014. We find that the stock market is significantly correlated to policy uncertainty based on the results of the Vector Auto Regression (VAR) and Structural Vector Auto Regression (SVAR) models. In contrast, the results of the Dynamic Conditional Correlation Generalized Multivariate Autoregressive Conditional Heteroscedasticity (DCC-MGARCH) model surprisingly show a low dynamic correlation coefficient between policy uncertainty and market returns, suggesting that the fluctuations of each variable are greatly influenced by their values in the preceding period. Our analysis highlights the understanding of the dynamical relationship between stock market and fiscal and monetary policy.

Numerical Analysis of Thermo Hydraulic Conditions in Car Fog Lamp

NASA Astrophysics Data System (ADS)

Ramšak, M.; Žunič, Z.; Škerget, L.; Jurejevčič, T.

2009-08-01

In the article a coupled heat transfer in the solid and fluid inside of a car fog lamp is presented using CFD software CFX [1]. All three basic principles of heat transfer are dealt with: conduction, convection and radiation. Two different approaches to radiation modeling are compared. Laminar and turbulent flow modeling are compared since computed Rayleight number indicates transitional flow regime. Results are in good agreement with the measurements.

Expertise Effects in Face-Selective Areas are Robust to Clutter and Diverted Attention, but not to Competition.

PubMed

McGugin, Rankin Williams; Van Gulick, Ana E; Tamber-Rosenau, Benjamin J; Ross, David A; Gauthier, Isabel

2015-09-01

Expertise effects for nonface objects in face-selective brain areas may reflect stable aspects of neuronal selectivity that determine how observers perceive objects. However, bottom-up (e.g., clutter from irrelevant objects) and top-down manipulations (e.g., attentional selection) can influence activity, affecting the link between category selectivity and individual performance. We test the prediction that individual differences expressed as neural expertise effects for cars in face-selective areas are sufficiently stable to survive clutter and manipulations of attention. Additionally, behavioral work and work using event related potentials suggest that expertise effects may not survive competition; we investigate this using functional magnetic resonance imaging. Subjects varying in expertise with cars made 1-back decisions about cars, faces, and objects in displays containing one or 2 objects, with only one category attended. Univariate analyses suggest car expertise effects are robust to clutter, dampened by reducing attention to cars, but nonetheless more robust to manipulations of attention than competition. While univariate expertise effects are severely abolished by competition between cars and faces, multivariate analyses reveal new information related to car expertise. These results demonstrate that signals in face-selective areas predict expertise effects for nonface objects in a variety of conditions, although individual differences may be expressed in different dependent measures depending on task and instructions. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Rage against the machine? Google's self-driving cars versus human drivers.

PubMed

Teoh, Eric R; Kidd, David G

2017-12-01

Automated driving represents both challenges and opportunities in highway safety. Google has been developing self-driving cars and testing them under employee supervision on public roads since 2009. These vehicles have been involved in several crashes, and it is of interest how this testing program compares to human drivers in terms of safety. Google car crashes were coded by type and severity based on narratives released by Google. Crash rates per million vehicle miles traveled (VMT) were computed for crashes deemed severe enough to be reportable to police. These were compared with police-reported crash rates for human drivers. Crash types also were compared. Google cars had a much lower rate of police-reportable crashes per million VMT than human drivers in Mountain View, Calif., during 2009-2015 (2.19 vs 6.06), but the difference was not statistically significant. The most common type of collision involving Google cars was when they got rear-ended by another (human-driven) vehicle. Google cars shared responsibility for only one crash. These results suggest Google self-driving cars, while a test program, are safer than conventional human-driven passenger vehicles; however, currently there is insufficient information to fully examine the extent to which disengagements affected these results. Results suggest that highly-automated vehicles can perform more safely than human drivers in certain conditions, but will continue to be involved in crashes with conventionally-driven vehicles. Copyright © 2017. Published by Elsevier Ltd.

Impact of the electric compressor for automotive air conditioning system on fuel consumption and performance analysis

NASA Astrophysics Data System (ADS)

Zulkifli, A. A.; Dahlan, A. A.; Zulkifli, A. H.; Nasution, H.; Aziz, A. A.; Perang, M. R. M.; Jamil, H. M.; Misseri, M. N.

2015-12-01

Air conditioning system is the biggest auxiliary load in a vehicle where the compressor consumed the largest. Problem with conventional compressor is the cooling capacity cannot be control directly to fulfill the demand of thermal load inside vehicle cabin. This study is conducted experimentally to analyze the difference of fuel usage and air conditioning performance between conventional compressor and electric compressor of the air conditioning system in automobile. The electric compressor is powered by the car battery in non-electric vehicle which the alternator will recharge the battery. The car is setup on a roller dynamometer and the vehicle speed is varied at 0, 30, 60, 90 and 110 km/h at cabin temperature of 25°C and internal heat load of 100 and 400 Watt. The results shows electric compressor has better fuel consumption and coefficient of performance compared to the conventional compressor.

Business cycles and fertility dynamics in the United States: a vector autoregressive model.

PubMed

Mocan, N H

1990-01-01

"Using vector-autoregressions...this paper shows that fertility moves countercyclically over the business cycle....[It] shows that the United States fertility is not governed by a deterministic trend as was assumed by previous studies. Rather, fertility evolves around a stochastic trend. It is shown that a bivariate analysis between fertility and unemployment yields a procyclical picture of fertility. However, when one considers the effects on fertility of early marriages and the divorce behavior as well as economic activity, fertility moves countercyclically." excerpt

Processing on weak electric signals by the autoregressive model

NASA Astrophysics Data System (ADS)

Ding, Jinli; Zhao, Jiayin; Wang, Lanzhou; Li, Qiao

2008-10-01

A model of the autoregressive model of weak electric signals in two plants was set up for the first time. The result of the AR model to forecast 10 values of the weak electric signals is well. It will construct a standard set of the AR model coefficient of the plant electric signal and the environmental factor, and can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on agricultural productions.

Fisher Consistency of AM-Estimates of the Autoregression Parameter Using Hard Rejection Filter Cleaners

DTIC Science & Technology

1987-02-04

U5tr,)! P(U 5-t Since U - F with F RS, we get (3.1). Case b: 0 S 5 k -a Now P([U~t]riM) = P(UZk-a) and P([ Ugt ]rM) = P(US-k-a) S P(US-(k-a)) which again...robustness for autoregressive processes." The Annals of Statistics, 12, 843-863. Mallows, C.L. (1980). "Some theory of nonlinear smoothen." The Annals of

Simulation-based power calculation for designing interrupted time series analyses of health policy interventions.

PubMed

Zhang, Fang; Wagner, Anita K; Ross-Degnan, Dennis

2011-11-01

Interrupted time series is a strong quasi-experimental research design to evaluate the impacts of health policy interventions. Using simulation methods, we estimated the power requirements for interrupted time series studies under various scenarios. Simulations were conducted to estimate the power of segmented autoregressive (AR) error models when autocorrelation ranged from -0.9 to 0.9 and effect size was 0.5, 1.0, and 2.0, investigating balanced and unbalanced numbers of time periods before and after an intervention. Simple scenarios of autoregressive conditional heteroskedasticity (ARCH) models were also explored. For AR models, power increased when sample size or effect size increased, and tended to decrease when autocorrelation increased. Compared with a balanced number of study periods before and after an intervention, designs with unbalanced numbers of periods had less power, although that was not the case for ARCH models. The power to detect effect size 1.0 appeared to be reasonable for many practical applications with a moderate or large number of time points in the study equally divided around the intervention. Investigators should be cautious when the expected effect size is small or the number of time points is small. We recommend conducting various simulations before investigation. Copyright © 2011 Elsevier Inc. All rights reserved.

Increased performance in the short-term water demand forecasting through the use of a parallel adaptive weighting strategy

NASA Astrophysics Data System (ADS)

Sardinha-Lourenço, A.; Andrade-Campos, A.; Antunes, A.; Oliveira, M. S.

2018-03-01

Recent research on water demand short-term forecasting has shown that models using univariate time series based on historical data are useful and can be combined with other prediction methods to reduce errors. The behavior of water demands in drinking water distribution networks focuses on their repetitive nature and, under meteorological conditions and similar consumers, allows the development of a heuristic forecast model that, in turn, combined with other autoregressive models, can provide reliable forecasts. In this study, a parallel adaptive weighting strategy of water consumption forecast for the next 24-48 h, using univariate time series of potable water consumption, is proposed. Two Portuguese potable water distribution networks are used as case studies where the only input data are the consumption of water and the national calendar. For the development of the strategy, the Autoregressive Integrated Moving Average (ARIMA) method and a short-term forecast heuristic algorithm are used. Simulations with the model showed that, when using a parallel adaptive weighting strategy, the prediction error can be reduced by 15.96% and the average error by 9.20%. This reduction is important in the control and management of water supply systems. The proposed methodology can be extended to other forecast methods, especially when it comes to the availability of multiple forecast models.

CARS measurement of vibrational and rotational temperature with high power laser and high speed visualization of total radiation behind hypervelocity shock waves of 5-7km/s

NASA Astrophysics Data System (ADS)

Sakurai, Kotaro; Bindu, Venigalla Hima; Niinomi, Shota; Ota, Masanori; Maeno, Kazuo

2010-09-01

Coherent Anti-Stokes Raman Spectroscopy (CARS) method is commonly used for measuring molecular structure or condition. In the aerospace technology, this method is applies to measure the temperature in thermic fluid with relatively long time duration of millisecond or sub millisecond. On the other hand, vibrational/rotational temperatures behind hypervelocity shock wave are important for heat-shield design in phase of reentry flight. The non-equilibrium flow with radiative heating from strongly shocked air ahead of the vehicles plays an important role on the heat flux to the wall surface structure as well as convective heating. In this paper CARS method is applied to measure the vibrational/rotational temperature of N2 behind hypervelocity shock wave. The strong shock wave in front of the reentering space vehicles can be experimentally realigned by free-piston, double-diaphragm shock tube with low density test gas. However CARS measurement is difficult for our experiment. Our measurement needs very short pulse which order of nanosecond and high power laser for CARS method. It is due to our measurement object is the momentary phenomena which velocity is 7km/s. In addition the observation section is low density test gas, and there is the strong background light behind the shock wave. So we employ the CARS method with high power, order of 1J/pulse, and very short pulse (10ns) laser. By using this laser the CARS signal can be acquired even in the strong radiation area. Also we simultaneously try to use the CCD camera to obtain total radiation with CARS method.

Risks of pedestrian serious injuries and fatalities associated with impact velocities of cars in car-versus-pedestrian accidents in Japan.

PubMed

Matsui, Yasuhiro; Oikawa, Shoko; Ando, Kenichi

2013-11-01

The first purpose of this study is to clarify the relation between the car impact velocity and pedestrian injury severity or mortality risk. We investigated the frequency of serious injuries and fatalities of pedestrians using vehicle-pedestrian accident data from the database of the Institute for Traffic Accident Research and Data Analysis (ITARDA) in Japan. The vehicle types considered are sedans, minivans, and box vans (ordinary automobiles) and light passenger cars and light cargo vans (light automobiles). The results revealed that a 10-km/h reduction in impact velocity could mitigate severe pedestrian injuries in cases involving impact velocities of 40 km/h or more for the five vehicle types analyzed. Specifically, if the impact velocity was 30 km/h or less, the frequency of serious injuries was less than 27% and the frequency of fatalities was less than 5% for the five vehicle types. Therefore, if the collision damage mitigation braking system (CDMBS) that uses a sensor to detect pedestrians can effectively reduce the impact velocity for various vehicle types, pedestrian injuries will be greatly mitigated. The second purpose of this study is to identify the factors that affect injury risk. Impact experiments were conducted in which a sedan impacted against a pedestrian full-scale dummy at 40 km/h and a pedestrian headform impactor was impacted against a road surface. The results indicated that the risk of pedestrian serious injury was significantly affected by multiple impact conditions, such as the pedestrian height, car impact velocity, car frontal shape, and car stiffness in cases where the car impacted the pedestrian's head, the degrees of influence of which were driven by the vehicle impact velocity.

Extracellular NGFR Spacers Allow Efficient Tracking and Enrichment of Fully Functional CAR-T Cells Co-Expressing a Suicide Gene

PubMed Central

Casucci, Monica; Falcone, Laura; Camisa, Barbara; Norelli, Margherita; Porcellini, Simona; Stornaiuolo, Anna; Ciceri, Fabio; Traversari, Catia; Bordignon, Claudio; Bonini, Chiara; Bondanza, Attilio

2018-01-01

Chimeric antigen receptor (CAR)-T cell immunotherapy is at the forefront of innovative cancer therapeutics. However, lack of standardization of cellular products within the same clinical trial and lack of harmonization between different trials have hindered the clear identification of efficacy and safety determinants that should be unveiled in order to advance the field. With the aim of facilitating the isolation and in vivo tracking of CAR-T cells, we here propose the inclusion within the CAR molecule of a novel extracellular spacer based on the low-affinity nerve-growth-factor receptor (NGFR). We screened four different spacer designs using as target antigen the CD44 isoform variant 6 (CD44v6). We successfully generated NGFR-spaced CD44v6 CAR-T cells that could be efficiently enriched with clinical-grade immuno-magnetic beads without negative consequences on subsequent expansion, immuno-phenotype, in vitro antitumor reactivity, and conditional ablation when co-expressing a suicide gene. Most importantly, these cells could be tracked with anti-NGFR monoclonal antibodies in NSG mice, where they expanded, persisted, and exerted potent antitumor effects against both high leukemia and myeloma burdens. Similar results were obtained with NGFR-enriched CAR-T cells specific for CD19 or CEA, suggesting the universality of this strategy. In conclusion, we have demonstrated that the incorporation of the NGFR marker gene within the CAR sequence allows for a single molecule to simultaneously work as a therapeutic and selection/tracking gene. Looking ahead, NGFR spacer enrichment might allow good manufacturing procedures-manufacturing of standardized CAR-T cell products with high therapeutic potential, which could be harmonized in different clinical trials and used in combination with a suicide gene for future application in the allogeneic setting. PMID:29619024

Chemotherapy-Refractory Diffuse Large B-Cell Lymphoma and Indolent B-Cell Malignancies Can Be Effectively Treated With Autologous T Cells Expressing an Anti-CD19 Chimeric Antigen Receptor

PubMed Central

Kochenderfer, James N.; Dudley, Mark E.; Kassim, Sadik H.; Somerville, Robert P.T.; Carpenter, Robert O.; Stetler-Stevenson, Maryalice; Yang, James C.; Phan, Giao Q.; Hughes, Marybeth S.; Sherry, Richard M.; Raffeld, Mark; Feldman, Steven; Lu, Lily; Li, Yong F.; Ngo, Lien T.; Goy, Andre; Feldman, Tatyana; Spaner, David E.; Wang, Michael L.; Chen, Clara C.; Kranick, Sarah M.; Nath, Avindra; Nathan, Debbie-Ann N.; Morton, Kathleen E.; Toomey, Mary Ann; Rosenberg, Steven A.

2015-01-01

Purpose T cells can be genetically modified to express an anti-CD19 chimeric antigen receptor (CAR). We assessed the safety and efficacy of administering autologous anti-CD19 CAR T cells to patients with advanced CD19+ B-cell malignancies. Patients and Methods We treated 15 patients with advanced B-cell malignancies. Nine patients had diffuse large B-cell lymphoma (DLBCL), two had indolent lymphomas, and four had chronic lymphocytic leukemia. Patients received a conditioning chemotherapy regimen of cyclophosphamide and fludarabine followed by a single infusion of anti-CD19 CAR T cells. Results Of 15 patients, eight achieved complete remissions (CRs), four achieved partial remissions, one had stable lymphoma, and two were not evaluable for response. CRs were obtained by four of seven evaluable patients with chemotherapy-refractory DLBCL; three of these four CRs are ongoing, with durations ranging from 9 to 22 months. Acute toxicities including fever, hypotension, delirium, and other neurologic toxicities occurred in some patients after infusion of anti-CD19 CAR T cells; these toxicities resolved within 3 weeks after cell infusion. One patient died suddenly as a result of an unknown cause 16 days after cell infusion. CAR T cells were detected in the blood of patients at peak levels, ranging from nine to 777 CAR-positive T cells/μL. Conclusion This is the first report to our knowledge of successful treatment of DLBCL with anti-CD19 CAR T cells. These results demonstrate the feasibility and effectiveness of treating chemotherapy-refractory B-cell malignancies with anti-CD19 CAR T cells. The numerous remissions obtained provide strong support for further development of this approach. PMID:25154820

Cortisol awakening response and emotion at extreme altitudes on Mount Kangchenjunga.

PubMed

Aguilar, Raúl; Martínez, Carlos; Alvero-Cruz, José R

2017-12-24

The cortisol awakening response (CAR) was examined over a 45days stay at extreme altitudes (above of about 5500m) on Mount Kangchenjunga. The CAR refers to a peak cortisol response during the waking period that is superimposed to the diurnal rhythmicity in cortisol secretion, whose function has been proposed to be the anticipation of demands of the upcoming day (the CAR anticipation hypothesis). According to this hypothesis, we distinguished between resting days on which the expedition team engaged in routine activities in the base camp, and ascent days on which it planned to climb up a very demanding track. We were also interested in examining the association of testosterone with emotional anticipation, given the role of this steroid hormone in reward-related processes in challenge situations. Results showed that the climber group had a bigger CAR on ascent days, relative to the Sherpa group at the same altitude and the non-climber group at sea level. Several methodological issues, however, made it difficult to interpret these group differences in terms of the CAR anticipation hypothesis (e.g. a seemingly influential covariate was awakening time). Although based on tentative results, correlational and regression analyses controlling for awakening time coherently showed that the CAR was associated with anticipation of a hard day and feelings of fear, and testosterone was associated with feelings of energy and positive affect. Whether or not the anticipation of a hard day played a key role in regulation of the CAR, the observation of an intact CAR in the climber group under hypobaric hypoxia conditions would require in-depth reflection from the perspective of human adaptive evolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Medium- and Long-term Prediction of LOD Change by the Leap-step Autoregressive Model

NASA Astrophysics Data System (ADS)

Wang, Qijie

2015-08-01

The accuracy of medium- and long-term prediction of length of day (LOD) change base on combined least-square and autoregressive (LS+AR) deteriorates gradually. Leap-step autoregressive (LSAR) model can significantly reduce the edge effect of the observation sequence. Especially, LSAR model greatly improves the resolution of signals’ low-frequency components. Therefore, it can improve the efficiency of prediction. In this work, LSAR is used to forecast the LOD change. The LOD series from EOP 08 C04 provided by IERS is modeled by both the LSAR and AR models. The results of the two models are analyzed and compared. When the prediction length is between 10-30 days, the accuracy improvement is less than 10%. When the prediction length amounts to above 30 day, the accuracy improved obviously, with the maximum being around 19%. The results show that the LSAR model has higher prediction accuracy and stability in medium- and long-term prediction.

Acceleration and Velocity Sensing from Measured Strain

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truax, Roger

2015-01-01

A simple approach for computing acceleration and velocity of a structure from the strain is proposed in this study. First, deflection and slope of the structure are computed from the strain using a two-step theory. Frequencies of the structure are computed from the time histories of strain using a parameter estimation technique together with an autoregressive moving average model. From deflection, slope, and frequencies of the structure, acceleration and velocity of the structure can be obtained using the proposed approach. Simple harmonic motion is assumed for the acceleration computations, and the central difference equation with a linear autoregressive model is used for the computations of velocity. A cantilevered rectangular wing model is used to validate the simple approach. Quality of the computed deflection, acceleration, and velocity values are independent of the number of fibers. The central difference equation with a linear autoregressive model proposed in this study follows the target response with reasonable accuracy. Therefore, the handicap of the backward difference equation, phase shift, is successfully overcome.

Sleep analysis for wearable devices applying autoregressive parametric models.

PubMed

Mendez, M O; Villantieri, O; Bianchi, A; Cerutti, S

2005-01-01

We applied time-variant and time-invariant parametric models in both healthy subjects and patients with sleep disorder recordings in order to assess the skills of those approaches to sleep disorders diagnosis in wearable devices. The recordings present the Obstructive Sleep Apnea (OSA) pathology which is characterized by fluctuations in the heart rate, bradycardia in apneonic phase and tachycardia at the recovery of ventilation. Data come from a web database in www.physionet.org. During OSA the spectral indexes obtained by time-variant lattice filters presented oscillations that correspond to the changes brady-tachycardia of the RR intervals and greater values than healthy ones. Multivariate autoregressive models showed an increment in very low frequency component (PVLF) at each apneic event. Also a rise in high frequency component (PHF) occurred over the breathing restore in the spectrum of both quadratic coherence and cross-spectrum in OSA. These autoregressive parametric approaches could help in the diagnosis of Sleep Disorder inside of the wearable devices.

[A novel method of multi-channel feature extraction combining multivariate autoregression and multiple-linear principal component analysis].

PubMed

Wang, Jinjia; Zhang, Yanna

2015-02-01

Brain-computer interface (BCI) systems identify brain signals through extracting features from them. In view of the limitations of the autoregressive model feature extraction method and the traditional principal component analysis to deal with the multichannel signals, this paper presents a multichannel feature extraction method that multivariate autoregressive (MVAR) model combined with the multiple-linear principal component analysis (MPCA), and used for magnetoencephalography (MEG) signals and electroencephalograph (EEG) signals recognition. Firstly, we calculated the MVAR model coefficient matrix of the MEG/EEG signals using this method, and then reduced the dimensions to a lower one, using MPCA. Finally, we recognized brain signals by Bayes Classifier. The key innovation we introduced in our investigation showed that we extended the traditional single-channel feature extraction method to the case of multi-channel one. We then carried out the experiments using the data groups of IV-III and IV - I. The experimental results proved that the method proposed in this paper was feasible.

The cold driver: Cold stress while driving results in dangerous behavior.

PubMed

Morris, Drew M; Pilcher, June J

2016-10-01

Cool vehicle cabin temperatures can induce short-term non-hypothermic cold stress. The current study created a cold condition to examine the impact of cold stress on driving behavior. Forty-four participants drove a high-fidelity driving simulator during a thermal neutral or local torso cooled condition. Participants performed additional tasks to assess attention, psychomotor vigilance, and manual dexterity. Skin temperature was significantly lower in the cold condition while internal temperature was unaffected. Participants who had higher subjective ratings of cold followed lead vehicles closer and started to brake later. Participants in the cold condition followed the lead car 22% (0.82s) closer and started braking 20% (2.35s) later when approaching a stop sign during the car-following task. No change in attention, psychomotor vigilance, or dexterity was observed. The current results suggest that cold environmental conditions can contribute to dangerous driving behaviors. Measures of cold perception were also shown to predict changes in driving behavior. Copyright © 2016 Elsevier B.V. All rights reserved.

CARS diagnostics of the burning of H{sub 2} - O{sub 2} and CH{sub 4} - O{sub 2} mixtures at high temperatures and pressures

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

Vereshchagin, K A; Smirnov, Valery V; Stel'makh, O M

2012-01-31

Coherent anti-Stokes Raman scattering (CARS) spectroscopy is used to determine the parameters of gaseous combustion products of hydrogen and hydrocarbon fuels with oxygen at high temperatures and pressures. The methodical aspects of CARS thermometry, which are related to the optimal choice of molecules (diagnostic references) and specific features of their spectra, dependent on temperature and pressure, are analysed. Burning is modelled under the conditions similar to those of real spacecraft propulsion systems using a specially designed laboratory combustion chamber, operating in the pulse-periodic regime at high temperatures (to 3500 K) and pressures (to 20 MPa) of combustion products. (nonlinear opticalmore » phenomena)« less

Small passenger car transmission test-Chevrolet 200 transmission

NASA Technical Reports Server (NTRS)

Bujold, M. P.

1980-01-01

The small passenger car transmission was tested to supply electric vehicle manufacturers with technical information regarding the performance of commerically available transmissions which would enable them to design a more energy efficient vehicle. With this information the manufacturers could estimate vehicle driving range as well as speed and torque requirements for specific road load performance characteristics. A 1979 Chevrolet Model 200 automatic transmission was tested per a passenger car automatic transmission test code (SAE J651b) which required drive performance, coast performance, and no load test conditions. The transmission attained maximum efficiencies in the mid-eighty percent range for both drive performance tests and coast performance tests. Torque, speed and efficiency curves map the complete performance characteristics for Chevrolet Model 200 transmission.

A method of real-time detection for distant moving obstacles by monocular vision

NASA Astrophysics Data System (ADS)

Jia, Bao-zhi; Zhu, Ming

2013-12-01

In this paper, we propose an approach for detection of distant moving obstacles like cars and bicycles by a monocular camera to cooperate with ultrasonic sensors in low-cost condition. We are aiming at detecting distant obstacles that move toward our autonomous navigation car in order to give alarm and keep away from them. Method of frame differencing is applied to find obstacles after compensation of camera's ego-motion. Meanwhile, each obstacle is separated from others in an independent area and given a confidence level to indicate whether it is coming closer. The results on an open dataset and our own autonomous navigation car have proved that the method is effective for detection of distant moving obstacles in real-time.

An extended car-following model considering the acceleration derivative in some typical traffic environments

NASA Astrophysics Data System (ADS)

Zhou, Tong; Chen, Dong; Liu, Weining

2018-03-01

Based on the full velocity difference and acceleration car-following model, an extended car-following model is proposed by considering the vehicle’s acceleration derivative. The stability condition is given by applying the control theory. Considering some typical traffic environments, the results of theoretical analysis and numerical simulation show the extended model has a more actual acceleration of string vehicles than that of the previous models in starting process, stopping process and sudden brake. Meanwhile, the traffic jams more easily occur when the coefficient of vehicle’s acceleration derivative increases, which is presented by space-time evolution. The results confirm that the vehicle’s acceleration derivative plays an important role in the traffic jamming transition and the evolution of traffic congestion.

Drive Control of an Electric Vehicle by a Non-linear Controller

NASA Astrophysics Data System (ADS)

Mubin, Marizan; Ouchi, Shigeto; Anabuki, Masatoshi; Hirata, Hiroshi

The driving force of automobiles is transmitted by the frictional force between the tires and the road surface. This frictional force is a function of the weight of the car-body and the friction coefficient μ between the tires and the road surface. The friction coefficient μ is also a function of the following parameters: the slip ratio λ determined by the car-body speed and the wheel speed, and the condition of the road surface. Slippage of automobiles which causes much damage often occurs during accelerating and braking. In this paper, we propose a new drive control system which has an effect on acceleration and braking. In the drive control system, a non-linear controller designed by using a Lyapunov function is used. This non-linear controller has two functions: first one is μ control which moves the car-body, another one is λ control. The controller is designed in order that μ and λ work at noslip and with slip respectively. As another controller, a disturbance observer is used for estimating the car-body speed which is difficult to be measured. Then, this lead to the proof of the stability condition of the combined system which consists of two controllers: the non-linear controller and the disturbance observer. Finally, the effectiveness of this control system is proved by a very satisfactory simulation and experimental results for two cases.

Different enzymatic antioxidative pathways operate within the sheep caruncular and intercaruncular endometrium throughout the estrous cycle and early pregnancy.

PubMed

Al-Gubory, K H; Faure, P; Garrel, C

2017-09-01

There has been a growing interest in the role played by antioxidant enzymes in the regulation of endometrial function in mammals. However, little is known about enzymatic antioxidative pathways involved in conditioning the cyclic and early pregnant endometrium for conceptus attachment and implantation in domestic ruminants. We aimed to investigate changes in activities of superoxide dismutase 1 and 2 (SOD1, SOD2), glutathione peroxidase (GPX), glutathione reductase (GR) and catalase (CAT) in sheep caruncles (CAR) and intercaruncles (ICAR) endometrial tissues of cyclic and early pregnant ewes. Irrespective of day of cycle or pregnancy, CAR demonstrated higher activities of SOD1 and SOD2 than in ICAR. On day 12 of the estrous cycle, ICAR demonstrated higher activity of GPX and GR than in CAR tissues. On days 12 and 16 the estrous cycle, ICAR demonstrated higher activity of CAT than in CAR. CAR demonstrated higher activity of GPX on day 18 than on days 4, 8, 12 and 16 of the estrous cycle. CAR demonstrated higher activity of CAT on day 18 than on days 4, 8, 12 and 16 of the estrous cycle. ICAR demonstrated higher activity of CAT on day 18 than on days 4, 8, and 16 of the estrous cycle. The activity of CAT in ICAR increased from days 4 and 8 to day 12 of the estrous cycle. The activity of SOD2 in CAR increased from day 16 to day 18 of pregnancy. On day 12 of pregnancy, CAR demonstrated higher activity of GPX than in ICAR. On day 16 of pregnancy, ICAR demonstrated higher activity of GPX than in CAR. The activity of GPX in ICAR increased from day 12 to day 16 of pregnancy. The activity of GPX in CAR increased from day 16 to day 18 of pregnancy. The activity of GR in CAR and ICAR increased from days 12 and 16 to day 18 of pregnancy. On days 16 and 18 of pregnancy, ICAR demonstrated higher activity of CAT than in CAR. The activity of CAT in CAR decreased from day 12 to days 16 and 18 of pregnancy. The activity of CAT in ICAR decreased from day 12 to day 16 of pregnancy and then increased from day 16 to day 18 of pregnancy. In conclusion, different antioxidant mechanisms operate within CAR and ICAR endometrium throughout the estrous cycle and during early pregnancy. This might be related to the different but important roles of CAR and ICAR endometrial tissues for the establishment of pregnancy. Copyright © 2017. Published by Elsevier Inc.

Automobile exhaust as a means of suicide: an experimental study with a proposed model.

PubMed

Morgen, C; Schramm, J; Kofoed, P; Steensberg, J; Theilade, P

1998-07-01

Experiments were conducted to investigate the concentration of carbon monoxide (CO) in a car cabin under suicide attempts with different vehicles and different start situations, and a mathematical model describing the concentration of CO in the cabin was constructed. Three cars were set up to donate the exhaust. The first vehicle didn't have any catalyst, the second one was equipped with a malfunctioning three-way catalyst, and the third car was equipped with a well-functioning three-way catalyst. The three different starting situations were cold, tepid and warm engine start, respectively. Measurements of the CO concentrations were made in both the cabin and in the exhaust pipe. Lethal concentrations were measured in the cabin using all three vehicles as the donor car, including the vehicle with the well-functioning catalyst. The model results in most cases gave a good prediction of the CO concentration in the cabin. Four case studies of cars used for suicides were described. In each case measurements of CO were made in both the cabin and the exhaust under different starting conditions, and the mathematical model was tested on these cases. In most cases the model predictions were good.

Reciprocal Associations between Negative Affect, Binge Eating, and Purging in the Natural Environment in Women with Bulimia Nervosa

PubMed Central

Lavender, Jason M.; Utzinger, Linsey M.; Cao, Li; Wonderlich, Stephen A.; Engel, Scott G.; Mitchell, James E.; Crosby, Ross D.

2016-01-01

Although negative affect (NA) has been identified as a common trigger for bulimic behaviors, findings regarding NA following such behaviors have been mixed. This study examined reciprocal associations between NA and bulimic behaviors using real-time, naturalistic data. Participants were 133 women with DSM-IV bulimia nervosa (BN) who completed a two-week ecological momentary assessment (EMA) protocol in which they recorded bulimic behaviors and provided multiple daily ratings of NA. A multilevel autoregressive cross-lagged analysis was conducted to examine concurrent, first-order autoregressive, and prospective associations between NA, binge eating, and purging across the day. Results revealed positive concurrent associations between all variables across all time points, as well as numerous autoregressive associations. For prospective associations, higher NA predicted subsequent bulimic symptoms at multiple time points; conversely, binge eating predicted lower NA at multiple time points, and purging predicted higher NA at one time point. Several autoregressive and prospective associations were also found between binge eating and purging. This study used a novel approach to examine NA in relation to bulimic symptoms, contributing to the existing literature by directly examining the magnitude of the associations, examining differences in the associations across the day, and controlling for other associations in testing each effect in the model. These findings may have relevance for understanding the etiology and/or maintenance of bulimic symptoms, as well as potentially informing psychological interventions for BN. PMID:26692122

Economic growth and CO2 emissions: an investigation with smooth transition autoregressive distributed lag models for the 1800-2014 period in the USA.

PubMed

Bildirici, Melike; Ersin, Özgür Ömer

2018-01-01

The study aims to combine the autoregressive distributed lag (ARDL) cointegration framework with smooth transition autoregressive (STAR)-type nonlinear econometric models for causal inference. Further, the proposed STAR distributed lag (STARDL) models offer new insights in terms of modeling nonlinearity in the long- and short-run relations between analyzed variables. The STARDL method allows modeling and testing nonlinearity in the short-run and long-run parameters or both in the short- and long-run relations. To this aim, the relation between CO 2 emissions and economic growth rates in the USA is investigated for the 1800-2014 period, which is one of the largest data sets available. The proposed hybrid models are the logistic, exponential, and second-order logistic smooth transition autoregressive distributed lag (LSTARDL, ESTARDL, and LSTAR2DL) models combine the STAR framework with nonlinear ARDL-type cointegration to augment the linear ARDL approach with smooth transitional nonlinearity. The proposed models provide a new approach to the relevant econometrics and environmental economics literature. Our results indicated the presence of asymmetric long-run and short-run relations between the analyzed variables that are from the GDP towards CO 2 emissions. By the use of newly proposed STARDL models, the results are in favor of important differences in terms of the response of CO 2 emissions in regimes 1 and 2 for the estimated LSTAR2DL and LSTARDL models.

Multifractality and autoregressive processes of dry spell lengths in Europe: an approach to their complexity and predictability

NASA Astrophysics Data System (ADS)

Lana, X.; Burgueño, A.; Serra, C.; Martínez, M. D.

2017-01-01

Dry spell lengths, DSL, defined as the number of consecutive days with daily rain amounts below a given threshold, may provide relevant information about drought regimes. Taking advantage of a daily pluviometric database covering a great extension of Europe, a detailed analysis of the multifractality of the dry spell regimes is achieved. At the same time, an autoregressive process is applied with the aim of predicting DSL. A set of parameters, namely Hurst exponent, H, estimated from multifractal spectrum, f( α), critical Hölder exponent, α 0, for which f( α) reaches its maximum value, spectral width, W, and spectral asymmetry, B, permits a first clustering of European rain gauges in terms of the complexity of their DSL series. This set of parameters also allows distinguishing between time series describing fine- or smooth-structure of the DSL regime by using the complexity index, CI. Results of previous monofractal analyses also permits establishing comparisons between smooth-structures, relatively low correlation dimensions, notable predictive instability and anti-persistence of DSL for European areas, sometimes submitted to long droughts. Relationships are also found between the CI and the mean absolute deviation, MAD, and the optimum autoregressive order, OAO, of an ARIMA( p, d,0) autoregressive process applied to the DSL series. The detailed analysis of the discrepancies between empiric and predicted DSL underlines the uncertainty over predictability of long DSL, particularly for the Mediterranean region.

A Power-Law Growth and Decay Model with Autocorrelation for Posting Data to Social Networking Services.

PubMed

Fujiyama, Toshifumi; Matsui, Chihiro; Takemura, Akimichi

2016-01-01

We propose a power-law growth and decay model for posting data to social networking services before and after social events. We model the time series structure of deviations from the power-law growth and decay with a conditional Poisson autoregressive (AR) model. Online postings related to social events are described by five parameters in the power-law growth and decay model, each of which characterizes different aspects of interest in the event. We assess the validity of parameter estimates in terms of confidence intervals, and compare various submodels based on likelihoods and information criteria.

Molecular Determinants of the Human α2C-Adrenergic Receptor Temperature-Sensitive Intracellular Traffic

PubMed Central

Pullikuth, Ashok K.; Guidry, Jessie J.

2015-01-01

The human α2C-adrenergic receptor (α2C-AR) is localized intracellularly at physiologic temperature. Decreasing the environmental temperature strongly stimulates the receptor transport to the cell surface. In contrast, rat and mouse α2C-AR plasma membrane levels are less sensitive to decrease in temperature, whereas the opossum α2C-AR cell surface levels are not changed in these conditions. Structural analysis demonstrated that human α2C-AR has a high number of arginine residues in the third intracellular loop and in the C-terminus, organized as putative RXR motifs. Although these motifs do not affect the receptor subcellular localization at 37°C, deletion of the arginine clusters significantly enhanced receptor plasma membrane levels at reduced temperature. We found that this exaggerated transport of the human receptor is mediated by two functional arginine clusters, one in the third intracellular loop and one in the C-terminus. This effect is mediated by interactions with COPI vesicles, but not by 14-3-3 proteins. In rat α2C-AR, the arginine cluster from the third intracellular loop is shifted to the left due to three missing residues. Reinsertion of these residues in the rat α2C-AR restored the same temperature sensitivity as in the human receptor. Proteomic and coimmunoprecipitation experiments identified pontin as a molecule having stronger interactions with human α2C-AR compared with rat α2C-AR. Inhibition of pontin activity enhanced human receptor plasma membrane levels and signaling at 37°C. Our results demonstrate that human α2C-AR has a unique temperature-sensitive traffic pattern within the G protein–coupled receptor class due to interactions with different molecular chaperones, mediated in part by strict spatial localization of specific arginine residues. PMID:25680754

Smooth individual level covariates adjustment in disease mapping.

PubMed

Huque, Md Hamidul; Anderson, Craig; Walton, Richard; Woolford, Samuel; Ryan, Louise

2018-05-01

Spatial models for disease mapping should ideally account for covariates measured both at individual and area levels. The newly available "indiCAR" model fits the popular conditional autoregresssive (CAR) model by accommodating both individual and group level covariates while adjusting for spatial correlation in the disease rates. This algorithm has been shown to be effective but assumes log-linear associations between individual level covariates and outcome. In many studies, the relationship between individual level covariates and the outcome may be non-log-linear, and methods to track such nonlinearity between individual level covariate and outcome in spatial regression modeling are not well developed. In this paper, we propose a new algorithm, smooth-indiCAR, to fit an extension to the popular conditional autoregresssive model that can accommodate both linear and nonlinear individual level covariate effects while adjusting for group level covariates and spatial correlation in the disease rates. In this formulation, the effect of a continuous individual level covariate is accommodated via penalized splines. We describe a two-step estimation procedure to obtain reliable estimates of individual and group level covariate effects where both individual and group level covariate effects are estimated separately. This distributed computing framework enhances its application in the Big Data domain with a large number of individual/group level covariates. We evaluate the performance of smooth-indiCAR through simulation. Our results indicate that the smooth-indiCAR method provides reliable estimates of all regression and random effect parameters. We illustrate our proposed methodology with an analysis of data on neutropenia admissions in New South Wales (NSW), Australia. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Safe distance car-following model including backward-looking and its stability analysis

NASA Astrophysics Data System (ADS)

Yang, Da; Jin, Peter Jing; Pu, Yun; Ran, Bin

2013-03-01

The focus of this paper is the car-following behavior including backward-looking, simply called the bi-directional looking car-following behavior. This study is motivated by the potential changes of the physical properties of traffic flow caused by the fast developing intelligent transportation system (ITS), especially the new connected vehicle technology. Existing studies on this topic focused on general motors (GM) models and optimal velocity (OV) models. The safe distance car-following model, Gipps' model, which is more widely used in practice have not drawn too much attention in the bi-directional looking context. This paper explores the property of the bi-directional looking extension of Gipps' safe distance model. The stability condition of the proposed model is derived using the linear stability theory and is verified using numerical simulations. The impacts of the driver and vehicle characteristics appeared in the proposed model on the traffic flow stability are also investigated. It is found that taking into account the backward-looking effect in car-following has three types of effect on traffic flow: stabilizing, destabilizing and producing non-physical phenomenon. This conclusion is more sophisticated than the study results based on the OV bi-directional looking car-following models. Moreover, the drivers who have the smaller reaction time or the larger additional delay and think the other vehicles have larger maximum decelerations can stabilize traffic flow.

Dismissive and deceptive car dealerships create barriers to electric vehicle adoption at the point of sale

NASA Astrophysics Data System (ADS)

Zarazua de Rubens, Gerardo; Noel, Lance; Sovacool, Benjamin K.

2018-06-01

As most consumers do not have pre-existing knowledge of electric vehicles (EVs), and current market conditions favour petrol and diesel vehicles, car dealership experiences may strongly influence EV purchasing decisions. Here, we show that car dealerships pose a significant barrier at the point of sale due to a perceived lack of business case viability in relation to petrol and diesel vehicles. In 126 shopping experiences at 82 car dealerships across Denmark, Finland, Iceland, Norway and Sweden, we find that dealers were dismissive of EVs, misinformed shoppers on vehicle specifications, omitted EVs from the sales conversation and strongly oriented customers towards petrol and diesel vehicle options. Dealers' technological orientation, willingness to sell and displayed knowledge of EVs were the main contributors to likely purchase intentions. These findings combined with expert interviews suggest that government and industry signalling affect sales strategies and purchasing trends. Policy and business strategies that address barriers at the point of sale are needed to accelerate EV adoption.

Effects of wear and service conditions on residual stresses in commuter car wheels

DOT National Transportation Integrated Search

2004-09-01

This paper illustrates application of the shakedown residual stress estimation technique to : assess the effects of service conditions on wheel residual stresses. The examples described provide the : technical details on how the technique is practica...

How does a modal shift from short car trips to cycling affect road safety?

PubMed

Schepers, J P; Heinen, E

2013-01-01

Governments aim to promote a shift from car to bicycle, but concerns about road safety seem to represent an important argument against this encouragement. This study examines the road safety impact of a modal shift from short car trips to cycling in Dutch municipalities. The road safety effect is estimated using Accident Prediction Models (APMs) that account for the non-linearity of risk. APMs are developed utilizing Negative Binomial regression. This study is the first to develop APMs using crash and mobility data from municipalities, and utilizing these models to estimate the effects of changing modal splits of current car and bicycle use to modal splits that actually exist in these municipalities. The results suggest that, under conditions such as in Dutch municipalities, transferring short trips made by cars to bicycles does not change the number of fatalities, but increases the number of serious road injuries. The neutral effect on fatalities, despite the high fatality risk for cyclists, can be explained by there being fewer cars on the road to pose a risk to others, the shorter length of bicycle trips compared to the car trips they replace, and the "safety in numbers" phenomenon. The rise in the number of serious road injuries is due wholly to the high number of cycling crashes with no other vehicle involved. The effect of a modal shift is dependent on the age of the population in which the shift is concentrated, and can be influenced by measures affecting cyclists' injury risk. Copyright © 2012 Elsevier Ltd. All rights reserved.

Impact of mobile phone use on car-following behaviour of young drivers.

PubMed

Saifuzzaman, Mohammad; Haque, Md Mazharul; Zheng, Zuduo; Washington, Simon

2015-09-01

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18-26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33s in time headway when a driver is engaged in hands-free phone conversation and a 0.75s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Pedestrians' perception and response towards vehicles during road-crossing at nighttime.

PubMed

Balasubramanian, Venkatesh; Bhardwaj, Rahul

2018-01-01

Pedestrian being involved in road traffic accidents (RTA) is about 22% of all road traffic related deaths. In this study, we have estimated the pedestrian's response towards an approaching vehicle and the time taken to correctly recognize it while they crossed the road in dim-light nighttime conditions. This is also extendable to cycles and other low powered vehicles. Thirty volunteers participated in this study. A collection of six videos, which comprised of different vehicle scenarios were shown to each of the participants. It was observed that correct identification and time to recognize the vehicle was fastest when light emitting diode (LED) strip was fixed between headlights of a four-wheeler. Average time to recognize a low beam car and a high beam car with an LED strip was 7.62±2.39s and 11.23±2.94s respectively, whereas correct identification rates of the said low beam and high beam cars with LED strips were 93.33% and 86.67% respectively. Earlier when no LED was used, time to recognize low beam car and high beam car without LED strip were 20.55±3.50s and 25.57±4.14s respectively whereas correct identification of low beam car without LED strip and high beam car without LED strip were 90.00% and 56.67% respectively. Pedestrians are therefore less confused and can take right decision while crossing the road - particularly in a poor lighting environment - when there is a demarcating illumination between headlights of vehicle. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neutrophil-derived JAML Inhibits Repair of Intestinal Epithelial Injury During Acute Inflammation

PubMed Central

Weber, Dominique A.; Sumagin, Ronen; McCall, Ingrid C.; Leoni, Giovanna; Neumann, Philipp A.; Andargachew, Rakieb; Brazil, Jennifer C.; Medina-Contreras, Oscar; Denning, Timothy L.; Nusrat, Asma; Parkos, Charles A.

2014-01-01

Neutrophil transepithelial migration (TEM) during acute inflammation is associated with mucosal injury. Using models of acute mucosal injury in-vitro and in-vivo, we describe a new mechanism by which neutrophils infiltrating the intestinal mucosa disrupt epithelial homeostasis. We report that junctional adhesion molecule-like protein (JAML) is cleaved from neutrophil surface by zinc-metalloproteases during TEM. Neutrophil-derived soluble JAML bound to the epithelial tight junction protein coxsackie-adenovirus receptor (CAR) resulting in compromised barrier and inhibition of wound repair, through decreased epithelial proliferation. The deleterious effects of JAML on barrier and wound repair were reversed with an anti-JAML mAb that inhibits JAML-CAR binding. Thus, JAML released from transmigrating neutrophils across inflamed epithelia can promote recruitment of leukocytes and aid in clearance of invading microorganisms. However, sustained release of JAML under pathologic conditions associated with persistence of large numbers of infiltrated neutrophil would compromise intestinal barrier and inhibit mucosal healing. Targeting JAML-CAR interactions may thus improve mucosal healing responses under conditions of dysregulated neutrophil recruitment. PMID:24621992

Fuel consumption optimization for smart hybrid electric vehicle during a car-following process

NASA Astrophysics Data System (ADS)

Li, Liang; Wang, Xiangyu; Song, Jian

2017-03-01

Hybrid electric vehicles (HEVs) provide large potential to save energy and reduce emission, and smart vehicles bring out great convenience and safety for drivers. By combining these two technologies, vehicles may achieve excellent performances in terms of dynamic, economy, environmental friendliness, safety, and comfort. Hence, a smart hybrid electric vehicle (s-HEV) is selected as a platform in this paper to study a car-following process with optimizing the fuel consumption. The whole process is a multi-objective optimal problem, whose optimal solution is not just adding an energy management strategy (EMS) to an adaptive cruise control (ACC), but a deep fusion of these two methods. The problem has more restricted conditions, optimal objectives, and system states, which may result in larger computing burden. Therefore, a novel fuel consumption optimization algorithm based on model predictive control (MPC) is proposed and some search skills are adopted in receding horizon optimization to reduce computing burden. Simulations are carried out and the results indicate that the fuel consumption of proposed method is lower than that of the ACC+EMS method on the condition of ensuring car-following performances.

Geometry and physical conditions in the stellar wind of AG Carinae

NASA Technical Reports Server (NTRS)

Leitherer, Claus; Allen, Richard; Altner, Bruce; Damineli, Augusto; Drissen, Laurent; Idiart, Thais; Lupie, Olivia; Nota, Antonella; Robert, Carmelle; Schmutz, Werner

1994-01-01

AG Carinae is one of the prototypes of the class of Luminous Blue Variables (LBVs). Since 1990 the star has continuously brightened in its visual continuum. We report on a multi-instrument and -wavelength observing campaign to monitor the current activity phase of AG Car. Ground-based photometry, polarimetry, spectroscopy, and space-ultraviolet spectroscopy and spectropolarimetry have been obtained. From the variability of the polarization at ultraviolet and optical wavelengths we detect significant intrinsic polarization. P(sub int) greater than or equal to 0.5% is a large value for a hot, luminous star, suggesting departure from spherical symmetry in the wind of AG Car. The intrinsic polarization is variable on a timescale of 2 months or less. The measured ultraviolet polarization (intrinsic + interstellar) dropped to 0.5% in 1992 May and returned to 1% in 1992 July. The results are interpreted in terms of a variable outflow with a density enhancement in the equatorial plane. A similar model was suggested for the related object R127 in the Large Magellanic Cloud (LMC). This geometry is reminiscent of the large-scale morphology of the gas nebula and dust 'jet' surrounding AG Car. It is therefore likely that physical conditions close to the stellar surface are responsible for the geometry of the spatially resolved circumstellar material around AG Car. Despite the drastic change of the photospheric conditions, the mass-loss rate did not increase. We find no evidence for a positive correlation between wind density and stellar radius. This makes models that explain the radius increase by opacity effects in the outflow unlikely. The mechanism responsible for the temperature and radius variations is still unknown but most likely has its origin in subphotospheric regions.

Volatile nanoparticle formation and growth within a diluting diesel car exhaust.

PubMed

Uhrner, Ulrich; Zallinger, Michael; von Löwis, Sibylle; Vehkamäki, Hanna; Wehner, Birgit; Stratmann, Frank; Wiedensohler, Alfred

2011-04-01

A major source of particle number emissions is road traffic. However, scientific knowledge concerning secondary particle formation and growth of ultrafine particles within vehicle exhaust plumes is still very limited. Volatile nanoparticle formation and subsequent growth conditions were analyzed here to gain a better understanding of "real-world" dilution conditions. Coupled computational fluid dynamics and aerosol microphysics models together with measured size distributions within the exhaust plume of a diesel car were used. The impact of soot particles on nucleation, acting as a condensational sink, and the possible role of low-volatile organic components in growth were assessed. A prescribed reduction of soot particle emissions by 2 orders of magnitude (to capture the effect of a diesel particle filter) resulted in concentrations of nucleation-mode particles within the exhaust plume that were approximately 1 order of magnitude larger. Simulations for simplified sulfuric acid-water vapor gas-oil containing nucleation-mode particles show that the largest particle growth is located in a recirculation zone in the wake of the car. Growth of particles within the vehicle exhaust plume up to detectable size depends crucially on the relationship between the mass rate of gaseous precursor emissions and rapid dilution. Chassis dynamometer measurements indicate that emissions of possible hydrocarbon precursors are significantly enhanced under high engine load conditions and high engine speed. On the basis of results obtained for a diesel passenger car, the contributions from light diesel vehicles to the observed abundance of measured nucleation-mode particles near busy roads might be attributable to the impact of two different time scales: (1) a short one within the plume, marked by sufficient precursor emissions and rapid dilution; and (2) a second and comparatively long time scale resulting from the mix of different precursor sources and the impact of atmospheric chemistry.

RNA-Seq reveals common and unique PXR- and CAR-target gene signatures in the mouse liver transcriptome.

PubMed

Cui, Julia Yue; Klaassen, Curtis D

2016-09-01

The pregnane X receptor (PXR) and constitutive androstane receptor (CAR) are well-known xenobiotic-sensing nuclear receptors with overlapping functions. However, there lacks a quantitative characterization to distinguish between the PXR and CAR target genes and signaling pathways in the liver. The present study performed a transcriptomic comparison of the PXR- and CAR-targets using RNA-Seq in livers of adult wild-type mice that were treated with the prototypical PXR ligand PCN (200mg/kg, i.p. once daily for 4days in corn oil) or the prototypical CAR ligand TCPOBOP (3mg/kg, i.p., once daily for 4days in corn oil). At the given doses, TCPOBOP differentially regulated many more genes (2125) than PCN (212), and 147 of the same genes were differentially regulated by both chemicals. As expected, the top pathways differentially regulated by both PCN and TCPOBOP were involved in xenobiotic metabolism, and they also up-regulated genes involved in retinoid metabolism, but down-regulated genes involved in inflammation and iron homeostasis. Regarding unique pathways, PXR activation appeared to overlap with the aryl hydrocarbon receptor signaling, whereas CAR activation appeared to overlap with the farnesoid X receptor signaling, acute-phase response, and mitochondrial dysfunction. The mRNAs of differentially regulated drug-processing genes (DPGs) partitioned into three patterns, namely TCPOBOP-induced, PCN-induced, as well as TCPOBOP-suppressed gene clusters. The cumulative mRNAs of the differentially regulated DPGs, phase-I and -II enzymes, as well as efflux transporters were all up-regulated by both PCN and TCPOBOPOP, whereas the cumulative mRNAs of the uptake transporters were down-regulated only by TCPOBOP. The absolute mRNA abundance in control and receptor-activated conditions was examined in each DPG category to predict the contribution of specific DPG genes in the PXR/CAR-mediated pharmacokinetic responses. The preferable differential regulation by TCPOBOP in the entire hepatic transcriptome correlated with a marked change in the expression of many DNA and histone epigenetic modifiers. In conclusion, the present study has revealed known and novel, as well as common and unique targets of PXR and CAR in mouse liver following pharmacological activation using their prototypical ligands. Results from this study will further support the role of these receptors in regulating the homeostasis of xenobiotic and intermediary metabolism in the liver, and aid in distinguishing between PXR and CAR signaling at various physiological and pathophysiological conditions. This article is part of a Special Issue entitled: Xenobiotic nuclear receptors: New Tricks for An Old Dog, edited by Dr. Wen Xie. Copyright © 2016 Elsevier B.V. All rights reserved.

Failure monitoring in dynamic systems: Model construction without fault training data

NASA Technical Reports Server (NTRS)

Smyth, P.; Mellstrom, J.

1993-01-01

Advances in the use of autoregressive models, pattern recognition methods, and hidden Markov models for on-line health monitoring of dynamic systems (such as DSN antennas) have recently been reported. However, the algorithms described in previous work have the significant drawback that data acquired under fault conditions are assumed to be available in order to train the model used for monitoring the system under observation. This article reports that this assumption can be relaxed and that hidden Markov monitoring models can be constructed using only data acquired under normal conditions and prior knowledge of the system characteristics being measured. The method is described and evaluated on data from the DSS 13 34-m beam wave guide antenna. The primary conclusion from the experimental results is that the method is indeed practical and holds considerable promise for application at the 70-m antenna sites where acquisition of fault data under controlled conditions is not realistic.

78 FR 32617 - Proposed Modification of Significant New Uses of 1-Propene, 2,3,3,3-tetrafluoro-

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-31

... vehicle air conditioning systems in new passenger cars and vehicles as reported in the original PMN is not... attempting to recharge air conditioning systems in vehicles originally charged with the refrigerant... substance by consumers to recharge air conditioning systems in vehicles originally charged with the...

Determinants of Motion Sickness in Tilting Trains: Coriolis/Cross-Coupling Stimuli and Tilt Delay

PubMed Central

Bertolini, Giovanni; Durmaz, Meek Angela; Ferrari, Kim; Küffer, Alexander; Lambert, Charlotte; Straumann, Dominik

2017-01-01

Faster trains require tilting of the cars to counterbalance the centrifugal forces during curves. Motion sensitive passengers, however, complain of discomfort and overt motion sickness. A recent study comparing different control systems in a tilting train, suggested that the delay of car tilts relative to the curve of the track contributes to motion sickness. Other aspects of the motion stimuli, like the lateral accelerations and the car jitters, differed between the tested conditions and prevented a final conclusion on the role of tilt delay. Nineteen subjects were tested on a motorized 3D turntable that simulated the roll tilts during yaw rotations experienced on a tilting train, isolating them from other motion components. Each session was composed of two consecutive series of 12 ideal curves that were defined on the bases of recordings during an actual train ride. The simulated car tilts started either at the beginning of the curve acceleration phase (no-delay condition) or with 3 s of delay (delay condition). Motion sickness was self-assessed by each subject at the end of each series using an analog motion sickness scale. All subjects were tested in both conditions. Significant increases of motion sickness occurred after the first sequence of 12 curves in the delay condition, but not in the no-delay condition. This increase correlated with the sensitivity of motion sickness, which was self-assessed by each subject before the experiment. The second sequence of curve did not lead to a significant further increase of motion sickness in any condition. Our results demonstrate that, even if the speed and amplitude are as low as those experienced on tilting trains, a series of roll tilts with a delay relative to the horizontal rotations, isolated from other motion stimuli occurring during a travel, generate Coriolis/cross-coupling stimulations sufficient to rapidly induce motion sickness in sensitive individuals. The strength and the rapid onset of the motion sickness reported confirm that, even if the angular velocity involved are low, the Coriolis/cross-coupling resulting from the delay is a major factor in causing sickness that can be resolved by improving the tilt timing relative to the horizontal rotation originating from the curve. PMID:28555125

AR(p) -based detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Alvarez-Ramirez, J.; Rodriguez, E.

2018-07-01

Autoregressive models are commonly used for modeling time-series from nature, economics and finance. This work explored simple autoregressive AR(p) models to remove long-term trends in detrended fluctuation analysis (DFA). Crude oil prices and bitcoin exchange rate were considered, with the former corresponding to a mature market and the latter to an emergent market. Results showed that AR(p) -based DFA performs similar to traditional DFA. However, the former DFA provides information on stability of long-term trends, which is valuable for understanding and quantifying the dynamics of complex time series from financial systems.

Standoff detection of trace amounts of solids by nonlinear Raman spectroscopy using shaped femtosecond pulses

NASA Astrophysics Data System (ADS)

Katz, O.; Natan, A.; Silberberg, Y.; Rosenwaks, S.

2008-04-01

We demonstrate a single-beam, standoff (>10m) detection and identification of various materials including minute amounts of explosives under ambient light conditions. This is obtained by multiplex coherent anti-Stokes Raman scattering spectroscopy (CARS) using a single femtosecond phase-shaped laser pulse. We exploit the strong nonresonant background for amplification of the backscattered resonant CARS signals by employing a homodyne detection scheme. The simple and highly sensitive spectroscopic technique has a potential for hazardous materials standoff detection applications.

The influence of the non-motor vehicles for the car-following model considering traffic jerk

NASA Astrophysics Data System (ADS)

Liu, Yi; Cheng, Rong-jun; Lei, Li; Ge, Hong-xia

2016-12-01

The influence of the non-motor vehicles and traffic jerk is considered for the car-following model in this paper. The control method is used to analyze the stability of the model. A control signal which is the velocity difference between the target vehicle and the following vehicle is added into the model and the stability condition is obtained. Numerical simulation is used to display the results for the stability of the model with and without control signal.

Crosswind stability of FSAE race car considering the location of the pressure center

NASA Astrophysics Data System (ADS)

Zhao, Lijun; He, Huimin; Wang, Jianfeng; Li, Yaou; Yang, Na; Liu, Yiqun

2017-09-01

An 8-DOF vehicle dynamic model of FSAE race car was established, including the lateral motion, pitch motion, roll motion, yaw motion and four tires rotation. The model of aerodynamic lateral force and pressure center model were set up based on the vehicle speed and crosswind parameters. The simulation model was built by Simulink, to analyse the crosswind stability for straight-line condition. Results showed that crosswind influences the yawing velocity and sideslip angle seriously.

Disease Mapping of Zero-excessive Mesothelioma Data in Flanders

PubMed Central

Neyens, Thomas; Lawson, Andrew B.; Kirby, Russell S.; Nuyts, Valerie; Watjou, Kevin; Aregay, Mehreteab; Carroll, Rachel; Nawrot, Tim S.; Faes, Christel

2016-01-01

Purpose To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion. Methods The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero-inflation and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature. Results The results indicate that hurdle models with a random effects term accounting for extra-variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra-variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra-variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary. Conclusions Models taking into account zero-inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this. PMID:27908590

Disease mapping of zero-excessive mesothelioma data in Flanders.

PubMed

Neyens, Thomas; Lawson, Andrew B; Kirby, Russell S; Nuyts, Valerie; Watjou, Kevin; Aregay, Mehreteab; Carroll, Rachel; Nawrot, Tim S; Faes, Christel

2017-01-01

To investigate the distribution of mesothelioma in Flanders using Bayesian disease mapping models that account for both an excess of zeros and overdispersion. The numbers of newly diagnosed mesothelioma cases within all Flemish municipalities between 1999 and 2008 were obtained from the Belgian Cancer Registry. To deal with overdispersion, zero inflation, and geographical association, the hurdle combined model was proposed, which has three components: a Bernoulli zero-inflation mixture component to account for excess zeros, a gamma random effect to adjust for overdispersion, and a normal conditional autoregressive random effect to attribute spatial association. This model was compared with other existing methods in literature. The results indicate that hurdle models with a random effects term accounting for extra variance in the Bernoulli zero-inflation component fit the data better than hurdle models that do not take overdispersion in the occurrence of zeros into account. Furthermore, traditional models that do not take into account excessive zeros but contain at least one random effects term that models extra variance in the counts have better fits compared to their hurdle counterparts. In other words, the extra variability, due to an excess of zeros, can be accommodated by spatially structured and/or unstructured random effects in a Poisson model such that the hurdle mixture model is not necessary. Models taking into account zero inflation do not always provide better fits to data with excessive zeros than less complex models. In this study, a simple conditional autoregressive model identified a cluster in mesothelioma cases near a former asbestos processing plant (Kapelle-op-den-Bos). This observation is likely linked with historical local asbestos exposures. Future research will clarify this. Copyright © 2016 Elsevier Inc. All rights reserved.

Hierarchical Bayesian spatial models for multispecies conservation planning and monitoring.

PubMed

Carroll, Carlos; Johnson, Devin S; Dunk, Jeffrey R; Zielinski, William J

2010-12-01

Biologists who develop and apply habitat models are often familiar with the statistical challenges posed by their data's spatial structure but are unsure of whether the use of complex spatial models will increase the utility of model results in planning. We compared the relative performance of nonspatial and hierarchical Bayesian spatial models for three vertebrate and invertebrate taxa of conservation concern (Church's sideband snails [Monadenia churchi], red tree voles [Arborimus longicaudus], and Pacific fishers [Martes pennanti pacifica]) that provide examples of a range of distributional extents and dispersal abilities. We used presence-absence data derived from regional monitoring programs to develop models with both landscape and site-level environmental covariates. We used Markov chain Monte Carlo algorithms and a conditional autoregressive or intrinsic conditional autoregressive model framework to fit spatial models. The fit of Bayesian spatial models was between 35 and 55% better than the fit of nonspatial analogue models. Bayesian spatial models outperformed analogous models developed with maximum entropy (Maxent) methods. Although the best spatial and nonspatial models included similar environmental variables, spatial models provided estimates of residual spatial effects that suggested how ecological processes might structure distribution patterns. Spatial models built from presence-absence data improved fit most for localized endemic species with ranges constrained by poorly known biogeographic factors and for widely distributed species suspected to be strongly affected by unmeasured environmental variables or population processes. By treating spatial effects as a variable of interest rather than a nuisance, hierarchical Bayesian spatial models, especially when they are based on a common broad-scale spatial lattice (here the national Forest Inventory and Analysis grid of 24 km(2) hexagons), can increase the relevance of habitat models to multispecies conservation planning. Journal compilation © 2010 Society for Conservation Biology. No claim to original US government works.

Electromobility concept for racing cars based on lithium-ion batteries and supercapacitors

NASA Astrophysics Data System (ADS)

Frenzel, B.; Kurzweil, P.; Rönnebeck, H.

For the construction of an all-electric race car, all aspects from engineering design over cost estimation up to the road capability are illuminated. From the most promising batteries for electric vehicle propulsion, the state-of-the art and commercial availability of lithium-ion secondary batteries is critically discussed with respect to cycle-life and unfavorable charge-discharge conditions. A market-overview is given with respect to a small electric car. Different combinations of electric motors and a recuperation system have been investigated. Weight aspects of central drive systems were considered and compared with decentralized wheel-hub drives. As a result, a centralized high-speed drive train based on a permanent-magnet synchronous engine with high-energy magnets seems to be superior due to limited space for assembly.

Experimental investigation of disc brakes for formula Bharat

NASA Astrophysics Data System (ADS)

Misra, Sheelam; Chandra, Sharad; Bagwadi, Ashutosh

2018-05-01

we have made the brake assembly for Formula Student India in which we gathered the information about the force distribution in Master Cylinder, Assembly of Master Cylinder, Disc Brakes, Pedal Assembly has been gathered from various sources in which we come to know about that Vertical Master Cylinder is much better than the Horizontal Master Cylinder because of which we are able to reduce the weight of the Formula Student Car which ultimately affects the performance of the car. In other words, we have considered the various environmental conditions in which this braking system. The dimensions for the Disc Brake rotor is considered according to the space constraints and the material is finalized according to the hunch of calculations and the environmental conditions.

Reciprocal associations between negative affect, binge eating, and purging in the natural environment in women with bulimia nervosa.

PubMed

Lavender, Jason M; Utzinger, Linsey M; Cao, Li; Wonderlich, Stephen A; Engel, Scott G; Mitchell, James E; Crosby, Ross D

2016-04-01

Although negative affect (NA) has been identified as a common trigger for bulimic behaviors, findings regarding NA following such behaviors have been mixed. This study examined reciprocal associations between NA and bulimic behaviors using real-time, naturalistic data. Participants were 133 women with bulimia nervosa (BN) according to the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders who completed a 2-week ecological momentary assessment protocol in which they recorded bulimic behaviors and provided multiple daily ratings of NA. A multilevel autoregressive cross-lagged analysis was conducted to examine concurrent, first-order autoregressive, and prospective associations between NA, binge eating, and purging across the day. Results revealed positive concurrent associations between all variables across all time points, as well as numerous autoregressive associations. For prospective associations, higher NA predicted subsequent bulimic symptoms at multiple time points; conversely, binge eating predicted lower NA at multiple time points, and purging predicted higher NA at 1 time point. Several autoregressive and prospective associations were also found between binge eating and purging. This study used a novel approach to examine NA in relation to bulimic symptoms, contributing to the existing literature by directly examining the magnitude of the associations, examining differences in the associations across the day, and controlling for other associations in testing each effect in the model. These findings may have relevance for understanding the etiology and/or maintenance of bulimic symptoms, as well as potentially informing psychological interventions for BN. (c) 2016 APA, all rights reserved).

Application of a new hybrid model with seasonal auto-regressive integrated moving average (ARIMA) and nonlinear auto-regressive neural network (NARNN) in forecasting incidence cases of HFMD in Shenzhen, China.

PubMed

Yu, Lijing; Zhou, Lingling; Tan, Li; Jiang, Hongbo; Wang, Ying; Wei, Sheng; Nie, Shaofa

2014-01-01

Outbreaks of hand-foot-mouth disease (HFMD) have been reported for many times in Asia during the last decades. This emerging disease has drawn worldwide attention and vigilance. Nowadays, the prevention and control of HFMD has become an imperative issue in China. Early detection and response will be helpful before it happening, using modern information technology during the epidemic. In this paper, a hybrid model combining seasonal auto-regressive integrated moving average (ARIMA) model and nonlinear auto-regressive neural network (NARNN) is proposed to predict the expected incidence cases from December 2012 to May 2013, using the retrospective observations obtained from China Information System for Disease Control and Prevention from January 2008 to November 2012. The best-fitted hybrid model was combined with seasonal ARIMA [Formula: see text] and NARNN with 15 hidden units and 5 delays. The hybrid model makes the good forecasting performance and estimates the expected incidence cases from December 2012 to May 2013, which are respectively -965.03, -1879.58, 4138.26, 1858.17, 4061.86 and 6163.16 with an obviously increasing trend. The model proposed in this paper can predict the incidence trend of HFMD effectively, which could be helpful to policy makers. The usefulness of expected cases of HFMD perform not only in detecting outbreaks or providing probability statements, but also in providing decision makers with a probable trend of the variability of future observations that contains both historical and recent information.

Chemical composition and source of fine and nanoparticles from recent direct injection gasoline passenger cars: Effects of fuel and ambient temperature

NASA Astrophysics Data System (ADS)

Fushimi, Akihiro; Kondo, Yoshinori; Kobayashi, Shinji; Fujitani, Yuji; Saitoh, Katsumi; Takami, Akinori; Tanabe, Kiyoshi

2016-01-01

Particle number, mass, and chemical compositions (i.e., elemental carbon (EC), organic carbon (OC), elements, ions, and organic species) of fine particles emitted from four of the recent direct injection spark ignition (DISI) gasoline passenger cars and a port fuel injection (PFI) gasoline passenger car were measured under Japanese official transient mode (JC08 mode). Total carbon (TC = EC + OC) dominated the particulate mass (90% on average). EC dominated the TC for both hot and cold start conditions. The EC/TC ratios were 0.72 for PFI and 0.88-1.0 (average = 0.92) for DISI vehicles. A size-resolved chemical analysis of a DISI car revealed that the major organic components were the C20-C28 hydrocarbons for both the accumulation-mode particles and nanoparticles. Contribution of engine oil was estimated to be 10-30% for organics and the sum of the measured elements. The remaining major fraction likely originated from gasoline fuel. Therefore, it is suggested that soot (EC) also mainly originated from the gasoline. In experiments using four fuels at three ambient temperatures, the emission factors of particulate mass were consistently higher with regular gasoline than with premium gasoline. This result suggest that the high content of less-volatile compounds in fuel increase particulate emissions. These results suggest that focusing on reducing fuel-derived EC in the production process of new cars would effectively reduce particulate emission from DISI cars.

Survey report: control technology for autobody repair and painting shops at Church Brother's Collision Repair, Greenwood, Indiana, October 10-11, 1991

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

Heitbrink, W.A.; Cooper, T.C.; Edmonds, M.A.

1992-03-01

A study was made to evaluate and document the effectiveness of a metal inert gas (MIG) welder with built in ventilation to control potentially hazardous conditions at Church Brother's Collision Repair (SIC-7531), Greenwood, Indiana. Air contaminant exposures were measured during a 1 hour repair job while using a ventilated MIG welder and while using a conventional MIG welder. The ventilation system of the MIG did reduce worker exposure to welding fumes. However, the sampling was done on a single repair job, thus limiting the conclusions which can be drawn from the study. Some welding fumes were not captured by themore » ventilated welder, suggesting that the MIG with ventilation provided incomplete control of the generated fumes. In some cases the metal on the other side of the welding area became sufficiently hot to generate its own fumes. The car body itself appears to block the capture of these fumes by the ventilated MIG welder. When welding inside the car without the ventilated welder, the fumes generated were more concentrated than those generated by welding outside of the car under similar conditions. There is a decreased dilution of the fumes inside the car due to a lack of air movement. The authors conclude that while the control technique appeared to lessen exposure to welding fumes, additional investigation is needed to verify the data.« less

Looming auditory collision warnings for driving.

PubMed

Gray, Rob

2011-02-01

A driving simulator was used to compare the effectiveness of increasing intensity (looming) auditory warning signals with other types of auditory warnings. Auditory warnings have been shown to speed driver reaction time in rear-end collision situations; however, it is not clear which type of signal is the most effective. Although verbal and symbolic (e.g., a car horn) warnings have faster response times than abstract warnings, they often lead to more response errors. Participants (N=20) experienced four nonlooming auditory warnings (constant intensity, pulsed, ramped, and car horn), three looming auditory warnings ("veridical," "early," and "late"), and a no-warning condition. In 80% of the trials, warnings were activated when a critical response was required, and in 20% of the trials, the warnings were false alarms. For the early (late) looming warnings, the rate of change of intensity signaled a time to collision (TTC) that was shorter (longer) than the actual TTC. Veridical looming and car horn warnings had significantly faster brake reaction times (BRT) compared with the other nonlooming warnings (by 80 to 160 ms). However, the number of braking responses in false alarm conditions was significantly greater for the car horn. BRT increased significantly and systematically as the TTC signaled by the looming warning was changed from early to veridical to late. Looming auditory warnings produce the best combination of response speed and accuracy. The results indicate that looming auditory warnings can be used to effectively warn a driver about an impending collision.

Regulation of mouse lung development by the extracellular calcium-sensing receptor, CaR

PubMed Central

Finney, Brenda A; del Moral, Pierre M; Wilkinson, William J; Cayzac, Sebastien; Cole, Martin; Warburton, David; Kemp, Paul J; Riccardi, Daniela

2008-01-01

Postnatal lung function is critically dependent upon optimal embryonic lung development. As the free ionized plasma calcium concentration ([Ca2+]o) of the fetus is higher than that of the adult, the process of lung development occurs in a hypercalcaemic environment. In the adult, [Ca2+]o is monitored by the G-protein coupled, extracellular calcium-sensing receptor (CaR), but neither its ontogeny nor its potential role in lung development are known. Here, we demonstrate that CaR is expressed in the mouse lung epithelium, and that its expression is developmentally regulated, with a peak of expression at embryonic day 12.5 (E12.5) and a subsequent decrease by E18, after which the receptor is absent. Experiments carried out using the lung explant culture model in vitro show that lung branching morphogenesis is sensitive to [Ca2+]o, being maximal at physiological adult [Ca2+]o (i.e. 1.0–1.3 mm) and lowest at the higher, fetal (i.e. 1.7 mm) [Ca2+]o. Administration of the specific CaR positive allosteric modulator, the calcimimetic R-568, mimics the suppressive effects of high [Ca2+]o on branching morphogenesis while both phospholipase C and PI3 kinase inhibition reverse these effects. CaR activation suppresses cell proliferation while it enhances intracellular calcium signalling, lung distension and fluid secretion. Conditions which are restrictive either to branching or to secretion can be rescued by manipulating [Ca2+]o in the culture medium. In conclusion, fetal Cao2+, acting through a developmentally regulated CaR, is an important extrinsic factor that modulates the intrinsic lung developmental programme. Our observations support a novel role for the CaR in preventing hyperplastic lung disease in utero. PMID:18955379

Unstimulated cortisol secretory activity in everyday life and its relationship with fatigue and chronic fatigue syndrome: a systematic review and subset meta-analysis.

PubMed

Powell, Daniel J H; Liossi, Christina; Moss-Morris, Rona; Schlotz, Wolff

2013-11-01

The hypothalamic-pituitary-adrenal (HPA) axis is a psychoneuroendocrine regulator of the stress response and immune system, and dysfunctions have been associated with outcomes in several physical health conditions. Its end product, cortisol, is relevant to fatigue due to its role in energy metabolism. The systematic review examined the relationship between different markers of unstimulated salivary cortisol activity in everyday life in chronic fatigue syndrome (CFS) and fatigue assessed in other clinical and general populations. Search terms for the review related to salivary cortisol assessments, everyday life contexts, and fatigue. All eligible studies (n=19) were reviewed narratively in terms of associations between fatigue and assessed cortisol markers, including the cortisol awakening response (CAR), circadian profile (CP) output, and diurnal cortisol slope (DCS). Subset meta-analyses were conducted of case-control CFS studies examining group differences in three cortisol outcomes: CAR output; CAR increase; and CP output. Meta-analyses revealed an attenuation of the CAR increase within CFS compared to controls (d=-.34) but no statistically significant differences between groups for other markers. In the narrative review, total cortisol output (CAR or CP) was rarely associated with fatigue in any population; CAR increase and DCS were most relevant. Outcomes reflecting within-day change in cortisol levels (CAR increase; DCS) may be the most relevant to fatigue experience, and future research in this area should report at least one such marker. Results should be considered with caution due to heterogeneity in one meta-analysis and the small number of studies. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Landscape pattern and car use: Linking household data with satellite imagery

NASA Astrophysics Data System (ADS)

Keller, R.; Vance, C.

2013-12-01

Landscape pattern has long been hypothesized to influence automobile dependency. Because choices about land development tend to have long-lasting impacts that span over decades, understanding the magnitude of this influence is critical to the design of policies to reduce emissions and other negative externalities associated with car use. Combining household survey data from Germany with satellite imagery and other geo-referenced data sources, we undertake an econometric analysis of the relation between landscape pattern and automobile dependency. Specifically, we employ a two-part model to investigate two dimensions of car use, the discrete decision to own a car and, conditional upon ownership, the continuous decision of how far to drive. Results indicate that landscape pattern, as captured by measures of both land cover (e.g. the extent of open space and landscape diversity) and land use (e.g. the density of regional businesses) are important predictors of car ownership and use. Other policy-relevant variables, such as fuel prices and public transit infrastructure, are also identified as correlates. Based on the magnitude of our estimates, we conclude that carefully considered land development and zoning measures - ones that encourage dense development, diverse land cover and mixed land use - can have beneficial impacts in reducing car dependency that extend far into the future. Key terms: Landscape pattern, Satellite imagery, Germany, Two-part model Figure 1. Distribution of Elasticities of Landscape and Social Effects on German Household Weekly Car Use Results from Two Part Model N = 13,089 (probit) N = 10,987 (OLS)Robust standard errors in parentheses***, **, and *, denotes significance at the 0.01, 0.05, and 0.1 levels

Access to recreational physical activities by car and bus: an assessment of socio-spatial inequalities in mainland Scotland.

PubMed

Ferguson, Neil S; Lamb, Karen E; Wang, Yang; Ogilvie, David; Ellaway, Anne

2013-01-01

Obesity and other chronic conditions linked with low levels of physical activity (PA) are associated with deprivation. One reason for this could be that it is more difficult for low-income groups to access recreational PA facilities such as swimming pools and sports centres than high-income groups. In this paper, we explore the distribution of access to PA facilities by car and bus across mainland Scotland by income deprivation at datazone level. GIS car and bus networks were created to determine the number of PA facilities accessible within travel times of 10, 20 and 30 minutes. Multilevel negative binomial regression models were then used to investigate the distribution of the number of accessible facilities, adjusting for datazone population size and local authority. Access to PA facilities by car was significantly (p<0.01) higher for the most affluent quintile of area-based income deprivation than for most other quintiles in small towns and all other quintiles in rural areas. Accessibility by bus was significantly lower for the most affluent quintile than for other quintiles in urban areas and small towns, but not in rural areas. Overall, we found that the most disadvantaged groups were those without access to a car and living in the most affluent areas or in rural areas.

Hybrid Engine Powered City Car: Fuzzy Controlled Approach

NASA Astrophysics Data System (ADS)

Rahman, Ataur; Mohiuddin, AKM; Hawlader, MNA; Ihsan, Sany

2017-03-01

This study describes a fuzzy controlled hybrid engine powered car. The car is powered by the lithium ion battery capacity of 1000 Wh is charged by the 50 cc hybrid engine and power regenerative mode. The engine is operated with lean mixture at 3000 rpm to charge the battery. The regenerative mode that connects with the engine generates electrical power of 500-600 W for the deceleration of car from 90 km/h to 20 km/h. The regenerated electrical power has been used to power the air-conditioning system and to meet the other electrical power. The battery power only used to propel the car. The regenerative power also found charging the battery for longer operation about 40 minutes and more. The design flexibility of this vehicle starts with whole-vehicle integration based on radical light weighting, drag reduction, and accessory efficiency. The energy efficient hybrid engine cut carbon dioxide (CO2) and nitrogen oxides (N2O) emission about 70-80% as the loads on the crankshaft such as cam-follower and its associated rotating components are replaced by electromagnetic systems, and the flywheel, alternator and starter motor are replaced by a motor generator. The vehicle was tested and found that it was able to travel 70 km/litre with the power of hybrid engine.

Maximum Potential of the Car Cabin Temperature in the Outdoor Parking Conditions as a Source of Energy in Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Sunawar, A.; Garniwa, I.

2017-03-01

Cars using the principle of converting heat energy into mechanical energy, but a lot of wasted heat energy not entirely transformed into mechanical energy, studies have been conducted that converts the heat energy into electrical energy using the principle thermoelectrically. However, there are many other energies that can be harnessed from the car, such as when the car is parked in the sun or driving in the heat of the sun, the temperature in the cabin can reach 80 degrees Celsius. The heat can be harmful to humans and the children immediately into the vehicle, as well as for the goods stored in the cabin if it contains toxins can evaporate because of the heat and dangerous. The danger can be prevented by reducing the heat in the cabin and transform into other forms of energy such as electricity. By providing a temperature difference of 40 degrees on the cold side of the module can be acquired electricity thermoelectrically up to 0.17W for one of its module, if it is made a module block the energy produced is enough to lower the temperature and charge batteries for further cooling. This study will use experiment method to get the maximum drop in temperature in the car cabin

Optimal HRF and smoothing parameters for fMRI time series within an autoregressive modeling framework.

PubMed

Galka, Andreas; Siniatchkin, Michael; Stephani, Ulrich; Groening, Kristina; Wolff, Stephan; Bosch-Bayard, Jorge; Ozaki, Tohru

2010-12-01

The analysis of time series obtained by functional magnetic resonance imaging (fMRI) may be approached by fitting predictive parametric models, such as nearest-neighbor autoregressive models with exogeneous input (NNARX). As a part of the modeling procedure, it is possible to apply instantaneous linear transformations to the data. Spatial smoothing, a common preprocessing step, may be interpreted as such a transformation. The autoregressive parameters may be constrained, such that they provide a response behavior that corresponds to the canonical haemodynamic response function (HRF). We present an algorithm for estimating the parameters of the linear transformations and of the HRF within a rigorous maximum-likelihood framework. Using this approach, an optimal amount of both the spatial smoothing and the HRF can be estimated simultaneously for a given fMRI data set. An example from a motor-task experiment is discussed. It is found that, for this data set, weak, but non-zero, spatial smoothing is optimal. Furthermore, it is demonstrated that activated regions can be estimated within the maximum-likelihood framework.

Spectral Analysis of Ultrasound Radiofrequency Backscatter for the Detection of Intercostal Blood Vessels.

PubMed

Klingensmith, Jon D; Haggard, Asher; Fedewa, Russell J; Qiang, Beidi; Cummings, Kenneth; DeGrande, Sean; Vince, D Geoffrey; Elsharkawy, Hesham

2018-04-19

Spectral analysis of ultrasound radiofrequency backscatter has the potential to identify intercostal blood vessels during ultrasound-guided placement of paravertebral nerve blocks and intercostal nerve blocks. Autoregressive models were used for spectral estimation, and bandwidth, autoregressive order and region-of-interest size were evaluated. Eight spectral parameters were calculated and used to create random forests. An autoregressive order of 10, bandwidth of 6 dB and region-of-interest size of 1.0 mm resulted in the minimum out-of-bag error. An additional random forest, using these chosen values, was created from 70% of the data and evaluated independently from the remaining 30% of data. The random forest achieved a predictive accuracy of 92% and Youden's index of 0.85. These results suggest that spectral analysis of ultrasound radiofrequency backscatter has the potential to identify intercostal blood vessels. (jokling@siue.edu) © 2018 World Federation for Ultrasound in Medicine and Biology. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

On The Value at Risk Using Bayesian Mixture Laplace Autoregressive Approach for Modelling the Islamic Stock Risk Investment

NASA Astrophysics Data System (ADS)

Miftahurrohmah, Brina; Iriawan, Nur; Fithriasari, Kartika

2017-06-01

Stocks are known as the financial instruments traded in the capital market which have a high level of risk. Their risks are indicated by their uncertainty of their return which have to be accepted by investors in the future. The higher the risk to be faced, the higher the return would be gained. Therefore, the measurements need to be made against the risk. Value at Risk (VaR) as the most popular risk measurement method, is frequently ignore when the pattern of return is not uni-modal Normal. The calculation of the risks using VaR method with the Normal Mixture Autoregressive (MNAR) approach has been considered. This paper proposes VaR method couple with the Mixture Laplace Autoregressive (MLAR) that would be implemented for analysing the first three biggest capitalization Islamic stock return in JII, namely PT. Astra International Tbk (ASII), PT. Telekomunikasi Indonesia Tbk (TLMK), and PT. Unilever Indonesia Tbk (UNVR). Parameter estimation is performed by employing Bayesian Markov Chain Monte Carlo (MCMC) approaches.

Kepler AutoRegressive Planet Search (KARPS)

NASA Astrophysics Data System (ADS)

Caceres, Gabriel

2018-01-01

One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The Kepler AutoRegressive Planet Search (KARPS) project implements statistical methodology associated with autoregressive processes (in particular, ARIMA and ARFIMA) to model stellar lightcurves in order to improve exoplanet transit detection. We also develop a novel Transit Comb Filter (TCF) applied to the AR residuals which provides a periodogram analogous to the standard Box-fitting Least Squares (BLS) periodogram. We train a random forest classifier on known Kepler Objects of Interest (KOIs) using select features from different stages of this analysis, and then use ROC curves to define and calibrate the criteria to recover the KOI planet candidates with high fidelity. These statistical methods are detailed in a contributed poster (Feigelson et al., this meeting).These procedures are applied to the full DR25 dataset of NASA’s Kepler mission. Using the classification criteria, a vast majority of known KOIs are recovered and dozens of new KARPS Candidate Planets (KCPs) discovered, including ultra-short period exoplanets. The KCPs will be briefly presented and discussed.

Time series modelling of increased soil temperature anomalies during long period

NASA Astrophysics Data System (ADS)

Shirvani, Amin; Moradi, Farzad; Moosavi, Ali Akbar

2015-10-01

Soil temperature just beneath the soil surface is highly dynamic and has a direct impact on plant seed germination and is probably the most distinct and recognisable factor governing emergence. Autoregressive integrated moving average as a stochastic model was developed to predict the weekly soil temperature anomalies at 10 cm depth, one of the most important soil parameters. The weekly soil temperature anomalies for the periods of January1986-December 2011 and January 2012-December 2013 were taken into consideration to construct and test autoregressive integrated moving average models. The proposed model autoregressive integrated moving average (2,1,1) had a minimum value of Akaike information criterion and its estimated coefficients were different from zero at 5% significance level. The prediction of the weekly soil temperature anomalies during the test period using this proposed model indicated a high correlation coefficient between the observed and predicted data - that was 0.99 for lead time 1 week. Linear trend analysis indicated that the soil temperature anomalies warmed up significantly by 1.8°C during the period of 1986-2011.

Monthly streamflow forecasting with auto-regressive integrated moving average

NASA Astrophysics Data System (ADS)

Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

2017-09-01

Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

Applying the LANL Statistical Pattern Recognition Paradigm for Structural Health Monitoring to Data from a Surface-Effect Fast Patrol Boat

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

Hoon Sohn; Charles Farrar; Norman Hunter

2001-01-01

This report summarizes the analysis of fiber-optic strain gauge data obtained from a surface-effect fast patrol boat being studied by the staff at the Norwegian Defense Research Establishment (NDRE) in Norway and the Naval Research Laboratory (NRL) in Washington D.C. Data from two different structural conditions were provided to the staff at Los Alamos National Laboratory. The problem was then approached from a statistical pattern recognition paradigm. This paradigm can be described as a four-part process: (1) operational evaluation, (2) data acquisition & cleansing, (3) feature extraction and data reduction, and (4) statistical model development for feature discrimination. Given thatmore » the first two portions of this paradigm were mostly completed by the NDRE and NRL staff, this study focused on data normalization, feature extraction, and statistical modeling for feature discrimination. The feature extraction process began by looking at relatively simple statistics of the signals and progressed to using the residual errors from auto-regressive (AR) models fit to the measured data as the damage-sensitive features. Data normalization proved to be the most challenging portion of this investigation. A novel approach to data normalization, where the residual errors in the AR model are considered to be an unmeasured input and an auto-regressive model with exogenous inputs (ARX) is then fit to portions of the data exhibiting similar waveforms, was successfully applied to this problem. With this normalization procedure, a clear distinction between the two different structural conditions was obtained. A false-positive study was also run, and the procedure developed herein did not yield any false-positive indications of damage. Finally, the results must be qualified by the fact that this procedure has only been applied to very limited data samples. A more complete analysis of additional data taken under various operational and environmental conditions as well as other structural conditions is necessary before one can definitively state that the procedure is robust enough to be used in practice.« less

Effect of land cover change on snow free surface albedo across the continental United States

USGS Publications Warehouse

Wickham, J.; Nash, M.S.; Barnes, Christopher A.

2016-01-01

Land cover changes (e.g., forest to grassland) affect albedo, and changes in albedo can influence radiative forcing (warming, cooling). We empirically tested albedo response to land cover change for 130 locations across the continental United States using high resolution (30 m-×-30 m) land cover change data and moderate resolution (~ 500 m-×-500 m) albedo data. The land cover change data spanned 10 years (2001 − 2011) and the albedo data included observations every eight days for 13 years (2001 − 2013). Empirical testing was based on autoregressive time series analysis of snow free albedo for verified locations of land cover change. Approximately one-third of the autoregressive analyses for woody to herbaceous or forest to shrub change classes were not significant, indicating that albedo did not change significantly as a result of land cover change at these locations. In addition, ~ 80% of mean differences in albedo arising from land cover change were less than ± 0.02, a nominal benchmark for precision of albedo measurements that is related to significant changes in radiative forcing. Under snow free conditions, we found that land cover change does not guarantee a significant albedo response, and that the differences in mean albedo response for the majority of land cover change locations were small.

An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations

NASA Astrophysics Data System (ADS)

Kargoll, Boris; Omidalizarandi, Mohammad; Loth, Ina; Paffenholz, Jens-André; Alkhatib, Hamza

2018-03-01

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.

A test-retest assessment of the effects of mental load on ratings of affect, arousal and perceived exertion during submaximal cycling.

PubMed

Vera, Jesús; Perales, José C; Jiménez, Raimundo; Cárdenas, David

2018-04-24

This study aimed to test the effects of mental (i.e. executive) load during a dual physical-mental task on ratings of perceived exertion (RPE), affective valence, and arousal. The protocol included two dual tasks with matched physical demands but different executive demands (2-back and oddball), carried out on different days. The procedure was run twice to assess the sensitivity and stability of RPE, valence and arousal across the two trials. Linear mixed-effects analyses showed less positive valence (-0.44 points on average in a 1-9 scale; R β 2  = 0.074 [CI90%, 0.052-0.098]), and heightened arousal (+0.13 points on average in a 1-9 scale; R β 2  = 0.006 [CI90%, 0.001-0.015]), for the high executive load condition, but showed no effect of mental load on RPE. Separated analyses for the two task trials yielded best-fitting models that were identical across trials for RPE and valence, but not for arousal. Model fitting was improved by assuming a 1-level autoregressive covariance structure for all analyses. In conclusion, executive load during a dual physical-mental task modulates the emotional response to effort, but not RPE. The autoregressive covariance suggests that people tend to anchor estimates on prior ones, which imposes certain limits on scales' usability.

Granger causality for state-space models

NASA Astrophysics Data System (ADS)

Barnett, Lionel; Seth, Anil K.

2015-04-01

Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations—commonplace in application domains as diverse as climate science, econometrics, and the neurosciences—induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.

An algebraic method for constructing stable and consistent autoregressive filters

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

Harlim, John, E-mail: jharlim@psu.edu; Department of Meteorology, the Pennsylvania State University, University Park, PA 16802; Hong, Hoon, E-mail: hong@ncsu.edu

2015-02-15

In this paper, we introduce an algebraic method to construct stable and consistent univariate autoregressive (AR) models of low order for filtering and predicting nonlinear turbulent signals with memory depth. By stable, we refer to the classical stability condition for the AR model. By consistent, we refer to the classical consistency constraints of Adams–Bashforth methods of order-two. One attractive feature of this algebraic method is that the model parameters can be obtained without directly knowing any training data set as opposed to many standard, regression-based parameterization methods. It takes only long-time average statistics as inputs. The proposed method provides amore » discretization time step interval which guarantees the existence of stable and consistent AR model and simultaneously produces the parameters for the AR models. In our numerical examples with two chaotic time series with different characteristics of decaying time scales, we find that the proposed AR models produce significantly more accurate short-term predictive skill and comparable filtering skill relative to the linear regression-based AR models. These encouraging results are robust across wide ranges of discretization times, observation times, and observation noise variances. Finally, we also find that the proposed model produces an improved short-time prediction relative to the linear regression-based AR-models in forecasting a data set that characterizes the variability of the Madden–Julian Oscillation, a dominant tropical atmospheric wave pattern.« less

Assessing the effects of pharmacological agents on respiratory dynamics using time-series modeling.

PubMed

Wong, Kin Foon Kevin; Gong, Jen J; Cotten, Joseph F; Solt, Ken; Brown, Emery N

2013-04-01

Developing quantitative descriptions of how stimulant and depressant drugs affect the respiratory system is an important focus in medical research. Respiratory variables-respiratory rate, tidal volume, and end tidal carbon dioxide-have prominent temporal dynamics that make it inappropriate to use standard hypothesis-testing methods that assume independent observations to assess the effects of these pharmacological agents. We present a polynomial signal plus autoregressive noise model for analysis of continuously recorded respiratory variables. We use a cyclic descent algorithm to maximize the conditional log likelihood of the parameters and the corrected Akaike's information criterion to choose simultaneously the orders of the polynomial and the autoregressive models. In an analysis of respiratory rates recorded from anesthetized rats before and after administration of the respiratory stimulant methylphenidate, we use the model to construct within-animal z-tests of the drug effect that take account of the time-varying nature of the mean respiratory rate and the serial dependence in rate measurements. We correct for the effect of model lack-of-fit on our inferences by also computing bootstrap confidence intervals for the average difference in respiratory rate pre- and postmethylphenidate treatment. Our time-series modeling quantifies within each animal the substantial increase in mean respiratory rate and respiratory dynamics following methylphenidate administration. This paradigm can be readily adapted to analyze the dynamics of other respiratory variables before and after pharmacologic treatments.

Computational problems in autoregressive moving average (ARMA) models

NASA Technical Reports Server (NTRS)

Agarwal, G. C.; Goodarzi, S. M.; Oneill, W. D.; Gottlieb, G. L.

1981-01-01

The choice of the sampling interval and the selection of the order of the model in time series analysis are considered. Band limited (up to 15 Hz) random torque perturbations are applied to the human ankle joint. The applied torque input, the angular rotation output, and the electromyographic activity using surface electrodes from the extensor and flexor muscles of the ankle joint are recorded. Autoregressive moving average models are developed. A parameter constraining technique is applied to develop more reliable models. The asymptotic behavior of the system must be taken into account during parameter optimization to develop predictive models.

49 CFR 38.127 - Sleeping compartments.

Code of Federal Regulations, 2012 CFR

2012-10-01

... SPECIFICATIONS FOR TRANSPORTATION VEHICLES Intercity Rail Cars and Systems § 38.127 Sleeping compartments. (a...., heating and air conditioning controls, lighting controls, call buttons, electrical outlets, etc.) shall be...

49 CFR 38.127 - Sleeping compartments.

Code of Federal Regulations, 2013 CFR

2013-10-01

... SPECIFICATIONS FOR TRANSPORTATION VEHICLES Intercity Rail Cars and Systems § 38.127 Sleeping compartments. (a...., heating and air conditioning controls, lighting controls, call buttons, electrical outlets, etc.) shall be...

49 CFR 38.127 - Sleeping compartments.

Code of Federal Regulations, 2014 CFR

2014-10-01

... SPECIFICATIONS FOR TRANSPORTATION VEHICLES Intercity Rail Cars and Systems § 38.127 Sleeping compartments. (a...., heating and air conditioning controls, lighting controls, call buttons, electrical outlets, etc.) shall be...

49 CFR 38.127 - Sleeping compartments.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SPECIFICATIONS FOR TRANSPORTATION VEHICLES Intercity Rail Cars and Systems § 38.127 Sleeping compartments. (a...., heating and air conditioning controls, lighting controls, call buttons, electrical outlets, etc.) shall be...

49 CFR 38.127 - Sleeping compartments.

Code of Federal Regulations, 2010 CFR

2010-10-01

... SPECIFICATIONS FOR TRANSPORTATION VEHICLES Intercity Rail Cars and Systems § 38.127 Sleeping compartments. (a...., heating and air conditioning controls, lighting controls, call buttons, electrical outlets, etc.) shall be...

Automotive sulfate emission data.

PubMed Central

Somers, J H

1975-01-01

This paper discusses automotive sulfate emission results obtained by the Office of Mobile Source Air Pollution Control of EPA, General Motors, Ford, Chrysler, and Esso. This work has been directed towards obtaining sulfate emission factors for cars with and without catalyst. While the EPA and Chrysler investigations have found significant sulfate formation in noncatalyst cars, GM, Ford, and Esso have found only trace levels from noncatalyst cars. All of these investigators agree that much higher quantities of sulfate are emitted from catalyst cars. The work done to date shows pelleted catalysts to have much lower sulfate emissions over the low speed-EPA Federal Test Procedures than monolith catalysts. This is probably due to temporary storage of sulfates on the catalyst due to chemical interaction with the alumina pellets. The sulfate compounds are, to a large degree, emitted later under higher speed conditions which result in higher catalyst temperatures which decompose the alumina salt. Future work will be directed towards further elucidation of this storage mechanism as well as determining in detail how factors such as air injection rate and catalyst location affect sulfate emissions. PMID:50932

An extended car-following model to describe connected traffic dynamics under cyberattacks

NASA Astrophysics Data System (ADS)

Wang, Pengcheng; Yu, Guizhen; Wu, Xinkai; Qin, Hongmao; Wang, Yunpeng

2018-04-01

In this paper, the impacts of the potential cyberattacks on vehicles are modeled through an extended car-following model. To better understand the mechanism of traffic disturbance under cyberattacks, the linear and nonlinear stability analysis are conducted respectively. Particularly, linear stability analysis is performed to obtain different neutral stability conditions with various parameters; and nonlinear stability analysis is carried out by using reductive perturbation method to derive the soliton solution of the modified Korteweg de Vries equation (mKdV) near the critical point, which is used to draw coexisting stability lines. Furthermore, by applying linear and nonlinear stability analysis, traffic flow state can be divided into three states, i.e., stable, metastable and unstable states which are useful to describe shockwave dynamics and driving behaviors under cyberattacks. The theoretical results show that the proposed car-following model is capable of successfully describing the car-following behavior of connected vehicles with cyberattacks. Finally, numerical simulation using real values has confirmed the validity of theoretical analysis. The results further demonstrate our model can be used to help avoid collisions and relieve traffic congestion with cybersecurity threats.

Exposure to carbon monoxide, fine particle mass, and ultrafine particle number in Jakarta, Indonesia: effect of commute mode.

PubMed

Both, Adam F; Westerdahl, Dane; Fruin, Scott; Haryanto, Budi; Marshall, Julian D

2013-01-15

We measured real-time exposure to PM(2.5), ultrafine PM (particle number) and carbon monoxide (CO) for commuting workers school children, and traffic police, in Jakarta, Indonesia. In total, we measured exposures for 36 individuals covering 93 days. Commuters in private cars experienced mean (st dev) exposures of 22 (9.4) ppm CO, 91 (38) μg/m(3)PM(2.5), and 290 (150)×10(3) particles cm(-3). Mean concentrations were higher in public transport than in private cars for PM(2.5) (difference in means: 22%) and particle counts (54%), but not CO, likely reflecting in-vehicle particle losses in private cars owing to air-conditioning. However, average commute times were longer for private car commuters than public transport commuters (in our sample, 24% longer: 3.0 vs. 2.3 h per day). Commute and traffic-related exposures experienced by Jakarta residents are among the highest in the world, owing to high on-road concentrations and multi-hour commutes. Copyright © 2012 Elsevier B.V. All rights reserved.

Air quality in passenger cars of the ground railway transit system in Beijing, China.

PubMed

Li, Tian-Tian; Bai, Yu-Hua; Liu, Zhao-Rong; Liu, Jin-Feng; Zhang, Guang-Shan; Li, Jin-Long

2006-08-15

This study examined the concentrations of carbon monoxide, carbon dioxide, TVOC, TSP, PM(10), PM(2.5), PM(1), benzene, toluene and xylene in passenger cars of the Beijing Ground Railway Transit System (Line No. 13). This system connects the northern suburb and downtown, and is equipped with air-conditioned passenger cars. In-train air quality monitoring was performed in both summer (July and August) and winter (December). To obtain representative data, the sampling design considered both rush and regular hours, urban and suburban areas, as well as the number of passengers. Meanwhile, questionnaires were distributed to the passengers. The monitoring results indicated that, overall, the air quality in the passenger cars was acceptable with a few exceptions, which is consistent with the passengers' perception. Concentrations of some air pollutants showed significant seasonal variations and had the significant difference between rush hour and regular hour. Furthermore, the in-train air quality was greatly influenced by the number of passengers. This paper describes the experimental design, and presents the preliminary results.

Invariance in the recurrence of large returns and the validation of models of price dynamics

NASA Astrophysics Data System (ADS)

Chang, Lo-Bin; Geman, Stuart; Hsieh, Fushing; Hwang, Chii-Ruey

2013-08-01

Starting from a robust, nonparametric definition of large returns (“excursions”), we study the statistics of their occurrences, focusing on the recurrence process. The empirical waiting-time distribution between excursions is remarkably invariant to year, stock, and scale (return interval). This invariance is related to self-similarity of the marginal distributions of returns, but the excursion waiting-time distribution is a function of the entire return process and not just its univariate probabilities. Generalized autoregressive conditional heteroskedasticity (GARCH) models, market-time transformations based on volume or trades, and generalized (Lévy) random-walk models all fail to fit the statistical structure of excursions.

A Power-Law Growth and Decay Model with Autocorrelation for Posting Data to Social Networking Services

PubMed Central

Fujiyama, Toshifumi; Matsui, Chihiro; Takemura, Akimichi

2016-01-01

We propose a power-law growth and decay model for posting data to social networking services before and after social events. We model the time series structure of deviations from the power-law growth and decay with a conditional Poisson autoregressive (AR) model. Online postings related to social events are described by five parameters in the power-law growth and decay model, each of which characterizes different aspects of interest in the event. We assess the validity of parameter estimates in terms of confidence intervals, and compare various submodels based on likelihoods and information criteria. PMID:27505155

Calibrating the pixel-level Kepler imaging data with a causal data-driven model

NASA Astrophysics Data System (ADS)

Wang, Dun; Foreman-Mackey, Daniel; Hogg, David W.; Schölkopf, Bernhard

2015-01-01

In general, astronomical observations are affected by several kinds of noise, each with it's own causal source; there is photon noise, stochastic source variability, and residuals coming from imperfect calibration of the detector or telescope. In particular, the precision of NASA Kepler photometry for exoplanet science—the most precise photometric measurements of stars ever made—appears to be limited by unknown or untracked variations in spacecraft pointing and temperature, and unmodeled stellar variability. Here we present the Causal Pixel Model (CPM) for Kepler data, a data-driven model intended to capture variability but preserve transit signals. The CPM works at the pixel level (not the photometric measurement level); it can capture more fine-grained information about the variation of the spacecraft than is available in the pixel-summed aperture photometry. The basic idea is that CPM predicts each target pixel value from a large number of pixels of other stars sharing the instrument variabilities while not containing any information on possible transits at the target star. In addition, we use the target star's future and past (auto-regression). By appropriately separating the data into training and test sets, we ensure that information about any transit will be perfectly isolated from the fitting of the model. The method has four hyper-parameters (the number of predictor stars, the auto-regressive window size, and two L2-regularization amplitudes for model components), which we set by cross-validation. We determine a generic set of hyper-parameters that works well on most of the stars with 11≤V≤12 mag and apply the method to a corresponding set of target stars with known planet transits. We find that we can consistently outperform (for the purposes of exoplanet detection) the Kepler Pre-search Data Conditioning (PDC) method for exoplanet discovery, often improving the SNR by a factor of two. While we have not yet exhaustively tested the method at other magnitudes, we expect that it should be generally applicable, with positive consequences for subsequent exoplanet detection or stellar variability (in which case we must exclude the autoregressive part to preserve intrinsic variability).

Agent-based modeling of lane discipline in heterogeneous traffic

NASA Astrophysics Data System (ADS)

Dailisan, Damian N.; Lim, May T.

2016-09-01

Designating lanes for different vehicle types is ideal road safety-wise. Practical considerations, however, require road sharing. Using a modified Nagel-Schreckenberg cellular automata model for two vehicle types (cars and motorcycles), we analyzed the interplay of lane discipline, lane changing, and vehicle density. In the absence of lane changing, the transition between free flow and congested states occurs at a higher vehicle (road occupation) density when the ratio of cars to motorcycles is increased. When lane changing is allowed, the smaller motorcycles tend to fill in unused spaces, until the point when the wider cars effectively block their way at high vehicle densities. When the condition of lane discipline is not imposed, i.e. staying wholly within lane boundaries is not required, further improvement in throughput becomes possible at the cost of required driver attentiveness.

An extended car-following model with consideration of vehicle to vehicle communication of two conflicting streams

NASA Astrophysics Data System (ADS)

Zhao, Jing; Li, Peng

2017-05-01

In this paper, we propose a car-following model to explore the influences of V2V communication on the driving behavior at un-signalized intersections with two crossing streams and to explore how the speed guidance strategy affects the operation efficiency. The numerical results illustrate that the benefits of the guidance strategy could be enhanced by lengthening the guiding space range and increasing the maximum speed limitation, and that the guidance strategy is more suitable under low to medium traffic density and small safety interval condition.

Simulator with integrated HW and SW for prediction of thermal comfort to provide feedback to the climate control system

NASA Astrophysics Data System (ADS)

Pokorný, Jan; Kopečková, Barbora; Fišer, Jan; JÍcha, Miroslav

2018-06-01

The aim of the paper is to assemble a simulator for evaluation of thermal comfort in car cabins in order to give a feedback to the HVAC (heating, ventilation and air conditioning) system. The HW (hardware) part of simulator is formed by thermal manikin Newton and RH (relative humidity), velocity and temperature probes. The SW (software) part consists of the Thermal Comfort Analyser (using ISO 14505-2) and Virtual Testing Stand of Car Cabin defining the heat loads of car cabin. Simulator can provide recommendation for the climate control how to improve thermal comfort in cabin by distribution and directing of air flow, and also by amount of ventilation power to keep optimal temperature inside a cabin. The methods of evaluation of thermal comfort were verified by tests with 10 test subjects for summer (summer clothing, ambient air temperature 30 °C, HVAC setup: +24 °C auto) and winter conditions (winter clothing, ambient air temperature -5 °C, HVAC setup: +18 °C auto). The tests confirmed the validity of the thermal comfort evaluation using the thermal manikin and ISO 14505-2.

Evaluation of an LED (Light-Emitting Diode) high-mounted signal lamp

NASA Astrophysics Data System (ADS)

Olson, P. L.

1987-02-01

Two studies are described evaluating high-mounted stoplights using light-emitting diodes (LEDs) compared with conventional incandescent units. The first of these studies obtained ratings from subjects who drove one car and followed another car that was equipped with the test lamps. The results indicate that the subjects generally preferred the LEDs to the conventional lamp. The second study was a laboratory evaluation of the attention-getting capabilities of LED and incandescent stoplights. Under all conditions tested subjects responded faster to the LED units. The response time advantage for the LED units increased with more difficult viewing conditions, such as high levels of illumination and long viewing distance. The results of these investigations are discussed in terms of the applicability of the LED technology to high mounted stoplights on motor vehicles.

Effect of passengers' active head tilt and opening/closure of eyes on motion sickness in lateral acceleration environment of cars.

PubMed

Wada, Takahiro; Yoshida, Keigo

2016-08-01

This study examined the effect of passengers' active head-tilt and eyes-open/eyes-closed conditions on the severity of motion sickness in the lateral acceleration environment of cars. In the centrifugal head-tilt condition, participants intentionally tilted their heads towards the centrifugal force, whereas in the centripetal head-tilt condition, the participants tilted their heads against the centrifugal acceleration. The eyes-open and eyes-closed cases were investigated for each head-tilt condition. In the experimental runs, the sickness rating in the centripetal head-tilt condition was significantly lower than that in the centrifugal head-tilt condition. Moreover, the sickness rating in the eyes-open condition was significantly lower than that in the eyes-closed condition. The results suggest that an active head-tilt motion against the centrifugal acceleration reduces the severity of motion sickness both in the eyes-open and eyes-closed conditions. They also demonstrate that the eyes-open condition significantly reduces the motion sickness even when the head-tilt strategy is used. Practitioner Summary: Little is known about the effect of head-tilt strategies on motion sickness. This study investigated the effects of head-tilt direction and eyes-open/eyes-closed conditions on motion sickness during slalom automobile driving. Passengers' active head tilt towards the centripetal direction and the eyes-open condition greatly reduce the severity of motion sickness.

A spatial analysis of social and economic determinants of tuberculosis in Brazil.

PubMed

Harling, Guy; Castro, Marcia C

2014-01-01

We investigated the spatial distribution, and social and economic correlates, of tuberculosis in Brazil between 2002 and 2009 using municipality-level age/sex-standardized tuberculosis notification data. Rates were very strongly spatially autocorrelated, being notably high in urban areas on the eastern seaboard and in the west of the country. Non-spatial ecological regression analyses found higher rates associated with urbanicity, population density, poor economic conditions, household crowding, non-white population and worse health and healthcare indicators. These associations remained in spatial conditional autoregressive models, although the effect of poverty appeared partially confounded by urbanicity, race and spatial autocorrelation, and partially mediated by household crowding. Our analysis highlights both the multiple relationships between socioeconomic factors and tuberculosis in Brazil, and the importance of accounting for spatial factors in analysing socioeconomic determinants of tuberculosis. © 2013 Published by Elsevier Ltd.

Effects of 3D virtual haptics force feedback on brand personality perception: the mediating role of physical presence in advergames.

PubMed

Jin, Seung-A Annie

2010-06-01

This study gauged the effects of force feedback in the Novint Falcon haptics system on the sensory and cognitive dimensions of a virtual test-driving experience. First, in order to explore the effects of tactile stimuli with force feedback on users' sensory experience, feelings of physical presence (the extent to which virtual physical objects are experienced as actual physical objects) were measured after participants used the haptics interface. Second, to evaluate the effects of force feedback on the cognitive dimension of consumers' virtual experience, this study investigated brand personality perception. The experiment utilized the Novint Falcon haptics controller to induce immersive virtual test-driving through tactile stimuli. The author designed a two-group (haptics stimuli with force feedback versus no force feedback) comparison experiment (N = 238) by manipulating the level of force feedback. Users in the force feedback condition were exposed to tactile stimuli involving various force feedback effects (e.g., terrain effects, acceleration, and lateral forces) while test-driving a rally car. In contrast, users in the control condition test-drove the rally car using the Novint Falcon but were not given any force feedback. Results of ANOVAs indicated that (a) users exposed to force feedback felt stronger physical presence than those in the no force feedback condition, and (b) users exposed to haptics stimuli with force feedback perceived the brand personality of the car to be more rugged than those in the control condition. Managerial implications of the study for product trial in the business world are discussed.

Constraining Basal Conditions across the Amundsen Sea Embayment of West Antarctica using a Synthesis of the PASIN and HiCARS Radar Sounding Data

NASA Astrophysics Data System (ADS)

Hilger, A. M.; Schroeder, D. M.; Corr, H. F. J.; Blankenship, D. D.; Paden, J. D.

2017-12-01

Recent observational studies and models have shown that ocean forcing, bed topography, and basal conditions are major controls of the behavior of the Amundsen Sea Embayment of the West Antarctic Ice Sheet. This region contains Thwaites Glacier and Pine Island Glacier, the two most rapidly changing glaciers in Antarctica. Because they are adjacent, interactions between these two glaciers could potentially cause further destabilization as either glacier retreats. Accordingly, it is important to understand the basal conditions on the Thwaites-Pine Island boundary in order to accurately model the present and future behavior of these glaciers. Previous airborne geophysical surveys in this area have provided dense radar sounding coverage using multiple radar sounding systems, including the UTIG HiCARS system and the BAS PASIN system used in the 2004 AGASEA survey. Because the boundary region between Thwaites and Pine Island Glacier is at the respective boundaries of the UTIG and BAS surveys, accurate characterization of the basal conditions requires a synthesis of the data produced by the BAS and HiCARS systems. To this end, we present estimates of bed reflectivity spanning both glacier catchments. These estimates were produced using empirically determined attenuation rates. To improve the consistency of these attenuation rates, we fit across a two-dimensional area, rather than a one-dimensional line as in previous work. These estimates also include cross-calibration to account for the radar sounding systems' differing power and center frequency. This will provide the first cross-survey map of basal reflectivity spanning the entire Amundsen Sea Embayment.

Kepler AutoRegressive Planet Search

NASA Astrophysics Data System (ADS)

Feigelson, Eric

NASA's Kepler mission is the source of more exoplanets than any other instrument, but the discovery depends on complex statistical analysis procedures embedded in the Kepler pipeline. A particular challenge is mitigating irregular stellar variability without loss of sensitivity to faint periodic planetary transits. This proposal presents a two-stage alternative analysis procedure. First, parametric autoregressive ARFIMA models, commonly used in econometrics, remove most of the stellar variations. Second, a novel matched filter is used to create a periodogram from which transit-like periodicities are identified. This analysis procedure, the Kepler AutoRegressive Planet Search (KARPS), is confirming most of the Kepler Objects of Interest and is expected to identify additional planetary candidates. The proposed research will complete application of the KARPS methodology to the prime Kepler mission light curves of 200,000: stars, and compare the results with Kepler Objects of Interest obtained with the Kepler pipeline. We will then conduct a variety of astronomical studies based on the KARPS results. Important subsamples will be extracted including Habitable Zone planets, hot super-Earths, grazing-transit hot Jupiters, and multi-planet systems. Groundbased spectroscopy of poorly studied candidates will be performed to better characterize the host stars. Studies of stellar variability will then be pursued based on KARPS analysis. The autocorrelation function and nonstationarity measures will be used to identify spotted stars at different stages of autoregressive modeling. Periodic variables with folded light curves inconsistent with planetary transits will be identified; they may be eclipsing or mutually-illuminating binary star systems. Classification of stellar variables with KARPS-derived statistical properties will be attempted. KARPS procedures will then be applied to archived K2 data to identify planetary transits and characterize stellar variability.

Nonrandom variability in respiratory cycle parameters of humans during stage 2 sleep.

PubMed

Modarreszadeh, M; Bruce, E N; Gothe, B

1990-08-01

We analyzed breath-to-breath inspiratory time (TI), expiratory time (TE), inspiratory volume (VI), and minute ventilation (Vm) from 11 normal subjects during stage 2 sleep. The analysis consisted of 1) fitting first- and second-order autoregressive models (AR1 and AR2) and 2) obtaining the power spectra of the data by fast-Fourier transform. For the AR2 model, the only coefficients that were statistically different from zero were the average alpha 1 (a1) for TI, VI, and Vm (a1 = 0.19, 0.29, and 0.15, respectively). However, the power spectra of all parameters often exhibited peaks at low frequency (less than 0.2 cycles/breath) and/or at high frequency (greater than 0.2 cycles/breath), indicative of periodic oscillations. After accounting for the corrupting effects of added oscillations on the a1 estimates, we conclude that 1) breath-to-breath fluctuations of VI, and to a lesser extent TI and Vm, exhibit a first-order autoregressive structure such that fluctuations of each breath are positively correlated with those of immediately preceding breaths and 2) the correlated components of variability in TE are mostly due to discrete high- and/or low-frequency oscillations with no underlying autoregressive structure. We propose that the autoregressive structure of VI, TI, and Vm during spontaneous breathing in stage 2 sleep may reflect either a central neural mechanism or the effects of noise in respiratory chemical feedback loops; the presence of low-frequency oscillations, seen more often in Vm, suggests possible instability in the chemical feedback loops. Mechanisms of high-frequency periodicities, seen more often in TE, are unknown.

Autoregressive Processes in Homogenization of GNSS Tropospheric Data

NASA Astrophysics Data System (ADS)

Klos, A.; Bogusz, J.; Teferle, F. N.; Bock, O.; Pottiaux, E.; Van Malderen, R.

2016-12-01

Offsets due to changes in hardware equipment or any other artificial event are all a subject of a task of homogenization of tropospheric data estimated within a processing of Global Navigation Satellite System (GNSS) observables. This task is aimed at identifying exact epochs of offsets and estimate their magnitudes since they may artificially under- or over-estimate trend and its uncertainty delivered from tropospheric data and used in climate studies. In this research, we analysed a common data set of differences of Integrated Water Vapour (IWV) from GPS and ERA-Interim (1995-2010) provided for a homogenization group working within ES1206 COST Action GNSS4SWEC. We analysed daily IWV records of GPS and ERA-Interim in terms of trend, seasonal terms and noise model with Maximum Likelihood Estimation in Hector software. We found that this data has a character of autoregressive process (AR). Basing on this analysis, we performed Monte Carlo simulations of 25 years long data with two different noise types: white as well as combination of white and autoregressive and also added few strictly defined offsets. This synthetic data set of exactly the same character as IWV from GPS and ERA-Interim was then subjected to a task of manual and automatic/statistical homogenization. We made blind tests and detected possible epochs of offsets manually. We found that simulated offsets were easily detected in series with white noise, no influence of seasonal signal was noticed. The autoregressive series were much more problematic when offsets had to be determined. We found few epochs, for which no offset was simulated. This was mainly due to strong autocorrelation of data, which brings an artificial trend within. Due to regime-like behaviour of AR it is difficult for statistical methods to properly detect epochs of offsets, which was previously reported by climatologists.

Black carbon, particle number concentration and nitrogen oxide emission factors of random in-use vehicles measured with the on-road chasing method

NASA Astrophysics Data System (ADS)

Ježek, I.; Katrašnik, T.; Westerdahl, D.; Močnik, G.

2015-06-01

The chasing method was used in an on-road measurement campaign, and emission factors (EF) of black carbon (BC), particle number (PN) and nitrogen oxides (NOx) were determined for 139 individual vehicles of different types encountered on the roads. The aggregated results provide EFs for BC, NOx and PN for three vehicle categories: goods vehicles, gasoline and diesel passenger cars. This is the first on-road measurement study where BC EFs of numerous individual diesel cars were determined in real-world driving conditions. We found good agreement between EFs of goods vehicles determined in this campaign and the results of previous studies that used either chasing or remote sensing measurement techniques. The composition of the sampled car fleet determined from the national vehicle registry information is reflective of Eurostat statistical data on the Slovenian and European vehicle fleet. The median BC EF of diesel and gasoline cars that were in use for less than 5 years, decreased by 60 and 47% from those in use for 5-10 years, respectively, the median NOx and PN EFs, of goods vehicles that were in use for less than five years, decreased from those in use for 5-10 years by 52 and 67%, respectively. The influence of engine maximum power of the measured EFs showed an increase in NOx EF from least to more powerful vehicles with diesel engines. Finally a disproportionate contribution of high emitters to the total emissions of the measured fleet was found; the top 25% of emitting diesel cars contributed 63, 47 and 61% of BC, NOx and PN emissions respectively. With the combination of relatively simple on-road measurements with sophisticated post processing individual vehicles EF can be determined and useful information about the fleet emissions can be obtained by exactly representing vehicles which contribute disproportionally to vehicle fleet emissions; and monitor how the numerous emission reduction approaches are reflected in on-road driving conditions.

The consequences of an increase in heavy goods vehicles for passenger car drivers' mental workload and behaviour: a simulator study.

PubMed

de Waard, Dick; Kruizinga, Anje; Brookhuis, Karel A

2008-03-01

The effects of an increase in Heavy Goods Vehicles (HGVs) on merging behaviour and on mental workload of motorists during filtering in and out of traffic were studied. Participants drove in a driving simulator in a total of 12 conditions; twice in each of two weather conditions and in three traffic conditions. The weather conditions were clear weather and foggy weather. The traffic conditions were without HGVs (i.e. only private cars), the current mix of HGVs and private cars, and a condition with a 70% increase of HGVs leading to an HGV column in the slow lane. The focus of the study was on assessing effects on behaviour and mental workload during filtering into traffic, and during exiting from the motorway. During the experiment driving performance was registered, behaviour was observed, self reports were collected, and the participant's heart rate was recorded. The results showed that directly after filtering into traffic the variation in driving speed increased and the minimum time headway decreased with an increase in the proportion of HGVs. Joining motorway traffic was considered to involve greater effort and risk in the condition with a column of HGVs. The effects of the conditions on heart rate are less clear, although the moment when the participants joined the traffic is clearly visible. The effects of weather conditions were limited, drivers adapting their driving behaviour in adverse weather by reducing speed. To exit the motorway is not a difficult manoeuvre. For that reason the lane change from the left hand to the right hand lane that preceded the exit was analysed. Although increased mental effort was reported and the lane change was visible in the heart rate record, no critical changes as a result of increase in proportion of HGVs were found for this manoeuvre. However, in the condition with a column of HGVs, the exit that had to be taken was most frequently missed as HGVs obstructed the view of the exit signs. It is concluded that an increase in HGVs will make merging into traffic more mentally demanding and will decrease safety margins.

Stress Markers During a Rally Car Competition.

PubMed

Del Rosso, Sebastián; Abreu, Laurinda; Webb, Heather E; Zouhal, Hassane; Boullosa, Daniel A

2016-03-01

The aim of the study was to assess the stress responses in drivers during an official rally car race and the influence of fitness and body composition on stress hormones. Fitness and body composition were assessed in 9 rally car drivers with an incremental exercise test for determination of maximum aerobic speed (MAS) and 6-site skinfold method, respectively. Before (pre) and after (post) the first stage of an official rally car race, data were collected for heart rate (HR), blood samples were collected for analysis of hormones (i.e., epinephrine [EPI], norepinephrine [NE], cortisol, and aldosterone) and metabolites (i.e., lactate [LA], glucose, and ammonia). There were significant (p ≤ 0.05) increases in all assessed variables except glucose at postrace. Heart rate increased 93% (p ≤ 0.05) at the end of the race stage, reaching 88.77 ± 4.96% of HRpeak. Also, EPI and NE significantly (p = 0.001) increased by 45 and 65%, respectively, and LA increased by 395% (p < 0.001). Significant correlations between percent body fat (%BF) and postrace EPI (r = 0.95; p < 0.001), and percentage change of EPI (r = 0.83; p = 0.012) were observed. The MAS was not associated to any metabolic or hormonal variable. These results suggest that psycho-physiological stress induced by the race elicited important changes in hormonal and metabolic variables and that %BF could be an important mediator of psycho-physiological stress in rally car drivers. Specific programs, including both strength and aerobic training, and nutritional plans should be implemented for appropriate conditioning of rally car drivers.

The Transportation Leapfrog: Using Smart Phones to Collect Driving Data and Model Fuel Economy in India

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

Gopal, Anand; Schewel, Laura; Saxena, Samveg

Car ownership in India is expected to skyrocket in the coming decades, strongly driven by rising incomes. This phenomenon provides unprecedented opportunities for automakers and equally unprecedented social and environmental challenges. Policymakers, urban planners and civil society see this car boom leading to an explosion in problems related to congestion, infrastructure, air pollution, safety, higher oil imports and climate change. For all these stakeholders to take effective action, good data on how people use their cars, their demand for mobility and their behavior in mobility is essential. Unfortunately, there is very little data on the Indian transport sector as amore » whole and virtually none on real-world vehicle performance and use. The rapid development of high quality mobile telecommunications infrastructure provides India with the opportunity to leapfrog the West in cheaply collecting vast amounts of useful data from transportation. In this paper, we describe a pilot project in which we use commercial smart phone apps to collect per second car driving data from the city of Pune, instantly upload it through 3G and prepare it for analysis using advanced noise filtering algorithms for less than $1 per day per car. We then use our data in an Autonomie simulation to show that India’s currently planned fuel economy test procedures will result in over-estimates of fuel economy of approximately 35% for a typical Indian car when it is operated in real world conditions. Supporting better driving cycle development is just one of many applications for smart phone derived data in Indian transportation.« less

CD19 chimeric antigen receptor (CD19 CAR)-redirected adoptive T-cell immunotherapy for the treatment of relapsed or refractory B-cell Non-Hodgkin's Lymphomas.

PubMed

Onea, Alexandra S; Jazirehi, Ali R

2016-01-01

Recovery rates for B-cell Non-Hodgkin's Lymphoma (NHL) are up to 70% with current standard-of-care treatments including rituximab (chimeric anti-CD20 monoclonal antibody) in combination with chemotherapy (R-CHOP). However, patients who do not respond to first-line treatment or develop resistance have a very poor prognosis. This signifies the need for the development of an optimal treatment approach for relapsed/refractory B-NHL. Novel CD19- chimeric antigen receptor (CAR) T-cell redirected immunotherapy is an attractive option for this subset of patients. Anti-CD19 CAR T-cell therapy has already had remarkable efficacy in various leukemias as well as encouraging outcomes in phase I clinical trials of relapsed/refractory NHL. In going forward with additional clinical trials, complementary treatments that may circumvent potential resistance mechanisms should be used alongside anti-CD19 T-cells in order to prevent relapse with resistant strains of disease. Some such supplementary tactics include conditioning with lymphodepletion agents, sensitizing with kinase inhibitors and Bcl-2 inhibitors, enhancing function with multispecific CAR T-cells and CD40 ligand-expressing CAR T-cells, and safeguarding with lymphoma stem cell-targeted treatments. A therapy regimen involving anti-CD19 CAR T-cells and one or more auxiliary treatments could dramatically improve prognoses for patients with relapsed/refractory B-cell NHL. This approach has the potential to revolutionize B-NHL salvage therapy in much the same way rituximab did for first-line treatments.

CD19 chimeric antigen receptor (CD19 CAR)-redirected adoptive T-cell immunotherapy for the treatment of relapsed or refractory B-cell Non-Hodgkin’s Lymphomas

PubMed Central

Onea, Alexandra S; Jazirehi, Ali R

2016-01-01

Recovery rates for B-cell Non-Hodgkin’s Lymphoma (NHL) are up to 70% with current standard-of-care treatments including rituximab (chimeric anti-CD20 monoclonal antibody) in combination with chemotherapy (R-CHOP). However, patients who do not respond to first-line treatment or develop resistance have a very poor prognosis. This signifies the need for the development of an optimal treatment approach for relapsed/refractory B-NHL. Novel CD19- chimeric antigen receptor (CAR) T-cell redirected immunotherapy is an attractive option for this subset of patients. Anti-CD19 CAR T-cell therapy has already had remarkable efficacy in various leukemias as well as encouraging outcomes in phase I clinical trials of relapsed/refractory NHL. In going forward with additional clinical trials, complementary treatments that may circumvent potential resistance mechanisms should be used alongside anti-CD19 T-cells in order to prevent relapse with resistant strains of disease. Some such supplementary tactics include conditioning with lymphodepletion agents, sensitizing with kinase inhibitors and Bcl-2 inhibitors, enhancing function with multispecific CAR T-cells and CD40 ligand-expressing CAR T-cells, and safeguarding with lymphoma stem cell-targeted treatments. A therapy regimen involving anti-CD19 CAR T-cells and one or more auxiliary treatments could dramatically improve prognoses for patients with relapsed/refractory B-cell NHL. This approach has the potential to revolutionize B-NHL salvage therapy in much the same way rituximab did for first-line treatments. PMID:27186412

Efficient detection of human circulating tumor cells without significant production of false-positive cells by a novel conditionally replicating adenovirus

PubMed Central

Sakurai, Fuminori; Narii, Nobuhiro; Tomita, Kyoko; Togo, Shinsaku; Takahashi, Kazuhisa; Machitani, Mitsuhiro; Tachibana, Masashi; Ouchi, Masaaki; Katagiri, Nobuyoshi; Urata, Yasuo; Fujiwara, Toshiyoshi; Mizuguchi, Hiroyuki

2016-01-01

Circulating tumor cells (CTCs) are promising biomarkers in several cancers, and thus methods and apparatuses for their detection and quantification in the blood have been actively pursued. A novel CTC detection system using a green fluorescence protein (GFP)–expressing conditionally replicating adenovirus (Ad) (rAd-GFP) was recently developed; however, there is concern about the production of false-positive cells (GFP-positive normal blood cells) when using rAd-GFP, particularly at high titers. In addition, CTCs lacking or expressing low levels of coxsackievirus–adenovirus receptor (CAR) cannot be detected by rAd-GFP, because rAd-GFP is constructed based on Ad serotype 5, which recognizes CAR. In order to suppress the production of false-positive cells, sequences perfectly complementary to blood cell–specific microRNA, miR-142-3p, were incorporated into the 3′-untranslated region of the E1B and GFP genes. In addition, the fiber protein was replaced with that of Ad serotype 35, which recognizes human CD46, creating rAdF35-142T-GFP. rAdF35-142T-GFP efficiently labeled not only CAR-positive tumor cells but also CAR-negative tumor cells with GFP. The numbers of false-positive cells were dramatically lower for rAdF35-142T-GFP than for rAd-GFP. CTCs in the blood of cancer patients were detected by rAdF35-142T-GFP with a large reduction in false-positive cells. PMID:26966699

Intersection delay estimation from floating car data via principal curves: a case study on Beijing's road network

NASA Astrophysics Data System (ADS)

Liu, Xiliang; Lu, Feng; Zhang, Hengcai; Qiu, Peiyuan

2013-06-01

It is a pressing task to estimate the real-time travel time on road networks reliably in big cities, even though floating car data has been widely used to reflect the real traffic. Currently floating car data are mainly used to estimate the real-time traffic conditions on road segments, and has done little for turn delay estimation. However, turn delays on road intersections contribute significantly to the overall travel time on road networks in modern cities. In this paper, we present a technical framework to calculate the turn delays on road networks with float car data. First, the original floating car data collected with GPS equipped taxies was cleaned and matched to a street map with a distributed system based on Hadoop and MongoDB. Secondly, the refined trajectory data set was distributed among 96 time intervals (from 0: 00 to 23: 59). All of the intersections where the trajectories passed were connected with the trajectory segments, and constituted an experiment sample, while the intersections on arterial streets were specially selected to form another experiment sample. Thirdly, a principal curve-based algorithm was presented to estimate the turn delays at the given intersections. The algorithm argued is not only statistically fitted the real traffic conditions, but also is insensitive to data sparseness and missing data problems, which currently are almost inevitable with the widely used floating car data collecting technology. We adopted the floating car data collected from March to June in Beijing city in 2011, which contains more than 2.6 million trajectories generated from about 20000 GPS-equipped taxicabs and accounts for about 600 GB in data volume. The result shows the principal curve based algorithm we presented takes precedence over traditional methods, such as mean and median based approaches, and holds a higher estimation accuracy (about 10%-15% higher in RMSE), as well as reflecting the changing trend of traffic congestion. With the estimation result for the travel delay at intersections, we analyzed the spatio-temporal distribution of turn delays in three time scenarios (0: 00-0: 15, 8: 15-8: 30 and 12: 00-12: 15). It indicates that during one's single trip in Beijing, average 60% of the travel time on the road networks is wasted on the intersections, and this situation is even worse in daytime. Although the 400 main intersections take only 2.7% of all the intersections, they occupy about 18% travel time.

A photoreceptor calcium binding protein is recognized by autoantibodies obtained from patients with cancer-associated retinopathy

PubMed Central

1991-01-01

Cancer-associated retinopathy (CAR), a paraneoplastic syndrome, is characterized by the degeneration of retinal photoreceptors under conditions where the tumor and its metastases have not invaded the eye. The retinopathy often is apparent before the diagnosis of cancer and may be associated with autoantibodies that react with specific sites in the retina. We have examined the sera from patients with CAR to further characterize the retinal antigen. Western blot analysis of human retinal proteins reveals a prominent band at 26 kD that is labeled by the CAR antisera. Antibodies to the 26-kD protein were affinity- purified from complex CAR antisera and used for EM-immunocytochemical localization of the protein to the nuclei, inner and outer segments of both rod and cone cells. Other antibodies obtained from the CAR sera did not label photoreceptors. Using the affinity-purified antibodies for detection, the 26-kD protein, designated p26, was purified to homogeneity from the outer segments of bovine rod photoreceptor cells by Phenyl-Sepharose and ion exchange chromatography. Partial amino acid sequence of p26 was determined by gas phase Edman degradation and revealed extensive homology with a cone-specific protein, visinin. Based upon structural relatedness, both the p26 rod protein and visinin are members of the calmodulin family and contain calcium binding domains of the E-F hand structure. PMID:1999465

Access to Recreational Physical Activities by Car and Bus: An Assessment of Socio-Spatial Inequalities in Mainland Scotland

PubMed Central

Ferguson, Neil S.; Lamb, Karen E.; Wang, Yang; Ogilvie, David; Ellaway, Anne

2013-01-01

Obesity and other chronic conditions linked with low levels of physical activity (PA) are associated with deprivation. One reason for this could be that it is more difficult for low-income groups to access recreational PA facilities such as swimming pools and sports centres than high-income groups. In this paper, we explore the distribution of access to PA facilities by car and bus across mainland Scotland by income deprivation at datazone level. GIS car and bus networks were created to determine the number of PA facilities accessible within travel times of 10, 20 and 30 minutes. Multilevel negative binomial regression models were then used to investigate the distribution of the number of accessible facilities, adjusting for datazone population size and local authority. Access to PA facilities by car was significantly (p<0.01) higher for the most affluent quintile of area-based income deprivation than for most other quintiles in small towns and all other quintiles in rural areas. Accessibility by bus was significantly lower for the most affluent quintile than for other quintiles in urban areas and small towns, but not in rural areas. Overall, we found that the most disadvantaged groups were those without access to a car and living in the most affluent areas or in rural areas. PMID:23409012

Multimodal Nonlinear Optical Imaging for Sensitive Detection of Multiple Pharmaceutical Solid-State Forms and Surface Transformations.

PubMed

Novakovic, Dunja; Saarinen, Jukka; Rojalin, Tatu; Antikainen, Osmo; Fraser-Miller, Sara J; Laaksonen, Timo; Peltonen, Leena; Isomäki, Antti; Strachan, Clare J

2017-11-07

Two nonlinear imaging modalities, coherent anti-Stokes Raman scattering (CARS) and sum-frequency generation (SFG), were successfully combined for sensitive multimodal imaging of multiple solid-state forms and their changes on drug tablet surfaces. Two imaging approaches were used and compared: (i) hyperspectral CARS combined with principal component analysis (PCA) and SFG imaging and (ii) simultaneous narrowband CARS and SFG imaging. Three different solid-state forms of indomethacin-the crystalline gamma and alpha forms, as well as the amorphous form-were clearly distinguished using both approaches. Simultaneous narrowband CARS and SFG imaging was faster, but hyperspectral CARS and SFG imaging has the potential to be applied to a wider variety of more complex samples. These methodologies were further used to follow crystallization of indomethacin on tablet surfaces under two storage conditions: 30 °C/23% RH and 30 °C/75% RH. Imaging with (sub)micron resolution showed that the approach allowed detection of very early stage surface crystallization. The surfaces progressively crystallized to predominantly (but not exclusively) the gamma form at lower humidity and the alpha form at higher humidity. Overall, this study suggests that multimodal nonlinear imaging is a highly sensitive, solid-state (and chemically) specific, rapid, and versatile imaging technique for understanding and hence controlling (surface) solid-state forms and their complex changes in pharmaceuticals.

Understanding smallholders’ intended deforestation behavior in the Brazilian Cerrado following environmental registry

NASA Astrophysics Data System (ADS)

Vang Rasmussen, Laura; Jung, Suhyun; Dantas Brites, Alice; Watkins, Cristy; Agrawal, Arun

2016-09-01

Brazil’s Rural Environmental Registry (CAR) is a potentially promising avenue to slow deforestation on private properties as it facilitates the monitoring of land use. Yet limited empirical evidence exists on how the CAR affects smallholders’ behavior and recent scholarly efforts have in fact indicated that it may be doing less to protect forests than previously assumed. Based on 1177 smallholder surveys conducted in the Cerrado, we assess 1) whether the CAR might incentivize smallholders to pursue deforestation and 2) which factors are associated with smallholders’ intended deforestation behavior. We find that upon CAR registration, factors significantly associated with smallholders’ intention to deforest are: the existing percentage of native vegetation on the property, the use of agricultural loans, property owner’s age, and livestock production experience. To curb deforestation that may follow expressed intentions of smallholders, the CAR, and environmental registration programs alike, should account for existing land use by, for example, improving the system already in place for trading areas of native vegetation as this system is not widely adopted by those smallholders with more native vegetation than the legal cut-off. Also, such programs should assess the role of whether conditions related to land cover maintenance may protect against deforestation if credit access is supported especially to younger smallholders and/or livestock producers with a high percentage of native vegetation in their properties.

Effects of enactment in episodic memory: a pilot virtual reality study with young and elderly adults.

PubMed

Jebara, Najate; Orriols, Eric; Zaoui, Mohamed; Berthoz, Alain; Piolino, Pascale

2014-01-01

None of the previous studies on aging have tested the influence of action with respect to the degree of interaction with the environment (active or passive navigation) and the source of itinerary choice (self or externally imposed), on episodic memory (EM) encoding. The aim of this pilot study was to explore the influence of these factors on feature binding (the association between what, where, and when) in EM and on the subjective sense of remembering. Navigation in a virtual city was performed by 64 young and 64 older adults in one of four modes of exploration: (1) passive condition where participants were immersed as passengers of a virtual car [no interaction, no itinerary control (IC)], (2) IC (the subject chose the itinerary, but did not drive the car), (3) low, or (4) high navigation control (the subject just moved the car on rails or drove the car with a steering-wheel and a gas pedal on a fixed itinerary, respectively). The task was to memorize as many events encountered in the virtual environment as possible along with their factual (what), spatial (where), and temporal (when) details, and then to perform immediate and delayed memory tests. An age-related decline was evidenced for immediate and delayed feature binding. Compared to passive and high navigation conditions, and regardless of age-groups, feature binding was enhanced by low navigation and IC conditions. The subjective sense of remembering was boosted by the IC in older adults. Memory performance following high navigation was specifically linked to variability in executive functions. The present findings suggest that the decision of the itinerary is beneficial to boost EM in aging, although it does not eliminate age-related deficits. Active navigation can also enhance EM when it is not too demanding for subjects' cognitive resources.

Effects of Enactment in Episodic Memory: A Pilot Virtual Reality Study with Young and Elderly Adults

PubMed Central

Jebara, Najate; Orriols, Eric; Zaoui, Mohamed; Berthoz, Alain; Piolino, Pascale

2014-01-01

None of the previous studies on aging have tested the influence of action with respect to the degree of interaction with the environment (active or passive navigation) and the source of itinerary choice (self or externally imposed), on episodic memory (EM) encoding. The aim of this pilot study was to explore the influence of these factors on feature binding (the association between what, where, and when) in EM and on the subjective sense of remembering. Navigation in a virtual city was performed by 64 young and 64 older adults in one of four modes of exploration: (1) passive condition where participants were immersed as passengers of a virtual car [no interaction, no itinerary control (IC)], (2) IC (the subject chose the itinerary, but did not drive the car), (3) low, or (4) high navigation control (the subject just moved the car on rails or drove the car with a steering-wheel and a gas pedal on a fixed itinerary, respectively). The task was to memorize as many events encountered in the virtual environment as possible along with their factual (what), spatial (where), and temporal (when) details, and then to perform immediate and delayed memory tests. An age-related decline was evidenced for immediate and delayed feature binding. Compared to passive and high navigation conditions, and regardless of age-groups, feature binding was enhanced by low navigation and IC conditions. The subjective sense of remembering was boosted by the IC in older adults. Memory performance following high navigation was specifically linked to variability in executive functions. The present findings suggest that the decision of the itinerary is beneficial to boost EM in aging, although it does not eliminate age-related deficits. Active navigation can also enhance EM when it is not too demanding for subjects’ cognitive resources. PMID:25566069

Contextual and behavioral control of antipsychotic sensitization induced by haloperidol and olanzapine.

PubMed

Zhang, Chen; Li, Ming

2012-02-01

Repeated administration of haloperidol (HAL) and olanzapine (OLZ) causes a progressively enhanced disruption of the conditioned avoidance response (CAR) and a progressively enhanced inhibition of phencyclidine (PCP)-induced hyperlocomotion in rats (termed antipsychotic sensitization). Both actions are thought to reflect intrinsic antipsychotic activity. The present study examined the extent to which antipsychotic-induced sensitization in one model (e.g. CAR) can be transferred or maintained in another (e.g. PCP hyperlocomotion) as a means of investigating the contextual and behavioral controls of antipsychotic sensitization. Well-trained male Sprague-Dawley rats were first repeatedly tested in the CAR or the PCP (3.2 mg/kg, subcutaneously) hyperlocomotion model under HAL or OLZ for 5 consecutive days. Then they were switched to the other model and tested for the expression of sensitization. Finally, all rats were switched back to the original model and retested for the expression of sensitization. Repeated HAL or OLZ treatment progressively disrupted avoidance responding and decreased PCP-induced hyperlocomotion, indicating a robust sensitization. When tested in a different model, rats previously treated with HAL or OLZ did not show a stronger inhibition of CAR-induced or PCP-induced hyperlocomotion than those treated with these drugs for the first time; however, they did show such an effect when tested in the original model in which they received repeated antipsychotic treatment. These findings suggest that the expression of antipsychotic sensitization is strongly influenced by the testing environment and/or selected behavioral response under certain experimental conditions. Distinct contextual cues and behavioral responses may develop an association with unconditional drug effects through a Pavlovian conditioning process. They may also serve as occasion setters to modulate the expression of sensitized responses. As antipsychotic sensitization mimics the clinical effects of antipsychotic treatment, understanding the neurobiological mechanisms of antipsychotic sensitization and its contextual control would greatly enhance our understanding of the psychological and neurochemical nature of antipsychotic treatment in the clinic.

Contextual and behavioral control of antipsychotic sensitization induced by haloperidol and olanzapine

PubMed Central

Zhang, Chen; Li, Ming

2011-01-01

Repeated administration of haloperidol and olanzapine causes a progressively enhanced disruption of conditioned avoidance response (CAR) and a progressively enhanced inhibition of phencyclidine (PCP)-induced hyperlocomotion in rats (termed antipsychotic sensitization). Both actions are thought to reflect intrinsic antipsychotic activity. The present study examined to the extent to which antipsychotic-induced sensitization in one model (e.g. CAR) can be transferred or maintained in another (e.g. PCP hyperlocomotion) as a means of investigating the contextual and behavioral controls of antipsychotic sensitization. Well-trained male Sprague-Dawley rats were first repeatedly tested in the CAR or PCP (3.2 mg/kg, sc) hyperlocomotion model under haloperidol or olanzapine for five consecutive days. Then they were switched to the other model and tested for the expression of sensitization. Finally, all rats were switched back to the original model and retested for the expression of sensitization. Repeated haloperidol or olanzapine treatment progressively disrupted avoidance responding and decreased PCP-induced hyperlocomotion, indicating a robust sensitization. When tested in a different model, rats previously treated with haloperidol or olanzapine did not show a stronger inhibition of CAR or PCP-induced hyperlocomotion than those treated with these drugs for the first time; however, they did show such an effect when tested in the original model in which they received repeated antipsychotic treatment. These findings suggest that the expression of antipsychotic sensitization is strongly influenced by the testing environment and/or selected behavioral response under certain experimental conditions. Distinct contextual cues and behavioral responses may enter an association with unconditional drug effects via a Pavlovian conditioning process. They may also serve as occasion-setters to modulate the expression of sensitized responses. Because antipsychotic sensitization mimics clinical effects of antipsychotic treatment, understanding the neurobiological mechanisms of antipsychotic sensitization and its contextual control would greatly enhance our understanding of the psychological and neurochemical nature of antipsychotic treatment in the clinic. PMID:22157143

Impact self-excited vibrations of linear motor

NASA Astrophysics Data System (ADS)

Zhuravlev, V. Ph.

2010-08-01

Impact self-exciting vibration modes in a linear motor of a monorail car are studied. Existence and stability conditions of self-exciting vibrations are found. Ways of avoiding the vibrations are discussed.

40 CFR 201.25 - Measurement location and weather conditions for measurement on receiving property of the noise of...

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 26 2013-07-01 2013-07-01 false Measurement location and weather conditions for measurement on receiving property of the noise of retarders, car coupling, locomotive load... EQUIPMENT; INTERSTATE RAIL CARRIERS Measurement Criteria § 201.25 Measurement location and weather...

40 CFR 201.25 - Measurement location and weather conditions for measurement on receiving property of the noise of...

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 25 2011-07-01 2011-07-01 false Measurement location and weather conditions for measurement on receiving property of the noise of retarders, car coupling, locomotive load... EQUIPMENT; INTERSTATE RAIL CARRIERS Measurement Criteria § 201.25 Measurement location and weather...

40 CFR 201.25 - Measurement location and weather conditions for measurement on receiving property of the noise of...

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 25 2014-07-01 2014-07-01 false Measurement location and weather conditions for measurement on receiving property of the noise of retarders, car coupling, locomotive load... EQUIPMENT; INTERSTATE RAIL CARRIERS Measurement Criteria § 201.25 Measurement location and weather...

40 CFR 201.25 - Measurement location and weather conditions for measurement on receiving property of the noise of...

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 26 2012-07-01 2011-07-01 true Measurement location and weather conditions for measurement on receiving property of the noise of retarders, car coupling, locomotive load... EQUIPMENT; INTERSTATE RAIL CARRIERS Measurement Criteria § 201.25 Measurement location and weather...

Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables

NASA Astrophysics Data System (ADS)

Barnett, Lionel; Barrett, Adam B.; Seth, Anil K.

2009-12-01

Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. While it has been recognized that the two concepts must be related, the exact relationship has until now not been formally described. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.

iVAR: a program for imputing missing data in multivariate time series using vector autoregressive models.

PubMed

Liu, Siwei; Molenaar, Peter C M

2014-12-01

This article introduces iVAR, an R program for imputing missing data in multivariate time series on the basis of vector autoregressive (VAR) models. We conducted a simulation study to compare iVAR with three methods for handling missing data: listwise deletion, imputation with sample means and variances, and multiple imputation ignoring time dependency. The results showed that iVAR produces better estimates for the cross-lagged coefficients than do the other three methods. We demonstrate the use of iVAR with an empirical example of time series electrodermal activity data and discuss the advantages and limitations of the program.

Maximum likelihood estimation for periodic autoregressive moving average models

USGS Publications Warehouse

Vecchia, A.V.

1985-01-01

A useful class of models for seasonal time series that cannot be filtered or standardized to achieve second-order stationarity is that of periodic autoregressive moving average (PARMA) models, which are extensions of ARMA models that allow periodic (seasonal) parameters. An approximation to the exact likelihood for Gaussian PARMA processes is developed, and a straightforward algorithm for its maximization is presented. The algorithm is tested on several periodic ARMA(1, 1) models through simulation studies and is compared to moment estimation via the seasonal Yule-Walker equations. Applicability of the technique is demonstrated through an analysis of a seasonal stream-flow series from the Rio Caroni River in Venezuela.

TaiWan Ionospheric Model (TWIM) prediction based on time series autoregressive analysis

NASA Astrophysics Data System (ADS)

Tsai, L. C.; Macalalad, Ernest P.; Liu, C. H.

2014-10-01

As described in a previous paper, a three-dimensional ionospheric electron density (Ne) model has been constructed from vertical Ne profiles retrieved from the FormoSat3/Constellation Observing System for Meteorology, Ionosphere, and Climate GPS radio occultation measurements and worldwide ionosonde foF2 and foE data and named the TaiWan Ionospheric Model (TWIM). The TWIM exhibits vertically fitted α-Chapman-type layers with distinct F2, F1, E, and D layers, and surface spherical harmonic approaches for the fitted layer parameters including peak density, peak density height, and scale height. To improve the TWIM into a real-time model, we have developed a time series autoregressive model to forecast short-term TWIM coefficients. The time series of TWIM coefficients are considered as realizations of stationary stochastic processes within a processing window of 30 days. These autocorrelation coefficients are used to derive the autoregressive parameters and then forecast the TWIM coefficients, based on the least squares method and Lagrange multiplier technique. The forecast root-mean-square relative TWIM coefficient errors are generally <30% for 1 day predictions. The forecast TWIM values of foE and foF2 values are also compared and evaluated using worldwide ionosonde data.

Principal dynamic mode analysis of neural mass model for the identification of epileptic states

NASA Astrophysics Data System (ADS)

Cao, Yuzhen; Jin, Liu; Su, Fei; Wang, Jiang; Deng, Bin

2016-11-01

The detection of epileptic seizures in Electroencephalography (EEG) signals is significant for the diagnosis and treatment of epilepsy. In this paper, in order to obtain characteristics of various epileptiform EEGs that may differentiate different states of epilepsy, the concept of Principal Dynamic Modes (PDMs) was incorporated to an autoregressive model framework. First, the neural mass model was used to simulate the required intracerebral EEG signals of various epileptiform activities. Then, the PDMs estimated from the nonlinear autoregressive Volterra models, as well as the corresponding Associated Nonlinear Functions (ANFs), were used for the modeling of epileptic EEGs. The efficient PDM modeling approach provided physiological interpretation of the system. Results revealed that the ANFs of the 1st and 2nd PDMs for the auto-regressive input exhibited evident differences among different states of epilepsy, where the ANFs of the sustained spikes' activity encountered at seizure onset or during a seizure were the most differentiable from that of the normal state. Therefore, the ANFs may be characteristics for the classification of normal and seizure states in the clinical detection of seizures and thus provide assistance for the diagnosis of epilepsy.

Modeling Polio Data Using the First Order Non-Negative Integer-Valued Autoregressive, INAR(1), Model

NASA Astrophysics Data System (ADS)

Vazifedan, Turaj; Shitan, Mahendran

Time series data may consists of counts, such as the number of road accidents, the number of patients in a certain hospital, the number of customers waiting for service at a certain time and etc. When the value of the observations are large it is usual to use Gaussian Autoregressive Moving Average (ARMA) process to model the time series. However if the observed counts are small, it is not appropriate to use ARMA process to model the observed phenomenon. In such cases we need to model the time series data by using Non-Negative Integer valued Autoregressive (INAR) process. The modeling of counts data is based on the binomial thinning operator. In this paper we illustrate the modeling of counts data using the monthly number of Poliomyelitis data in United States between January 1970 until December 1983. We applied the AR(1), Poisson regression model and INAR(1) model and the suitability of these models were assessed by using the Index of Agreement(I.A.). We found that INAR(1) model is more appropriate in the sense it had a better I.A. and it is natural since the data are counts.

[Determining the car driver's position at the moment of the frontal crash with a moving KAMAZ truck].

PubMed

Gusarov, A A; Fetisov, V A; Smirenin, S A

2016-01-01

This article is designed to report the results of the comprehensive forensic medical and autotechnical expertise for determining the positions of the driver and the first seat passenger of the GAS-3110 car at the moment of the frontal crash with a KAMAZ-5312 truck. The comparative analysis of the injuries in two subjects one of whom died as a result of the given accident made it possible to conclude that he had occupied the driver's seat in the car. The differential diagnosis was based on the peculiarities of the injuries to the upper extremities with the predominance of the most severe wounds at the right side of the body. Also taken into consideration were the specific conditions of the given frontal collision, design of the GAS-3110 passenger compartment, winter season, night time, and possible neglect of the passive safety means, etc.

An extended car-following model at un-signalized intersections under V2V communication environment

PubMed Central

Wang, Tao; Li, Peng

2018-01-01

An extended car-following model is proposed in this paper to analyze the impacts of V2V (vehicle to vehicle) communication on the micro driving behavior at the un-signalized intersection. A four-leg un-signalized intersection with twelve streams (left-turn, through movement, and right turn from each leg) is used. The effect of the guidance strategy on the reduction of the rate of stops and total delay is explored by comparing the proposed model and the traditional FVD car-following model. The numerical results illustrate that potential conflicts between vehicles can be predicted and some stops can be avoided by decelerating in advance. The driving comfort and traffic efficiency can be improved accordingly. More benefits could be obtained under the long communication range, low to medium traffic density, and simple traffic pattern conditions. PMID:29425243

Early detection of ventricular tachycardia with sending messages to cell phone

NASA Astrophysics Data System (ADS)

Ramirez, L. J.; Lozano, F. A.; Rondon, C. R.

2011-09-01

Sustained ventricular tachycardia (VTs) can be asymptomatic for some people, but for other is deadly because it is a major cause of sudden cardiac death [1]. Some patients may present this arrhythmia, and even so, they decide to drive car increasing the likelihood of VTs, putting at risk not only his life but that of the other drivers. We developed a system for early detection of VTs, consisting of EKG sensors, a card of processing and a cell phone, which detects this arrhythmia, gives an alarm signal to the driver, and it simultaneously sending to text messages a specialist doctor and a relative or friend, all in real time. This design was conditioned to the car, is light and comfortable, that allowed that work of car's driver without discomfort. This system will save lives, since in case of emergency sends a help message, no matter where you are in the driver.

Stochastic Car-Following Model for Explaining Nonlinear Traffic Phenomena

NASA Astrophysics Data System (ADS)

Meng, Jianping; Song, Tao; Dong, Liyun; Dai, Shiqiang

There is a common time parameter for representing the sensitivity or the lag (response) time of drivers in many car-following models. In the viewpoint of traffic psychology, this parameter could be considered as the perception-response time (PRT). Generally, this parameter is set to be a constant in previous models. However, PRT is actually not a constant but a random variable described by the lognormal distribution. Thus the probability can be naturally introduced into car-following models by recovering the probability of PRT. For demonstrating this idea, a specific stochastic model is constructed based on the optimal velocity model. By conducting simulations under periodic boundary conditions, it is found that some important traffic phenomena, such as the hysteresis and phantom traffic jams phenomena, can be reproduced more realistically. Especially, an interesting experimental feature of traffic jams, i.e., two moving jams propagating in parallel with constant speed stably and sustainably, is successfully captured by the present model.

Effects of Seawater Salinity and Temperature on Growth and Pigment Contents in Hypnea cervicornis J. Agardh (Gigartinales, Rhodophyta)

PubMed Central

Ding, Lanping; Ma, Yuanyuan; Huang, Bingxin; Chen, Shanwen

2013-01-01

This study simulated outdoor environmental living conditions and observed the growth rates and changes of several photosynthetic pigments (Chl a, Car, PE, and PC) in Hypnea cervicornis J. Agardh (Gigartinales, Rhodophyta) by setting up different ranges of salinity (25, 30, 35, 40, 45, and 50) and temperature (15, 20, 25, and 30°C). At conditions of culture, the results are as follows. (1) Changes in salinity and temperature have significant effects on the growth of H. cervicornis. The growth rates first increase then decrease as the temperature increases, while growth tends to decline as salinity increases. The optimum salinity and temperature conditions for growth are 25 and 25°C, respectively. (2) Salinity and temperature have significant or extremely significant effects on photosynthetic pigments (Chl a, Car, PE, and PC) in H. cervicornis. The results of this study are advantageous to ensure propagation and economic development of this species in the southern sea area of China. PMID:24350276

Light-induced carotenogenesis in Myxococcus xanthus: evidence that CarS acts as an anti-repressor of CarA.

PubMed

Whitworth, D E; Hodgson, D A

2001-11-01

In the bacterium Myxococcus xanthus, carotenoids are produced in response to illumination, as a result of expression of the crt carotenoid biosynthesis genes. The majority of crt genes are clustered in the crtEBDC operon, which is repressed in the dark by CarA. Genetic data suggest that, in the light, CarS is synthesized and achieves activation of the crtEBDC operon by removing the repressive action of CarA. As CarS contains no known DNA-binding motif, the relief of CarA-mediated repression was postulated to result from a direct interaction between these two proteins. Use of the yeast two-hybrid system demonstrated direct interaction between CarA and CarS. The two-hybrid system also implied that CarA and, possibly, CarS are capable of homodimerization. Direct evidence for CarS anti-repressor action was provided in vitro. A glutathione S-transferase (GST)-CarA protein fusion was shown to bind specifically to a palindromic operator sequence within the crtEBDC promoter. CarA was prevented from binding to its operator, and prebound CarA was removed by the addition of purified CarS. CarS is therefore an anti-repressor.

Genetic Testing for Inherited Heart Disease

MedlinePlus

... are also inherited heart conditions that affect the electric system of the heart, causing abnormal heart rhythms ... mistakenly labeled as a heart attack, drowning, or car accident. The sudden death of a previously healthy ...

Speech Auditory Alerts Promote Memory for Alerted Events in a Video-Simulated Self-Driving Car Ride.

PubMed

Nees, Michael A; Helbein, Benji; Porter, Anna

2016-05-01

Auditory displays could be essential to helping drivers maintain situation awareness in autonomous vehicles, but to date, few or no studies have examined the effectiveness of different types of auditory displays for this application scenario. Recent advances in the development of autonomous vehicles (i.e., self-driving cars) have suggested that widespread automation of driving may be tenable in the near future. Drivers may be required to monitor the status of automation programs and vehicle conditions as they engage in secondary leisure or work tasks (entertainment, communication, etc.) in autonomous vehicles. An experiment compared memory for alerted events-a component of Level 1 situation awareness-using speech alerts, auditory icons, and a visual control condition during a video-simulated self-driving car ride with a visual secondary task. The alerts gave information about the vehicle's operating status and the driving scenario. Speech alerts resulted in better memory for alerted events. Both auditory display types resulted in less perceived effort devoted toward the study tasks but also greater perceived annoyance with the alerts. Speech auditory displays promoted Level 1 situation awareness during a simulation of a ride in a self-driving vehicle under routine conditions, but annoyance remains a concern with auditory displays. Speech auditory displays showed promise as a means of increasing Level 1 situation awareness of routine scenarios during an autonomous vehicle ride with an unrelated secondary task. © 2016, Human Factors and Ergonomics Society.

Forecasting conditional climate-change using a hybrid approach

USGS Publications Warehouse

Esfahani, Akbar Akbari; Friedel, Michael J.

2014-01-01

A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.

Static load simulation of steering knuckle for a formula student race car

NASA Astrophysics Data System (ADS)

Saputro, Bagus Aulia; Ubaidillah, Triono, Dicky Agus; Pratama, Dzaky Roja; Cahyono, Sukmaji Indro; Imaduddin, Fitrian

2018-02-01

This research aims to determine the stress distribution which occurs on the steering knuckle and to define its safety factor number. Steering knuckle is the most critical part of a car's steering system. Steering knuckle supports the tie rod, brake caliper, and the wheels to provide stability. Steering knuckle withstands the load which given on the front wheels and functions as the wheel's axis. Balljoint and king support the rotation of the suspension arm. When the car is in idle position, knuckle hold the weight of the car, it gets braking force when it's braking and cornering. Knuckle is designed to have the strength that could withstand load and to have a good safety factor value. Knuckle is designed using Fusion software then simulated using Fusion simulation software with a static load, moment braking force, and cornering force as the loads in this simulation. The simulation works in ideal condition. The result of this simulation is satisfying. This simulation produces a maximum displacement of 0.01281mm, the maximum shear stress is 3.707 MPa on the stub hole, and the safety factor is 5.24. The material used for this product is mild steel AISI 1018.

Development and field performance of indy race car head impact padding.

PubMed

Melvin, J W; Bock, H; Anderson, K; Gideon, T

2001-11-01

The close-fitting cockpit of the modern Indy car single seat race car has the potential to provide a high level of head and neck impact protection in rear and side impacts. Crash investigation has shown that a wide variety of materials have been used as the padding for these cockpits and, as a result, produced varying outcomes in crashes. Additionally, these pads have not always been positioned for optimal performance. The purpose of this study was to investigate the head impact performance of a variety of energy-absorbing padding materials under impact conditions typical of Indy car rear impacts and to identify superior materials and methods of improving their performance as race car head pads. An extensive series of tests with the helmeted Hybrid III test dummy head and neck on an impact mini-sled was conducted to explore head padding concepts. Following this, a performance specification for a simplified impact test using a rigid headform that simulates the helmeted head was developed and recommendations for performance levels of head padding based on biomechanical data on helmeted head impacts were made. In 1997, during the time that the head pad research was being performed, the Indy Racing League introduced a new chassis specification for their cars. There were a number of rear- and side-impact crashes during that season that resulted in seven severe head injuries. Examples of the head padding in those cars were included in the experimental study. The results of the head pad research were used to specify new padding materials that met the new biomechanical criteria. The placement of the head pads was also changed for better location of the padding. These changes instituted in 1998 have reduced the number of head injuries in crashes similar to or more severe than those of 1997 and have resulted in only occasional moderate head injuries (concussions) in the 1998 and 1999 seasons.

Spatial patterns of multidrug resistant tuberculosis and relationships to socio-economic, demographic and household factors in northwest Ethiopia.

PubMed

Alene, Kefyalew Addis; Viney, Kerri; McBryde, Emma S; Clements, Archie C A

2017-01-01

Understanding the geographical distribution of multidrug-resistant tuberculosis (MDR-TB) in high TB burden countries such as Ethiopia is crucial for effective control of TB epidemics in these countries, and thus globally. We present the first spatial analysis of multidrug resistant tuberculosis, and its relationship to socio-economic, demographic and household factors in northwest Ethiopia. An ecological study was conducted using data on patients diagnosed with MDR-TB at the University of Gondar Hospital MDR-TB treatment centre, for the period 2010 to 2015. District level population data were extracted from the Ethiopia National and Regional Census Report. Spatial autocorrelation was explored using Moran's I statistic, Local Indicators of Spatial Association (LISA), and the Getis-Ord statistics. A multivariate Poisson regression model was developed with a conditional autoregressive (CAR) prior structure, and with posterior parameters estimated using a Bayesian Markov chain Monte Carlo (MCMC) simulation approach with Gibbs sampling, in WinBUGS. A total of 264 MDR-TB patients were included in the analysis. The overall crude incidence rate of MDR-TB for the six-year period was 3.0 cases per 100,000 population. The highest incidence rate was observed in Metema (21 cases per 100,000 population) and Humera (18 cases per 100,000 population) districts; whereas nine districts had zero cases. Spatial clustering of MDR-TB was observed in districts located in the Ethiopia-Sudan and Ethiopia-Eritrea border regions, where large numbers of seasonal migrants live. Spatial clustering of MDR-TB was positively associated with urbanization (RR: 1.02; 95%CI: 1.01, 1.04) and the percentage of men (RR: 1.58; 95% CI: 1.26, 1.99) in the districts; after accounting for these factors there was no residual spatial clustering. Spatial clustering of MDR-TB, fully explained by demographic factors (urbanization and percent male), was detected in the border regions of northwest Ethiopia, in locations where seasonal migrants live and work. Cross-border initiatives including options for mobile TB treatment and follow up are important for the effective control of MDR-TB in the region.

Forecast Model Analysis for the Morbidity of Tuberculosis in Xinjiang, China

PubMed Central

Zheng, Yan-Ling; Zhang, Li-Ping; Zhang, Xue-Liang; Wang, Kai; Zheng, Yu-Jian

2015-01-01

Tuberculosis is a major global public health problem, which also affects economic and social development. China has the second largest burden of tuberculosis in the world. The tuberculosis morbidity in Xinjiang is much higher than the national situation; therefore, there is an urgent need for monitoring and predicting tuberculosis morbidity so as to make the control of tuberculosis more effective. Recently, the Box-Jenkins approach, specifically the autoregressive integrated moving average (ARIMA) model, is typically applied to predict the morbidity of infectious diseases; it can take into account changing trends, periodic changes, and random disturbances in time series. Autoregressive conditional heteroscedasticity (ARCH) models are the prevalent tools used to deal with time series heteroscedasticity. In this study, based on the data of the tuberculosis morbidity from January 2004 to June 2014 in Xinjiang, we establish the single ARIMA (1, 1, 2) (1, 1, 1)12 model and the combined ARIMA (1, 1, 2) (1, 1, 1)12-ARCH (1) model, which can be used to predict the tuberculosis morbidity successfully in Xinjiang. Comparative analyses show that the combined model is more effective. To the best of our knowledge, this is the first study to establish the ARIMA model and ARIMA-ARCH model for prediction and monitoring the monthly morbidity of tuberculosis in Xinjiang. Based on the results of this study, the ARIMA (1, 1, 2) (1, 1, 1)12-ARCH (1) model is suggested to give tuberculosis surveillance by providing estimates on tuberculosis morbidity trends in Xinjiang, China. PMID:25760345

A short-term ensemble wind speed forecasting system for wind power applications

NASA Astrophysics Data System (ADS)

Baidya Roy, S.; Traiteur, J. J.; Callicutt, D.; Smith, M.

2011-12-01

This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 hour ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather Research and Forecasting Single Column Model (WRFSCM) and a persistence model. The ensemble is calibrated against observations for a 2 month period (June-July, 2008) at a potential wind farm site in Illinois using the Bayesian Model Averaging (BMA) technique. The forecasting system is evaluated against observations for August 2008 at the same site. The calibrated ensemble forecasts significantly outperform the forecasts from the uncalibrated ensemble while significantly reducing forecast uncertainty under all environmental stability conditions. The system also generates significantly better forecasts than persistence, autoregressive (AR) and autoregressive moving average (ARMA) models during the morning transition and the diurnal convective regimes. This forecasting system is computationally more efficient than traditional numerical weather prediction models and can generate a calibrated forecast, including model runs and calibration, in approximately 1 minute. Currently, hour-ahead wind speed forecasts are almost exclusively produced using statistical models. However, numerical models have several distinct advantages over statistical models including the potential to provide turbulence forecasts. Hence, there is an urgent need to explore the role of numerical models in short-term wind speed forecasting. This work is a step in that direction and is likely to trigger a debate within the wind speed forecasting community.

A frequency domain global parameter estimation method for multiple reference frequency response measurements

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

A method of using the matrix Auto-Regressive Moving Average (ARMA) model in the Laplace domain for multiple-reference global parameter identification is presented. This method is particularly applicable to the area of modal analysis where high modal density exists. The method is also applicable when multiple reference frequency response functions are used to characterise linear systems. In order to facilitate the mathematical solution, the Forsythe orthogonal polynomial is used to reduce the ill-conditioning of the formulated equations and to decouple the normal matrix into two reduced matrix blocks. A Complex Mode Indicator Function (CMIF) is introduced, which can be used to determine the proper order of the rational polynomials.

Forecasting vegetation greenness with satellite and climate data

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2004-01-01

A new and unique vegetation greenness forecast (VGF) model was designed to predict future vegetation conditions to three months through the use of current and historical climate data and satellite imagery. The VGF model is implemented through a seasonality-adjusted autoregressive distributed-lag function, based on our finding that the normalized difference vegetation index is highly correlated with lagged precipitation and temperature. Accurate forecasts were obtained from the VGF model in Nebraska grassland and cropland. The regression R2 values range from 0.97-0.80 for 2-12 week forecasts, with higher R2 associated with a shorter prediction. An important application would be to produce real-time forecasts of greenness images.

The relationship between trading volumes, number of transactions, and stock volatility in GARCH models

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya; Chen, Ting Ting

2016-08-01

We examine the relationship between trading volumes, number of transactions, and volatility using daily stock data of the Tokyo Stock Exchange. Following the mixture of distributions hypothesis, we use trading volumes and the number of transactions as proxy for the rate of information arrivals affecting stock volatility. The impact of trading volumes or number of transactions on volatility is measured using the generalized autoregressive conditional heteroscedasticity (GARCH) model. We find that the GARCH effects, that is, persistence of volatility, is not always removed by adding trading volumes or number of transactions, indicating that trading volumes and number of transactions do not adequately represent the rate of information arrivals.

Markov Switching Autoregressive Conditional Heteroscedasticity (SWARCH) Model to Detect Financial Crisis in Indonesia Based on Import and Export Indicators

NASA Astrophysics Data System (ADS)

Sugiyanto; Zukhronah, Etik; Susanti, Yuliana; Rahma Dwi, Sisca

2017-06-01

A country is said to be a crisis when the financial system is experiencing a disruption that affects systems that can not function efficiently. The performance efficiency of macroeconomic indicators especially in imports and exports can be used to detect the financial crisis in Indonesia. Based on the import and export indicators from 1987 to 2015, the movement of these indicators can be modelled using SWARCH three states. The results showed that SWARCH (3,1) model was able to detect the crisis that occurred in Indonesia in 1997 and 2008. Using this model, it can be concluded that Indonesia is prone to financial crisis in 2016.

Quenching of chlorophyll a singlets and triplets by carotenoids in light-harvesting complex of photosystem II: comparison of aggregates with trimers

NASA Astrophysics Data System (ADS)

Naqvi, K. Razi; Melø, T. B.; Raju, B. Bangar; Jávorfi, Tamás; Simidjiev, Ilian; Garab, Gyözö

1997-12-01

Laser-induced changes in the absorption spectra of isolated light-harvesting chlorophyll a/ b complex (LHC II) associated with photosystem II of higher plants have been recorded under anaerobic conditions and at ambient temperature by using multichannel detection with sub-microsecond time resolution. Difference spectra (Δ A) of LHC II aggregates have been found to differ from the corresponding spectra of trimers on two counts: (i) in the aggregates, the carotenoid (Car) triplet-triplet absorption band (Δ A>0) is red-shifted and broader; and (ii) the features attributable to the perturbation of the Qy band of a chlorophyll a (Chl a) by a nearby Car triplet are more pronounced, than in trimers. Aggregation, which is known to be accompanied by a reduction in the fluorescence yield of Chl a, is shown to cause a parallel decline in the triplet formation yield of Chl a; on the other hand, the efficiency (100%) of Chl a-to-Car transfer of triplet energy and the lifetime (9.3 μs) of Car triplets are not affected by aggregation. These findings are rationalized by postulating that the antenna Cars transact, besides light-harvesting and photoprotection, a third process: energy dissipation within the antenna. The suggestion is advanced that luteins, which are buried inside the LHC II monomers, as well as the other, peripheral, xanthophylls (neoxanthin and violaxanthin) quench the excited singlet state of Chl a by catalyzing internal conversion, a decay channel that competes with fluorescence and intersystem crossing; support for this explanation is presented by recalling reports of similar behaviour in bichromophoric model compounds in which one moiety is a Car and the other a porphyrin or a pyropheophorbide.

Physical demands, injuries, and conditioning practices of stock car drivers.

PubMed

Ebben, William P; Suchomel, Timothy J

2012-05-01

The purpose of this study was to assess the physical demands, injuries, and conditioning practices of stock car drivers. Forty stock car drivers from 27 states in the United States participated in the interviews for 43.9 ± 13.9 minutes. The interviews examined background information, the physical demands of racing, injuries associated with racing, and the athletic and fitness background and practices of the subjects. Numerical data were analyzed using Pearson's correlation coefficients. Responses to open-ended questions were analyzed using inductive content analysis. Results revealed significant correlation between track points standings and the length of the resistance training sessions (R = -0.71, p = 0.002) and subject self-assessment of their fitness (R = -0.53, p = 0.045). Results also revealed that "upper-body strength" was identified as the most important physical demand. Extreme fatigue was the most common feeling after a demanding race. Subjects reported that shoulder fatigue was the most common form of muscle soreness experienced after a race. Back and torso injuries were the most common injury, although head injuries most frequently required medical attention. The subjects' biggest fear was fire, followed closely by head and neck injury. The bench press and running were the most commonly performed resistance training and cardiovascular exercises, respectively. Subjects reported that their highest motivation for training was to improve their racing performance. Many subjects had athletic backgrounds with football identified as the sport they had most commonly participated in. This study provides additional detailed information. Results of this study can assist strength and conditioning professionals in the development of strength and conditioning programs for performance enhancement and injury prevention that are specific to the needs of this population of athletes.

Nonlinear GARCH model and 1 / f noise

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Ruseckas, J.

2015-06-01

Auto-regressive conditionally heteroskedastic (ARCH) family models are still used, by practitioners in business and economic policy making, as a conditional volatility forecasting models. Furthermore ARCH models still are attracting an interest of the researchers. In this contribution we consider the well known GARCH(1,1) process and its nonlinear modifications, reminiscent of NGARCH model. We investigate the possibility to reproduce power law statistics, probability density function and power spectral density, using ARCH family models. For this purpose we derive stochastic differential equations from the GARCH processes in consideration. We find the obtained equations to be similar to a general class of stochastic differential equations known to reproduce power law statistics. We show that linear GARCH(1,1) process has power law distribution, but its power spectral density is Brownian noise-like. However, the nonlinear modifications exhibit both power law distribution and power spectral density of the 1 /fβ form, including 1 / f noise.

Simulation of high-energy radiation belt electron fluxes using NARMAX-VERB coupled codes

PubMed Central

Pakhotin, I P; Drozdov, A Y; Shprits, Y Y; Boynton, R J; Subbotin, D A; Balikhin, M A

2014-01-01

This study presents a fusion of data-driven and physics-driven methodologies of energetic electron flux forecasting in the outer radiation belt. Data-driven NARMAX (Nonlinear AutoRegressive Moving Averages with eXogenous inputs) model predictions for geosynchronous orbit fluxes have been used as an outer boundary condition to drive the physics-based Versatile Electron Radiation Belt (VERB) code, to simulate energetic electron fluxes in the outer radiation belt environment. The coupled system has been tested for three extended time periods totalling several weeks of observations. The time periods involved periods of quiet, moderate, and strong geomagnetic activity and captured a range of dynamics typical of the radiation belts. The model has successfully simulated energetic electron fluxes for various magnetospheric conditions. Physical mechanisms that may be responsible for the discrepancies between the model results and observations are discussed. PMID:26167432

Conditional parametric models for storm sewer runoff

NASA Astrophysics Data System (ADS)

Jonsdottir, H.; Nielsen, H. Aa; Madsen, H.; Eliasson, J.; Palsson, O. P.; Nielsen, M. K.

2007-05-01

The method of conditional parametric modeling is introduced for flow prediction in a sewage system. It is a well-known fact that in hydrological modeling the response (runoff) to input (precipitation) varies depending on soil moisture and several other factors. Consequently, nonlinear input-output models are needed. The model formulation described in this paper is similar to the traditional linear models like final impulse response (FIR) and autoregressive exogenous (ARX) except that the parameters vary as a function of some external variables. The parameter variation is modeled by local lines, using kernels for local linear regression. As such, the method might be referred to as a nearest neighbor method. The results achieved in this study were compared to results from the conventional linear methods, FIR and ARX. The increase in the coefficient of determination is substantial. Furthermore, the new approach conserves the mass balance better. Hence this new approach looks promising for various hydrological models and analysis.

Compatibility problems in frontal, side, single car collisions and car-to-pedestrian accidents in Japan.

PubMed

Mizuno, K; Kajzer, J

1999-07-01

Compatibility problems in car-to-car frontal, side, single car and car-to-pedestrian collisions in Japan are discussed using traffic accident data. The number of serious and fatal injuries is investigated for the subject car and other cars, which are categorized by their class and mass. The aggressivity of the cars is calculated by the number of fatalities, fatality rates and by the number of car registrations. The results show that in car-to-car frontal collisions, cars with a mass of 1150 kg are the most compatible among the current car population. In both car-to-car frontal and side collisions, the sports utility vehicle and mini car are found to be the most incompatible car types with high and low aggressivity, respectively. On the other hand, the accident data show that the wagon and midsize sedan are the most compatible car types. The compatibility of fixed objects in the road environment with cars and cars with pedestrians is also discussed. In a single car collision with a fixed object, the guardrail is the most compatible object and can reduce the fatality rate on prefecture roads by about 60%. The front geometry of the car has large effect on compatibility with a pedestrian.

Fact Sheet: Protection of the Stratospheric Ozone: New Substitute in the Motor Vehicle Air Conditioning Sector under the Significant New Alternatives Policy (SNAP) Program

EPA Pesticide Factsheets

Under the Significant New Alternatives Policy (SNAP) program, EPA is listing HFO-1234yf as an acceptable substitute for ozone depleting substances (ODS) in motor vehicle air conditioning (MVAC) systems in new cars and other light duty-vehicles and is speci

Use of Energy Efficient Sensor Networks to Enhance Dynamic Data Gathering Systems: A Comparative Study between Bluetooth and ZigBee.

PubMed

Gheorghiu, Razvan Andrei; Iordache, Valentin

2018-06-03

As road traffic conditions worsen due to the constantly increasing number of cars, traffic management systems are struggling to provide a suitable environment, by gathering all the relevant information from the road network. However, in most cases these are obtained via traffic detectors placed near road junctions, thus providing no information on the conditions in between. A large-scale sensor network using detectors on the majority of vehicles would certainly be capable of providing useful data, but has two major impediments: the equipment installed on the vehicles should be cheap enough (assuming the willingness of private car owners to be a part of the network) and be capable of transferring the required amount of data in due time, as the vehicle passes by the road side unit that acts as interface with the traffic management system. These restrictions reduce the number of technologies that can be used. In this article a series of comprehensive tests have been performed to evaluate the Bluetooth and ZigBee protocols for this purpose from many points of view: handshake time, static and dynamic data transfer (in laboratory conditions and in real traffic conditions). An assessment of the environmental conditions (during tests and probable to be encountered in real conditions) was also provided.

High flow rate development: process optimization using megasonic immersion development (MID)

NASA Astrophysics Data System (ADS)

Courboin, Daniel; Choi, Jong Woo; Jung, Sang Hyun; Baek, Seung Hee; Kim, Lee Ju

2004-12-01

In previous study the high impact of development by-products on Critical Dimension (CD) through the microloading effect has been demonstrated for a Novolak resist. In this paper, through further tests involving Chemically Amplified Resist (CAR) and Novolak resist, the microloading effect of development is characterized and tentative mechanism is presented. Megasonic Immersion Development (MID), a high flow rate development technique similar to the Proximity Gap Suction Development (PGSD), was used and compared with spin spray development and puddle development. On TOK IP3600, a Novolak resist, we have explored a wide range of process conditions with MID. Developer temperature was varied from 5°C to 40°C with TMAH developer concentration of 1.9% and 2.38% resulting in an isofocal dose range of 90mJ to 190mJ. Exposure Focus Matrix (EFM) with a specific microloading pattern and resist cross sections were performed. The best conditions are quite far from the standard process advised by the resist supplier. Very nice standing wave profile was obtained at high temperature development. On CAR, JEOL 9000MVII, a 50kV e-beam vector scan tool, and ETEC ALTA 4300, a DUV raster scan tool, were used with different develop process techniques including MID. FujiFilm Arch FEP-171 positive CAR and Sumitomo NEB-22 negative CAR were used on 50kV writing tool. Sumitomo PEK-130 was used on DUV writing tool. FEP-171 and PEK-1300 show microloading effect on high density patterns but not NEB-22. MID shows also improved reproduction of develop features in the chrome and a 20% improvement of CD uniformity. The results of this study seem to indicate that a closer look in their development process is needed for 90nm and 65nm technologies.

Emissions from diesel and stratified charge powered cars. Final report

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

Springer, K.J.

A total of ten passenger cars, four powered by diesel engines, two by stratified charge gasoline engines, one by a stratified charge operating on gasoline and diesel fuel, two by control equipped conventional engines, and one powered by a gas turbine, have been subjected to a wide variety of emissions evaluations. The vehicles, all late model, low mileage, included a Nissan Datsun, a Mercedes 220D, a Peugeot 504D, an Opel Rekord 2100D, a standard Capri, a stratified charge (PROCO) Capri, a low emission prototype Ford LTD, the Texaco TCCS stratified charge powered Cricket operated on gasoline and on diesel fuel,more » a Honda CVCC stratified charge, and a Chrysler gas turbine car. All were 4-cylinder except the LTD and the gas turbine. Tailpipe emissions were measured by the 1975 light duty Federal Test Procedure for gaseous emissions. Smoke and fuel economy were also determined during this test cycle. Chassis dynamometer versions of the 1974 heavy duty diesel smoke and gaseous emissions tests were employed. Odor and related instrumental-chemical measurements were made under seven steady state and three acceleration conditions. The prototype diesel odor analytical system, developed under CRC contract, was applied to the exhaust from both diesel and gasoline engines. Its use as a predictive method of diesel odor was investigated. Noise measurements were taken by SAE driveby as well as under a variety of exterior-interior conditions. Comparisons of the results for all vehicles are by emission category. The emissions from the group of diesel cars are compared to the conventional gasoline, Ford PROCO, Texas TCCS, and Honda CVCC.« less

The assessment and evaluation of low-frequency noise near the region of infrasound.

PubMed

Ziaran, Stanislav

2014-01-01

The main aim of this paper is to present recent knowledge about the assessment and evaluation of low-frequency sounds (noise) and infrasound, close to the threshold of hearing, and identify their potential effect on human health and annoyance. Low-frequency noise generated by air flowing over a moving car with an open window was chosen as a typical scenario which can be subjectively assessed by people traveling by automobile. The principle of noise generated within the interior of the car and its effects on the comfort of the driver and passengers are analyzed at different velocities. An open window of a car at high velocity behaves as a source of specifically strong tonal low-frequency noise which is generally perceived as annoying. The interior noise generated by an open window of a passenger car was measured under different conditions: Driving on a highway and driving on a typical roadway. First, an octave-band analysis was used to assess the noise level and its impact on the driver's comfort. Second, a fast Fourier transform (FFT) analysis and one-third octave-band analysis were used for the detection of tonal low-frequency noise. Comparison between two different car makers was also done. Finally, the paper suggests some possibilities for scientifically assessing and evaluating low-frequency sounds in general, and some recommendations are introduced for scientific discussion, since sounds with strong low-frequency content (but not only strong) engender greater annoyance than is predicted by an A-weighted sound pressure level.

Residual stresses in passenger car wheels

DOT National Transportation Integrated Search

2006-11-05

The purpose of this paper is to present the extension of previous studies aimed at understanding the residual stress distribution in as-manufactured railroad wheels. In order to address loading conditions which are not axially symmetric, a manufactur...

The evaluation of partial binocular overlap on car maneuverability: A pilot study

NASA Technical Reports Server (NTRS)

Tsou, Brian H.; Rogers-Adams, Beth M.; Goodyear, Charles D.

1992-01-01

An engineering approach to enlarge the helmet mounted display (HMD) field of view (FOV) and maintain resolution and weight by partially overlapping the binocular FOV has received renewed interest among human factors scientists. It is evident, based on the brief literature review, that any panoramic display with a binocular overlap, less than a minimum amount, annoys the viewer, degrades performance, and elicits undesirable behavior. The major finding is that across the 60 deg conditions, subjects moved their heads a greater distance (by about 5 degs on each side) than in the 180 deg condition, presumably to compensate for the lack of FOV. It is quite clear that the study, based on simple car maneuverability and two subjects, reveals differences in FOV, but nothing significant between binocular overlap levels and configurations. This tentatively indicates that some tradeoffs of binocular vision for a larger overall display FOV are acceptable.

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

PubMed

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

2018-04-01

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

Self-esteem Is Mostly Stable Across Young Adulthood: Evidence from Latent STARTS Models.

PubMed

Wagner, Jenny; Lüdtke, Oliver; Trautwein, Ulrich

2016-08-01

How stable is self-esteem? This long-standing debate has led to different conclusions across different areas of psychology. Longitudinal data and up-to-date statistical models have recently indicated that self-esteem has stable and autoregressive trait-like components and state-like components. We applied latent STARTS models with the goal of replicating previous findings in a longitudinal sample of young adults (N = 4,532; Mage  = 19.60, SD = 0.85; 55% female). In addition, we applied multigroup models to extend previous findings on different patterns of stability for men versus women and for people with high versus low levels of depressive symptoms. We found evidence for the general pattern of a major proportion of stable and autoregressive trait variance and a smaller yet substantial amount of state variance in self-esteem across 10 years. Furthermore, multigroup models suggested substantial differences in the variance components: Females showed more state variability than males. Individuals with higher levels of depressive symptoms showed more state and less autoregressive trait variance in self-esteem. Results are discussed with respect to the ongoing trait-state debate and possible implications of the group differences that we found in the stability of self-esteem. © 2015 Wiley Periodicals, Inc.

A MISO-ARX-Based Method for Single-Trial Evoked Potential Extraction.

PubMed

Yu, Nannan; Wu, Lingling; Zou, Dexuan; Chen, Ying; Lu, Hanbing

2017-01-01

In this paper, we propose a novel method for solving the single-trial evoked potential (EP) estimation problem. In this method, the single-trial EP is considered as a complex containing many components, which may originate from different functional brain sites; these components can be distinguished according to their respective latencies and amplitudes and are extracted simultaneously by multiple-input single-output autoregressive modeling with exogenous input (MISO-ARX). The extraction process is performed in three stages: first, we use a reference EP as a template and decompose it into a set of components, which serve as subtemplates for the remaining steps. Then, a dictionary is constructed with these subtemplates, and EPs are preliminarily extracted by sparse coding in order to roughly estimate the latency of each component. Finally, the single-trial measurement is parametrically modeled by MISO-ARX while characterizing spontaneous electroencephalographic activity as an autoregression model driven by white noise and with each component of the EP modeled by autoregressive-moving-average filtering of the subtemplates. Once optimized, all components of the EP can be extracted. Compared with ARX, our method has greater tracking capabilities of specific components of the EP complex as each component is modeled individually in MISO-ARX. We provide exhaustive experimental results to show the effectiveness and feasibility of our method.

Autoregressive modelling of species richness in the Brazilian Cerrado.

PubMed

Vieira, C M; Blamires, D; Diniz-Filho, J A F; Bini, L M; Rangel, T F L V B

2008-05-01

Spatial autocorrelation is the lack of independence between pairs of observations at given distances within a geographical space, a phenomenon commonly found in ecological data. Taking into account spatial autocorrelation when evaluating problems in geographical ecology, including gradients in species richness, is important to describe both the spatial structure in data and to correct the bias in Type I errors of standard statistical analyses. However, to effectively solve these problems it is necessary to establish the best way to incorporate the spatial structure to be used in the models. In this paper, we applied autoregressive models based on different types of connections and distances between 181 cells covering the Cerrado region of Central Brazil to study the spatial variation in mammal and bird species richness across the biome. Spatial structure was stronger for birds than for mammals, with R(2) values ranging from 0.77 to 0.94 for mammals and from 0.77 to 0.97 for birds, for models based on different definitions of spatial structures. According to the Akaike Information Criterion (AIC), the best autoregressive model was obtained by using the rook connection. In general, these results furnish guidelines for future modelling of species richness patterns in relation to environmental predictors and other variables expressing human occupation in the biome.

Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.

PubMed

Biswas, Paritosh K; Islam, Md Zohorul; Debnath, Nitish C; Yamage, Mat

2014-01-01

The highly pathogenic avian influenza A virus subtype H5N1 (HPAI H5N1) is a deadly zoonotic pathogen. Its persistence in poultry in several countries is a potential threat: a mutant or genetically reassorted progenitor might cause a human pandemic. Its world-wide eradication from poultry is important to protect public health. The global trend of outbreaks of influenza attributable to HPAI H5N1 shows a clear seasonality. Meteorological factors might be associated with such trend but have not been studied. For the first time, we analyze the role of meteorological factors in the occurrences of HPAI outbreaks in Bangladesh. We employed autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to assess the roles of different meteorological factors in outbreaks of HPAI. Outbreaks were modeled best when multiplicative seasonality was incorporated. Incorporation of any meteorological variable(s) as inputs did not improve the performance of any multivariable models, but relative humidity (RH) was a significant covariate in several ARIMA and SARIMA models with different autoregressive and moving average orders. The variable cloud cover was also a significant covariate in two SARIMA models, but air temperature along with RH might be a predictor when moving average (MA) order at lag 1 month is considered.

Evaluation of statistical models for forecast errors from the HBV model

NASA Astrophysics Data System (ADS)

Engeland, Kolbjørn; Renard, Benjamin; Steinsland, Ingelin; Kolberg, Sjur

2010-04-01

SummaryThree statistical models for the forecast errors for inflow into the Langvatn reservoir in Northern Norway have been constructed and tested according to the agreement between (i) the forecast distribution and the observations and (ii) median values of the forecast distribution and the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order auto-regressive model was constructed for the forecast errors. The parameters were conditioned on weather classes. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order auto-regressive model was constructed for the forecast errors. For the third model positive and negative errors were modeled separately. The errors were first NQT-transformed before conditioning the mean error values on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: we wanted (a) the forecast distribution to be reliable; (b) the forecast intervals to be narrow; (c) the median values of the forecast distribution to be close to the observed values. Models 1 and 2 gave almost identical results. The median values improved the forecast with Nash-Sutcliffe R eff increasing from 0.77 for the original forecast to 0.87 for the corrected forecasts. Models 1 and 2 over-estimated the forecast intervals but gave the narrowest intervals. Their main drawback was that the distributions are less reliable than Model 3. For Model 3 the median values did not fit well since the auto-correlation was not accounted for. Since Model 3 did not benefit from the potential variance reduction that lies in bias estimation and removal it gave on average wider forecasts intervals than the two other models. At the same time Model 3 on average slightly under-estimated the forecast intervals, probably explained by the use of average measures to evaluate the fit.