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Sample records for modeling daily precipitationat

  1. Stochastic daily modeling of arctic tundra ecosystems

    NASA Astrophysics Data System (ADS)

    Erler, A.; Epstein, H. E.; Frazier, J.

    2011-12-01

    ArcVeg is a dynamic vegetation model that has simulated interannual variability of production and abundance of arctic tundra plant types in previous studies. In order to address the effects of changing seasonality on tundra plant community composition and productivity, we have uniquely adapted the model to operate on the daily timescale. Each section of the model-weather generation, nitrogen mineralization, and plant growth dynamics-are driven by daily fluctuations in simulated temperature conditions. These simulation dynamics are achieved by calibrating stochastic iterative loops and mathematical functions with raw field data. Air temperature is the fundamental driver in the model, parameterized by climate data collected in the field across numerous arctic tundra sites, and key daily statistics are extracted (mean and standard deviation of temperature for each day of the year). Nitrogen mineralization is calculated as an exponential function from the simulated temperature. The seasonality of plant growth is driven by the availability of nitrogen and constrained by historical patterns and dynamics of the remotely sensed normalized difference vegetation index (NDVI), as they pertain to the seasonal onset of growth. Here we describe the methods used for daily weather generation, nitrogen mineralization, and the daily competition among twelve plant functional types for nitrogen and subsequent growth. This still rather simple approach to vegetation dynamics has the capacity to generate complex relationships between seasonal patterns of temperature and arctic tundra vegetation community structure and function.

  2. Modelling erosion on a daily basis

    NASA Astrophysics Data System (ADS)

    Pikha Shrestha, Dhruba; Jetten, Victor

    2016-04-01

    Effect of soil erosion causing negative impact on ecosystem services and food security is well known. To assess annual erosion rates various empirical models have been extensively used in all the climatic regions. While these models are simple to operate and do not require lot of input data, the effect of extreme rain is not taken into account in the annual estimations. For analysing the effects of extreme rain the event- based models become handy. These models can simulate detail erosional processes including particle detachment, transportation and deposition of sediments during a storm. But they are not applicable for estimating annual erosion rates. Moreover storm event data may not be available everywhere which prohibits their extensive use. In this paper we describe a method by adapting the revised MMF model to assess erosion on daily basis so that the effects of extreme rains are taken into account. We couple it to a simple surface soil moisture balance on a daily basis and include estimation of daily vegetation cover changes. Annual soil loss is calculated by adding daily erosion rates. We compare the obtained results with that obtained from applying the revised MMF model in a case study in the Mamora plateau in northwest Morocco which is affected by severe gully formation. The results show clearly the effects of exceptional rain in erosional processes which cannot be captured in an annual model.

  3. Global daily reference evapotranspiration modeling and evaluation

    USGS Publications Warehouse

    Senay, G.B.; Verdin, J.P.; Lietzow, R.; Melesse, Assefa M.

    2008-01-01

    Accurate and reliable evapotranspiration (ET) datasets are crucial in regional water and energy balance studies. Due to the complex instrumentation requirements, actual ET values are generally estimated from reference ET values by adjustment factors using coefficients for water stress and vegetation conditions, commonly referred to as crop coefficients. Until recently, the modeling of reference ET has been solely based on important weather variables collected from weather stations that are generally located in selected agro-climatic locations. Since 2001, the National Oceanic and Atmospheric Administration’s Global Data Assimilation System (GDAS) has been producing six-hourly climate parameter datasets that are used to calculate daily reference ET for the whole globe at 1-degree spatial resolution. The U.S. Geological Survey Center for Earth Resources Observation and Science has been producing daily reference ET (ETo) since 2001, and it has been used on a variety of operational hydrological models for drought and streamflow monitoring all over the world. With the increasing availability of local station-based reference ET estimates, we evaluated the GDAS-based reference ET estimates using data from the California Irrigation Management Information System (CIMIS). Daily CIMIS reference ET estimates from 85 stations were compared with GDAS-based reference ET at different spatial and temporal scales using five-year daily data from 2002 through 2006. Despite the large difference in spatial scale (point vs. ∼100 km grid cell) between the two datasets, the correlations between station-based ET and GDAS-ET were very high, exceeding 0.97 on a daily basis to more than 0.99 on time scales of more than 10 days. Both the temporal and spatial correspondences in trend/pattern and magnitudes between the two datasets were satisfactory, suggesting the reliability of using GDAS parameter-based reference ET for regional water and energy balance studies in many parts of the world

  4. Models for estimating daily rainfall erosivity in China

    NASA Astrophysics Data System (ADS)

    Xie, Yun; Yin, Shui-qing; Liu, Bao-yuan; Nearing, Mark A.; Zhao, Ying

    2016-04-01

    The rainfall erosivity factor (R) represents the multiplication of rainfall energy and maximum 30 min intensity by event (EI30) and year. This rainfall erosivity index is widely used for empirical soil loss prediction. Its calculation, however, requires high temporal resolution rainfall data that are not readily available in many parts of the world. The purpose of this study was to parameterize models suitable for estimating erosivity from daily rainfall data, which are more widely available. One-minute resolution rainfall data recorded in sixteen stations over the eastern water erosion impacted regions of China were analyzed. The R-factor ranged from 781.9 to 8258.5 MJ mm ha-1 h-1 y-1. A total of 5942 erosive events from one-minute resolution rainfall data of ten stations were used to parameterize three models, and 4949 erosive events from the other six stations were used for validation. A threshold of daily rainfall between days classified as erosive and non-erosive was suggested to be 9.7 mm based on these data. Two of the models (I and II) used power law functions that required only daily rainfall totals. Model I used different model coefficients in the cool season (Oct.-Apr.) and warm season (May-Sept.), and Model II was fitted with a sinusoidal curve of seasonal variation. Both Model I and Model II estimated the erosivity index for average annual, yearly, and half-month temporal scales reasonably well, with the symmetric mean absolute percentage error MAPEsym ranging from 10.8% to 32.1%. Model II predicted slightly better than Model I. However, the prediction efficiency for the daily erosivity index was limited, with the symmetric mean absolute percentage error being 68.0% (Model I) and 65.7% (Model II) and Nash-Sutcliffe model efficiency being 0.55 (Model I) and 0.57 (Model II). Model III, which used the combination of daily rainfall amount and daily maximum 60-min rainfall, improved predictions significantly, and produced a Nash-Sutcliffe model efficiency

  5. Daily total global solar radiation modeling from several meteorological data

    NASA Astrophysics Data System (ADS)

    Bilgili, Mehmet; Ozgoren, Muammer

    2011-05-01

    This paper investigates the modeling of the daily total global solar radiation in Adana city of Turkey using multi-linear regression (MLR), multi-nonlinear regression (MNLR) and feed-forward artificial neural network (ANN) methods. Several daily meteorological data, i.e., measured sunshine duration, air temperature and wind speed and date of the year, i.e., monthly and daily, were used as independent variables to the MLR, MNLR and ANN models. In order to determine the relationship between the total global solar radiation and other meteorological data, and also to obtain the best independent variables, the MLR and MNLR analyses were performed with the "Stepwise" method in the Statistical Packages for the Social Sciences (SPSS) program. Thus, various models consisting of the combination of the independent variables were constructed and the best input structure was investigated. The performances of all models in the training and testing data sets were compared with the measured daily global solar radiation values. The obtained results indicated that the ANN method was better than the other methods in modeling daily total global solar radiation. For the ANN model, mean absolute error (MAE), mean absolute percentage error (MAPE), correlation coefficient ( R) and coefficient of determination ( R 2) for the training/testing data set were found to be 0.89/1.00 MJ/m2 day, 7.88/9.23%, 0.9824/0.9751, and 0.9651/0.9508, respectively.

  6. Stochastic daily precipitation model with a heavy-tailed component

    NASA Astrophysics Data System (ADS)

    Neykov, N. M.; Neytchev, P. N.; Zucchini, W.

    2014-09-01

    Stochastic daily precipitation models are commonly used to generate scenarios of climate variability or change on a daily timescale. The standard models consist of two components describing the occurrence and intensity series, respectively. Binary logistic regression is used to fit the occurrence data, and the intensity series is modeled using a continuous-valued right-skewed distribution, such as gamma, Weibull or lognormal. The precipitation series is then modeled using the joint density, and standard software for generalized linear models can be used to perform the computations. A drawback of these precipitation models is that they do not produce a sufficiently heavy upper tail for the distribution of daily precipitation amounts; they tend to underestimate the frequency of large storms. In this study, we adapted the approach of Furrer and Katz (2008) based on hybrid distributions in order to correct for this shortcoming. In particular, we applied hybrid gamma-generalized Pareto (GP) and hybrid Weibull-GP distributions to develop a stochastic precipitation model for daily rainfall at Ihtiman in western Bulgaria. We report the results of simulations designed to compare the models based on the hybrid distributions and those based on the standard distributions. Some potential difficulties are outlined.

  7. Stochastic daily precipitation model with a heavy-tailed component

    NASA Astrophysics Data System (ADS)

    Neykov, N. M.; Neytchev, P. N.; Zucchini, W.

    2014-02-01

    Stochastic daily precipitation models are commonly used to generate scenarios of climate variability or change on a daily time scale. The standard models consist of two components describing the occurrence and intensity series, respectively. Binary logistic regression is used to fit the occurrence data, and the intensity series is modeled by a continuous-valued right-skewed distribution, such as gamma, Weibull or lognormal. The precipitation series is then modeled using the joint density and standard software for generalized linear models can be used to perform the computations. A drawback of these precipitation models is that they do not produce a sufficiently heavy upper tail for the distribution of daily precipitation amounts; they tend to underestimate the frequency of large storms. In this study we adapted the approach of Furrer and Katz (2008) based on hybrid distributions in order to correct for this shortcoming. In particular we applied hybrid gamma - generalized Pareto (GP) and hybrid Weibull-GP distributions to develop a stochastic precipitation model for daily rainfall at Ihtiman in western Bulgaria. We report the results of simulations designed to compare the models based on the hybrid distributions and those based on the standard distributions. Some potential difficulties are outlined.

  8. Statistical procedures for evaluating daily and monthly hydrologic model predictions

    USGS Publications Warehouse

    Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.

    2004-01-01

    The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

  9. A stochastic model for the analysis of maximum daily temperature

    NASA Astrophysics Data System (ADS)

    Sirangelo, B.; Caloiero, T.; Coscarelli, R.; Ferrari, E.

    2016-08-01

    In this paper, a stochastic model for the analysis of the daily maximum temperature is proposed. First, a deseasonalization procedure based on the truncated Fourier expansion is adopted. Then, the Johnson transformation functions were applied for the data normalization. Finally, the fractionally autoregressive integrated moving average model was used to reproduce both short- and long-memory behavior of the temperature series. The model was applied to the data of the Cosenza gauge (Calabria region) and verified on other four gauges of southern Italy. Through a Monte Carlo simulation procedure based on the proposed model, 105 years of daily maximum temperature have been generated. Among the possible applications of the model, the occurrence probabilities of the annual maximum values have been evaluated. Moreover, the procedure was applied for the estimation of the return periods of long sequences of days with maximum temperature above prefixed thresholds.

  10. Models of Deafness: Cochlear Implants in the Australian Daily Press

    ERIC Educational Resources Information Center

    Power, Des

    2005-01-01

    This article examined a database of Australian daily newspapers on the terms cochlear implant and deaf children to investigate how journalists and columnists report competing models of deafness: as either "medical" (deafness is a condition to be cured) or "sociocultural" (deafness provides a way of life to be lived). The…

  11. A fuzzy-autoregressive model of daily river flows

    NASA Astrophysics Data System (ADS)

    Greco, Roberto

    2012-06-01

    A model for the identification of daily river flows has been developed, consisting of the combination of an autoregressive model with a fuzzy inference system. The AR model is devoted to the identification of base flow, supposed to be described by linear laws. The fuzzy model identifies the surface runoff, by applying a small set of linguistic statements, deriving from the knowledge of the physical features of the nonlinear rainfall-runoff transformation, to the inflow entering the river basin. The model has been applied to the identification of the daily flow series of river Volturno at Cancello-Arnone (Southern Italy), with a drainage basin of around 5560 km2, observed between 1970 and 1974. The inflow was estimated on the basis of daily precipitations registered during the same years at six rain gauges located throughout the basin. The first two years were used for model training, the remaining three for the validation. The obtained results show that the proposed model provides good predictions of either low river flows or high floods, although the analysis of residuals, which do not turn out to be a white noise, indicates that the cause and effect relationship between rainfall and runoff is not completely identified by the model.

  12. A fuzzy-autoregressive model of daily river flows

    NASA Astrophysics Data System (ADS)

    Greco, R.

    2012-04-01

    A model for the identification of daily river flows has been developed, consisting of the combination of an autoregressive model with a fuzzy inference system. The AR model is devoted to the identification of base flow, supposed to be described by linear laws. The fuzzy model identifies the surface runoff, by applying a small set of linguistic statements, deriving from the knowledge of the physical features of the non linear rainfall-runoff transformation, to the inflow entering the river basin. The model has been applied to the identification of the daily flow series of river Volturno at Cancello-Arnone (Southern Italy), with a drainage basin of around 5560 km2, observed between 1970 and 1974. The inflow was estimated on the basis of daily precipitations registered during the same years at six rain gauges located throughout the basin. The first two years were used for model training, the remaining three for the validation. The obtained results show that the proposed model provides good predictions of either low river flows or high floods, although the analysis of residuals, which do not turn out to be a white noise, indicates that the cause and effect relationship between rainfall and runoff is not completely identified by the model.

  13. Bayesian multinomial probit modeling of daily windows of ...

    EPA Pesticide Factsheets

    Past epidemiologic studies suggest maternal ambient air pollution exposure during critical periods of the pregnancy is associated with fetal development. We introduce a multinomial probit model that allows for the joint identification of susceptible daily periods during the pregnancy for 12 individual types of CHDs with respect to maternal PM2.5 exposure. We apply the model to a dataset of mothers from the National Birth Defect Prevention Study where daily PM2.5 exposures from weeks 2-8 of pregnancy are assigned (specific to each location and pregnancy date) using predictions from the downscaler pollution model. Results are compared to an aggregated exposure model which defines exposure as the average value over pregnancy weeks 2-8. Increased PM2.5 exposure during pregnancy days 53 and 50-51 for pulmonary valve stenosis and tetralogy of Fallot, respectively, are associated with an increased probability of development of each CHD. The largest estimated effect is seen for atrioventricular septal defects on pregnancy day 14. The aggregated exposure model fails to identify any significant windows of susceptibility during pregnancy weeks 2-8 for the considered CHDs. Considering daily PM2.5 exposures in a new modeling framework revealed positive associations for defects that the standard aggregated exposure model was unable to identify. Disclaimer: The views expressed in this manuscript are those of the authors and do not necessarily represent the views or policie

  14. Reconstruction of missing daily streamflow data using dynamic regression models

    NASA Astrophysics Data System (ADS)

    Tencaliec, Patricia; Favre, Anne-Catherine; Prieur, Clémentine; Mathevet, Thibault

    2015-12-01

    River discharge is one of the most important quantities in hydrology. It provides fundamental records for water resources management and climate change monitoring. Even very short data-gaps in this information can cause extremely different analysis outputs. Therefore, reconstructing missing data of incomplete data sets is an important step regarding the performance of the environmental models, engineering, and research applications, thus it presents a great challenge. The objective of this paper is to introduce an effective technique for reconstructing missing daily discharge data when one has access to only daily streamflow data. The proposed procedure uses a combination of regression and autoregressive integrated moving average models (ARIMA) called dynamic regression model. This model uses the linear relationship between neighbor and correlated stations and then adjusts the residual term by fitting an ARIMA structure. Application of the model to eight daily streamflow data for the Durance river watershed showed that the model yields reliable estimates for the missing data in the time series. Simulation studies were also conducted to evaluate the performance of the procedure.

  15. An empirical model of the quiet daily geomagnetic field variation

    USGS Publications Warehouse

    Yamazaki, Y.; Yumoto, K.; Cardinal, M.G.; Fraser, B.J.; Hattori, P.; Kakinami, Y.; Liu, J.Y.; Lynn, K.J.W.; Marshall, R.; McNamara, D.; Nagatsuma, T.; Nikiforov, V.M.; Otadoy, R.E.; Ruhimat, M.; Shevtsov, B.M.; Shiokawa, K.; Abe, S.; Uozumi, T.; Yoshikawa, A.

    2011-01-01

    An empirical model of the quiet daily geomagnetic field variation has been constructed based on geomagnetic data obtained from 21 stations along the 210 Magnetic Meridian of the Circum-pan Pacific Magnetometer Network (CPMN) from 1996 to 2007. Using the least squares fitting method for geomagnetically quiet days (Kp ??? 2+), the quiet daily geomagnetic field variation at each station was described as a function of solar activity SA, day of year DOY, lunar age LA, and local time LT. After interpolation in latitude, the model can describe solar-activity dependence and seasonal dependence of solar quiet daily variations (S) and lunar quiet daily variations (L). We performed a spherical harmonic analysis (SHA) on these S and L variations to examine average characteristics of the equivalent external current systems. We found three particularly noteworthy results. First, the total current intensity of the S current system is largely controlled by solar activity while its focus position is not significantly affected by solar activity. Second, we found that seasonal variations of the S current intensity exhibit north-south asymmetry; the current intensity of the northern vortex shows a prominent annual variation while the southern vortex shows a clear semi-annual variation as well as annual variation. Thirdly, we found that the total intensity of the L current system changes depending on solar activity and season; seasonal variations of the L current intensity show an enhancement during the December solstice, independent of the level of solar activity. Copyright 2011 by the American Geophysical Union.

  16. Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

    NASA Technical Reports Server (NTRS)

    Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

    2013-01-01

    The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

  17. Spatial and temporal modeling of daily pollen concentrations

    NASA Astrophysics Data System (ADS)

    Dellavalle, Curt T.; Triche, Elizabeth W.; Bell, Michelle L.

    2012-01-01

    Accurate assessments of pollen counts are valuable to allergy sufferers, the medical industry, and health researchers; however, monitoring stations do not exist in most areas. In addition, the degree of spatial reliability provided by the limited number of monitoring stations is poorly understood. We developed and compared spatial models to estimate pollen concentrations in locations without monitoring stations. Daily Acer, Quercus, and overall tree, grass, and weed pollen counts, in grains/m3, were obtained from 14 aeroallergen monitoring stations located in the northeastern and mid-Atlantic region of the United States from 2003 to 2006. Pollen counts were spatially interpolated using ordinary kriging. Mixed effects and generalized estimating equations incorporating daily and seasonal weather characteristics, pollen season characteristics and land-cover information were also developed to estimate daily pollen concentrations. We then compared observed values from a monitoring station to model estimates for that location. Observed counts and kriging estimates for tree pollen differed ( p = 0.04), but not when peak periods were removed ( p = 0.29). No differences between observed and kriging estimates of Acer ( p = 0.46), Quercus ( p = 0.24), grass ( p = 0.31) or weed pollen ( p = 0.29) were found. Estimates from longitudinal models also demonstrated good agreement with observed counts, except for the extremes of pollen distributions. Our results demonstrate that spatial interpolation techniques as well as regression methods incorporating both weather and land-cover characteristics can provide reliable estimates of daily pollen concentrations in areas where monitors do not exist for all but periods of extremely high pollen.

  18. Retrospective forecast of ETAS model with daily parameters estimate

    NASA Astrophysics Data System (ADS)

    Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang

    2016-04-01

    We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.

  19. Statistical Modeling of Daily Stream Temperature for Mitigating Fish Mortality

    NASA Astrophysics Data System (ADS)

    Caldwell, R. J.; Rajagopalan, B.

    2011-12-01

    Water allocations in the Central Valley Project (CVP) of California require the consideration of short- and long-term needs of many socioeconomic factors including, but not limited to, agriculture, urban use, flood mitigation/control, and environmental concerns. The Endangered Species Act (ESA) ensures that the decision-making process provides sufficient water to limit the impact on protected species, such as salmon, in the Sacramento River Valley. Current decision support tools in the CVP were deemed inadequate by the National Marine Fisheries Service due to the limited temporal resolution of forecasts for monthly stream temperature and fish mortality. Finer scale temporal resolution is necessary to account for the stream temperature variations critical to salmon survival and reproduction. In addition, complementary, long-range tools are needed for monthly and seasonal management of water resources. We will present a Generalized Linear Model (GLM) framework of maximum daily stream temperatures and related attributes, such as: daily stream temperature range, exceedance/non-exceedance of critical threshold temperatures, and the number of hours of exceedance. A suite of predictors that impact stream temperatures are included in the models, including current and prior day values of streamflow, water temperatures of upstream releases from Shasta Dam, air temperature, and precipitation. Monthly models are developed for each stream temperature attribute at the Balls Ferry gauge, an EPA compliance point for meeting temperature criteria. The statistical framework is also coupled with seasonal climate forecasts using a stochastic weather generator to provide ensembles of stream temperature scenarios that can be used for seasonal scale water allocation planning and decisions. Short-term weather forecasts can also be used in the framework to provide near-term scenarios useful for making water release decisions on a daily basis. The framework can be easily translated to other

  20. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    USGS Publications Warehouse

    Hwang, Y.; Clark, M.; Rajagopalan, B.; Leavesley, G.

    2012-01-01

    Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

  1. 10-daily soil erosion modelling over sub-Saharan Africa.

    PubMed

    Symeonakis, Elias; Drake, Nick

    2010-02-01

    Soil erosion is considered to be one of the greatest environmental problems of sub-Saharan Africa. This paper investigates the advantages and disadvantages of modelling soil erosion at the continental scale and suggests an operational methodology for mapping and quantifying 10-daily water runoff and soil erosion over this scale using remote sensing data in a geographical information system framework. An attempt is made to compare the estimates of this study with general data on the severity of soil erosion over Africa and with measured rates of soil loss at different locations over the continent. The results show that the measured and estimated rates of erosion are in some areas very similar and in general within the same order of magnitude. The importance and the potential of using the soil erosion estimates with simple models and easily accessible free data for various continental-scale environmental applications are also demonstrated.

  2. The modeling of daily precipitation in Costa Rica

    NASA Astrophysics Data System (ADS)

    Harrison, John Michael

    The understanding of precipitation and its underlying processes is important to many human activities. Agricultural planning, hydroelectric resource management, and industrial infrastructure development all rely heavily on being able to make reasonable predictions concerning rainfall. The lack of sufficient rainfall can have devastating social and economic consequences for developing nations that are reliant on subsistence agriculture and hydroelectric power. This study examines the means by which daily precipitation in Costa Rica can be modeled, and how the El Nino-Southern Oscillation (ENSO) affects the precipitation generating mechanisms. A selection of three meteorological stations are used to test how daily rainfall can be characterized by the occurrence and intensity of the individual rainfall events. The occurrence is modeled using a two-state first-order Markov model, which provides insight into the relative length of wet and dry spells. The intensity model uses L-moments to determine the optimum statistical distribution. These statistical parameters are used to understand the inter-annual and inter-seasonal variations in the precipitation-generating mechanisms as they are modified by the ENSO phenomenon. The parameters are also combined to create monthly rainfall simulations based on the state of the ENSO, as well as test whether accurate forecasts can be created up to one year in advance. It is found that the ENSO plays an important role in the daily rainfall process, by altering the behavior of the Inter-Tropical Convergence Zone (ITCZ), the Northeast Trade Winds, and the advance of cold air masses from North America during the winter. The eastern Caribbean slope of the country receives proportionally more rainfall during El Nino events, while the western Pacific slope receives less rainfall during the same period. Cold front (norte) intrusion is minimized by the El Nino, resulting in less winter rainfall during El Nino years. Simulations based on the

  3. Regional Model Nesting Within GFS Daily Forecasts Over West Africa

    NASA Technical Reports Server (NTRS)

    Druyan, Leonard M.; Fulakeza, Matthew; Lonergan, Patrick; Worrell, Ruben

    2010-01-01

    The study uses the RM3, the regional climate model at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies (CCSR/GISS). The paper evaluates 30 48-hour RM3 weather forecasts over West Africa during September 2006 made on a 0.5 grid nested within 1 Global Forecast System (GFS) global forecasts. September 2006 was the Special Observing Period #3 of the African Monsoon Multidisciplinary Analysis (AMMA). Archived GFS initial conditions and lateral boundary conditions for the simulations from the US National Weather Service, National Oceanographic and Atmospheric Administration were interpolated four times daily. Results for precipitation forecasts are validated against Tropical Rainfall Measurement Mission (TRMM) satellite estimates and data from the Famine Early Warning System (FEWS), which includes rain gauge measurements, and forecasts of circulation are compared to reanalysis 2. Performance statistics for the precipitation forecasts include bias, root-mean-square errors and spatial correlation coefficients. The nested regional model forecasts are compared to GFS forecasts to gauge whether nesting provides additional realistic information. They are also compared to RM3 simulations driven by reanalysis 2, representing high potential skill forecasts, to gauge the sensitivity of results to lateral boundary conditions. Nested RM3/GFS forecasts generate excessive moisture advection toward West Africa, which in turn causes prodigious amounts of model precipitation. This problem is corrected by empirical adjustments in the preparation of lateral boundary conditions and initial conditions. The resulting modified simulations improve on the GFS precipitation forecasts, achieving time-space correlations with TRMM of 0.77 on the first day and 0.63 on the second day. One realtime RM3/GFS precipitation forecast made at and posted by the African Centre of Meteorological Application for Development (ACMAD) in Niamey, Niger

  4. Statistical models for estimating daily streamflow in Michigan

    USGS Publications Warehouse

    Holtschlag, D.J.; Salehi, Habib

    1992-01-01

    Statistical models for estimating daily streamflow were analyzed for 25 pairs of streamflow-gaging stations in Michigan. Stations were paired by randomly choosing a station operated in 1989 at which 10 or more years of continuous flow data had been collected and at which flow is virtually unregulated; a nearby station was chosen where flow characteristics are similar. Streamflow data from the 25 randomly selected stations were used as the response variables; streamflow data at the nearby stations were used to generate a set of explanatory variables. Ordinary-least squares regression (OLSR) equations, autoregressive integrated moving-average (ARIMA) equations, and transfer function-noise (TFN) equations were developed to estimate the log transform of flow for the 25 randomly selected stations. The precision of each type of equation was evaluated on the basis of the standard deviation of the estimation errors. OLSR equations produce one set of estimation errors; ARIMA and TFN models each produce l sets of estimation errors corresponding to the forecast lead. The lead-l forecast is the estimate of flow l days ahead of the most recent streamflow used as a response variable in the estimation. In this analysis, the standard deviation of lead l ARIMA and TFN forecast errors were generally lower than the standard deviation of OLSR errors for l < 2 days and l < 9 days, respectively. Composite estimates were computed as a weighted average of forecasts based on TFN equations and backcasts (forecasts of the reverse-ordered series) based on ARIMA equations. The standard deviation of composite errors varied throughout the length of the estimation interval and generally was at maximum near the center of the interval. For comparison with OLSR errors, the mean standard deviation of composite errors were computed for intervals of length 1 to 40 days. The mean standard deviation of length-l composite errors were generally less than the standard deviation of the OLSR errors for l < 32

  5. Daily Flow Model of the Delaware River Basin. Main Report.

    DTIC Science & Technology

    1981-09-01

    first volume presents phase I of this study and contains the preliminary work of developing 50 years of historical natural inflows for selected...Delaware Memorial Bridge. A task committee was set up to direct the study . Members of the committee included persons from the Philadelphia District...INTRODUCTION Authority I-i Purpose I-1 Description of the Study Area 1-2 II NATURALIZATION OF MEAN DAILY FLOW DATA II-1 Introduction II-1 I Basin

  6. Measuring Disability: Application of the Rasch Model to Activities of Daily Living (ADL/IADL).

    ERIC Educational Resources Information Center

    Sheehan, T. Joseph; DeChello, Laurie M.; Garcia, Ramon; Fifield, Judith; Rothfield, Naomi; Reisine, Susan

    2001-01-01

    Performed a comparative analysis of Activities of Daily Living (ADL) items administered to 4,430 older adults and Instrumental Activities of Daily Living administered to 605 people with rheumatoid arthritis scoring both with Likert and Rasch measurement models. Findings show the superiority of the Rasch approach over the Likert method. (SLD)

  7. Upscaling instantaneous to daily evapotranspiration using modelled daily shortwave radiation for remote sensing applications: an artificial neural network approach

    NASA Astrophysics Data System (ADS)

    Wandera, Loise; Mallick, Kaniska; Kiely, Gerard; Roupsard, Olivier; Peichl, Matthias; Magliulo, Vincenzo

    2017-01-01

    Upscaling instantaneous evapotranspiration retrieved at any specific time-of-day (ETi) to daily evapotranspiration (ETd) is a key challenge in mapping regional ET using polar orbiting sensors. Various studies have unanimously cited the shortwave incoming radiation (RS) to be the most robust reference variable explaining the ratio between ETd and ETi. This study aims to contribute in ETi upscaling for global studies using the ratio between daily and instantaneous incoming shortwave radiation (RSd / RSi) as a factor for converting ETi to ETd.This paper proposes an artificial neural network (ANN) machine-learning algorithm first to predict RSd from RSi followed by using the RSd / RSi ratio to convert ETi to ETd across different terrestrial ecosystems. Using RSi and RSd observations from multiple sub-networks of the FLUXNET database spread across different climates and biomes (to represent inputs that would typically be obtainable from remote sensors during the overpass time) in conjunction with some astronomical variables (e.g. solar zenith angle, day length, exoatmospheric shortwave radiation), we developed the ANN model for reproducing RSd and further used it to upscale ETi to ETd. The efficiency of the ANN is evaluated for different morning and afternoon times of day, under varying sky conditions, and also at different geographic locations. RS-based upscaled ETd produced a significant linear relation (R2 = 0.65 to 0.69), low bias (-0.31 to -0.56 MJ m-2 d-1; approx. 4 %), and good agreement (RMSE 1.55 to 1.86 MJ m-2 d-1; approx. 10 %) with the observed ETd, although a systematic overestimation of ETd was also noted under persistent cloudy sky conditions. Inclusion of soil moisture and rainfall information in ANN training reduced the systematic overestimation tendency in predominantly overcast days. An intercomparison with existing upscaling method at daily, 8-day, monthly, and yearly temporal resolution revealed a robust performance of the ANN-driven RS-based ETi

  8. Instantaneous-to-daily GPP upscaling schemes based on a coupled photosynthesis-stomatal conductance model: correcting the overestimation of GPP by directly using daily average meteorological inputs.

    PubMed

    Wang, Fumin; Gonsamo, Alemu; Chen, Jing M; Black, T Andrew; Zhou, Bin

    2014-11-01

    Daily canopy photosynthesis is usually temporally upscaled from instantaneous (i.e., seconds) photosynthesis rate. The nonlinear response of photosynthesis to meteorological variables makes the temporal scaling a significant challenge. In this study, two temporal upscaling schemes of daily photosynthesis, the integrated daily model (IDM) and the segmented daily model (SDM), are presented by considering the diurnal variations of meteorological variables based on a coupled photosynthesis-stomatal conductance model. The two models, as well as a simple average daily model (SADM) with daily average meteorological inputs, were validated using the tower-derived gross primary production (GPP) to assess their abilities in simulating daily photosynthesis. The results showed IDM closely followed the seasonal trend of the tower-derived GPP with an average RMSE of 1.63 g C m(-2) day(-1), and an average Nash-Sutcliffe model efficiency coefficient (E) of 0.87. SDM performed similarly to IDM in GPP simulation but decreased the computation time by >66%. SADM overestimated daily GPP by about 15% during the growing season compared to IDM. Both IDM and SDM greatly decreased the overestimation by SADM, and improved the simulation of daily GPP by reducing the RMSE by 34 and 30%, respectively. The results indicated that IDM and SDM are useful temporal upscaling approaches, and both are superior to SADM in daily GPP simulation because they take into account the diurnally varying responses of photosynthesis to meteorological variables. SDM is computationally more efficient, and therefore more suitable for long-term and large-scale GPP simulations.

  9. The Communal Coping Model of Pain Catastrophizing in Daily Life: A Within-Couples Daily Diary Study

    PubMed Central

    Burns, John W.; Gerhart, James I.; Post, Kristina M.; Smith, David A.; Porter, Laura S.; Schuster, Erik; Buvanendran, Asokumar; Fras, Anne Marie; Keefe, Francis J.

    2015-01-01

    The Communal Coping Model (CCM) characterizes pain catastrophizing as a coping tactic whereby pain expression elicits assistance and empathic responses from others. Married couples (N = 105 couples; one spouse with chronic low back pain) completed electronic daily diary assessments 5 times/day for 14 days. On these diaries, patients reported pain catastrophizing, pain, function, and perceived spouse support, criticism and hostility. Non-patient spouses reported on their support, criticism, and hostility directed toward patients, as well as their observations of patient pain and pain behaviors. Hierarchical linear modeling tested concurrent and lagged (3 hours later) relationships. Principal findings included: a) within-person increases in pain catastrophizing were positively associated with spouse reports of patient pain behavior in concurrent and lagged analyses; b) within-person increases in pain catastrophizing were positively associated with patient perceptions of spouse support, criticism, and hostility in concurrent analyses; c) within-person increases in pain catastrophizing were negatively associated with spouse reports of criticism and hostility in lagged analyses. Spouses reported patient behaviors that were tied to elevated pain catastrophizing, and spouses changed their behavior during and following elevated pain catastrophizing episodes. Pain catastrophizing may affect the interpersonal environment of patients and spouses in ways consistent with the CCM. PMID:26320945

  10. Modeling daily flow patterns individuals to characterize disease spread

    SciTech Connect

    Smallwood, J.; Hyman, J. M.; Mirchandani, Pitu B.

    2002-11-17

    The effect of an individual's travels throughout a day on the spread of disease is examined using a deterministic SIR model. We determine which spatial and demographic characteristics most contribute to the disease spread and whether the progression of the disease can be slowed by appropriate vaccination of people belonging to a specific location-type.

  11. Models for estimating daily rainfall erosivity in China

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The multiplication of rainfall energy and maximum 30 minutes intensity (EI30) is the most widely used rainfall erosivity index for empirical soil loss prediction models, however its calculation requires high temporal resolution rainfall data which are often not readily available in China in most loc...

  12. Comparing an annual and daily time-step model for predicting field-scale phosphorus loss

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Numerous models exist for describing phosphorus (P) losses from agricultural fields. The complexity of these models varies considerably ranging from simple empirically-based annual time-step models to more complex process-based daily time step models. While better accuracy is often assumed with more...

  13. One-day offset in daily hydrologic modeling: An exploration of the issue in automatic model calibration

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The literature of daily hydrologic modelling illustrates that daily simulation models are incapable of accurately representing hydrograph timing due to relationships between precipitation and watershed hydrologic response. For watersheds with a time of concentration less than 24 hrs and a late day p...

  14. SELECTION OF CANDIDATE EUTROPHICATION MODELS FOR TOTAL MAXIMUM DAILY LOADS ANALYSES

    EPA Science Inventory

    A tiered approach was developed to evaluate candidate eutrophication models to select a common suite of models that could be used for Total Maximum Daily Loads (TMDL) analyses in estuaries, rivers, and lakes/reservoirs. Consideration for linkage to watershed models and ecologica...

  15. A dual pathway model of daily stressor effects on rheumatoid arthritis.

    PubMed

    Affleck, G; Urrows, S; Tennen, H; Higgins, P; Pav, D; Aloisi, R

    1997-01-01

    This study evaluated the initial promise of a dual-pathway conceptual model linking daily event stressors to rheumatoid arthritis (RA) disease activity through changes in immune system activation and mood. Fifty individuals, who were studied on five occasions two weeks apart, reported daily event stressors on the Daily Life Experience Checklist, daily mood on an abbreviated version of the Profile of Mood States-B, and daily joint pain on the Rapid Assessment of Disease Activity in Rheumatology. Serial clinical examinations comprised ratings of joint tenderness and swelling, and blood drawn during exams was analyzed for sedimentation rate (an indicator of systemic inflammation) and soluble interleukin-2 receptors (a marker of immune system activation known to correlate with RA disease activity). Across-person analyses failed to establish links from daily event stressors to either disease activity or composites of joint pain and joint inflammation when associations were adjusted for the effect of neuroticism on self-report measures. Pooled within-person analyses, however, were generally consistent with the relations predicted by the dual-pathway model. Increases in daily event stressors during the week preceding each clinical exam were associated with increased joint pain (regardless of changes in mood). At the same time, increased daily stressors were indirectly associated with decreased joint inflammation through reduction in levels of soluble interleukin-2 receptors. The dual-pathway model, which may be limited to short-term psychological and psychoimmunologic processes, underscores the importance of distinguishing potentially opposing effects of stress on pain versus inflammation in individuals with rheumatoid arthritis.

  16. Evaluation of a watershed model for estimating daily flow using limited flow measurements

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil and Water Assessment Tool (SWAT) model was evaluated for estimation of continuous daily flow based on limited flow measurements in the Upper Oyster Creek (UOC) watershed. SWAT was calibrated against limited measured flow data and then validated. The Nash-Sutcliffe model Efficiency (NSE) and...

  17. Estimation of instantaneous peak flow from simulated maximum daily flow using the HBV model

    NASA Astrophysics Data System (ADS)

    Ding, Jie; Haberlandt, Uwe

    2014-05-01

    Instantaneous peak flow (IPF) data are the foundation of the design of hydraulic structures and flood frequency analysis. However, the long discharge records published by hydrological agencies contain usually only average daily flows which are of little value for design in small catchments. In former research, statistical analysis using observed peak and daily flow data was carried out to explore the link between instantaneous peak flow (IPF) and maximum daily flow (MDF) where the multiple regression model is proved to have the best performance. The objective of this study is to further investigate the acceptability of the multiple regression model for post-processing simulated daily flows from hydrological modeling. The model based flood frequency analysis allows to consider change in the condition of the catchments and in climate for design. Here, the HBV model is calibrated on peak flow distributions and flow duration curves using two approaches. In a two -step approach the simulated MDF are corrected with a priory established regressions. In a one-step procedure the regression coefficients are calibrated together with the parameters of the model. For the analysis data from 18 mesoscale catchments in the Aller-Leine river basin in Northern Germany are used. The results show that: (1) the multiple regression model is capable to predict the peak flows with the simulated MDF data; (2) the calibrated hydrological model reproduces well the magnitude and frequency distribution of peak flows; (3) the one-step procedure outperforms the two-step procedure regarding the estimation of peak flows.

  18. Modelling the atmospheric boundary layer for remotely sensed estimates of daily evaporation

    NASA Technical Reports Server (NTRS)

    Gurney, R. J.; Blyth, K.; Camillo, P. J.

    1984-01-01

    An energy and moisture balance model of the soil surface was used to estimate daily evaporation from wheat and barley fields in West Germany. The model was calibrated using remotely sensed surface temperature estimates. Complete atmospheric boundary layer models are difficult to use because of the number of parameters involved and a simplified model was used here. The resultant evaporation estimates were compared to eddy correlation evaporation estimates and good agreement was found.

  19. Investigation of simple daily solar radiation models suitable for use in the design of solar heating systems

    SciTech Connect

    Sillman, S.

    1980-08-01

    Solar heating system simulations typically require hourly weather data and the use of a main-line computer. A simpler alternative is to use daily steps with a model for daily solar collection. This report investigates the accuracy of sinusoidal radiation models for use in solar heating simulation. Accuracy of daily radiation models is assessed in two ways: by a theoretical comparison with hourly weather data, and by analysis of results of daily simulation. Results indicate that a daily radiation model can be designed with errors of less than 2%.

  20. Modeling turbidity and flow at daily steps in karst using ARIMA/ARFIMA-GARCH error models

    NASA Astrophysics Data System (ADS)

    Massei, N.

    2013-12-01

    Hydrological and physico-chemical variations recorded at karst springs usually reflect highly non-linear processes and the corresponding time series are then very often also highly non-linear. Among others, turbidity, as an important parameter regarding water quality and management, is a very complex response of karst systems to rain events, involving direct transfer of particles from point-source recharge as well as resuspension of particles previously deposited and stored within the system. For those reasons, turbidity modeling has not been well taken in karst hydrological models so far. Most of the time, the modeling approaches would involve stochastic linear models such ARIMA-type models and their derivatives (ARMA, ARMAX, ARIMAX, ARFIMA...). Yet, linear models usually fail to represent well the whole (stochastic) process variability, and their residuals still contain useful information that can be used to either understand the whole variability or to enhance short-term predictability and forecasting. Model residuals are actually not i.i.d., which can be identified by the fact that squared residuals still present clear and significant serial correlation. Indeed, high (low) amplitudes are followed in time by high (low) amplitudes, which can be seen on residuals time series as periods of time during which amplitudes are higher (lower) then the mean amplitude. This is known as the ARCH effet (AutoRegressive Conditional Heteroskedasticity), and the corresponding non-linear process affecting residuals of a linear model can be modeled using ARCH or generalized ARCH (GARCH) non-linear modeling, which approaches are very well known in econometrics. Here we investigated the capability of ARIMA-GARCH error models to represent a ~20-yr daily turbidity time series recorded at a karst spring used for water supply of the city of Le Havre (Upper Normandy, France). ARIMA and ARFIMA models were used to represent the mean behavior of the time series and the residuals clearly

  1. Examining the Effects of Video Modeling and Prompts to Teach Activities of Daily Living Skills.

    PubMed

    Aldi, Catarina; Crigler, Alexandra; Kates-McElrath, Kelly; Long, Brian; Smith, Hillary; Rehak, Kim; Wilkinson, Lisa

    2016-12-01

    Video modeling has been shown to be effective in teaching a number of skills to learners diagnosed with autism spectrum disorders (ASD). In this study, we taught two young men diagnosed with ASD three different activities of daily living skills (ADLS) using point-of-view video modeling. Results indicated that both participants met criterion for all ADLS. Participants did not maintain mastery criterion at a 1-month follow-up, but did score above baseline at maintenance with and without video modeling. • Point-of-view video models may be an effective intervention to teach daily living skills. • Video modeling with handheld portable devices (Apple iPod or iPad) can be just as effective as video modeling with stationary viewing devices (television or computer). • The use of handheld portable devices (Apple iPod and iPad) makes video modeling accessible and possible in a wide variety of environments.

  2. Modelling and forecasting monthly and daily river discharge data using hybrid models and considering autoregressive heteroscedasticity

    NASA Astrophysics Data System (ADS)

    Szolgayova, Elena

    2010-05-01

    hydrological models. However, the GARCH family of models proved to be suited in removing it only in daily time step. The basic GARCH model was not applicable on any of the time series. In all other investigated cases, the EGARCH(1,1) model had to be used. Unlike in econometric time series, where the so called leverage effect (i.e. the series reacts more strongly to negative changes) is present and pointed out by this model, here the data tends to react more strongly on positive changes. In this particular case it was found, that the general property of hydrological processes, that the rise of discharge is rainfall driven (a highly nonlinear chaotic intermittent process) and the decrease of discharge is ruled by the damping effects of the water storage in the driven system (catchment or river reach), is present also in the hydrological model error series. This shows, that the modelling and forecasting of floods (pulse like rising discharge) is a more demanding task than that of droughts (slowly decreasing flows). Even though the GARCH models did show partial improvements in the modelling and forecasting of flows, they still have several serious disadvantages (such as high sensitivity to the chosen fitting period) and possible further use should be further investigated. These results are of importance with respect to future attempts of modelling of error time series of hydrological models in such hybrid frameworks. They underpin the need of a non-mechanistic approach in the case based analysis of such data and the physical interpretation of statistical modelling results.

  3. Comparing flow duration curve and rainfall-runoff modelling for predicting daily runoff in ungauged catchments

    NASA Astrophysics Data System (ADS)

    Zhang, Yongqiang; Vaze, Jai; Chiew, Francis H. S.; Li, Ming

    2015-06-01

    Predicting daily runoff time series in ungauged catchments is both important and challenging. For the last few decades, the rainfall-runoff (RR) modelling approach has been the method of choice. There have been very few studies reported in literature which attempt to use flow duration curve (FDC) to predict daily runoff time series. This study comprehensively compares the two approaches using an extensive dataset (228 catchments) for a large region of south-eastern Australia and provides guidelines for choosing the suitable method. For each approach we used the nearest neighbour method and two weightings - a 5-donor simple mathematical average (SA) and a 5-donor inverse-distance weighting (5-IDW) - to predict daily runoff time series. The results show that 5-IDW was noticeably better than a single donor to predict daily runoff time series, especially for the FDC approach. The RR modelling approach calibrated against daily runoff outperformed the FDC approach for predicting high flows. The FDC approach was better at predicting medium to low flows in traditional calibration against the Nash-Sutcliffe-Efficiency or Root Mean Square Error, but when calibrated against a low flow objective function, both the FDC and rainfall-runoff models performed equally well in simulating the low flows. These results indicate that both methods can be further improved to simulate daily hydrographs describing the range of flow metrics in ungauged catchments. Further studies should be carried out for improving the accuracy of predicted FDC in ungauged catchments, including improving the FDC model structure and parameter fitting.

  4. Modeling bulk density and snow water equivalent using daily snow depth observations

    NASA Astrophysics Data System (ADS)

    McCreight, J. L.; Small, E. E.

    2014-03-01

    Bulk density is a fundamental property of snow relating its depth and mass. Previously, two simple models of bulk density (depending on snow depth, date, and location) have been developed to convert snow depth observations to snow water equivalent (SWE) estimates. However, these models were not intended for application at the daily time step. We develop a new model of bulk density for the daily time step and demonstrate its improved skill over the existing models. Snow depth and density are negatively correlated at short (10 days) timescales while positively correlated at longer (90 days) timescales. We separate these scales of variability by modeling smoothed, daily snow depth (long timescales) and the observed positive and negative anomalies from the smoothed time series (short timescales) as separate terms. A climatology of fit is also included as a predictor variable. Over half a million daily observations of depth and SWE at 345 snowpack telemetry (SNOTEL) sites are used to fit models and evaluate their performance. For each location, we train the three models to the neighboring stations within 70 km, transfer the parameters to the location to be modeled, and evaluate modeled time series against the observations at that site. Our model exhibits improved statistics and qualitatively more-realistic behavior at the daily time step when sufficient local training data are available. We reduce density root mean square error (RMSE) by 9.9 and 4.5% compared to previous models while increasing R2 from 0.46 to 0.52 to 0.56 across models. Focusing on the 21-day window around peak SWE in each water year, our model reduces density RMSE by 24 and 17.4% relative to the previous models, with R2 increasing from 0.55 to 0.58 to 0.71 across models. Removing the challenge of parameter transfer over the full observational record increases R2 scores for both the existing and new models, but the gain is greatest for the new model (R2 = 0.75). Our model shows general improvement over

  5. Dynamic regression modeling of daily nitrate-nitrogen concentrations in a large agricultural watershed.

    PubMed

    Feng, Zhujing; Schilling, Keith E; Chan, Kung-Sik

    2013-06-01

    Nitrate-nitrogen concentrations in rivers represent challenges for water supplies that use surface water sources. Nitrate concentrations are often modeled using time-series approaches, but previous efforts have typically relied on monthly time steps. In this study, we developed a dynamic regression model of daily nitrate concentrations in the Raccoon River, Iowa, that incorporated contemporaneous and lags of precipitation and discharge occurring at several locations around the basin. Results suggested that 95 % of the variation in daily nitrate concentrations measured at the outlet of a large agricultural watershed can be explained by time-series patterns of precipitation and discharge occurring in the basin. Discharge was found to be a more important regression variable than precipitation in our model but both regression parameters were strongly correlated with nitrate concentrations. The time-series model was consistent with known patterns of nitrate behavior in the watershed, successfully identifying contemporaneous dilution mechanisms from higher relief and urban areas of the basin while incorporating the delayed contribution of nitrate from tile-drained regions in a lagged response. The first difference of the model errors were modeled as an AR(16) process and suggest that daily nitrate concentration changes remain temporally correlated for more than 2 weeks although temporal correlation was stronger in the first few days before tapering off. Consequently, daily nitrate concentrations are non-stationary, i.e. of strong memory. Using time-series models to reliably forecast daily nitrate concentrations in a river based on patterns of precipitation and discharge occurring in its basin may be of great interest to water suppliers.

  6. An improved hybrid data-driven model and its application in daily rainfall-runoff simulation

    NASA Astrophysics Data System (ADS)

    Kan, Guangyuan; He, Xiaoyan; Ding, Liuqian; Li, Jiren; Lei, Tianjie; Liang, Ke; Hong, Yang

    2016-11-01

    In previous literatures, a coupled data-driven rainfall-runoff (RR) model, NU-PEK, has been proposed and successfully applied in hourly RR simulation task. However, numerical experiments show that its performance for daily RR simulation is unsatisfactory. It is noticed that the poor performance is due to the inability of the original model to capture the much higher non-linear characteristics contained in the daily data. In order to improve the nonlinearity simulation capability of the original model, an improved model named NU-PKEK and its calibration methodology are developed in this paper. The improved model is constituted by adding a K-means clustering module and utilizing multiple NU-PEK modules instead of using only one NU-PEK model. This study applies the improved model, the Xinanjiang model, and the original model for daily RR simulation in Chengcun catchment for intercomparison and verification. The simulation results prove that the NU-PKEK performs best, and has better simulation and forecasting capability.

  7. MULTIVARIATE STATISTICAL MODELS FOR EFFECTS OF PM AND COPOLLUTANTS IN A DAILY TIME SERIES EPIDEMIOLOGY STUDY

    EPA Science Inventory

    Most analyses of daily time series epidemiology data relate mortality or morbidity counts to PM and other air pollutants by means of single-outcome regression models using multiple predictors, without taking into account the complex statistical structure of the predictor variable...

  8. Modeling Comparative Daily Enrollment Indicators To Aid Intelligent College Decisions. AIR 2001 Annual Forum Paper.

    ERIC Educational Resources Information Center

    Lajubutu, Oyebanjo A.

    This paper shows how three critical enrollment indicators drawn from a relationship database were used to guide planning and management decisions. The paper discusses the guidelines for the development of the model, attributes needed, variables to be calculated, and other issues that may improve the effectiveness and efficiency of daily enrollment…

  9. The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data

    SciTech Connect

    Behrang, M.A.; Assareh, E.; Ghanbarzadeh, A.; Noghrehabadi, A.R.

    2010-08-15

    The main objective of present study is to predict daily global solar radiation (GSR) on a horizontal surface, based on meteorological variables, using different artificial neural network (ANN) techniques. Daily mean air temperature, relative humidity, sunshine hours, evaporation, and wind speed values between 2002 and 2006 for Dezful city in Iran (32 16'N, 48 25'E), are used in this study. In order to consider the effect of each meteorological variable on daily GSR prediction, six following combinations of input variables are considered: (I)Day of the year, daily mean air temperature and relative humidity as inputs and daily GSR as output. (II)Day of the year, daily mean air temperature and sunshine hours as inputs and daily GSR as output. (III)Day of the year, daily mean air temperature, relative humidity and sunshine hours as inputs and daily GSR as output. (IV)Day of the year, daily mean air temperature, relative humidity, sunshine hours and evaporation as inputs and daily GSR as output. (V)Day of the year, daily mean air temperature, relative humidity, sunshine hours and wind speed as inputs and daily GSR as output. (VI)Day of the year, daily mean air temperature, relative humidity, sunshine hours, evaporation and wind speed as inputs and daily GSR as output. Multi-layer perceptron (MLP) and radial basis function (RBF) neural networks are applied for daily GSR modeling based on six proposed combinations. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data. The comparison of obtained results from ANNs and different conventional GSR prediction (CGSRP) models shows very good improvements (i.e. the predicted values of best ANN model (MLP-V) has a mean absolute percentage error (MAPE) about 5.21% versus 10.02% for best CGSRP model (CGSRP 5)). (author)

  10. Application of Markov chain model to daily maximum temperature for thermal comfort in Malaysia

    NASA Astrophysics Data System (ADS)

    Nordin, Muhamad Asyraf bin Che; Hassan, Husna

    2015-10-01

    The Markov chain's first order principle has been widely used to model various meteorological fields, for prediction purposes. In this study, a 14-year (2000-2013) data of daily maximum temperatures in Bayan Lepas were used. Earlier studies showed that the outdoor thermal comfort range based on physiologically equivalent temperature (PET) index in Malaysia is less than 34°C, thus the data obtained were classified into two state: normal state (within thermal comfort range) and hot state (above thermal comfort range). The long-run results show the probability of daily temperature exceed TCR will be only 2.2%. On the other hand, the probability daily temperature within TCR will be 97.8%.

  11. Application of Markov chain model to daily maximum temperature for thermal comfort in Malaysia

    SciTech Connect

    Nordin, Muhamad Asyraf bin Che; Hassan, Husna

    2015-10-22

    The Markov chain’s first order principle has been widely used to model various meteorological fields, for prediction purposes. In this study, a 14-year (2000-2013) data of daily maximum temperatures in Bayan Lepas were used. Earlier studies showed that the outdoor thermal comfort range based on physiologically equivalent temperature (PET) index in Malaysia is less than 34°C, thus the data obtained were classified into two state: normal state (within thermal comfort range) and hot state (above thermal comfort range). The long-run results show the probability of daily temperature exceed TCR will be only 2.2%. On the other hand, the probability daily temperature within TCR will be 97.8%.

  12. Artificial neural networks modeling for forecasting the maximum daily total precipitation at Athens, Greece

    NASA Astrophysics Data System (ADS)

    Nastos, P. T.; Paliatsos, A. G.; Koukouletsos, K. V.; Larissi, I. K.; Moustris, K. P.

    2014-07-01

    Extreme daily precipitation events are involved in significant environmental damages, even in life loss, because of causing adverse impacts, such as flash floods, in urban and sometimes in rural areas. Thus, long-term forecast of such events is of great importance for the preparation of local authorities in order to confront and mitigate the adverse consequences. The objective of this study is to estimate the possibility of forecasting the maximum daily precipitation for the next coming year. For this reason, appropriate prognostic models, such as Artificial Neural Networks (ANNs) were developed and applied. The data used for the analysis concern annual maximum daily precipitation totals, which have been recorded at the National Observatory of Athens (NOA), during the long term period 1891-2009. To evaluate the potential of daily extreme precipitation forecast by the applied ANNs, a different period for validation was considered than the one used for the ANNs training. Thus, the datasets of the period 1891-1980 were used as training datasets, while the datasets of the period 1981-2009 as validation datasets. Appropriate statistical indices, such as the coefficient of determination (R2), the index of agreement (IA), the Root Mean Square Error (RMSE) and the Mean Bias Error (MBE), were applied to test the reliability of the models. The findings of the analysis showed that, a quite satisfactory relationship (R2 = 0.482, IA = 0.817, RMSE = 16.4 mm and MBE = + 5.2 mm) appears between the forecasted and the respective observed maximum daily precipitation totals one year ahead. The developed ANN seems to overestimate the maximum daily precipitation totals appeared in 1988 while underestimate the maximum in 1999, which could be attributed to the relatively low frequency of occurrence of these extreme events within GAA having impact on the optimum training of ANN.

  13. Daily Spillover From Family to Work: A Test of the Work-Home Resources Model.

    PubMed

    Du, Danyang; Derks, Daantje; Bakker, Arnold B

    2017-02-02

    The present study examines a mediated moderation model of the day-level effects of family hassles and family-work spillover (affect and cognition) on the relationship between job resources and employees' flourishing at work. Based on the work-home resources model, the authors hypothesized that demands from one domain (family) induce repetitive thoughts or negative feelings about those problems, so that individuals are not able to function optimally and to make full use of contextual resources in the other domain (work). Multilevel analyses of 108 Chinese working parents' 366 daily surveys revealed that the relationship between morning job resources and afternoon flourishing was significantly positive when previous day family hassles were low; the relationship became nonsignificant when previous day family hassles were high. In addition, as predicted, daily rumination also attenuated the relationship between morning job resources and afternoon flourishing, whereas daily affect did not. Finally, the moderating effect of previous day family hassles was mediated by daily rumination. The findings contribute to spillover theories by revealing the roles of affective and cognitive spillover from family to work. (PsycINFO Database Record

  14. Modeling of daily body weights and body weight changes of Nordic Red cows.

    PubMed

    Mäntysaari, P; Mäntysaari, E A

    2015-10-01

    Increased availability of automated weighing systems have made it possible to record massive amounts of body weight (BW) data in a short time. If the BW measurement is unbiased, the changes in BW reflect the energy status of the cow and can be used for management or breeding purposes. The usefulness of the BW data depends on the reliability of the measures. The noise in BW measurements can be smoothed by fitting a parametric or time series model into the BW measurements. This study examined the accuracy of different models to predict BW of the cows based on daily BW measurements and investigated the usefulness of modeling in increasing the value of BW measurements as management and breeding tools. Data included daily BW measurements, production, and intake from 230 Nordic Red dairy cows. The BW of the cows was recorded twice a day on their return from milking. In total, the data included 50,594 daily observations with 98,418 BW measurements. A clear diurnal change was present in the BW of the cows even if they had feed available 24 h. The daily average BW were used in the modeling. Five different models were tested: (1) a cow-wise fixed second-order polynomial regression model (FiX) including the exponential Wilmink term, (2) a random regression model with fixed and random animal lactation stage functions (MiX), (3) MiX with 13 periods of weighing added (PER), (4) natural cubic smoothing splines with 8 equally spaced knots (SPk8), and (5) spline model with no restriction on knots but a smoothing parameter corresponding to a fit of 5 degrees of freedom (SPdf5). In the original measured BW data, the within-animal variation was 6.4% of the total variance. Modeling decreased the within animal variation to levels of 2.9 to 5.1%. The smallest day-to-day variation and thereafter highest day-to-day repeatabilities were with PER and MiX models. The usability of modeled BW as energy balance (EB) indicator were evaluated by estimating relationships between EB, or EB

  15. A Temperature-Based Model for Estimating Monthly Average Daily Global Solar Radiation in China

    PubMed Central

    Li, Huashan; Cao, Fei; Wang, Xianlong; Ma, Weibin

    2014-01-01

    Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China. PMID:24605046

  16. A temperature-based model for estimating monthly average daily global solar radiation in China.

    PubMed

    Li, Huashan; Cao, Fei; Wang, Xianlong; Ma, Weibin

    2014-01-01

    Since air temperature records are readily available around the world, the models based on air temperature for estimating solar radiation have been widely accepted. In this paper, a new model based on Hargreaves and Samani (HS) method for estimating monthly average daily global solar radiation is proposed. With statistical error tests, the performance of the new model is validated by comparing with the HS model and its two modifications (Samani model and Chen model) against the measured data at 65 meteorological stations in China. Results show that the new model is more accurate and robust than the HS, Samani, and Chen models in all climatic regions, especially in the humid regions. Hence, the new model can be recommended for estimating solar radiation in areas where only air temperature data are available in China.

  17. Effects of temperature seasonality on tundra vegetation productivity using a daily vegetation dynamics model

    NASA Astrophysics Data System (ADS)

    Epstein, H. E.; Erler, A.; Frazier, J.; Bhatt, U. S.

    2011-12-01

    Changes in the seasonality of air temperature will elicit interacting effects on the dynamics of snow cover, nutrient availability, vegetation growth, and other ecosystem properties and processes in arctic tundra. Simulation models often do not have the fine temporal resolution necessary to develop theory and propose hypotheses for the effects of daily and weekly timescale changes on ecosystem dynamics. We therefore developed a daily version of an arctic tundra vegetation dynamics model (ArcVeg) to simulate how changes in the seasonality of air temperatures influences the dynamics of vegetation growth and carbon sequestration across regions of arctic tundra. High temporal-resolution air and soil temperature data collected from field sites across the five arctic tundra bioclimate subzones were used to develop a daily weather generator operable for sites throughout the arctic tundra. Empirical relationships between temperature and soil nitrogen were used to generate daily dynamics of soil nitrogen availability, which drive the daily uptake of nitrogen and growth among twelve tundra plant functional types. Seasonal dynamics of the remotely sensed normalized difference vegetation index (NDVI) and remotely sensed land surface temperature from the Advanced Very High Resolution Radiometer (AVHRR) GIMMS 3g dataset were used to investigate constraints on the start of the growing season, although there was no indication of any spatially consistent temperature or day-length controls on greening onset. Because of the exponential nature of the relationship between soil temperature and nitrogen mineralization, temperature changes during the peak of the growing season had greater effects on vegetation productivity than changes earlier in the growing season. However, early season changes in temperature had a greater effect on the relative productivities of different plant functional types, with potential influences on species composition.

  18. Semiparametric Modeling of Daily Ammonia Levels in Naturally Ventilated Caged-Egg Facilities

    PubMed Central

    Gutiérrez-Zapata, Diana María; Galeano-Vasco, Luis Fernando; Cerón-Muñoz, Mario Fernando

    2016-01-01

    Ammonia concentration (AMC) in poultry facilities varies depending on different environmental conditions and management; however, this is a relatively unexplored subject in Colombia (South America). The objective of this study was to model daily AMC variations in a naturally ventilated caged-egg facility using generalized additive models. Four sensor nodes were used to record AMC, temperature, relative humidity and wind speed on a daily basis, with 10 minute intervals for 12 weeks. The following variables were included in the model: Heat index, Wind, Hour, Location, Height of the sensor to the ground level, and Period of manure accumulation. All effects included in the model were highly significant (p<0.001). The AMC was higher during the night and early morning when the wind was not blowing (0.0 m/s) and the heat index was extreme. The average and maximum AMC were 5.94±3.83 and 31.70 ppm, respectively. Temperatures above 25°C and humidity greater than 80% increased AMC levels. In naturally ventilated caged-egg facilities the daily variations observed in AMC primarily depend on cyclic variations of the environmental conditions and are also affected by litter handling (i.e., removal of the bedding material). PMID:26812150

  19. Semiparametric Modeling of Daily Ammonia Levels in Naturally Ventilated Caged-Egg Facilities.

    PubMed

    Gutiérrez-Zapata, Diana María; Galeano-Vasco, Luis Fernando; Cerón-Muñoz, Mario Fernando

    2016-01-01

    Ammonia concentration (AMC) in poultry facilities varies depending on different environmental conditions and management; however, this is a relatively unexplored subject in Colombia (South America). The objective of this study was to model daily AMC variations in a naturally ventilated caged-egg facility using generalized additive models. Four sensor nodes were used to record AMC, temperature, relative humidity and wind speed on a daily basis, with 10 minute intervals for 12 weeks. The following variables were included in the model: Heat index, Wind, Hour, Location, Height of the sensor to the ground level, and Period of manure accumulation. All effects included in the model were highly significant (p<0.001). The AMC was higher during the night and early morning when the wind was not blowing (0.0 m/s) and the heat index was extreme. The average and maximum AMC were 5.94±3.83 and 31.70 ppm, respectively. Temperatures above 25°C and humidity greater than 80% increased AMC levels. In naturally ventilated caged-egg facilities the daily variations observed in AMC primarily depend on cyclic variations of the environmental conditions and are also affected by litter handling (i.e., removal of the bedding material).

  20. Stressor diversity: Introduction and empirical integration into the daily stress model.

    PubMed

    Koffer, Rachel E; Ram, Nilam; Conroy, David E; Pincus, Aaron L; Almeida, David M

    2016-06-01

    The present study examined whether and how stressor diversity, the extent to which stressor events are spread across multiple types of stressors, contributes to daily affective well-being through the adult life span. Stressor diversity was examined as a unique predictor of daily affect and as a moderator of stressor exposure and stressor reactivity effects. Analyses span 2 independent studies of daily stress: the National Study of Daily Experiences with N = 2,022 adults, aged 33 to 85 years, assessed over T = 8 days, and the Intraindividual Study of Affect, Health, and Interpersonal Behavior with N = 150 adults, aged 18 to 89 years, assessed over T = 63 days. Across both studies, older age was associated with less stressor diversity. Additionally, multivariate multilevel models indicated higher stressor diversity was linked with better affective well-being. Age, however, was not a consistent moderator of such associations. The combination of low stressor diversity and high stressor exposure is discussed as an operationalization of chronic stressors, and this combination was associated with particularly high negative affect and low positive affect. We believe further work will benefit from including both the frequency and diversity of stressor experiences in analyses in order to better characterize individuals' stressor experiences. (PsycINFO Database Record

  1. Quantum spatial-periodic harmonic model for daily price-limited stock markets

    NASA Astrophysics Data System (ADS)

    Meng, Xiangyi; Zhang, Jian-Wei; Xu, Jingjing; Guo, Hong

    2015-11-01

    We investigate the behaviors of stocks in daily price-limited stock markets by purposing a quantum spatial-periodic harmonic model. The stock price is considered to be oscillating and damping in a quantum spatial-periodic harmonic oscillator potential well. A complicated non-linear relation including inter-band positive correlation and intra-band negative correlation between the volatility and trading volume of a stock is numerically derived with the energy band structure of the model concerned. The effectiveness of price limit is re-examined, with some observed characteristics of price-limited stock markets in China studied by applying our quantum model.

  2. A regional neural network model for predicting mean daily river water temperature

    USGS Publications Warehouse

    Wagner, Tyler; DeWeber, Jefferson Tyrell

    2014-01-01

    Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate

  3. Daily Dosing of Rifapentine Cures Tuberculosis in Three Months or Less in the Murine Model

    PubMed Central

    Rosenthal, Ian M; Zhang, Ming; Williams, Kathy N; Peloquin, Charles A; Tyagi, Sandeep; Vernon, Andrew A; Bishai, William R; Chaisson, Richard E; Grosset, Jacques H; Nuermberger, Eric L

    2007-01-01

    Background Availability of an ultra-short-course drug regimen capable of curing patients with tuberculosis in 2 to 3 mo would significantly improve global control efforts. Because immediate prospects for novel treatment-shortening drugs remain uncertain, we examined whether better use of existing drugs could shorten the duration of treatment. Rifapentine is a long-lived rifamycin derivative currently recommended only in once-weekly continuation-phase regimens. Moxifloxacin is an 8-methoxyfluoroquinolone currently used in second-line regimens. Methods and Findings Using a well-established mouse model with a high bacterial burden and human-equivalent drug dosing, we compared the efficacy of rifapentine- and moxifloxacin-containing regimens with that of the standard daily short-course regimen based on rifampin, isoniazid, and pyrazinamide. Bactericidal activity was assessed by lung colony-forming unit counts, and sterilizing activity was assessed by the proportion of mice with culture-positive relapse after 2, 3, 4, and 6 mo of treatment. Here, we demonstrate that replacing rifampin with rifapentine and isoniazid with moxifloxacin dramatically increased the activity of the standard daily regimen. After just 2 mo of treatment, mice receiving rifapentine- and moxifloxacin-containing regimens were found to have negative lung cultures, while those given the standard regimen still harbored 3.17 log10 colony-forming units in the lungs (p < 0.01). No relapse was observed after just 3 mo of treatment with daily and thrice-weekly administered rifapentine- and moxifloxacin-containing regimens, whereas the standard daily regimen required 6 mo to prevent relapse in all mice. Conclusions Rifapentine should no longer be viewed solely as a rifamycin for once-weekly administration. Our results suggest that treatment regimens based on daily and thrice-weekly administration of rifapentine and moxifloxacin may permit shortening the current 6 mo duration of treatment to 3 mo or less

  4. Impact of intra-daily SST variability on ENSO characteristics in a coupled model

    NASA Astrophysics Data System (ADS)

    Masson, Sébastien; Terray, Pascal; Madec, Gurvan; Luo, Jing-Jia; Yamagata, Toshio; Takahashi, Keiko

    2012-08-01

    This paper explores the impact of intra-daily Sea Surface Temperature (SST) variability on the tropical large-scale climate variability and differentiates it from the response of the system to the forcing of the solar diurnal cycle. Our methodology is based on a set of numerical experiments based on a fully global coupled ocean-atmosphere general circulation in which we alter (1) the frequency at which the atmosphere sees the SST variations and (2) the amplitude of the SST diurnal cycle. Our results highlight the complexity of the scale interactions existing between the intra-daily and inter-annual variability of the tropical climate system. Neglecting the SST intra-daily variability results, in our CGCM, to a systematic decrease of 15% of El Niño—Southern Oscillation (ENSO) amplitude. Furthermore, ENSO frequency and skewness are also significantly modified and are in better agreement with observations when SST intra-daily variability is directly taken into account in the coupling interface of our CGCM. These significant modifications of the SST interannual variability are not associated with any remarkable changes in the mean state or the seasonal variability. They can therefore not be explained by a rectification of the mean state as usually advocated in recent studies focusing on the diurnal cycle and its impact. Furthermore, we demonstrate that SST high frequency coupling is systematically associated with a strengthening of the air-sea feedbacks involved in ENSO physics: SST/sea level pressure (or Bjerknes) feedback, zonal wind/heat content (or Wyrtki) feedback, but also negative surface heat flux feedbacks. In our model, nearly all these results (excepted for SST skewness) are independent of the amplitude of the SST diurnal cycle suggesting that the systematic deterioration of the air-sea coupling by a daily exchange of SST information is cascading toward the major mode of tropical variability, i.e. ENSO.

  5. Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

    NASA Astrophysics Data System (ADS)

    Williams, C.; Kniveton, D.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  6. Spatial modeling of the highest daily maximum temperature in Korea via max-stable processes

    NASA Astrophysics Data System (ADS)

    Lee, Youngsaeng; Yoon, Sanghoo; Murshed, Md. Sharwar; Kim, Maeng-Ki; Cho, ChunHo; Baek, Hee-Jeong; Park, Jeong-Soo

    2013-11-01

    This paper examines the annual highest daily maximum temperature (DMT) in Korea by using data from 56 weather stations and employing spatial extreme modeling. Our approach is based on max-stable processes (MSP) with Schlather’s characterization. We divide the country into four regions for a better model fit and identify the best model for each region. We show that regional MSP modeling is more suitable than MSP modeling for the entire region and the pointwise generalized extreme value distribution approach. The advantage of spatial extreme modeling is that more precise and robust return levels and some indices of the highest temperatures can be obtained for observation stations and for locations with no observed data, and so help to determine the effects and assessment of vulnerability as well as to downscale extreme events.

  7. Daily diaries and minority adolescents: random coefficient regression modeling of attributional style, coping, and affect.

    PubMed

    Roesch, Scott C; Vaughn, Allison A; Aldridge, Arianna A; Villodas, Feion

    2009-10-01

    Many researchers underscore the importance of coping in the daily lives of adolescents, yet very few studies measure this and related constructs at this level. Using a daily diary approach to stress and coping, the current study evaluated a series of mediational coping models in a sample of low-income minority adolescents (N = 89). Specifically, coping was hypothesized to mediate the relationship between attributional style (and dimensions) and daily affect. Using random coefficient regression modeling, the relationship between (a) the locus of causality dimension and positive affect was completely mediated by the use of acceptance and humor as coping strategies; (b) the stability dimension and positive affect was completely mediated by the use of both problem-solving and positive thinking; and (c) the stability dimension and negative affect was partially mediated by the use of religious coping. In addition, the locus of causality and stability (but not globality) dimensions were also directly related to affect. However, the relationship between pessimistic explanatory style and affect was not mediated by coping. Consistent with previous research, these findings suggest that attributions are both directly and indirectly related to indices of affect or adjustment. Thus, attributions may not only influence the type of coping strategy employed, but may also serve as coping strategies themselves.

  8. Climate change uncertainty for daily minimum and maximum temperatures: a model inter-comparison

    SciTech Connect

    Lobell, D; Bonfils, C; Duffy, P

    2006-11-09

    Several impacts of climate change may depend more on changes in mean daily minimum (T{sub min}) or maximum (T{sub max}) temperatures than daily averages. To evaluate uncertainties in these variables, we compared projections of T{sub min} and T{sub max} changes by 2046-2065 for 12 climate models under an A2 emission scenario. Average modeled changes in T{sub max} were slightly lower in most locations than T{sub min}, consistent with historical trends exhibiting a reduction in diurnal temperature ranges. However, while average changes in T{sub min} and T{sub max} were similar, the inter-model variability of T{sub min} and T{sub max} projections exhibited substantial differences. For example, inter-model standard deviations of June-August T{sub max} changes were more than 50% greater than for T{sub min} throughout much of North America, Europe, and Asia. Model differences in cloud changes, which exert relatively greater influence on T{sub max} during summer and T{sub min} during winter, were identified as the main source of uncertainty disparities. These results highlight the importance of considering separately projections for T{sub max} and T{sub min} when assessing climate change impacts, even in cases where average projected changes are similar. In addition, impacts that are most sensitive to summertime T{sub min} or wintertime T{sub max} may be more predictable than suggested by analyses using only projections of daily average temperatures.

  9. Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models

    NASA Astrophysics Data System (ADS)

    Bai, Yun; Chen, Zhiqiang; Xie, Jingjing; Li, Chuan

    2016-01-01

    Inflow forecasting applies data supports for the operations and managements of reservoirs. A multiscale deep feature learning (MDFL) method with hybrid models is proposed in this paper to deal with the daily reservoir inflow forecasting. Ensemble empirical mode decomposition and Fourier spectrum are first employed to extract multiscale (trend, period and random) features, which are then represented by three deep belief networks (DBNs), respectively. The weights of each DBN are subsequently applied to initialize a neural network (D-NN). The outputs of the three-scale D-NNs are finally reconstructed using a sum-up strategy toward the forecasting results. A historical daily inflow series (from 1/1/2000 to 31/12/2012) of the Three Gorges reservoir, China, is investigated by the proposed MDFL with hybrid models. For comparison, four peer models are adopted for the same task. The results show that, the present model overwhelms all the peer models in terms of mean absolute percentage error (MAPE = 11.2896%), normalized root-mean-square error (NRMSE = 0.2292), determination coefficient criteria (R2 = 0.8905), and peak percent threshold statistics (PPTS(5) = 10.0229%). The addressed method integrates the deep framework with multiscale and hybrid observations, and therefore being good at exploring sophisticated natures in the reservoir inflow forecasting.

  10. Selection of a mathematical model to generate lactation curves using daily milk yields of Holstein cows.

    PubMed

    Sherchand, L; McNew, R W; Kellogg, D W; Johnson, Z B

    1995-11-01

    Mathematical descriptions of early stages of lactation were investigated using daily milk yields of 117 first, 78 second, 57 third, and 36 fourth lactations of 120 Holstein cows fitted by 10 models. The measure of fit was the error mean squares, which were replaced by ranks to perform an analysis of variance with lactation number, model, and period as factors and with cows as replicates. The interaction of model and lactation number was significant for the fit of the entire lactation. A significant interaction of model and period was obtained for the fit of three 30-d intervals. For the entire lactation, the best fit for all four lactations occurred from the diphasic logistic function, y = d1(1-tanh2(b1(nk-c1))) + d2(1-tanh2(b2(n-c2))). For the first 30 d, a modified gamma function gave the best fit for the first lactation, the inverse polynomial function for the second lactation, and the quadratic log function for the third lactation. The diphasic logistic function gave the best fit for the remaining two periods and was not significantly different from the best fitting models for the first 30-d period. Hence, this function may be useful to describe the lactation curve of Holstein cows for dairy herds in which the daily milk yield of individual cows is constantly monitored with a computer.

  11. Prospective Measurement of Daily Health Behaviors: Modeling Temporal Patterns in Missing Data, Sexual Behavior, and Substance Use in an Online Daily Diary Study of Gay and Bisexual Men.

    PubMed

    Rendina, H Jonathon; Ventuneac, Ana; Mustanski, Brian; Grov, Christian; Parsons, Jeffrey T

    2016-08-01

    Daily diary and other intensive longitudinal methods are increasingly being used to investigate fluctuations in psychological and behavioral processes. To inform the development of this methodology, we sought to explore predictors of and patterns in diary compliance and behavioral reports. We used multilevel modeling to analyze data from an online daily diary study of 371 gay and bisexual men focused on sexual behavior and substance use. We found that greater education and older age as well as lower frequency of substance use were associated with higher compliance. Using polynomial and trigonometric functions, we found evidence for circaseptan patterns in compliance, sexual behavior, and substance use, as well as linear declines in compliance and behavior over time. The results suggest potential sources of non-random patterns of missing data and suggest that trigonometric terms provide a similar but more parsimonious investigation of circaseptan rhythms than do third-order polynomial terms.

  12. A Multivariate model for Monte-Carlo Simulation of Spatially and Temporally Correlated Daily Rainfall Intensities

    NASA Astrophysics Data System (ADS)

    Mok, C. M.; Suribhatla, R. M.; Wanakule, N.; Zhang, M.

    2009-12-01

    A reliability-based water resources management framework has been developed by AMEC Geomatrix over the last few years to optimally manage a water supply system that serves over two million people in the northern Tampa Bay region in Florida, USA, while protecting wetland health and preventing seawater intrusion. The framework utilizes stochastic optimization techniques to account for uncertainties associated with the prediction of water demand, surface water availability, baseline groundwater levels, a non-anthropogenic reservoir water budget, and hydrological/hydrogeological properties. Except for the hydro¬geological properties, these uncertainties are partially caused by uncertainties in future rainfall patterns in the region. We present here a novel multivariate statistical model of rainfall and a methodology for generating Monte-Carlo realizations based on the statistical model. The model is intended to capture spatial-temporal characteristics of daily rainfall intensity in 172 basins in the northern Tampa Bay region and is characterized by its high dimensionality. Daily rainfall intensity in each basin is expressed as product of a binary random variable (RV) corresponding to the event of rain and a continuous RV representing the amount of rain. For the binary RVs we use a bivariate transformation technique to generate the Monte-Carlo realizations that form the basis for sequential simulation of the continuous RVs. A non-parametric Gaussian copula is used to develop the multivariate model for continuous RVs. This methodology captures key spatial and temporal characteristics of daily rainfall intensities and overcomes numerical issues posed by high-dimensionality of the Gaussian copula.

  13. Modeling and estimation of stage-specific daily survival probabilities of nests

    USGS Publications Warehouse

    Stanley, T.R.

    2000-01-01

    In studies of avian nesting success, it is often of interest to estimate stage-specific daily survival probabilities of nests. When data can be partitioned by nesting stage (e.g., incubation stage, nestling stage), piecewise application of the Mayfield method or Johnsona??s method is appropriate. However, when the data contain nests where the transition from one stage to the next occurred during the interval between visits, piecewise approaches are inappropriate. In this paper, I present a model that allows joint estimation of stage-specific daily survival probabilities even when the time of transition between stages is unknown. The model allows interval lengths between visits to nests to vary, and the exact time of failure of nests does not need to be known. The performance of the model at various sample sizes and interval lengths between visits was investigated using Monte Carlo simulations, and it was found that the model performed quite well: bias was small and confidence-interval coverage was at the nominal 95% rate. A SAS program for obtaining maximum likelihood estimates of parameters, and their standard errors, is provided in the Appendix.

  14. Daily stress, coping, and well-being in parents of children with autism: a multilevel modeling approach.

    PubMed

    Pottie, Colin G; Ingram, Kathleen M

    2008-12-01

    This study used a repeated daily measurement design to examine the direct and moderating effects of coping on daily psychological distress and well-being in parents of children with Autism Spectrum Disorders (ASD). Twice weekly over a 12-week period, 93 parents provided reports of their daily stress, coping responses, and end-of-day mood. Multilevel modeling analyses identified 5 coping responses (e.g., seeking support, positive reframing) that predicted increased daily positive mood and 4 (e.g., escape, withdrawal) that were associated with decreased positive mood. Similarly, 2 coping responses were associated with decreased daily negative mood and 5 predicted increased negative mood. The moderating effects of gender and the 11 coping responses were also examined. Gender did not moderate the daily coping?mood relationship, however 3 coping responses (emotional regulation, social support, and worrying) were found to moderate the daily stress?mood relationship. Additionally, ASD symptomatology, and time since an ASD diagnosis were not found to predict daily parental mood. This study is perhaps the first to identify coping responses that enhance daily well-being and mitigate daily distress in parents of children with ASD.

  15. Modeling daily variation of trihalomethane compounds in drinking water system, Houston, Texas.

    PubMed

    Chaib, Embarka; Moschandreas, Demetrios

    2008-03-01

    Total trihalomethanes (TTHM) concentrations vary widely and periodically between 70 and 130 ppb. Data from the National Environmental Services Laboratory, Houston, Texas indicate that pH and free residual chlorine contribute minimally to the wide variability of TTHM levels. Temperature variation in drinking fluctuates from 11 to 27 degrees C. The objective of this research is to formulate a model that delineates more clearly the daily variations of the most prevalent volatile trihalomethane by-products: chloroform (CHCl3), bromodichloromethane (CHBr2Cl), and bromoform (CHBr3) levels from drinking water. This model simulates the daily fluctuation of THM at a single location and at any time during the day as a function of the water temperature and the average concentration of TTHM, which can be estimated. The hypothesis of this study is that observed daily fluctuations of TTHM, CHCl3, CHCl2Br, CHClBr2, and CHBr3 are periodic. This hypothesis is tested using autocorrelation functions and it is shown that for the series of pH the correlation coefficient is maximal at zero lags, rapidly decreases to zero, and increases again between 4- and 6-h period. Such pattern suggests random fluctuation unrelated to time. However, the series of free residual chlorine, temperature, TTHM, CHCl3, CHCl2Br, CHClBr2, and CHBr3 suggest a different pattern. The correlation coefficient increases when the time-shift approaches 24 h. These repetitions in fluctuation of content over a 24-h period are statistically significant. The model formulated in this study provides insights in TTHM variation and is a necessary tool to reduce the error when estimating potential risk from exposure to trihalomethane compounds in drinking water system. In general, calculation of potential risk by using a value measured early morning or late afternoon concentrations were found minimal lead to an underestimation of the population risk.

  16. Modeling and forecasting foreign exchange daily closing prices with normal inverse Gaussian

    NASA Astrophysics Data System (ADS)

    Teneng, Dean

    2013-09-01

    We fit the normal inverse Gaussian(NIG) distribution to foreign exchange closing prices using the open software package R and select best models by Käärik and Umbleja (2011) proposed strategy. We observe that daily closing prices (12/04/2008 - 07/08/2012) of CHF/JPY, AUD/JPY, GBP/JPY, NZD/USD, QAR/CHF, QAR/EUR, SAR/CHF, SAR/EUR, TND/CHF and TND/EUR are excellent fits while EGP/EUR and EUR/GBP are good fits with a Kolmogorov-Smirnov test p-value of 0.062 and 0.08 respectively. It was impossible to estimate normal inverse Gaussian parameters (by maximum likelihood; computational problem) for JPY/CHF but CHF/JPY was an excellent fit. Thus, while the stochastic properties of an exchange rate can be completely modeled with a probability distribution in one direction, it may be impossible the other way around. We also demonstrate that foreign exchange closing prices can be forecasted with the normal inverse Gaussian (NIG) Lévy process, both in cases where the daily closing prices can and cannot be modeled by NIG distribution.

  17. 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

  18. Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

    NASA Astrophysics Data System (ADS)

    Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  19. A hybrid orographic plus statistical model for downscaling daily precipitation in Northern California

    USGS Publications Warehouse

    Pandey, G.R.; Cayan, D.R.; Dettinger, M.D.; Georgakakos, K.P.

    2000-01-01

    A hybrid (physical-statistical) scheme is developed to resolve the finescale distribution of daily precipitation over complex terrain. The scheme generates precipitation by combining information from the upper-air conditions and from sparsely distributed station measurements; thus, it proceeds in two steps. First, an initial estimate of the precipitation is made using a simplified orographic precipitation model. It is a steady-state, multilayer, and two-dimensional model following the concepts of Rhea. The model is driven by the 2.5?? ?? 2.5?? gridded National Oceanic and Atmospheric Administration-National Centers for Environmental Prediction upper-air profiles, and its parameters are tuned using the observed precipitation structure of the region. Precipitation is generated assuming a forced lifting of the air parcels as they cross the mountain barrier following a straight trajectory. Second, the precipitation is adjusted using errors between derived precipitation and observations from nearby sites. The study area covers the northern half of California, including coastal mountains, central valley, and the Sierra Nevada. The model is run for a 5-km rendition of terrain for days of January-March over the period of 1988-95. A jackknife analysis demonstrates the validity of the approach. The spatial and temporal distributions of the simulated precipitation field agree well with the observed precipitation. Further, a mapping of model performance indices (correlation coefficients, model bias, root-mean-square error, and threat scores) from an array of stations from the region indicates that the model performs satisfactorily in resolving daily precipitation at 5-km resolution.

  20. [Estimation model for daily transpiration of greenhouse muskmelon in its vegetative growth period].

    PubMed

    Zhang, Da-Long; Li, Jian-Ming; Wu, Pu-Te; Li, Wei-Li; Zhao, Zhi-Hua; Xu, Fei; Li, Jun

    2013-07-01

    For developing an estimation method of muskmelon transpiration in greenhouse, an estimation model for the daily transpiration of greenhouse muskmelon in its vegetative growth period was established, based on the greenhouse environmental parameters, muskmelon growth and development parameters, and soil moisture parameters. According to the specific environment in greenhouse, the item of aerodynamics in Penman-Monteith equation was modified, and the greenhouse environmental sub-model suitable for calculating the reference crop evapotranspiration in greenhouse was deduced. The crop factor sub-model was established with the leaf area index as independent variable, and the form of the model was linear function. The soil moisture sub-model was established with the soil relative effective moisture content as independent variable, and the form of the model was logarithmic function. With interval sowing, the model parameters were estimated and analyzed, according to the measurement data of different sowing dates in a year. The prediction accuracy of the model for sufficient irrigation and water-saving irrigation was verified, according to measurement data when the relative soil moisture content was 80%, 70%, and 60%, and the mean relative error was 11.5%, 16.2% , and 16.9% respectively. The model was a beneficial exploration for the application of Penman-Monteith equation under greenhouse environment and water-saving irrigation, having good application foreground and popularization value.

  1. R-vine models for spatial time series with an application to daily mean temperature.

    PubMed

    Erhardt, Tobias Michael; Czado, Claudia; Schepsmeier, Ulf

    2015-06-01

    We introduce an extension of R-vine copula models to allow for spatial dependencies and model based prediction at unobserved locations. The proposed spatial R-vine model combines the flexibility of vine copulas with the classical geostatistical idea of modeling spatial dependencies using the distances between the variable locations. In particular, the model is able to capture non-Gaussian spatial dependencies. To develop and illustrate our approach, we consider daily mean temperature data observed at 54 monitoring stations in Germany. We identify relationships between the vine copula parameters and the station distances and exploit these in order to reduce the huge number of parameters needed to parametrize a 54-dimensional R-vine model fitted to the data. The new distance based model parametrization results in a distinct reduction in the number of parameters and makes parameter estimation and prediction at unobserved locations feasible. The prediction capabilities are validated using adequate scoring techniques, showing a better performance of the spatial R-vine copula model compared to a Gaussian spatial model.

  2. Short-Course Therapy with Daily Rifapentine in a Murine Model of Latent Tuberculosis Infection

    PubMed Central

    Zhang, Tianyu; Zhang, Ming; Rosenthal, Ian M.; Grosset, Jacques H.; Nuermberger, Eric L.

    2009-01-01

    Rationale: Regimens recommended to treat latent tuberculosis infection (LTBI) are 3 to 9 months long. A 2-month rifampin+pyrazinamide regimen is no longer recommended. Shorter regimens are highly desirable. Because substituting rifapentine for rifampin in the standard regimen for active tuberculosis halves the treatment duration needed to prevent relapse in mice, we hypothesized daily rifapentine-based regimens could shorten LTBI treatment to 2 months or less. Objectives: To improve an existing model of LTBI chemotherapy and evaluate the efficacy of daily rifapentine-based regimens. Methods: Mice were immunized with a more immunogenic recombinant Bacille Calmette-Guérin strain (rBCG30) and received very low-dose aerosol infection with Mycobacterium tuberculosis to establish a stable lung bacterial burden below 104 CFU without drug treatment. Mice received a control (isoniazid alone, rifampin alone, rifampin+isoniazid, rifampin+pyrazinamide) or test (rifapentine alone, rifapentine+isoniazid, rifapentine+pyrazinamide, rifapentine+isoniazid+pyrazinamide) regimen for 8 weeks. Rifamycin doses were 10 mg/kg/d, analogous to the same human doses. Outcomes were biweekly lung CFU counts and relapse after 4 to 8 weeks of treatment. Measurements and Main Results: M. tuberculosis CFU counts remained stable around 3.65 log10 in immunized, untreated mice. Isoniazid or rifampin left all or most mice culture-positive at week 8. Rifampin+isoniazid cured 0 and 53% of mice and rifampin+pyrazinamide cured 47 and 100% of mice in 4 and 8 weeks, respectively. Rifapentine-based regimens were more active than rifampin+isoniazid and indistinguishable from rifampin+pyrazinamide. Conclusions: In this improved murine model of LTBI chemotherapy with very low lung burden, existing regimens were well represented. Daily rifapentine-based regimens were at least as active as rifampin+pyrazinamide, suggesting they could effectively treat LTBI in 6 to 8 weeks. PMID:19729664

  3. Stochastic Modeling based on Dictionary Approach for the Generation of Daily Precipitation Occurrences

    NASA Astrophysics Data System (ADS)

    Panu, U. S.; Ng, W.; Rasmussen, P. F.

    2009-12-01

    The modeling of weather states (i.e., precipitation occurrences) is critical when the historical data are not long enough for the desired analysis. Stochastic models (e.g., Markov Chain and Alternating Renewal Process (ARP)) of the precipitation occurrence processes generally assume the existence of short-term temporal-dependency between the neighboring states while implying the existence of long-term independency (randomness) of states in precipitation records. Existing temporal-dependent models for the generation of precipitation occurrences are restricted either by the fixed-length memory (e.g., the order of a Markov chain model), or by the reining states in segments (e.g., persistency of homogenous states within dry/wet-spell lengths of an ARP). The modeling of variable segment lengths and states could be an arduous task and a flexible modeling approach is required for the preservation of various segmented patterns of precipitation data series. An innovative Dictionary approach has been developed in the field of genome pattern recognition for the identification of frequently occurring genome segments in DNA sequences. The genome segments delineate the biologically meaningful ``words" (i.e., segments with a specific patterns in a series of discrete states) that can be jointly modeled with variable lengths and states. A meaningful “word”, in hydrology, can be referred to a segment of precipitation occurrence comprising of wet or dry states. Such flexibility would provide a unique advantage over the traditional stochastic models for the generation of precipitation occurrences. Three stochastic models, namely, the alternating renewal process using Geometric distribution, the second-order Markov chain model, and the Dictionary approach have been assessed to evaluate their efficacy for the generation of daily precipitation sequences. Comparisons involved three guiding principles namely (i) the ability of models to preserve the short-term temporal-dependency in

  4. Temporal and spatial intermittency of sub-daily precipitation in general circulation models

    NASA Astrophysics Data System (ADS)

    Klingaman, Nicholas; Martin, Gill; Moise, Aurel

    2015-04-01

    General circulation models often fail to reproduce the observed spatial and temporal distributions of tropical precipitation (e.g. Stephens et al. 2010). The need for improved understanding of how a warming climate may change precipitation variability and extremes has focused model developers' attention on the inability of convection parameterizations to represent the observed range of deep convective processes (e.g. Rossow et al. 2013). As climate-model resolutions increase towards scales previously used for short-term forecasting, the benefits of seamless modelling are being balanced by increasingly apparent deficiencies in convection parameterizations. Under particular scrutiny are the consequences of poorly simulated sub-daily, gridpoint precipitation variability on rainfall distributions at longer (e.g., daily, seasonal, decadal) and larger scales. We present the behaviour of tropical convection in the MetUM in a hierarchy of global configurations from ~10km to ~100km resolution, and in ten climate models from the "Vertical Structure and Diabatic Processes of the Madden-Julian Oscillation" project. We establish new methods of analysing timestep precipitation that allow comparisons between resolutions and physical parameterizations. We first investigate the relationship between timestep-to-timestep variations of modelled convection at the gridbox scale and its variability on longer and larger scales, and compare simulated and observed rainfall variability. We demonstrate that convection parameterization changes that alter timestep variability (e.g., entrainment and detrainment rates and closure timescales) also affect longer-scale variability. For example, we show that ~100 km configurations exhibit coherent timestep intermittency at large spatial scales, which reduce at finer resolutions and with parameterisation changes that suppress the depth and intensity of convection. Despite a wide variety of timestep behaviour, the models from the "Vertical Structure

  5. Modeling daily average stream temperature from air temperature and watershed area

    NASA Astrophysics Data System (ADS)

    Butler, N. L.; Hunt, J. R.

    2012-12-01

    Habitat restoration efforts within watersheds require spatial and temporal estimates of water temperature for aquatic species especially species that migrate within watersheds at different life stages. Monitoring programs are not able to fully sample all aquatic environments within watersheds under the extreme conditions that determine long-term habitat viability. Under these circumstances a combination of selective monitoring and modeling are required for predicting future geospatial and temporal conditions. This study describes a model that is broadly applicable to different watersheds while using readily available regional air temperature data. Daily water temperature data from thirty-eight gauges with drainage areas from 2 km2 to 2000 km2 in the Sonoma Valley, Napa Valley, and Russian River Valley in California were used to develop, calibrate, and test a stream temperature model. Air temperature data from seven NOAA gauges provided the daily maximum and minimum air temperatures. The model was developed and calibrated using five years of data from the Sonoma Valley at ten water temperature gauges and a NOAA air temperature gauge. The daily average stream temperatures within this watershed were bounded by the preceding maximum and minimum air temperatures with smaller upstream watersheds being more dependent on the minimum air temperature than maximum air temperature. The model assumed a linear dependence on maximum and minimum air temperature with a weighting factor dependent on upstream area determined by error minimization using observed data. Fitted minimum air temperature weighting factors were consistent over all five years of data for each gauge, and they ranged from 0.75 for upstream drainage areas less than 2 km2 to 0.45 for upstream drainage areas greater than 100 km2. For the calibration data sets within the Sonoma Valley, the average error between the model estimated daily water temperature and the observed water temperature data ranged from 0.7

  6. The Earth's Shape and Movements: Teachers' Perception of the Relations Between Daily Observation and Scientific Models

    NASA Astrophysics Data System (ADS)

    Ferreira, Flávia Polati; Leite, Cristina

    2015-07-01

    The Earth’s shape and movements are some of the most common issues in official documents and research studies of astronomy education. Many didactic proposals suggest these issues within observational astronomy. Therefore, we present in this paper some of the main results of a research study of the teachers’ perception of the relations between the knowledge from daily observation and scientific models currently accepted about the “earth’s shape and movements”. Data were obtained in application of the didactic proposal during a teacher training course for teachers from São Paulo, have been constructed with the dynamics “Three Pedagogical Moments” and guided by some of the central ideas of the educator Paulo Freire. The results indicate that a small proportion of teachers seem to understand some of the relations of “apparent contradictions” and “limitations” with the concepts of spatiality, and many of them argued based only on vague phrases or "buzzwords", unconnected to the problem explored. The difficulties of teachers to relate elements of daily observation with scientific models seem to indicate a necessity to approach some these aspects with the astronomical knowledge in the teacher training courses.

  7. A stage structured mosquito model incorporating effects of precipitation and daily temperature fluctuations.

    PubMed

    Wang, Xia; Tang, Sanyi; Cheke, Robert A

    2016-12-21

    An outbreak of dengue fever in Guangdong province in 2014 was the most serious outbreak ever recorded in China. Given the known positive correlation between the abundance of mosquitoes and the number of dengue fever cases, a stage structured mosquito model was developed to investigate the cause of the large abundance of mosquitoes in 2014 and its implications for outbreaks of the disease. Data on the Breteau index (number of containers positive for larvae per 100 premises investigated), temperature and precipitation were used for model fitting. The egg laying rate, the development rate and the mortality rates of immatures and adults were obtained from the estimated parameters. Moreover, effects of daily fluctuations of temperature on these parameters were obtained and the effects of temperature and precipitation were analyzed by simulations. Our results indicated that the abundance of mosquitoes depended not only on the total annual precipitation but also on the distribution of the precipitation. The daily mean temperature had a nonlinear relationship with the abundance of mosquitoes, and large diurnal temperature differences can reduce the abundance of mosquitoes. In addition, effects of increasing precipitation and temperature were interdependent. Our findings suggest that the large abundance of mosquitoes in 2014 was mainly caused by the distribution of the precipitation. In the perspective of mosquito control, our results reveal that it is better to clear water early and spray insecticide between April and August in case of limited resources.

  8. Reconstruction of daily erythemal UV radiation values for the last century - The benefit of modelled ozone

    NASA Astrophysics Data System (ADS)

    Junk, J.; Feister, U.; Rozanov, E.; Krzyścin, J. W.

    2013-05-01

    Solar erythemal UV radiation (UVER) is highly relevant for numerous biological processes that affect plants, animals, and human health. Nevertheless, long-term UVER records are scarce. As significant declines in the column ozone concentration were observed in the past and a recovery of the stratospheric ozone layer is anticipated by the middle of the 21st century, there is a strong interest in the temporal variation of UVER time series. Therefore, we combined groundbased measurements of different meteorological variables with modeled ozone data sets to reconstruct time series of daily totals of UVER at the Meteorological Observatory Potsdam, Germany. Artificial neural networks were trained with measured UVER, sunshine duration, the day of year, measured and modeled total column ozone, as well as the minimum solar zenith angle. This allows for the reconstruction of daily totals of UVER for the period from 1901 to 1999. Additionally, analyses of the long-term variations from 1901 until 1999 of the reconstructed, new UVER data set are presented. The time series of monthly and annual totals of UVER provide a long-term meteorological basis for epidemiological investigations in human health and occupational medicine for the region of Potsdam and Berlin. A strong benefit of our ANN-approach is the fact that it can be easily adapted to different geographical locations, as successfully tested in the framework of the COSTAction 726.

  9. Temporal scaling analysis of irradiance estimated from daily satellite data and numerical modelling

    NASA Astrophysics Data System (ADS)

    Vindel, Jose M.; Navarro, Ana A.; Valenzuela, Rita X.; Ramírez, Lourdes

    2016-11-01

    The temporal variability of global irradiance estimated from daily satellite data and numerical models has been compared for different spans of time. According to the time scale considered, a different behaviour can be expected for each climate. Indeed, for all climates and at small scale, the persistence decreases as this scale increases, but the mediterranean climate, and its continental variety, shows higher persistence than oceanic climate. The probabilities of maintaining the values of irradiance after a certain period of time have been used as a first approximation to analyse the quality of each source, according to the climate. In addition, probability distributions corresponding to variations of clearness indices measured at several stations located in different climate zones have been compared with those obtained from satellite and modelling estimations. For this work, daily radiation data from the reanalysis carried out by the European Centre for Medium-Range Weather Forecasts and from the Satellite Application Facilities on climate monitoring have been used for mainland Spain. According to the results, the temporal series estimation of irradiance is more accurate when using satellite data, independent of the climate considered. In fact, the coefficients of determination corresponding to the locations studied are always above 0.92 in the case of satellite data, while this coefficient decreases to 0.69 for some cases of the numerical model. This conclusion is more evident in oceanic climates, where the most important errors can be observed. Indeed, in this case, the RRMSE derived from the CM-SAF estimations is 20.93%, while in the numerical model, it is 48.33%. Analysis of the probabilities corresponding to variations in the clearness indices also shows a better behaviour of the satellite-derived estimates for oceanic climate. For the standard mediterranean climate, the satellite also provides better results, though the numerical model improves

  10. Genetic parameters for functional traits in dairy cattle from daily random regression models.

    PubMed

    Karacaören, B; Jaffrézic, F; Kadarmideen, H N

    2006-02-01

    The objective of the research was to estimate genetic parameters, such as heritabilities and genetic correlations, using daily test day data for milk yield (MY), milking speed (MS), dry matter intake (DMI), and body weight (BW) using random regression methodology. Data were from first lactation dairy cows (n = 320) from the Chamau research farm of the Swiss Federal Institute of Technology, Switzerland over the period from April 1994 to 2004. All traits were recorded daily using automated machines. Estimated heritabilities (h(2)) varied from 0.18 to 0.30 (mean h(2) = 0.24) for MY, 0.003 to 0.098 (mean h(2) = 0.03) for MS, 0.22 to 0.53 (mean h(2) = 0.43) for BW, and 0.12 to 0.34 (mean h(2) = 0.23) for DMI. A permanent environmental effect was included in both the univariate and bivariate models, but was assumed constant in estimating some genetic correlations because of convergence problems. Estimated genetic correlations varied from 0.31 to 0.41 between MY and MS, from -0.47 to 0.29 between MY and DMI, from -0.60 to 0.54 between MY and BW, from 0.17 to 0.26 between MS and DMI, from -0.18 to 0.25 between MS and BW, and from -0.89 to 0.29 between DMI and BW. Genetic correlations for MY, MS, DMI, and BW from calving to midlactation decreased similarly to 0.40, 0.36, 0.14, and 0.36 and, at the end of the lactation, decreased to -0.06, 0.23, -0.07, and 0.09, respectively. Daily genetic variance-covariance of many functional traits are reported for the first time and will be useful when constructing selection indexes for more than one trait based on longitudinal genetic parameters.

  11. Modeling trait and state variation using multilevel factor analysis with PANAS daily diary data

    PubMed Central

    Merz, Erin L.; Roesch, Scott C.

    2011-01-01

    This study used daily diary data to model trait and state Positive Affect (PA) and Negative Affect (NA) using the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). Data were collected from 364 college students over five days. Intraclass correlation coefficients suggested approximately equal amounts of variability at the trait and state levels. Multilevel factor analysis revealed that the model specifying two correlated factors (PA, NA) and correlated uniqueness terms among redundant items provided the best fit. Trait and state PA and NA were generally associated with stress, anxiety, depression, and three types of self-esteem (performance, academic, social). The coefficients describing these relationships differed somewhat, suggesting that trait and state measurement may have different predictive utility. PMID:21516166

  12. HIGH-RESOLUTION SPATIAL MODELING OF DAILY WEATHER ELEMENTS FOR A CATCHMENT IN THE OREGON CASCADE MOUNTAINS, UNITED STATES

    EPA Science Inventory

    High-quality, daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decision making. This paper describes the development, application, and assessment of ...

  13. Bayesian multinomial probit modeling of daily windows of susceptibility for maternal PM2.5 exposure and congenital heart defects

    EPA Science Inventory

    Past epidemiologic studies suggest maternal ambient air pollution exposure during critical periods of the pregnancy is associated with fetal development. We introduce a multinomial probit model that allows for the joint identification of susceptible daily periods during the pregn...

  14. A current precipitation index-based model for continuous daily runoff simulation in seasonally snow covered sub-arctic catchments

    NASA Astrophysics Data System (ADS)

    Akanegbu, Justice O.; Marttila, Hannu; Ronkanen, Anna-Kaisa; Kløve, Bjørn

    2017-02-01

    A new precipitation index-based model, which includes a snow accumulation and melt component, has been developed to simulate hydrology in high latitude catchments. The model couples a point snowmelt model with a current precipitation index (CPI) formulation to simulate continuous daily runoff from catchments with seasonal snow cover. A new runoff conversion factor: CT and Lf, threshold flow factor ThQ and runoff transformation function Maxbas were introduced into the CPI equation, which converts and transforms the routed daily CPI into daily runoff and maintains the daily base flow in the catchment. The model was developed using twelve sub-arctic boreal catchments located above and below the Arctic Circle in northern Finland, representing a region with considerable seasonal snow cover. The results showed that the model can adequately simulate and produce the dynamics of daily runoff from catchments where the underlying physical conditions are not known. An open-access Excel-based model is provided with this paper for daily runoff simulations. The model can be used to estimate runoff in sub-arctic regions where little data is typically available but significant changes in climate are expected, with considerable shifts in the amount and timing of snowmelt and runoff.

  15. Evaluating regional climate models for simulating sub-daily rainfall extremes

    NASA Astrophysics Data System (ADS)

    Cortés-Hernández, Virginia Edith; Zheng, Feifei; Evans, Jason; Lambert, Martin; Sharma, Ashish; Westra, Seth

    2016-09-01

    Sub-daily rainfall extremes are of significant societal interest, with implications for flash flooding and the design of urban stormwater systems. It is increasingly recognised that extreme subdaily rainfall will intensify as a result of global temperature increases, with regional climate models (RCMs) representing one of the principal lines of evidence on the likely magnitude and spatiotemporal characteristics of these changes. To evaluate the ability of RCMs to simulate subdaily extremes, it is common to compare the simulated statistical characteristics of the extreme rainfall events with those from observational records. While such analyses are important, they provide insufficient insight into whether the RCM reproduces the correct underlying physical processes; in other words, whether the model "gets the right answers for the right reasons". This paper develops a range of metrics to assess the performance of RCMs in capturing the physical mechanisms that produce extreme rainfall. These metrics include the diurnal and seasonal cycles, relationship between rainfall intensity and temperature, temporal scaling, and the spatial structure of extreme rainfall events. We evaluate a high resolution RCM—the Weather Research Forecasting model—over the Greater Sydney region, using three alternative parametrization schemes. The model shows consistency with the observations for most of the proposed metrics. Where differences exist, these are dependent on both the rainfall duration and model parameterization strategy. The use of physically meaningful performance metrics not only enhances the confidence in model simulations, but also provides better diagnostic power to assist with future model improvement.

  16. Sleep and affect in older adults: using multilevel modeling to examine daily associations

    PubMed Central

    McCRAE, CHRISTINA S.; McNAMARA, JOSEPH P. H.; ROWE, MEREDETH A.; DZIERZEWSKI, JOSEPH M.; DIRK, JUDITH; MARSISKE, MICHAEL; CRAGGS, JASON G.

    2010-01-01

    SUMMARY The main objective of the present study was to examine daily associations (intraindividual variability or IIV) between sleep and affect in older adults. Greater understanding of these associations is important, because both sleep and affect represent modifiable behaviors that can have a major influence on older adults’ health and well-being. We collected sleep diaries, actigraphy, and affect data concurrently for 14 days in 103 community-dwelling older adults. Multilevel modeling was used to assess the sleep–affect relationship at both the group (between-persons) and individual (within-person or IIV) levels. We hypothesized that nights characterized by better sleep would be associated with days characterized by higher positive affect and lower negative affect, and that the inverse would be true for poor sleep. Daily associations were found between affect and subjective sleep, only and were in the hypothesized direction. Specifically, nights with greater reported awake time or lower sleep quality ratings were associated with days characterized by less positive affect and more negative affect. Gender was not a significant main effect in the present study, despite previous research suggesting gender differences in the sleep–affect relationship. The fact that self-ratings of sleep emerged as the best predictors of affect may suggest that perceived sleep is a particularly important predictor. Finally, our results suggest exploration of affect as a potential intervention target in late-life insomnia is warranted. PMID:18275554

  17. Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates

    PubMed Central

    Huang, Hongtai; Barzyk, Timothy M.

    2016-01-01

    Many different quantitative techniques have been developed to either assess Environmental Justice (EJ) issues or estimate exposure and dose for risk assessment. However, very few approaches have been applied to link EJ factors to exposure dose estimate and identify potential impacts of EJ factors on dose-related variables. The purpose of this study is to identify quantitative approaches that incorporate conventional risk assessment (RA) dose modeling and cumulative risk assessment (CRA) considerations of disproportionate environmental exposure. We apply the Average Daily Dose (ADD) model, which has been commonly used in RA, to better understand impacts of EJ indicators upon exposure dose estimates and dose-related variables, termed the Environmental-Justice-Average-Daily-Dose (EJ-ADD) approach. On the U.S. nationwide census tract-level, we defined and quantified two EJ indicators (poverty and race/ethnicity) using an EJ scoring method to examine their relation to census tract-level multi-chemical exposure dose estimates. Pollutant doses for each tract were calculated using the ADD model, and EJ scores were assigned to each tract based on poverty- or race-related population percentages. Single- and multiple-chemical ADD values were matched to the tract-level EJ scores to analyze disproportionate dose relationships and contributing EJ factors. We found that when both EJ indicators were examined simultaneously, ADD for all pollutants generally increased with larger EJ scores. To demonstrate the utility of using EJ-ADD on the local scale, we approximated ADD levels of lead via soil/dust ingestion for simulated communities with different EJ-related scenarios. The local-level simulation indicates a substantial difference in exposure-dose levels between wealthy and EJ communities. The application of the EJ-ADD approach can link EJ factors to exposure dose estimate and identify potential EJ impacts on dose-related variables. PMID:28036053

  18. A long range dependent model with nonlinear innovations for simulating daily river flows

    NASA Astrophysics Data System (ADS)

    Elek, P.; Márkus, L.

    2004-04-01

    We present the analysis aimed at the estimation of flood risks of Tisza River in Hungary on the basis of daily river discharge data registered in the last 100 years. The deseasonalised series has skewed and leptokurtic distribution and various methods suggest that it possesses substantial long memory. This motivates the attempt to fit a fractional ARIMA model with non-Gaussian innovations as a first step. Synthetic streamflow series can then be generated from the bootstrapped innovations. However, there remains a significant difference between the empirical and the synthetic density functions as well as the quantiles. This brings attention to the fact that the innovations are not independent, both their squares and absolute values are autocorrelated. Furthermore, the innovations display non-seasonal periods of high and low variances. This behaviour is characteristic to generalised autoregressive conditional heteroscedastic (GARCH) models. However, when innovations are simulated as GARCH processes, the quantiles and extremes of the discharge series are heavily overestimated. Therefore we suggest to fit a smooth transition GARCH-process to the innovations. In a standard GARCH model the dependence of the variance on the lagged innovation is quadratic whereas in our proposed model it is a bounded function. While preserving long memory and eliminating the correlation from both the generating noise and from its square, the new model is superior to the previously mentioned ones in approximating the probability density, the high quantiles and the extremal behaviour of the empirical river flows.

  19. On the use of gridded daily temperature data to calculate the extended spring indices phenological models

    NASA Astrophysics Data System (ADS)

    Zurita-Milla, Raul; Mehdipoor, Hamed; Batarseh, Sana; Ault, Toby; Schwartz, Mark D.

    2014-05-01

    Models that predict the timing of recurrent biological events play an important role in supporting the systematic study of phenological changes at a variety of spatial and temporal scales. One set of such models are the extended Spring indices (SI-x). These models predicts a suite of phenological metrics ("first leaf" and "first bloom," "last freeze" and the "damage index") from temperature data and geographic location (to model the duration of the day). The SI-x models were calibrated using historical phenological and weather observations from the continental US. In particular, the models relied on first leaf and first bloom observations for lilac and honeysuckle and on daily minimum and maximum temperature values from a number of weather stations located near to the sites where phenological observations were made. In this work, we study the use of DAYMET (http://daymet.ornl.gov/) to calculate the SI-x models over the continental USA. DAYMET offers daily gridded maximum and minimum temperature values for the period 1980 to 2012. Using an automatic downloader, we downloaded complete DAYMET temperature time series for the over 1100 geographic locations where historical lilac observations were made. The temperature values were parsed and, using the recently available MATLAB code, the SI-x indices were calculated. Subsequently, the predicted first leaf and first bloom dates were compared with historical lilac observations. The RMSE between predicted and observed lilac leaf/bloom dates was calculated after identifying data from the same geographic location and year. Results were satisfactory for the lilac observations in the Eastern US (e.g. the RMSE for the blooming date was of about 5 days). However, the correspondence between the observed and predicted lilac values in the West was rather week (e.g. RMSE for the blooming date of about 22 days). This might indicate that DAYMET temperature data in this region of the US might contain larger uncertainties due to a more

  20. Daily sesame oil supplement attenuates joint pain by inhibiting muscular oxidative stress in osteoarthritis rat model.

    PubMed

    Hsu, Dur-Zong; Chu, Pei-Yi; Jou, I-Ming

    2016-03-01

    Osteoarthritis (OA) is the most common form of arthritis, affecting approximately 15% of the population. The aim of this study was to evaluate the efficacy of sesame oil in controlling OA pain in rats. Rat joint pain was induced by medial meniscal transection in Sprague-Dawley rats and assessed by using hindlimb weight distribution method. Muscular oxidative stress was assessed by determining lipid peroxidation, reactive oxygen species and circulating antioxidants. Sesame oil significantly decreased joint pain compared with positive control group in a dose-dependent manner. Sesame oil decreased lipid peroxidation in muscle but not in serum. Further, sesame oil significantly decreased muscular superoxide anion and peroxynitrite generations but increased muscular glutathione and glutathione peroxidase levels. Further, sesame oil significantly increased nuclear factor erythroid-2-related factor (Nrf2) expression compared with positive control group. We concluded that daily sesame oil supplement may attenuate early joint pain by inhibiting Nrf2-associated muscular oxidative stress in OA rat model.

  1. An Evidence-Based Adoption of Technology Model for Remote Monitoring of Elders’ Daily Activities

    PubMed Central

    2011-01-01

    What benefit will new technologies offer if they are inadequately or not used? This work presents a meta-synthesis of adoption of technology related findings from four innovative monitoring intervention research studies with older adults and their informal and/or formal caregivers. Each study employed mixed methods analyses that lead to an understanding of the key variables that influenced adoption of telephone and Internet based wireless remote monitoring technologies by elders and their caregivers. The studies were all conducted in “real world” homes ranging from solo residences to multi-story independent living residential buildings. Insights gained came from issues not found in controlled laboratory environments but in the complex interplay of family-elder-staff dynamics around balancing safety and independence. Findings resulted in an adoption of technology model for remote monitoring of elders’ daily activities derived from evidence based research to advance both practical and theoretical development in the field of gerontechnology. PMID:21423843

  2. Estimation of completeness magnitude with a Bayesian modeling of daily and weekly variations in earthquake detectability

    NASA Astrophysics Data System (ADS)

    Iwata, T.

    2014-12-01

    In the analysis of seismic activity, assessment of earthquake detectability of a seismic network is a fundamental issue. For this assessment, the completeness magnitude Mc, the minimum magnitude above which all earthquakes are recorded, is frequently estimated. In most cases, Mc is estimated for an earthquake catalog of duration longer than several weeks. However, owing to human activity, noise level in seismic data is higher on weekdays than on weekends, so that earthquake detectability has a weekly variation [e.g., Atef et al., 2009, BSSA]; the consideration of such a variation makes a significant contribution to the precise assessment of earthquake detectability and Mc. For a quantitative evaluation of the weekly variation, we introduced the statistical model of a magnitude-frequency distribution of earthquakes covering an entire magnitude range [Ogata & Katsura, 1993, GJI]. The frequency distribution is represented as the product of the Gutenberg-Richter law and a detection rate function. Then, the weekly variation in one of the model parameters, which corresponds to the magnitude where the detection rate of earthquakes is 50%, was estimated. Because earthquake detectability also have a daily variation [e.g., Iwata, 2013, GJI], and the weekly and daily variations were estimated simultaneously by adopting a modification of a Bayesian smoothing spline method for temporal change in earthquake detectability developed in Iwata [2014, Aust. N. Z. J. Stat.]. Based on the estimated variations in the parameter, the value of Mc was estimated. In this study, the Japan Meteorological Agency catalog from 2006 to 2010 was analyzed; this dataset is the same as analyzed in Iwata [2013] where only the daily variation in earthquake detectability was considered in the estimation of Mc. A rectangular grid with 0.1° intervals covering in and around Japan was deployed, and the value of Mc was estimated for each gridpoint. Consequently, a clear weekly variation was revealed; the

  3. BIOMAP A Daily Time Step, Mechanistic Model for the Study of Ecosystem Dynamics

    NASA Astrophysics Data System (ADS)

    Wells, J. R.; Neilson, R. P.; Drapek, R. J.; Pitts, B. S.

    2010-12-01

    BIOMAP simulates competition between two Plant Functional Types (PFT) at any given point in the conterminous U.S. using a time series of daily temperature (mean, minimum, maximum), precipitation, humidity, light and nutrients, with PFT-specific rooting within a multi-layer soil. The model employs a 2-layer canopy biophysics, Farquhar photosynthesis, the Beer-Lambert Law for light attenuation and a mechanistic soil hydrology. In essence, BIOMAP is a re-built version of the biogeochemistry model, BIOME-BGC, into the form of the MAPSS biogeography model. Specific enhancements are: 1) the 2-layer canopy biophysics of Dolman (1993); 2) the unique MAPSS-based hydrology, which incorporates canopy evaporation, snow dynamics, infiltration and saturated and unsaturated percolation with ‘fast’ flow and base flow and a ‘tunable aquifer’ capacity, a metaphor of D’Arcy’s Law; and, 3) a unique MAPSS-based stomatal conductance algorithm, which simultaneously incorporates vapor pressure and soil water potential constraints, based on physiological information and many other improvements. Over small domains the PFTs can be parameterized as individual species to investigate fundamental vs. potential niche theory; while, at more coarse scales the PFTs can be rendered as more general functional groups. Since all of the model processes are intrinsically leaf to plot scale (physiology to PFT competition), it essentially has no ‘intrinsic’ scale and can be implemented on a grid of any size, taking on the characteristics defined by the homogeneous climate of each grid cell. Currently, the model is implemented on the VEMAP 1/2 degree, daily grid over the conterminous U.S. Although both the thermal and water-limited ecotones are dynamic, following climate variability, the PFT distributions remain fixed. Thus, the model is currently being fitted with a ‘reproduction niche’ to allow full dynamic operation as a Dynamic General Vegetation Model (DGVM). While global simulations

  4. A physics-based correction model for homogenizing sub-daily temperature series

    NASA Astrophysics Data System (ADS)

    Auchmann, R.; BröNnimann, S.

    2012-09-01

    A new physics-based technique for correcting inhomogeneities present in sub-daily temperature records is proposed. The approach accounts for changes in the sensor-shield characteristics that affect the energy balance dependent on ambient weather conditions (radiation, wind). An empirical model is formulated that reflects the main atmospheric processes and can be used in the correction step of a homogenization procedure. The model accounts for short- and long-wave radiation fluxes (including a snow cover component for albedo calculation) of a measurement system, such as a radiation shield. One part of the flux is further modulated by ventilation. The model requires only cloud cover and wind speed for each day, but detailed site-specific information is necessary. The final model has three free parameters, one of which is a constant offset. The three parameters can be determined, e.g., using the mean offsets for three observation times. The model is developed using the example of the change from the Wild screen to the Stevenson screen in the temperature record of Basel, Switzerland, in 1966. It is evaluated based on parallel measurements of both systems during a sub-period at this location, which were discovered during the writing of this paper. The model can be used in the correction step of homogenization to distribute a known mean step-size to every single measurement, thus providing a reasonable alternative correction procedure for high-resolution historical climate series. It also constitutes an error model, which may be applied, e.g., in data assimilation approaches.

  5. A biology-driven receptor model for daily pollen allergy risk in Korea based on Weibull probability density function

    NASA Astrophysics Data System (ADS)

    Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo

    2016-07-01

    Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.

  6. A biology-driven receptor model for daily pollen allergy risk in Korea based on Weibull probability density function

    NASA Astrophysics Data System (ADS)

    Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo

    2017-02-01

    Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.

  7. Statistical modeling of daily and subdaily stream temperatures: Application to the Methow River Basin, Washington

    NASA Astrophysics Data System (ADS)

    Caldwell, R. J.; Gangopadhyay, S.; Bountry, J.; Lai, Y.; Elsner, M. M.

    2013-07-01

    Management of water temperatures in the Columbia River Basin (Washington) is critical because water projects have substantially altered the habitat of Endangered Species Act listed species, such as salmon, throughout the basin. This is most important in tributaries to the Columbia, such as the Methow River, where the spawning and rearing life stages of these cold water fishes occurs. Climate change projections generally predict increasing air temperatures across the western United States, with less confidence regarding shifts in precipitation. As air temperatures rise, we anticipate a corresponding increase in water temperatures, which may alter the timing and availability of habitat for fish reproduction and growth. To assess the impact of future climate change in the Methow River, we couple historical climate and future climate projections with a statistical modeling framework to predict daily mean stream temperatures. A K-nearest neighbor algorithm is also employed to: (i) adjust the climate projections for biases compared to the observed record and (ii) provide a reference for performing spatiotemporal disaggregation in future hydraulic modeling of stream habitat. The statistical models indicate the primary drivers of stream temperature are maximum and minimum air temperature and stream flow and show reasonable skill in predictability. When compared to the historical reference time period of 1916-2006, we conclude that increases in stream temperature are expected to occur at each subsequent time horizon representative of the year 2020, 2040, and 2080, with an increase of 0.8 ± 1.9°C by the year 2080.

  8. A novel hybrid forecasting model for PM₁₀ and SO₂ daily concentrations.

    PubMed

    Wang, Ping; Liu, Yong; Qin, Zuodong; Zhang, Guisheng

    2015-02-01

    Air-quality forecasting in urban areas is difficult because of the uncertainties in describing both the emission and meteorological fields. The use of incomplete information in the training phase restricts practical air-quality forecasting. In this paper, we propose a hybrid artificial neural network and a hybrid support vector machine, which effectively enhance the forecasting accuracy of an artificial neural network (ANN) and support vector machine (SVM) by revising the error term of the traditional methods. The hybrid methodology can be described in two stages. First, we applied the ANN or SVM forecasting system with historical data and exogenous parameters, such as meteorological variables. Then, the forecasting target was revised by the Taylor expansion forecasting model using the residual information of the error term in the previous stage. The innovation involved in this approach is that it sufficiently and validly utilizes the useful residual information on an incomplete input variable condition. The proposed method was evaluated by experiments using a 2-year dataset of daily PM₁₀ (particles with a diameter of 10 μm or less) concentrations and SO₂ (sulfur dioxide) concentrations from four air pollution monitoring stations located in Taiyuan, China. The theoretical analysis and experimental results demonstrated that the forecasting accuracy of the proposed model is very promising.

  9. Coping with Daily Stressors: Modeling Intraethnic Variation in Mexican American Adolescents

    ERIC Educational Resources Information Center

    Aldridge, Arianna A.; Roesch, Scott C.

    2008-01-01

    Using daily diary methodology, 67 Mexican American adolescents completed measures assessing daily stressors experienced, specific coping strategies employed with reference to these stressors, and indices of psychological health over 5 consecutive days. With respect to coping usage, adolescents reported they most often used planning and least often…

  10. Multisite multivariate modeling of daily precipitation and temperature in the Canadian Prairie Provinces using generalized linear models

    NASA Astrophysics Data System (ADS)

    Asong, Zilefac E.; Khaliq, M. N.; Wheater, H. S.

    2016-11-01

    Based on the Generalized Linear Model (GLM) framework, a multisite stochastic modelling approach is developed using daily observations of precipitation and minimum and maximum temperatures from 120 sites located across the Canadian Prairie Provinces: Alberta, Saskatchewan and Manitoba. Temperature is modeled using a two-stage normal-heteroscedastic model by fitting mean and variance components separately. Likewise, precipitation occurrence and conditional precipitation intensity processes are modeled separately. The relationship between precipitation and temperature is accounted for by using transformations of precipitation as covariates to predict temperature fields. Large scale atmospheric covariates from the National Center for Environmental Prediction Reanalysis-I, teleconnection indices, geographical site attributes, and observed precipitation and temperature records are used to calibrate these models for the 1971-2000 period. Validation of the developed models is performed on both pre- and post-calibration period data. Results of the study indicate that the developed models are able to capture spatiotemporal characteristics of observed precipitation and temperature fields, such as inter-site and inter-variable correlation structure, and systematic regional variations present in observed sequences. A number of simulated weather statistics ranging from seasonal means to characteristics of temperature and precipitation extremes and some of the commonly used climate indices are also found to be in close agreement with those derived from observed data. This GLM-based modelling approach will be developed further for multisite statistical downscaling of Global Climate Model outputs to explore climate variability and change in this region of Canada.

  11. Comparative efficacy of two daily use mouthrinses: randomized clinical trial using an experimental gingivitis model.

    PubMed

    Charles, Christine Ann; McGuire, James Anthony; Sharma, Naresh Chandra; Qaqish, James

    2011-01-01

    Two antimicrobial agents, a fixed combination of essential oils (EOs) and 0.07% cetylpyridinium chloride (CPC) are found in commercially available mouthrinses, Listerine® Antiseptic and Crest® Pro HealthTM, respectively. Both mouthrinses have been shown to control dental plaque and gingivitis in short and longer term studies. The aim of this study was to determine the comparative effectiveness of these two mouthrinses using a 2-week experimental gingivitis model. Qualified subjects were randomly assigned to one of three mouthrinse groups: a fixed combination of EOs, 0.07% CPC, or negative control (C) rinse. Following baseline clinical assessments and a dental prophylaxis, subjects began a two-week period in which they rinsed twice daily with their assigned rinse and abstained from any mechanical oral hygiene procedures or other oral care products. Subjects were reassessed at the end of the two-week period. One hundred and forty-seven subjects were randomized and 142 completed this study. After two weeks use, the EOs rinse was superior (p < 0.011) to the CPC rinse in inhibiting the development of gingivitis, plaque, and bleeding, with 9.4% and 6.6% reductions compared to CPC for gingivitis and plaque, respectively. Both rinses were superior to the negative control rinse (p < 0.001). This study demonstrates that the essential oil-containing mouthrinse has superior antiplaque/antigingivitis effectiveness compared to the 0.07% CPC-containing mouthrinse without mechanical oral hygiene influence.

  12. Modeling and forecasting daily movement of ambient air mean PM₂.₅ concentration based on the elliptic orbit model with weekly quasi-periodic extension: a case study.

    PubMed

    Yang, Zong-chang

    2014-01-01

    Nowadays, the issue of air pollution has continuously been a global public health concern. Modeling and forecasting daily movement of ambient air mean PM2.5 concentration is an increasingly important task as it is intimately associated with human health that the air pollution has unignorable negative effects in reducing air quality, damaging environment, even causing serious harm to health. It is demonstrated that daily movement of mean PM₂.₅ concentration approximately exhibits weekly cyclical variations as daily particle pollution in the air is largely influenced by human daily activities. Then, based on weekly quasi-periodic extension for daily movement of mean PM₂.₅ concentration, the called elliptic orbit model is proposed to describe its movement. By mapping daily movement of mean PM₂.₅ concentration as one time series into the polar coordinates, each 7-day movement is depicted as one elliptic orbit. Experimental result and analysis indicate workability and effectiveness of the proposed method. Here we show that with the weekly quasi-periodic extension, daily movements of mean PM₂.₅ concentration at the given monitoring stations in Xiangtan of China are well described by the elliptic orbit model, which provides a vivid description for modeling and prediction daily movement of mean PM₂.₅ concentration in a concise and intuitive way.

  13. Modeling Approach to Estimate Daily Streamflow Characteristics at Monitoring Sites in New Jersey

    NASA Astrophysics Data System (ADS)

    Kauffman, L. J.; Ayers, M. A.; Wolock, D. M.

    2001-05-01

    Results of a recent U.S. Geological Survey (USGS) study of streams in northern New Jersey confirm the concern of many ecologists that the maintenance of forest cover, stable base flows, cobble habitats, and functioning wetland systems are critical to stream biological communities. In the study, biological communities were found to be affected adversely by increases in peak discharge, streamflow variability, impervious surfaces, and phosphorus concentrations--all of which are related to increases in human population density. The effect of changes in streamflow on aquatic community health led the USGS, in cooperation with the New Jersey Department of Environmental Protection, to develop a watershed modeling approach to define the flow characteristics associated with each of the 820 biologic monitoring sites in New Jersey. The flow characteristics generated with the model will provide key information for an assessment of the major factors that contribute to the current status of benthic invertebrate community health. The model also will be incorporated in a State planning "toolbox" for use in local and regional land-use planning. The watershed model uses daily precipitation and temperature values from 1948 to present that are estimated for each watershed by using a spatial regression approach with available National Weather Service station data. A topographic wetness index, derived from digital topography, is used in conjunction with soil depth and permeability as the basis for pervious-area runoff estimates. Pervious-area runoff parameters are calibrated to USGS streamflow data for watersheds with less than 5 percent total impervious surface cover (ISC). The parameters then are regionalized. With pervious-area parameters set, the impervious-area runoff is calibrated for gaged urban watersheds (ISC greater than 5 percent). Differences between observed and predicted runoff are assumed to be the result of changes in runoff caused by urban development. The effective

  14. Development of models to inform a national Daily Landslide Hazard Assessment for Great Britain

    NASA Astrophysics Data System (ADS)

    Dijkstra, Tom A.; Reeves, Helen J.; Dashwood, Claire; Pennington, Catherine; Freeborough, Katy; Mackay, Jonathan D.; Uhlemann, Sebastian S.; Chambers, Jonathan E.; Wilkinson, Paul B.

    2015-04-01

    were combined with records of observed landslide events to establish which antecedent effective precipitation (AEP) signatures of different duration could be used as a pragmatic proxy for the occurrence of landslides. It was established that 1, 7, and 90 days AEP provided the most significant correlations and these were used to calculate the probability of at least one landslide occurring. The method was then extended over the period 2006 to 2014 and the results evaluated against observed occurrences. It is recognised that AEP is a relatively poor proxy for simulating effective stress conditions along potential slip surfaces. However, the temporal pattern of landslide probability compares well to the observed occurrences and provides a potential benefit to assist with the DLHA. Further work is continuing to fine-tune the model for landslide type, better spatial resolution of effective precipitation input and cross-reference to models that capture changes in water balance and conditions along slip surfaces. The latter is facilitated by intensive research at several field laboratories, such as the Hollin Hill site in Yorkshire, England. At this site, a decade of activity has generated a broad range of research and a wealth of data. This paper reports on one example of recent work; the characterisation of near surface hydrology using infiltration experiments where hydrological pathways are captured, among others, by electrical resistivity tomography. This research, which has further developed our understanding of soil moisture movement in a heterogeneous landslide complex, has highlighted the importance of establishing detailed ground models to enable determination of landslide potential at high resolution. In turn, the knowledge gained through this research is used to enhance the expertise for the daily landslide hazard assessments at a national scale.

  15. A general model for estimation of daily global solar radiation using air temperatures and site geographic parameters in Southwest China

    NASA Astrophysics Data System (ADS)

    Li, Mao-Fen; Fan, Li; Liu, Hong-Bin; Guo, Peng-Tao; Wu, Wei

    2013-01-01

    Estimation of daily global solar radiation (Rs) from routinely measured temperature data has been widely developed and used in many different areas of the world. However, many of them are site specific. It is assumed that a general model for estimating daily Rs using temperature variables and geographical parameters could be achieved within a climatic region. This paper made an attempt to develop a general model to estimate daily Rs using routinely measured temperature data (maximum (Tmax, °C) and minimum (Tmin, °C) temperatures) and site geographical parameters (latitude (La, °N), longitude (Ld, °E) and altitude (Alt, m)) for Guizhou and Sichuan basin of southwest China, which was classified into the hot summer and cold winter climate zone. Comparison analysis was carried out through statistics indicators such as root mean squared error of percentage (RMSE%), modeling efficiency (ME), coefficient of residual mass (CRM) and mean bias error (MBE). Site-dependent daily Rs estimating models were calibrated and validated using long-term observed weather data. A general formula was then obtained from site geographical parameters and the better fit site-dependent models with mean RMSE% of 38.68%, mean MBE of 0.381 MJ m-2 d-1, mean CRM of 0.04 and mean ME value of 0.713.

  16. A spatial-temporal regression model to predict daily outdoor residential PAH concentrations in an epidemiologic study in Fresno, CA

    NASA Astrophysics Data System (ADS)

    Noth, Elizabeth M.; Hammond, S. Katharine; Biging, Gregory S.; Tager, Ira B.

    2011-05-01

    BackgroundPolycyclic aromatic hydrocarbons (PAHs) are generated as a byproduct of combustion, and are associated with respiratory symptoms and increased risk of asthma attacks. ObjectivesTo assign daily, outdoor exposures to participants in the Fresno Asthmatic Children's Environment Study (FACES) using land use regression models for the sum of 4-, 5- and 6-ring PAHs (PAH456). MethodsPAH data were collected daily at the EPA Supersite in Fresno, CA from 10/2000 through 2/2007. From 2/2002 to 2/2003, intensive air pollution sampling was conducted at 83 homes of participants in the FACES study. These measurement data were combined with meteorological data, source data, and other spatial variables to form a land use regression model to assign daily exposure at all FACES homes for all years of the study (2001-2008). ResultsThe model for daily, outdoor residential PAH456 concentrations accounted for 80% of the between-home variability and 18% of the within-home variability. Both temporal and spatial variables were significant in the model. Traffic characteristics and home heating fuel were the main spatial explanatory variables. ConclusionsBecause spatial and temporal distributions of PAHs vary on an intra-urban scale, the location of the child's home within the urban setting plays an important role in the level of exposure that each child has to PAHs.

  17. Development and evaluation of a daily temporal interpolation model for fine particulate matter species concentrations and source apportionment

    NASA Astrophysics Data System (ADS)

    Redman, Jeremiah D.; Holmes, Heather A.; Balachandran, Sivaraman; Maier, Marissa L.; Zhai, Xinxin; Ivey, Cesunica; Digby, Kyle; Mulholland, James A.; Russell, Armistead G.

    2016-09-01

    The impacts of emissions sources on air quality in St. Louis, Missouri are assessed for use in acute health effects studies. However, like many locations in the United States, the speciated particulate matter (PM) measurements from regulatory monitoring networks in St. Louis are only available every third day. The power of studies investigating acute health effects of air pollution is reduced when using one-in-three day source impacts compared to daily source impacts. This paper presents a temporal interpolation model to estimate daily speciated PM2.5 mass concentrations and source impact estimates using one-in-three day measurements. The model is used to interpolate 1-in-3 day source impact estimates and to interpolate the 1-in-3 day PM species concentrations prior to source apportionment (SA). Both approaches are compared and evaluated using two years (June 2001-May 2003) of daily data from the St. Louis Midwest Supersite (STL-SS). Data withholding is used to simulate a 1-in-3 day data set from the daily data to evaluate interpolated estimates. After evaluation using the STL-SS data, the model is used to estimate daily source impacts at another site approximately seven kilometers (7 km) northwest of the STL-SS (Blair); results between the sites are compared. For interpolated species concentrations, the model performs better for secondary species (sulfate, nitrate, ammonium, and organic carbon) than for primary species (metals and elemental carbon), likely due to the greater spatial autocorrelation of secondary species. Pearson correlation (R) values for sulfate, nitrate, ammonium, elemental carbon, and organic carbon ranged from 0.61 (elemental carbon, EC2) to 0.97 (sulfate). For trace metals, the R values ranged from 0.31 (Ba) to 0.81 (K). The interpolated source impact estimates also indicated a stronger correlation for secondary sources. Correlations of the secondary source impact estimates based on measurement data and interpolation data ranged from 0.68 to 0

  18. Comparison of Daily Total Precipitable Water From Satellite and Model Reanalysis Fields

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.; Suggs, R. J.; Haines, S. L.

    2000-01-01

    Previous studies have shown that there is fairly good agreement between the monthly values of total precipitable water (TPW) from the NVAP data set, a multi satellite and radiosonde merged data product, and the NCEP reanalysis TPW data. However, there are regions and time periods where significant differences between the data sets are found in the monthly mean TPW time series and period of record trends. To better understand these differences seen in the monthly data values, the daily mean TPW data are examined. Possible contributions to the TPW differences such as data quality of the individual NVAP data set components associated with missing or irregular daily values are addressed. Also, effects associated with the weighting of the individual NVAP data set components to form a merged product are considered. The daily variations in TPW exhibited by each data set are also quantified and compared between the data sets.

  19. Technical evaluation of a total maximum daily load model for Upper Klamath and Agency Lakes, Oregon

    USGS Publications Warehouse

    Wood, Tamara M.; Wherry, Susan A.; Carter, James L.; Kuwabara, James S.; Simon, Nancy S.; Rounds, Stewart A.

    2013-01-01

    We reviewed a mass balance model developed in 2001 that guided establishment of the phosphorus total maximum daily load (TMDL) for Upper Klamath and Agency Lakes, Oregon. The purpose of the review was to evaluate the strengths and weaknesses of the model and to determine whether improvements could be made using information derived from studies since the model was first developed. The new data have contributed to the understanding of processes in the lakes, particularly internal loading of phosphorus from sediment, and include measurements of diffusive fluxes of phosphorus from the bottom sediments, groundwater advection, desorption from iron oxides at high pH in a laboratory setting, and estimates of fluxes of phosphorus bound to iron and aluminum oxides. None of these processes in isolation, however, is large enough to account for the episodically high values of whole-lake internal loading calculated from a mass balance, which can range from 10 to 20 milligrams per square meter per day for short periods. The possible role of benthic invertebrates in lake sediments in the internal loading of phosphorus in the lake has become apparent since the development of the TMDL model. Benthic invertebrates can increase diffusive fluxes several-fold through bioturbation and biodiffusion, and, if the invertebrates are bottom feeders, they can recycle phosphorus to the water column through metabolic excretion. These organisms have high densities (1,822–62,178 individuals per square meter) in Upper Klamath Lake. Conversion of the mean density of tubificid worms (Oligochaeta) and chironomid midges (Diptera), two of the dominant taxa, to an areal flux rate based on laboratory measurements of metabolic excretion of two abundant species suggested that excretion by benthic invertebrates is at least as important as any of the other identified processes for internal loading to the water column. Data from sediment cores collected around Upper Klamath Lake since the development of the

  20. One-Day Offset between Simulated and Observed Daily Hydrographs: An Exploration of the Issue in Automatic Model Calibration

    NASA Astrophysics Data System (ADS)

    Asadzadeh, M.; Leon, L.; Yang, W.

    2014-12-01

    The literature of hydrologic modelling shows that in daily simulation of the rainfall-runoff relationship, the simulated hydrograph response to some rainfall events happens one day earlier than the observed one. This one-day offset issue results in significant residuals between the simulated and observed hydrographs and adversely impacts the model performance metrics that are based on the aggregation of daily residuals. Based on the analysis of sub-daily rainfall and runoff data sets in this study, the one-day offset issue appears to be inevitable when the same time interval, e.g. the calendar day, is used to measure daily rainfall and runoff data sets. This is an error introduced through data aggregation and needs to be properly addressed before calculating the model performance metrics. Otherwise, the metrics would not represent the modelling quality and could mislead the automatic calibration of the model. In this study, an algorithm is developed to scan the simulated hydrograph against the observed one, automatically detect all one-day offset incidents and shift the simulated hydrograph of those incidents one day forward before calculating the performance metrics. This algorithm is employed in the automatic calibration of the Soil and Water Assessment Tool that is set up for the Rouge River watershed in Southern Ontario, Canada. Results show that with the proposed algorithm, the automatic calibration to maximize the daily Nash-Sutcliffe (NS) identifies a solution that accurately estimates the magnitude of peak flow rates and the shape of rising and falling limbs of the observed hydrographs. But, without the proposed algorithm, the same automatic calibration finds a solution that systematically underestimates the peak flow rates in order to perfectly match the timing of simulated and observed peak flows.

  1. Daily fluctuations in teachers' well-being: a diary study using the Job Demands-Resources model.

    PubMed

    Simbula, Silvia

    2010-10-01

    The study tests the dynamic nature of the Job Demands-Resources model with regard to both motivational and health impairment processes. It does so by examining whether daily fluctuations in co-workers' support (i.e., a typical job resource) and daily fluctuations in work/family conflict (i.e., a typical job demand) predict day-levels of job satisfaction and mental health through work engagement and exhaustion, respectively. A total of 61 schoolteachers completed a general questionnaire and a daily survey over a period of five consecutive work days. Multilevel analyses provided evidence for both the above processes. Consistently with the hypotheses, our results showed that day-level work engagement mediated the impact of day-level co-workers' support on day-level job satisfaction and day-level mental health, after general levels of work engagement and outcome variables had been controlled for. Moreover, day-level exhaustion mediated the relationship between day-level work/family conflict and day-level job satisfaction and day-level mental health after general levels of exhaustion and outcome variables had been controlled for. These findings provide new insights into the dynamic psychological processes that determine daily fluctuations in employee well-being. Such insights may be transformed into job redesign strategies and other interventions designed to enhance work-related psychological well-being on a daily level.

  2. Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes

    USGS Publications Warehouse

    Yuan, W.; Liu, S.; Zhou, G.; Tieszen, L.L.; Baldocchi, D.; Bernhofer, C.; Gholz, H.; Goldstein, Allen H.; Goulden, M.L.; Hollinger, D.Y.; Hu, Y.; Law, B.E.; Stoy, P.C.; Vesala, T.; Wofsy, S.C.

    2007-01-01

    The quantitative simulation of gross primary production (GPP) at various spatial and temporal scales has been a major challenge in quantifying the global carbon cycle. We developed a light use efficiency (LUE) daily GPP model from eddy covariance (EC) measurements. The model, called EC-LUE, is driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux (used to calculate moisture stress). The EC-LUE model relies on two assumptions: First, that the fraction of absorbed PAR (fPAR) is a linear function of NDVI; Second, that the realized light use efficiency, calculated from a biome-independent invariant potential LUE, is controlled by air temperature or soil moisture, whichever is most limiting. The EC-LUE model was calibrated and validated using 24,349 daily GPP estimates derived from 28 eddy covariance flux towers from the AmeriFlux and EuroFlux networks, covering a variety of forests, grasslands and savannas. The model explained 85% and 77% of the observed variations of daily GPP for all the calibration and validation sites, respectively. A comparison with GPP calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS) indicated that the EC-LUE model predicted GPP that better matched tower data across these sites. The realized LUE was predominantly controlled by moisture conditions throughout the growing season, and controlled by temperature only at the beginning and end of the growing season. The EC-LUE model is an alternative approach that makes it possible to map daily GPP over large areas because (1) the potential LUE is invariant across various land cover types and (2) all driving forces of the model can be derived from remote sensing data or existing climate observation networks.

  3. Prioritization of pesticides based on daily dietary exposure potential as determined from the SHEDS model

    EPA Science Inventory

    A major pathway for exposure to many pesticides is through diet. The objectives were to rank pesticides by comparing their calculated daily dietary exposure as determined by EPA's Stochastic Human Exposure and Dose Simulation (SHEDS) to single pesticides for different age groups ...

  4. Suitability of global circulation model downscaled BCCA daily precipitation for local hydrologic applications

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Monthly precipitation projections for various climate change scenarios have been available for over a decade. More recently, Bias Corrected Constructed Analogue (BCCA) daily precipitation projections have been available for climate change investigations. In this study, the direct use of BCCA precipi...

  5. A NEW MODEL TO ESTIMATE DAILY ENERGY EXPENDITURE FOR WINTERING WATERFOWL

    EPA Science Inventory

    Activity budgets of wintering waterfowl have been widely used to assess habitat quality. However, when factors such as prey abundance or protection from exposure to cold or wind determine quality, measures of daily energy expenditure (DEE) may be more appropriate for this purpos...

  6. Daily Care

    MedlinePlus

    ... Life Daily Plan Activities Communication Food & Eating Music & Art Personal Care Incontinence Bathing Dressing & Grooming Dental Care ... About Us | News | Events | Press | Careers | Privacy Policy | Copyrights & Reprints | Contact Us National Headquarters Alzheimer's Association National ...

  7. Evaluation of SUNY satellite-to-irradiance model performance using ECMWF GEMS daily aerosol optical depth reanalysis data

    NASA Astrophysics Data System (ADS)

    Itterly, Kyle F.

    The current version of the State University of New York (SUNY) radiative transfer model (RTM) uses climatological monthly averages derived from a National Renewable Energy Labs (NREL) gridded dataset to parameterize aerosol optical depth (AOD), water vapor and ozone. This is mostly due to the limited availability of high spatially and temporally resolved observations. Several global chemical transport models are analyzed and compared in depth to determine which daily AOD dataset should be implemented into the SUNY Model. After thorough comparison, the chemical transport model chosen was the Global and regional Earth-system Monitoring using satellite and in-situ data (GEMS) model developed by the European Center for Medium Range Weather Forecasts (ECMWF). Using daily AOD values instead of monthly climatological values, the SUNY Model better captures events of extreme aerosol loadings, which greatly improves the accuracy in calculations of direct normal irradiance (DNI) and to a lesser extent, global horizontal irradiance (GHI). In clear-sky conditions with the sun directly overhead, a change in AOD from 0.1 to 0.5 is found to cause a 55% (20%) decrease in DNI (GHI) for Desert Rock, Nevada in January. A calibration scheme is applied to the daily GEMS AOD reanalysis data. For each site, the monthly means of the GEMS daily AOD are corrected by a factor to match the currently used monthly climatological AOD in order to avoid large errors caused by changing the magnitude of the monthly average AOD. The performance of the SUNY model improved significantly for many of the stations analyzed in this work after applying the daily-calibrated GEMS AOD. The Root Mean Squared Error (RMSE) was the most notable statistical improvement, which measures the model’s precision compared to the observed measurements from a ground station, and many other statistical improvements are also evident. All 7 SURFRAD locations showed improvements in DNI RMSE after using the calibrated GEMS

  8. Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

    NASA Technical Reports Server (NTRS)

    Mu, M.; Randerson, J. T.; vanderWerf, G. R.; Giglio, L.; Kasibhatla, P.; Morton, D.; Collatz, G. J.; DeFries, R. S.; Hyer, E. J.; Prins, E. M.; Griffith, D. W. T.; Wunch, D.; Toon, G. C.; Sherlock, V.; Wennberg, P. O.

    2011-01-01

    Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003.2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS) ]derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top ]down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from

  9. Evaluation of Downscaled CMIP5 Model Skill in Simulating Daily Maximum Temperature Over the Southeastern United States

    NASA Astrophysics Data System (ADS)

    Keellings, D.

    2015-12-01

    Downscaled CMIP5 climate projections of maximum daily temperature from the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections archive are examined regionally over the southeastern U.S. Three measures of model skill (means-based, distribution-based, extreme-based) are utilized to assess the ability of 15 downscaled models to simulate daily maximum temperature observations. A new test is proposed to determine statistical significance of the probability density function based skill measures. Skill scores are found to be generally high for all three measures throughout the study region, but lower scores are present in coastal and mountainous areas. Application of the significance test shows that while the skill scores may be high they are not significantly higher than could be expected at random in some areas. The distribution-based skill scores are not significant in much of Florida and the Appalachians. The extreme-based skill scores are not significant in more than 90% of the region for all models investigated. The findings suggest that although the downscaled models have simulated observed means well and are a good match to the entire distribution of observations, they are not simulating the occurrence of extreme (above 90th percentile) maximum daily temperatures.

  10. Achieving Consistent Multiple Daily Low-Dose Bacillus anthracis Spore Inhalation Exposures in the Rabbit Model

    PubMed Central

    Barnewall, Roy E.; Comer, Jason E.; Miller, Brian D.; Gutting, Bradford W.; Wolfe, Daniel N.; Director-Myska, Alison E.; Nichols, Tonya L.; Taft, Sarah C.

    2012-01-01

    Repeated low-level exposures to biological agents could occur before or after the remediation of an environmental release. This is especially true for persistent agents such as B. anthracis spores, the causative agent of anthrax. Studies were conducted to examine aerosol methods needed for consistent daily low aerosol concentrations to deliver a low-dose (less than 106 colony forming units (CFU) of B. anthracis spores) and included a pilot feasibility characterization study, acute exposure study, and a multiple 15 day exposure study. This manuscript focuses on the state-of-the-science aerosol methodologies used to generate and aerosolize consistent daily low aerosol concentrations and resultant low inhalation doses to rabbits. The pilot feasibility characterization study determined that the aerosol system was consistent and capable of producing very low aerosol concentrations. In the acute, single day exposure experiment, targeted inhaled doses of 1 × 102, 1 × 103, 1 × 104, and 1 × 105 CFU were used. In the multiple daily exposure experiment, rabbits were exposed multiple days to targeted inhaled doses of 1 × 102, 1 × 103, and 1 × 104 CFU. In all studies, targeted inhaled doses remained consistent from rabbit-to-rabbit and day-to-day. The aerosol system produced aerosolized spores within the optimal mass median aerodynamic diameter particle size range to reach deep lung alveoli. Consistency of the inhaled dose was aided by monitoring and recording respiratory parameters during the exposure with real-time plethysmography. Overall, the presented results show that the animal aerosol system was stable and highly reproducible between different studies and over multiple exposure days. PMID:22919662

  11. Markov Chains for Random Urinalysis III: Daily Model and Drug Kinetics

    DTIC Science & Technology

    1994-01-01

    III: Daily M and Drug Kinetcs E L ’-- TF " 94-04546 9 4 2 0 9 0 6 2 Ap ,o.vod f r p c, tease cdsibutn Is un a ted NPRDC-TN-94-12 January 1994 Markov...and maintairi- 9 the d~ata needed. a~d corro’eting a-!d rev~ewing the collection of infrmt~ationi Seid conriments regarding this burden estimate or any...PERFORMiNG ORGANIZATION Navy Personnel Research -and Development Center REPORT NUMBER San Diego, CA 92152-7250 NPRDC-TN-94-12 9 . SPONSO R!NGIMO NTO

  12. A Comparison of Satellite Based, Modeled Derived Daily Solar Radiation Data with Observed Data for the Continental US

    NASA Technical Reports Server (NTRS)

    White, Jeffrey W.; Hoogenboom, Gerrit; Wilkens, Paul W.; Stackhouse, Paul W., Jr.; Hoell, James M.

    2010-01-01

    Many applications of simulation models and related decision support tools for agriculture and natural resource management require daily meteorological data as inputs. Availability and quality of such data, however, often constrain research and decision support activities that require use of these tools. Daily solar radiation (SRAD) data are especially problematic because the instruments require electronic integrators, accurate sensors are expensive, and calibration standards are seldom available. The Prediction Of Worldwide Energy Resources (NASA/POWER; power.larc.nasa.gov) project at the NASA Langley Research Center estimates daily solar radiation based on data that are derived from satellite observations of outgoing visible radiances and atmospheric parameters based upon satellite observations and assimilation models. The solar data are available for a global 1 degree x 1 degree coordinate grid. SRAD can also be estimated based on attenuation of extraterrestrial radiation (Q0) using daily temperature and rainfall data to estimate the optical thickness of the atmosphere. This study compares daily solar radiation data from NASA/POWER (SRADNP) with instrument readings from 295 stations (SRADOB), as well as with values that were estimated with the WGENR solar generator. WGENR was used both with daily temperature and precipitation records from the stations reporting solar data and records from the NOAA Cooperative Observer Program (COOP), thus providing two additional sources of solar data, SRADWG and SRADCO. Values of SRADNP for different grid cells consistently showed higher correlations (typically 0.85 to 0.95) with SRADOB data than did SRADWG or SRADCO for sites within the corresponding cells. Mean values of SRADOB, SRADWG and SRADNP for sites within a grid cell usually were within 1 MJm-2d-1 of each other, but NASA/POWER values averaged 1.1 MJm-2d-1 lower than SRADOB. The magnitude of this bias was greater at lower latitudes and during summer months and may be at

  13. Daily and Hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

    NASA Technical Reports Server (NTRS)

    Mu, M.; Randerson, J. T.; van der Werf, G. R.; Giglio, L.; Kasibhatla, P.; Morton, D.; Collatz, G. J.; DeFries, R. S.; Hyer, E. J.; Prins, E. M.; Griffith, D. W. T.; Wunch, D.; Toon, G. C.; Sherlock, V.; Wennberg, P. O.

    2011-01-01

    Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We distributed monthly GFED3 emissions during 2003-2009 on a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) active fire observations. We found that patterns of daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of bunting in savannas. On diurnal timescales, our analysis of the GOES active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

  14. UNITED STATES METEOROLOGICAL DATA - DAILY AND HOURLY FILES TO SUPPORT PREDICTIVE EXPOSURE MODELING

    EPA Science Inventory

    ORD numerical models for pesticide exposure include a model of spray drift (AgDisp), a cropland pesticide persistence model (PRZM), a surface water exposure model (EXAMS), and a model of fish bioaccumulation (BASS). A unified climatological database for these models has been asse...

  15. Coping with daily thermal variability: behavioural performance of an ectotherm model in a warming world.

    PubMed

    Rojas, José M; Castillo, Simón B; Folguera, Guillermo; Abades, Sebastián; Bozinovic, Francisco

    2014-01-01

    Global climate change poses one of the greatest threats to species persistence. Most analyses of the potential biological impacts have focused on changes in mean temperature, but changes in thermal variance will also impact organisms and populations. We assessed the effects of acclimation to daily variance of temperature on dispersal and exploratory behavior in the terrestrial isopod Porcellio laevis in an open field. Acclimation treatments were 24 ± 0, 24 ± 4 and 24 ± 8 °C. Because the performance of ectotherms relates nonlinearly to temperature, we predicted that animals acclimated to a higher daily thermal variation should minimize the time exposed in the centre of open field, --i.e. increase the linearity of displacements. Consistent with our prediction, isopods acclimated to a thermally variable environment reduce their exploratory behaviour, hypothetically to minimize their exposure to adverse environmental conditions. This scenario as well as the long latency of animals after releases acclimated to variable environments is consistent with this idea. We suggested that to develop more realistic predictions about the biological impacts of climate change, one must consider the interactions between the mean and variance of environmental temperature on animals' performance.

  16. Coping with Daily Thermal Variability: Behavioural Performance of an Ectotherm Model in a Warming World

    PubMed Central

    Rojas, José M.; Castillo, Simón B.; Folguera, Guillermo; Abades, Sebastián; Bozinovic, Francisco

    2014-01-01

    Global climate change poses one of the greatest threats to species persistence. Most analyses of the potential biological impacts have focused on changes in mean temperature, but changes in thermal variance will also impact organisms and populations. We assessed the effects of acclimation to daily variance of temperature on dispersal and exploratory behavior in the terrestrial isopod Porcellio laevis in an open field. Acclimation treatments were 24±0, 24±4 and 24±8°C. Because the performance of ectotherms relates nonlinearly to temperature, we predicted that animals acclimated to a higher daily thermal variation should minimize the time exposed in the centre of open field, – i.e. increase the linearity of displacements. Consistent with our prediction, isopods acclimated to a thermally variable environment reduce their exploratory behaviour, hypothetically to minimize their exposure to adverse environmental conditions. This scenario as well as the long latency of animals after releases acclimated to variable environments is consistent with this idea. We suggested that to develop more realistic predictions about the biological impacts of climate change, one must consider the interactions between the mean and variance of environmental temperature on animals' performance. PMID:25207653

  17. Prioritization of pesticides based on daily dietary exposure potential as determined from the SHEDS model.

    PubMed

    Melnyk, Lisa Jo; Wang, Zhaohui; Li, Zhilin; Xue, Jianping

    2016-10-01

    A major pathway for exposure to many pesticides is through diet. The objectives were to rank pesticides by comparing their calculated daily dietary exposure as determined by EPA's Stochastic Human Exposure and Dose Simulation (SHEDS) to single pesticides for different age groups to acceptable daily intakes (ADI), characterize pesticide trends in exposures over different time periods, and determine commodities contributing to pesticide exposures. SHEDS was applied, using Pesticide Data Program (PDP) (1991-2011) and pesticide usage data on crops from USDA combined with NHANES dietary consumption data, to generate exposure estimates by age group. ADI data collected from EPA, WHO, and other sources were used to rank pesticides based on relativeness of the dietary exposure potential to ADI by age groups. Sensitivity analysis provided trends in pesticide exposures. Within SHEDS, commodities contributing the majority of pesticides with greatest exposure potential were determined. The results indicated that the highest ranking pesticides were methamidophos and diazinon which exceeded 100% of the ADI. Sensitivity analysis indicated that exposure to methamidophos, diazinon, malathion, ethion and formetanate hydrochloride had a marked decrease from 1991-1999 to 2000-2011. Contributions analysis indicated that apples, mushroom, carrots, and lettuce contributed to diazinon exposure. Beans and pepper contributed to methamidophos exposure.

  18. A Count Model to Study the Correlates of 60 Min of Daily Physical Activity in Portuguese Children

    PubMed Central

    Borges, Alessandra; Gomes, Thayse Natacha; Santos, Daniel; Pereira, Sara; dos Santos, Fernanda K.; Chaves, Raquel; Katzmarzyk, Peter T.; Maia, José

    2015-01-01

    This study aimed to present data on Portuguese children (aged 9–11 years) complying with moderate-to-vigorous physical activity (MVPA) guidelines, and to identify the importance of correlates from multiple domains associated with meeting the guidelines. Physical activity (PA) was objectively assessed by accelerometry throughout seven days on 777 children. A count model using Poisson regression was used to identify the best set of correlates that predicts the variability in meeting the guidelines. Only 3.1% of children met the recommended daily 60 min of MVPA for all seven days of the week. Further, the Cochrane–Armitage chi-square test indicated a linear and negative trend (p < 0.001) from none to all seven days of children complying with the guidelines. The count model explained 22% of the variance in meeting MVPA guidelines daily. Being a girl, having a higher BMI, belonging to families with higher income, sleeping more and taking greater time walking from home to a sporting venue significantly reduced the probability of meeting daily recommended MVPA across the seven days. Furthermore, compared to girls, increasing sleep time in boys increased their chances of compliance with the MVPA recommendations. These results reinforce the relevance of considering different covariates’ roles on PA compliance when designing efficient intervention strategies to promote healthy and active lifestyles in children. PMID:25730296

  19. The application of a Poisson model to the annual distribution of daily mortality at six Montreal hospitals.

    PubMed Central

    Zweig, J P; Csank, J Z

    1978-01-01

    The daily distributions of annual mortality for varying numbers of years between 1965 and 1975 were investigated in three geriatric hospitals and three general hospitals in the Montreal area. Nearly all the observed mortality distributions were found to mimic the classical Poisson distribution, with little departure. In two of the larger hospitals, the matching of the daily mortality distributions with their Poisson models met stringent statistical criteria. In one of them it was even possible to predict the expected mortality frequencies merely from a knowledge of the annual totals. The remaining four hospitals, which included the three geriatric institutions, also exhibited mortalities regarded as highly suggestive of Poisson distributions, although in one of the geriatric hospitals the mortality distribution tended to be somewhat erratic in this respect. PMID:711981

  20. A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

    NASA Astrophysics Data System (ADS)

    Duveiller, G.; Donatelli, M.; Fumagalli, D.; Zucchini, A.; Nelson, R.; Baruth, B.

    2017-02-01

    Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure

  1. Development of temporally refined land-use regression models predicting daily household-level air pollution in a panel study of lung function among asthmatic children.

    PubMed

    Johnson, Markey; Macneill, Morgan; Grgicak-Mannion, Alice; Nethery, Elizabeth; Xu, Xiaohong; Dales, Robert; Rasmussen, Pat; Wheeler, Amanda

    2013-01-01

    Regulatory monitoring data and land-use regression (LUR) models have been widely used for estimating individual exposure to ambient air pollution in epidemiologic studies. However, LUR models lack fine-scale temporal resolution for predicting acute exposure and regulatory monitoring provides daily concentrations, but fails to capture spatial variability within urban areas. This study coupled LUR models with continuous regulatory monitoring to predict daily ambient nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) at 50 homes in Windsor, Ontario. We compared predicted versus measured daily outdoor concentrations for 5 days in winter and 5 days in summer at each home. We also examined the implications of using modeled versus measured daily pollutant concentrations to predict daily lung function among asthmatic children living in those homes. Mixed effect analysis suggested that temporally refined LUR models explained a greater proportion of the spatial and temporal variance in daily household-level outdoor NO(2) measurements compared with daily concentrations based on regulatory monitoring. Temporally refined LUR models captured 40% (summer) and 10% (winter) more of the spatial variance compared with regulatory monitoring data. Ambient PM(2.5) showed little spatial variation; therefore, daily PM(2.5) models were similar to regulatory monitoring data in the proportion of variance explained. Furthermore, effect estimates for forced expiratory volume in 1 s (FEV(1)) and peak expiratory flow (PEF) based on modeled pollutant concentrations were consistent with effects based on household-level measurements for NO(2) and PM(2.5). These results suggest that LUR modeling can be combined with continuous regulatory monitoring data to predict daily household-level exposure to ambient air pollution. Temporally refined LUR models provided a modest improvement in estimating daily household-level NO(2) compared with regulatory monitoring data alone, suggesting that this

  2. Improving daily streamflow forecasts in mountainous Upper Euphrates basin by multi-layer perceptron model with satellite snow products

    NASA Astrophysics Data System (ADS)

    Uysal, Gökçen; Şensoy, Aynur; Şorman, A. Arda

    2016-12-01

    This paper investigates the contribution of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite Snow Cover Area (SCA) product and in-situ snow depth measurements to Artificial Neural Network model (ANN) based daily streamflow forecasting in a mountainous river basin. In order to represent non-linear structure of the snowmelt process, Multi-Layer Perceptron (MLP) Feed-Forward Backpropagation (FFBP) architecture is developed and applied in Upper Euphrates River Basin (10,275 km2) of Turkey where snowmelt constitutes approximately 2/3 of total annual volume of runoff during spring and early summer months. Snowmelt season is evaluated between March and July; 7 years (2002-2008) seasonal daily data are used during training while 3 years (2009-2011) seasonal daily data are split for forecasting. One of the fastest ANN training algorithms, the Levenberg-Marquardt, is used for optimization of the network weights and biases. The consistency of the network is checked with four performance criteria: coefficient of determination (R2), Nash-Sutcliffe model efficiency (ME), root mean square error (RMSE) and mean absolute error (MAE). According to the results, SCA observations provide useful information for developing of a neural network model to predict snowmelt runoff, whereas snow depth data alone are not sufficient. The highest performance is experienced when total daily precipitation, average air temperature data are combined with satellite snow cover data. The data preprocessing technique of Discrete Wavelet Analysis (DWA) is coupled with MLP modeling to further improve the runoff peak estimates. As a result, Nash-Sutcliffe model efficiency is increased from 0.52 to 0.81 for training and from 0.51 to 0.75 for forecasting. Moreover, the results are compared with that of a conceptual model, Snowmelt Runoff Model (SRM), application using SCA as an input. The importance and the main contribution of this study is to use of satellite snow products and data

  3. Estimating daily air temperature across the Southeastern United States using high-resolution satellite data: a statistical modeling study

    PubMed Central

    Shi, Liuhua; Liu, Pengfei; Kloog, Itai; Lee, Mihye; Kosheleva, Anna; Schwartz, Joel

    2015-01-01

    Accurate estimates of spatio-temporal resolved near-surface air temperature (Ta) are crucial for environmental epidemiological studies. However, values of Ta are conventionally obtained from weather stations, which have limited spatial coverage. Satellite surface temperature (Ts) measurements offer the possibility of local exposure estimates across large domains. The Southeastern United States has different climatic conditions, more small water bodies and wetlands, and greater humidity in contrast to other regions, which add to the challenge of modeling air temperature. In this study, we incorporated satellite Ts to estimate high resolution (1 km × 1 km) daily Ta across the southeastern USA for 2000-2014. We calibrated Ts to Ta measurements using mixed linear models, land use, and separate slopes for each day. A high out-of-sample cross-validated R2 of 0.952 indicated excellent model performance. When satellite Ts were unavailable, linear regression on nearby monitors and spatio-temporal smoothing was used to estimate Ta. The daily Ta estimations were compared to the NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) model. A good agreement with an R2 of 0.969 and a mean squared prediction error (RMSPE) of 1.376 °C was achieved. Our results demonstrate that Ta can be reliably predicted using this Ts-based prediction model, even in a large geographical area with topography and weather patterns varying considerably. PMID:26717080

  4. Estimating daily air temperature across the Southeastern United States using high-resolution satellite data: A statistical modeling study.

    PubMed

    Shi, Liuhua; Liu, Pengfei; Kloog, Itai; Lee, Mihye; Kosheleva, Anna; Schwartz, Joel

    2016-04-01

    Accurate estimates of spatio-temporal resolved near-surface air temperature (Ta) are crucial for environmental epidemiological studies. However, values of Ta are conventionally obtained from weather stations, which have limited spatial coverage. Satellite surface temperature (Ts) measurements offer the possibility of local exposure estimates across large domains. The Southeastern United States has different climatic conditions, more small water bodies and wetlands, and greater humidity in contrast to other regions, which add to the challenge of modeling air temperature. In this study, we incorporated satellite Ts to estimate high resolution (1km×1km) daily Ta across the southeastern USA for 2000-2014. We calibrated Ts-Ta measurements using mixed linear models, land use, and separate slopes for each day. A high out-of-sample cross-validated R(2) of 0.952 indicated excellent model performance. When satellite Ts were unavailable, linear regression on nearby monitors and spatio-temporal smoothing was used to estimate Ta. The daily Ta estimations were compared to the NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) model. A good agreement with an R(2) of 0.969 and a mean squared prediction error (RMSPE) of 1.376°C was achieved. Our results demonstrate that Ta can be reliably predicted using this Ts-based prediction model, even in a large geographical area with topography and weather patterns varying considerably.

  5. A Procedure for Inter-Comparing the Skill of Regional-Scale Air Quality Model Simulations of Daily Maximum 8-Hour Ozone Concentrations

    EPA Science Inventory

    An operational model evaluation procedure is described to quantitatively assess the relative skill among several regionalscale air quality models simulating various percentiles of the cumulative frequency distribution of observed daily maximum 8-h ozone concentrations. Bootstrap ...

  6. Comparing an annual and daily time-step model for predicting field-scale P loss

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Several models with varying degrees of complexity are available for describing P movement through the landscape. The complexity of these models is dependent on the amount of data required by the model, the number of model parameters needed to be estimated, the theoretical rigor of the governing equa...

  7. Process modeling of ICU patient flow: effect of daily load leveling of elective surgeries on ICU diversion.

    PubMed

    Kolker, Alexander

    2009-02-01

    Despite the considerable number of publications on ICU patient flow and analysis of its variability, a basic and practically important question remained unanswered: what maximum number of elective surgeries per day should be scheduled (along with the competing demand from emergency surgeries) in order to reduce diversion in an ICU with fixed bed capacity to an acceptable low level, or prevent it at all? The goal of this work was to develop a methodology to answer this question. An ICU patient flow simulation model was developed to establish a quantitative link between the daily load leveling of elective surgeries (elective schedule smoothing) and ICU diversion. It was demonstrated that by scheduling not more than four elective surgeries per day ICU diversion due to 'no ICU beds' would be practically eliminated. However this would require bumping 'extra' daily surgeries to the block time day of another week which could be up to 2 months apart. Because not all patients could wait that long for their elective surgery, another more practical scenario was tested that would also result in a very low ICU diversion: bumping 'extra' daily elective surgeries within less than 2 weeks apart, scheduling not more than five elective surgeries per day, and strict adherence to the ICU admission/ discharge criteria.

  8. Validating a model that predicts daily growth and feed quality of New Zealand dairy pastures.

    PubMed

    Woodward, S J

    2001-09-01

    The Pasture Quality (PQ) model is a simple, mechanistic, dynamical system model that was designed to capture the essential biological processes in grazed grass-clover pasture, and to be optimised to derive improved grazing strategies for New Zealand dairy farms. While the individual processes represented in the model (photosynthesis, tissue growth, flowering, leaf death, decomposition, worms) were based on experimental data, this did not guarantee that the assembled model would accurately predict the behaviour of the system as a whole (i.e., pasture growth and quality). Validation of the whole model was thus a priority, since any strategy derived from the model could impact a farm business in the order of thousands of dollars per annum if adopted. This paper describes the process of defining performance criteria for the model, obtaining suitable data to test the model, and carrying out the validation analysis. The validation process highlighted a number of weaknesses in the model, which will lead to the model being improved. As a result, the model's utility will be enhanced. Furthermore, validation was found to have an unexpected additional benefit, in that despite the model's poor initial performance, support was generated for the model among field scientists involved in the wider project.

  9. VT-1161 Dosed Once Daily or Once Weekly Exhibits Potent Efficacy in Treatment of Dermatophytosis in a Guinea Pig Model

    PubMed Central

    Hoekstra, W. J.; Moore, W. R.; Schotzinger, R. J.; Long, L.

    2015-01-01

    Current therapies used to treat dermatophytoses such as onychomycosis are effective but display room for improvement in efficacy, safety, and convenience of dosing. We report here that the investigational agent VT-1161 displays potent in vitro antifungal activity against dermatophytes, with MIC values in the range of ≤0.016 to 0.5 μg/ml. In pharmacokinetic studies supporting testing in a guinea pig model of dermatophytosis, VT-1161 plasma concentrations following single oral doses were dose proportional and persisted at or above the MIC values for at least 48 h, indicating potential in vivo efficacy with once-daily and possibly once-weekly dosing. Subsequently, in a guinea pig dermatophytosis model utilizing Trichophyton mentagrophytes and at oral doses of 5, 10, or 25 mg/kg of body weight once daily or 70 mg/kg once weekly, VT-1161 was statistically superior to untreated controls in fungal burden reduction (P < 0.001) and improvement in clinical scores (P < 0.001). The efficacy profile of VT-1161 was equivalent to those for doses and regimens of itraconazole and terbinafine except that VT-1161 was superior to itraconazole when each drug was dosed once weekly (P < 0.05). VT-1161 was distributed into skin and hair, with plasma and tissue concentrations in all treatment and regimen groups ranging from 0.8 to 40 μg/ml (or μg/g), at or above the MIC against the isolate used in the model (0.5 μg/ml). These data strongly support the clinical development of VT-1161 for the oral treatment of onychomycosis using either once-daily or once-weekly dosing regimens. PMID:25605358

  10. Effects of Model Resolution and Subgrid-Scale Physics on the Simulation of Daily Precipitation in the Continental United States

    SciTech Connect

    Duffy, P B; Iorio, J P; Govindasamy, B; Thompson, S L; Khairoutdinov, M; Randall, D

    2004-07-28

    We analyze simulations of the global climate performed at a range of spatial resolutions to assess the effects of horizontal spatial resolution on the ability to simulate precipitation in the continental United States. The model investigated is the CCM3 general circulation model. We also preliminarily assess the effect of replacing cloud and convective parameterizations in a coarse-resolution (T42) model with an embedded cloud-system resolving model (CSRM). We examine both spatial patterns of seasonal-mean precipitation and daily-timescale temporal variability of precipitation in the continental United States. For DJF and SON, high-resolution simulations produce spatial patterns of seasonal-mean precipitation that agree more closely with observed precipitation patterns than do results from the same model (CCM3) at coarse resolution. However, in JJA and MAM, there is little improvement in spatial patterns of seasonal-mean precipitation with increasing resolution, particularly in the Southeast. This is owed to the dominance of convective (i.e., parameterized) precipitation in these two seasons. We further find that higher-resolution simulations have more realistic daily precipitation statistics. In particular, the well-known tendency at coarse resolution to have too many days with weak precipitation and not enough intense precipitation is partially eliminated in higher-resolution simulations. However, even at the highest resolution examined here (T239), the simulated intensity of the mean and of high-percentile daily precipitation amounts is too low. This is especially true in the Southeast, where the most extreme events occur. A new GCM, in which a cloud-resolving model (CSRM) is embedded in each grid cell and replaces convective and stratiform cloud parameterizations, solves this problem, and actually produces too much precipitation in the form of extreme events. However, in contrast to high-resolution versions of CCM3, this model produces little improvement in

  11. Performance of five surface energy balance models for estimatng daily evapotranspiration in high biomass sorghum

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Robust evapotranspiration (ET) models are required to predict water usage in a variety of terrestrial ecosystems under different geographical and agrometeorological conditions. As a result, numerous remote sensing-based ET models have been developed to estimate large-scale ET based on the surface en...

  12. Preserving spatial linear correlations between neighboring stations in simulating daily precipitation using extended Markov models

    NASA Astrophysics Data System (ADS)

    Ababaei, Behnam; Sohrabi, Teymour; Mirzaei, Farhad

    2014-10-01

    Most stochastic weather generators have their focus on precipitation because it is the most important variable affecting environmental processes. One of the methods to reproduce the precipitation occurrence time series is to use a Markov process. But, in addition to the simulation of short-term autocorrelations in one station, it is sometimes important to preserve the spatial linear correlations (SLC) between neighboring stations as well. In this research, an extension of one-site Markov models was proposed to preserve the SLC between neighboring stations. Qazvin station was utilized as the reference station and Takestan (TK), Magsal, Nirougah, and Taleghan stations were used as the target stations. The performances of different models were assessed in relation to the simulation of dry and wet spells and short-term dependencies in precipitation time series. The results revealed that in TK station, a Markov model with a first-order spatial model could be selected as the best model, while in the other stations, a model with the order of two or three could be selected. The selected (i.e., best) models were assessed in relation to preserving the SLC between neighboring stations. The results depicted that these models were very capable in preserving the SLC between the reference station and any of the target stations. But, their performances were weaker when the SLC between the other stations were compared. In order to resolve this issue, spatially correlated random numbers were utilized instead of independent random numbers while generating synthetic time series using the Markov models. Although this method slightly reduced the model performances in relation to dry and wet spells and short-term dependencies, the improvements related to the simulation of the SLC between the other stations were substantial.

  13. Bayesian multinomial probit modeling of daily windows of susceptibility for maternal PM2.5 exposure and congenital heart defects.

    PubMed

    Warren, Joshua L; Stingone, Jeanette A; Herring, Amy H; Luben, Thomas J; Fuentes, Montserrat; Aylsworth, Arthur S; Langlois, Peter H; Botto, Lorenzo D; Correa, Adolfo; Olshan, Andrew F

    2016-07-20

    Epidemiologic studies suggest that maternal ambient air pollution exposure during critical periods of pregnancy is associated with adverse effects on fetal development. In this work, we introduce new methodology for identifying critical periods of development during post-conception gestational weeks 2-8 where elevated exposure to particulate matter less than 2.5 µm (PM2.5 ) adversely impacts development of the heart. Past studies have focused on highly aggregated temporal levels of exposure during the pregnancy and have failed to account for anatomical similarities between the considered congenital heart defects. We introduce a multinomial probit model in the Bayesian setting that allows for joint identification of susceptible daily periods during pregnancy for 12 types of congenital heart defects with respect to maternal PM2.5 exposure. We apply the model to a dataset of mothers from the National Birth Defect Prevention Study where daily PM2.5 exposures from post-conception gestational weeks 2-8 are assigned using predictions from the downscaler pollution model. This approach is compared with two aggregated exposure models that define exposure as the average value over post-conception gestational weeks 2-8 and the average over individual weeks, respectively. Results suggest an association between increased PM2.5 exposure on post-conception gestational day 53 with the development of pulmonary valve stenosis and exposures during days 50 and 51 with tetralogy of Fallot. Significant associations are masked when using the aggregated exposure models. Simulation study results suggest that the findings are robust to multiple sources of error. The general form of the model allows for different exposures and health outcomes to be considered in future applications. Copyright © 2016 John Wiley & Sons, Ltd.

  14. Revision and proposed modification for a total maximum daily load model for Upper Klamath Lake, Oregon

    USGS Publications Warehouse

    Wherry, Susan A.; Wood, Tamara M.; Anderson, Chauncey W.

    2015-01-01

    Using the extended 1991–2010 external phosphorus loading dataset, the lake TMDL model was recalibrated following the same procedures outlined in the Phase 1 review. The version of the model selected for further development incorporated an updated sediment initial condition, a numerical solution method for the chlorophyll a model, changes to light and phosphorus factors limiting algal growth, and a new pH-model regression, which removed Julian day dependence in order to avoid discontinuities in pH at year boundaries. This updated lake TMDL model was recalibrated using the extended dataset in order to compare calibration parameters to those obtained from a calibration with the original 7.5-year dataset. The resulting algal settling velocity calibrated from the extended dataset was more than twice the value calibrated with the original dataset, and, because the calibrated values of algal settling velocity and recycle rate are related (more rapid settling required more rapid recycling), the recycling rate also was larger than that determined with the original dataset. These changes in calibration parameters highlight the uncertainty in critical rates in the Upper Klamath Lake TMDL model and argue for their direct measurement in future data collection to increase confidence in the model predictions.

  15. Simulation of daily streamflows at gaged and ungaged locations within the Cedar River Basin, Iowa, using a Precipitation-Runoff Modeling System model

    USGS Publications Warehouse

    Christiansen, Daniel E.

    2012-01-01

    The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted a study to examine techniques for estimation of daily streamflows using hydrological models and statistical methods. This report focuses on the use of a hydrologic model, the U.S. Geological Survey's Precipitation-Runoff Modeling System, to estimate daily streamflows at gaged and ungaged locations. The Precipitation-Runoff Modeling System is a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The Cedar River Basin was selected to construct a Precipitation-Runoff Modeling System model that simulates the period from January 1, 2000, to December 31, 2010. The calibration period was from January 1, 2000, to December 31, 2004, and the validation periods were from January 1, 2005, to December 31, 2010 and January 1, 2000 to December 31, 2010. A Geographic Information System tool was used to delineate the Cedar River Basin and subbasins for the Precipitation-Runoff Modeling System model and to derive parameters based on the physical geographical features. Calibration of the Precipitation-Runoff Modeling System model was completed using a U.S. Geological Survey calibration software tool. The main objective of the calibration was to match the daily streamflow simulated by the Precipitation-Runoff Modeling System model with streamflow measured at U.S. Geological Survey streamflow gages. The Cedar River Basin daily streamflow model performed with a Nash-Sutcliffe efficiency ranged from 0.82 to 0.33 during the calibration period, and a Nash-Sutcliffe efficiency ranged from 0.77 to -0.04 during the validation period. The Cedar River Basin model is meeting the criteria of greater than 0.50 Nash-Sutcliffe and is a good fit for streamflow conditions for the calibration period at all but one location, Austin, Minnesota

  16. Reliability and Stability of VLBI-Derived Sub-Daily EOP Models

    NASA Technical Reports Server (NTRS)

    Artz, Thomas; Boeckmann, Sarah; Jensen, Laura; Nothnagel, Axel; Steigenberger, Peter

    2010-01-01

    Recent investigations have shown significant shortcomings in the model which is proposed by the IERS to account for the variations in the Earth s rotation with periods around one day and less. To overcome this, an empirical model can be estimated more or less directly from the observations of space geodetic techniques. The aim of this paper is to evaluate the quality and reliability of such a model based on VLBI observations. Therefore, the impact of the estimation method and the analysis options as well as the temporal stability are investigated. It turned out that, in order to provide a realistic accuracy measure of the model coefficients, the formal errors should be inflated by a factor of three. This coincides with the noise floor and the repeatability of the model coefficients and it captures almost all of the differences that are caused by different estimation techniques. The impact of analysis options is small but significant when changing troposphere parameterization or including harmonic station position variations.

  17. Modelling wet and dry spells for daily rainfall data series: an application to irrigation management in North-West Italy

    NASA Astrophysics Data System (ADS)

    Ferraris, Stefano; Agnese, Carmelo; Baiamonte, Giorgio; Cat Berro, Daniele; Mercalli, Luca

    2016-04-01

    Rainfall time variability is relevant for agricultural production. The daily time scale is often used in modelling crop and soil water balance. In this work a novel statistical analysis of wet and dry spells is presented, together with an application in an Italian area characterised by a relevant climate spatial variability, due to the presence of both high mountains (e.g.: Mont Blanc) and of the Mediterranean Sea. Statistical analysis of the sequences of rainy days, wet spells (WS), and that of no-rainy days, dry spells (DS), could be carried out separately (as widely applied in the past) or jointly, by introducing the inter-arrival time (IT), representing the time elapsed between two subsequent rainy days. Investigating on daily rainfall data series recorded in Sicily, Agnese et al. (2014) found that IT statistics can be described by the 3-parameter Lerch distribution; in turn, WS and DS distributions can be easily derived from IT distribution. Alternatively, the knowledge of both WS and DS distributions allow deriving IT distribution; in this case, WScan be described by the well-accepted geometric distribution, whereas the 2-parameter polylogarithm distribution can be used for DS, as recently suggested (Agnese et al., 2012) in place of the previously used 1-parameter logarithmic distribution (Chatfield, 1966). In this work, by using some daily rainfall data series recorded in Alpine and Sub-Alpine Areas, the equivalence between the above-mentioned approaches is showed. Furthermore, some interesting relationships between respective parameters are also illustrated. A simple soil water model is then used, using this rainfall statistical model, in order to evaluate the irrigation efficiency as a consequence of variations in the timing of surface irrigation, following the approach described in the paper of Canone et al. (2015). Agnese C., Baiamonte G., Cammalleri C., Cat Berro D., Ferraris S., Mercalli L. (2012). "Statistical analysis of inter-arrival times of

  18. Daily water and sediment discharges from selected rivers of the eastern United States; a time-series modeling approach

    USGS Publications Warehouse

    Fitzgerald, Michael G.; Karlinger, Michael R.

    1983-01-01

    Time-series models were constructed for analysis of daily runoff and sediment discharge data from selected rivers of the Eastern United States. Logarithmic transformation and first-order differencing of the data sets were necessary to produce second-order, stationary time series and remove seasonal trends. Cyclic models accounted for less than 42 percent of the variance in the water series and 31 percent in the sediment series. Analysis of the apparent oscillations of given frequencies occurring in the data indicates that frequently occurring storms can account for as much as 50 percent of the variation in sediment discharge. Components of the frequency analysis indicate that a linear representation is reasonable for the water-sediment system. Models that incorporate lagged water discharge as input prove superior to univariate techniques in modeling and prediction of sediment discharges. The random component of the models includes errors in measurement and model hypothesis and indicates no serial correlation. An index of sediment production within or between drain-gage basins can be calculated from model parameters.

  19. Estimation of genetic parameters for average daily gain using models with competition effects

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Components of variance for ADG with models including competition effects were estimated from data provided by Pig Improvement Company on 11,235 pigs from 4 selected lines of swine. Fifteen pigs with average age of 71 d were randomly assigned to a pen by line and sex and taken off test after approxi...

  20. Daily evapotranspiration estimates by scaling instantaneous latent heat flux derived from a two-source model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Radiometric brightness temperature can be used in energy balance models that estimate sensible and latent heat fluxes of the land surface. However, brightness temperature is usually available only at one time of day when acquired from aircraft, fine-scale satellite platforms, or infrared thermometer...

  1. Daily potential evapotranspiration and diurnal climate forcings: influence on the numerical modelling of soil water dynamics and evapotranspiration

    NASA Astrophysics Data System (ADS)

    Liu, Siqing; Graham, Wendy D.; Jacobs, Jennifer M.

    2005-07-01

    A physically based, variably saturated flow model was developed to predict soil water dynamics, evapotranspiration (ET) from the vadose zone, and recharge to (or exfiltration from) the saturated zone using mean daily atmospheric forcings and to identify the value of diurnal climate forcings on those predictions. The vadose zone flow is modelled using the Galerkin finite element technique to solve Richards' equation in one-dimension. The model was able to accurately predict measured soil moisture, water table elevation and actual ET at Paynes Prairie State Preserve in Florida. The forecast Nash-Sutcliffe efficiencies of actual ET, water table and average soil moisture content increased modestly, from 0.605-0.653, 0.888-0.916 to 0.902-0.913, respectively, when the average daily ET forcing was replaced with a diurnal evaporation cycle. Several additional numerical experiments were conducted to evaluate the influence of the evaporation cycle disaggregation approach on modelled ET and soil moisture content for different soil textures, vegetation surfaces, and water table depth. The results show that the enhanced predictive value of the diurnal ET cycle increases with decreasing vegetation, decreasing clay content, and increasing water table depth. Using numerical studies, actual evaporation is shown to be higher for daily average evaporation as compared to the diurnal cycle evaporation for specific ranges of shallow water table depth. For clay soils, this range occurs from approximately 40 to 300 cm below land surface for bare soils and from approximately 40 to well below 300 cm below land surface for vegetated soils. The range for sandy soils is approximately 80-200 cm below land surface for both bare and vegetated soils. Within this range, the maximum difference of the actual to potential evapotranspiration ratio for the clay soil, resulting from using different forcing methods, is 20 and 10% for bare soil and vegetated conditions, respectively. The forcing method

  2. Video Modeling for Teaching Daily Living Skills to Children with Autism Spectrum Disorder: A Pilot Study

    ERIC Educational Resources Information Center

    Meister, Christine; Salls, Joyce

    2015-01-01

    This pilot study investigated the efficacy of point-of-view video modeling as an intervention strategy to improve self-help skills in children with autism spectrum disorder (ASD). A single-subject A-B design was implemented with eight school-aged children ages 7.5 years to 13.5 years. Six of the students participated in general education classes…

  3. An operational model to estimate hourly and daily crop evapotranspiration in hilly terrain: validation on wheat and oat crops

    NASA Astrophysics Data System (ADS)

    Rana, Gianfranco; Katerji, Nader; Ferrara, Rossana M.; Martinelli, Nicola

    2011-03-01

    In this paper, we present an operational model to estimate the actual evapotranspiration (ET) of crops cultivated on hilly terrains. This new model has the following three characteristics: (1) ET modelling is based on a Penman-Monteith (PM) type equation (Monteith 1965) where canopy resistance is simulated by following an approach already illustrated by Katerji and Perrier (Agronomie 3(6):513-521, 1983); (2) the estimation of ET, by means of the PM equation, is made by using meteorological variables simulated on sloped sites as input; (3) these variables are simulated by using simple relationships linking the variables measured at a reference site on plane to the topographic characteristics of the site (slope, orientation, altitude as difference between reference, and sloped sites). This approach presents two advantages if compared with previously proposed models: Not only computation steps are greatly simplified but also error sources due to the simulation of climatic variables in sloped sites and the ET estimation are well distinguished. This model was validated at hourly and daily scales at four sites cultivated with wheat and oats offering a wide range of slope and orientation values: a reference site on plane, site 1 (9° sloping, NW orientation, 7 m from the reference site in plane), site 2 (6°, SE, 12 m) and site 3 (1°, SE, 18 m). At hourly scale, the new model performed well at all sites studied. The observed slope of the linear relationships between estimated and measured ET values ranged between 0.93 and 1.03, with coefficients of determination, r 2, between 0.80 and 0.98. At daily scale, the slopes of the linear relationships between measured and estimated ET for the sites on plane and the sloped sites were practically the same (0.98 ± 0.01); however, the coefficient of determination r 2 observed in the site on plane was clearly greater (0.98) than that observed in the sloped sites (0.83). The presented analysis does not show any significant

  4. Hierarchical Bayesian modeling of heterogeneous variances in average daily weight gain of commercial feedlot cattle.

    PubMed

    Cernicchiaro, N; Renter, D G; Xiang, S; White, B J; Bello, N M

    2013-06-01

    Variability in ADG of feedlot cattle can affect profits, thus making overall returns more unstable. Hence, knowledge of the factors that contribute to heterogeneity of variances in animal performance can help feedlot managers evaluate risks and minimize profit volatility when making managerial and economic decisions in commercial feedlots. The objectives of the present study were to evaluate heteroskedasticity, defined as heterogeneity of variances, in ADG of cohorts of commercial feedlot cattle, and to identify cattle demographic factors at feedlot arrival as potential sources of variance heterogeneity, accounting for cohort- and feedlot-level information in the data structure. An operational dataset compiled from 24,050 cohorts from 25 U. S. commercial feedlots in 2005 and 2006 was used for this study. Inference was based on a hierarchical Bayesian model implemented with Markov chain Monte Carlo, whereby cohorts were modeled at the residual level and feedlot-year clusters were modeled as random effects. Forward model selection based on deviance information criteria was used to screen potentially important explanatory variables for heteroskedasticity at cohort- and feedlot-year levels. The Bayesian modeling framework was preferred as it naturally accommodates the inherently hierarchical structure of feedlot data whereby cohorts are nested within feedlot-year clusters. Evidence for heterogeneity of variance components of ADG was substantial and primarily concentrated at the cohort level. Feedlot-year specific effects were, by far, the greatest contributors to ADG heteroskedasticity among cohorts, with an estimated ∼12-fold change in dispersion between most and least extreme feedlot-year clusters. In addition, identifiable demographic factors associated with greater heterogeneity of cohort-level variance included smaller cohort sizes, fewer days on feed, and greater arrival BW, as well as feedlot arrival during summer months. These results support that

  5. Simulation of daily streamflow for nine river basins in eastern Iowa using the Precipitation-Runoff Modeling System

    USGS Publications Warehouse

    Haj, Adel E.; Christiansen, Daniel E.; Hutchinson, Kasey J.

    2015-10-14

    The accuracy of Precipitation-Runoff Modeling System model streamflow estimates of nine river basins in eastern Iowa as compared to measured values at U.S. Geological Survey streamflow-gaging stations varied. The Precipitation-Runoff Modeling System models of nine river basins in eastern Iowa were satisfactory at estimating daily streamflow at 57 of the 79 calibration sites and 13 of the 14 validation sites based on statistical results. Unsatisfactory performance can be contributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) the availability and accuracy of meteorological input data. The Precipitation- Runoff Modeling System models of nine river basins in eastern Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.

  6. Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds

    USGS Publications Warehouse

    Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.

    2015-08-24

    Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.

  7. Integration of Satellite Estimates of Daily Inundation Extent into a Land Surface Ecosystem-Atmosphere Gas Exchange Model: Impacts on Methane Modeling

    NASA Astrophysics Data System (ADS)

    Galantowicz, J. F.; Wei, L. H.; Samanta, A.; Picton, J.; Zhang, B.; Lu, C.; Yang, J.; Tian, H.; Eluszkiewicz, J.; Nehrkorn, T.; Mountain, M.

    2013-12-01

    Soil moisture and the spatial extent of soil saturation, transient inundation, and wetland ecosystems are key determinants of greenhouse gas (GHG, e.g., methane) emissions from the land surface to the atmosphere. We are investigating how near-daily surface water and soil moisture observations such as those expected from NASA's planned Soil Moisture Active-Passive (SMAP) mission could be integrated into an ecosystem-atmosphere gas exchange model to improve its estimates of GHG fluxes. SMAP, to be launched in November 2014, will combine ~3-km resolution synthetic aperture radar (SAR), ~40-km-resolution L-band radiometry, and 3-day revisit period to make a novel dataset expected to provide inundation and soil moisture estimates superior to alternative methods at that temporal-spatial scale. We test the potential impact of this new data source using the Dynamic Land Surface Ecosystem Model (DLEM). DLEM quantifies regional fluxes of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) given atmospheric forcing data, with soil saturation as a prognostic variable. In this presentation, we discuss the results of integrating DLEM CH4 emission model products with time-varying subgrid inundation extent estimates from satellite remote sensing observations of North America. To emulate SMAP observations, we have derived a new daily inundation fraction dataset for 2008-2010 using data from NASA's Advanced Microwave Scanning Radiometer-EOS (AMSR-E). To test data-model integration, we created a testbed composed of two separate multi-year DLEM runs in which subgrid land cover conditions were artificially prescribed: one run with maximum wetlands coverage and one with no wetlands. We can combine CH4 products from the two runs using our daily inundation fraction estimates or other inundation representations such that the combination approximates CH4 flux results from a model with explicit inundation forcing. The testbed allows us to simulate a larger array of mixed-grid cases

  8. Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

    NASA Technical Reports Server (NTRS)

    Bell, Jordan R.; Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.

    2012-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the SPoRT-MODIS GVF dataset on a land surface model (LSM) apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. In the West, higher latent heat fluxes prevailed, which enhanced the rates of evapotranspiration and soil moisture depletion in the LSM. By late Summer and Autumn, both the average sensible and latent heat fluxes increased in the West as a result of the more rapid soil drying and higher coverage of GVF. The impacts of the SPoRT GVF dataset on NWP was also examined for a single severe weather case study using the Weather Research and Forecasting (WRF) model. Two separate coupled LIS/WRF model simulations were made for the 17 July 2010 severe weather event in the Upper Midwest using the NCEP and SPoRT GVFs, with all other model parameters remaining the same. Based on the sensitivity results, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and

  9. West African monsoon intraseasonal activity and its daily precipitation indices in regional climate models: diagnostics and challenges

    NASA Astrophysics Data System (ADS)

    Poan, E. D.; Gachon, P.; Dueymes, G.; Diaconescu, E.; Laprise, R.; Seidou Sanda, I.

    2016-11-01

    The West African monsoon intraseasonal variability has huge socio-economic impacts on local populations but understanding and predicting it still remains a challenge for the weather prediction and climate scientific community. This paper analyses an ensemble of simulations from six regional climate models (RCMs) taking part in the coordinated regional downscaling experiment, the ECMWF ERA-Interim reanalysis (ERAI) and three satellite-based and observationally-constrained daily precipitation datasets, to assess the performance of the RCMs with regard to the intraseasonal variability. A joint analysis of seasonal-mean precipitation and the total column water vapor (also called precipitable water— PW) suggests the existence of important links at different timescales between these two variables over the Sahel and highlights the relevance of using PW to follow the monsoon seasonal cycle. RCMs that fail to represent the seasonal-mean position and amplitude of the meridional gradient of PW show the largest discrepancies with respect to seasonal-mean observed precipitation. For both ERAI and RCMs, spectral decompositions of daily PW as well as rainfall show an overestimation of low-frequency activity (at timescales longer than 10 days) at the expense of the synoptic (timescales shorter than 10 days) activity. Consequently, the effects of the African Easterly Waves and the associated mesoscale convective systems are substantially underestimated, especially over continental regions. Finally, the study investigates the skill of the models with respect to hydro-climatic indices related to the occurrence, intensity and frequency of precipitation events at the intraseasonal scale. Although most of these indices are generally better reproduced with RCMs than reanalysis products, this study indicates that RCMs still need to be improved (especially with respect to their subgrid-scale parameterization schemes) to be able to reproduce the intraseasonal variance spectrum adequately.

  10. A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags

    PubMed Central

    Hocking, Daniel J.; O’Neil, Kyle; Whiteley, Andrew R.; Nislow, Keith H.; O’Donnell, Matthew J.

    2016-01-01

    Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade−1) and a widening of the synchronized period (29 d decade−1). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network. PMID:26966662

  11. A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags.

    PubMed

    Letcher, Benjamin H; Hocking, Daniel J; O'Neil, Kyle; Whiteley, Andrew R; Nislow, Keith H; O'Donnell, Matthew J

    2016-01-01

    Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade(-1)) and a widening of the synchronized period (29 d decade(-1)). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.

  12. Identification of the best architecture of a multilayer perceptron in modeling daily total ozone concentration over Kolkata, India

    NASA Astrophysics Data System (ADS)

    De, Syam; De, Barin; Chattopadhyay, Goutami; Paul, Suman; Haldar, Dilip; Chakrabarty, Dipak

    2011-04-01

    Autoregressive neural network (AR-NN) models of various orders have been generated in this work for the daily total ozone (TO) time series over Kolkata (22.56°N, 88.5°E). Artificial neural network in the form of multilayer perceptron (MLP) is implemented in order to generate the AR-NN models of orders varying from 1 to 13. An extensive variable selection method through multiple linear regression (MLR) is implemented while developing the AR-NNs. The MLPs are characterized by sigmoid non-linearity. The optimum size of the hidden layer is identified in each model and prediction are produced by validating it over the test cases using the coefficient of determination (R 2) and Willmott's index (WI). It is observed that AR-NN model of order 7 having 6 nodes in the hidden layer has maximum prediction capacity. It is further observed that any increase in the orders of AR-NN leads to less accurate prediction.

  13. A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags

    USGS Publications Warehouse

    Letcher, Benjamin; Hocking, Daniel; O'Neil, Kyle; Whiteley, Andrew R.; Nislow, Keith H.; O'Donnell, Matthew

    2016-01-01

    Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C), identified a clear warming trend (0.63 °C decade−1) and a widening of the synchronized period (29 d decade−1). We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data). Missing all data for a year decreased performance (∼0.6 °C jump in RMSE), but this decrease was moderated when data were available from other streams in the network.

  14. Changes in sub-daily precipitation extremes in a global climate model with super-parameterization under CO2 warming

    NASA Astrophysics Data System (ADS)

    Khairoutdinov, Marat; Zhou, Xin

    2015-04-01

    Virtually all of the projections for future change of extreme precipitation statistics under CO2 warming have been made using global climate models (GCMs) in which clouds and, in particular, convective cloud systems are not explicitly resolved, but rather parameterized. In our study, a different kind of a GCM, a super-parameterized Community Atmosphere Model (SP-CAM), is employed. In SP-CAM, all the conventional cloud parameterizations are replaced with a small-domain cloud resolving model (CRM), called super-parameterization (SP). The SP is embedded in each grid column of the host GCM. The resolution of each embedded CRM is 4 km, which is generally sufficient to explicitly represent deep convection, which is mostly responsible for extreme precipitation events. In this study, we use the SP-CAM to contrast to the present and to conventional climate model, CAM, the sub-daily extreme precipitation statistics in response to the sea-surface temperatures (SSTs) and CO2 levels as projected for the end of 21st century in response to the IPCC AR5 RCP8.5 emission scenario. Different mechanisms for extreme precipitation changes are discussed.

  15. Using a spatio-temporal dynamic state-space model with the EM algorithm to patch gaps in daily riverflow series

    NASA Astrophysics Data System (ADS)

    Amisigo, B. A.; van de Giesen, N. C.

    2005-09-01

    A spatio-temporal linear dynamic model has been developed for patching short gaps in daily river runoff series. The model was cast in a state-space form in which the state variable was estimated using the Kalman smoother (RTS smoother). The EM algorithm was used to concurrently estimate both parameter and missing runoff values. Application of the model to daily runoff series in the Volta Basin of West Africa showed that the model was capable of providing good estimates of missing runoff values at a gauging station from the remaining time series at the station and at spatially correlated stations in the same sub-basin.

  16. Validating the simulation of optical reflectance by a vertically resolved canopy biophysics model with MODIS daily observations

    NASA Astrophysics Data System (ADS)

    Drewry, D. T.; Duveiller, G.

    2012-12-01

    , hydrological and energetic (ie. biochemical, water stress, energy balance) states and fluxes and remotely sensed reflectances across the visible and near infrared bands observed by MODIS. Special care is made to ensure that the satellite observations match adequately, in both time and space, with the coupled model simulations. To do so, daily MODIS observations are used for which the exact time when they have been calculated is known by the satellite orbits. A previously-developed model of the spatial response of the sensor is also used to ensure that each footprint of every observation is within the target fields. This latter step is necessary for using daily MODIS data, as the observation footprint is often much larger than the 250 meter pixel it is encoded in, with further variation according to the orbit. This study focuses on the agro-ecosystem of the Central US, characterized by large-scale annual plantations of soybean and maize, for which MLCan has been rigorously validated.

  17. Comparison of Two Stochastic Daily Rainfall Models and their Ability to Preserve Multi-year Rainfall Variability

    NASA Astrophysics Data System (ADS)

    Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony; Parana Manage, Nadeeka

    2016-04-01

    Stochastic simulation of rainfall is often required in the simulation of streamflow and reservoir levels for water security assessment. As reservoir water levels generally vary on monthly to multi-year timescales, it is important that these rainfall series accurately simulate the multi-year variability. However, the underestimation of multi-year variability is a well-known issue in daily rainfall simulation. Focusing on this issue, we developed a hierarchical Markov Chain (MC) model in a traditional two-part MC-Gamma Distribution modelling structure, but with a new parameterization technique. We used two parameters of first-order MC process (transition probabilities of wet-to-wet and dry-to-dry days) to simulate the wet and dry days, and two parameters of Gamma distribution (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. We found that use of deterministic Gamma parameter values results in underestimation of multi-year variability of rainfall depths. Therefore, we calculated the Gamma parameters for each month of each year from the observed data. Then, for each month, we fitted a multi-variate normal distribution to the calculated Gamma parameter values. In the model, we stochastically sampled these two Gamma parameters from the multi-variate normal distribution for each month of each year and used them to generate rainfall depth in wet days using the Gamma distribution. In another study, Mehrotra and Sharma (2007) proposed a semi-parametric Markov model. They also used a first-order MC process for rainfall occurrence simulation. But, the MC parameters were modified by using an additional factor to incorporate the multi-year variability. Generally, the additional factor is analytically derived from the rainfall over a pre-specified past periods (e.g. last 30, 180, or 360 days). They used a non-parametric kernel density process to simulate the wet day rainfall depths. In this study, we have compared the performance of our

  18. Combining remote sensing and GIS climate modelling to estimate daily forest evapotranspiration in a Mediterranean mountain area

    NASA Astrophysics Data System (ADS)

    Cristóbal, J.; Poyatos, R.; Ninyerola, M.; Llorens, P.; Pons, X.

    2011-05-01

    Evapotranspiration monitoring allows us to assess the environmental stress on forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the main techniques used for calculating evapotranspiration at catchment and regional scales. In this study we present a methodology, based on the energy balance equation (B-method), that combines remote sensing imagery with GIS-based climate modelling to estimate daily evapotranspiration (ETd) for several dates between 2003 and 2005. The three main variables needed to compute ETd were obtained as follows: (i) Land surface temperature by means of the Landsat-5 TM and Landsat-7 ETM+ thermal band, (ii) air temperature by means of multiple regression analysis and spatial interpolation from meteorological ground stations data at satellite pass, and (iii) net radiation by means of the radiative balance. We calculated ETd using remote sensing data at different spatial and temporal scales (Landsat-7 ETM+, Landsat-5 TM and TERRA/AQUA MODIS, with a spatial resolution of 60, 120 and 1000 m, respectively) and combining three different approaches to calculate the B parameter, which represents an average bulk conductance for the daily-integrated sensible heat flux. We then compared these estimates with sap flow measurements from a Scots pine (Pinus sylvestris L.) stand in a Mediterranean mountain area. This procedure allowed us to better understand the limitations of ETd modelling and how it needs to be improved, especially in heterogeneous forest areas. The method using Landsat data resulted in a good agreement, R2 test of 0.89, with a mean RMSE value of about 0.6 mm day-1 and an estimation error of ±30 %. The poor agreement obtained using TERRA/AQUA MODIS, with a mean RMSE value of 1.8 and 2.4 mm day-1 and an estimation error of about ±57 and 50 %, respectively. This reveals that ETd retrieval from coarse resolution remote sensing data is troublesome in these heterogeneous areas, and

  19. Development of total maximum daily loads for bacteria impaired watershed using the comprehensive hydrology and water quality simulation model.

    PubMed

    Kim, Sang M; Brannan, Kevin M; Zeckoski, Rebecca W; Benham, Brian L

    2014-01-01

    The objective of this study was to develop bacteria total maximum daily loads (TMDLs) for the Hardware River watershed in the Commonwealth of Virginia, USA. The TMDL program is an integrated watershed management approach required by the Clean Water Act. The TMDLs were developed to meet Virginia's water quality standard for bacteria at the time, which stated that the calendar-month geometric mean concentration of Escherichia coli should not exceed 126 cfu/100 mL, and that no single sample should exceed a concentration of 235 cfu/100 mL. The bacteria impairment TMDLs were developed using the Hydrological Simulation Program-FORTRAN (HSPF). The hydrology and water quality components of HSPF were calibrated and validated using data from the Hardware River watershed to ensure that the model adequately simulated runoff and bacteria concentrations. The calibrated and validated HSPF model was used to estimate the contributions from the various bacteria sources in the Hardware River watershed to the in-stream concentration. Bacteria loads were estimated through an extensive source characterization process. Simulation results for existing conditions indicated that the majority of the bacteria came from livestock and wildlife direct deposits and pervious lands. Different source reduction scenarios were evaluated to identify scenarios that meet both the geometric mean and single sample maximum E. coli criteria with zero violations. The resulting scenarios required extreme and impractical reductions from livestock and wildlife sources. Results from studies similar to this across Virginia partially contributed to a reconsideration of the standard's applicability to TMDL development.

  20. A Conceptual Model for Teaching the Relationship of Daily Life and Human Environmental Impact to Ecological Function

    ERIC Educational Resources Information Center

    Wyner, Yael

    2013-01-01

    In the general activity of daily life, it is easy to miss our dependency on the Earth's ecology. At the same time that people are living apparently separate from the environment, our impact on the Earth is increasing. This study seeks to understand how teachers can bridge this persistent disconnect of daily life from ecology and human impact.…

  1. The Role of Competence and Value Beliefs in Students' Daily Emotional Experiences: A Multilevel Test of a Transactional Model

    ERIC Educational Resources Information Center

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

    2010-01-01

    This study examined the mutual influence of relatively stable personal competence and value beliefs and lesson specific appraisals of competence and value on daily emotional experiences of students in the classroom context. Personal competence and value beliefs were measured by means of questionnaire whereas appraisals and daily emotions were…

  2. Evaluation of five lactation curve models fitted for fat:protein ratio of milk and daily energy balance.

    PubMed

    Buttchereit, N; Stamer, E; Junge, W; Thaller, G

    2010-04-01

    Selection for milk yield increases the metabolic load of dairy cows. The fat:protein ratio of milk (FPR) could serve as a measure of the energy balance status and might be used as a selection criterion to improve metabolic stability. The fit of different fixed and random regression models describing FPR and daily energy balance was tested to establish appropriate models for further genetic analyses. In addition, the relationship between both traits was evaluated for the best fitting model. Data were collected on a dairy research farm running a bull dam performance test. Energy balance was calculated using information on milk yield, feed intake per day, and live weight. Weekly FPR measurements were available. Three data sets were created containing records of 577 primiparous cows with observations from lactation d 11 to 180 as well as records of 613 primiparous cows and 96 multiparous cows with observations from lactation d 11 to 305. Five well-established parametric functions of days in milk (Ali and Schaeffer, Guo and Swalve, Wilmink, Legendre polynomials of third and fourth degree) were chosen for modeling the lactation curves. Evaluation of goodness of fit was based on the corrected Akaike information criterion, the Bayesian information criterion, correlation between the real observation and the estimated value, and on inspection of the residuals plotted against days in milk. The best model was chosen for estimation of correlations between both traits at different lactation stages. Random regression models were superior compared with the fixed regression models. In general, the Ali and Schaeffer function appeared most suitable for modeling both the fixed and the random regression part of the mixed model. The FPR is greatest in the initial lactation period when energy deficit is most pronounced. Energy balance stabilizes at the same point as the decrease in FPR stops. The inverted patterns indicate a causal relationship between the 2 traits. A common pattern was

  3. Modelling a model?!! Prediction of observed and calculated daily pan evaporation in New Mexico, U.S.A.

    NASA Astrophysics Data System (ADS)

    Beriro, D. J.; Abrahart, R. J.; Nathanail, C. P.

    2012-04-01

    Data-driven modelling is most commonly used to develop predictive models that will simulate natural processes. This paper, in contrast, uses Gene Expression Programming (GEP) to construct two alternative models of different pan evaporation estimations by means of symbolic regression: a simulator, a model of a real-world process developed on observed records, and an emulator, an imitator of some other model developed on predicted outputs calculated by that source model. The solutions are compared and contrasted for the purposes of determining whether any substantial differences exist between either option. This analysis will address recent arguments over the impact of using downloaded hydrological modelling datasets originating from different initial sources i.e. observed or calculated. These differences can be easily be overlooked by modellers, resulting in a model of a model developed on estimations derived from deterministic empirical equations and producing exceptionally high goodness-of-fit. This paper uses different lines-of-evidence to evaluate model output and in so doing paves the way for a new protocol in machine learning applications. Transparent modelling tools such as symbolic regression offer huge potential for explaining stochastic processes, however, the basic tenets of data quality and recourse to first principles with regard to problem understanding should not be trivialised. GEP is found to be an effective tool for the prediction of observed and calculated pan evaporation, with results supported by an understanding of the records, and of the natural processes concerned, evaluated using one-at-a-time response function sensitivity analysis. The results show that both architectures and response functions are very similar, implying that previously observed differences in goodness-of-fit can be explained by whether models are applied to observed or calculated data.

  4. Daily and compulsive internet use and well-being in adolescence: a diathesis-stress model based on big five personality traits.

    PubMed

    van der Aa, Niels; Overbeek, Geertjan; Engels, Rutger C M E; Scholte, Ron H J; Meerkerk, Gert-Jan; Van den Eijnden, Regina J J M

    2009-07-01

    This study examined the associations between adolescents' daily Internet use and low well-being (i.e., loneliness, low self-esteem, and depressive moods). We hypothesized that (a) linkages between high levels of daily Internet use and low well-being would be mediated by compulsive Internet use (CIU), and (b) that adolescents with low levels of agreeableness and emotional stability, and high levels of introversion would be more likely to develop CIU and lower well-being. Data were used from a sample of 7888 Dutch adolescents (11-21 years). Results from structural equation modeling analyses showed that daily Internet use was indirectly related to low well-being through CIU. In addition, daily Internet use was found to be more strongly related to CIU in introverted, low-agreeable, and emotionally less-stable adolescents. In turn, again, CIU was more strongly linked to loneliness in introverted, emotionally less-stable, and less agreeable adolescents.

  5. Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model

    NASA Astrophysics Data System (ADS)

    Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.; Branson, Mark D.; Randall, David A.

    2016-03-01

    This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super-Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual-mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double-ITCZ bias. However, unfolding intensity distributions reveal several improvements in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden-Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM's low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved-scale processes in CAM, few differences discriminate the rainfall properties of the two models. These results are discussed in light of their implication for future rainfall changes in response to climate forcing.

  6. From daily to sub-daily time steps - Creating a high temporal and spatial resolution climate reference data set for hydrological modeling and bias-correction of RCM data

    NASA Astrophysics Data System (ADS)

    Willkofer, Florian; Wood, Raul R.; Schmid, Josef; von Trentini, Fabian; Ludwig, Ralf

    2016-04-01

    The ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) focuses on the effects of climate change on hydro-meteorological extreme events and their implications for water management in Bavaria and Québec. It builds on the conjoint analysis of a large ensemble of the CRCM5, driven by 50 members of the CanESM2, and the latest information provided through the CORDEX-initiative, to better assess the influence of natural climate variability and climatic change on the dynamics of extreme events. A critical point in the entire project is the preparation of a meteorological reference dataset with the required temporal (1-6h) and spatial (500m) resolution to be able to better evaluate hydrological extreme events in mesoscale river basins. For Bavaria a first reference data set (daily, 1km) used for bias-correction of RCM data was created by combining raster based data (E-OBS [1], HYRAS [2], MARS [3]) and interpolated station data using the meteorological interpolation schemes of the hydrological model WaSiM [4]. Apart from the coarse temporal and spatial resolution, this mosaic of different data sources is considered rather inconsistent and hence, not applicable for modeling of hydrological extreme events. Thus, the objective is to create a dataset with hourly data of temperature, precipitation, radiation, relative humidity and wind speed, which is then used for bias-correction of the RCM data being used as driver for hydrological modeling in the river basins. Therefore, daily data is disaggregated to hourly time steps using the 'Method of fragments' approach [5], based on available training stations. The disaggregation chooses fragments of daily values from observed hourly datasets, based on similarities in magnitude and behavior of previous and subsequent events. The choice of a certain reference station (hourly data, provision of fragments) for disaggregating daily station data (application

  7. Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

    NASA Technical Reports Server (NTRS)

    Bell, Jordan R.; Case, Jonathan L.; Molthan, Andrew L.

    2011-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center develops new products and techniques that can be used in operational meteorology. The majority of these products are derived from NASA polar-orbiting satellite imagery from the Earth Observing System (EOS) platforms. One such product is a Greenness Vegetation Fraction (GVF) dataset, which is produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the new SPoRT-MODIS GVF dataset on land surface models apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. The second phase of the project is to examine the impacts of the SPoRT GVF dataset on NWP using the Weather Research and Forecasting (WRF) model. Two separate WRF model simulations were made for individual severe weather case days using the NCEP GVF (control) and SPoRT GVF (experimental), with all other model parameters remaining the same. Based on the sensitivity results in these case studies, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). The opposite was true

  8. Daily intake of Jeju groundwater improves the skin condition of the model mouse for human atopic dermatitis.

    PubMed

    Tanaka, Akane; Jung, Kyungsook; Matsuda, Akira; Jang, Hyosun; Kajiwara, Naoki; Amagai, Yosuke; Oida, Kumiko; Ahn, Ginnae; Ohmori, Keitaro; Kang, Kyung-goo; Matsuda, Hiroshi

    2013-03-01

    Drinking water is an important nutrient for human health. The mineral ingredients included in drinking water may affect the physical condition of people. Various kinds of natural water are in circulation as bottled water in developed countries; however, its influence on clinical conditions of patients with certain diseases has not been fully evaluated. In this study, effects of the natural groundwater from Jeju Island on clinical symptoms and skin barrier function in atopic dermatitis (AD) were evaluated. NC/Tnd mice, a model for human AD, with moderate to severe dermatitis were used. Mice were given different natural groundwater or tap water for 8 weeks from 4 weeks of age. Clinical skin severity scores were recorded every week. Scratching analysis and measurement of transepidermal water loss were performed every other week. The pathological condition of the dorsal skin was evaluated histologically. Real-time polymerase chain reaction analysis was performed for cytokine expression in the affected skin. The epidermal hyperplasia and allergic inflammation were reduced in atopic mice supplied with Jeju groundwater when compared to those supplied with tap water or other kinds of natural groundwater. The increase in scratching behavior with the aggravation of clinical severity of dermatitis was favorably controlled. Moreover, transepidermal water loss that reflects skin barrier function was recovered. The early inflammation and hypersensitivity in the atopic skin was alleviated in mice supplied with Jeju groundwater, suggesting its profitable potential on the daily care of patients with skin troubles including AD.

  9. A Hybrid Framework to Bias Correct and Empirically Downscale Daily Temperature and Precipitation from Regional Climate Models

    NASA Astrophysics Data System (ADS)

    Tan, P.; Abraham, Z.; Winkler, J. A.; Perdinan, P.; Zhong, S. S.; Liszewska, M.

    2013-12-01

    Bias correction and statistical downscaling are widely used approaches for postprocessing climate simulations generated by global and/or regional climate models. The skills of these approaches are typically assessed in terms of their ability to reproduce historical climate conditions as well as the plausibility and consistency of the derived statistical indicators needed by end users. Current bias correction and downscaling approaches often do not adequately satisfy the two criteria of accurate prediction and unbiased estimation. To overcome this limitation, a hybrid regression framework was developed to both minimize prediction errors and preserve the distributional characteristics of climate observations. Specifically, the framework couples the loss functions of standard (linear or nonlinear) regression methods with a regularization term that penalizes for discrepancies between the predicted and observed distributions. The proposed framework can also be extended to generate physically-consistent outputs across multiple response variables, and to incorporate both reanalysis-driven and GCM-driven RCM outputs into a unified learning framework. The effectiveness of the framework is demonstrated using daily temperature and precipitation simulations from the North American Regional Climate Change Program (NARCCAP) . The accuracy of the framework is comparable to standard regression methods, but, unlike the standard regression methods, the proposed framework is able to preserve many of the distribution properties of the response variables, akin to bias correction approaches such as quantile mapping and bivariate geometric quantile mapping.

  10. Long-term outcome and prediction models of activities of daily living in Alzheimer disease with cholinesterase inhibitor treatment.

    PubMed

    Wattmo, Carina; Wallin, Åsa K; Londos, Elisabet; Minthon, Lennart

    2011-01-01

    In untreated patients with Alzheimer disease (AD) the functional ability is gradually lost. What happens to the patients after continuous long-term cholinesterase inhibitor (ChEI) treatment is less investigated. The objective of this study was to describe the longitudinal functional outcome and analyze factors affecting the outcome in ChEI-treated patients. In an open, 3-year, nonrandomized, prospective, multicenter study in a routine clinical setting, 790 patients were treated with either donepezil, rivastigmine, or galantamine. At baseline and every 6 months, they were assessed with several rating scales including Instrumental Activities of Daily Living (IADL), Physical Self-Maintenance Scale (PSMS), and Mini-Mental State Examination (MMSE). A faster functional decline was associated with lower cognitive ability at baseline, older age, and the interaction of higher education and longer time in the study. The patients residing with a spouse or relative showed slower deterioration in IADL score. A higher mean dose of ChEI, regardless of drug agent, was also related to slower instrumental ADL decline. Prediction models for longitudinal functional outcome were provided. AD severity at baseline is a key factor in obtaining reliable clinical prognoses of the long-term ADL ability. The dosage of ChEI treatment could possibly lead to a different functional outcome.

  11. Using spatially detailed water-quality data and solute-transport modeling to improve support total maximum daily load development

    USGS Publications Warehouse

    Walton-Day, Katherine; Runkel, Robert L.; Kimball, Briant A.

    2012-01-01

    Spatially detailed mass-loading studies and solute-transport modeling using OTIS (One-dimensional Transport with Inflow and Storage) demonstrate how natural attenuation and loading from distinct and diffuse sources control stream water quality and affect load reductions predicted in total maximum daily loads (TMDLs). Mass-loading data collected during low-flow from Cement Creek (a low-pH, metal-rich stream because of natural and mining sources, and subject to TMDL requirements) were used to calibrate OTIS and showed spatially variable effects of natural attenuation (instream reactions) and loading from diffuse (groundwater) and distinct sources. OTIS simulations of the possible effects of TMDL-recommended remediation of mine sites showed less improvement to dissolved zinc load and concentration (14% decrease) than did the TMDL (53-63% decrease). The TMDL (1) assumed conservative transport, (2) accounted for loads removed by remediation by subtracting them from total load at the stream mouth, and (3) did not include diffuse-source loads. In OTIS, loads were reduced near their source; the resulting concentration was decreased by natural attenuation and increased by diffuse-source loads during downstream transport. Thus, by not including natural attenuation and loading from diffuse sources, the TMDL overestimated remediation effects at low flow. Use of the techniques presented herein could improve TMDLs by incorporating these processes during TMDL development.

  12. Spatio-temporal models to estimate daily concentrations of fine particulate matter in Montreal: Kriging with external drift and inverse distance-weighted approaches.

    PubMed

    Ramos, Yuddy; St-Onge, Benoît; Blanchet, Jean-Pierre; Smargiassi, Audrey

    2016-06-01

    Air pollution is a major environmental and health problem, especially in urban agglomerations. Estimating personal exposure to fine particulate matter (PM2.5) remains a great challenge because it requires numerous point measurements to explain the daily spatial variation in pollutant levels. Furthermore, meteorological variables have considerable effects on the dispersion and distribution of pollutants, which also depends on spatio-temporal emission patterns. In this study we developed a hybrid interpolation technique that combined the inverse distance-weighted (IDW) method with Kriging with external drift (KED), and applied it to daily PM2.5 levels observed at 10 monitoring stations. This provided us with downscaled high-resolution maps of PM2.5 for the Island of Montreal. For the KED interpolation, we used spatio-temporal daily meteorological estimates and spatial covariates as land use and vegetation density. Different KED and IDW daily estimation models for the year 2010 were developed for each of the six synoptic weather classes. These clusters were developed using principal component analysis and unsupervised hierarchical classification. The results of the interpolation models were assessed with a leave-one-station-out cross-validation. The performance of the hybrid model was better than that of the KED or the IDW alone for all six synoptic weather classes (the daily estimate for R(2) was 0.66-0.93 and for root mean square error (RMSE) 2.54-1.89 μg/m(3)).

  13. Daily exposure to summer circadian cycles affects spermatogenesis, but not fertility in an in vivo rabbit model.

    PubMed

    Sabés-Alsina, Maria; Planell, Núria; Torres-Mejia, Elen; Taberner, Ester; Maya-Soriano, Maria José; Tusell, Llibertat; Ramon, Josep; Dalmau, Antoni; Piles, Miriam; Lopez-Bejar, Manel

    2015-01-15

    Heat stress (HS) in mammals is a determining factor in the deterioration of spermatogenesis and can cause infertility. The aim of this study was to evaluate the effect of continuous summer circadian cycles on semen production, sperm cell features, fertility, prolificacy, and fecal cortisol metabolites from rabbits kept under an in vivo HS model. We split randomly 60 New Zealand White rabbits into two temperature-controlled rooms: The control group was maintained at comfort temperature (18 °C-22 °C) and an HS group, where the environmental temperature was programmed to increase from 22 °C to 31 °C and be maintained for 3 hours to this temperature at the central part of the day. Fecal cortisol metabolites were assessed to evaluate the stress conditions. Seminal parameters were analyzed. Although animals exposed to HS showed higher values of fecal cortisol metabolites (P = 0.0003), no differences were detected in fertility or prolificacy. Semen samples from HS males showed a significant decrease (P < 0.05) with respect to the controls in the percentage of viable spermatozoa (80.71% vs. 74.21%), and a significant (P ≤ 0.01) increase in the percentage of acrosomic abnormalities (22.57% vs. 36.96%) and tailless spermatozoa (7.91% vs. 12.83). Among motility parameters, no differences were found. This study describes a model of HS simulating a continuous summer daily cycle that allows periods of time to recover as it occurs under natural conditions. Although negative effects have been detected in several sperm parameters, fertility and prolificacy were not affected, suggesting a recovery of the reproductive function when normal conditions are reestablished.

  14. Combining remote sensing and GIS climate modelling to estimate daily forest evapotranspiration in a Mediterranean mountain area

    NASA Astrophysics Data System (ADS)

    Cristóbal, J.; Poyatos, R.; Ninyerola, M.; Llorens, P.; Pons, X.

    2011-01-01

    Evapotranspiration monitoring allows us to assess the environmental stress on forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the main techniques used for calculating evapotranspiration at catchment and regional scales. In this study we present a methodology, based on the energy balance equation (B-method), that combines remote sensing imagery with GIS climate modelling to estimate daily evapotranspiration (ETd) for several dates between 2003 and 2005. The three main variables needed to compute ETd were obtained as follows: (i) Land surface temperature by means of the Landsat-5 TM and Landsat-7 ETM+ thermal band, (ii) air temperature by means of multiple regression analysis and spatial interpolation from meteorological ground stations data at satellite pass, and (iii) net radiation by means of the radiative balance. We calculated ETd using remote sensing data at different spatial and temporal scales (TERRA/AQUA MODIS and Landsat-5 TM/Landsat-7 ETM+) and combining three different approaches to calculate the B parameter. We then compared these estimates with sap flow measurements from a Scots pine (Pinus sylvestris L.) stand in a Mediterranean mountain area. This procedure allowed us to better understand the limitations of ETd modelling and how it needs to be improved, especially in heterogeneous forest areas. The method using Landsat data resulted in a good agreement, with a mean RMSE value of about 0.6 mm day-1 and an estimation error of ±30%. The poor agreement obtained using MODIS data reveals that ETd retrieval from coarse resolution remote sensing data is troublesome in these heterogeneous areas, and therefore further research is necessary on this issue.

  15. Future daily PM10 concentrations prediction by combining regression models and feedforward backpropagation models with principle component analysis (PCA)

    NASA Astrophysics Data System (ADS)

    Ul-Saufie, Ahmad Zia; Yahaya, Ahmad Shukri; Ramli, Nor Azam; Rosaida, Norrimi; Hamid, Hazrul Abdul

    2013-10-01

    Future PM10 concentration prediction is very important because it can help local authorities to enact preventative measures to reduce the impact of air pollution. The aims of this study are to improve prediction of Multiple Linear Regression (MLR) and Feedforward backpropagation (FFBP) by combining them with principle component analysis for predicting future (next day, next two-day and next three-day) PM10 concentration in Negeri Sembilan, Malaysia. Annual hourly observations for PM10 in Negeri Sembilan, Malaysia from January 2003 to December 2010 were selected for predicting PM10 concentration level. Eighty percent of the monitoring records were used for training and twenty percent were used for validation of the models. Three accuracy measures - Prediction Accuracy (PA), Coefficient of Determination (R2) and Index of Agreement (IA), as well as two error measures - Normalized Absolute Error (NAE) and Root Mean Square Error (RMSE) were used to evaluate the performance of the models. Results show that PCA models combined with MLR and PCA with FFBP improved MLR and FFBP models for all three days in advance of predicting PM10 concentration, with reduced errors by as much as 18.1% (PCA-MLR) and 17.68% (PCA-FFBP) for next day, 19.2% (PCA-MLR) and 22.1% (PCA-FFBP) for next two-day and 18.7% (PCA-MLR) and 22.79% (PCA-FFBP) for next three-day predictions. Including PCA improved the accuracy of the models by as much as by 12.9% (PCA-MLR) and 13.3% (PCA-FFBP) for next day, 32.3% (PCA-MLR) and 14.7% (PCA-FFBP) for next two-day and 46.1% (PCA-MLR) and 19.3% (PCA-FFBP) for next three-day predictions.

  16. Review of revised Klamath River Total Maximum Daily Load models from Link River Dam to Keno Dam, Oregon

    USGS Publications Warehouse

    Rounds, Stewart A.; Sullivan, Annett B.

    2013-01-01

    Flow and water-quality models are being used to support the development of Total Maximum Daily Load (TMDL) plans for the Klamath River downstream of Upper Klamath Lake (UKL) in south-central Oregon. For riverine reaches, the RMA-2 and RMA-11 models were used, whereas the CE-QUAL-W2 model was used to simulate pooled reaches. The U.S. Geological Survey (USGS) was asked to review the most upstream of these models, from Link River Dam at the outlet of UKL downstream through the first pooled reach of the Klamath River from Lake Ewauna to Keno Dam. Previous versions of these models were reviewed in 2009 by USGS. Since that time, important revisions were made to correct several problems and address other issues. This review documents an assessment of the revised models, with emphasis on the model revisions and any remaining issues. The primary focus of this review is the 19.7-mile Lake Ewauna to Keno Dam reach of the Klamath River that was simulated with the CE-QUAL-W2 model. Water spends far more time in the Lake Ewauna to Keno Dam reach than in the 1-mile Link River reach that connects UKL to the Klamath River, and most of the critical reactions affecting water quality upstream of Keno Dam occur in that pooled reach. This model review includes assessments of years 2000 and 2002 current conditions scenarios, which were used to calibrate the model, as well as a natural conditions scenario that was used as the reference condition for the TMDL and was based on the 2000 flow conditions. The natural conditions scenario included the removal of Keno Dam, restoration of the Keno reef (a shallow spot that was removed when the dam was built), removal of all point-source inputs, and derivation of upstream boundary water-quality inputs from a previously developed UKL TMDL model. This review examined the details of the models, including model algorithms, parameter values, and boundary conditions; the review did not assess the draft Klamath River TMDL or the TMDL allocations

  17. Toward the Development of an Inventory of Daily Widowed Life (IDWL): Guided by the Dual Process Model of Coping with Bereavement

    ERIC Educational Resources Information Center

    Caserta, Michael S.; Lund, Dale A.

    2007-01-01

    "The Dual Process Model of Coping with Bereavement" (M. Stroebe & H. Schut, 1999) suggests that the most effective adaptation involves oscillation between 2 coping processes: loss-orientation (LO) and restoration-orientation (RO). A 22-item Inventory of Daily Widowed Life (IDWL) was developed to measure these processes and the…

  18. Use of Video Modeling and Video Prompting Interventions for Teaching Daily Living Skills to Individuals with Autism Spectrum Disorders: A Review

    ERIC Educational Resources Information Center

    Gardner, Stephanie; Wolfe, Pamela

    2013-01-01

    Identifying methods to increase the independent functioning of individuals with autism spectrum disorders (ASD) is vital in enhancing their quality of life; teaching students with ASD daily living skills can foster independent functioning. This review examines interventions that implement video modeling and/or prompting to teach individuals with…

  19. Using a Hero as a Model in Video Instruction to Improve the Daily Living Skills of an Elementary-Aged Student with Autism Spectrum Disorder: A Pilot Study

    ERIC Educational Resources Information Center

    Ohtake, Yoshihisa

    2015-01-01

    The present pilot study investigated the impact of video hero modelling (VHM) on the daily living skills of an elementary-aged student with autism spectrum disorder. The VHM, in which a character much admired by the student exhibited a correct response, was shown to the participant immediately before the situation where he needed to exhibit the…

  20. Estimation of daily global solar radiation using wavelet regression, ANN, GEP and empirical models: A comparative study of selected temperature-based approaches

    NASA Astrophysics Data System (ADS)

    Sharifi, Sayed Saber; Rezaverdinejad, Vahid; Nourani, Vahid

    2016-11-01

    Although the sunshine-based models generally have a better performance than temperature-based models for estimating solar radiation, the limited availability of sunshine duration records makes the development of temperature-based methods inevitable. This paper presents a comparative study between Artificial Neural Networks (ANNs), Gene Expression Programming (GEP), Wavelet Regression (WR) and 5 selected temperature-based empirical models for estimating the daily global solar radiation. A new combination of inputs including four readily accessible parameters have been employed: daily mean clearness index (KT), temperature range (ΔT), theoretical sunshine duration (N) and extraterrestrial radiation (Ra). Ten statistical indicators in a form of GPI (Global Performance Indicator) is used to ascertain the suitability of the models. The performance of selected models across the range of solar radiation values, was depicted by the quantile-quantile (Q-Q) plots. Comparing these plots makes it evident that ANNs can cover a broader range of solar radiation values. The results shown indicate that the performance of ANN model was clearly superior to the other models. The findings also demonstrated that WR model performed well and presented high accuracy in estimations of daily global solar radiation.

  1. Estimation of Daily Reference Evapotranspiration using Temperature Based Models and Remotely Sensed Data over Indian River Basin

    NASA Astrophysics Data System (ADS)

    R, Shwetha H.; D, Nagesh Kumar

    2015-04-01

    Reference evapotranspiration (ETo) is the most significant component of the hydrological budget. Accurate quantification of ETo is vital for proper water management, efficient agricultural activities, irrigation planning and irrigation scheduling. FAO Penman Montieth (FAO-PM) is the widely accepted and used method for the ETo estimation under all climatic conditions, but needs numerous inputs which are difficult to acquire in developing countries. In such conditions, temperature based models such as Hargreaves-Samani (HS) equation and Penman Montieth temperature (PMT) can be used, where only maximum and minimum temperatures are required. Spatial interpolation of meteorological parameters to calculate spatial variation of ETo results in inaccurate estimations at lowly densed weather stations. Hence, there is a necessity of simple and easy method to estimate spatial distribution of ETo. In this regard, remotely sensed data provides viable alternative approach to obtain continuous spatio-temporal ETo. In this study, we used temperature based ETo models with remotely sensed LST data to estimate spatio-temporal variation of ETo. Day and night LST (MYD11A1) data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS sensor of Aqua satellite. Firstly, day and night land surface temperatures (LST) with HS and PMT methods were applied to estimate ETo. Secondly, maximum and minimum air temperatures were estimated from day and night LST respectively using simple linear regression and these air temperature data were used to estimate ETo. Estimated results were validated with the ETo calculated using meteorological data obtained from Automatic Weather Stations (AWS) by applying standard FAO-PM. The preliminary results revealed that, HS method with LST overestimated ETo in the study region. Statistical analysis showed PMT method with both LST and air temperatures performed better than the HS method. These two temperature based methods are often used for

  2. The challenge of modelling nitrogen management at the field scale: simulation and sensitivity analysis of N2O fluxes across nine experimental sites using DailyDayCent

    NASA Astrophysics Data System (ADS)

    Fitton, N.; Datta, A.; Hastings, A.; Kuhnert, M.; Topp, C. F. E.; Cloy, J. M.; Rees, R. M.; Cardenas, L. M.; Williams, J. R.; Smith, K.; Chadwick, D.; Smith, P.

    2014-09-01

    The United Kingdom currently reports nitrous oxide emissions from agriculture using the IPCC default Tier 1 methodology. However Tier 1 estimates have a large degree of uncertainty as they do not account for spatial variations in emissions. Therefore biogeochemical models such as DailyDayCent (DDC) are increasingly being used to provide a spatially disaggregated assessment of annual emissions. Prior to use, an assessment of the ability of the model to predict annual emissions should be undertaken, coupled with an analysis of how model inputs influence model outputs, and whether the modelled estimates are more robust that those derived from the Tier 1 methodology. The aims of the study were (a) to evaluate if the DailyDayCent model can accurately estimate annual N2O emissions across nine different experimental sites, (b) to examine its sensitivity to different soil and climate inputs across a number of experimental sites and (c) to examine the influence of uncertainty in the measured inputs on modelled N2O emissions. DailyDayCent performed well across the range of cropland and grassland sites, particularly for fertilized fields indicating that it is robust for UK conditions. The sensitivity of the model varied across the sites and also between fertilizer/manure treatments. Overall our results showed that there was a stronger correlation between the sensitivity of N2O emissions to changes in soil pH and clay content than the remaining input parameters used in this study. The lower the initial site values for soil pH and clay content, the more sensitive DDC was to changes from their initial value. When we compared modelled estimates with Tier 1 estimates for each site, we found that DailyDayCent provided a more accurate representation of the rate of annual emissions.

  3. Combining a two-sourcepatch model with satellite data to monitor daily evapotranspiration at a regional scale

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this work, we present a micro-meteorological approach for estimating surface energy fluxes that can be operationally used together with satellite images to monitor surface energy fluxes at a regional scale. In particular we will focus on the retrieval of daily evapotranspiration. The feasibility ...

  4. Daily exercise vs. caloric restriction for prevention of nonalcoholic fatty liver disease in the OLETF rat model.

    PubMed

    Rector, R Scott; Uptergrove, Grace M; Morris, E Matthew; Borengasser, Sarah J; Laughlin, M Harold; Booth, Frank W; Thyfault, John P; Ibdah, Jamal A

    2011-05-01

    The maintenance of normal body weight either through dietary modification or being habitually more physically active is associated with reduced incidence of nonalcoholic fatty liver disease (NAFLD). However, the means by which weight gain is prevented and potential mechanisms activated remain largely unstudied. Here, we sought to determine the effects of obesity prevention by daily exercise vs. caloric restriction on NAFLD in the hyperphagic, Otsuka Long-Evans Tokushima Fatty (OLETF) rat. At 4 wk of age, male OLETF rats (n = 7-8/group) were randomized to groups of ad libitum fed, sedentary (OLETF-SED), voluntary wheel running exercise (OLETF-EX), or caloric restriction (OLETF-CR; 70% of SED) until 40 wk of age. Nonhyperphagic, control strain Long-Evans Tokushima Otsuka (LETO) rats were kept in sedentary cage conditions for the duration of the study (LETO-SED). Both daily exercise and caloric restriction prevented obesity and the development of type 2 diabetes observed in the OLETF-SED rats, with glucose tolerance during a glucose tolerance test improved to a greater extent in the OLETF-EX animals (30-50% lower glucose and insulin areas under the curve, P < 0.05). Both daily exercise and caloric restriction also prevented excess hepatic triglyceride and diacylglycerol accumulation (P < 0.001), hepatocyte ballooning and nuclear displacement, and the increased perivenular fibrosis and collagen deposition that occurred in the obese OLETF-SED animals. However, despite similar hepatic phenotypes, OLETF-EX rats also exhibited increased hepatic mitochondrial fatty acid oxidation, enhanced oxidative enzyme function and protein content, and further suppression of hepatic de novo lipogenesis proteins compared with OLETF-CR. Prevention of obesity by either daily exercise or caloric restriction attenuates NAFLD development in OLETF rats. However, daily exercise may offer additional health benefits on glucose homeostasis and hepatic mitochondrial function compared with

  5. Modelling the impact of riparian forest changes on daily sediment yield: A case study in a meso-scale catchment in SE Germany.

    NASA Astrophysics Data System (ADS)

    Keesstra, Saskia; Temme, Arnaud; Feger, Karl-Heinz; van Miltenburg, Saskia

    2010-05-01

    The newly developed sediment delivery model LAPSUS-D has been tested in the meso-scale catchment (60km2) of the Wilde Weisseritz in South-East Germany. LAPSUS-D is the first sediment delivery model that runs with a daily time step and only uses the following input parameters: a DEM, a land use map, a soil map and daily precipitation and discharge data. As the model is new and was calibrated only for a catchment in South-West Poland, the model is now run simultaneous with a widely used sediment delivery model WaTEM/SEDEM (developed in Leuven, Belgium) which simulates erosion and deposition processes on a yearly basis. After a first assessment of the model performance in the German catchment, two scenarios to reduce the sediment yield at the outlet were run. The scenarios were made based on actual river restoration projects elsewhere in similar river settings, to make the scenarios a realistic option for the future. These scenarios were used to run both models to test how the new LAPSUS-D model performs. The comparison reveals the contrast between a yearly and RUSLE based model and the water balance model LAPSUS-D using daily input. The water balance approach includes the effects of the water storage capacity. Locally decreasing water storage capacity causes increased run-off and erosion at lower positions in the landscape. This effect is not visible with the RUSLE approach. Furthermore, the position of the riparian forest scenarios results in differences in the sediment yield simulated by the LAPSUS-D model. While modeling the riparian forest scenarios at different locations in the catchment by the WaTEM/SEDEM causes no difference in sedimentation yield.

  6. Myocardial infarction, ST-elevation and non-ST-elevation myocardial infarction and modelled daily pollution concentrations: a case-crossover analysis of MINAP data

    PubMed Central

    Butland, Barbara K; Atkinson, Richard W; Milojevic, Ai; Heal, Mathew R; Doherty, Ruth M; Armstrong, Ben G; MacKenzie, Ian A; Vieno, Massimo; Lin, Chun; Wilkinson, Paul

    2016-01-01

    Objectives To investigate associations between daily concentrations of air pollution and myocardial infarction (MI), ST-elevation MI (STEMI) and non-ST-elevation MI (NSTEMI). Methods Modelled daily ground-level gaseous, total and speciated particulate pollutant concentrations and ground-level daily mean temperature, all at 5 km×5 km horizontal resolution, were linked to 202 550 STEMI and 322 198 NSTEMI events recorded on the England and Wales Myocardial Ischaemia National Audit Project (MINAP) database. The study period was 2003–2010. A case-crossover design was used, stratified by year, month and day of the week. Data were analysed using conditional logistic regression, with pollutants modelled as unconstrained distributed lags 0–2 days. Results are presented as percentage change in risk per 10 µg/m3 increase in the pollutant relevant metric, having adjusted for daily mean temperature, public holidays, weekly influenza consultation rates and a sine-cosine annual cycle. Results There was no evidence of an association between MI or STEMI and any of O3, NO2, PM2.5, PM10 or selected PM2.5 components (sulfate and elemental carbon). For NSTEMI, there was a positive association with daily maximum 1-hour NO2 (0.27% (95% CI 0.01% to 0.54%)), which persisted following adjustment for O3 and adjustment for PM2.5. The association appeared to be confined to the midland and southern regions of England and Wales. Conclusions The study found no evidence of an association between the modelled pollutants (including components) investigated and STEMI but did find some evidence of a positive association between NO2 and NSTEMI. Confirmation of this association in other studies is required. PMID:27621827

  7. Nonparametric temporal downscaling with event-based population generating algorithm for RCM daily precipitation to hourly: Model development and performance evaluation

    NASA Astrophysics Data System (ADS)

    Lee, Taesam; Park, Taewoong

    2017-04-01

    It is critical to downscale temporally coarse GCM or RCM outputs (e.g., monthly or daily) to fine time scales, such as sub-daily or hourly. Recently, a temporal downscaling model employing a nonparametric framework (NTD) with k-nearest resampling and a genetic algorithm has been developed to preserve key statistics as well as the diurnal cycle. However, this model's usage can be limited in estimating precipitation for design storms or floods because the key statistics of annual maximum precipitation (AMP), especially for longer hourly durations, present a systematic bias that cannot be preserved due to the discontinuity of multiday consecutive precipitation events in the downscaling procedure. In the current study, we develop an approach to downscale a consecutive daily precipitation at once focusing on the reproduction of AMP totals for different durations instead of day-by-day downscaling. The proposed model has been verified with the precipitation datasets for the 60 stations across South Korea over the period 1979-2005. Additionally, two validation studies were performed with the recent datasets of 2006-2014 and nearest neighbor stations. The verification and the two validation tests conclude that the population-based NTD (PNTD) model proposed in the current study is superior to the existing NTD model in preserving the key statistics of the observed AMP series and suitable for downscaling future climate scenarios.

  8. Effects of stage of pregnancy on variance components, daily milk yields and 305-day milk yield in Holstein cows, as estimated by using a test-day model.

    PubMed

    Yamazaki, T; Hagiya, K; Takeda, H; Osawa, T; Yamaguchi, S; Nagamine, Y

    2016-08-01

    Pregnancy and calving are elements indispensable for dairy production, but the daily milk yield of cows decline as pregnancy progresses, especially during the late stages. Therefore, the effect of stage of pregnancy on daily milk yield must be clarified to accurately estimate the breeding values and lifetime productivity of cows. To improve the genetic evaluation model for daily milk yield and determine the effect of the timing of pregnancy on productivity, we used a test-day model to assess the effects of stage of pregnancy on variance component estimates, daily milk yields and 305-day milk yield during the first three lactations of Holstein cows. Data were 10 646 333 test-day records for the first lactation; 8 222 661 records for the second; and 5 513 039 records for the third. The data were analyzed within each lactation by using three single-trait random regression animal models: one model that did not account for the stage of pregnancy effect and two models that did. The effect of stage of pregnancy on test-day milk yield was included in the model by applying a regression on days pregnant or fitting a separate lactation curve for each days open (days from calving to pregnancy) class (eight levels). Stage of pregnancy did not affect the heritability estimates of daily milk yield, although the additive genetic and permanent environmental variances in late lactation were decreased by accounting for the stage of pregnancy effect. The effects of days pregnant on daily milk yield during late lactation were larger in the second and third lactations than in the first lactation. The rates of reduction of the 305-day milk yield of cows that conceived fewer than 90 days after the second or third calving were significantly (P<0.05) greater than that after the first calving. Therefore, we conclude that differences between the negative effects of early pregnancy in the first, compared with later, lactations should be included when determining the optimal number of days open

  9. Comparison between two statistically based methods, and two physically based models developed to compute daily mean streamflow at ungaged locations in the Cedar River Basin, Iowa

    USGS Publications Warehouse

    Linhart, S. Mike; Nania, Jon F.; Christiansen, Daniel E.; Hutchinson, Kasey J.; Sanders, Curtis L.; Archfield, Stacey A.

    2013-01-01

    A variety of individuals from water resource managers to recreational users need streamflow information for planning and decisionmaking at locations where there are no streamgages. To address this problem, two statistically based methods, the Flow Duration Curve Transfer method and the Flow Anywhere method, were developed for statewide application and the two physically based models, the Precipitation Runoff Modeling-System and the Soil and Water Assessment Tool, were only developed for application for the Cedar River Basin. Observed and estimated streamflows for the two methods and models were compared for goodness of fit at 13 streamgages modeled in the Cedar River Basin by using the Nash-Sutcliffe and the percent-bias efficiency values. Based on median and mean Nash-Sutcliffe values for the 13 streamgages the Precipitation Runoff Modeling-System and Soil and Water Assessment Tool models appear to have performed similarly and better than Flow Duration Curve Transfer and Flow Anywhere methods. Based on median and mean percent bias values, the Soil and Water Assessment Tool model appears to have generally overestimated daily mean streamflows, whereas the Precipitation Runoff Modeling-System model and statistical methods appear to have underestimated daily mean streamflows. The Flow Duration Curve Transfer method produced the lowest median and mean percent bias values and appears to perform better than the other models.

  10. Application of random regression model to estimate genetic parameters for average daily gains in Lori-Bakhtiari sheep breed of Iran.

    PubMed

    Farhangfar, H; Naeemipour, H; Zinvand, B

    2007-07-15

    A random regression model was applied to estimate (co) variances, heritabilities and additive genetic correlations among average daily gains. The data was a total of 10876 records belonging to 1828 lambs (progenies of 123 sires and 743 dams) born between 1995 and 2001 in a single large size flock of Lori-Bakhtiari sheep breed in Iran. In the model, fixed environmental effects of year-season of birth, sex, birth type, age of dam and random effects of direct and maternal additive genetic and permanent environment were included. Orthogonal polynomial regression (on the Legendre scale) of third order (cubic) was utilized to model the genetic and permanent environmental (co) variance structure throughout the growth trajectory. Direct and maternal heritability estimates of average daily gains ranged from 0.011 to 0.131 and 0.008 to 0.181, respectively in which pre-weaning average daily gain (0-3 in months) had the lowest direct and highest maternal heritability estimates among the other age groups. The highest and lowest positive direct additive genetic correlations were found to be 0.993 and 0.118 between ADG (0-9) and ADG (0-12) and between ADG (0-3) and ADG (0-12), respectively. The direct additive genetic correlations between adjacent age groups were more closely than between remote age groups.

  11. Pharmacodynamics of once-daily amikacin in various combinations with cefepime, aztreonam, and ceftazidime against Pseudomonas aeruginosa in an in vitro infection model.

    PubMed Central

    McGrath, B J; Bailey, E M; Lamp, K C; Rybak, M J

    1992-01-01

    The pharmacodynamics of once-daily amikacin administered as monotherapy and in combination with aztreonam, ceftazidime, and cefepime against Pseudomonas aeruginosa ATCC 27853 and clinical isolate 16690 (moderately susceptible to ceftazidime) were investigated with an in vitro model of infection over a 24-h period. Monotherapy with aztreonam, ceftazidime, and cefepime and combinations of aztreonam with cefepime or ceftazidime were also studied. MICs and MBCs were determined for viable organisms at 24 h to test for the development of resistance. Once-daily amikacin demonstrated killing activity over the initial 8 h superior to those of all other drugs administered as monotherapy against both strains tested (P < 0.01). Regrowth by 24 h was greatest for the amikacin regimen (P < 0.01) but was apparent for all monotherapy regimens against both strains. No changes in susceptibilities were observed. All combination therapies containing once-daily amikacin achieved 99.9% reductions in log10 CFU/ml by 2.0 h against both strains, with no regrowth of organisms at 24 h. Aztreonam-cefepime and -ceftazidime combinations required approximately 5 to 6 h to achieve a 99.9% reduction in log10 CFU/ml. Although there was no difference in time to the 99.9% kill between the aztreonam-cefepime and -ceftazidime regimens against either strain, the killing activity of these combinations was significantly less than those of regimens containing once-daily amikacin (P < 0.01). Minor differences in the initial susceptibilities of beta-lactams and the monobactam aztreonam against P. aeruginosa may not be important for therapeutic outcomes when used in combination with single-daily aminoglycoside therapy. PMID:1482142

  12. Proposed Hydrodynamic Model Increases the Ability of Land-Surface Models to Capture Intra-Daily Dynamics of Transpiration and Canopy Structure Effects

    NASA Astrophysics Data System (ADS)

    Matheny, A. M.; Bohrer, G.; Mirfenderesgi, G.; Schafer, K. V.; Ivanov, V. Y.

    2014-12-01

    Hydraulic limitations are known to control transpiration in forest ecosystems when the soil is drying or when the vapor pressure deficit between the air and stomata is very large, but they can also impact stomatal apertures under conditions of adequate soil moisture and lower evaporative demand. We use the NACP dataset of latent heat flux measurements and model observations for multiple sites and models to demonstrate models' difficulties in capturing intra-daily hysteresis. We hypothesize that this is a result of un-resolved afternoon stomata closure due to hydrodynamic stresses. The current formulations for stomatal conductance and the empirical coupling between stomatal conductance and soil moisture used by these models does not resolve the hydrodynamic process of water movement from the soil to the leaves. This approach does not take advantage of advances in our understanding of water flow and storage in the trees, or of tree and canopy structure. A more thorough representation of the tree-hydrodynamic processes could potentially remedy this significant source of model error. In a forest plot at the University of Michigan Biological Station, we use measurements of sap flux and leaf water potential to demonstrate that trees of similar type - late successional deciduous trees - have very different hydrodynamic strategies that lead to differences in their temporal patterns of stomatal conductance and thus hysteretic cycles of transpiration. These differences will lead to large differences in conductance and water use based on the species composition of the forest. We also demonstrate that the size and shape of the tree branching system leads to differences in extent of hydrodynamic stress, which may change the forest respiration patterns as the forest grows and ages. We propose a framework to resolve tree hydrodynamics in global and regional models based on the Finite-Elements Tree-Crown Hydrodynamics model (FETCH) -a hydrodynamic model that can resolve the fast

  13. Daily precipitation analysis using the CLARIS-LPB models over hydrological basins and climate regions within the CORDEX South America domain

    NASA Astrophysics Data System (ADS)

    Remedio, A. C.; Carril, A. F.; Jacob, D.; Menendez, C.; Pfeifer, S.; Cavalcanti, I. F.; Solman, S.; Da Rocha, R.; Mourao, C. F.; Samuelsson, P.; Sanchez, E.; Li, L.; Berbery, E.; Marengo, J.

    2013-05-01

    Multiyear simulations of the South America daily precipitation are derived by six regional models and a stretched-grid general circulation model within the framework of the EU FP7 CLARIS-LPB Project. The different institution and models which participated in the coordinated project are SMHI RCA, MPI-M REMO, UCLM PROMES, USP RegCM3, CIMA MM5, IPSL LMDZ and INPE ETA. The setup of the different models attempts to follow the WCRP CORDEX protocol closely such as the horizontal resolution of about 50 km and size of the domain, which covers the whole continent of South America. These models have been integrated for the period of 1989-2008 using the ECMWF ERA-Interim reanalysis as initial and lateral boundary conditions. The daily precipitation observational dataset used is from the NOAA Climate Prediction Center (CPC) with a resolution of 0.5 degree. The precipitation estimates from the high resolution TRMM are also used to ascertain observational uncertainties. The skill of the models and ensemble are evaluated using the probabilistic distribution function over twelve regions with different hydrological and climate characteristics. The seven regions representing hydrological basins are South Amazon, Northeast Brazil, South Atlantic Convergence Zone, Paraguay, Upper Parana, Lower Parana and Uruguay. The other five regions have tropical humid, tropical wet-dry, dry semi-arid, subtropical humid and temperate oceanic climate based on the Koeppen-Trewartha classification. The regions are established to evaluate the simulated daily precipitation at areas of similar characteristics. The seasonal means and extreme indices based on percentile approach are also calculated The models have a relatively high skill in simulating the wintertime precipitation at the different regions. During summer, when the precipitation is mainly driven by convective activity, most of the models have relatively low skill. Attempts are made to explain the different biases among each region due to the

  14. Development of a daily mortality probability prediction model from Intensive Care Unit patients using a discrete-time event history analysis.

    PubMed

    Huang, Ying Che; Chang, Kuang Yi; Lin, Shih Pin; Chen, Kung; Chan, Kwok Hon; Chang, Polun

    2013-08-01

    As studies have pointed out, severity scores are imperfect at predicting individual clinical chance of survival. The clinical condition and pathophysiological status of these patients in the Intensive Care Unit might differ from or be more complicated than most predictive models account for. In addition, as the pathophysiological status changes over time, the likelihood of survival day by day will vary. Actually, it would decrease over time and a single prediction value cannot address this truth. Clearly, alternative models and refinements are warranted. In this study, we used discrete-time-event models with the changes of clinical variables, including blood cell counts, to predict daily probability of mortality in individual patients from day 3 to day 28 post Intensive Care Unit admission. Both models we built exhibited good discrimination in the training (overall area under ROC curve: 0.80 and 0.79, respectively) and validation cohorts (overall area under ROC curve: 0.78 and 0.76, respectively) to predict daily ICU mortality. The paper describes the methodology, the development process and the content of the models, and discusses the possibility of them to serve as the foundation of a new bedside advisory or alarm system.

  15. Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951-2005 using a regional climate model

    NASA Astrophysics Data System (ADS)

    Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.; Chase, Thomas N.; Nath Goswami, Bhupendra

    2016-05-01

    Daily moderate rainfall events, which constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 through 2005. On the other hand, mean and extreme near-surface daily temperature during the monsoon season have increased by a maximum of 1-1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) and prescribed land cover of years 1950 and 2005, it is demonstrated that part of the changes in moderate rainfall events and temperature have been caused by land-use/land-cover change (LULCC), which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over central India coincides with the region of decrease in forest and increase in crop cover. Our results also show that LULCC alone causes warming in the extremes of daily mean and maximum temperatures by a maximum of 1-1.2 °C, which is comparable with the observed increasing trend in the extremes. Decrease in forest cover and simultaneous increase in crops not only reduces the evapotranspiration over land and large-scale convective instability, but also contributes toward decrease in moisture convergence through reduced surface roughness. These factors act together in reducing significantly the moderate rainfall events and the amount of rainfall in that category over central India. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures over the Indian Ocean. As a result, enhanced warming at the surface and greater decrease in moderate rainfall events over central India compared to the earlier set of simulations are noticed. Results from these additional experiments corroborate our initial findings and confirm the contribution of LULCC in the decrease in moderate rainfall events and increase in daily mean and extreme temperature over India. Therefore, this study demonstrates the important implications of LULCC over

  16. A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

    NASA Technical Reports Server (NTRS)

    Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

    2014-01-01

    The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions

  17. A model for developing job rotation schedules that eliminate sequential high workloads and minimize between-worker variability in cumulative daily workloads: Application to automotive assembly lines.

    PubMed

    Yoon, Sang-Young; Ko, Jeonghan; Jung, Myung-Chul

    2016-07-01

    The aim of study is to suggest a job rotation schedule by developing a mathematical model in order to reduce cumulative workload from the successive use of the same body region. Workload assessment using rapid entire body assessment (REBA) was performed for the model in three automotive assembly lines of chassis, trim, and finishing to identify which body part exposed to relatively high workloads at workstations. The workloads were incorporated to the model to develop a job rotation schedule. The proposed schedules prevent the exposure to high workloads successively on the same body region and minimized between-worker variance in cumulative daily workload. Whereas some of workers were successively assigned to high workload workstation under no job rotation and serial job rotation. This model would help to reduce the potential for work-related musculoskeletal disorders (WMSDs) without additional cost for engineering work, although it may need more computational time and relative complex job rotation sequences.

  18. Evaluating five remote sensing based single-source surface energy balance models for estimating daily evapotranspiration in a humid subtropical climate

    NASA Astrophysics Data System (ADS)

    Bhattarai, Nishan; Shaw, Stephen B.; Quackenbush, Lindi J.; Im, Jungho; Niraula, Rewati

    2016-07-01

    In the last two decades, a number of single-source surface energy balance (SEB) models have been proposed for mapping evapotranspiration (ET); however, there is no clear guidance on which models are preferable under different conditions. In this paper, we tested five models-Surface Energy Balance Algorithm for Land (SEBAL), Mapping ET at high Resolution with Internalized Calibration (METRIC), Simplified Surface Energy Balance Index (S-SEBI), Surface Energy Balance System (SEBS), and operational Simplified Surface Energy Balance (SSEBop)-to identify the single-source SEB models most appropriate for use in the humid southeastern United States. ET predictions from these models were compared with measured ET at four sites (marsh, grass, and citrus surfaces) for 149 cloud-free Landsat image acquisition days between 2000 and 2010. The overall model evaluation statistics showed that SEBS generally outperformed the other models in terms of estimating daily ET from different land covers (e.g., the root mean squared error (RMSE) was 0.74 mm day-1). SSEBop was consistently the worst performing model and overestimated ET at all sites (RMSE = 1.67 mm day-1), while the other models typically fell in between SSEBop and SEBS. However, for short grass conditions, SEBAL, METRIC, and S-SEBI appear to work much better than SEBS. Overall, our study suggests that SEBS may be the best SEB model in humid regions, although it may require modifications to work better over short vegetation.

  19. Chance-constrained overland flow modeling for improving conceptual distributed hydrologic simulations based on scaling representation of sub-daily rainfall variability.

    PubMed

    Han, Jing-Cheng; Huang, Guohe; Huang, Yuefei; Zhang, Hua; Li, Zhong; Chen, Qiuwen

    2015-08-15

    Lack of hydrologic process representation at the short time-scale would lead to inadequate simulations in distributed hydrological modeling. Especially for complex mountainous watersheds, surface runoff simulations are significantly affected by the overland flow generation, which is closely related to the rainfall characteristics at a sub-time step. In this paper, the sub-daily variability of rainfall intensity was considered using a probability distribution, and a chance-constrained overland flow modeling approach was proposed to capture the generation of overland flow within conceptual distributed hydrologic simulations. The integrated modeling procedures were further demonstrated through a watershed of China Three Gorges Reservoir area, leading to an improved SLURP-TGR hydrologic model based on SLURP. Combined with rainfall thresholds determined to distinguish various magnitudes of daily rainfall totals, three levels of significance were simultaneously employed to examine the hydrologic-response simulation. Results showed that SLURP-TGR could enhance the model performance, and the deviation of runoff simulations was effectively controlled. However, rainfall thresholds were so crucial for reflecting the scaling effect of rainfall intensity that optimal levels of significance and rainfall threshold were 0.05 and 10 mm, respectively. As for the Xiangxi River watershed, the main runoff contribution came from interflow of the fast store. Although slight differences of overland flow simulations between SLURP and SLURP-TGR were derived, SLURP-TGR was found to help improve the simulation of peak flows, and would improve the overall modeling efficiency through adjusting runoff component simulations. Consequently, the developed modeling approach favors efficient representation of hydrological processes and would be expected to have a potential for wide applications.

  20. A mathematical model linking tree sap flow dynamics to daily stem diameter fluctuations and radial stem growth.

    PubMed

    Steppe, Kathy; De Pauw, Dirk J W; Lemeur, Raoul; Vanrolleghem, Peter A

    2006-03-01

    To date, models for simulating sap flow dynamics in individual trees with a direct link to stem diameter variation include only the diameter fluctuation driven by a change in stem water storage. This paper reports results obtained with a comprehensive flow and storage model using whole-tree leaf transpiration as the only input variable. The model includes radial stem growth based on Lockhart's equation for irreversible cell expansion. It was demonstrated that including growth is essential to obtaining good simulation results. To model sap flow dynamics, capacitance of storage tissues was assumed either constant (i.e., electrical analogue approach) or variable and dependent on the water content of the respective storage tissue (i.e., hydraulic system approach). These approaches resulted in different shapes for the desorption curve used to calculate the capacitance of storage tissues. Comparison of these methods allowed detection of specific differences in model simulation of sap flow at the stem base (F(stem)) and stem diameter variation (D). Sensitivity analysis was performed to select a limited subset of identifiable parameters driving most of the variability in model predictions of F(stem) and D Both the electrical analogue and the hydraulic system approach for the flow and storage model were successfully calibrated and validated for the case of a young beech tree (Fagus sylvatica L.). Use of an objective model selection criterion revealed that the flow and storage model based on the electrical analogue approach yielded better predictions.

  1. Teaching Daily Living Skills to Seven Individuals with Severe Intellectual Disabilities: A Comparison of Video Prompting to Video Modeling

    ERIC Educational Resources Information Center

    Cannella-Malone, Helen I.; Fleming, Courtney; Chung, Yi-Cheih; Wheeler, Geoffrey M.; Basbagill, Abby R.; Singh, Angella H.

    2011-01-01

    We conducted a systematic replication of Cannella-Malone et al. by comparing the effects of video prompting to video modeling for teaching seven students with severe disabilities to do laundry and wash dishes. The video prompting and video modeling procedures were counterbalanced across tasks and participants and compared in an alternating…

  2. Generalized Models for the Classification of Abnormal Movements in Daily Life and its Applicability to Epilepsy Convulsion Recognition.

    PubMed

    Villar, José R; Vergara, Paula; Menéndez, Manuel; de la Cal, Enrique; González, Víctor M; Sedano, Javier

    2016-09-01

    The identification and the modeling of epilepsy convulsions during everyday life using wearable devices would enhance patient anamnesis and monitoring. The psychology of the epilepsy patient penalizes the use of user-driven modeling, which means that the probability of identifying convulsions is driven through generalized models. Focusing on clonic convulsions, this pre-clinical study proposes a method for generating a type of model that can evaluate the generalization capabilities. A realistic experimentation with healthy participants is performed, each with a single 3D accelerometer placed on the most affected wrist. Unlike similar studies reported in the literature, this proposal makes use of [Formula: see text] cross-validation scheme, in order to evaluate the generalization capabilities of the models. Event-based error measurements are proposed instead of classification-error measurements, to evaluate the generalization capabilities of the model, and Fuzzy Systems are proposed as the generalization modeling technique. Using this method, the experimentation compares the most common solutions in the literature, such as Support Vector Machines, [Formula: see text]-Nearest Neighbors, Decision Trees and Fuzzy Systems. The event-based error measurement system records the results, penalizing those models that raise false alarms. The results showed the good generalization capabilities of Fuzzy Systems.

  3. Developing a model for understanding patient collection of observations of daily living: A qualitative meta-synthesis of the Project HealthDesign Program.

    PubMed

    Cohen, Deborah J; Keller, Sara R; Hayes, Gillian R; Dorr, David A; Ash, Joan S; Sittig, Dean F

    2015-01-01

    We conducted a meta-synthesis of five different studies that developed, tested, and implemented new technologies for the purpose of collecting Observations of Daily Living (ODL). From this synthesis, we developed a model to explain user motivation as it relates to ODL collection. We describe this model that includes six factors that motivate patients' collection of ODL data: usability, illness experience, relevance of ODLs, information technology infrastructure, degree of burden, and emotional activation. We show how these factors can act as barriers or facilitators to the collection of ODL data and how interacting with care professionals and sharing ODL data may also influence ODL collection, health-related awareness, and behavior change. The model we developed and used to explain ODL collection can be helpful to researchers and designers who study and develop new, personal health technologies to empower people to improve their health.

  4. Developing a model for understanding patient collection of observations of daily living: A qualitative meta-synthesis of the Project HealthDesign Program

    PubMed Central

    Cohen, Deborah J.; Keller, Sara R.; Hayes, Gillian R.; Dorr, David A.; Ash, Joan S.; Sittig, Dean F.

    2016-01-01

    We conducted a meta-synthesis of five different studies that developed, tested, and implemented new technologies for the purpose of collecting Observations of Daily Living (ODL). From this synthesis, we developed a model to explain user motivation as it relates to ODL collection. We describe this model that includes six factors that motivate patients’ collection of ODL data: usability, illness experience, relevance of ODLs, information technology infrastructure, degree of burden, and emotional activation. We show how these factors can act as barriers or facilitators to the collection of ODL data and how interacting with care professionals and sharing ODL data may also influence ODL collection, health-related awareness, and behavior change. The model we developed and used to explain ODL collection can be helpful to researchers and designers who study and develop new, personal health technologies to empower people to improve their health. PMID:26949381

  5. Investigating the impact of land-use land-cover change on Indian summer monsoon daily rainfall and temperature during 1951-2005 using a regional climate model

    NASA Astrophysics Data System (ADS)

    Halder, S.; Saha, S. K.; Dirmeyer, P. A.; Chase, T. N.; Goswami, B. N.

    2015-07-01

    Daily moderate rainfall events, that constitute a major portion of seasonal summer monsoon rainfall over central India, have decreased significantly during the period 1951 till 2005. Mean and extreme near surface daily temperature during the monsoon season have also increased by a maximum of 1-1.5 °C. Using simulations made with a high-resolution regional climate model (RegCM4) with prescribed vegetation cover of 1950 and 2005, it is demonstrated that part of the above observed changes in moderate rainfall events and temperature have been caused by land-use land-cover change (LULCC) which is mostly anthropogenic. Model simulations show that the increase in seasonal mean and extreme temperature over central India coincides with the region of decreased (increased) forest (crop) cover. The results also show that land-use land-cover alone causes warming in the extremes of daily mean and maximum temperatures by maximum of 1-1.2 °C, that is comparable with the observed increasing trend in the extremes. Decrease (increase) in forest (crop) cover reduces the evapotranspiration over land and large-scale convective instability, apart from decreasing the moisture convergence. These factors act together not only in reducing the moderate rainfall events over central India but also the amount of rainfall in that category, significantly. This is the most interesting result of this study. Additionally, the model simulations are repeated by removing the warming trend in sea surface temperatures. As a result, there is enhanced warming at the surface and decrease in moderate rainfall events over central India. Results from the additional experiments corroborate our initial findings and confirm the contribution of land-use land-cover change on increase in daily mean and extreme temperature and decrease in moderate rainfall events. This study not only demonstrates the important implications of LULCC over India, but also shows the necessity for inclusion of projected anthropogenic

  6. Selecting the optimal method to calculate daily global reference potential evaporation from CFSR reanalysis data for application in a hydrological model study

    NASA Astrophysics Data System (ADS)

    Sperna Weiland, F. C.; Tisseuil, C.; Dürr, H. H.; Vrac, M.; van Beek, L. P. H.

    2012-03-01

    Potential evaporation (PET) is one of the main inputs of hydrological models. Yet, there is limited consensus on which PET equation is most applicable in hydrological climate impact assessments. In this study six different methods to derive global scale reference PET daily time series from Climate Forecast System Reanalysis (CFSR) data are compared: Penman-Monteith, Priestley-Taylor and original and re-calibrated versions of the Hargreaves and Blaney-Criddle method. The calculated PET time series are (1) evaluated against global monthly Penman-Monteith PET time series calculated from CRU data and (2) tested on their usability for modeling of global discharge cycles. A major finding is that for part of the investigated basins the selection of a PET method may have only a minor influence on the resulting river flow. Within the hydrological model used in this study the bias related to the PET method tends to decrease while going from PET, AET and runoff to discharge calculations. However, the performance of individual PET methods appears to be spatially variable, which stresses the necessity to select the most accurate and spatially stable PET method. The lowest root mean squared differences and the least significant deviations (95% significance level) between monthly CFSR derived PET time series and CRU derived PET were obtained for a cell-specific re-calibrated Blaney-Criddle equation. However, results show that this re-calibrated form is likely to be unstable under changing climate conditions and less reliable for the calculation of daily time series. Although often recommended, the Penman-Monteith equation applied to the CFSR data did not outperform the other methods in a evaluation against PET derived with the Penman-Monteith equation from CRU data. In arid regions (e.g. Sahara, central Australia, US deserts), the equation resulted in relatively low PET values and, consequently, led to relatively high discharge values for dry basins (e.g. Orange, Murray and

  7. Development of nonlinear empirical models to forecast daily PM2.5 and ozone levels in three large Chinese cities

    NASA Astrophysics Data System (ADS)

    Lv, Baolei; Cobourn, W. Geoffrey; Bai, Yuqi

    2016-12-01

    Empirical regression models for next-day forecasting of PM2.5 and O3 air pollution concentrations have been developed and evaluated for three large Chinese cities, Beijing, Nanjing and Guangzhou. The forecast models are empirical nonlinear regression models designed for use in an automated data retrieval and forecasting platform. The PM2.5 model includes an upwind air quality variable, PM24, to account for regional transport of PM2.5, and a persistence variable (previous day PM2.5 concentration). The models were evaluated in the hindcast mode with a two-year air quality and meteorological data set using a leave-one-month-out cross validation method, and in the forecast mode with a one-year air quality and forecasted weather dataset that included forecasted air trajectories. The PM2.5 models performed well in the hindcast mode, with coefficient of determination (R2) values of 0.54, 0.65 and 0.64, and normalized mean error (NME) values of 0.40, 0.26 and 0.23 respectively, for the three cities. The O3 models also performed well in the hindcast mode, with R2 values of 0.75, 0.55 and 0.73, and NME values of 0.29, 0.26 and 0.24 in the three cities. The O3 models performed better in summertime than in winter in Beijing and Guangzhou, and captured the O3 variations well all the year round in Nanjing. The overall forecast performance of the PM2.5 and O3 models during the test year varied from fair to good, depending on location. The forecasts were somewhat degraded compared with hindcasts from the same year, depending on the accuracy of the forecasted meteorological input data. For the O3 models, the model forecast accuracy was strongly dependent on the maximum temperature forecasts. For the critical forecasts, involving air quality standard exceedences, the PM2.5 model forecasts were fair to good, and the O3 model forecasts were poor to fair.

  8. A simple daily soil-water balance model for estimating the spatial and temporal distribution of groundwater recharge in temperate humid areas

    USGS Publications Warehouse

    Dripps, W.R.; Bradbury, K.R.

    2007-01-01

    Quantifying the spatial and temporal distribution of natural groundwater recharge is usually a prerequisite for effective groundwater modeling and management. As flow models become increasingly utilized for management decisions, there is an increased need for simple, practical methods to delineate recharge zones and quantify recharge rates. Existing models for estimating recharge distributions are data intensive, require extensive parameterization, and take a significant investment of time in order to establish. The Wisconsin Geological and Natural History Survey (WGNHS) has developed a simple daily soil-water balance (SWB) model that uses readily available soil, land cover, topographic, and climatic data in conjunction with a geographic information system (GIS) to estimate the temporal and spatial distribution of groundwater recharge at the watershed scale for temperate humid areas. To demonstrate the methodology and the applicability and performance of the model, two case studies are presented: one for the forested Trout Lake watershed of north central Wisconsin, USA and the other for the urban-agricultural Pheasant Branch Creek watershed of south central Wisconsin, USA. Overall, the SWB model performs well and presents modelers and planners with a practical tool for providing recharge estimates for modeling and water resource planning purposes in humid areas. ?? Springer-Verlag 2007.

  9. A simple daily soil water balance model for estimating the spatial and temporal distribution of groundwater recharge in temperate humid areas

    NASA Astrophysics Data System (ADS)

    Dripps, W. R.; Bradbury, K. R.

    2007-05-01

    Quantifying the spatial and temporal distribution of natural groundwater recharge is usually a prerequisite for effective groundwater modeling and management. As flow models become increasingly utilized for management decisions, there is an increased need for simple, practical methods to delineate recharge zones and quantify recharge rates. Existing models for estimating recharge distributions are data intensive, require extensive parameterization, and take a significant investment of time in order to establish. The Wisconsin Geological and Natural History Survey (WGNHS) has developed a simple daily soil water balance (SWB) model that uses readily available soil, land cover, topographic, and climatic data in conjunction with a geographic information system (GIS) to estimate the temporal and spatial distribution of groundwater recharge at the watershed scale for temperate humid areas. To demonstrate the methodology and the applicability and performance of the model, two case studies are presented: one for the forested Trout Lake watershed of north central Wisconsin, USA and the other for the urban-agricultural Pheasant Branch Creek watershed of south central Wisconsin, USA. Overall, the SWB model performs well and presents modelers and planners with a practical tool for providing recharge estimates for modeling and water resource planning purposes in humid areas.

  10. The acute effects of daily nicotine intake on heart rate--a toxicokinetic and toxicodynamic modelling study.

    PubMed

    Gajewska, M; Worth, A; Urani, C; Briesen, H; Schramm, K-W

    2014-10-01

    Joint physiologically-based toxicokinetic and toxicodynamic (PBTK/TD) modelling was applied to simulate concentration-time profiles of nicotine, a well-known stimulant, in the human body following single and repeated dosing. Both kinetic and dynamic models were first calibrated by using in vivo literature data for the Caucasian population. The models were then used to estimate the blood and liver concentrations of nicotine in terms of the Area Under Curve (AUC) and the peak concentration (Cmax) for selected exposure scenarios based on inhalation (cigarette smoking), oral intake (nicotine lozenges) and dermal absorption (nicotine patches). The model simulations indicated that whereas frequent cigarette smoking gives rise to high AUC and Cmax in blood, the use of nicotine-rich dermal patches leads to high AUC and Cmax in the liver. Venous blood concentrations were used to estimate one of the most common acute effects, mean heart rate, both at rest and during exercise. These estimations showed that cigarette smoking causes a high peak heart rate, whereas dermal absorption causes a high mean heart rate over 48h. This study illustrates the potential of using PBTK/TD modelling in the safety assessment of nicotine-containing products.

  11. Pharmacological doses of daily ascorbate protect tumors from radiation damage after a single dose of radiation in an intracranial mouse glioma model.

    PubMed

    Grasso, Carole; Fabre, Marie-Sophie; Collis, Sarah V; Castro, M Leticia; Field, Cameron S; Schleich, Nanette; McConnell, Melanie J; Herst, Patries M

    2014-01-01

    Pharmacological ascorbate is currently used as an anti-cancer treatment, potentially in combination with radiation therapy, by integrative medicine practitioners. In the acidic, metal-rich tumor environment, ascorbate acts as a pro-oxidant, with a mode of action similar to that of ionizing radiation; both treatments kill cells predominantly by free radical-mediated DNA damage. The brain tumor, glioblastoma multiforme (GBM), is very resistant to radiation; radiosensitizing GBM cells will improve survival of GBM patients. Here, we demonstrate that a single fraction (6 Gy) of radiation combined with a 1 h exposure to ascorbate (5 mM) sensitized murine glioma GL261 cells to radiation in survival and colony-forming assays in vitro. In addition, we report the effect of a single fraction (4.5 Gy) of whole brain radiation combined with daily intraperitoneal injections of ascorbate (1 mg/kg) in an intracranial GL261 glioma mouse model. Tumor-bearing C57BL/6 mice were divided into four groups: one group received a single dose of 4.5 Gy to the brain 8 days after tumor implantation, a second group received daily intraperitoneal injections of ascorbate (day 8-45) after implantation, a third group received both treatments and a fourth control group received no treatment. While radiation delayed tumor progression, intraperitoneal ascorbate alone had no effect on tumor progression. Tumor progression was faster in tumor-bearing mice treated with radiation and daily ascorbate than in those treated with radiation alone. Histological analysis showed less necrosis in tumors treated with both radiation and ascorbate, consistent with a radio-protective effect of ascorbate in vivo. Discrepancies between our in vitro and in vivo results may be explained by differences in the tumor microenvironment, which determines whether ascorbate remains outside the cell, acting as a pro-oxidant, or whether it enters the cells and acts as an anti-oxidant.

  12. A thermal-based remote sensing modeling system for estimating daily evapotranspiration from field to global scales

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Thermal-infrared (TIR) remote sensing of land surface temperature (LST) provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition as well as providing useful information for constraining prognostic land surface models. This presentation d...

  13. A Daily Diary Study of Coping in the Context of the Job Demands-Control-Support Model

    ERIC Educational Resources Information Center

    Daniels, Kevin; Harris, Claire

    2005-01-01

    We examined one of the processes thought to underpin Karasek and Theorell's job demands-control-support model (1990). This is that control and support accentuate better well-being by fostering problem-focused coping with work demands. We also examined whether other forms of coping implemented through control and support are related to indicators…

  14. Why Are Children Different in Their Daily Sedentariness? An Approach Based on the Mixed-Effects Location Scale Model.

    PubMed

    Gomes, Thayse Natacha; Hedeker, Donald; dos Santos, Fernanda Karina; Pereira, Sara; Katzmarzyk, Peter T; Maia, José A R

    2015-01-01

    This study aimed to investigate the between- and within-individual variability in sedentary time over seven days, using a mixed-effects location scale model. The sample comprised 686 Portuguese children (381 girls) aged 9-11 years, from 23 schools. Sedentary time was estimated by the Actigraph GT3X+ accelerometer, which was used 24 hours/day for 7 consecutive days; height, sitting height, and weight were measured, BMI was computed (WHO cut-points were used to classify subjects as normal weight or overweight/obese), and maturity offset was estimated. Information regarding the home environment was obtained by questionnaire. Results revealed that (i) children were more sedentary on Friday, but less so on Saturday and Sunday (compared to Monday), with significant variation between- and within-subjects (between-subject variance=0.800, within-subject variance=1.793, intra-subject correlation=0.308); (ii) there is a sex effect on sedentariness, with boys being less sedentary than girls (p<0.001), and the between-subject variance was 1.48 times larger for boys than girls; (iii) in terms of the within-subject variance, or erraticism, Tuesday, Wednesday and Friday have similar erraticism levels as Monday (Thursday has less, while Saturday and Sunday have more); in addition, girls (variance ratio=0.632, p<0.001), overweight/obese children (variance ratio=0.861, p=0.019), and those later mature (variance ratio=0.849, p=0.013) have less erraticism than their counterparts; (iv) the within-subject variance varied significantly across subjects (scale std dev=0.342±0.037, p<0.001); and (v) in the fixed part of the model, only biological maturation was positively related to sedentariness. This study demonstrated that there is significant between- and within-subject variability in sedentariness across a whole week. This implies that a focus on intra-individual variability, instead of only on mean values, would provide relevant information towards a more complete map of children

  15. Why Are Children Different in Their Daily Sedentariness? An Approach Based on the Mixed-Effects Location Scale Model

    PubMed Central

    Gomes, Thayse Natacha; Hedeker, Donald; dos Santos, Fernanda Karina; Pereira, Sara; Katzmarzyk, Peter T.; Maia, José A. R.

    2015-01-01

    This study aimed to investigate the between- and within-individual variability in sedentary time over seven days, using a mixed-effects location scale model. The sample comprised 686 Portuguese children (381 girls) aged 9–11 years, from 23 schools. Sedentary time was estimated by the Actigraph GT3X+ accelerometer, which was used 24 hours/day for 7 consecutive days; height, sitting height, and weight were measured, BMI was computed (WHO cut-points were used to classify subjects as normal weight or overweight/obese), and maturity offset was estimated. Information regarding the home environment was obtained by questionnaire. Results revealed that (i) children were more sedentary on Friday, but less so on Saturday and Sunday (compared to Monday), with significant variation between- and within-subjects (between-subject variance=0.800, within-subject variance=1.793, intra-subject correlation=0.308); (ii) there is a sex effect on sedentariness, with boys being less sedentary than girls (p<0.001), and the between-subject variance was 1.48 times larger for boys than girls; (iii) in terms of the within-subject variance, or erraticism, Tuesday, Wednesday and Friday have similar erraticism levels as Monday (Thursday has less, while Saturday and Sunday have more); in addition, girls (variance ratio=0.632, p<0.001), overweight/obese children (variance ratio=0.861, p=0.019), and those later mature (variance ratio=0.849, p=0.013) have less erraticism than their counterparts; (iv) the within-subject variance varied significantly across subjects (scale std dev=0.342±0.037, p<0.001); and (v) in the fixed part of the model, only biological maturation was positively related to sedentariness. This study demonstrated that there is significant between- and within-subject variability in sedentariness across a whole week. This implies that a focus on intra-individual variability, instead of only on mean values, would provide relevant information towards a more complete map of children

  16. Daily ingestion of the probiotic Lactobacillus paracasei ST11 decreases Vaccinia virus dissemination and lethality in a mouse model.

    PubMed

    Dos Santos Pereira Andrade, A C; Lima, M Teixeira; Oliveira, G Pereira; Calixto, R Silva; de Sales E Souza, É Lorenna; da Glória de Souza, D; de Almeida Leite, C M; Ferreira, J M Siqueira; Kroon, E G; de Oliveira, D Bretas; Dos Santos Martins, F; Abrahão, J S

    2017-02-07

    Vaccinia virus (VACV) is an important pathogen. Although studies have shown relationships between probiotics and viruses, the effect of probiotics on VACV infection is unknown. Therefore, this work aims to investigate the probiotics effects on VACV infection. Mice were divided into four groups, two non-infected groups, one receiving the probiotic, the other one not receiving it, and two groups infected intranasally with VACV Western Reserve (VACV-WR) receiving or not receiving the probiotic. Viral titres in organs and cytokine production in the lungs were analysed. Lung samples were also subjected to histological analysis. The intake of probiotic results in reduction in viral spread with a significant decrease of VACV titer on lung, liver and brain of treated group. In addition,treatment with the probiotic results in attenuated mice lung inflammation showing fewer lesions on histological findings and decreased lethality in mice infected with VACV. The ingestion of Lactobacillus paracasei ST11 (LPST11) after VACV infection resulted in 2/9 animal lethality compared with 4/9 in the VACV group. This is the first study on probiotics and VACV interactions, providing not only information about this interaction, but also proposing a model for future studies involving probiotics and other poxvirus.

  17. Tips for Daily Living

    MedlinePlus

    ... Tips and Gadgets for Daily Activities Dressing Tips Shopping Tips Modifying the Bathroom Driving After Stroke Medication ... and resources. Find a group in your area . Online Support If there is not a support group ...

  18. Two-stage model for time-varying effects of discrete longitudinal covariates with applications in analysis of daily process data.

    PubMed

    Yang, Hanyu; Cranford, James A; Li, Runze; Buu, Anne

    2015-02-20

    This study proposes a generalized time-varying effect model that can be used to characterize a discrete longitudinal covariate process and its time-varying effect on a later outcome that may be discrete. The proposed method can be applied to examine two important research questions for daily process data: measurement reactivity and predictive validity. We demonstrate these applications using health risk behavior data collected from alcoholic couples through an interactive voice response system. The statistical analysis results show that the effect of measurement reactivity may only be evident in the first week of interactive voice response assessment. Moreover, the level of urge to drink before measurement reactivity takes effect may be more predictive of a later depression outcome. Our simulation study shows that the performance of the proposed method improves with larger sample sizes, more time points, and smaller proportions of zeros in the binary longitudinal covariate.

  19. A comprehensively quantitative method of evaluating the impact of drought on crop yield using daily multi-scale SPEI and crop growth process model

    NASA Astrophysics Data System (ADS)

    Wang, Qianfeng; Wu, Jianjun; Li, Xiaohan; Zhou, Hongkui; Yang, Jianhua; Geng, Guangpo; An, Xueli; Liu, Leizhen; Tang, Zhenghong

    2016-11-01

    The quantitative evaluation of the impact of drought on crop yield is one of the most important aspects in agricultural water resource management. To assess the impact of drought on wheat yield, the Environmental Policy Integrated Climate (EPIC) crop growth model and daily Standardized Precipitation Evapotranspiration Index (SPEI), which is based on daily meteorological data, are adopted in the Huang Huai Hai Plain. The winter wheat crop yields are estimated at 28 stations, after calibrating the cultivar coefficients based on the experimental site data, and SPEI data was taken 11 times across the growth season from 1981 to 2010. The relationship between estimated yield and multi-scale SPEI were analyzed. The optimum time scale SPEI to monitor drought during the crop growth period was determined. The reference yield was determined by averaging the yields from numerous non-drought years. From this data, we propose a comprehensive quantitative method which can be used to predict the impact of drought on wheat yields by combining the daily multi-scale SPEI and crop growth process model. This method was tested in the Huang Huai Hai Plain. The results suggested that estimation of calibrated EPIC was a good predictor of crop yield in the Huang Huai Hai Plain, with lower RMSE (15.4 %) between estimated yield and observed yield at six agrometeorological stations. The soil moisture at planting time was affected by the precipitation and evapotranspiration during the previous 90 days (about 3 months) in the Huang Huai Hai Plain. SPEIG90 was adopted as the optimum time scale SPEI to identify the drought and non-drought years, and identified a drought year in 2000. The water deficit in the year 2000 was significant, and the rate of crop yield reduction did not completely correspond with the volume of water deficit. Our proposed comprehensive method which quantitatively evaluates the impact of drought on crop yield is reliable. The results of this study further our understanding

  20. A comprehensively quantitative method of evaluating the impact of drought on crop yield using daily multi-scale SPEI and crop growth process model.

    PubMed

    Wang, Qianfeng; Wu, Jianjun; Li, Xiaohan; Zhou, Hongkui; Yang, Jianhua; Geng, Guangpo; An, Xueli; Liu, Leizhen; Tang, Zhenghong

    2017-04-01

    The quantitative evaluation of the impact of drought on crop yield is one of the most important aspects in agricultural water resource management. To assess the impact of drought on wheat yield, the Environmental Policy Integrated Climate (EPIC) crop growth model and daily Standardized Precipitation Evapotranspiration Index (SPEI), which is based on daily meteorological data, are adopted in the Huang Huai Hai Plain. The winter wheat crop yields are estimated at 28 stations, after calibrating the cultivar coefficients based on the experimental site data, and SPEI data was taken 11 times across the growth season from 1981 to 2010. The relationship between estimated yield and multi-scale SPEI were analyzed. The optimum time scale SPEI to monitor drought during the crop growth period was determined. The reference yield was determined by averaging the yields from numerous non-drought years. From this data, we propose a comprehensive quantitative method which can be used to predict the impact of drought on wheat yields by combining the daily multi-scale SPEI and crop growth process model. This method was tested in the Huang Huai Hai Plain. The results suggested that estimation of calibrated EPIC was a good predictor of crop yield in the Huang Huai Hai Plain, with lower RMSE (15.4 %) between estimated yield and observed yield at six agrometeorological stations. The soil moisture at planting time was affected by the precipitation and evapotranspiration during the previous 90 days (about 3 months) in the Huang Huai Hai Plain. SPEIG90 was adopted as the optimum time scale SPEI to identify the drought and non-drought years, and identified a drought year in 2000. The water deficit in the year 2000 was significant, and the rate of crop yield reduction did not completely correspond with the volume of water deficit. Our proposed comprehensive method which quantitatively evaluates the impact of drought on crop yield is reliable. The results of this study further our

  1. Daily precipitation grids for Austria since 1961—development and evaluation of a spatial dataset for hydroclimatic monitoring and modelling

    NASA Astrophysics Data System (ADS)

    Hiebl, Johann; Frei, Christoph

    2017-03-01

    Spatial precipitation datasets that are long-term consistent, highly resolved and extend over several decades are an increasingly popular basis for modelling and monitoring environmental processes and planning tasks in hydrology, agriculture, energy resources management, etc. Here, we present a grid dataset of daily precipitation for Austria meant to promote such applications. It has a grid spacing of 1 km, extends back till 1961 and is continuously updated. It is constructed with the classical two-tier analysis, involving separate interpolations for mean monthly precipitation and daily relative anomalies. The former was accomplished by kriging with topographic predictors as external drift utilising 1249 stations. The latter is based on angular distance weighting and uses 523 stations. The input station network was kept largely stationary over time to avoid artefacts on long-term consistency. Example cases suggest that the new analysis is at least as plausible as previously existing datasets. Cross-validation and comparison against experimental high-resolution observations (WegenerNet) suggest that the accuracy of the dataset depends on interpretation. Users interpreting grid point values as point estimates must expect systematic overestimates for light and underestimates for heavy precipitation as well as substantial random errors. Grid point estimates are typically within a factor of 1.5 from in situ observations. Interpreting grid point values as area mean values, conditional biases are reduced and the magnitude of random errors is considerably smaller. Together with a similar dataset of temperature, the new dataset (SPARTACUS) is an interesting basis for modelling environmental processes, studying climate change impacts and monitoring the climate of Austria.

  2. User-Driven Workflow for Modeling, Monitoring, Product Development, and Flood Map Delivery Using Satellites for Daily Coverage Over Texas May-June 2015

    NASA Astrophysics Data System (ADS)

    Green, D. S.; Frye, S. W.; Wells, G. L.; Adler, R. F.; Brakenridge, R.; Bolten, J. D.; Murray, J. J.; Slayback, D. A.; Kirschbaum, D.; Wu, H.; Cappelaere, P. G.; Schumann, G.; Howard, T.; Flamig, Z.; Clark, R. A.; Stough, T.; Chini, M.; Matgen, P.

    2015-12-01

    Intense rainfall during late April and early May 2015 in Texas and Oklahoma led to widespread flooding in several river basins in that region. Texas state agencies were activated for the May-June floods and severe weather event that ensued for six weeks from May 8 until June 19 following Tropical Storm Bill. This poster depicts a case study where modeling flood potential informed decision making authorities for user-driven high resolution satellite acquisitions over the most critical areas and how experimental flood mapping techniques provided the capability for daily on-going monitoring of these events through the use of increased automation. Recent improvements in flood models resulting from higher frequency updates, better spatial resolution, and increased accuracy of now cast and forecast precipitation products coupled with advanced technology to improve situational awareness for decision makers. These advances enabled satellites to be tasked, data products to be developed and distributed, and feedback loops between the emergency authorities, satellite operators, and mapping researchers to deliver a daily stream of relevant products that informed deployment of emergency resources and improved management of the large-scale event across the local, state, and national levels. This collaboration was made possible through inter-agency cooperation on an international scale through the Committee on Earth Observation Satellites Flood Pilot activity that is supported in the USA by NASA, NOAA, and USGS and includes numerous civilian space agency assets from the European Space Agency along with national agencies from Italy, France, Germany, Japan, and others. The poster describes the inter-linking technology infrastructure, the development and delivery of mapping products, and the lessons learned for product improvement in the future.

  3. Forecasting peak daily ozone levels: part 2--A regression with time series errors model having a principal component trigger to forecast 1999 and 2002 ozone levels.

    PubMed

    Liu, Pao-Wen Grace; Johnson, Richard

    2003-12-01

    A modified time series approach, a Box-Jenkins regression with time series errors (RTSE) model plus a principal component (PC) trigger, has been developed to forecast peak daily 1-hr ozone (O3) in real time at the University of Wisconsin-Milwaukee North (UWM-N) during 1999 and 2002. The PC trigger acts as a predictor variable in the RTSE model. It tries to answer the question: will the next day be a possible high O3 day? To answer this question, three PC trigger rules were developed: (1) Hi-Low Checklist, (2) Discriminant Function Approach I, and (3) Discriminant Function Approach II. Also, a pure RTSE model without including the PC trigger and a persistence approach were tested for comparison. The RTSE model with DFA I successfully forecast the only two 1-hr federal exceedances (124 ppb), one in 1999 and one in 2002. In terms of the O3 100-ppb exceedances, 60-80% of the incorrect forecasts occurred with incorrect PC decisions. A few others may have been caused by unexpected O3-weather relations. When the three approaches used UWM-N data to forecast a 100-ppb exceedance somewhere in the Milwaukee, WI, metropolitan area, their performance was dramatically improved: the false alarm rate was reduced from 0.89 to 0.44, and the probability of detection was increased from 0.71 to 0.88.

  4. The effects of videotape modeling and daily feedback on residential electricity conservation, home temperature and humidity, perceived comfort, and clothing worn: Winter and summer.

    PubMed

    Winett, R A; Hatcher, J W; Fort, T R; Leckliter, I N; Love, S Q; Riley, A W; Fishback, J F

    1982-01-01

    Two studies were conducted in all-electric townhouses and apartments in the winter (N = 83) and summer (N = 54) to ascertain how energy conservation strategies focusing on thermostat change and set-backs and other low-cost/no-cost approaches would affect overall electricity use and electricity used for heating and cooling, the home thermal environment, the perceived comfort of participants, and clothing that was worn. The studies assessed the effectiveness of videotape modeling programs that demonstrated these conservation strategies when used alone or combined with daily feedback on electricity use. In the winter, the results indicated that videotape modeling and/or feedback were effective relative to baseline and to a control group in reducing overall electricity use by about 15% and electricity used for heating by about 25%. Hygrothermographs, which accurately and continuously recorded temperature and humidity in the homes, indicated that participants were able to live with no reported loss in comfort and no change in attire at a mean temperature of about 62 degrees F when home and about 59 degrees F when asleep. The results were highly discrepant with prior laboratory studies indicating comfort at 75 degrees F with the insulation value of the clothing worn by participants in this study. In the summer, a combination of strategies designed to keep a home cool with minimal or no air conditioning, in conjunction with videotape modeling and/or daily feedback, resulted in overall electricity reductions of about 15% with reductions on electricity for cooling of about 34%, but with feedback, and feedback and modeling more effective than modeling alone. Despite these electricity savings, hygrothermograph recordings indicated minimal temperature change in the homes, with no change in perceived comfort or clothing worn. The results are discussed in terms of discrepancies with laboratory studies, optimal combinations of video-media and personal contact to promote behavior

  5. Daily simulation using a three-dimensional atmosphere-ocean regional coupled model, CReSS-NHOES over the CINDY/DYNAMO observation region

    NASA Astrophysics Data System (ADS)

    Shinoda, T.; Yoshioka, M. K.; Aiki, H.; Kato, M.; Masunaga, H.; Smedstad, L. F.; Katsumata, M.; Yoneyama, K.; Higuchi, A.; Tsuboki, K.; Uyeda, H.

    2012-12-01

    We develop a three-dimensional atmosphere-ocean regional coupled-model with cloud-permitting scale; the atmosphere part is Cloud Resolving Storm Simulator (CReSS) and the ocean one is Non Hydrostatic Ocean model for the Earth Simulator (NHOES). This study shows results of daily simulation over the CINDY/DYNAMO observation region using CReSS-NHOES. Three types of sensitivity experiment are carried out to clarify the effect of the two-way coupled simulation and horizontal grid resolutions. One is the CReSS-NHOES two-way coupled simulation with horizontal grid spacing of 0.045 degree (approximately 4.8 km). Another two simulations are the CReSS simulations without coupling NHOES with horizontal grid spacing of 0.045 and 0.0225 degrees (approximately 2.4 km). The Global Spectral Model (GSM: Horizontal grid resolution is approximately 50 km) data provided by Japan Meteorological Agency (JMA) are used as the initial and boundary conditions of the atmosphere in CReSS and CReSS-NHOES. Three-dimensional Navy Coastal Ocean Model (NCOM) data provided by Naval Research Laboratory are used as the initial and boundary conditions of the ocean in CReSS-NHOES. The daily simulation is carried out for 36 hours from 12 UTC from October 1, 2011 to January 31, 2012 almost every day. We reproduce approximately 30-day surface pressure perturbation that should be related to the Madden-Julian Oscillation, half-day surface pressure perturbation that is related to the atmospheric tide, and the existence of low equivalent potential temperature airmass in the middle troposphere at a fixed observation point of the R/V Mirai (80.5E, 8S). However, the sharp vertical gradient of temperature and salinity at the bottom of the ocean mixed layer at the same point cannot be reproduced. The sensitivity of the coupling of the ocean model is not critical, because the difference of area-averaged sea surface temperature, sensible and latent heat fluxes from the sea surface is quite small. This should be

  6. The effects of videotape modeling and daily feedback on residential electricity conservation, home temperature and humidity, perceived comfort, and clothing worn: Winter and summer

    PubMed Central

    Winett, Richard A.; Hatcher, Joseph W.; Fort, T. Richard; Leckliter, Ingrid N.; Love, Susan Q.; Riley, Anne W.; Fishback, James F.

    1982-01-01

    Two studies were conducted in all-electric townhouses and apartments in the winter (N = 83) and summer (N = 54) to ascertain how energy conservation strategies focusing on thermostat change and set-backs and other low-cost/no-cost approaches would affect overall electricity use and electricity used for heating and cooling, the home thermal environment, the perceived comfort of participants, and clothing that was worn. The studies assessed the effectiveness of videotape modeling programs that demonstrated these conservation strategies when used alone or combined with daily feedback on electricity use. In the winter, the results indicated that videotape modeling and/or feedback were effective relative to baseline and to a control group in reducing overall electricity use by about 15% and electricity used for heating by about 25%. Hygrothermographs, which accurately and continuously recorded temperature and humidity in the homes, indicated that participants were able to live with no reported loss in comfort and no change in attire at a mean temperature of about 62°F when home and about 59°F when asleep. The results were highly discrepant with prior laboratory studies indicating comfort at 75°F with the insulation value of the clothing worn by participants in this study. In the summer, a combination of strategies designed to keep a home cool with minimal or no air conditioning, in conjunction with videotape modeling and/or daily feedback, resulted in overall electricity reductions of about 15% with reductions on electricity for cooling of about 34%, but with feedback, and feedback and modeling more effective than modeling alone. Despite these electricity savings, hygrothermograph recordings indicated minimal temperature change in the homes, with no change in perceived comfort or clothing worn. The results are discussed in terms of discrepancies with laboratory studies, optimal combinations of video-media and personal contact to promote behavior change, and energy

  7. Effects of climate change on daily minimum and maximum temperatures and cloudiness in the Shikoku region: a statistical downscaling model approach

    NASA Astrophysics Data System (ADS)

    Tatsumi, Kenichi; Oizumi, Tsutao; Yamashiki, Yosuke

    2015-04-01

    In this study, we present a detailed analysis of the effect of changes in cloudiness (CLD) between a future period (2071-2099) and the base period (1961-1990) on daily minimum temperature (TMIN) and maximum temperature (TMAX) in the same period for the Shikoku region, Japan. This analysis was performed using climate data obtained with the use of the Statistical DownScaling Model (SDSM). We calibrated the SDSM using the National Center for Environmental Prediction (NCEP) reanalysis dataset for the SDSM input and daily time series of temperature and CLD from 10 surface data points (SDP) in Shikoku. Subsequently, we validated the SDSM outputs, specifically, TMIN, TMAX, and CLD, obtained with the use of the NCEP reanalysis dataset and general circulation model (GCM) data against the SDP. The GCM data used in the validation procedure were those from the Hadley Centre Coupled Model, version 3 (HadCM3) for the Special Report on Emission Scenarios (SRES) A2 and B2 scenarios and from the third generation Coupled Global Climate Model (CGCM3) for the SRES A2 and A1B scenarios. Finally, the validated SDSM was run to study the effect of future changes in CLD on TMIN and TMAX. Our analysis showed that (1) the negative linear fit between changes in TMAX and those in CLD was statistically significant in winter while the relationship between the two changes was not evident in summer, (2) the dependency of future changes in TMAX and TMIN on future changes in CLD were more evident in winter than in other seasons with the present SDSM, (3) the diurnal temperature range (DTR) decreased in the southern part of Shikoku in summer in all the SDSM projections while DTR increased in the northern part of Shikoku in the same season in these projections, (4) the dependencies of changes in DTR on changes in CLD were unclear in summer and winter. Results of the SDSM simulations performed for climate change scenarios such as those from this study contribute to local-scale agricultural and

  8. Using a spatio-temporal dynamic state-space model with the EM algorithm to patch gaps in daily riverflow series, with examples from the Volta Basin, West Africa

    NASA Astrophysics Data System (ADS)

    Amisigo, B. A.; van de Giesen, N. C.

    2005-04-01

    A spatio-temporal linear dynamic model has been developed for patching short gaps in daily river runoff series. The model was cast in a state-space form in which the state variable was estimated using the Kalman smoother (RTS smoother). The EM algorithm was used to concurrently estimate both parameter and missing runoff values. Application of the model to daily runoff series in the Volta Basin of West Africa showed that the model was capable of providing good estimates of missing runoff values at a gauging station from the remaining series at the station and at spatially correlated stations in the same sub-basin.

  9. Pharmacological Doses of Daily Ascorbate Protect Tumors from Radiation Damage after a Single Dose of Radiation in an Intracranial Mouse Glioma Model

    PubMed Central

    Grasso, Carole; Fabre, Marie-Sophie; Collis, Sarah V.; Castro, M. Leticia; Field, Cameron S.; Schleich, Nanette; McConnell, Melanie J.; Herst, Patries M.

    2014-01-01

    Pharmacological ascorbate is currently used as an anti-cancer treatment, potentially in combination with radiation therapy, by integrative medicine practitioners. In the acidic, metal-rich tumor environment, ascorbate acts as a pro-oxidant, with a mode of action similar to that of ionizing radiation; both treatments kill cells predominantly by free radical-mediated DNA damage. The brain tumor, glioblastoma multiforme (GBM), is very resistant to radiation; radiosensitizing GBM cells will improve survival of GBM patients. Here, we demonstrate that a single fraction (6 Gy) of radiation combined with a 1 h exposure to ascorbate (5 mM) sensitized murine glioma GL261 cells to radiation in survival and colony-forming assays in vitro. In addition, we report the effect of a single fraction (4.5 Gy) of whole brain radiation combined with daily intraperitoneal injections of ascorbate (1 mg/kg) in an intracranial GL261 glioma mouse model. Tumor-bearing C57BL/6 mice were divided into four groups: one group received a single dose of 4.5 Gy to the brain 8 days after tumor implantation, a second group received daily intraperitoneal injections of ascorbate (day 8–45) after implantation, a third group received both treatments and a fourth control group received no treatment. While radiation delayed tumor progression, intraperitoneal ascorbate alone had no effect on tumor progression. Tumor progression was faster in tumor-bearing mice treated with radiation and daily ascorbate than in those treated with radiation alone. Histological analysis showed less necrosis in tumors treated with both radiation and ascorbate, consistent with a radio-protective effect of ascorbate in vivo. Discrepancies between our in vitro and in vivo results may be explained by differences in the tumor microenvironment, which determines whether ascorbate remains outside the cell, acting as a pro-oxidant, or whether it enters the cells and acts as an anti-oxidant. PMID:25566497

  10. Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications.

    PubMed

    Sun, Wenchao; Ishidaira, Hiroshi; Bastola, Satish; Yu, Jingshan

    2015-05-01

    Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash-Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins.

  11. Using the Enhanced Daily Load Stimulus Model to Quantify the Mechanical Load and Bone Mineral Density Changes Experienced by Crew Members on the International Space Station

    NASA Technical Reports Server (NTRS)

    Genc, K. O.; Gopalakrishnan, R.; Kuklis, M. M.; Maender, C. C.; Rice, A. J.; Cavanagh, P. R.

    2009-01-01

    Despite the use of exercise countermeasures during long-duration space missions, bone mineral density (BMD) and predicted bone strength of astronauts continue to show decreases in the lower extremities and spine. This site-specific bone adaptation is most likely caused by the effects of microgravity on the mechanical loading environment of the crew member. There is, therefore, a need to quantify the mechanical loading experienced on Earth and on-orbit to define the effect of a given "dose" of loading on bone homeostasis. Gene et al. recently proposed an enhanced DLS (EDLS) model that, when used with entire days of in-shoe forces, takes into account recently developed theories on the importance of factors such as saturation, recovery, and standing and their effects on the osteogenic response of bone to daily physical activity. This algorithm can also quantify the tinting and type of activity (sit/unload, stand, walk, run or other loaded activity) performed throughout the day. The purpose of the current study was to use in-shoe force measurements from entire typical work days on Earth and on-orbit in order to quantify the type and amount of loading experienced by crew members. The specific aim was to use these measurements as inputs into the EDLS model to determine activity timing/type and the mechanical "dose" imparted on the musculoskeletal system of crew members and relate this dose to changes in bone homeostasis.

  12. Analysis of the impacts of EC-Earth Global Circulation Model in the RCP45 climate change scenario on maximum daily streamflow quantiles at global scale

    NASA Astrophysics Data System (ADS)

    Silvestro, Francesco; Campo, Lorenzo; Rudari, Roberto; Herold, Christian; De Angeli, Silvia; Gabellani, Simone; D'Andrea, Mirko; Rodila, Denisa

    2016-04-01

    Climate changes can have an impact on various components of hydrological cycle. From a risk assessment point of view it is certainly interesting understanding how extreme streamflow values can change as a consequence of climate variability. In order to do this the outputs of a climate model (EC-EARTH) that accounts for a standard climate scenario were used to feed a hydrological model and to generate 140 years (1960-2100) of continuous streamflow simulations in a large number of stations that cover all the world. These time series were then post-processed in order to evaluate how annual daily maximum streamflow quantiles change because of climate scenarios. The analysis highlights that in many cases there is an increment or a decrease of the quantiles for fixed return periods, but only in a reduced number of situations these variation lay out of the confidence intervals of the quantiles estimated in current climate. The analysis was carried out on over 5000 stations distributed in all continents and spanned the period 1960-2100 according to the climate scenario RCP45.

  13. Using repeated daily assessments to uncover oscillating patterns and temporally-dynamic triggers in structures of psychopathology: Applications to the DSM-5 alternative model of personality disorders.

    PubMed

    Roche, Michael J; Jacobson, Nicholas C; Pincus, Aaron L

    2016-11-01

    Articulating an accurate and clinically useful structure of psychopathology is a crucial and difficult task. Dimensions identified through cross-sectional factor analyses are increasingly being linked with temporally dynamic processes of social cognition, emotion regulation, symptom expression, and functional impairment to demonstrate how between-person structures and within-person dynamics can be integrated. The present research considers how structure and processes are integrated in the DSM-5, specifically in the alternative model for personality disorders (AMPD). Participants (n = 248) completed a 14-day electronic diary, and results indicated that personality impairments oscillated across days and were triggered by daily negative emotions and cognitive distortions. Importantly, some aspects of the AMPD model that are identified as potentially redundant in cross-sectional research are shown here to increment each other in the prediction of dynamic oscillations and triggers. Thus, longitudinal designs and temporally dynamic analyses may provide new and novel evidence to fully inform structures of psychopathology. Such research is a needed step in the integration of the structure and process in classification and diagnosis of psychopathology. (PsycINFO Database Record

  14. Daily and Compulsive Internet Use and Well-Being in Adolescence: A Diathesis-Stress Model Based on Big Five Personality Traits

    ERIC Educational Resources Information Center

    van der Aa, Niels; Overbeek, Geertjan; Engels, Rutger C. M. E.; Scholte, Ron H. J.; Meerkerk, Gert-Jan; Van den Eijnden, Regina J. J. M.

    2009-01-01

    This study examined the associations between adolescents' daily Internet use and low well-being (i.e., loneliness, low self-esteem, and depressive moods). We hypothesized that (a) linkages between high levels of daily Internet use and low well-being would be mediated by compulsive Internet use (CIU), and (b) that adolescents with low levels of…

  15. Calibration and parameterization of a semi-distributed hydrological model to support sub-daily ensemble flood forecasting; a watershed in southeast Brazil

    NASA Astrophysics Data System (ADS)

    de Almeida Bressiani, D.; Srinivasan, R.; Mendiondo, E. M.

    2013-12-01

    The use of distributed or semi-distributed models to represent the processes and dynamics of a watershed in the last few years has increased. These models are important tools to predict and forecast the hydrological responses of the watersheds, and they can subside disaster risk management and planning. However they usually have a lot of parameters, of which, due to the spatial and temporal variability of the processes, are not known, specially in developing countries; therefore a robust and sensible calibration is very important. This study conduced a sub-daily calibration and parameterization of the Soil & Water Assessment Tool (SWAT) for a 12,600 km2 watershed in southeast Brazil, and uses ensemble forecasts to evaluate if the model can be used as a tool for flood forecasting. The Piracicaba Watershed, in São Paulo State, is mainly rural, but has about 4 million of population in highly relevant urban areas, and three cities in the list of critical cities of the National Center for Natural Disasters Monitoring and Alerts. For calibration: the watershed was divided in areas with similar hydrological characteristics, for each of these areas one gauge station was chosen for calibration; this procedure was performed to evaluate the effectiveness of calibrating in fewer places, since areas with the same group of groundwater, soil, land use and slope characteristics should have similar parameters; making calibration a less time-consuming task. The sensibility analysis and calibration were performed on the software SWAT-CUP with the optimization algorithm: Sequential Uncertainly Fitting Version 2 (SUFI-2), which uses Latin hypercube sampling scheme in an iterative process. The performance of the models to evaluate the calibration and validation was done with: Nash-Sutcliffe efficiency coefficient (NSE), determination coefficient (r2), root mean square error (RMSE), and percent bias (PBIAS), with monthly average values of NSE around 0.70, r2 of 0.9, normalized RMSE of 0

  16. Toothbrushing: Do It Daily.

    ERIC Educational Resources Information Center

    Texas Child Care, 1993

    1993-01-01

    Offers a practical guide for promoting daily toothbrushing in young children. Discusses the importance of proper dental care, explains the causes of tooth decay, describes proper dental care for infants and young children, recommends materials and teaching methods, and discusses visits to the dentist and the benefits of fluoride for dental health.…

  17. Daily rainfall and temperature estimation by kriging with external drift in an Alpine Catchment. Sensitivity analysis to the temporal scale adopted to define the variogram models. (southeast Spain)

    NASA Astrophysics Data System (ADS)

    Juan Collados-Lara, Antonio; Pardo-Iguzquiza, Eulogio; Pulido-Velazquez, David; Jimenez-Sanchez, Jorge

    2016-04-01

    The knowledge of the climatic historical variables in a River Basin is essential for an appropriate management of the water resources in the system. Temperature and precipitation are the most important variables from the point of view of the assessment of water availability and its spatially and temporal distribution. The aim of this work is to estimate temperature and precipitation using kriging with external drift (KED). A grid with a spatial resolution of 1 km and a daily temporal resolution has been adopted to estimate values for the period 1980 to 2014 in the "Alto Genil" basin (southeast Spain). The altitude in the catchment changes from 530 to 3100 m a.s.l. The climatic variables depend of the altitude and this variable has been used as external drift. Data from 119 precipitation station and 72 temperature station of the AEMET have been employed. The relationship between the altitude and the variables has been analyzed using the regression function of daily mean precipitation and temperature for annual and monthly scale. Normally the temperature and precipitation increase linearly with the altitude. The relationship between temperature and altitude is clearly linear. In the case of the precipitation there is a value of altitude (approximately 1500 m) from which the precipitation decreases with the altitude (inverse rainfall gradient) for every months with the exception of July that has a linear relationship. This inverse rainfall gradient has been observed in other cases as Andes Mountains, some African high mountains, tropical or subtropical high mountains. Therefore, in the case of the precipitation we have a quadratic external drift and for the temperature we have a linear external drift. The monthly and annual climatic variograms were calibrated in order to study if the climatic variables have a seasonal conduct. The KED allows to obtain an estimation with both models (annual and monthly) for the two variables and we can quantify the sensibility of the

  18. Accelerometer measured daily physical activity and sedentary pursuits–comparison between two models of the Actigraph and the importance of data reduction

    PubMed Central

    2013-01-01

    Background Very few validation studies have been performed between different generations of the commonly used Actigraph accelerometers. We compared daily physical activity data generated from the old generation Actigraph model 7164 with the new generation Actigraph GT1M accelerometer in 15 young females for eight consecutive days. We also investigated if different wear time thresholds had any impact on the findings. Minutes per day of moderate and vigorous physical activity (MVPA), vigorous physical activity (VPA) and very vigorous physical activity (VVPA) were calculated. Moreover, minutes of sedentary pursuits per day were calculated. Findings There were significant (P < 0.05) differences between the Actigraph 7164 and the GT1M concerning MVPA (61 ± 21vs. 56 ± 23 min/day), VPA (12 ± 8 vs. 9 ± 3 min/day) and VVPA (3.2 ± 3.0 vs. 0.3 ± 1.1 min/day). The different wear time thresholds had little impact on minutes per day in different intensities. Median minutes of sedentary pursuits per day ranged from 159 to 438 minutes depending on which wear time threshold was used (i.e. 10, 30 or 60 minutes), whereas very small differences were observed between the two different models. Conclusions Data from the old generation Actigraph 7164 and the new generation Actigraph GT1M accelerometers differ, where the Actigraph GT1M generates lower minutes spent in free living physical activity. Median minutes of sedentary pursuits per day are highly dependent on which wear time threshold that is used, and not by accelerometer model. PMID:24176143

  19. On using a generalized linear model to downscale daily precipitation for the center of Portugal: an analysis of trends and extremes

    NASA Astrophysics Data System (ADS)

    Pulquério, Mário; Garrett, Pedro; Santos, Filipe Duarte; Cruz, Maria João

    2015-04-01

    Portugal is on a climate change hot spot region, where precipitation is expected to decrease with important impacts regarding future water availability. As one of the European countries affected more by droughts in the last decades, it is important to assess how future precipitation regimes will change in order to study its impacts on water resources. Due to the coarse scale of global circulation models, it is often needed to downscale climate variables to the regional or local scale using statistical and/or dynamical techniques. In this study, we tested the use of a generalized linear model, as implemented in the program GLIMCLIM, to downscale precipitation for the center of Portugal where the Tagus basin is located. An analysis of the method performance is done as well as an evaluation of future precipitation trends and extremes for the twenty-first century. Additionally, we perform the first analysis of the evolution of droughts in climate change scenarios by the Standardized Precipitation Index in the study area. Results show that GLIMCLIM is able to capture the precipitation's interannual variation and seasonality correctly. However, summer precipitation is considerably overestimated. Additionally, precipitation extremes are in general well recovered, but high daily rainfall may be overestimated, and dry spell lengths are not correctly recovered by the model. Downscaled projections show a reduction in precipitation between 19 and 28 % at the end of the century. Results indicate that precipitation extremes will decrease and the magnitude of droughts can increase up to three times in relation to the 1961-1990 period which can have strong ecological, social, and economic impacts.

  20. An analysis of the daily precipitation variability in the Himalayan orogen using a statistical parameterisation and its potential in driving landscape evolution models with stochastic climatic forcing

    NASA Astrophysics Data System (ADS)

    Deal, Eric; Braun, Jean

    2015-04-01

    A current challenge in landscape evolution modelling is to integrate realistic precipitation patterns and behaviour into longterm fluvial erosion models. The effect of precipitation on fluvial erosion can be subtle as well as nonlinear, implying that changes in climate (e.g. precipitation magnitude or storminess) may have unexpected outcomes in terms of erosion rates. For example Tucker and Bras (2000) show theoretically that changes in the variability of precipitation (storminess) alone can influence erosion rate across a landscape. To complicate the situation further, topography, ultimately driven by tectonic uplift but shaped by erosion, has a major influence on the distribution and style of precipitation. Therefore, in order to untangle the coupling between climate, erosion and tectonics in an actively uplifting orogen where fluvial erosion is dominant it is important to understand how the 'rain dial' used in a landscape evolution model (LEM) corresponds to real precipitation patterns. One issue with the parameterisation of rainfall for use in an LEM is the difference between the timescales for precipitation (≤ 1 year) and landscape evolution (> 103 years). As a result, precipitation patterns must be upscaled before being integrated into a model. The relevant question then becomes: What is the most appropriate measure of precipitation on a millennial timescale? Previous work (Tucker and Bras, 2000; Lague, 2005) has shown that precipitation can be properly upscaled by taking into account its variable nature, along with its average magnitude. This captures the relative size and frequency of extreme events, ensuring a more accurate characterisation of the integrated effects of precipitation on erosion over long periods of time. In light of this work, we present a statistical parameterisation that accurately models the mean and daily variability of ground based (APHRODITE) and remotely sensed (TRMM) precipitation data in the Himalayan orogen with only a few

  1. SU-E-J-257: A PCA Model to Predict Adaptive Changes for Head&neck Patients Based On Extraction of Geometric Features From Daily CBCT Datasets

    SciTech Connect

    Chetvertkov, M; Siddiqui, F; Chetty, I; Kim, J; Kumarasiri, A; Liu, C; Gordon, J

    2015-06-15

    Purpose: Using daily cone beam CTs (CBCTs) to develop principal component analysis (PCA) models of anatomical changes in head and neck (H&N) patients and to assess the possibility of using these prospectively in adaptive radiation therapy (ART). Methods: Planning CT (pCT) images of 4 H&N patients were deformed to model several different systematic changes in patient anatomy during the course of the radiation therapy (RT). A Pinnacle plugin was used to linearly interpolate the systematic change in patient for the 35 fraction RT course and to generate a set of 35 synthetic CBCTs. Each synthetic CBCT represents the systematic change in patient anatomy for each fraction. Deformation vector fields (DVFs) were acquired between the pCT and synthetic CBCTs with random fraction-to-fraction changes were superimposed on the DVFs. A patient-specific PCA model was built using these DVFs containing systematic plus random changes. It was hypothesized that resulting eigenDVFs (EDVFs) with largest eigenvalues represent the major anatomical deformations during the course of treatment. Results: For all 4 patients, the PCA model provided different results depending on the type and size of systematic change in patient’s body. PCA was more successful in capturing the systematic changes early in the treatment course when these were of a larger scale with respect to the random fraction-to-fraction changes in patient’s anatomy. For smaller scale systematic changes, random changes in patient could completely “hide” the systematic change. Conclusion: The leading EDVF from the patientspecific PCA models could tentatively be identified as a major systematic change during treatment if the systematic change is large enough with respect to random fraction-to-fraction changes. Otherwise, leading EDVF could not represent systematic changes reliably. This work is expected to facilitate development of population-based PCA models that can be used to prospectively identify significant

  2. Effect of icariin in combination with daily sildenafil on penile atrophy and erectile dysfunction in a rat model of bilateral cavernous nerves injury.

    PubMed

    Xu, Y; Xin, H; Wu, Y; Guan, R; Lei, H; Fu, X; Xin, Z; Yang, Y

    2017-03-10

    The commonly utilized phosphodiesterase type 5 inhibitors do not lead to satisfactory penile erection after radical prostatectomy mainly because of insufficient nitric oxide drive from the damaged cavernous nerves. The aim of this study was to assess the efficacy and mechanisms of icariin in combination with daily sildenafil on neurogenic erectile dysfunction and penile atrophy in a rat model of bilateral cavernous nerves injury. Sixty male Sprague-Dawley rats injected with 5-ethynyl-2-deoxyuridine (50 mg/kg) at postnatal day 1 for the purpose of tracking endogenous stem cells in penis. Forty-eight rats of bilateral cavernous nerves injury were randomized equally into gavage feeding of vehicle, sildenafil (10 mg/kg), icariin (1.5 mg/kg) and sildenafil + icariin, respectively. Twelve sham-operated rats served as control. The intracavernous pressure and mean arterial pressure was measured and mid-penile cross sections were histologically examined 5 weeks after surgery. Western blotting of cavernous tissue protein was also performed. Animals treated with sildenafil + icariin had significantly higher mean intracavernous pressure/mean arterial pressure ratio relative to other rats with bilateral cavernous nerves injury (p < 0.05). The circumference and mean cross-sectional area of the paired corpus cavernosum were effectively preserved in the sildenafil + icariin. Treatment with sildenafil + icariin significantly increased the cavernous cyclic guanosine monophosphate concentration compared with the icariin group (p < 0.05). In addition, the numbers of neuronal nitric oxide synthase-positive nerves and 5-ethynyl-2-deoxyuridine-positive cells co-expressing S100 in the icariin-treated groups were greater compared with the bilateral cavernous nerves injury control group (p < 0.05). These data suggest that the combined use of icariin and daily sildenafil holds promise as a potential therapy for neurogenic erectile dysfunction in the future. The underlying

  3. New daily persistent headache.

    PubMed

    Tyagi, Alok

    2012-08-01

    New daily persistent headache (NDPH) is a chronic headache developing in a person who does not have a past history of headaches. The headache begins acutely and reaches its peak within 3 days. It is important to exclude secondary causes, particularly headaches due to alterations in cerebrospinal fluid (CSF) pressure and volume. A significant proportion of NDPH sufferers may have intractable headaches that are refractory to treatment. The condition is best viewed as a syndrome rather than a diagnosis. The headache can mimic chronic migraine and chronic tension-type headache, and it is also important to exclude secondary causes, particularly headaches due to alterations in CSF pressure and volume. A large proportion of NDPH sufferers have migrainous features to their headache and should be managed with treatments used for treating migraine. A small group of NDPH sufferers may have intractable headaches that are refractory to treatment.

  4. Inter-daily variability of a strong thermally-driven wind system over the Atacama Desert of South America: synoptic forcing and short-term predictability using the GFS global model

    NASA Astrophysics Data System (ADS)

    Jacques-Coper, Martín; Falvey, Mark; Muñoz, Ricardo C.

    2015-07-01

    Crucial aspects of a strong thermally-driven wind system in the Atacama Desert in northern Chile during the extended austral winter season (May-September) are studied using 2 years of measurement data from the Sierra Gorda 80-m meteorological mast (SGO, 22° 56' 24″ S; 69° 7' 58″ W, 2,069 m above sea level (a.s.l.)). Daily cycles of atmospheric variables reveal a diurnal (nocturnal) regime, with northwesterly (easterly) flow and maximum mean wind speed of 8 m/s (13 m/s) on average. These distinct regimes are caused by pronounced topographic conditions and the diurnal cycle of the local radiative balance. Wind speed extreme events of each regime are negatively correlated at the inter-daily time scale: High diurnal wind speed values are usually observed together with low nocturnal wind speed values and vice versa. The associated synoptic conditions indicate that upper-level troughs at the coastline of southwestern South America reinforce the diurnal northwesterly wind, whereas mean undisturbed upper-level conditions favor the development of the nocturnal easterly flow. We analyze the skill of the numerical weather model Global Forecast System (GFS) in predicting wind speed at SGO. Although forecasted wind speeds at 800 hPa do show the diurnal and nocturnal phases, observations at 80 m are strongly underestimated by the model. This causes a pronounced daily cycle of root-mean-squared error (RMSE) and bias in the forecasts. After applying a simple Model Output Statistics (MOS) post-processing, we achieve a good representation of the wind speed intra-daily and inter-daily variability, a first step toward reducing the uncertainties related to potential wind energy projects in the region.

  5. Analysis of daily latitude variations

    NASA Technical Reports Server (NTRS)

    Graber, M. A.

    1979-01-01

    The daily latitude measurements of the International Polar Motion Service are analyzed. The annual oscillation in the data was modeled by separate oscillations in each observatory's latitude data. The separate oscillations varied in amplitude from 0.05 sec to 0.15 sec with standard deviations of about 0.007 sec. Within the resolution of the latitude residuals (150 cm), there is no indication of the sharp changes which might be associated with earthquake effects. Then, applying Schuster's test to a periodogram of the residuals indicates that there are probably several processes occurring at amplitudes between 0.007 sec and 0.03 sec whose solution awaits a more precise measurement technique.

  6. Quantification of Daily Physical Activity

    NASA Technical Reports Server (NTRS)

    Whalen, Robert; Breit, Greg; Quintana, Jason

    1994-01-01

    The influence of physical activity on the maintenance and adaptation of musculoskeletal tissue is difficult to assess. Cumulative musculoskeletal loading is hard to quantify and the attributes of the daily tissue loading history affecting bone metabolism have not been completely identified. By monitoring the vertical component of the daily ground reaction force (GRFz), we have an indirect measure of cumulative daily lower limb musculoskeletal loading to correlate with bone density and structure. The objective of this research is to develop instrumentation and methods of analysis to quantify activity level in terms of the daily history of ground reaction forces.

  7. Temporal disaggregation of daily meteorological grid data

    NASA Astrophysics Data System (ADS)

    Vormoor, K.; Skaugen, T.

    2012-04-01

    For operational flood forecasting, the Norwegian Water Resources and Energy Administration (NVE) applies the conceptual HBV rainfall-runoff model for 117 catchments. The hydrological models are calibrated and run using an extensive meteorological grid data set providing daily temperature and precipitation data back to 1957 for entire Norway at 1x1 km grid resolution (seNorge grids). The daily temporal resolution is dictated by the resolution of historical meteorological data. However, since meteorological forecasts and runoff observations are also available at a much finer than a daily time-resolution (e.g. 6 hourly), and many hydrological extreme events happens at a temporal scale of less than daily, it is important to try to establish a historical dataset of meteorological input at a finer corresponding temporal resolution. We present a simple approach for the temporal disaggregation of the daily meteorological seNorge grids into 6-hour values by consulting a HIRLAM hindcast grid data series with an hourly time resolution and a 10x10 km grid resolution. The temporal patterns of the hindcast series are used to disaggregate the daily interpolated observations from the seNorge grids. In this way, we produce a historical grid dataset from 1958-2010 with 6-hourly temperature and precipitation for entire Norway on a 1x1 km grid resolution. For validation and to see if additional information is gained, the disaggregated data is compared with observed values from selected meteorological stations. In addition, the disaggregated data is evaluated against daily data, simply split into four fractions. The validation results indicate that additional information is indeed gained and point out the benefit of disaggregated data compared to daily data split into four. With regard to temperature, the disaggregated values show very low deviations (MAE, RMSE), and are highly correlated with observed values. Regarding precipitation, the disaggregated data shows cumulative

  8. Nowcasting daily minimum air and grass temperature.

    PubMed

    Savage, M J

    2016-02-01

    Site-specific and accurate prediction of daily minimum air and grass temperatures, made available online several hours before their occurrence, would be of significant benefit to several economic sectors and for planning human activities. Site-specific and reasonably accurate nowcasts of daily minimum temperature several hours before its occurrence, using measured sub-hourly temperatures hours earlier in the morning as model inputs, was investigated. Various temperature models were tested for their ability to accurately nowcast daily minimum temperatures 2 or 4 h before sunrise. Temperature datasets used for the model nowcasts included sub-hourly grass and grass-surface (infrared) temperatures from one location in South Africa and air temperature from four subtropical sites varying in altitude (USA and South Africa) and from one site in central sub-Saharan Africa. Nowcast models used employed either exponential or square root functions to describe the rate of nighttime temperature decrease but inverted so as to determine the minimum temperature. The models were also applied in near real-time using an open web-based system to display the nowcasts. Extrapolation algorithms for the site-specific nowcasts were also implemented in a datalogger in an innovative and mathematically consistent manner. Comparison of model 1 (exponential) nowcasts vs measured daily minima air temperatures yielded root mean square errors (RMSEs) <1 °C for the 2-h ahead nowcasts. Model 2 (also exponential), for which a constant model coefficient (b = 2.2) was used, was usually slightly less accurate but still with RMSEs <1 °C. Use of model 3 (square root) yielded increased RMSEs for the 2-h ahead comparisons between nowcasted and measured daily minima air temperature, increasing to 1.4 °C for some sites. For all sites for all models, the comparisons for the 4-h ahead air temperature nowcasts generally yielded increased RMSEs, <2.1 °C. Comparisons for all model nowcasts of the daily grass

  9. Nowcasting daily minimum air and grass temperature

    NASA Astrophysics Data System (ADS)

    Savage, M. J.

    2016-02-01

    Site-specific and accurate prediction of daily minimum air and grass temperatures, made available online several hours before their occurrence, would be of significant benefit to several economic sectors and for planning human activities. Site-specific and reasonably accurate nowcasts of daily minimum temperature several hours before its occurrence, using measured sub-hourly temperatures hours earlier in the morning as model inputs, was investigated. Various temperature models were tested for their ability to accurately nowcast daily minimum temperatures 2 or 4 h before sunrise. Temperature datasets used for the model nowcasts included sub-hourly grass and grass-surface (infrared) temperatures from one location in South Africa and air temperature from four subtropical sites varying in altitude (USA and South Africa) and from one site in central sub-Saharan Africa. Nowcast models used employed either exponential or square root functions to describe the rate of nighttime temperature decrease but inverted so as to determine the minimum temperature. The models were also applied in near real-time using an open web-based system to display the nowcasts. Extrapolation algorithms for the site-specific nowcasts were also implemented in a datalogger in an innovative and mathematically consistent manner. Comparison of model 1 (exponential) nowcasts vs measured daily minima air temperatures yielded root mean square errors (RMSEs) <1 °C for the 2-h ahead nowcasts. Model 2 (also exponential), for which a constant model coefficient ( b = 2.2) was used, was usually slightly less accurate but still with RMSEs <1 °C. Use of model 3 (square root) yielded increased RMSEs for the 2-h ahead comparisons between nowcasted and measured daily minima air temperature, increasing to 1.4 °C for some sites. For all sites for all models, the comparisons for the 4-h ahead air temperature nowcasts generally yielded increased RMSEs, <2.1 °C. Comparisons for all model nowcasts of the daily grass

  10. REL3.0 LPLA DAILY NC

    Atmospheric Science Data Center

    2016-10-05

    ... 3.0 Langley Parameterized Longwave Model daily Data in 1x1 Degree NetCDF Format News:  LPLA Project ... Temporal Resolution:  3-hourly averaged by day File Format:  NETCDF Tools:  Search and ...

  11. A model to approximate lake temperature from gridded daily air temperature records and its application in risk assessment for the establishment of fish diseases in the UK.

    PubMed

    Thrush, M A; Peeler, E J

    2013-10-01

    Ambient water temperature is a key factor controlling the distribution and impact of disease in fish populations, and optimum temperature ranges have been characterised for the establishment of a number important aquatic diseases exotic to the UK. This study presents a simple regression method to approximate daily average surface water temperature in lakes of 0.5-15 ha in size across the UK using 5 km(2) gridded daily average air temperatures provided by the UK Meteorological Office. A Geographic information system (GIS) is used to present thematic maps of relative risk scores established for each grid cell based on the mean number of days per year that water temperature satisfied optimal criteria for the establishment of two economically important pathogens of cyprinid fish (koi herpesvirus (KHV) and spring viraemia of carp virus (SVCV)) and the distribution and density of fish populations susceptible to these viruses. High-density susceptible populations broadly overlap the areas where the temperature profiles are optimal for KHV (central and south-east England); however, few fish populations occur in areas where temperature profiles are most likely to result in the establishment of spring viremia of carp (SVC) (namely northern England and Scotland). The highest grid-cell risk scores for KHV and SVC were 7 and 6, respectively, out of a maximum score of 14. The proportion of grid cells containing susceptible populations with risk scores of 5 or more was 37% and 5% for KHV and SVC, respectively. This work demonstrates a risk-based approach to inform surveillance for exotic pathogens in aquatic animal health management, allowing efficient use of resources directed towards higher risk animals and geographic areas for early disease detection. The methodology could be used to examine the change in distribution of high-risk areas for both exotic and endemic fish diseases under different climate change scenarios.

  12. Allosteric Learning Model in English Lesson: Teachers' Views, the Instructions of Curriculum and Course Book, a Sample of Daily Lesson Plan

    ERIC Educational Resources Information Center

    Berkant, Hasan Güner; Baysal, Seda

    2017-01-01

    The changes which occur during the learning process have been explained by many teaching-learning models and theories. One of these models is allosteric learning model (ALM) which was developed by André Giordan in 1989. This model was derived from a biological metaphor related to proteins. The interaction between individual and environment in a…

  13. Daily Inter-Annual Simulations of SST and MLD using Atmospherically Forced OGCMs: Model Evaluation in Comparison to Buoy Time Series

    DTIC Science & Technology

    2008-01-30

    verification procedure for analyzing embedded in the dynamical model (Wallcraft et al., the model output is specifically designed for application 2003; Kara...8217E to navy.mil/nmld/nmld.html. 77.21°W. All models have 6 dynamical layers plus the The net surface heat flux that has been absorbed (or mixed layer...unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT A systematic methodology for model-data comparisons of sea surface temperature (SST) and mixed layer

  14. The patient with daily headaches.

    PubMed

    Maizels, Morris

    2004-12-15

    The term "chronic daily headache" (CDH) describes a variety of headache types, of which chronic migraine is the most common. Daily headaches often are disabling and may be challenging to diagnose and treat. Medication overuse, or drug rebound headache, is the most treatable cause of refractory daily headache. A pathologic underlying cause should be considered in patients with recent-onset daily headache, a change from a previous headache pattern, or associated neurologic or systemic symptoms. Treatment of CDH focuses on reduction of headache triggers and use of preventive medication, most commonly anti-depressants, antiepileptic drugs, and beta blockers. Medication overuse must be treated with discontinuation of symptomatic medicines, a transitional therapy, and long-term prophylaxis. Anxiety and depression are common in patients with CDH and should be identified and treated. Although the condition is challenging, appropriate treatment of patients with CDH can bring about significant improvement in the patient's quality-of-life.

  15. Daily exposure to summer temperatures affects the motile subpopulation structure of epididymal sperm cells but not male fertility in an in vivo rabbit model.

    PubMed

    Maya-Soriano, M J; Taberner, E; Sabés-Alsina, M; Ramon, J; Rafel, O; Tusell, L; Piles, M; López-Béjar, M

    2015-08-01

    High temperatures have negative effects on sperm quality leading to temporary or permanent sterility. The aim of the study was to assess the effect of long exposure to summer circadian heat stress cycles on sperm parameters and the motile subpopulation structure of epididymal sperm cells from rabbit bucks. Twelve White New Zealand rabbit bucks were exposed to a daily constant temperature of the thermoneutral zone (from 18 °C to 22 °C; control group) or exposed to a summer circadian heat stress cycles (30 °C, 3 h/day; heat stress group). Spermatozoa were flushed from the epididymis and assessed for sperm quality parameters at recovery. Sperm total motility and progressivity were negatively affected by high temperatures (P < 0.05), as were also specific motility parameters (curvilinear velocity, linear velocity, mean velocity, straightness coefficient, linearity coefficient, wobble coefficient, and frequency of head displacement; P < 0.05, but not the mean amplitude of lateral head displacement). Heat stress significantly increased the percentage of less-motile sperm subpopulations, although the percentage of the high-motile subpopulation was maintained, which is consistent with the fact that no effect was detected on fertility rates. However, prolificacy was reduced in females submitted to heat stress when inseminated by control bucks. In conclusion, our results suggest that environmental high temperatures are linked to changes in the proportion of motile sperm subpopulations of the epididymis, although fertility is still preserved despite the detrimental effects of heat stress. On the other hand, prolificacy seems to be affected by the negative effects of high temperatures, especially by altering female reproduction.

  16. Modelling in-stream temperature and dissolved oxygen at sub-daily time steps: an application to the River Kennet, UK.

    PubMed

    Williams, Richard J; Boorman, David B

    2012-04-15

    The River Kennet in southern England shows a clear diurnal signal in both water temperature and dissolved oxygen concentrations through the summer months. The water quality model QUESTOR was applied in a stepwise manner (adding modelled processes or additional data) to simulate the flow, water temperature and dissolved oxygen concentrations along a 14 km reach. The aim of the stepwise model building was to find the simplest process-based model which simulated the observed behaviour accurately. The upstream boundary used was a diurnal signal of hourly measurements of water temperature and dissolved oxygen. In the initial simulations, the amplitude of the signal quickly reduced to zero as it was routed through the model; a behaviour not seen in the observed data. In order to keep the correct timing and amplitude of water temperature a heating term had to be introduced into the model. For dissolved oxygen, primary production from macrophytes was introduced to better simulate the oxygen pattern. Following the modifications an excellent simulation of both water temperature and dissolved oxygen was possible at an hourly resolution. It is interesting to note that it was not necessary to include nutrient limitation to the primary production model. The resulting model is not sufficiently proven to support river management but suggests that the approach has some validity and merits further development.

  17. Modeling daily reference ET in the karst area of northwest Guangxi (China) using gene expression programming (GEP) and artificial neural network (ANN)

    NASA Astrophysics Data System (ADS)

    Wang, Sheng; Fu, Zhi-yong; Chen, Hong-song; Nie, Yun-peng; Wang, Ke-lin

    2016-11-01

    Nonlinear complexity is a characteristic of hydrologic processes. Using fewer model parameters is recommended to reduce error. This study investigates, and compares, the ability of gene expression programming (GEP) and artificial neural network (ANN) techniques in modeling ET0 by using fewer meteorological parameters in the karst area of northwest Guangxi province, China. Over a 5-year period (2008-2012), meteorological data consisting of maximum and minimum air temperature, relative humidity, wind speed, and sunshine duration were collected from four weather stations: BaiSe, DuAn, HeChi, and RongAn. The ET0 calculated by the FAO-56 PM equation was used as a reference to evaluate results for GEP, ANN, and Hargreaves models. The coefficient of determination ( R 2) and the root mean square error (RMSE) were used as statistical indicators. Evaluations revealed that GEP, and ANN, can be used to successfully model ET0. In most cases, when using the same input variables, ANN models were superior to GEP. We then established ET0 equations with fewer parameters under various conditions. GEP can produce simple explicit mathematical formulations which are easier to use than the ANN models.

  18. Daily Interpersonal and Affective Dynamics in Personality Disorder

    PubMed Central

    Wright, Aidan G.C.; Hopwood, Christopher J.; Simms, Leonard J.

    2015-01-01

    In this naturalistic study we adopt the lens of interpersonal theory to examine between-and within-person differences in dynamic processes of daily affect and interpersonal behaviors among individuals (N = 101) previously diagnosed with personality disorders who completed daily diaries over the course of 100 days. Dispositional ratings of interpersonal problems and measures of daily stress were used as predictors of daily shifts in interpersonal behavior and affect in multilevel models. Results indicate that ~40%–50% of the variance in interpersonal behavior and affect is due to daily fluctuations, which are modestly related to dispositional measures of interpersonal problems but strongly related to daily stress. The findings support conceptions of personality disorders as a dynamic form of psychopathology involving the individuals interacting with and regulating in response to the contextual features of their environment. PMID:26200849

  19. An empirical model to estimate daily forest fire smoke exposure over a large geographic area using air quality, meteorological, and remote sensing data.

    PubMed

    Yao, Jiayun; Henderson, Sarah B

    2014-01-01

    Exposure to forest fire smoke (FFS) is associated with a range of adverse health effects. The British Columbia Asthma Medication Surveillance (BCAMS) product was developed to detect potential impacts from FFS in British Columbia (BC), Canada. However, it has been a challenge to estimate FFS exposure with sufficient spatial coverage for the provincial population. We constructed an empirical model to estimate FFS-related fine particulate matter (PM2.5) for all populated areas of BC using data from the most extreme FFS days in 2003 through 2012. The input data included PM2.5 measurements on the previous day, remotely sensed aerosols, remotely sensed fires, hand-drawn tracings of smoke plumes from satellite images, fire danger ratings, and the atmospheric venting index. The final model explained 71% of the variance in PM2.5 observations. Model performance was tested in days with high, moderate, and low levels of FFS, resulting in correlations from 0.57 to 0.83. We also developed a method to assign the model estimates to geographical local health areas for use in BCAMS. The simplicity of the model allows easy application in time-constrained public health surveillance, and its sufficient spatial coverage suggests utility as an exposure assessment tool for epidemiologic studies on FFS exposure.

  20. The Daily Curriculum Guide, Year II, Weeks 1-10.

    ERIC Educational Resources Information Center

    Dissemination and Assessment Center for Bilingual Education, Austin, TX.

    Spanning two years, the program set forth in the Daily Curriculum Guide for preschool Spanish-speaking children is essentially a language maintenance model in which Spanish is used as a means to develop basic concepts, skills and attitudes. This guide gives daily lesson plans for the first ten weeks of the second year. Each lesson, written in…

  1. Calibration and validation of the SWAT model for predicting daily ET for irrigated crops in the Texas High Plains using lysimetric data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil and Water Assessment Tool (SWAT) model has been used to assess the impacts of alternative agricultural management practices on non-point source pollution in watersheds of various topography and scale throughout the world. Water balance is the driving force behind all processes of SWAT, as i...

  2. Calibration and validation of the SWAT model for predicting daily ET over irrigated crops in the Texas High Plains using lysimetric data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil Water Assessment Tool (SWAT) is a widely used watershed model for simulating stream flow, overland flow, sediment, pesticide, and bacterial loading in response to management practices. All SWAT processes are directly dependent upon the accurate representation of hydrology. Evapotranspiratio...

  3. Improving ozone modeling in complex terrain at a fine grid resolution - Part II: Influence of schemes in MM5 on daily maximum 8-h ozone concentrations and RRFs (Relative Reduction Factors) for SIPs in the non-attainment areas

    NASA Astrophysics Data System (ADS)

    Kim, Yunhee; Fu, Joshua S.; Miller, Terry L.

    2010-06-01

    Part II presents a comprehensive evaluation of CMAQ for August of 2002 on twenty-one sensitivity simulations (detailed in Part I) in MM5 to investigate the model performance for O 3 SIPs (State Implementation Plans) in the complex terrain. CMAQ performance was quite consistent with the results of MM5, meaning that accurate meteorological fields predicted in MM5 as an input resulted in good model performance of CMAQ. In this study, PBL scheme plays a more important role than its land surface models (LSMs) for the model performance of CMAQ. Our results have shown that the outputs of CMAQ on eighteen sensitivity simulations using two different nudging coefficients for winds (2.5 and 4.5 × 10 -4 s -1, respectively) tend to under predict daily maximum 8-h ozone concentrations at valley areas except the TKE PBL sensitivity simulations (ETA M-Y PBL scheme with Noah LSMs and 5-layer soil model and Gayno-Seaman PBL) using 6.0 × 10 -4 s -1 with positive MB (Mean Bias). At mountain areas, none of the sensitivity simulations has presented over predictions for 8-h O 3, due to relatively poor meteorological model performance. When comparing 12-km and 4-km grid resolutions for the PX simulation in CMAQ statistics analysis, the CMAQ results at 12-km grid resolution consistently show under predictions of 8-h O 3 at both of valley and mountain areas and particularly, it shows relatively poor model performance with a 15.1% of NMB (Normalized Mean Bias). Based on our sensitivity simulations, the TKE PBL sensitivity simulations using a maximum value (6 × 10 -4) among other sensitivity simulations yielded better model performance of CMAQ at all areas in the complex terrain. As a result, the sensitivity of RRFs to the PBL scheme may be considerably significant with about 1-3 ppb in difference in determining whether the attainment test is passed or failed. Furthermore, we found that the result of CMAQ model performance depending on meteorological variations is affected on estimating

  4. Daily practices, consumption and citizenship.

    PubMed

    Mazzarino, Jane M; Morigi, Valdir J; Kaufmann, Cristine; Farias, Alessandra M B; Fernandes, Diefersom A

    2011-12-01

    This paper promotes a reflection on the relationship between daily practices and consumption. Understanding how conflicts, resistance and consensus are generated from daily consumption practices opens up possibilities for reflecting on the construction of sustainability in the context of diversity, one of the landmarks of the globalized world. Within this socio-cultural context, the central issue is: can consumption generate citizenship practices? The concepts of subject and agent help one think about collective action and subjectivation processes and their interferences on the collective consuming behavior. Based on empirical data from a research carried out in the municipality of Estrela in 2007, in the Taquari Valley - Rio Grande do Sul (Southern Brazil) on local reality consumption practices, it was possible to conclude that various reasoning mechanisms and values underlie the daily consumption practices. Citizenship construction, based on consumption practices, depends on the subject's reflection capacity on his/her daily practices or on what goes through the circulation of environmental information based on sociability spaces.

  5. Tractor Operation and Daily Care.

    ERIC Educational Resources Information Center

    Fore, J. M.; And Others

    Written for the tractor operator, the manual describes, with the aid of colored illustrations and diagrams, the tasks involved in the proper operation and daily maintenance of tractors. It offers explanations for the desirability of the various servicing and adjustment operations, as well as guidelines for tractor operation and safety. The…

  6. Digital Daily Cycles of Individuals

    NASA Astrophysics Data System (ADS)

    Aledavood, Talayeh; Lehmann, Sune; Saramäki, Jari

    2015-10-01

    Humans, like almost all animals, are phase-locked to the diurnal cycle. Most of us sleep at night and are active through the day. Because we have evolved to function with this cycle, the circadian rhythm is deeply ingrained and even detectable at the biochemical level. However, within the broader day-night pattern, there are individual differences: e.g., some of us are intrinsically morning-active, while others prefer evenings. In this article, we look at digital daily cycles: circadian patterns of activity viewed through the lens of auto-recorded data of communication and online activity. We begin at the aggregate level, discuss earlier results, and illustrate differences between population-level daily rhythms in different media. Then we move on to the individual level, and show that there is a strong individual-level variation beyond averages: individuals typically have their distinctive daily pattern that persists in time. We conclude by discussing the driving forces behind these signature daily patterns, from personal traits (morningness/eveningness) to variation in activity level and external constraints, and outline possibilities for future research.

  7. Southern California Daily Energy Report

    EIA Publications

    2016-01-01

    EIA has updated its Southern California Daily Energy Report to provide additional information on key energy market indicators for the winter season. The dashboard includes information that EIA regularly compiles about energy operations and the management of natural gas and electricity systems in Southern California in the aftermath of a leak at the Aliso Canyon natural gas storage facility outside of Los Angeles

  8. Teaching Activities of Daily Living.

    ERIC Educational Resources Information Center

    McCormack, James E.

    Provided are strategies for teaching activities of daily living (ADL), which include dressing, eating, grooming, toileting, and basic homemakine, to severely retarded students. Reviewed are the steps necessary to teach ADL skills: ADL assessment, identification of appropriate strategies and tactics, and task analysis. Explained are four common…

  9. The probability distribution of intense daily precipitation

    NASA Astrophysics Data System (ADS)

    Cavanaugh, Nicholas R.; Gershunov, Alexander; Panorska, Anna K.; Kozubowski, Tomasz J.

    2015-03-01

    The probability tail structure of over 22,000 weather stations globally is examined in order to identify the physically and mathematically consistent distribution type for modeling the probability of intense daily precipitation and extremes. Results indicate that when aggregating data annually, most locations are to be considered heavy tailed with statistical significance. When aggregating data by season, it becomes evident that the thickness of the probability tail is related to the variability in precipitation causing events and thus that the fundamental cause of precipitation volatility is weather diversity. These results have both theoretical and practical implications for the modeling of high-frequency climate variability worldwide.

  10. Effects of climate and lifeform on dry matter yield (epsilon) from simulations using BIOME BGC. [ecosystem process model for vegetation biomass production using daily absorbed photosynthetically active radiation

    NASA Technical Reports Server (NTRS)

    Hunt, E. R., Jr.; Running, Steven W.

    1992-01-01

    An ecosystem process simulation model, BIOME-BGC, is used in a sensitivity analysis to determine the factors that may cause the dry matter yield (epsilon) and annual net primary production to vary for different ecosystems. At continental scales, epsilon is strongly correlated with annual precipitation. At a single location, year-to-year variation in net primary production (NPP) and epsilon is correlated with either annual precipitation or minimum air temperatures. Simulations indicate that forests have lower epsilon than grasslands. The most sensitive parameter affecting forest epsilon is the total amount of living woody biomass, which affects NPP by increasing carbon loss by maintenance respiration. A global map of woody biomass should significantly improve estimates of global NPP using remote sensing.

  11. Daily Water Use in Nine Cities

    NASA Astrophysics Data System (ADS)

    Maidment, David R.; Miaou, Shaw-Pin

    1986-06-01

    Transfer functions are used to model the short-term response of daily municipal water use to rainfall and air temperature variations. Daily water use data from nine cities are studied, three cities each from Florida, Pennsylvania, and Texas. The dynamic response of water use to rainfall and air temperature is similar across the cities within each State; in addition the responses of the Texas and Florida cities are very similar to one another while the response of the Pennsylvania cities is more sensitive to air temperature and less to rainfall. There is little impact of city size on the response functions. The response of water use to rainfall depends first on the occurrence of rainfall and second on its magnitude. The occurrence of a rainfall more than 0.05 in./day (0.13 cm/day) causes a drop in the seasonal component of water use one day later that averages 38% for the Texas cities, 42% for the Florida cities, and 7% for the Pennsylvania cities. In Austin, Texas, a spatially averaged rainfall series shows a clearer relationship with water use than does rainfall data from a single gage. There is a nonlinear response of water use to air temperature changes with no response for daily maximum air temperatures between 40° and 70°F (4-21°C) an increase in water use with air temperature beyond 70°F; above 85°-90°F (29°-32°C) water use increases 3-5 times more per degree than below that limit in Texas and Florida. The model resulting from these studies can be used for daily water use forecasting and water conservation analysis.

  12. The Effect of Personality on Daily Life Emotional Processes

    PubMed Central

    Komulainen, Emma; Meskanen, Katarina; Lipsanen, Jari; Lahti, Jari Marko; Jylhä, Pekka; Melartin, Tarja; Wichers, Marieke; Isometsä, Erkki; Ekelund, Jesper

    2014-01-01

    Personality features are associated with individual differences in daily emotional life, such as negative and positive affectivity, affect variability and affect reactivity. The existing literature is somewhat mixed and inconclusive about the nature of these associations. The aim of this study was to shed light on what personality features represent in daily life by investigating the effect of the Five Factor traits on different daily emotional processes using an ecologically valid method. The Experience Sampling Method was used to collect repeated reports of daily affect and experiences from 104 healthy university students during one week of their normal lives. Personality traits of the Five Factor model were assessed using NEO Five Factor Inventory. Hierarchical linear modeling was used to analyze the effect of the personality traits on daily emotional processes. Neuroticism predicted higher negative and lower positive affect, higher affect variability, more negative subjective evaluations of daily incidents, and higher reactivity to stressors. Conscientiousness, by contrast, predicted lower average level, variability, and reactivity of negative affect. Agreeableness was associated with higher positive and lower negative affect, lower variability of sadness, and more positive subjective evaluations of daily incidents. Extraversion predicted higher positive affect and more positive subjective evaluations of daily activities. Openness had no effect on average level of affect, but predicted higher reactivity to daily stressors. The results show that the personality features independently predict different aspects of daily emotional processes. Neuroticism was associated with all of the processes. Identifying these processes can help us to better understand individual differences in daily emotional life. PMID:25343494

  13. Long-term daily vibration exposure alters current perception threshold (CPT) sensitivity and myelinated axons in a rat-tail model of vibration-induced injury.

    PubMed

    Krajnak, Kristine; Raju, Sandya G; Miller, G Roger; Johnson, Claud; Waugh, Stacey; Kashon, Michael L; Riley, Danny A

    2016-01-01

    Repeated exposure to hand-transmitted vibration through the use of powered hand tools may result in pain and progressive reductions in tactile sensitivity. The goal of the present study was to use an established animal model of vibration-induced injury to characterize changes in sensory nerve function and cellular mechanisms associated with these alterations. Sensory nerve function was assessed weekly using the current perception threshold test and tail-flick analgesia test in male Sprague-Dawley rats exposed to 28 d of tail vibration. After 28 d of exposure, Aβ fiber sensitivity was reduced. This reduction in sensitivity was partly attributed to structural disruption of myelin. In addition, the decrease in sensitivity was also associated with a reduction in myelin basic protein and 2',3'- cyclic nucleotide phosphodiasterase (CNPase) staining in tail nerves, and an increase in circulating calcitonin gene-related peptide (CGRP) concentrations. Changes in Aβ fiber sensitivity and CGRP concentrations may serve as early markers of vibration-induced injury in peripheral nerves. It is conceivable that these markers may be utilized to monitor sensorineural alterations in workers exposed to vibration to potentially prevent additional injury.

  14. Analysis of the dynamics of adaptation to transgenic corn and crop rotation by western corn rootworm (Coleoptera: Chrysomelidae) using a daily time-step model.

    PubMed

    Crowder, D W; Onstad, D W; Cray, M E; Pierce, C M F; Hager, A G; Ratcliffe, S T; Steffey, K L

    2005-04-01

    Western corn rootworm, Diabrotica virgifera virgifera LeConte, has overcome crop rotation in several areas of the north central United States. The effectiveness of crop rotation for management of corn rootworm has begun to fail in many areas of the midwestern United States, thus new management strategies need to be developed to control rotation-resistant populations. Transgenic corn, Zea mays L., effective against western corn rootworm, may be the most effective new technology for control of this pest in areas with or without populations adapted to crop rotation. We expanded a simulation model of the population dynamics and genetics of the western corn rootworm for a landscape of corn; soybean, Glycine max (L.); and other crops to study the simultaneous development of resistance to both crop rotation and transgenic corn. Results indicate that planting transgenic corn to first-year cornfields is a robust strategy to prevent resistance to both crop rotation and transgenic corn in areas where rotation-resistant populations are currently a problem or may be a problem in the future. In these areas, planting transgenic corn only in continuous cornfields is not an effective strategy to prevent resistance to either trait. In areas without rotation-resistant populations, gene expression of the allele for resistance to transgenic corn, R, is the most important factor affecting the evolution of resistance. If R is recessive, resistance can be delayed longer than 15 yr. If R is dominant, resistance may be difficult to prevent. In a sensitivity analysis, results indicate that density dependence, rotational level in the landscape, and initial allele frequency are the three most important factors affecting the results.

  15. Short-term effects of daily air pollution on mortality

    NASA Astrophysics Data System (ADS)

    Wan Mahiyuddin, Wan Rozita; Sahani, Mazrura; Aripin, Rasimah; Latif, Mohd Talib; Thach, Thuan-Quoc; Wong, Chit-Ming

    2013-02-01

    The daily variations of air pollutants in the Klang Valley, Malaysia, which includes Kuala Lumpur were investigated for its association with mortality counts using time series analysis. This study located in the tropic with much less seasonal variation than typically seen in more temperate climates. Data on daily mortality for the Klang Valley (2000-2006), daily mean concentrations of air pollutants of PM10, SO2, CO, NO2, O3, daily maximum O3 and meteorological conditions were obtained from Malaysian Department of Environment. We examined the association between pollutants and daily mortality using Poisson regression while controlling for time trends and meteorological factors. Effects of the pollutants (Relative Risk, RR) on current-day (lag 0) mortality to seven previous days (lag 7) and the effects of the pollutants from the first two days (lag 01) to the first eight days (lag 07) were determined. We found significant associations in the single-pollutant model for PM10 and the daily mean O3 with natural mortality. For the daily mean O3, the highest association was at lag 05 (RR = 1.0215, 95% CI = 1.0013-1.0202). CO was found not significantly associated with natural mortality, however the RR's of CO were found to be consistently higher than PM10. In spite of significant results of PM10, the magnitude of RR's of PM10 was not important for natural mortality in comparison with either daily mean O3 or CO. There is an association between daily mean O3 and natural mortality in a two-pollutants model after adjusting for PM10. Most pollutants except SO2, were significantly associated with respiratory mortality in a single pollutant model. Daily mean O3 is also important for respiratory mortality, with over 10% of mortality associated with every IQR increased. These findings are noteworthy because seasonal confounding is unlikely in this relatively stable climate, by contrast with more temperate regions.

  16. Observability of market daily volatility

    NASA Astrophysics Data System (ADS)

    Petroni, Filippo; Serva, Maurizio

    2016-02-01

    We study the price dynamics of 65 stocks from the Dow Jones Composite Average from 1973 to 2014. We show that it is possible to define a Daily Market Volatility σ(t) which is directly observable from data. This quantity is usually indirectly defined by r(t) = σ(t) ω(t) where the r(t) are the daily returns of the market index and the ω(t) are i.i.d. random variables with vanishing average and unitary variance. The relation r(t) = σ(t) ω(t) alone is unable to give an operative definition of the index volatility, which remains unobservable. On the contrary, we show that using the whole information available in the market, the index volatility can be operatively defined and detected.

  17. Physiological responses to daily light exposure

    NASA Astrophysics Data System (ADS)

    Yang, Yefeng; Yu, Yonghua; Yang, Bo; Zhou, Hong; Pan, Jinming

    2016-04-01

    Long daylength artificial light exposure associates with disorders, and a potential physiological mechanism has been proposed. However, previous studies have examined no more than three artificial light treatments and limited metabolic parameters, which have been insufficient to demonstrate mechanical responses. Here, comprehensive physiological response curves were established and the physiological mechanism was strengthened. Chicks were illuminated for 12, 14, 16, 18, 20, or 22 h periods each day. A quadratic relationship between abdominal adipose weight (AAW) and light period suggested that long-term or short-term light exposure could decrease the amount of AAW. Quantitative relationships between physiological parameters and daily light period were also established in this study. The relationships between triglycerides (TG), cholesterol (TC), glucose (GLU), phosphorus (P) levels and daily light period could be described by quadratic regression models. TG levels, AAW, and BW positively correlated with each other, suggesting long-term light exposure significantly increased AAW by increasing TG thus resulting in greater BW. A positive correlation between blood triiodothyronine (T3) levels and BW suggested that daily long-term light exposure increased BW by thyroid hormone secretion. Though the molecular pathway remains unknown, these results suggest a comprehensive physiological mechanism through which light exposure affects growth.

  18. The Probability Distribution of Daily Streamflow

    NASA Astrophysics Data System (ADS)

    Blum, A.; Vogel, R. M.

    2015-12-01

    Flow duration curves (FDCs) are a graphical illustration of the cumulative distribution of streamflow. Daily streamflows often range over many orders of magnitude, making it extremely challenging to find a probability distribution function (pdf) which can mimic the steady state or period of record FDC (POR-FDC). Median annual FDCs (MA-FDCs) describe the pdf of daily streamflow in a typical year. For POR- and MA-FDCs, Lmoment diagrams, visual assessments of FDCs and Quantile-Quantile probability plot correlation coefficients are used to evaluate goodness of fit (GOF) of candidate probability distributions. FDCs reveal that both four-parameter kappa (KAP) and three-parameter generalized Pareto (GP3) models result in very high GOF for the MA-FDC and a relatively lower GOF for POR-FDCs at over 500 rivers across the coterminous U.S. Physical basin characteristics, such as baseflow index as well as hydroclimatic indices such as the aridity index and the runoff ratio are found to be correlated with one of the shape parameters (kappa) of the KAP and GP3 pdfs. Our work also reveals several important areas for future research including improved parameter estimators for the KAP pdf, as well as increasing our understanding of the conditions which give rise to improved GOF of analytical pdfs to large samples of daily streamflows.

  19. Progress towards daily "swath" solutions from GRACE

    NASA Astrophysics Data System (ADS)

    Save, H.; Bettadpur, S. V.; Sakumura, C.

    2015-12-01

    The GRACE mission has provided invaluable and the only data of its kind that measures the total water column in the Earth System over the past 13 years. The GRACE solutions available from the project have been monthly average solutions. There have been attempts by several groups to produce shorter time-window solutions with different techniques. There is also an experimental quick-look GRACE solution available from CSR that implements a sliding window approach while applying variable daily data weights. All of these GRACE solutions require special handling for data assimilation. This study explores the possibility of generating a true daily GRACE solution by computing a daily "swath" total water storage (TWS) estimate from GRACE using the Tikhonov regularization and high resolution monthly mascon estimation implemented at CSR. This paper discusses the techniques for computing such a solution and discusses the error and uncertainty characterization. We perform comparisons with official RL05 GRACE solutions and with alternate mascon solutions from CSR to understand the impact on the science results. We evaluate these solutions with emphasis on the temporal characteristics of the signal content and validate them against multiple models and in-situ data sets.

  20. Physiological responses to daily light exposure

    PubMed Central

    Yang, Yefeng; Yu, Yonghua; Yang, Bo; Zhou, Hong; Pan, Jinming

    2016-01-01

    Long daylength artificial light exposure associates with disorders, and a potential physiological mechanism has been proposed. However, previous studies have examined no more than three artificial light treatments and limited metabolic parameters, which have been insufficient to demonstrate mechanical responses. Here, comprehensive physiological response curves were established and the physiological mechanism was strengthened. Chicks were illuminated for 12, 14, 16, 18, 20, or 22 h periods each day. A quadratic relationship between abdominal adipose weight (AAW) and light period suggested that long-term or short-term light exposure could decrease the amount of AAW. Quantitative relationships between physiological parameters and daily light period were also established in this study. The relationships between triglycerides (TG), cholesterol (TC), glucose (GLU), phosphorus (P) levels and daily light period could be described by quadratic regression models. TG levels, AAW, and BW positively correlated with each other, suggesting long-term light exposure significantly increased AAW by increasing TG thus resulting in greater BW. A positive correlation between blood triiodothyronine (T3) levels and BW suggested that daily long-term light exposure increased BW by thyroid hormone secretion. Though the molecular pathway remains unknown, these results suggest a comprehensive physiological mechanism through which light exposure affects growth. PMID:27098210

  1. Single daily dosing of aminoglycosides.

    PubMed

    Preston, S L; Briceland, L L

    1995-01-01

    To evaluate the rationale behind dosing aminoglycosides as a single daily dose versus traditional dosing approaches, we conducted a MEDLINE search to identify all pertinent articles, and also reviewed the references of all articles. Single daily dosing of aminoglycosides is not a new concept, having been examined since 1974. The advantages of this regimen include optimum concentration-dependent bactericidal activity, longer dosing intervals due to the postantibiotic effect (PAE), and prevention of bacterial adaptive resistance. Because of longer dosing intervals, toxicity may also be delayed or reduced. Costs may be reduced due to decreased monitoring and administration. Clinically, the regimen has been implemented in various patient populations with reported success. Questions remain, however, about optimum dose, peak and trough serum concentrations, and dose adjustment in patients with renal impairment or neutropenia. More clinical experience with this method in large numbers of patients has to be published. Pharmacists can be instrumental in monitoring patients receiving once-daily therapy and by educating health care professionals as to the rationale behind the therapy.

  2. 50 CFR 20.24 - Daily limit.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 50 Wildlife and Fisheries 6 2010-10-01 2010-10-01 false Daily limit. 20.24 Section 20.24 Wildlife... (CONTINUED) MIGRATORY BIRD HUNTING Taking § 20.24 Daily limit. No person shall take in any 1 calendar day, more than the daily bag limit or aggregate daily bag limit, whichever applies....

  3. Analysis of daily latitude variations

    NASA Technical Reports Server (NTRS)

    Graber, M. A.

    1978-01-01

    The daily latitude measurements of the International polar motion service are analyzed. The results indicate that the annual polar oscillation is probably due to local phenomena with amplitudes varying from 0.05 to 0.15 min. Within the resolution of the residuals (150 cm), there is no indication of the sharp changes which might be associated with earthquake effects. Then, applying Schuster's test to a periodogram of the residuals indicates that there are probably several processes occurring at amplitudes between 0.007 and 0.03 min whose solution awaits a more precise measurement technique.

  4. Managing Hypertriglyceridemia in Daily Practice.

    PubMed

    Pramono, Laurentius A; Harbuwono, Dante S

    2015-07-01

    Hypertriglyceridemia is a form of dyslipidemia, which usually occurs in combination with hypercholesterolemia, high-LDL or low-HDL cholesterol level. Most studies suggest that hypertriglyceridemia is associated with many metabolic disorders such as metabolic syndrome, diabetes, obesity, and also cardio-cerebrovascular diseases. Treatment of hypertriglyceridemia is often not comprehensively addressed by many physicians, who usually only include prescribing drugs without encouraging patients to perform physical activity, to take a true healthy diet for dyslipidemia and to stop smoking. This review article discusses evaluation, diagnosis and a comprehensive, yet simple management of hypertriglyceridemia, which can be easily applied in daily clinical practice.

  5. Daily Job Demands and Employee Work Engagement: The Role of Daily Transformational Leadership Behavior.

    PubMed

    Breevaart, Kimberley; Bakker, Arnold B

    2017-03-30

    Using job demands-resources (JD-R) theory, the present study integrates the challenge stressor-hindrance stressor framework and leadership theory to investigate the relationship between daily transformational leadership behavior and employee work engagement. We hypothesized that daily transformational leadership behavior (a) sustains employee work engagement on days characterized by high challenge job demands, and (b) protects work engagement on days characterized by high hindrance job demands. Teachers filled out a short online questionnaire at the end of each workday during a 2-week period (N = 271 × 5.68 days = 1539). Results of latent moderated structural equation modeling showed that teachers' daily challenge demands (workload and cognitive demands) had a positive relationship with work engagement on the days transformational leadership was high (vs. low). In addition, teachers' daily hindrance demands (role-conflict, but not family to work conflict) had a negative relationship with work engagement on the days transformational leadership was low (vs. high). These findings show that the function of transformational leadership behavior changes from day to day, and depends on the type of job demand. We discuss the practical and theoretical implications of these findings. (PsycINFO Database Record

  6. Phosphorus balance with daily dialysis.

    PubMed

    Kooienga, Laura

    2007-01-01

    Hyperphosphatemia is an almost universal finding in patients with end-stage renal disease and is associated with increased all-cause mortality, cardiovascular mortality, and vascular calcification. These associations have raised the question of whether reducing phosphorus levels could result in improved survival. In light of the recent findings that increased per-session dialysis dose, as assessed by urea kinetics, did not result in improved survival, the definition of adequacy of dialysis should be re-evaluated and consideration given to alternative markers. Two alternatives to conventional thrice weekly dialysis (CHD) are nocturnal hemodialysis (NHD) and short daily hemodialysis (SDHD). The elimination kinetics of phosphorus as they relate to these alternative daily dialysis schedules and the clinical implications of overall phosphorus balance are discussed here. The total weekly phosphorus removal with NHD is more than twice that removed by CHD (4985 mg/week +/- 1827 mg vs. 2347 mg/week +/- 697 mg) and this is associated with a significantly lower average serum phosphorous (4.0 mg/dl vs. 6.5 mg/dl). In spite of the observed increase in protein and phosphorus intake seen in patients on SDHD, phosphate binder requirements and serum phosphorus levels are generally stable to decrease although this effect is strongly dependent on the frequency and overall treatment time.

  7. Daily cycles in coastal dunes

    USGS Publications Warehouse

    Hunter, R.E.; Richmond, B.M.

    1988-01-01

    Daily cycles of summer sea breezes produce distinctive cyclic foreset deposits in dune sands of the Texas and Oregon coasts. In both areas the winds are strong enough to transport sand only during part of the day, reach a peak during the afternoon, and vary little in direction during the period of sand transport. Cyclicity in the foreset deposits is made evident by variations in the type of sedimentary structure, the texture, and the heavy-mineral content of the sand. Some of the cyclic deposits are made up entirely of one basic type of structure, in which the character of the structure varies cyclically; for example, the angle of climb in a climbing-wind-ripple structure may vary cyclically. Other cyclic deposits are characterized by alternations of two or more structural types. Variations in the concentration of fine-grained heavy minerals, which account for the most striking cyclicity, arise mainly because of segregation on wind-rippled depositional surfaces: where the ripples climb at low angles, the coarsegrained light minerals, which accumulate preferentially on ripple crests, tend to be excluded from the local deposit. Daily cyclic deposits are thickest and best developed on small dunes and are least recognizable near the bases of large dunes. ?? 1988.

  8. Intent to Quit among Daily and Non-Daily College Student Smokers

    ERIC Educational Resources Information Center

    Pinsker, E. A.; Berg, C. J.; Nehl, E. J.; Prokhorov, A. V.; Buchanan, T. S.; Ahluwalia, J. S.

    2013-01-01

    Given the high prevalence of young adult smoking, we examined (i) psychosocial factors and substance use among college students representing five smoking patterns and histories [non-smokers, quitters, native non-daily smokers (i.e. never daily smokers), converted non-daily smokers (i.e. former daily smokers) and daily smokers] and (ii) smoking…

  9. A statistical analysis of the daily streamflow hydrograph

    NASA Astrophysics Data System (ADS)

    Kavvas, M. L.; Delleur, J. W.

    1984-03-01

    In this study a periodic statistical analysis of daily streamflow data in Indiana, U.S.A., was performed to gain some new insight into the stochastic structure which describes the daily streamflow process. This analysis was performed by the periodic mean and covariance functions of the daily streamflows, by the time and peak discharge -dependent recession limb of the daily streamflow hydrograph, by the time and discharge exceedance level (DEL) -dependent probability distribution of the hydrograph peak interarrival time, and by the time-dependent probability distribution of the time to peak discharge. Some new statistical estimators were developed and used in this study. In general features, this study has shown that: (a) the persistence properties of daily flows depend on the storage state of the basin at the specified time origin of the flow process; (b) the daily streamflow process is time irreversible; (c) the probability distribution of the daily hydrograph peak interarrival time depends both on the occurrence time of the peak from which the inter-arrival time originates and on the discharge exceedance level; and (d) if the daily streamflow process is modeled as the release from a linear watershed storage, this release should depend on the state of the storage and on the time of the release as the persistence properties and the recession limb decay rates were observed to change with the state of the watershed storage and time. Therefore, a time-varying reservoir system needs to be considered if the daily streamflow process is to be modeled as the release from a linear watershed storage.

  10. Contrails reduce daily temperature range.

    PubMed

    Travis, David J; Carleton, Andrew M; Lauritsen, Ryan G

    2002-08-08

    The potential of condensation trails (contrails) from jet aircraft to affect regional-scale surface temperatures has been debated for years, but was difficult to verify until an opportunity arose as a result of the three-day grounding of all commercial aircraft in the United States in the aftermath of the terrorist attacks on 11 September 2001. Here we show that there was an anomalous increase in the average diurnal temperature range (that is, the difference between the daytime maximum and night-time minimum temperatures) for the period 11-14 September 2001. Because persisting contrails can reduce the transfer of both incoming solar and outgoing infrared radiation and so reduce the daily temperature range, we attribute at least a portion of this anomaly to the absence of contrails over this period.

  11. Daily Medicine Record for Your Child

    MedlinePlus

    ... the-Counter Pain Relievers and Fever Reducers Daily Medicine Record for Your Child (English) Share Tweet Linkedin ... Age: ____ 2 years old___ Weight: ___ 30 pounds ___ Daily Medicine Record Child’s name: ___________________ Today’s date: _________________ Age: ____________ Weight: ________________ (pounds) ...

  12. Daily Social Exchanges and Affect in Middle and Later Adulthood: The Impact of Loneliness and Age

    ERIC Educational Resources Information Center

    Russell, Alissa; Bergeman, C. S.; Scott, Stacey B.

    2012-01-01

    Although daily social exchanges are important for well-being, it is unclear how different types of exchanges affect daily well-being, as well as which factors influence the way in which individuals react to their daily social encounters. The present study included a sample of 705 adults aged 31 to 91, and using Multilevel Modeling analyses…

  13. The Daily Practices of Successful Principals

    ERIC Educational Resources Information Center

    Brock, Barbara L.; Grady, Marilyn L.

    2011-01-01

    While many books outline the attributes of successful school leaders, few describe how those traits manifest in daily practice. "The Daily Practices of Successful Principals" goes beyond the outward picture of excellence and provides a compendium of daily practices used by successful principals in various settings. Written by former administrators…

  14. Spatial downscaling and mapping of daily precipitation and air temperature using daily station data and monthly mean maps

    NASA Astrophysics Data System (ADS)

    Flint, A. L.; Flint, L. E.; Stern, M. A.

    2013-12-01

    Accurate maps of daily weather variables are an essential component of hydrologic and ecologic modeling. Here we present a four-step method that uses daily station data and transient monthly maps of precipitation and air temperature. This method uses the monthly maps to help interpolate between stations for more accurate production of daily maps at any spatial resolution. The first step analyzes the quality of the each station's data using a discrepancy analysis that compares statistics derived from a statistical jack-knifing approach with a time-series evaluation of discrepancies generated for each station. Although several methods could be used for the second step of producing initial maps, such as kriging, splines, etc., we used a gradient plus inverse distance squared method that was developed to produce accurate climate maps for sparse data regions with widely separated and few climate stations, far fewer than would be needed for techniques such as kriging. The gradient plus inverse distance squared method uses local gradients in the climate parameters, easting, northing, and elevation, to adjust the inverse distance squared estimates for local gradients such as lapse rates, inversions, or rain shadows at scales of 10's of meters to kilometers. The third step is to downscale World Wide Web (web) based transient monthly data, such as Precipitation-Elevation Regression on Independent Slope Method (PRISM) for the US (4 km or 800 m maps) or Climate Research Unit (CRU 3.1) data sets (40 km for global applications) to the scale of the daily data's digital elevation model. In the final step the downscaled transient monthly maps are used to adjust the daily time-series mapped data (~30 maps/month) for each month. These adjustments are used to scale daily maps so that summing them for precipitation or averaging them for temperature would more accurately reproduce the variability in selected monthly maps. This method allows for individual days to have maxima or minima

  15. Evaluating simulations of daily discharge from large watersheds using autoregression and an index of flashiness

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Watershed models are calibrated to simulate stream discharge as accurately as possible. Modelers will often calculate model validation statistics on aggregate (often monthly) time periods, rather than the daily step at which models typically operate. This is because daily hydrologic data exhibit lar...

  16. Ozone and daily mortality in Shanghai, China

    SciTech Connect

    Zhang, Y.H.; Huang, W.; London, S.J.; Song, G.X.; Chen, G.H.; Jiang, L.L.; Zhao, N.Q.; Chen, B.H.; Kan, H.D.

    2006-08-15

    Given the changes in types of air pollution from conventional coal combustion to the mixed coal combustion/motor vehicle emissions in China's large cities, it is worthwhile to investigate the acute effect of O{sub 3} on mortality outcomes in the country. We conducted a time-series study to investigate the relation between O{sub 3} and daily mortality in Shanghai using 4 years of daily data (2001-2004). O{sub 3} was found to be significantly associated with total and cardiovascular mortality in the cold season but not in the warm season. In the whole-year analysis, an increase of 10 pg/m{sup 3} of 2-day average O{sub 3} corresponds to 0.45% (95% confidence interval (CI), 0.16-0.73%), 0.53% (95% CI, 0.10-0.96%), and 0.35% (95% CI, -0.40 to 1.09%) increase of total nonaccidental, cardiovascular, and respiratory mortality, respectively. In the cold season, the estimates increased to 1.38% (95% CI , 0.68-2.07%), 1.53% (95% CI, 0.54-2.52%), and 0.95% (95% CI, -0.71 to 2.60%), respectively. In the warm season, we did not observe significant associations for both total and causespecific mortality. The results were generally insensitive to model specifications such as lag structure of O{sub 3} concentrations and degree of freedom for time trend. Multipoflutant models indicate that the effect of O{sub 3} was not confounded by particulate matter {<=} 10 {mu} m in diameter (PM10) or by sulfur dioxide; however, after adding nitrogen dioxide into the model, the association of O{sub 3} with total and cardiovascular mortality became statistically insignificant.

  17. Sedoanalgesia in pediatric daily surgery

    PubMed Central

    Ozkan, Aybars; Okur, Mesut; Kaya, Murat; Kaya, Ertugrul; Kucuk, Adem; Erbas, Mesut; Kutlucan, Leyla; Sahan, Leyla

    2013-01-01

    Purpose: The present report was focused on clinical advantages of sedoanalgesia in the pediatric outpatient surgical cases. Method: Sedoanalgesia has been used to sedate patients for a variety of pediatric procedures in our department between 2007 and 2010. This is a retrospective review of 2720 pediatric patients given ketamine for sedation with midazolam premedication. Ketamine was given intravenously (1-2 mg/kg) together with atropine (0.02 mg/kg) and midazolam (0.1 mg/kg) + a local infiltration anesthetic 2 mg/kg 0.5% bupivacaine hydrochloride. Result: Median age of the patients included in the study was 5.76 ± 2.12 (0-16 years). The main indications for ketamine include circumcision (69%), inguinal pathologies (inguinal hernia (17%), orchidopexy (2.68%), hydrocele (3.38%), hypospadias (1.94%), urethral fistula repair (0.33%), urethral dilatation (0.25%), and other conditions. All of our patients were discharged home well. In this regard, we have the largest group of patients ever given ketamine. Conclusion: Sedoanalgesia might be used as a quite effective method for daily surgical procedures in children. PMID:23936597

  18. Appraisal-emotion relationships in daily life.

    PubMed

    Nezlek, John B; Vansteelandt, Kristof; Van Mechelen, Iven; Kuppens, Peter

    2008-02-01

    Using a daily process design, the present study examined relationships between momentary appraisals and emotional experience based on Smith and Lazarus' (1993) theory of emotions (1993). Nine times a day for 2 weeks, participants (N = 33, 23 women) recorded their momentary experience of 2 positive emotions (joy, love) and 4 negative emotions (anger, guilt, fear, sadness) and the core relational theme appraisal contents Smith and Lazarus hypothesized as corresponding to these emotions. A series of multilevel modeling analyses found that the hypothesized relationships between appraisal contents and these emotions were stronger than relationships between contents and other emotions, although appraisals were related to other emotions in many cases. Moreover, there were some individual differences in the strength of these relationships. These results suggest that there are no one-to-one relationships between appraisal contents and specific emotional experiences, and that specific emotions are associated with different appraisal contents, and that specific appraisals are associated with different emotions.

  19. Cokriging estimation of daily suspended sediment loads

    USGS Publications Warehouse

    Li, Z.; Zhang, Y.-K.; Schilling, K.; Skopec, M.

    2006-01-01

    Daily suspended sediment loads (S) were estimated using cokriging (CK) of S with daily river discharge based on weekly, biweekly, or monthly sampled sediment data. They were also estimated with ordinary kriging (OK) and a rating curve method. The estimated daily loads were compared with the daily measured values over a nine-year-period. The results show that the estimated daily sediment loads with the CK using the weekly measured data best matched the measured daily values. The rating curve method based on the same data provides a fairly good match but it tends to underestimate the peak and overestimate the low values. The CK estimation was better than the rating curve because CK considers the temporal correlation among the data values and honors the measured points whereas the rating curve method does not. For the site studied, weekly sampling may be frequent enough for estimating daily sediment loads with CK when daily discharge data is available. The estimated daily loads with CK were less reliable when the sediment samples were taken less frequently, i.e., biweekly or monthly. The OK estimates using the weekly measured data significantly underestimates the daily S because unlike CK and the rating curve, OK makes no use of the correlation of sediment loads with frequently measured river discharge. ?? 2005 Elsevier B.V. All rights reserved.

  20. Analyzing clinical trial outcomes based on incomplete daily diary reports.

    PubMed

    Thomas, Neal; Harel, Ofer; Little, Roderick J A

    2016-07-30

    A case study is presented assessing the impact of missing data on the analysis of daily diary data from a study evaluating the effect of a drug for the treatment of insomnia. The primary analysis averaged daily diary values for each patient into a weekly variable. Following the commonly used approach, missing daily values within a week were ignored provided there was a minimum number of diary reports (i.e., at least 4). A longitudinal model was then fit with treatment, time, and patient-specific effects. A treatment effect at a pre-specified landmark time was obtained from the model. Weekly values following dropout were regarded as missing, but intermittent daily missing values were obscured. Graphical summaries and tables are presented to characterize the complex missing data patterns. We use multiple imputation for daily diary data to create completed data sets so that exactly 7 daily diary values contribute to each weekly patient average. Standard analysis methods are then applied for landmark analysis of the completed data sets, and the resulting estimates are combined using the standard multiple imputation approach. The observed data are subject to digit heaping and patterned responses (e.g., identical values for several consecutive days), which makes accurate modeling of the response data difficult. Sensitivity analyses under different modeling assumptions for the data were performed, along with pattern mixture models assessing the sensitivity to the missing at random assumption. The emphasis is on graphical displays and computational methods that can be implemented with general-purpose software. Copyright © 2016 John Wiley & Sons, Ltd.

  1. Enhancement of the MODIS Daily Snow Albedo Product

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Schaaf, Crystal B.; Wang, Zhuosen; Riggs, George A.

    2009-01-01

    The MODIS daily snow albedo product is a data layer in the MOD10A1 snow-cover product that includes snow-covered area and fractional snow cover as well as quality information and other metadata. It was developed to augment the MODIS BRDF/Albedo algorithm (MCD43) that provides 16-day maps of albedo globally at 500-m resolution. But many modelers require daily snow albedo, especially during the snowmelt season when the snow albedo is changing rapidly. Many models have an unrealistic snow albedo feedback in both estimated albedo and change in albedo over the seasonal cycle context, Rapid changes in snow cover extent or brightness challenge the MCD43 algorithm; over a 16-day period, MCD43 determines whether the majority of clear observations was snow-covered or snow-free then only calculates albedo for the majority condition. Thus changes in snow albedo and snow cover are not portrayed accurately during times of rapid change, therefore the current MCD43 product is not ideal for snow work. The MODIS daily snow albedo from the MOD10 product provides more frequent, though less robust maps for pixels defined as "snow" by the MODIS snow-cover algorithm. Though useful, the daily snow albedo product can be improved using a daily version of the MCD43 product as described in this paper. There are important limitations to the MOD10A1 daily snow albedo product, some of which can be mitigated. Utilizing the appropriate per-pixel Bidirectional Reflectance Distribution Functions (BRDFs) can be problematic, and correction for anisotropic scattering must be included. The BRDF describes how the reflectance varies with view and illumination geometry. Also, narrow-to-broadband conversion specific for snow on different surfaces must be calculated and this can be difficult. In consideration of these limitations of MOD10A1, we are planning to improve the daily snow albedo algorithm by coupling the periodic per-pixel snow albedo from MCD43, with daily surface ref|outanoom, In this paper, we

  2. Forecasting of daily total atmospheric ozone in Isfahan.

    PubMed

    Yazdanpanah, H; Karimi, M; Hejazizadeh, Z

    2009-10-01

    A neural network combined to an artificial neural network model is used to forecast daily total atmospheric ozone over Isfahan city in Iran. In this work, in order to forecast the total column ozone over Isfahan, we have examined several neural networks algorithms with different meteorological predictors based on the ozone-meteorological relationships with previous day's ozone value. The meteorological predictors consist of temperatures (dry and dew point) and geopotential heights at standard levels of 100, 50, 30, 20 and 10 hPa with their wind speed and direction. These data together with previous day total ozone forms the input matrix of the neural model that is based on the back propagation algorithm (BPA) structure. The output matrix is the daily total atmospheric ozone. The model was build based on daily data from 1997 to 2004 obtained from Isfahan ozonometric station data. After modeling these data we used 3 year (from 2001 to 2003) of daily total ozone for testing the accuracy of model. In this experiment, with the final neural network, the total ozone are fairly well predicted, with an Agreement Index 76%.

  3. Estimation of Daily Stream Temperatures in a Mountain River Network

    NASA Astrophysics Data System (ADS)

    Sohrabi, M.; Benjankar, R. M.; Isaak, D.; Wenger, S.; Tonina, D.

    2013-12-01

    Stream temperature plays an important role in aquatic ecosystems. Concentrations of dissolved oxygen, water and spawning habitat quality, growth of fish populations are functions of stream temperature. Therefore, accurate estimates of daily stream temperatures can provide beneficial information for water resource managers and decision makers. Here, we develop a model for precise daily water temperature estimates that is applicable even in places lacking various meteorological and hydrological data. The water temperature model in this study is a piecewise model that considers both linear and non-linear relationships between dependent and independent variables including maximum and minimum temperature (meteorological derivers) and precipitation (hydrological deriver). We demonstrated the model in the Boise River Basin, in central Idaho, USA. The hydrology of this basin is snow-dominated and complex due to the mountainous terrain. We predicted daily stream temperature at 34 sites using 12 weather and Snowtel stations for deriving variables. Results of the stream temperature model indicate average Root Mean Square Error of 1.28 degree of Celsius along with average 0.91 of Nash-Sutcliffe coefficient for all stations. Comparison of the results of this study to Mohseni et al.'s model (1998), which is widely applied in water temperature studies, shows better performance of the model presented in this study. Our approach can be used to provide historical reconstructions of daily stream temperatures or projections of stream temperatures under climate change scenarios in any location with at least one year of daily stream temperature observations and with contemporaneous regional air temperature and precipitation data.

  4. Daily Stressors in School-Age Children: A Multilevel Approach

    ERIC Educational Resources Information Center

    Escobar, Milagros; Alarcón, Rafael; Blanca, María J.; Fernández-Baena, F. Javier; Rosel, Jesús F.; Trianes, María Victoria

    2013-01-01

    This study uses hierarchical or multilevel modeling to identify variables that contribute to daily stressors in a population of schoolchildren. Four hierarchical levels with several predictive variables were considered: student (age, sex, social adaptation of the student, number of life events and chronic stressors experienced, and educational…

  5. Daily Self-Disclosure and Sleep in Couples

    PubMed Central

    Kane, Heidi S.; Slatcher, Richard B.; Reynolds, Bridget M.; Repetti, Rena L.; Robles, Theodore F.

    2014-01-01

    Objective An emerging literature provides evidence for the association between romantic relationship quality and sleep, an important factor in health and well-being. However, we still know very little about the specific relationship processes that affect sleep behavior. Therefore, the goal of this study was to examine how self-disclosure, an important relational process linked to intimacy, relationship satisfaction and health, is associated with sleep behavior. Method As part of a larger study of family processes, wives (n=46) and husbands (n=38) from 46 cohabiting families completed 56 days of daily diaries. Spouses completed evening diaries assessing daily self-disclosure, relationship satisfaction, and mood and morning diaries assessing the prior night's sleep. Multilevel modeling was used to explore the effects of both daily variation in and average levels across the 56 days of self-disclosure on sleep. Results Daily variation in self-disclosure predicted sleep outcomes for wives, but not for husbands. On days when wives self-disclosed more to their spouses than their average level, their subjective sleep quality and sleep efficiency that night improved. Furthermore, daily self-disclosure buffered the negative effect of daily negative mood on sleep latency for wives, but not husbands. In contrast, higher average levels of self-disclosure predicted less waking during the night for husbands, but not for wives. Conclusion The association between self-disclosure and sleep is one mechanism by which daily relationship functioning may influence health and well-being. Gender may play a role in how self-disclosure is associated with sleep. PMID:25068453

  6. TRENDS IN ESTIMATED MIXING DEPTH DAILY MAXIMUMS

    SciTech Connect

    Buckley, R; Amy DuPont, A; Robert Kurzeja, R; Matt Parker, M

    2007-11-12

    Mixing depth is an important quantity in the determination of air pollution concentrations. Fireweather forecasts depend strongly on estimates of the mixing depth as a means of determining the altitude and dilution (ventilation rates) of smoke plumes. The Savannah River United States Forest Service (USFS) routinely conducts prescribed fires at the Savannah River Site (SRS), a heavily wooded Department of Energy (DOE) facility located in southwest South Carolina. For many years, the Savannah River National Laboratory (SRNL) has provided forecasts of weather conditions in support of the fire program, including an estimated mixing depth using potential temperature and turbulence change with height at a given location. This paper examines trends in the average estimated mixing depth daily maximum at the SRS over an extended period of time (4.75 years) derived from numerical atmospheric simulations using two versions of the Regional Atmospheric Modeling System (RAMS). This allows for differences to be seen between the model versions, as well as trends on a multi-year time frame. In addition, comparisons of predicted mixing depth for individual days in which special balloon soundings were released are also discussed.

  7. The Daily Routine of the Oldest Old.

    ERIC Educational Resources Information Center

    Barer, Barbara M.

    Individuals who are beyond the age of 85 have to confront the decrements of aging that are commonly recognized. This study examined the daily routine of the oldest old through interviews. Subjects were asked about the logistics of their daily lives, what they liked best to do, what they didn't like to do, what made a day good for them, and what…

  8. 1 CFR 5.6 - Daily publication.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 1 General Provisions 1 2010-01-01 2010-01-01 false Daily publication. 5.6 Section 5.6 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER GENERAL § 5.6 Daily publication. There shall be an edition of the Federal Register published for each official Federal working day....

  9. 1 CFR 5.6 - Daily publication.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 1 General Provisions 1 2011-01-01 2011-01-01 false Daily publication. 5.6 Section 5.6 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER GENERAL § 5.6 Daily publication. There shall be an edition of the Federal Register published for each official Federal working day....

  10. How the Daily Press Looks at Hunger.

    ERIC Educational Resources Information Center

    Robinson, Sondra G.

    Utilizing both content analysis of 139 editorials appearing in 19 United States daily newspapers and the results of a survey of 146 newspaper editors, a study asked three questions: (1) To what extent is hunger covered in the news and editorial columns of U.S. daily newspapers? (2) How is hunger defined as a problem in terms of its causes in those…

  11. Techniques for Daily Living: Curriculum Guides.

    ERIC Educational Resources Information Center

    Wooldridge, Lillian; And Others

    Presented are specific guides concerning techniques for daily living which were developed by the child care staff at the Illinois Braille and Sight Saving School. The guides are designed for cottage parents of the children, who may have both visual and other handicaps, and show what daily living skills are necessary and appropriate for the…

  12. 1 CFR 5.6 - Daily publication.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 1 General Provisions 1 2014-01-01 2012-01-01 true Daily publication. 5.6 Section 5.6 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER GENERAL § 5.6 Daily publication. There shall be an edition of the Federal Register published for each official Federal working day....

  13. 1 CFR 5.6 - Daily publication.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 1 General Provisions 1 2013-01-01 2012-01-01 true Daily publication. 5.6 Section 5.6 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER GENERAL § 5.6 Daily publication. There shall be an edition of the Federal Register published for each official Federal working day....

  14. 1 CFR 5.6 - Daily publication.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 1 General Provisions 1 2012-01-01 2012-01-01 false Daily publication. 5.6 Section 5.6 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER GENERAL § 5.6 Daily publication. There shall be an edition of the Federal Register published for each official Federal working day....

  15. Daily Stressors in Primary Education Students

    ERIC Educational Resources Information Center

    Fernández-Baena, F. Javier; Trianes, María V.; Escobar, Milagros; Blanca, María J.; Muñoz, Ángela M.

    2015-01-01

    Daily stress can have a bearing on children's emotional and academic development. This study aimed to assess daily stressors and to determine their prevalence among primary education students, taking into account their gender, academic year, social adaptation, and the school location. A sample of 7,354 Spanish schoolchildren aged between 6 and 13…

  16. Daily Spiritual Experiences and Prosocial Behavior

    ERIC Educational Resources Information Center

    Einolf, Christopher J.

    2013-01-01

    This paper examines how the Daily Spiritual Experiences Scale (DSES) relates to range of prosocial behaviors, using a large, nationally representative U.S. data set. It finds that daily spiritual experiences are a statistically and substantively significant predictor of volunteering, charitable giving, and helping individuals one knows personally.…

  17. Exercise and sleep predict personal resources in employees' daily lives.

    PubMed

    Nägel, Inga J; Sonnentag, Sabine

    2013-11-01

    The present study investigates the interaction of exercise and sleep on state-like personal resources in employees' daily lives. Further, the study examines the association between state-like personal resources and emotional exhaustion. We conducted a diary study over five consecutive working days (total of 443 days) with 144 employees who answered daily online surveys after work and before bedtime. Multilevel modeling showed that exercise after work was positively related to the next day's personal resources when sleep duration during the night time was longer compared to other nights. Furthermore, personal resources positively related to lower emotional exhaustion after work on the next day. This study demonstrates that exercise and sleep may help to renew personal resources. Results stress the importance of balancing exercise and sleep in daily life.

  18. Perceived health status and daily activity participation of older Malaysians.

    PubMed

    Ng, Sor Tho; Tengku-Aizan, Hamid; Tey, Nai Peng

    2011-07-01

    This article investigates the influence of perceived health status on the daily activity participation of older Malaysians. Data from the Survey on Perceptions of Needs and Problems of the Elderly, which was conducted in 1999, were used. The negative binomial regression results show that older persons with good perceived health status reported more varieties of daily activity participation, especially among the uneducated and those with below-average self-esteem. The multinomial logistic regression model suggests that older persons with good perceived health status tended to engage daily in paid work only or with leisure activities, whereas those perceived to have poor health were more likely to engage in leisure activities only or leisure and family role activities. Promotion of a healthy lifestyle at a younger age encourages every person to monitor and take responsibility for their own health, which is a necessary strategy to ensure active participation at an older age, and thus improve their well-being.

  19. Adolescent daily and general maladjustment: is there reactivity to daily repeated measures methodologies?

    PubMed

    Nishina, Adrienne

    2012-01-01

    The present study examined whether repeated exposure to daily surveys about negative social experiences predicts changes in adolescents' daily and general maladjustment, and whether question content moderates these changes. Across a 2-week period, 6th-grade students (N = 215; mode age = 11) completed 5 daily reports tapping experienced or experienced and witnessed negative events, or they completed no daily reports. General maladjustment was measured in 2-week intervals before, at the end of, and 2 weeks after the daily report study. Daily maladjustment either decreased or did not change across the 5 daily report exposures. General maladjustment decreased across the three 2-week intervals. Combined, results indicate that short-term daily report studies do not place youth at risk for increased maladjustment.

  20. Daily social exchanges and affect in middle and later adulthood: the impact of loneliness and age.

    PubMed

    Russell, Alissa; Bergeman, C S; Scott, Stacey B

    2012-01-01

    Although daily social exchanges are important for well-being, it is unclear how different types of exchanges affect daily well-being, as well as which factors influence the way in which individuals react to their daily social encounters. The present study included a sample of 705 adults aged 31 to 91, and using Multilevel Modeling analyses investigated whether loneliness or age moderate the relationship between daily affect and daily social exchanges with family and friends. Results indicated differences between events involving family and those involving friends. Furthermore, lonelier individuals benefitted more from positive events than less lonely adults but were not more negatively reactive to negative events. Moreover, results suggested that older adults' affect is more independent of both positive and negative social events compared to younger people. Implications are discussed for the importance of daily social exchanges, daily social stress vulnerability, and the influences of loneliness across middle and later adulthood.

  1. Simulating Daily and Sub-daily Water Flow in Large, Semi-arid Watershed Using SWAT: A Case Study of Nueces River Basin, Texas

    NASA Astrophysics Data System (ADS)

    Bassam, S.; Ren, J.

    2015-12-01

    Runoff generated during heavy rainfall imposes quick, but often intense, changes in the flow of streams, which increase the chance of flash floods in the vicinity of the streams. Understanding the temporal response of streams to heavy rainfall requires a hydrological model that considers meteorological, hydrological, and geological components of the streams and their watersheds. SWAT is a physically-based, semi-distributed model that is capable of simulating water flow within watersheds with both long-term, i.e. annually and monthly, and short-term (daily and sub-daily) time scales. However, the capability of SWAT in sub-daily water flow modeling within large watersheds has not been studied much, compare to long-term and daily time scales. In this study we are investigating the water flow in a large, semi-arid watershed, Nueces River Basin (NRB) with the drainage area of 16950 mi2 located in South Texas, with daily and sub-daily time scales. The objectives of this study are: (1) simulating the response of streams to heavy, and often quick, rainfall, (2) evaluating SWAT performance in sub-daily modeling of water flow within a large watershed, and (3) examining means for model performance improvement during model calibration and verification based on results of sensitivity and uncertainty analysis. The results of this study can provide important information for water resources planning during flood seasons.

  2. Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City.

    PubMed

    Chau, Tang-Tat; Wang, Kuo-Ying

    2016-01-01

    An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007-2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0-15 years old). Middle-aged people (16-65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8-1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place.

  3. Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City

    PubMed Central

    Chau, Tang-Tat; Wang, Kuo-Ying

    2016-01-01

    An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007–2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0–15 years old). Middle-aged people (16–65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8–1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place. PMID

  4. When Daily Sunspot Births Become Positively Correlated

    NASA Astrophysics Data System (ADS)

    Shapoval, Alexander; Le Mouël, Jean-Louis; Shnirman, Mikhail; Courtillot, Vincent

    2015-10-01

    We study the first differences w(t) of the International Sunspot Number (ISSN) daily series for the time span 1850 - 2013. The one-day correlations ρ1 between w(t) and w(t+1) are computed within four-year sliding windows and are found to shift from negative to positive values near the end of Cycle 17 ({˜} 1945). They remain positive during the last Grand Maximum and until {˜} 2009, when they fall to zero. We also identify a prominent regime change in {˜} 1915, strengthening previous evidence of major anomalies in solar activity at this date. We test an autoregressive process of order 1 (AR(1)) as a model that can reproduce the high-frequency component of ISSN: we compute ρ1 for this AR(1) process and find that it is negative. Positive values of ρ1 are found only if the process involves positive correlation: this leads us to suggest that the births of successive spots are positively correlated during the last Grand Maximum.

  5. Daily Cybervictimization Among Latino Adolescents: Links with Emotional, Physical and School Adjustment

    PubMed Central

    Espinoza, Guadalupe

    2015-01-01

    The current study examines how Latino adolescents’ daily cybervictimization experiences are associated with their emotional and physical well-being and school adjustment. Latino high school students (N = 118) completed daily checklists across five consecutive school days. Hierarchical linear modeling results revealed that daily cybervictimization experiences were associated with greater feelings of distress, anger, shame and physical symptoms. Moderation analyses showed gender differences such that the daily level associations with distress and anger were significant for Latinas but not Latino adolescents. Daily cybervictimization experiences were also related to increased school attendance problems such as arriving late to class or skipping a class. Mediation models indicated that daily feelings of distress accounted for the association between single episodes of cybervictimization and attendance problems. The results address several voids in the cybervictimization literature and demonstrate that a discrete encounter of victimization online is associated with compromised well-being and school adjustment among Latino adolescents. PMID:27307652

  6. Daily Cybervictimization Among Latino Adolescents: Links with Emotional, Physical and School Adjustment.

    PubMed

    Espinoza, Guadalupe

    2015-01-01

    The current study examines how Latino adolescents' daily cybervictimization experiences are associated with their emotional and physical well-being and school adjustment. Latino high school students (N = 118) completed daily checklists across five consecutive school days. Hierarchical linear modeling results revealed that daily cybervictimization experiences were associated with greater feelings of distress, anger, shame and physical symptoms. Moderation analyses showed gender differences such that the daily level associations with distress and anger were significant for Latinas but not Latino adolescents. Daily cybervictimization experiences were also related to increased school attendance problems such as arriving late to class or skipping a class. Mediation models indicated that daily feelings of distress accounted for the association between single episodes of cybervictimization and attendance problems. The results address several voids in the cybervictimization literature and demonstrate that a discrete encounter of victimization online is associated with compromised well-being and school adjustment among Latino adolescents.

  7. Expression of schizophrenia-spectrum personality traits in daily life.

    PubMed

    Chun, Charlotte A; Barrantes-Vidal, Neus; Sheinbaum, Tamara; Kwapil, Thomas R

    2017-01-01

    The present study examined the expression of the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) schizotypal, schizoid, and paranoid personality disorder (PD) traits in daily life using experience sampling methodology in 206 nonclinically ascertained Spanish young adults oversampled for risk for schizophrenia-spectrum psychopathology. This study examined the overlap and differentiation of pathological personality traits in daily life settings, according to both diagnostic and multidimensional models. Daily life outcomes differentiated among schizophrenia-spectrum disorders. The assignment of Cluster A personality traits to positive, negative, paranoid, and disorganized dimensions provided an alternative to the traditional PD diagnoses. Positive, disorganized, and paranoid schizotypy were associated with elevated stress reactivity, whereas negative schizotypy was associated with diminished reactivity in daily life. The current diagnostic model is limited by the considerable overlap among the PD traits. Nonetheless, experience sampling methodology is sensitive enough to detect differences in day-to-day impairment and can be a powerful research tool for the examination of dynamic constructs such as personality pathology. (PsycINFO Database Record

  8. REL3.0 SW DAILY UTC

    Atmospheric Science Data Center

    2016-10-05

    ... Active Radiation Flux Cloud Fraction Cosine Solar Zenith Angle From Satellite Cosine Solar Zenith Angle From Astronomy ... ISCCP Data Table SSE Renewable Energy Readme Files:  Readme_3.0_sw_daily ...

  9. REL3.0 SW DAILY LOCAL

    Atmospheric Science Data Center

    2016-10-05

    ... Active Radiation Flux Cloud Fraction Cosine Solar Zenith Angle From Satellite Cosine Solar Zenith Angle From Astronomy ... ISCCP Data Table SSE Renewable Energy Readme Files:  Readme_3.0_sw_daily ...

  10. Percent Daily Value: What Does It Mean?

    MedlinePlus

    Healthy Lifestyle Nutrition and healthy eating What do the Daily Value numbers mean on food labels? Answers from ... 15, 2016 Original article: http://www.mayoclinic.org/healthy-lifestyle/nutrition-and-healthy-eating/expert-answers/food-and- ...

  11. AMSR2 Daily Arctic Sea Ice - 2014

    NASA Video Gallery

    In this animation, the daily Arctic sea ice and seasonal land cover change progress through time, from March 21, 2014 through the 3rd of August, 2014. Over the water, Arctic sea ice changes from da...

  12. Twice-Daily versus Once-Daily Pramipexole Extended Release Dosage Regimens in Parkinson's Disease.

    PubMed

    Yun, Ji Young; Kim, Young Eun; Yang, Hui-Jun; Kim, Han-Joon; Jeon, Beomseok

    2017-01-01

    This open-label study aimed to compare once-daily and twice-daily pramipexole extended release (PER) treatment in Parkinson's disease (PD). PD patients on dopamine agonist therapy, but with unsatisfactory control, were enrolled. Existing agonist doses were switched into equivalent PER doses. Subjects were consecutively enrolled into either once-daily-first or twice-daily-first groups and received the prescribed amount in one or two, respectively, daily doses for 8 weeks. For the second period, subjects switched regimens in a crossover manner. The forty-four patients completed a questionnaire requesting preference during their last visit. We measured the UPDRS-III, Hoehn and Yahr stages (H&Y) in medication-on state, Parkinson's disease sleep scale (PDSS), and Epworth Sleepiness Scale. Eighteen patients preferred a twice-daily regimen, 12 preferred a once-daily regimen, and 14 had no preference. After the trial, 14 subjects wanted to be on a once-daily regimen, 25 chose a twice-daily regimen, and 5 wanted to maintain the prestudy regimen. Main reasons for choosing the twice-daily regimen were decreased off-duration, more tolerable off-symptoms, and psychological stability. The mean UPDRS-III, H&Y, and PDSS were not different. Daytime sleepiness was significantly high in the once-daily regimen, whereas nocturnal hallucinations were more common in the twice-daily. Multiple dosing should be considered if once-daily dosing is unsatisfactory. This study is registered as NCT01515774 at ClinicalTrials.gov.

  13. Twice-Daily versus Once-Daily Pramipexole Extended Release Dosage Regimens in Parkinson's Disease

    PubMed Central

    Kim, Young Eun; Yang, Hui-Jun; Kim, Han-Joon

    2017-01-01

    This open-label study aimed to compare once-daily and twice-daily pramipexole extended release (PER) treatment in Parkinson's disease (PD). PD patients on dopamine agonist therapy, but with unsatisfactory control, were enrolled. Existing agonist doses were switched into equivalent PER doses. Subjects were consecutively enrolled into either once-daily-first or twice-daily-first groups and received the prescribed amount in one or two, respectively, daily doses for 8 weeks. For the second period, subjects switched regimens in a crossover manner. The forty-four patients completed a questionnaire requesting preference during their last visit. We measured the UPDRS-III, Hoehn and Yahr stages (H&Y) in medication-on state, Parkinson's disease sleep scale (PDSS), and Epworth Sleepiness Scale. Eighteen patients preferred a twice-daily regimen, 12 preferred a once-daily regimen, and 14 had no preference. After the trial, 14 subjects wanted to be on a once-daily regimen, 25 chose a twice-daily regimen, and 5 wanted to maintain the prestudy regimen. Main reasons for choosing the twice-daily regimen were decreased off-duration, more tolerable off-symptoms, and psychological stability. The mean UPDRS-III, H&Y, and PDSS were not different. Daytime sleepiness was significantly high in the once-daily regimen, whereas nocturnal hallucinations were more common in the twice-daily. Multiple dosing should be considered if once-daily dosing is unsatisfactory. This study is registered as NCT01515774 at ClinicalTrials.gov. PMID:28265478

  14. On the adaptive daily forecasting of seismic aftershock hazard

    NASA Astrophysics Data System (ADS)

    Ebrahimian, Hossein; Jalayer, Fatemeh; Asprone, Domenico; Lombardi, Anna Maria; Marzocchi, Warner; Prota, Andrea; Manfredi, Gaetano

    2013-04-01

    Post-earthquake ground motion hazard assessment is a fundamental initial step towards time-dependent seismic risk assessment for buildings in a post main-shock environment. Therefore, operative forecasting of seismic aftershock hazard forms a viable support basis for decision-making regarding search and rescue, inspection, repair, and re-occupation in a post main-shock environment. Arguably, an adaptive procedure for integrating the aftershock occurrence rate together with suitable ground motion prediction relations is key to Probabilistic Seismic Aftershock Hazard Assessment (PSAHA). In the short-term, the seismic hazard may vary significantly (Jordan et al., 2011), particularly after the occurrence of a high magnitude earthquake. Hence, PSAHA requires a reliable model that is able to track the time evolution of the earthquake occurrence rates together with suitable ground motion prediction relations. This work focuses on providing adaptive daily forecasts of the mean daily rate of exceeding various spectral acceleration values (the aftershock hazard). Two well-established earthquake occurrence models suitable for daily seismicity forecasts associated with the evolution of an aftershock sequence, namely, the modified Omori's aftershock model and the Epidemic Type Aftershock Sequence (ETAS) are adopted. The parameters of the modified Omori model are updated on a daily basis using Bayesian updating and based on the data provided by the ongoing aftershock sequence based on the methodology originally proposed by Jalayer et al. (2011). The Bayesian updating is used also to provide sequence-based parameter estimates for a given ground motion prediction model, i.e. the aftershock events in an ongoing sequence are exploited in order to update in an adaptive manner the parameters of an existing ground motion prediction model. As a numerical example, the mean daily rates of exceeding specific spectral acceleration values are estimated adaptively for the L'Aquila 2009

  15. Pain and negative mood during rehabilitation after anterior cruciate ligament reconstruction: a daily process analysis.

    PubMed

    Brewer, B W; Cornelius, A E; Sklar, J H; Van Raalte, J L; Tennen, H; Armeli, S; Corsetti, J R; Brickner, J C

    2007-10-01

    Daily diary methods were used to examine changes in pain and negative mood over the first 6 weeks of rehabilitation after surgical reconstruction of the anterior cruciate ligament (ACL). Participants (58 men and 33 women) completed measures of personal factors (i.e., age, athletic identity, neuroticism, optimism) before surgery and indices of daily pain, negative mood, and stress for 42 days after surgery. Multilevel modeling revealed that, as would be expected, daily pain ratings decreased significantly over the course of the study and that the rate of decline in pain ratings decreased over time. Age and daily negative mood were positively associated with daily pain ratings. Daily negative mood also decreased significantly over the course of the study and was positively associated with neuroticism, daily pain, and daily stress. Athletic identity and optimism interacted with time since surgery in predicting daily negative mood such that participants with high levels of athletic identity and low levels of optimism reported greater decreases in daily negative mood over time. Overall, the findings reveal a pattern of improved psychological functioning over the early stages of post-operative ACL rehabilitation.

  16. Skeletal Adaptation to Daily Activity: A Biochemical Perspective

    NASA Technical Reports Server (NTRS)

    Whalen, Robert T.; Dalton, Bonnie (Technical Monitor)

    2002-01-01

    Musculoskeletal forces generated by normal daily activity on Earth maintain the functional and structural properties of muscle and bone throughout most of one's adult life. A reduction in the level of cumulative daily loading caused by space flight, bed rest or spinal cord injury induces rapid muscle atrophy, functional changes in muscle, and bone resorption in regions subjected to the reduced loading. Bone cells in culture and bone tissue reportedly respond to a wide variety of non-mechanical and mechanical stimuli ranging, from electromagnetic fields, and hormones to small amplitude, high frequency vibrations, fluid flow, strain rate, and stress/strain magnitude. However, neither the transduction mechanism that transforms the mechanical input into a muscle or bone metabolic response nor the characteristics, of the loading history that directly or indirectly stimulates the cell is known. Identifying the factors contributing to the input stimulus will have a major impact on the design of effective countermeasures for long duration space flight. This talk will present a brief overview of current theories of bone remodeling and functional adaptation to mechanical loading. Work from our lab will be presented from the perspective of daily cumulative loading on Earth and its relationship to bone density and structure. Our objective is to use the tibia and calcaneus as model bone sites of cortical and cancellous bone adaptation, loaded daily by musculoskeletal forces in equilibrium with the ground reaction force. All materials that will be discussed are in the open scientific literature.

  17. Development of daily "swath" mascon solutions from GRACE

    NASA Astrophysics Data System (ADS)

    Save, Himanshu; Bettadpur, Srinivas

    2016-04-01

    The Gravity Recovery and Climate Experiment (GRACE) mission has provided invaluable and the only data of its kind over the past 14 years that measures the total water column in the Earth System. The GRACE project provides monthly average solutions and there are experimental quick-look solutions and regularized sliding window solutions available from Center for Space Research (CSR) that implement a sliding window approach and variable daily weights. The need for special handling of these solutions in data assimilation and the possibility of capturing the total water storage (TWS) signal at sub-monthly time scales motivated this study. This study discusses the progress of the development of true daily high resolution "swath" mascon total water storage estimate from GRACE using Tikhonov regularization. These solutions include the estimates of daily total water storage (TWS) for the mascon elements that were "observed" by the GRACE satellites on a given day. This paper discusses the computation techniques, signal, error and uncertainty characterization of these daily solutions. We discuss the comparisons with the official GRACE RL05 solutions and with CSR mascon solution to characterize the impact on science results especially at the sub-monthly time scales. The evaluation is done with emphasis on the temporal signal characteristics and validated against in-situ data set and multiple models.

  18. Negative Affective Spillover from Daily Events Predicts Early Response to Cognitive Therapy for Depression

    ERIC Educational Resources Information Center

    Cohen, Lawrence H.; Gunthert, Kathleen C.; Butler, Andrew C.; Parrish, Brendt P.; Wenze, Susan J.; Beck, Judith S.

    2008-01-01

    This study evaluated the predictive role of depressed outpatients' (N = 62) affective reactivity to daily stressors in their rates of improvement in cognitive therapy (CT). For 1 week before treatment, patients completed nightly electronic diaries that assessed daily stressors and negative affect (NA). The authors used multilevel modeling to…

  19. Relationship of Dyadic Closeness with Work-Related Stress: A Daily Diary Study

    ERIC Educational Resources Information Center

    Lavee, Yoav; Ben-Ari, Adital

    2007-01-01

    We examined the association between work-related stress of both spouses and daily fluctuations in their affective states and dyadic closeness. Daily diary data from 169 Israeli dual-earner couples were analyzed using multilevel modeling. The findings indicate that work stress has no direct effect on dyadic closeness but rather is mediated by the…

  20. Increases in Physical Activity Result in Diminishing Increments in Daily Energy Expenditure in Mice.

    PubMed

    O'Neal, Timothy J; Friend, Danielle M; Guo, Juen; Hall, Kevin D; Kravitz, Alexxai V

    2017-02-06

    Exercise is a common component of weight loss strategies, yet exercise programs are associated with surprisingly small changes in body weight [1-4]. This may be due in part to compensatory adaptations, in which calories expended during exercise are counteracted by decreases in other aspects of energy expenditure [1, 5-10]. Here we examined the relationship between a rodent model of voluntary exercise- wheel running- and total daily energy expenditure. Use of a running wheel for 3 to 7 days increased daily energy expenditure, resulting in a caloric deficit of ∼1 kcal/day; however, total daily energy expenditure remained stable after the first week of wheel access, despite further increases in wheel use. We hypothesized that compensatory mechanisms accounted for the lack of increase in daily energy expenditure after the first week. Supporting this idea, we observed a decrease in off-wheel ambulation when mice were using the wheels, indicating behavioral compensation. Finally, we asked whether individual variation in wheel use within a group of mice would be associated with different levels of daily energy expenditure. Despite a large variation in wheel running, we did not observe a significant relationship between the amount of daily wheel running and total daily energy expenditure or energy intake across mice. Together, our experiments support a model in which the transition from sedentary to light activity is associated with an increase in daily energy expenditure, but further increases in physical activity produce diminishingly small increments in daily energy expenditure.

  1. Simulating multimodal seasonality in extreme daily precipitation occurrence

    NASA Astrophysics Data System (ADS)

    Tye, Mari R.; Blenkinsop, Stephen; Fowler, Hayley J.; Stephenson, David B.; Kilsby, Christopher G.

    2016-06-01

    Floods pose multi-dimensional hazards to critical infrastructure and society and these hazards may increase under climate change. While flood conditions are dependent on catchment type and soil conditions, seasonal precipitation extremes also play an important role. The extreme precipitation events driving flood occurrence may arrive non-uniformly in time. In addition, their seasonal and inter-annual patterns may also cause sequences of several events and enhance likely flood responses. Spatial and temporal patterns of extreme daily precipitation occurrence are characterized across the UK. Extreme and very heavy daily precipitation is not uniformly distributed throughout the year, but exhibits spatial differences, arising from the relative proximity to the North Atlantic Ocean or North Sea. Periods of weeks or months are identified during which extreme daily precipitation occurrences are most likely to occur, with some regions of the UK displaying multimodal seasonality. A Generalized Additive Model is employed to simulate extreme daily precipitation occurrences over the UK from 1901 to 2010 and to allow robust statistical testing of temporal changes in the seasonal distribution. Simulations show that seasonality has the strongest correlation with intra-annual variations in extreme event occurrence, while Sea Surface Temperature (SST) and Mean Sea Level Pressure (MSLP) have the strongest correlation with inter-annual variations. The north and west of the UK are dominated by MSLP in the mid-North Atlantic and the south and east are dominated by local SST. All regions now have a higher likelihood of autumnal extreme daily precipitation than earlier in the twentieth century. This equates to extreme daily precipitation occurring earlier in the autumn in the north and west, and later in the autumn in the south and east. The change in timing is accompanied by increases in the probability of extreme daily precipitation occurrences during the autumn, and in the number of

  2. Executive function in daily life: Age-related influences of executive processes on instrumental activities of daily living.

    PubMed

    Vaughan, Leslie; Giovanello, Kelly

    2010-06-01

    The present study of older adults used structural equation modeling (SEM) to examine the relationships between 3 executive processes underlying executive function (EF) (inhibition, task switching, updating in working memory), and 2 types of instrumental activities of daily living (IADLs) (self-report, performance based). Experimental tasks of executive attention and self-report or performance-based IADL tests were administered to create latent constructs of EF and IADLs. Confirmatory factor analysis (CFA) was used to examine the construct validity of EF and IADLs. This analysis indicated a 3-factor model of inhibition, updating, and task switching and a 2-factor model of self-report and performance-based IADLs. As predicted, when the latent variable relationships were analyzed, executive processes had a significant relationship with performance-based, but not self-report, IADLs. In addition, task switching had a strong and significant relationship with performance-based IADLs. The results of this study uniquely show a direct relationship between executive processes and performance-based IADLs, thus demonstrating the ecological utility of experimental measures of EF to predict daily function. Furthermore, these results point to areas of cognitive training that may strategically impact older adults' performance on daily life activities.

  3. Deriving Daily Purpose through Daily Events and Role Fulfillment among Asian American Youth

    ERIC Educational Resources Information Center

    Kiang, Lisa

    2012-01-01

    Establishing life purpose is a key developmental task; however, how it is linked to adolescents' everyday family, school, extracurricular, and leisure experiences remains unclear. Using daily diary data from 180 Asian American ninth and tenth graders (50% ninth; 58% female; 25% first generation), daily purpose was positively related to daily…

  4. Products to Aid in Daily Living

    MedlinePlus

    ... for an update to this message. Product List Product/Services Topics Care Services Information and Referral Service (800) 782-4747 alsinfo@alsa-national.org For People with ALS and ... Videos Factsheets Products to Aid in Daily Living Informative Web Links ...

  5. Daily Physical Education/Fitness. Survey.

    ERIC Educational Resources Information Center

    Manitoba Dept. of Education, Winnipeg.

    Physical education staff (principals and division superintendents) in the Manitoba, Canada department of education responded to a survey pertaining to time allotments of physical education programs. Survey results indicated that all levels of administration supported the implementation of daily physical education programs. There is general…

  6. Big Ideas behind Daily 5 and CAFE

    ERIC Educational Resources Information Center

    Boushey, Gail; Moser, Joan

    2012-01-01

    The Daily 5 and CAFE were born out of The Sister's research and observations of instructional mentors, their intense desire to be able to deliver highly intentional, focused instruction to small groups and individuals while the rest of the class was engaged in truly authentic reading and writing, and their understanding that a one size fits all…

  7. INTERPOLATING VANCOUVER'S DAILY AMBIENT PM 10 FIELD

    EPA Science Inventory

    In this article we develop a spatial predictive distribution for the ambient space- time response field of daily ambient PM10 in Vancouver, Canada. Observed responses have a consistent temporal pattern from one monitoring site to the next. We exploit this feature of the field b...

  8. REL3.1 LW DAILY NC

    Atmospheric Science Data Center

    2016-10-05

    ... Budget (SRB) Release 3.1 GEWEX Longwave Daily Data in 1x1 Degree NetCDF Format News:  GEWEX Project ... Temporal Resolution:  3-hourly averaged by day File Format:  NETCDF Tools:  Search and ...

  9. Daily Routines of Young Children. (Draft).

    ERIC Educational Resources Information Center

    Rossbach, Hans-Guenther

    This pilot study of the structural characteristics of daily routines of young children also explored aspects of conceptual framework and research instruments. Four data collection instruments were developed. Two of the three retrospective measures used were questionnaires for mothers about their child's routine on the previous day. The other…

  10. Good Ideas for Teaching Daily Adult Living.

    ERIC Educational Resources Information Center

    Leigh, Robert K.

    Intended for practicing Adult Basic Education teachers, this handbook provides materials for teaching specific coping skills in the area of daily adult living. Three areas of study are explored: (1) community, which includes organizations, health, nutrition, safety, money management, and media; (2) government and law, which includes citizenship,…

  11. 27 CFR 19.650 - Daily records.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... OF THE TREASURY LIQUORS DISTILLED SPIRITS PLANTS Production of Vinegar by the Vaporizing Process Required Records for Vinegar Plants § 19.650 Daily records. Each manufacturer of vinegar by the vaporizing... proof gallons of distilled spirits used in the manufacture of vinegar; (e) The wine gallons of...

  12. 27 CFR 19.829 - Daily records.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... OF THE TREASURY LIQUORS DISTILLED SPIRITS PLANTS Production of Vinegar by the Vaporizing Process Records § 19.829 Daily records. Each manufacturer of vinegar by the vaporizing process shall keep accurate... spirits used in the manufacture of vinegar; (e) The wine gallons of vinegar produced; and (f) The...

  13. 27 CFR 19.650 - Daily records.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... OF THE TREASURY LIQUORS DISTILLED SPIRITS PLANTS Production of Vinegar by the Vaporizing Process Required Records for Vinegar Plants § 19.650 Daily records. Each manufacturer of vinegar by the vaporizing... proof gallons of distilled spirits used in the manufacture of vinegar; (e) The wine gallons of...

  14. 27 CFR 19.650 - Daily records.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... OF THE TREASURY ALCOHOL DISTILLED SPIRITS PLANTS Production of Vinegar by the Vaporizing Process Required Records for Vinegar Plants § 19.650 Daily records. Each manufacturer of vinegar by the vaporizing... proof gallons of distilled spirits used in the manufacture of vinegar; (e) The wine gallons of...

  15. 27 CFR 19.650 - Daily records.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... OF THE TREASURY ALCOHOL DISTILLED SPIRITS PLANTS Production of Vinegar by the Vaporizing Process Required Records for Vinegar Plants § 19.650 Daily records. Each manufacturer of vinegar by the vaporizing... proof gallons of distilled spirits used in the manufacture of vinegar; (e) The wine gallons of...

  16. Creating a global sub-daily precipitation dataset

    NASA Astrophysics Data System (ADS)

    Lewis, Elizabeth; Blenkinsop, Stephen; Fowler, Hayley

    2016-04-01

    Extremes of precipitation can cause flooding and droughts which can lead to substantial damages to infrastructure and ecosystems and can result in loss of life. It is still uncertain how hydrological extremes will change with global warming as we do not fully understand the processes that cause extreme precipitation under current climate variability. The INTENSE project is using a novel and fully-integrated data-modelling approach to provide a step-change in our understanding of the nature and drivers of global precipitation extremes and change on societally relevant timescales, leading to improved high-resolution climate model representation of extreme rainfall processes. The INTENSE project is in conjunction with the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges Project (GEWEX) Science questions. The first step towards achieving this is to construct a new global sub-daily precipitation dataset. Data collection is ongoing and already covers North America, Europe, Asia and Australasia. Comprehensive, open source quality control software is being developed to set a new standard for verifying sub-daily precipitation data and a set of global hydroclimatic indices will be produced based upon stakeholder recommendations. This will provide a unique global data resource on sub-daily precipitation whose derived indices, e.g. monthly/annual maxima, will be freely available to the wider scientific community.

  17. Combination of radar and daily precipitation data to estimate meaningful sub-daily point precipitation extremes

    NASA Astrophysics Data System (ADS)

    Bárdossy, András; Pegram, Geoffrey

    2017-01-01

    The use of radar measurements for the space time estimation of precipitation has for many decades been a central topic in hydro-meteorology. In this paper we are interested specifically in daily and sub-daily extreme values of precipitation at gauged or ungauged locations which are important for design. The purpose of the paper is to develop a methodology to combine daily precipitation observations and radar measurements to estimate sub-daily extremes at point locations. Radar data corrected using precipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities of correcting systematic errors using the daily observations are investigated. Observed gauged daily amounts are interpolated to unsampled points and subsequently disaggregated using the sub-daily values obtained by the radar. Different corrections based on the spatial variability and the subdaily entropy of scaled rainfall distributions are used to provide unbiased corrections of short duration extremes. Additionally a statistical procedure not based on a matching day by day correction is tested. In this last procedure as we are only interested in rare extremes, low to medium values of rainfall depth were neglected leaving a small number of L days of ranked daily maxima in each set per year, whose sum typically comprises about 50% of each annual rainfall total. The sum of these L day maxima is first iterpolated using a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbour procedure. The daily sums are then disaggregated by using the relative values of the biggest L radar based days. Of course, the timings of radar and gauge maxima can be different, so the method presented here uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract the maxima of sub-hourly through to daily rainfall. The methodologies were tested in South Africa, where an S-band radar operated relatively continuously at

  18. Emotion regulation strategies in daily life: mindfulness, cognitive reappraisal and emotion suppression.

    PubMed

    Brockman, Robert; Ciarrochi, Joseph; Parker, Philip; Kashdan, Todd

    2017-03-01

    Most empirical studies of emotion regulation have relied on retrospective trait measures, and have not examined the link between daily regulatory strategies and every day emotional well-being. We used a daily diary methodology with multilevel modelling data analyses (n = 187) to examine the influence of three emotion regulation strategies (mindfulness, cognitive reappraisal and emotion suppression) on the experience of daily negative and positive affect. Our results suggested that daily mindfulness was associated with lower negative and higher positive affect whereas the converse pattern was found for daily emotion suppression; cognitive reappraisal was related to daily positive, but not negative affect. When daily mindfulness, suppression and reappraisal were included in the same models, these strategies predicted unique variance in emotional well-being. Random slope analyses revealed substantial variability in the utility of these strategies. Indeed the presumably "adaptive" cognitive reappraisal strategy seemed to confer no benefit to the regulation of negative affect in approximately half the sample. Additional analyses revealed that age moderates the effect of cognitive reappraisal on daily negative affect: Higher use of reappraisal was associated with more negative affect for adolescents (aged 17 to 19) but became associated with less negative affect with increasing age. We interpret these results in line with a contextual view of emotion regulation where no strategy is inherently "good" or "bad".

  19. Daily Bone Alignment With Limited Repeat CT Correction Rivals Daily Ultrasound Alignment for Prostate Radiotherapy

    SciTech Connect

    O'Daniel, Jennifer C.; Dong Lei Zhang Lifei; Wang He; Tucker, Susan L.; Kudchadker, Rajat J.; Lee, Andrew K.; Cheung, Rex; Cox, James D.; Kuban, Deborah A.; Mohan, Radhe

    2008-05-01

    Purpose: To compare the effectiveness of daily ultrasound (US)- and computed tomography (CT)-guided alignments with an off-line correction protocol using daily bone alignment plus a correction factor for systematic internal prostate displacement (CF{sub ID}). Methods and Materials: Ten prostate cancer patients underwent CT scans three times weekly using an integrated CT-linear accelerator system, followed by alignment using US for daily radiotherapy. Intensity-modulated radiotherapy plans were designed with our current clinical margins. The treatment plan was copied onto the repeat CT images and aligned using several methods: (1) bone alignment plus CF{sub ID} after three off-line CT scans (bone+3CT), (2) bone alignment plus CF{sub ID} after six off-line CT scans (bone+6CT), (3) US alignment, and (4) CT alignment. The accuracy of the repeated US and CT measurements to determine the CF{sub ID} was compared. The target dosimetric effect was quantified. Results: The CF{sub ID} for internal systematic prostate displacements was more accurately measured with limited repeat CT scans than with US (residual error, 0.0 {+-} 0.7 mm vs. 2.0 {+-} 3.2 mm). Bone+3CT, bone+6CT, and US provided equivalent prostate and seminal vesicle dose coverage, but bone+3CT and bone+6CT produced more precise daily alignments. Daily CT alignment provided the greatest target dose coverage. Conclusion: Daily bone alignment plus CF{sub ID} for internal systematic prostate displacement provided better daily alignment precision and equivalent dose coverage compared with daily US alignment. The CF{sub ID} should be based on at least three repeat CT scans, which could be collected before the start of treatment or during the first 3 treatment days. Daily bone alignment plus CF{sub ID} provides another option for accurate prostate cancer patient positioning.

  20. Interracial roommate relationships: negotiating daily interactions.

    PubMed

    Trail, Thomas E; Shelton, J Nicole; West, Tessa V

    2009-06-01

    Jobs, social group memberships, or living arrangements lead many people to interact every day with another person from a different racial background. Given that research has shown that interracial interactions are often stressful, it is important to know how these daily interactions unfold across time and what factors contribute to the success or failure of these interactions. Both members of same-race and mixed-race college roommate pairs completed daily questionnaires measuring their emotional experiences and their perceptions of their roommate. Results revealed that roommates in mixed-race dyads experienced less positive emotions and intimacy toward their roommates than did roommates in same-race dyads and that the experience of positive emotions declined over time for ethnic minority students with White roommates. Mediation analyses showed that the negative effects of roommate race were mediated by the level of intimacy-building behaviors performed by the roommate. Implications for future research and university policies are discussed.

  1. An introduction to quiet daily geomagnetic fields

    USGS Publications Warehouse

    Campbell, W.H.

    1989-01-01

    On days that are quiet with respect to solar-terrestrial activity phenomena, the geomagnetic field has variations, tens of gamma in size, with major spectral components at about 24, 12, 8, and 6 hr in period. These quiet daily field variations are primarily due to the dynamo currents flowing in the E region of the earth's ionosphere, are driven by the global thermotidal wind systems, and are dependent upon the local tensor conductivity and main geomagnetic field vector. The highlights of the behavior and interpretation of these quiet field changes, from their discovery in 1634 until the present, are discussed as an introduction to the special journal issue on Quiet Daily Geomagnetic Fields. ?? 1989 Birkha??user Verlag.

  2. Induction of testicular damage by daily methamphetamine administration in rats.

    PubMed

    Lin, Ji-Fan; Lin, Yi-Hsuan; Liao, Po-Cheng; Lin, Yi-Chia; Tsai, Te-Fu; Chou, Kuang-Yu; Chen, Hung-En; Tsai, Shiow-Chwen; Hwang, Thomas I-Sheng

    2014-02-28

    Methamphetamine (METH)-induced brain damage and apoptosis within the central nervous system are well documented. This study was conducted to investigate the toxic effects of daily METH administration on the testes in a rat model. Male Sprague-Dawley rats (5 weeks old, ~100 g, n = 64) were divided into two groups and treated with vehicle (saline, control) or METH (10 mg/kg) for 15, 30, 60 and 90 days. The results showed that daily administration of METH decreased the body, testicular and epididymis weights as well as the serum levels of total testosterone. The increased apoptotic index (Bad/Bcl2 expression ratio) and levels of cleaved caspase-3 indicated that apoptosis had occurred in the testes of the METH-treated rats. The oxidative stress levels increased as the reduced and oxidized glutathione (GSH/GSSG) ratio decreased. The overall sperm counts decreased at 15 and 90 days, where- as morphologically abnormal sperm counts increased at 30, 60 and 90 days in the METH-treated rats. This study demonstrates that daily exposure to METH significantly reduced the number and quality of sperm in rats. The underlying pathophysiological mechanisms likely include the reduction of serum testosterone levels and the increase of oxidative stress and apoptosis in the rat testes.

  3. Recognition of Daily Gestures with Wearable Inertial Rings and Bracelets.

    PubMed

    Moschetti, Alessandra; Fiorini, Laura; Esposito, Dario; Dario, Paolo; Cavallo, Filippo

    2016-08-22

    Recognition of activities of daily living plays an important role in monitoring elderly people and helping caregivers in controlling and detecting changes in daily behaviors. Thanks to the miniaturization and low cost of Microelectromechanical systems (MEMs), in particular of Inertial Measurement Units, in recent years body-worn activity recognition has gained popularity. In this context, the proposed work aims to recognize nine different gestures involved in daily activities using hand and wrist wearable sensors. Additionally, the analysis was carried out also considering different combinations of wearable sensors, in order to find the best combination in terms of unobtrusiveness and recognition accuracy. In order to achieve the proposed goals, an extensive experimentation was performed in a realistic environment. Twenty users were asked to perform the selected gestures and then the data were off-line analyzed to extract significant features. In order to corroborate the analysis, the classification problem was treated using two different and commonly used supervised machine learning techniques, namely Decision Tree and Support Vector Machine, analyzing both personal model and Leave-One-Subject-Out cross validation. The results obtained from this analysis show that the proposed system is able to recognize the proposed gestures with an accuracy of 89.01% in the Leave-One-Subject-Out cross validation and are therefore promising for further investigation in real life scenarios.

  4. Recognition of Daily Gestures with Wearable Inertial Rings and Bracelets

    PubMed Central

    Moschetti, Alessandra; Fiorini, Laura; Esposito, Dario; Dario, Paolo; Cavallo, Filippo

    2016-01-01

    Recognition of activities of daily living plays an important role in monitoring elderly people and helping caregivers in controlling and detecting changes in daily behaviors. Thanks to the miniaturization and low cost of Microelectromechanical systems (MEMs), in particular of Inertial Measurement Units, in recent years body-worn activity recognition has gained popularity. In this context, the proposed work aims to recognize nine different gestures involved in daily activities using hand and wrist wearable sensors. Additionally, the analysis was carried out also considering different combinations of wearable sensors, in order to find the best combination in terms of unobtrusiveness and recognition accuracy. In order to achieve the proposed goals, an extensive experimentation was performed in a realistic environment. Twenty users were asked to perform the selected gestures and then the data were off-line analyzed to extract significant features. In order to corroborate the analysis, the classification problem was treated using two different and commonly used supervised machine learning techniques, namely Decision Tree and Support Vector Machine, analyzing both personal model and Leave-One-Subject-Out cross validation. The results obtained from this analysis show that the proposed system is able to recognize the proposed gestures with an accuracy of 89.01% in the Leave-One-Subject-Out cross validation and are therefore promising for further investigation in real life scenarios. PMID:27556473

  5. Daily animal exposure and children's biological concepts.

    PubMed

    Geerdts, Megan S; Van de Walle, Gretchen A; LoBue, Vanessa

    2015-02-01

    A large body of research has focused on the developmental trajectory of children's acquisition of a theoretically coherent naive biology. However, considerably less work has focused on how specific daily experiences shape the development of children's knowledge about living things. In the current research, we investigated one common experience that might contribute to biological knowledge development during early childhood-pet ownership. In Study 1, we investigated how children interact with pets by observing 24 preschool-aged children with their pet cats or dogs and asking parents about their children's daily involvement with the pets. We found that most of young children's observed and reported interactions with their pets are reciprocal social interactions. In Study 2, we tested whether children who have daily social experiences with animals are more likely to attribute biological properties to animals than children without pets. Both 3- and 5-year-olds with pets were more likely to attribute biological properties to animals than those without pets. Similarly, both older and younger children with pets showed less anthropocentric patterns of extension of novel biological information. The results suggest that having pets may facilitate the development of a more sophisticated, human-inclusive representation of animals.

  6. Daily Interpersonal Events in Pain Patients

    PubMed Central

    Davis, Mary C.; Affleck, Glenn; Zautra, Alex J.; Tennen, Howard

    2008-01-01

    Action theory proposes that individuals actively shape and then respond to their environments, highlighting the role of stable person characteristics in the development and maintenance of life’s interpersonal difficulties. In this study, we adopted the action perspective in our examination of the daily lives of chronic pain patients with rheumatoid arthritis. Our evaluation of patients’ daily diary reports indicated that individuals played a more prominent role in shaping their positive versus their negative social worlds. The contribution of symptoms of ill health and demographic characteristics, as well as personality attributes were also examined as stable factors that predicted exposure to and appraisal of events. In addition to between-person measures, day to day variations in illness symptoms also played a key role in predicting their social experinces. Together, these findings suggest that stable person characteristics and within-person fluctuations in ill health are each tied to daily interpersonal experiences for those in chronic pain. More broadly, they point to the value of capturing the experiences of individuals intensively over time, an approach that can help to elaborate the contributions of both stable factors and circumstance in shaping our social contexts. PMID:16810668

  7. Understanding metropolitan patterns of daily encounters.

    PubMed

    Sun, Lijun; Axhausen, Kay W; Lee, Der-Horng; Huang, Xianfeng

    2013-08-20

    Understanding of the mechanisms driving our daily face-to-face encounters is still limited; the field lacks large-scale datasets describing both individual behaviors and their collective interactions. However, here, with the help of travel smart card data, we uncover such encounter mechanisms and structures by constructing a time-resolved in-vehicle social encounter network on public buses in a city (about 5 million residents). Using a population scale dataset, we find physical encounters display reproducible temporal patterns, indicating that repeated encounters are regular and identical. On an individual scale, we find that collective regularities dominate distinct encounters' bounded nature. An individual's encounter capability is rooted in his/her daily behavioral regularity, explaining the emergence of "familiar strangers" in daily life. Strikingly, we find individuals with repeated encounters are not grouped into small communities, but become strongly connected over time, resulting in a large, but imperceptible, small-world contact network or "structure of co-presence" across the whole metropolitan area. Revealing the encounter pattern and identifying this large-scale contact network are crucial to understanding the dynamics in patterns of social acquaintances, collective human behaviors, and--particularly--disclosing the impact of human behavior on various diffusion/spreading processes.

  8. Sex-specific daily spawning seaward migration of striped mullet Mugil cephalus in a coastal lagoon.

    PubMed

    Katselis, G; Koukou, K; Ramfos, A; Moutopoulos, D K

    2015-08-01

    The sex-specific daily spawning seaward migration of striped mullet Mugil cephalus was analysed in Palaiopotamos Lagoon (western Greek coast, eastern Mediterranean Sea) in an 86 day time series. The data set included the daily number of M. cephalus catches in barrier traps, as well as a time series of some weather variables. The analysis revealed an important linkage of the daily migration rate as well as a sex-specific response of the species to the lunar cycle and the short-term fluctuation of weather variables. The daily migration pattern of females was more persistent than that of males, indicating a possible female leadership role during the spawning migration. Multiregression models described quite accurately the sex-specific daily migration rates of the species, thus providing a potentially powerful tool regarding the lagoon fishery management of M. cephalus, especially in the context of climate change.

  9. Weather, season, and daily stroke admissions in Hong Kong

    NASA Astrophysics Data System (ADS)

    Goggins, William B.; Woo, Jean; Ho, Suzanne; Chan, Emily Y. Y.; Chau, P. H.

    2012-09-01

    Previous studies examining daily temperature and stroke incidence have given conflicting results. We undertook this retrospective study of all stroke admissions in those aged 35 years old and above to Hong Kong public hospitals from 1999 through 2006 in order to better understand the effects of meteorological conditions on stroke risk in a subtropical setting. We used Poisson Generalized Additive Models with daily hemorrhagic (HS) and ischemic stroke (IS) counts separately as outcomes, and daily mean temperature, humidity, solar radiation, rainfall, air pressure, pollutants, flu consultation rates, day of week, holidays, time trend and seasonality as predictors. Lagged effects of temperature, humidity and pollutants were also considered. A total of 23,457 HS and 107,505 IS admissions were analyzed. Mean daily temperature had a strong, consistent, negative linear association with HS admissions over the range (8.2-31.8°C) observed. A 1°C lower average temperature over the same day and previous 4 days (lags 0-4) being associated with a 2.7% (95% CI: 2.0-3.4%, P < .0.0001) higher admission rate after controlling for other variables. This association was stronger among older subjects and females. Higher lag 0-4 average change in air pressure from previous day was modestly associated with higher HS risk. The association between IS and temperature was weaker and apparent only below 22°C, with a 1°C lower average temperature (lags 0-13) below this threshold being associated with a 1.6% (95% CI:1.0-2.2%, P < 0.0001) higher IS admission rate. Pollutant levels were not associated with HS or IS. Future studies should examine HS and IS risk separately.

  10. Loneliness, Daily Pain, and Perceptions of Interpersonal Events in Adults with Fibromyalgia

    PubMed Central

    Wolf, Laurie Dempsey; Davis, Mary C.

    2014-01-01

    Objective This study examined whether individual differences in loneliness and/or daily exacerbations in loneliness relate to daily pain and frequency and perception of interpersonal events among individuals with fibromyalgia (FM). Methods 118 participants with FM completed electronic diaries each evening for 21 days to assess the occurrence of positive and negative interpersonal events, event appraisals, and pain. Multilevel modeling was used to examine relations of chronic and transitory loneliness to daily life outcomes, controlling for daily depressive symptoms. Results Chronic and transitory loneliness were associated with more frequent reports of negative and less frequent reports of positive interpersonal daily events, higher daily stress ratings and lower daily enjoyment ratings, and higher daily pain levels. Neither chronic nor transitory loneliness moderated the relations between daily negative events and either stress appraisals or pain. However, both chronic and transitory loneliness moderated the relation between daily positive events and enjoyment appraisals. Specifically, on days of greater numbers of positive events than usual, lonely people had larger boosts in enjoyment than did nonlonely people. Similarly, days with greater than usual numbers of positive events were related to larger boosts in enjoyment if an individual was also experiencing higher than usual loneliness levels. Conclusions Chronic and transient episodes of loneliness are associated with more negative daily social relations and pain. However, boosts in positive events yield greater boosts in day-to-day enjoyment of social relations for lonely versus nonlonely individuals, and during loneliness episodes, a finding that can inform future interventions for individuals with chronic pain. PMID:25180546

  11. 20 CFR 330.3 - Daily rate of compensation.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 20 Employees' Benefits 1 2014-04-01 2012-04-01 true Daily rate of compensation. 330.3 Section 330... INSURANCE ACT DETERMINATION OF DAILY BENEFIT RATES § 330.3 Daily rate of compensation. (a) Definition. An employee's daily rate of compensation is his or her straight-time rate of pay, including any...

  12. The Impact of Intercity Competition on Daily Newspaper Content.

    ERIC Educational Resources Information Center

    Lacy, Stephen

    A study examined whether intercity competition affects the content of daily newspapers and whether the content profile is consistent with the umbrella competition theory elaborated by James N. Rosse. Rosse's theory hypothesized four layers of newspaper competition--large metropolitan dailies, satellite daily papers, suburban dailies, and weekly…

  13. Difference in nephrotoxicity of vancomycin administered once daily and twice daily in rats.

    PubMed

    Konishi, Hiroki; Morita, Yukiko; Mizumura, Miyo; Iga, Ikumi; Nagai, Katsuhito

    2013-10-01

    We compared the degree of nephrotoxicity of vancomycin (VCM) administered once daily and twice daily in rats. VCM was intraperitoneally administered once daily to rats at a dose of 400 mg/kg (VCM-1-treated) or administered at a dose of 200 mg/kg twice daily at 12-hour intervals (VCM-2-treated) for 7 consecutive days. Creatinine clearance was decreased more markedly in VCM-1 rats relative to VCM-2 rats, although there was no significant difference in renal accumulation of VCM between the two groups. Renal superoxide dismutase activity was lower in VCM-1 rats than that in VCM-2 rats. The magnitude of histological change in kidney tissue was in agreement with the degree of alterations in the abovementioned biochemical values. These results suggest that the nephrotoxic effect of once-daily VCM administration is more pronounced than that of the twice-daily treatment. Our findings provide fundamental evidence for the advantage in choosing a divided VCM administration to attenuate nephrotoxicity.

  14. Map correlation method: Selection of a reference streamgage to estimate daily streamflow at ungaged catchments.

    USGS Publications Warehouse

    Archfield, Stacey A.; Vogel, Richard M.

    2010-01-01

    Daily streamflow time series are critical to a very broad range of hydrologic problems. Whereas daily streamflow time series are readily obtained from gaged catchments, streamflow information is commonly needed at catchments for which no measured streamflow information exists. At ungaged catchments, methods to estimate daily streamflow time series typically require the use of a reference streamgage, which transfers properties of the streamflow time series at a reference streamgage to the ungaged catchment. Therefore, the selection of a reference streamgage is one of the central challenges associated with estimation of daily streamflow at ungaged basins. The reference streamgage is typically selected by choosing the nearest streamgage; however, this paper shows that selection of the nearest streamgage does not provide a consistent selection criterion. We introduce a new method, termed the map-correlation method, which selects the reference streamgage whose daily streamflows are most correlated with an ungaged catchment. When applied to the estimation of daily streamflow at 28 streamgages across southern New England, daily streamflows estimated by a reference streamgage selected using the map-correlation method generally provides improved estimates of daily streamflow time series over streamflows estimated by the selection and use of the nearest streamgage. The map correlation method could have potential for many other applications including identifying redundancy and uniqueness in a streamgage network, calibration of rainfall runoff models at ungaged sites, as well as for use in catchment classification.

  15. A Hybrid Architecture of Neural Networks for Daily Streamflow Forecasting

    NASA Astrophysics Data System (ADS)

    Moradkhani, H.

    2001-12-01

    Streamflow forecasting has always been a challenging task for water resources engineers and managers and the major component of water resources system control. For years numerous techniques have been suggested and employed for streamflow forecasting. Computational Neural Networks (NNs), which are capable of recognizing hidden patterns in data, have recently become popular in many hydrologic applications. In this study, hybrid NN is developed for one step ahead forecasting of daily streamflow. Radial Basis Function (RBF) composed of a group of Gausian functions is used in conjunction with Self-Organizing Feature Map (SOFM) used in data classification. RBF transfers those classified input variables into the desired output estimate. Eight years of daily rainfall, streamflow, and temperature in Salt River basin were used for calibration and validation. Since 60%-80% of the water supply produced by the basin comes in the form of snow, further consideration of the existing time delay of snow melting process in the basin to the watershed outlet is important. Therefore two separated settings were considered in this simulation: the first one only includes several short-term daily rainfall and streamflow in the input sequence; the second setting, on the other hand, includes a longer time period (three-months) of temperature data sequence. Various statistical analyses, such as root mean square error, bias estimate, noise to signal ratio, and correlation coefficients of estimates and observations, were done to evaluate the forecast models. The preliminary results show that the accuracy of the model once considering the long-term effect of the snowmelt is conspicuous with respect to short-term effect. The effectiveness of the proposed and current operational models is evaluated.

  16. Towards a new high resolution gridded daily precipitation dataset over Europe

    NASA Astrophysics Data System (ADS)

    Toreti, Andrea; Naveau, Philippe

    2016-04-01

    The availability of high resolution daily gridded observational datasets is essential in many applications and to properly evaluate regional climate models. As the horizontal resolution of such models has significantly increased in recent modelling exercises (e.g., Euro-Cordex), while the one of the available observational datasets has remained constant (approx. 25km), new approaches are needed to develop gridded dataset of daily precipitation. Here, we discuss a statistical conceptual framework to combine data from neighbouring stations and model outputs. Our approach is based on recent statistical models for precipitation distributions, meshed with a data assimilation scheme. Our study focuses on the European region.

  17. Forecasting daily streamflow using online sequential extreme learning machines

    NASA Astrophysics Data System (ADS)

    Lima, Aranildo R.; Cannon, Alex J.; Hsieh, William W.

    2016-06-01

    While nonlinear machine methods have been widely used in environmental forecasting, in situations where new data arrive continually, the need to make frequent model updates can become cumbersome and computationally costly. To alleviate this problem, an online sequential learning algorithm for single hidden layer feedforward neural networks - the online sequential extreme learning machine (OSELM) - is automatically updated inexpensively as new data arrive (and the new data can then be discarded). OSELM was applied to forecast daily streamflow at two small watersheds in British Columbia, Canada, at lead times of 1-3 days. Predictors used were weather forecast data generated by the NOAA Global Ensemble Forecasting System (GEFS), and local hydro-meteorological observations. OSELM forecasts were tested with daily, monthly or yearly model updates. More frequent updating gave smaller forecast errors, including errors for data above the 90th percentile. Larger datasets used in the initial training of OSELM helped to find better parameters (number of hidden nodes) for the model, yielding better predictions. With the online sequential multiple linear regression (OSMLR) as benchmark, we concluded that OSELM is an attractive approach as it easily outperformed OSMLR in forecast accuracy.

  18. Retrieving daily global solar radiation from routine climate variables

    NASA Astrophysics Data System (ADS)

    Moradi, Isaac; Mueller, Richard; Perez, Richard

    2014-05-01

    Solar radiation is an important variable for studies related to solar energy applications, meteorology, climatology, hydrology, and agricultural meteorology. However, solar radiation is not routinely measured at meteorological stations; therefore, it is often required to estimate it using other techniques such as retrieving from satellite data or estimating using other geophysical variables. Over the years, many models have been developed to estimate solar radiation from other geophysical variables such as temperature, rainfall, and sunshine duration. The aim of this study was to evaluate six of these models using data measured at four independent worldwide networks. The dataset included 13 stations from Australia, 25 stations from Germany, 12 stations from Saudi Arabia, and 48 stations from the USA. The models require either sunshine duration hours (Ångstrom) or daily range of air temperature (Bristow and Campbell, Donatelli and Bellocchi, Donatelli and Campbell, Hargreaves, and Hargreaves and Samani) as input. According to the statistical parameters, Ångstrom and Bristow and Campbell indicated a better performance than the other models. The bias and root mean square error for the Ångstrom model were less than 0.25 MJ m2 day-1 and 2.25 MJ m2 day-1, respectively, and the correlation coefficient was always greater than 95 %. Statistical analysis using Student's t test indicated that the residuals for Ångstrom, Bristow and Campbell, Hargreaves, and Hargreaves and Samani are not statistically significant at the 5 % level. In other words, the estimated values by these models are statistically consistent with the measured data. Overall, given the simplicity and performance, the Ångstrom model is the best choice for estimating solar radiation when sunshine duration measurements are available; otherwise, Bristow and Campbell can be used to estimate solar radiation using daily range of air temperature.

  19. Daily Spiritual Experiences and Adolescent Treatment Response

    PubMed Central

    LEE, MATTHEW T.; VETA, PAIGE S.; JOHNSON, BYRON R.; PAGANO, MARIA E.

    2014-01-01

    The purpose of this study is to explore changes in belief orientation during treatment and the impact of increased daily spiritual experiences (DSE) on adolescent treatment response. One-hundred ninety-five adolescents court-referred to a 2-month residential treatment program were assessed at intake and discharge. Forty percent of youth who entered treatment as agnostic or atheist identified themselves as spiritual or religious at discharge. Increased DSE was associated with greater likelihood of abstinence, increased prosocial behaviors, and reduced narcissistic behaviors. Results indicate a shift in DSE that improves youth self-care and care for others that may inform intervention approaches for adolescents with addiction. PMID:25525291

  20. BOREAS TE-21 Daily Surface Meteorological Data

    NASA Technical Reports Server (NTRS)

    Kimball, John; Hall, Forrest G. (Editor); Papagno, Andrea (Editor)

    2000-01-01

    The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-21 (Terrestrial Ecology) team collected data sets in support of its efforts to characterize and interpret information on the meteorology of boreal forest areas. Daily meteorological data were derived from half-hourly BOREAS tower flux (TF) and Automatic Meteorological Station (AMS) mesonet measurements collected in the Southern and Northern Study Areas (SSA and NSA) for the period of 01 Jan 1994 until 31 Dec 1994. The data were stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

  1. Passive wireless sensor systems can recognize activites of daily living.

    PubMed

    Urwyler, Prabitha; Stucki, Reto; Muri, Rene; Mosimann, Urs P; Nef, Tobias

    2015-08-01

    The ability to determine what activity of daily living a person performs is of interest in many application domains. It is possible to determine the physical and cognitive capabilities of the elderly by inferring what activities they perform in their houses. Our primary aim was to establish a proof of concept that a wireless sensor system can monitor and record physical activity and these data can be modeled to predict activities of daily living. The secondary aim was to determine the optimal placement of the sensor boxes for detecting activities in a room. A wireless sensor system was set up in a laboratory kitchen. The ten healthy participants were requested to make tea following a defined sequence of tasks. Data were collected from the eight wireless sensor boxes placed in specific places in the test kitchen and analyzed to detect the sequences of tasks performed by the participants. These sequence of tasks were trained and tested using the Markov Model. Data analysis focused on the reliability of the system and the integrity of the collected data. The sequence of tasks were successfully recognized for all subjects and the averaged data pattern of tasks sequences between the subjects had a high correlation. Analysis of the data collected indicates that sensors placed in different locations are capable of recognizing activities, with the movement detection sensor contributing the most to detection of tasks. The central top of the room with no obstruction of view was considered to be the best location to record data for activity detection. Wireless sensor systems show much promise as easily deployable to monitor and recognize activities of daily living.

  2. Air pollution and daily mortality in Seoul and Ulsan, Korea.

    PubMed Central

    Lee, J T; Shin, D; Chung, Y

    1999-01-01

    The relationship between air pollution and daily mortality for the period 1991-1995 was examined in two Korean cities, Seoul and Ulsan. The observed concentrations of sulfur dioxide (SO2; mean = 28.7 ppb), ozone (O3; mean = 29.2 ppb), and total suspended particulates (TSP; mean = 82.3 microg/m3) during the study period were at levels below Korea's current ambient air quality standards. Daily death counts were regressed separately in the two cities, using Poisson regression on SO2, O3, and/or TSP controlling for variability in the weather and seasons. When considered singly in Poisson regression models controlling for seasonal variations and weather conditions, the nonaccidental mortality associated with a 50-ppb increment in a 3-day moving average of SO2 concentrations, including the concurrent day and the preceding 2 days, was 1.078 [95% confidence interval (CI), 1.057-1.099] for Seoul and 1.051 (CI, 0.991-1.115) for Ulsan. The rate ratio was 1.051 (CI, 1.031-1.072) in Seoul and 0.999 (CI, 0. 961-1.039) in Ulsan per 100 microg/m3 for TSP, and 1.015 (CI, 1. 005-1.025) in Seoul and 1.020 (0.889-1.170) in Ulsan per 50 ppb for 1-hr maximum O3. When TSP was considered simultaneously with other pollutants, the TSP association was no longer significant. We observed independent pollution effects on daily mortality even after using various approaches to control for either weather or seasonal variables in the regression model. This study demonstrated increased mortality associated with air pollution at both SO2 and O3 levels below the current World Health Organization recommendations. Images Figure 1 Figure 2 Figure 3 PMID:9924011

  3. Performance comparison of three predictor selection methods for statistical downscaling of daily precipitation

    NASA Astrophysics Data System (ADS)

    Yang, Chunli; Wang, Ninglian; Wang, Shijin; Zhou, Liang

    2016-10-01

    Predictor selection is a critical factor affecting the statistical downscaling of daily precipitation. This study provides a general comparison between uncertainties in downscaled results from three commonly used predictor selection methods (correlation analysis, partial correlation analysis, and stepwise regression analysis). Uncertainty is analyzed by comparing statistical indices, including the mean, variance, and the distribution of monthly mean daily precipitation, wet spell length, and the number of wet days. The downscaled results are produced by the artificial neural network (ANN) statistical downscaling model and 50 years (1961-2010) of observed daily precipitation together with reanalysis predictors. Although results show little difference between downscaling methods, stepwise regression analysis is generally the best method for selecting predictors for the ANN statistical downscaling model of daily precipitation, followed by partial correlation analysis and then correlation analysis.

  4. Vestibular Function and Activities of Daily Living

    PubMed Central

    Harun, Aisha; Semenov, Yevgeniy R.; Agrawal, Yuri

    2015-01-01

    Objective: Vestibular dysfunction increases with age and is associated with mobility difficulties and fall risk in older individuals. We evaluated whether vestibular function influences the ability to perform activities of daily living (ADLs). Method: We analyzed the 1999 to 2004 National Health and Nutrition Examination Survey of adults aged older than 40 years (N = 5,017). Vestibular function was assessed with the Modified Romberg test. We evaluated the association between vestibular function and difficulty level in performing specific basic and instrumental ADLs, and total number of ADL impairments. Results: Vestibular dysfunction was associated with significantly higher odds of difficulty with nine ADLs, most strongly with difficulty managing finances (odds ratio [OR] = 2.64, 95% confidence interval [CI] = [1.18, 5.90]). In addition, vestibular dysfunction was associated with a significantly greater number of ADL impairments (β = .21, 95% CI = [0.09, 0.33]). This effect size was comparable with the influence of heavy smoking (β = .21, 95% CI = [0.06, 0.36]) and hypertension (β = .10, 95% CI = [0.02, 0.18]) on the number of ADL impairments. Conclusion: Vestibular dysfunction significantly influences ADL difficulty, most strongly with a cognitive rather than mobility-based task. These findings underscore the importance of vestibular inputs for both cognitive and physical daily activities. PMID:26753170

  5. Chronic daily headache in the elderly.

    PubMed

    Özge, Aynur

    2013-12-01

    Disabling headache disorders are ubiquitous in all age groups, including the elderly, yet they are under-recognized, underdiagnosed and undertreated worldwide. Surveys and clinic-based research reports on headache disorders in elderly populations are extremely limited in number. Chronic daily headache (CDH) is an important and growing subtype of primary headache disorders, associated with increased burden and disruption to quality of life. CDH can be divided into two forms, based on headache duration. Common forms of primary headache disorders of long duration (>4 hours) were comprehensively defined in the third edition of the International Classification of Headache Disorders (ICHD-3 beta). These include chronic migraine, chronic tension-type headache, new daily persistent headache, and hemicrania continua. Rarer short-duration (<4 hours) forms of CDH are chronic cluster headache, chronic paroxysmal hemicrania, SUNCT, and hypnic headache. Accurate diagnosis, management, and relief of the burden of CDH in the elderly population present numerous unique challenges as the "aging world" continues to grow. In order to implement appropriate coping strategies for the elderly, it is essential to establish the correct diagnosis at each step and to exercise caution in differentiating from secondary causes, while always taking into consideration the unique needs and limitations of the aged body.

  6. Daily Rhythms in Mobile Telephone Communication

    PubMed Central

    Aledavood, Talayeh; López, Eduardo; Roberts, Sam G. B.; Reed-Tsochas, Felix; Moro, Esteban; Dunbar, Robin I. M.; Saramäki, Jari

    2015-01-01

    Circadian rhythms are known to be important drivers of human activity and the recent availability of electronic records of human behaviour has provided fine-grained data of temporal patterns of activity on a large scale. Further, questionnaire studies have identified important individual differences in circadian rhythms, with people broadly categorised into morning-like or evening-like individuals. However, little is known about the social aspects of these circadian rhythms, or how they vary across individuals. In this study we use a unique 18-month dataset that combines mobile phone calls and questionnaire data to examine individual differences in the daily rhythms of mobile phone activity. We demonstrate clear individual differences in daily patterns of phone calls, and show that these individual differences are persistent despite a high degree of turnover in the individuals’ social networks. Further, women’s calls were longer than men’s calls, especially during the evening and at night, and these calls were typically focused on a small number of emotionally intense relationships. These results demonstrate that individual differences in circadian rhythms are not just related to broad patterns of morningness and eveningness, but have a strong social component, in directing phone calls to specific individuals at specific times of day. PMID:26390215

  7. New developments on the homogenization of Canadian daily temperature data

    NASA Astrophysics Data System (ADS)

    Vincent, Lucie A.; Wang, Xiaolan L.

    2010-05-01

    Long-term and homogenized surface air temperature datasets had been prepared for the analysis of climate trends in Canada (Vincent and Gullett 1999). Non-climatic steps due to instruments relocation/changes and changes in observing procedures were identified in the annual mean of the daily maximum and minimum temperatures using a technique based on regression models (Vincent 1998). Monthly adjustments were derived from the regression models and daily adjustments were obtained from an interpolation procedure using the monthly adjustments (Vincent et al. 2002). Recently, new statistical tests have been developed to improve the power of detecting changepoints in climatological data time series. The penalized maximal t (PMT) test (Wang et al. 2007) and the penalized maximal F (PMF) test (Wang 2008b) were developed to take into account the position of each changepoint in order to minimize the effect of unequal and small sample size. A software package RHtestsV3 (Wang and Feng 2009) has also been developed to implement these tests to homogenize climate data series. A recursive procedure was developed to estimate the annual cycle, linear trend, and lag-1 autocorrelation of the base series in tandem, so that the effect of lag-1 autocorrelation is accounted for in the tests. A Quantile Matching (QM) algorithm (Wang 2009) was also developed for adjusting Gaussian daily data so that the empirical distributions of all segments of the detrended series match each other. The RHtestsV3 package was used to prepare a second generation of homogenized temperatures in Canada. Both the PMT test and the PMF test were applied to detect shifts in monthly mean temperature series. Reference series was used in conducting a PMT test. Whenever possible, the main causes of the shifts were retrieved through historical evidence such as the station inspection reports. Finally, the QM algorithm was used to adjust the daily temperature series for the artificial shifts identified from the respective

  8. Does negative affect mediate the relationship between daily PTSD symptoms and daily alcohol involvement in female rape victims? Evidence from 14 days of interactive voice response assessment

    PubMed Central

    Cohn, Amy; Hagman, Brett T.; Moore, Kathleen; Mitchell, Jessica; Ehlke, Sarah

    2014-01-01

    The negative reinforcement model of addiction posits that individuals may use alcohol to reduce with negative affective (NA) distress. The current study investigated the mediating effect of daily NA on the relationship between daily PTSD symptoms and same-day and next-day alcohol involvement (consumption and desire to drink) in a sample of 54 non-treatment-seeking female rape victims who completed 14 days of interactive voice response assessment. The moderating effect of lifetime alcohol use disorder diagnosis (AUD) on daily relationships was also examined. Multilevel models suggested that NA mediated the relationship between PTSD and same-day, but not next-day alcohol involvement. NA was greater on days characterized by more severe PTSD symptoms, and alcohol consumption and desire to drink were greater on days characterized by higher NA. Further, daily PTSD symptoms and NA were more strongly associated with same-day (but not next-day) alcohol consumption and desire to drink for women with an AUD than without. Results suggest that NA plays an important role in female rape victims’ daily alcohol use. Differences between women with and without an AUD indicate the need for treatment matching to sub-types of female rape victims. PMID:24731112

  9. Daily oral iron supplementation during pregnancy

    PubMed Central

    Peña-Rosas, Juan Pablo; De-Regil, Luz Maria; Dowswell, Therese; Viteri, Fernando E

    2014-01-01

    Background Iron and folic acid supplementation has been the preferred intervention to improve iron stores and prevent anaemia among pregnant women, and it may also improve other maternal and birth outcomes. Objectives To assess the effects of daily oral iron supplements for pregnant women, either alone or in conjunction with folic acid, or with other vitamins and minerals as a public health intervention. Search methods We searched the Cochrane Pregnancy and Childbirth Group’s Trials Register (2 July 2012). We also searched the WHO International Clinical Trials Registry Platform (ICTRP) (2 July 2012) and contacted relevant organisations for the identification of ongoing and unpublished studies. Selection criteria Randomised or quasi-randomised trials evaluating the effects of oral preventive supplementation with daily iron, iron + folic acid or iron + other vitamins and minerals during pregnancy. Data collection and analysis We assessed the methodological quality of trials using standard Cochrane criteria. Two review authors independently assessed trial eligibility, extracted data and conducted checks for accuracy. Main results We included 60 trials. Forty-three trials, involving more than 27,402 women, contributed data and compared the effects of daily oral supplements containing iron versus no iron or placebo. Overall, women taking iron supplements were less likely to have low birthweight newborns (below 2500 g) compared with controls (8.4% versus 10.2%, average risk ratio (RR) 0.81; 95% confidence interval (CI) 0.68 to 0.97, 11 trials, 8480 women) and mean birthweight was 30.81 g greater for those infants whose mothers received iron during pregnancy (average mean difference (MD) 30.81; 95% CI 5.94 to 55.68, 14 trials, 9385 women). Preventive iron supplementation reduced the risk of maternal anaemia at term by 70% (RR 0.30; 95% CI 0.19 to 0.46, 14 trials, 2199 women) and iron deficiency at term by 57% (RR 0.43; 95% CI 0.27 to 0.66, seven trials, 1256 women

  10. Daily Air Temperature and Electricity Load in Spain.

    NASA Astrophysics Data System (ADS)

    Valor, Enric; Meneu, Vicente; Caselles, Vicente

    2001-08-01

    Weather has a significant impact on different sectors of the economy. One of the most sensitive is the electricity market, because power demand is linked to several weather variables, mainly the air temperature. This work analyzes the relationship between electricity load and daily air temperature in Spain, using a population-weighted temperature index. The electricity demand shows a significant trend due to socioeconomic factors, in addition to daily and monthly seasonal effects that have been taken into account to isolate the weather influence on electricity load. The results indicate that the relationship is nonlinear, showing a `comfort interval' of ±3°C around 18°C and two saturation points beyond which the electricity load no longer increases. The analysis has also revealed that the sensitivity of electricity load to daily air temperature has increased along time, in a higher degree for summer than for winter, although the sensitivity in the cold season is always more significant than in the warm season. Two different temperature-derived variables that allow a better characterization of the observed relationship have been used: the heating and cooling degree-days. The regression of electricity data on them defines the heating and cooling demand functions, which show correlation coefficients of 0.79 and 0.87, and predicts electricity load with standard errors of estimate of ±4% and ±2%, respectively. The maximum elasticity of electricity demand is observed at 7 cooling degree-days and 9 heating degree-days, and the saturation points are reached at 11 cooling degree-days and 13 heating degree-days, respectively. These results are helpful in modeling electricity load behavior for predictive purposes.

  11. Daily Aspirin May Help Prevent Some Recurrent Miscarriages

    MedlinePlus

    ... https://medlineplus.gov/news/fullstory_163515.html Daily Aspirin May Help Prevent Some Recurrent Miscarriages Approach seemed ... as simple as taking a daily low-dose aspirin could help prevent a recurrence. The intervention appears ...

  12. Distribution of some daily and seasonal events in relation to changes of physical factors

    NASA Astrophysics Data System (ADS)

    Dreisig, H.; Nachman, G.

    1983-03-01

    A special case of the Weibull distribution model is used in describing the course of behavioural transformation processes in relation to some cyclic physical factor. The model assumes that the rate of the process increases, the less inhibiting the physical factor, and the faster the factor changes. However, due to some resistance or a depletion, the rate slows down, the further the process progresses. The model was tested on the daily onset of activity in nocturnal insects, daily roosting flight of blackbirds, dark and light adaptation by pigment migration in insect eyes, photoperiodic response of an insect, and daily emergence of tiger beetles. The assumptions of the model are tested and discussed. One of these is violated in unnaturally fast changes of the physical factor because the process reaches some constant minimum duration, and proportionality between rate of process and rate of factor can no longer be maintained.

  13. 1 CFR 6.3 - Daily lists of parts affected.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 1 General Provisions 1 2010-01-01 2010-01-01 false Daily lists of parts affected. 6.3 Section 6.3 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER INDEXES AND ANCILLARIES § 6.3 Daily lists of parts affected. (a) Each daily issue of the Federal Register shall carry...

  14. 1 CFR 6.1 - Index to daily issues.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 1 General Provisions 1 2010-01-01 2010-01-01 false Index to daily issues. 6.1 Section 6.1 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER INDEXES AND ANCILLARIES § 6.1 Index to daily issues. Each daily issue of the Federal Register shall be appropriately indexed....

  15. 1 CFR 6.3 - Daily lists of parts affected.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 1 General Provisions 1 2011-01-01 2011-01-01 false Daily lists of parts affected. 6.3 Section 6.3 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER INDEXES AND ANCILLARIES § 6.3 Daily lists of parts affected. (a) Each daily issue of the Federal Register shall carry...

  16. 1 CFR 6.1 - Index to daily issues.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 1 General Provisions 1 2011-01-01 2011-01-01 false Index to daily issues. 6.1 Section 6.1 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER INDEXES AND ANCILLARIES § 6.1 Index to daily issues. Each daily issue of the Federal Register shall be appropriately indexed....

  17. 20 CFR 330.3 - Daily rate of compensation.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Daily rate of compensation. 330.3 Section 330.3 Employees' Benefits RAILROAD RETIREMENT BOARD REGULATIONS UNDER THE RAILROAD UNEMPLOYMENT INSURANCE ACT DETERMINATION OF DAILY BENEFIT RATES § 330.3 Daily rate of compensation. (a) Definition....

  18. 20 CFR 330.2 - Computation of daily benefit rate.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Computation of daily benefit rate. 330.2 Section 330.2 Employees' Benefits RAILROAD RETIREMENT BOARD REGULATIONS UNDER THE RAILROAD UNEMPLOYMENT INSURANCE ACT DETERMINATION OF DAILY BENEFIT RATES § 330.2 Computation of daily benefit rate. (a)...

  19. Racial Differences in Exposure and Reactivity to Daily Family Stressors

    ERIC Educational Resources Information Center

    Cichy, Kelly E.; Stawski, Robert S.; Almeida, David M.

    2012-01-01

    Using data from the National Study of Daily Experiences, the authors examined racial differences in exposure and reactivity to daily stressors involving family members. Respondents included African American and European American adults age 34 to 84 (N = 1,931) who participated in 8 days of daily interviews during which they reported on daily…

  20. Daily simulations of urban heat load in Vienna for 2011

    NASA Astrophysics Data System (ADS)

    Hollosi, Brigitta; Zuvela-Aloise, Maja; Koch, Roland

    2014-05-01

    In this study, the dynamical urban climate model MUKLIMO3 (horizontal resolution of 100 m) is uni-directionally coupled with the operational weather forecast model ALARO-ALADIN of the ZAMG (horizontal resolution of 4.8 km) to simulate the development of the urban heat island in Vienna on a daily basis. The aim is to evaluate the performance of the urban climate model applied for climatological studies in a weather prediction mode. The focus of the investigation is on assessment of the urban heat load during day-time. We used the archived daily forecast data for the summer period in 2011 (April - October) as input data for the urban climate model. The high resolution simulations were initialized with vertical profiles of temperature and relative humidity and prevailing wind speed and direction in the rural area near the city in the early morning hours. The model output for hourly temperature and relative humidity has been evaluated against the monitoring data at 9 weather stations in the area of the city. Additionally, spatial gradients in temperature were evaluated by comparing the grid point values with the data collected during a mobile measuring campaign taken on a multi-vehicle bicycle tour on the 7th of July, 2011. The results show a good agreement with observations on a district scale. Particular challenge in the modeling approach is achieving robust and numerically stable model solutions for different weather situation. Therefore, we analyzed modeled wind patterns for different atmospheric conditions in the summer period. We found that during the calm hot days, due to the inhomogeneous surface and complex terrain, the local-scale temperature gradients can induce strong anomalies, which in turn could affect the circulation on a larger scale. However, these results could not be validated due to the lack of observations. In the following years extreme hot conditions are very likely to occur more frequently and with higher intensity. Combining urban climate

  1. Day-to-day variations in health behaviors and daily functioning: two intensive longitudinal studies.

    PubMed

    Flueckiger, Lavinia; Lieb, Roselind; Meyer, Andrea H; Witthauer, Cornelia; Mata, Jutta

    2017-04-01

    In two intensive longitudinal studies we examined the daily dynamics in health behaviors and their associations with two important indicators of young adults' daily functioning, namely, affect and academic performance. Over a period of 8 months, university students (Study 1: N = 292; Study 2: N = 304) reported sleep, physical activity, snacking, positive and negative affect, and learning goal achievement. A subsample wore an actigraph to provide an additional measurement of sleep and physical activity and participated in a controlled laboratory snacking situation. Multilevel structural equation models showed that better day-to-day sleep quality or more physical activity than usual, but not snacking, were associated with improved daily functioning, namely, affect and learning goal achievement. Importantly, self-report measurements of health behaviors correlated with behavioral measurements. These findings have the potential to inform health promotion programs aimed at supporting young adults in their daily functioning in good physical and mental health.

  2. Depressive symptoms in native and immigrant adolescents: the role of critical life events and daily hassles.

    PubMed

    Stefanek, Elisabeth; Strohmeier, Dagmar; Fandrem, Hildegunn; Spiel, Christiane

    2012-03-01

    The present study compared native Austrian, first and second generation immigrant adolescents regarding their level of depressive symptoms, critical live events, and daily hassles. Furthermore, the associations between these constructs were tested in the three groups. The sample comprised 330 native Austrian (52.1% girls), 120 first generation immigrants (49.2% girls and 159 second generation immigrants (54.2% girls) aged 14-19 (M=15.61). Compared with native adolescents, first generation immigrant adolescents reported more depressive symptoms and daily hassles related to parents, the self, leisure, romantic partner, and future, whilst second generation immigrant adolescents reported more daily hassles related to parents, school, and romantic partner. Controlling for gender, multiple group structural equation models revealed that daily hassles fully mediated the path between critical live events and depressive symptoms in all three groups of adolescents. Implications for future research on immigrant adolescents' psychological well-being are discussed.

  3. Psychological control in daily parent-child interactions increases children's negative emotions.

    PubMed

    Aunola, Kaisa; Tolvanen, Asko; Viljaranta, Jaana; Nurmi, Jari-Erik

    2013-06-01

    The aim of the present study was to investigate the temporal dynamics between parental behaviors in daily interactions with their offspring, that is, affection and psychological control, and children's negative emotions. The participants were 152 Finnish families with a 6- to 7-year-old child. Children's negative emotions and parental affection and psychological control in interactions with their child were measured daily using diary questionnaires filled in by the mothers and fathers over 7 successive days. The results of multilevel modeling showed that psychological control applied by mothers and fathers in daily interactions with their child leads to an increase in negative emotions in the child. Parental affection in daily interactions with their child was not associated with the child's negative emotions.

  4. Non-Invasive Investigation of Bone Adaptation in Humans to Cumulative Daily Mechanical Loading

    NASA Technical Reports Server (NTRS)

    Whalen, Robert; Cleek, Tammy; Sode, Miki

    2003-01-01

    The goal of our research is to better understand the functional relationship between cumulative daily skeletal loading generated by daily activity and the regulation of bone density and bone structure. We have proposed the calcaneus and tibia as useful model bone sites loaded by internal forces in equilibrium with the ground reaction force during gait. The daily history of the ground reaction force is a good relative measure of daily lower limb and calcaneal loading that can be compared to bone density and structure of the calcaneus and cross-sectional geometry of the tibia and fibula. Over the past several years, we have developed image-processing technologies to improve our ability to measure bone density and structure in the calcaneus and lower leg non-invasively with computed tomography and bone densitometry, or DXA. The objective of our current research effort is to determine the accuracy and precision of our CT and DXA image processing methods.

  5. Service Workers' Chain Reactions to Daily Customer Mistreatment: Behavioral Linkages, Mechanisms, and Boundary Conditions.

    PubMed

    Chi, Nai-Wen; Yang, Jixia; Lin, Chia-Ying

    2016-10-27

    Drawing on the stressor-emotion model, we examine how customer mistreatment can evoke service workers' passive forms of deviant behaviors (i.e., work withdrawal behavior [WWB]) and negative impacts on their home life (i.e., work-family conflict [WFC]), and whether individuals' core self-evaluations and customer service training can buffer the negative effects of customer mistreatment. Using the experience sampling method, we collect daily data from 77 customer service employees for 10 consecutive working days, yielding 546 valid daily responses. The results show that daily customer mistreatment increases service workers' daily WWB and WFC through negative emotions. Furthermore, employees with high core self-evaluations and employees who received customer service training are less likely to experience negative emotions when faced with customer mistreatment, and thus are less likely to engage in WWB or provoke WFC. (PsycINFO Database Record

  6. Resilience in Daily Occupations of Indonesian Mothers of Children With Autism Spectrum Disorder.

    PubMed

    Santoso, Tri Budi; Ito, Yuko; Ohshima, Nobuo; Hidaka, Mikiyo; Bontje, Peter

    2015-01-01

    This qualitative study investigated how resilience functions in the context of daily occupations for mothers of children with autism spectrum disorder (ASD). Fourteen mothers of children with ASD participated in two focus groups that were used to elicit stories of the mothers' resilience in daily occupations. A constant comparative method was used for data analysis. A model of resilience in daily occupations of mothers of children with ASD was developed consisting of four categories: (1) creating and re-creating accepting conditions, (2) finding solutions, (3) striving for balance among daily occupations, and (4) thinking about the child's future. Sources of resilience were found to reside in both the mothers themselves and their social environments. Occupational therapy practitioners can use these findings in developing supportive approaches aimed at mothers, family members, and other people in the lives of children with ASD.

  7. Bursts of Self-Conscious Emotions in the Daily Lives of Emerging Adults

    PubMed Central

    Conroy, David E.; Ram, Nilam; Pincus, Aaron L.; Rebar, Amanda L.

    2015-01-01

    Self-conscious emotions play a role in regulating daily achievement strivings, social behavior, and health, but little is known about the processes underlying their daily manifestation. Emerging adults (n = 182) completed daily diaries for eight days and multilevel models were estimated to evaluate whether, how much, and why their emotions varied from day-to-day. Within-person variation in authentic pride was normally-distributed across people and days whereas the other emotions were burst-like and characterized by zero-inflated, negative binomial distributions. Perceiving social interactions as generally communal increased the odds of hubristic pride activation and reduced the odds of guilt activation; daily communal behavior reduced guilt intensity. Results illuminated processes through which meaning about the self-in-relation-to-others is constructed during a critical period of development. PMID:25859164

  8. Regulating positive and negative emotions in daily life.

    PubMed

    Nezlek, John B; Kuppens, Peter

    2008-06-01

    The present study examined how people regulate their emotions in daily life and how such regulation is related to their daily affective experience and psychological adjustment. Each day for an average of 3 weeks, participants described how they had regulated their emotions in terms of the reappraisal and suppression (inhibiting the expression) of positive and negative emotions, and they described their emotional experience, self-esteem, and psychological adjustment in terms of Beck's triadic model of depression. Reappraisal was used more often than suppression, and suppressing positive emotions was used less than the other three strategies. In general, regulation through reappraisal was found to be beneficial, whereas regulation by suppression was not. Reappraisal of positive emotions was associated with increases in positive affect, self-esteem, and psychological adjustment, whereas suppressing positive emotions was associated with decreased positive emotion, self-esteem, and psychological adjustment, and increased negative emotions. Moreover, relationships between reappraisal and psychological adjustment and self-esteem were mediated by experienced positive affect, whereas relationships between suppression of positive emotions and self-esteem adjustment were mediated by negative affect.

  9. Poorest countries experience earlier anthropogenic emergence of daily temperature extremes

    NASA Astrophysics Data System (ADS)

    Harrington, Luke J.; Frame, David J.; Fischer, Erich M.; Hawkins, Ed; Joshi, Manoj; Jones, Chris D.

    2016-05-01

    Understanding how the emergence of the anthropogenic warming signal from the noise of internal variability translates to changes in extreme event occurrence is of crucial societal importance. By utilising simulations of cumulative carbon dioxide (CO2) emissions and temperature changes from eleven earth system models, we demonstrate that the inherently lower internal variability found at tropical latitudes results in large increases in the frequency of extreme daily temperatures (exceedances of the 99.9th percentile derived from pre-industrial climate simulations) occurring much earlier than for mid-to-high latitude regions. Most of the world’s poorest people live at low latitudes, when considering 2010 GDP-PPP per capita; conversely the wealthiest population quintile disproportionately inhabit more variable mid-latitude climates. Consequently, the fraction of the global population in the lowest socio-economic quintile is exposed to substantially more frequent daily temperature extremes after much lower increases in both mean global warming and cumulative CO2 emissions.

  10. The Daily Curriculum Guide, Year II, Weeks 21-34. A Preschool Program for the Spanish-Speaking Child.

    ERIC Educational Resources Information Center

    Dissemination and Assessment Center for Bilingual Education, Austin, TX.

    Daily lesson plans for weeks 21 through 34 are provided in this guide, the third and last in the Year II sequence of the Daily Curriculum Guide preschool program for the Spanish-speaking child. The program is based on a language maintenance model in which Spanish is used as a means to develop basic concepts, skills and attitudes. Written in both…

  11. Relationship between Sleep Disturbance and Functional Outcomes in Daily Life Habits of Children with Down Syndrome

    PubMed Central

    Churchill, Shervin S.; Kieckhefer, Gail M.; Bjornson, Kristie F.; Herting, Jerald R.

    2015-01-01

    Objectives: The goal of this study was to describe sleep patterns and accomplishment of daily life habits in children with Down syndrome (DS) and to investigate the relationship between subjective indicators of sleep disturbance with functional outcomes in daily life. Design: Cross-sectional study with an Internet sample Setting: Online survey filled out at home Participants: 110 parents of children with DS and 29 parents of children with typical development (TD), age 5 to 18 years. Interventions: N/A. Measurements and Results: Children's Sleep Habits Questionnaire was employed to collect information about sleep disturbances in 8 domains (subscales) and a total score. The Life Habits questionnaire (Life-H) sampled information about daily life habits in 11 domains. Multivariable regression modeling was used to assess the associations between sleep disturbances and the accomplishment of daily life habits. Sleep disordered breathing (SDB) was a significant explanatory factor in 10 of 11 daily life habits and the total Life-H score. Sleep anxiety and parasomnias significantly influenced the accomplishment of life habits in children with DS as compared to children with typical development. When evaluated in multivariable models in conjunction with the other 7 domains of sleep disturbances, SDB was the most dominant explanatory factor for accomplishment of life habits. Conclusions: Sleep disturbances are negatively related to accomplishment of daily life functions. Prevention and treatment of sleep problems, particularly sleep disordered breathing, in children with Down syndrome may lead to enhanced accomplishment of daily life habits and activities. Citation: Churchill SS, Kieckhefer GM, Bjornson KF, Herting JR. Relationship between sleep disturbance and functional outcomes in daily life habits of children with Down syndrome. SLEEP 2015;38(1):61–71. PMID:25325444

  12. Daily cognitive appraisals, daily affect, and long-term depressive symptoms: the role of self-esteem and self-concept clarity in the stress process.

    PubMed

    Lee-Flynn, Sharon C; Pomaki, Georgia; Delongis, Anita; Biesanz, Jeremy C; Puterman, Eli

    2011-02-01

    The current study investigated how self-esteem and self-concept clarity are implicated in the stress process both in the short and long term. Initial and 2-year follow-up interviews were completed by 178 participants from stepfamily unions. In twice-daily structured diaries over 7 days, participants reported their main family stressor, cognitive appraisals (perceived stressor threat and stressor controllability), and negative affect. Results of multilevel modeling indicated that high self-esteem ameliorated the effect of daily negative cognitive appraisals on daily negative affect. Self-concept clarity also buffered the effect of low self-self-esteem on depressive symptoms 2 years later. Our findings point to the vulnerability of those having low self-esteem or low self-concept clarity in terms of both short- and long-term adaptation to stress. They indicate the need for the consideration of such individual differences in designing stress management interventions.

  13. Estimating missing daily temperature extremes in Jaffna, Sri Lanka

    NASA Astrophysics Data System (ADS)

    Thevakaran, A.; Sonnadara, D. U. J.

    2017-02-01

    The accuracy of reconstructing missing daily temperature extremes in the Jaffna climatological station, situated in the northern part of the dry zone of Sri Lanka, is presented. The adopted method utilizes standard departures of daily maximum and minimum temperature values at four neighbouring stations, Mannar, Anuradhapura, Puttalam and Trincomalee to estimate the standard departures of daily maximum and minimum temperatures at the target station, Jaffna. The daily maximum and minimum temperatures from 1966 to 1980 (15 years) were used to test the validity of the method. The accuracy of the estimation is higher for daily maximum temperature compared to daily minimum temperature. About 95% of the estimated daily maximum temperatures are within ±1.5 °C of the observed values. For daily minimum temperature, the percentage is about 92. By calculating the standard deviation of the difference in estimated and observed values, we have shown that the error in estimating the daily maximum and minimum temperatures is ±0.7 and ±0.9 °C, respectively. To obtain the best accuracy when estimating the missing daily temperature extremes, it is important to include Mannar which is the nearest station to the target station, Jaffna. We conclude from the analysis that the method can be applied successfully to reconstruct the missing daily temperature extremes in Jaffna where no data is available due to frequent disruptions caused by civil unrests and hostilities in the region during the period, 1984 to 2000.

  14. Daily phosphorus variation in a mountain stream

    NASA Astrophysics Data System (ADS)

    Hatch, Lorin K.; Reuter, John E.; Goldman, Charles R.

    1999-12-01

    Monthly diel monitoring studies for phosphorus content were conducted (1995-1996 period) for multiple stations on Incline Creek, a mountain stream in the Lake Tahoe basin (California-Nevada). Large discharge and particulate P (PP) concentration fluctuations occurred during June in the early evening as snowmelt from higher elevations arrived at the lower stream reaches. June diel dissolved organic P (DOP) concentrations steadily increased, while soluble reactive P (SRP) concentrations remained constant. June diel PP concentrations associated with sand-sized particles (PPsand: >63 μm) exhibited a clockwise hysteresis, indicating possible sediment source depletion on a daily timescale. June diel PP associated with silt- and clay-sized particles (PPSC: >0.45 μm and <63 μm) exhibited counterclockwise hysteresis behavior, suggesting a potential groundwater contribution to PPSC. PPSC comprised the majority of PP concentration, except during high-discharge events when PPsand concentration was dominant. Areal PP loading, specifically PPsand, appears to originate primarily from the lower eastern branch of Incline Creek during the spring snowmelt season. Possible sources include a ski resort/parking lot and a golf course. DOP and SRP areal loads were greatest from the undeveloped upper subwatershed, suggesting that natural factors such as slope are influencing loading of small-sized P fractions.

  15. Daily prickly pear consumption improves platelet function.

    PubMed

    Wolfram, R; Budinsky, A; Efthimiou, Y; Stomatopoulos, J; Oguogho, A; Sinzinger, H

    2003-07-01

    Prickly pear is traditionally used by Pima Indians as a dietary nutrient against diabetes mellitus. We examined the effect of daily consumption of 250 g in 8 healthy volunteers and 8 patients with mild familial heterozygous hypercholesterolemia on various parameters of platelet function. Beside its action on lipids and lipoproteins, prickly pear consumption significantly reduced the platelet proteins (platelet factor 4 and beta-thromboglobulin), ADP-induced platelet aggregation and improved platelet sensitivity (against PGI2 and PGE1) in volunteers as well as in patients. Also plasma 11-DH-TXB2 and the WU-test showed a significant improvement in both patients and volunteers. In contrast, collagen-induced platelet aggregation and the number of circulating endothelial cells showed a significant response in patients only. No influence of prickly pear ingestion on peripheral platelet count was monitored. The dietary run-in period did not influence any of the parameters of haemostasis examined. No sex difference was seen. Prickly pear may induce at least part of its beneficial actions on the cardiovascular system via decreasing platelet activity and thereby improving haemostatic balance.

  16. Daily tonometric curves after cataract surgery

    PubMed Central

    Sacca, S; Marletta, A; Pascotto, A; Barabino, S; Rolando, M; Giannetti, R; Calabria, G

    2001-01-01

    AIM—To evaluate daily tonometric curves after cataract surgery in patients with cataract only and in patients with cataract and glaucoma.
METHODS—108 patients scheduled for cataract surgery were randomly allocated to two groups: 57 patients with cataract only (normal) and 51 with cataract and primary open angle glaucoma (POAG). All patients underwent extracapsular cataract extraction (ECCE) (manual technique with long wound), phacoemulsification (automated technique with short wound), or nucleus capture (manual technique with short wound). Intraocular pressure (IOP) was measured by Goldmann tonometry in all patients every 2 hours for 12 hours before the operation and at 1 and 6 months postoperatively.
RESULTS—79 patients completed the 6 month examination. ECCE resulted in greater reductions in IOP than the other procedures (ECCE: 27% and 36% in normal patients and those with POAG, respectively; nucleus capture: 20% and 31%, respectively; phacoemulsification: 19% and 22%, respectively). The fluctuations in IOP before and after surgery were not statistically significant.
CONCLUSION—Cataract surgery in normal patients reduces IOP but does not eliminate fluctuations which are directly proportional to the IOP value and result partly from circadian rhythms. This important finding might influence our approach to treatment of patients with glaucoma.

 PMID:11133707

  17. Kiwifruit: our daily prescription for health.

    PubMed

    Stonehouse, Welma; Gammon, Cheryl S; Beck, Kathryn L; Conlon, Cathryn A; von Hurst, Pamela R; Kruger, Rozanne

    2013-06-01

    Kiwifruit are unequalled, compared with other commonly consumed fruit, for their nutrient density, health benefits, and consumer appeal. Research into their health benefits has focussed on the cultivars Actinidia deliciosa 'Hayward' (green kiwifruit) and Actinidia chinensis 'Hort 16A', ZESPRI(®) (gold kiwifruit). Compared with other commonly consumed fruit, both green and gold kiwifruit are exceptionally high in vitamins C, E, K, folate, carotenoids, potassium, fibre, and phytochemicals acting in synergy to achieve multiple health benefits. Kiwifruit, as part of a healthy diet, may increase high-density lipoprotein cholesterol, and decrease triglycerides, platelet aggregation, and elevated blood pressure. Consuming gold kiwifruit with iron-rich meals improves poor iron status, and green kiwifruit aids digestion and laxation. As a rich source of antioxidants, they may protect the body from endogenous oxidative damage. Kiwifruit may support immune function and reduce the incidence and severity of cold or flu-like illness in at-risk groups such as older adults and children. However, kiwifruit are allergenic, and although symptoms in most susceptible individuals are mild, severe reactions have been reported. While many research gaps remain, kiwifruit with their multiple health benefits have the potential to become part of our "daily prescription for health."

  18. Estimating daily net radiation in the FAO Penman-Monteith method

    NASA Astrophysics Data System (ADS)

    Carmona, Facundo; Rivas, Raúl; Kruse, Eduardo

    2016-03-01

    In this work, we evaluate the procedures of the Manual No. 56 of the FAO (United Nations Food and Agriculture Organization) for predicting daily net radiation using measures collected in Tandil (Argentina) between March 2007 and June 2010. In addition, a new methodology is proposed for estimating daily net radiation over the reference crop considered in the FAO Penman-Monteith method. The calculated and observed values of daily net radiation are compared. Estimation errors are reduced from ±22 to ±12 W m-2 considering the new model. From spring-summer data, estimation errors of less than ±10 % were observed for the new physical model, which represents an error of just ±0.4 mm d-1 for computing reference evapotranspiration. The new model presented here is not restricted to a climate regime and is mainly appropriate for application in the FAO Penman-Monteith method to determine the reference crop evapotranspiration.

  19. Approach to forecasting daily maximum ozone levels in St. Louis

    NASA Technical Reports Server (NTRS)

    Prior, E. J.; Schiess, J. R.; Mcdougal, D. S.

    1981-01-01

    Measurements taken in 1976 from the St. Louis Regional Air Pollution Study (RAPS) data base, conducted by EPA, were analyzed to determine an optimum set of air-quality and meteorological variables for predicting maximum ozone levels for each day in 1976. A 'leaps and bounds' regression analysis was used to identify the best subset of variables. Three particular variables, the 9 a.m. ozone level, the forecasted maximum temperature, and the 6-9 a.m. averaged wind speed, have useful forecasting utility. The trajectory history of air masses entering St. Louis was studied, and it was concluded that transport-related variables contribute to the appearance of very high ozone levels. The final empirical forecast model predicts the daily maximum ozone over 341 days with a standard deviation of 11 ppb, which approaches the estimated error.

  20. Daily Negative Work Events and Employees' Physiological and Psychological Reactions

    PubMed Central

    Volmer, Judith; Fritsche, Andrea

    2016-01-01

    Scholars have accumulated an abundant amount of knowledge on the association between work stressors and employees' health and well-being. However, notions of the complex interplay of physiological and psychological components of stress reactions are still in their infancy. Building on the Allostatic Load (AL) model, the present study considers short-term within-person effects of negative work events (NWEs) on indicators of both physiological (i.e., salivary cortisol) and psychological distress responses (i.e., negative affect and emotional exhaustion). Multilevel findings from an experience sampling study with 83 healthcare professionals suggest that reported NWEs predict employees' psychological but not endocrine stress responses. Results contribute to a more comprehensive understanding of employees' daily response patterns to occupational stressors. PMID:27877145

  1. A daily global mesoscale ocean eddy dataset from satellite altimetry.

    PubMed

    Faghmous, James H; Frenger, Ivy; Yao, Yuanshun; Warmka, Robert; Lindell, Aron; Kumar, Vipin

    2015-01-01

    Mesoscale ocean eddies are ubiquitous coherent rotating structures of water with radial scales on the order of 100 kilometers. Eddies play a key role in the transport and mixing of momentum and tracers across the World Ocean. We present a global daily mesoscale ocean eddy dataset that contains ~45 million mesoscale features and 3.3 million eddy trajectories that persist at least two days as identified in the AVISO dataset over a period of 1993-2014. This dataset, along with the open-source eddy identification software, extract eddies with any parameters (minimum size, lifetime, etc.), to study global eddy properties and dynamics, and to empirically estimate the impact eddies have on mass or heat transport. Furthermore, our open-source software may be used to identify mesoscale features in model simulations and compare them to observed features. Finally, this dataset can be used to study the interaction between mesoscale ocean eddies and other components of the Earth System.

  2. Large uncertainties in observed daily precipitation extremes over land

    NASA Astrophysics Data System (ADS)

    Herold, Nicholas; Behrangi, Ali; Alexander, Lisa V.

    2017-01-01

    We explore uncertainties in observed daily precipitation extremes over the terrestrial tropics and subtropics (50°S-50°N) based on five commonly used products: the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset, the Global Precipitation Climatology Centre-Full Data Daily (GPCC-FDD) dataset, the Tropical Rainfall Measuring Mission (TRMM) multi-satellite research product (T3B42 v7), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and the Global Precipitation Climatology Project's One-Degree Daily (GPCP-1DD) dataset. We use the precipitation indices R10mm and Rx1day, developed by the Expert Team on Climate Change Detection and Indices, to explore the behavior of "moderate" and "extreme" extremes, respectively. In order to assess the sensitivity of extreme precipitation to different grid sizes we perform our calculations on four common spatial resolutions (0.25° × 0.25°, 1° × 1°, 2.5° × 2.5°, and 3.75° × 2.5°). The impact of the chosen "order of operation" in calculating these indices is also determined. Our results show that moderate extremes are relatively insensitive to product and resolution choice, while extreme extremes can be very sensitive. For example, at 0.25° × 0.25° quasi-global mean Rx1day values vary from 37 mm in PERSIANN-CDR to 62 mm in T3B42. We find that the interproduct spread becomes prominent at resolutions of 1° × 1° and finer, thus establishing a minimum effective resolution at which observational products agree. Without improvements in interproduct spread, these exceedingly large observational uncertainties at high spatial resolution may limit the usefulness of model evaluations. As has been found previously, resolution sensitivity can be largely eliminated by applying an order of operation where indices are calculated prior to regridding. However, this approach is not appropriate when true area averages are desired

  3. The concentration-response relation between air pollution and daily deaths.

    PubMed Central

    Schwartz, J; Ballester, F; Saez, M; Pérez-Hoyos, S; Bellido, J; Cambra, K; Arribas, F; Cañada, A; Pérez-Boillos, M J; Sunyer, J

    2001-01-01

    Studies on three continents have reported associations between various measures of airborne particles and daily deaths. Sulfur dioxide has also been associated with daily deaths, particularly in Europe. Questions remain about the shape of those associations, particularly whether there are thresholds at low levels. We examined the association of daily concentrations of black smoke and SO(2) with daily deaths in eight Spanish cities (Barcelona, Bilbao, Castellón, Gijón, Oviedo, Valencia, Vitoria, and Zaragoza) with different climates and different environmental and social characteristics. We used nonparametric smoothing to estimate the shape of the concentration-response curve in each city and combined those results using a metasmoothing technique developed by Schwartz and Zanobetti. We extended their method to incorporate random variance components. Black smoke had a nearly linear association with daily deaths, with no evidence of a threshold. A 10 microg/m(3) increase in black smoke was associated with a 0.88% increase in daily deaths (95% confidence interval, 0.56%-1.20%). SO(2) had a less plausible association: Daily deaths increased at very low concentrations, but leveled off and then decreased at higher concentrations. These findings held in both one- and two-pollutant models and held whether we optimized our weather and seasonal model in each city or used the same smoothing parameters in each city. We conclude that the association with particle levels is more convincing than for SO(2), and without a threshold. Linear models provide an adequate estimation of the effect of particulate air pollution on mortality at low to moderate concentrations. PMID:11675264

  4. Prediction of daily sea surface temperature using efficient neural networks

    NASA Astrophysics Data System (ADS)

    Patil, Kalpesh; Deo, Makaranad Chintamani

    2017-02-01

    Short-term prediction of sea surface temperature (SST) is commonly achieved through numerical models. Numerical approaches are more suitable for use over a large spatial domain than in a specific site because of the difficulties involved in resolving various physical sub-processes at local levels. Therefore, for a given location, a data-driven approach such as neural networks may provide a better alternative. The application of neural networks, however, needs a large experimentation in their architecture, training methods, and formation of appropriate input-output pairs. A network trained in this manner can provide more attractive results if the advances in network architecture are additionally considered. With this in mind, we propose the use of wavelet neural networks (WNNs) for prediction of daily SST values. The prediction of daily SST values was carried out using WNN over 5 days into the future at six different locations in the Indian Ocean. First, the accuracy of site-specific SST values predicted by a numerical model, ROMS, was assessed against the in situ records. The result pointed out the necessity for alternative approaches. First, traditional networks were tried and after noticing their poor performance, WNN was used. This approach produced attractive forecasts when judged through various error statistics. When all locations were viewed together, the mean absolute error was within 0.18 to 0.32 °C for a 5-day-ahead forecast. The WNN approach was thus found to add value to the numerical method of SST prediction when location-specific information is desired.

  5. Worldwide forecast of the biologically effective UV radiation: UV index and daily dose

    NASA Astrophysics Data System (ADS)

    Schmalwieser, Alois W.; Schauberger, Guenther; Janouch, Michal; Nunez, Manuel; Koskela, Tapani; Berger, Daniel; Karamanian, Gabriel; Prosek, Pavel; Laska, Kamil

    2002-01-01

    Since October 1995 a global daily forecast of the UV index and the daily dose, as the irradiance of the biologically effective ultraviolet radiation, for clear sky is calculated. The Austrian model as well as the input parameters are described. By connecting the daily dose with the sensitivity of the photobiological skin types, a recommendation is given to select an appropriate sun protection factor of a sunscreen to avoid overexposure of the skin. The validation of the Austrian forecast model is done by long-term measurements of the biologically effective ultraviolet radiation. Measurements were taken from 6 different sites at 4 continents (Antarctica, Australia, America and Europe) covering the latitudinal range from 67 degree(s)N to 60 degree(s)S. By using the underestimation as criteria in the sense of radiation protection, the Austrian model shows less than 12% underestimation over the whole period for the UV index and less than 10% for the daily dose. The evaluation shows further that the forecast of the daily dose is much more influenced by the attenuation due to clouds than the UV index.

  6. Daily mood and sleep: reciprocal relations and links with adjustment problems.

    PubMed

    Kouros, Chrystyna D; El-Sheikh, Mona

    2015-02-01

    Children's sleep problems are common and associated with increased risk for adjustment problems. We examined daily links between children's sleep and mood, using a daily diary method and actigraphy. We also tested children's daily mood as a mediator of relations among sleep and children's broader internalizing and externalizing symptoms. A community sample of 142 children (mean age = 10.69 years; 57% girls; 69% European American, 31% African American) and their parents participated. For 1 week, children wore actigraphs and parents completed a daily telephone interview about their child's mood. Following the week of actigraphy, mothers and fathers reported on their child's adjustment. Multi-level models indicated within-person relations between children's mood and subsequent sleep fragmentation (indicated by increased activity) and sleep latency, and between-person relations between sleep latency and subsequent mood on the next day. Significant indirect effects were found such that a more negative daily mood (aggregated across diary days) mediated relations between poor sleep efficiency and longer sleep latency and parent-reported internalizing and externalizing symptoms. Findings extend previous research by highlighting disruptions to children's daily mood as a potential mechanism linking sleep problems to children's mental health.

  7. Changes in daily pollen concentration based on meteorological data and days after seasonal initiation - a case study for Japanese hop

    NASA Astrophysics Data System (ADS)

    Choe, H.; Kim, K. R.; Kim, M.; Han, M. J.; Cho, C.; Choi, B. C.

    2014-12-01

    Pollinosis causes various allergy symptoms such as seasonal rhinitis, asthma, and conjunctivitis (Min, 1991). Japanese hop (Humulus japonicus) is a major allergen in southern Gyonggi-do during the fall seasons (Park, 1998). So that it is needed to forecast the concentration of its pollens.For the germination of Japanese hop, a period of low temperature (<5C) followed by warm (~20C) and humid conditions is needed (Growing and Protecting New Zealand(2010)). The daily concentration of the pollens increases rapidly then decreases a few days afterward. In this study, the changes in daily pollen concentration were analyzed to yield a prediction model.As a result, a regression model was produced to forecast daily pollen concentration. It can be integrated into the daily pollinosis warning system of the Korea Meteorological Administration (KMA) and provide more accurate daily risk information.

  8. Gender, Emotion Work, and Relationship Quality: A Daily Diary Study

    PubMed Central

    Curran, Melissa A.; McDaniel, Brandon T.; Pollitt, Amanda M.; Totenhagen, Casey J.

    2015-01-01

    We use the gender relations perspective from feminist theorizing to investigate how gender and daily emotion work predict daily relationship quality in 74 couples (148 individuals in dating, cohabiting, or married relationships) primarily from the southwest U.S. Emotion work is characterized by activities that enhance others’ emotional well-being. We examined emotion work two ways: trait (individuals’ average levels) and state (individuals’ daily fluctuations). We examined actor and partner effects of emotion work and tested for gender differences. As outcome variables, we included six types of daily relationship quality: love, commitment, satisfaction, closeness, ambivalence, and conflict. This approach allowed us to predict three aspects of relationship quality: average levels, daily fluctuations, and volatility (overall daily variability across a week). Three patterns emerged. First, emotion work predicted relationship quality in this diverse set of couples. Second, gender differences were minimal for fixed effects: Trait and state emotion work predicted higher average scores on, and positive daily increases in, individuals’ own positive relationship quality and lower average ambivalence. Third, gender differences were more robust for volatility: For partner effects, having a partner who reported higher average emotion work predicted lower volatility in love, satisfaction, and closeness for women versus greater volatility in love and commitment for men. Neither gender nor emotion work predicted average levels, daily fluctuations, or volatility in conflict. We discuss implications and future directions pertaining to the unique role of gender in understanding the associations between daily emotion work and volatility in daily relationship quality for relational partners. PMID:26508808

  9. Self-Regulatory Strategies in Daily Life: Selection, Optimization, and Compensation and Everyday Memory Problems

    PubMed Central

    Stephanie, Robinson; Margie, Lachman; Elizabeth, Rickenbach

    2015-01-01

    The effective use of self-regulatory strategies, such as selection, optimization, and compensation (SOC) requires resources. However, it is theorized that SOC use is most advantageous for those experiencing losses and diminishing resources. The present study explored this seeming paradox within the context of limitations or constraints due to aging, low cognitive resources, and daily stress in relation to everyday memory problems. We examined whether SOC usage varied by age and level of constraints, and if the relationship between resources and memory problems was mitigated by SOC usage. A daily diary paradigm was used to explore day-to-day fluctuations in these relationships. Participants (n=145, ages 22 to 94) completed a baseline interview and a daily diary for seven consecutive days. Multilevel models examined between- and within-person relationships between daily SOC use, daily stressors, cognitive resources, and everyday memory problems. Middle-aged adults had the highest SOC usage, although older adults also showed high SOC use if they had high cognitive resources. More SOC strategies were used on high stress compared to low stress days. Moreover, the relationship between daily stress and memory problems was buffered by daily SOC use, such that on high-stress days, those who used more SOC strategies reported fewer memory problems than participants who used fewer SOC strategies. The paradox of resources and SOC use can be qualified by the type of resource-limitation. Deficits in global resources were not tied to SOC usage or benefits. Conversely, under daily constraints tied to stress, the use of SOC increased and led to fewer memory problems. PMID:26997686

  10. Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

    NASA Astrophysics Data System (ADS)

    Sommer, Philipp; Kaplan, Jed

    2016-04-01

    Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

  11. Optimization of Daily Flight Training Schedules

    DTIC Science & Technology

    2014-03-01

    ENS RL 1 2nd Lt GR 1 ENS YY 1 ENS DH 1 ENS FL 1 LTJG UM 1 LTJG PK ENS HG ENS CC 1 1 19 Table 10. Sample completed events The advanced strike...model uses one “ macro ” CQ event to schedule every CQ eligible student for multiple CQ events throughout the entire CQ training phase. This modeling

  12. Evaluating a coupled discrete wavelet transform and support vector regression for daily and monthly streamflow forecasting

    NASA Astrophysics Data System (ADS)

    Liu, Zhiyong; Zhou, Ping; Chen, Gang; Guo, Ledong

    2014-11-01

    This study investigated the performance and potential of a hybrid model that combined the discrete wavelet transform and support vector regression (the DWT-SVR model) for daily and monthly streamflow forecasting. Three key factors of the wavelet decomposition phase (mother wavelet, decomposition level, and edge effect) were proposed to consider for improving the accuracy of the DWT-SVR model. The performance of DWT-SVR models with different combinations of these three factors was compared with the regular SVR model. The effectiveness of these models was evaluated using the root-mean-squared error (RMSE) and Nash-Sutcliffe model efficiency coefficient (NSE). Daily and monthly streamflow data observed at two stations in Indiana, United States, were used to test the forecasting skill of these models. The results demonstrated that the different hybrid models did not always outperform the SVR model for 1-day and 1-month lead time streamflow forecasting. This suggests that it is crucial to consider and compare the three key factors when using the DWT-SVR model (or other machine learning methods coupled with the wavelet transform), rather than choosing them based on personal preferences. We then combined forecasts from multiple candidate DWT-SVR models using a model averaging technique based upon Akaike's information criterion (AIC). This ensemble prediction was superior to the single best DWT-SVR model and regular SVR model for both 1-day and 1-month ahead predictions. With respect to longer lead times (i.e., 2- and 3-day and 2-month), the ensemble predictions using the AIC averaging technique were consistently better than the best DWT-SVR model and SVR model. Therefore, integrating model averaging techniques with the hybrid DWT-SVR model would be a promising approach for daily and monthly streamflow forecasting. Additionally, we strongly recommend considering these three key factors when using wavelet-based SVR models (or other wavelet-based forecasting models).

  13. Daily stressors, war experiences, and mental health in Afghanistan.

    PubMed

    Miller, Kenneth E; Omidian, Patricia; Rasmussen, Andrew; Yaqubi, Aziz; Daudzai, Haqmal

    2008-12-01

    Working in Afghanistan's capital city of Kabul, the authors assessed the relative contribution of daily stressors and war-related experiences of violence and loss to levels of depression, PTSD, impaired functioning, and a culturally specific measure of general psychological distress. For women, daily stressors were a better predictor than war experiences of all mental health outcomes except for PTSD; for men, daily stressors were a better predictor of depression and functional impairment, while war experiences and daily stressors were similarly predictive of general distress. For men, daily stressors moderated the relationship between war experiences and PTSD, which was significant only under conditions of low daily stress. The study's implications for research and intervention in conflict and post-conflict settings are considered.

  14. Daily mood-drinking slopes as predictors: A new take on drinking motives and related outcomes

    PubMed Central

    Mohr, Cynthia D.; Brannan, Debi; Wendt, Staci; Jacobs, Laurie; Wright, Robert; Wang, Mo

    2014-01-01

    Motivational models of alcohol consumption have articulated the manner in which positive and negative experiences motivate drinking in unique social contexts (e.g., Cooper, Frone, Russell & Mudar, 1995). Daily process methodology, in which daily events, moods and drinking behaviors are reported daily or multiple times per day, has been used to examine behavioral patterns that are consistent with discrete motivations. We advance the notion that repeated patterns of drinking in various social contexts as a function of positive or negative mood increases can provide evidence of individual-level if-then drinking signatures, which in turn can predict drinking-related outcomes. The purpose of this study was to examine the utility of slopes to predict longer term drinking motivations and alcohol problems, employing a daily process study of non-clinical moderate alcohol drinkers (N=47; 49% women). Participants responded to thrice daily interviews administered via handheld computer for 30 days, followed by a longitudinal telephone survey for 12 months. Participants’ daily mood-drinking relationships were extracted from HLM and employed as predictors of 12-month outcomes in multiple regression analyses. Daily mood-drinking patterns demonstrated significant variability across persons, such that moderate drinkers could be reliably differentiated based on those patterns in terms of distinct drinking-related outcomes. Among the results, negative mood-solitary drinking slopes were associated with lower subsequent coping motives; yet, positive mood-solitary drinking slopes were predictive of higher coping and lower social motives. Conversely, positive mood-social drinking associations were predictive of higher enhancement motives and b-MAST scores. Results are interpreted in light of motivational models of consumption. PMID:23647154

  15. Weak associations between the daily number of suicide cases and amount of daily sunlight.

    PubMed

    Seregi, Bernadett; Kapitány, Balázs; Maróti-Agóts, Ákos; Rihmer, Zoltán; Gonda, Xénia; Döme, Péter

    2017-02-06

    Several environmental factors with periodic changes in intensity during the calendar year have been put forward to explain the increase in suicide frequency during spring and summer. In the current study we investigated the effect of averaged daily sunshine duration of periods with different lengths and 'lags' (i.e. the number of days between the last day of the period for which the averaged sunshine duration was calculated and the day of suicide) on suicide risk. We obtained data on daily numbers of suicide cases and daily sunshine duration in Hungary from 1979 to 2013. In order to remove the seasonal components from the two time series (i.e. numbers of suicide and sunshine hours) we used the differencing method. Pearson correlations (n=22,950) were calculated to reveal associations between sunshine duration and suicide risk. The final sample consisted of 122,116 suicide cases. Regarding the entire investigated period, after differencing, sunshine duration and number of suicides on the same days showed a distinctly weak, but highly significant positive correlation in the total sample (r=0.067; p=1.17*10(-13)). Positive significant correlations (p˂0.0001) between suicide risk on the index day and averaged sunshine duration in the previous days (up to 11days) were also found in the total sample. Our results from a large sample strongly support the hypothesis that sunshine has a prompt, but very weak increasing effect on the risk of suicide (especially violent cases among males). The main limitation is that possible confounding factors were not controlled for.

  16. A resampling procedure for generating conditioned daily weather sequences

    USGS Publications Warehouse

    Clark, M.P.; Gangopadhyay, S.; Brandon, D.; Werner, K.; Hay, L.; Rajagopalan, B.; Yates, D.

    2004-01-01

    [1] A method is introduced to generate conditioned daily precipitation and temperature time series at multiple stations. The method resamples data from the historical record "nens" times for the period of interest (nens = number of ensemble members) and reorders the ensemble members to reconstruct the observed spatial (intersite) and temporal correlation statistics. The weather generator model is applied to 2307 stations in the contiguous United States and is shown to reproduce the observed spatial correlation between neighboring stations, the observed correlation between variables (e.g., between precipitation and temperature), and the observed temporal correlation between subsequent days in the generated weather sequence. The weather generator model is extended to produce sequences of weather that are conditioned on climate indices (in this case the Nin??o 3.4 index). Example illustrations of conditioned weather sequences are provided for a station in Arizona (Petrified Forest, 34.8??N, 109.9??W), where El Nin??o and La Nin??a conditions have a strong effect on winter precipitation. The conditioned weather sequences generated using the methods described in this paper are appropriate for use as input to hydrologic models to produce multiseason forecasts of streamflow.

  17. Daily variability of rainfall and emergency department visits of acute gastrointestinal illness in North Carolina, 2006-2008

    EPA Science Inventory

    Background & Aims: Projections based on climate models suggest that the frequency of extreme rainfall events will continue to rise over the next several decades. We aim to investigate the temporal relationship between daily variability of rainfall and acute gastrointestinal illne...

  18. Reconstruction of MODIS daily land surface temperature under clouds

    NASA Astrophysics Data System (ADS)

    Sun, L.; Gao, F.; Chen, Z.; Song, L.; Xie, D.

    2015-12-01

    Land surface temperature (LST), generally defined as the skin temperature of the Earth's surface, controls the process of evapotranspiration, surface energy balance, soil moisture change and climate change. Moderate Resolution Imaging Spectrometer (MODIS) is equipped with 1km resolution thermal sensor andcapable of observing the earth surface at least once per day.Thermal infrared bands cannot penetrate cloud, which means we cannot get consistency drought monitoring condition at one area. However, the cloudy-sky conditions represent more than half of the actual day-to-day weather around the global. In this study, we developed an LST filled model based on the assumption that under good weather condition, LST difference between two nearby pixels are similar among the closest 8 days. We used all the valid pixels covered by a 9*9 window to reconstruct the gap LST. Each valid pixel is assigned a weight which is determined by the spatial distance and the spectral similarity. This model is applied in the Middle-East of China including Gansu, Ningxia, Shaanxi province. The terrain is complicated in this area including plain and hill. The MODIS daily LST product (MOD11A3) from 2000 to 2004 is tested. Almost all the gap pixels are filled, and the terrain information is reconstructed well and smoothly. We masked two areas in order to validate the model, one located in the plain, another located in the hill. The correlation coefficient is greater than 0.8, even up to 0.92 in a few days. We also used ground measured day maximum and mean surface temperature to valid our model. Although both the temporal and spatial scale are different between ground measured temperature and MODIS LST, they agreed well in all the stations. This LST filled model is operational because it only needs LST and reflectance, and does not need other auxiliary information such as climate factors. We will apply this model to more regions in the future.

  19. Weather factors in the short-term forecasting of daily ambulance calls.

    PubMed

    Wong, Ho-Ting; Lai, Poh-Chin

    2014-07-01

    The daily ambulance demand for Hong Kong is rising, and it has been shown that weather factors (temperature and humidity) play a role in the demand for ambulance services. This study aimed at developing short-term forecasting models of daily ambulance calls using the 7-day weather forecast data as predictors. We employed the autoregressive integrated moving average (ARIMA) method to analyze over 1.3 million cases of emergency attendance in May 2006 through April 2009 and the 7-day weather forecast data for the same period. Our results showed that the ARIMA model could offer reasonably accurate forecasts of daily ambulance calls at 1-7 days ahead of time and with improved accuracy by including weather factors. Specifically, the inclusion of average temperature alone in our ARIMA model improved the predictability of the 1-day forecast when compared to that of a simple ARIMA model (8.8% decrease in the root mean square error, RMSE=53 vs 58). The improvement in the 7-day forecast with average temperature as a predictor was more pronounced, with a 10% drop in prediction error (RMSE=62 vs 69). These findings suggested that weather forecast data can improve the 1- to 7-day forecasts of daily ambulance demand. As weather forecast data are readily accessible from Hong Kong Observatory's official website, there is virtually no cost to including them in the ARIMA models, which yield better prediction for forward planning and deployment of ambulance manpower.

  20. Particulate air pollution and daily mortality on Utah's Wasatch Front.

    PubMed Central

    Pope, C A; Hill, R W; Villegas, G M

    1999-01-01

    Reviews of daily time-series mortality studies from many cities throughout the world suggest that daily mortality counts are associated with short-term changes in particulate matter (PM) air pollution. One U.S. city, however, with conspicuously weak PM-mortality associations was Salt Lake City, Utah; however, relatively robust PM-mortality associations have been observed in a neighboring metropolitan area (Provo/Orem, Utah). The present study explored this apparent discrepancy by collecting, comparing, and analyzing mortality, pollution, and weather data for all three metropolitan areas on Utah's Wasatch Front region of the Wasatch Mountain Range (Ogden, Salt Lake City, and Provo/Orem) for approximately 10 years (1985-1995). Generalized additive Poisson regression models were used to estimate PM-mortality associations while controlling for seasonality, temperature, humidity, and barometric pressure. Salt Lake City experienced substantially more episodes of high PM that were dominated by windblown dust. When the data were screened to exclude obvious windblown dust episodes and when PM data from multiple monitors were used to construct an estimate of mean exposure for the area, comparable PM-mortality effects were estimated. After screening and by using constructed mean PM [less than/equal to] 10 microm in aerodynamic diameter (PM10) data, the estimated percent change in mortality associated with a 10-mg/m3 increase in PM10 (and 95% confidence intervals) for the three Wasatch Front metropolitan areas equaled approximately 1. 6% (0.3-2.9), 0.8% (0.3-1.3), and 1.0% (0.2-1.8) for the Ogden, Salt Lake City, and Provo/Orem areas, respectively. We conclude that stagnant air pollution episodes with higher concentrations of primary and secondary combustion-source particles were more associated with elevated mortality than windblown dust episodes with relatively higher concentrations of coarse crustal-derived particles. Images Figure 1 Figure 2 Figure 3 Figure 4 PMID:10379003

  1. Particulate air pollution and daily mortality in Bangkok

    NASA Astrophysics Data System (ADS)

    Vajanapoom, Nitaya

    1999-10-01

    This study was designed to assess the association between PM10 and visibility, and to determine whether the variations in daily mortality were associated with fluctuations in daily PM10 and visibility levels, in Bangkok during 1992-1997. Mortality data were extracted from death certificates, provided by the Bureau of Registration Administration. PM10 data were obtained from three monitoring stations operated by the Pollution Control Department, and visibility data were obtained from two monitoring stations operated by the Department of Meteorology. PM10 was regressed on visibility using multiple regression. Inverse and significant association was found between PM10 and visibility, after controlling for relative humidity, minimum temperature, and winter indicator variable. Positive association was found between total mortality and PM10, in Poisson regression model while controlling for long-term trends, season, and variations in weather. Five-day moving average of PM10 was significantly and most strongly associated with total mortality from non-external causes; a 2.3% (95% CI = 1.3, 3.3) increase in mortality was estimated for one interquartile range (30 μg/m3) increase in PM10. When PM10 was replaced with visibility, a 1.3% (95% CI = 0.4, 2.3) increase in mortality was estimated for one interquartile range (1.5 km) decrease in visibility. Lagged effects up to three day lags prior to death with similar patterns were observed for both PM10 and visibility. The findings suggest the possibility of using visibility as a surrogate for fine particulate matter. This approach is feasible because visibility data are usually routinely recorded at airports throughout the world. On the other hand, given the large number of population living in Bangkok, the small but significant percent excess deaths attributable to airborne particle exposure is an important public health concern.

  2. Daily affective experiences predict objective sleep outcomes among adolescents.

    PubMed

    Tavernier, Royette; Choo, Sungsub B; Grant, Kathryn; Adam, Emma K

    2016-02-01

    Adolescence is a sensitive period for changes in both sleep and affect. Although past research has assessed the association between affect and sleep among adolescents, few studies have examined both trait (typical) and day-to-day changes in affect, and fewer still have specifically examined negative social evaluative emotions (e.g. embarrassment) in relation to sleep. Both between- and within-person variations in daily affect were examined in relation to four objectively-measured sleep outcomes (sleep hours; sleep latency; sleep efficiency; and length of wake bouts) among adolescents. Participants (N = 77 high-school students; 42.9% female; M = 14.37 years) wore an actiwatch and completed daily-diaries for 3 days. The results of hierarchical linear models (controlling for age, gender, race, ethnicity, parental employment status, income, puberty and caffeine) indicated that negative social evaluative emotions and high-arousal affective experiences generally predicted poor sleep outcomes, whereas low-arousal affective experiences were associated with good sleep outcomes. Specifically, at the person level, adolescents reporting higher negative social evaluative emotions had shorter average sleep hours, and those experiencing higher anxiety–nervousness had longer wake bouts. In addition, individuals experiencing more dysphoria (sad, depressed, lonely) had longer average sleep hours and shorter wake bouts, while those experiencing more calmness had shorter sleep latencies. At the within-person level, individuals had longer sleep latencies following days that they had experienced high-arousal positive affect (e.g. excitement), and had longer wake bouts following days they had experienced more negative social evaluative emotions. The results highlight the detrimental effects of negative social evaluative emotions and high-arousal affective states for adolescent sleep.

  3. Daily Affective Experiences Predict Objective Sleep Outcomes among Adolescents

    PubMed Central

    Tavernier, Royette; Choo, Sungsub B; Grant, Kathryn; Adam, Emma K

    2015-01-01

    Summary Adolescence is a sensitive period for changes in both sleep and affect. Although past research has assessed the association between affect and sleep among adolescents, few studies have examined both trait (typical) and day-to-day changes in affect, and fewer still have specifically examined negative social evaluative emotions (NSEE; e.g., embarrassment) in relation to sleep. We examined both between- and within-person variations in daily affect in relation to four objectively-measured sleep outcomes (sleep hours, sleep latency, sleep efficiency, and length of wake bouts) among adolescents. Participants (N = 77 high school students, 42.9% female; M = 14.37 years) wore an actiwatch and completed daily diaries for 3 days. Results of hierarchical linear models (controlling for age, gender, race, ethnicity, parental employment status, income, puberty, and caffeine) indicated that NSEE and high arousal affective experiences generally predicted poor sleep outcomes, whereas low arousal affective experiences were associated with good sleep outcomes. Specifically, at the person level, adolescents reporting higher NSEE had shorter average sleep hours, and those experiencing higher anxiety-nervousness had longer wake bouts. In addition, individuals experiencing more dysphoria (sad, depressed, lonely) had longer average sleep hours and shorter wake bouts, while those experiencing more calmness had shorter sleep latencies. At the within person level, individuals had longer sleep latencies following days that they had experienced high arousal positive affect (e.g., excitement) and had longer wake bouts following days they had experienced more NSEE. Results highlight the detrimental effects of NSEE and high arousal affective states for adolescent sleep. PMID:26365539

  4. Mitigating effects of vaccination on influenza outbreaks given constraints in stockpile size and daily administration capacity

    PubMed Central

    2011-01-01

    Background Influenza viruses are a major cause of morbidity and mortality worldwide. Vaccination remains a powerful tool for preventing or mitigating influenza outbreaks. Yet, vaccine supplies and daily administration capacities are limited, even in developed countries. Understanding how such constraints can alter the mitigating effects of vaccination is a crucial part of influenza preparedness plans. Mathematical models provide tools for government and medical officials to assess the impact of different vaccination strategies and plan accordingly. However, many existing models of vaccination employ several questionable assumptions, including a rate of vaccination proportional to the population at each point in time. Methods We present a SIR-like model that explicitly takes into account vaccine supply and the number of vaccines administered per day and places data-informed limits on these parameters. We refer to this as the non-proportional model of vaccination and compare it to the proportional scheme typically found in the literature. Results The proportional and non-proportional models behave similarly for a few different vaccination scenarios. However, there are parameter regimes involving the vaccination campaign duration and daily supply limit for which the non-proportional model predicts smaller epidemics that peak later, but may last longer, than those of the proportional model. We also use the non-proportional model to predict the mitigating effects of variably timed vaccination campaigns for different levels of vaccination coverage, using specific constraints on daily administration capacity. Conclusions The non-proportional model of vaccination is a theoretical improvement that provides more accurate predictions of the mitigating effects of vaccination on influenza outbreaks than the proportional model. In addition, parameters such as vaccine supply and daily administration limit can be easily adjusted to simulate conditions in developed and developing

  5. Robust optimization for total maximum daily load allocations

    NASA Astrophysics Data System (ADS)

    Jia, Yanbing; Culver, Teresa B.

    2006-02-01

    The determination of the pollutant load distribution among different pollutant sources in a watershed is a critical step in total maximum daily load (TMDL) development. Under current TMDL practices, TMDL allocations are typically determined through a trial-and-error approach of reducing pollutant loadings until a watershed simulation model predicts that water quality standards will be met given a margin of safety. Unfortunately, many feasible combinations of load reductions and significant uncertainties may exist. Therefore it is difficult and time-consuming to compare various allocation scenarios using a trial-and-error approach. A robust optimization model is developed in this study to incorporate the uncertainty of water quality predictions and to minimize pollutant load reductions given various levels of reliability with respect to the water quality standards. The generalized likelihood uncertainty estimation approach is used to explicitly address the uncertainty of a watershed simulation model, the Hydrological Simulation Program-Fortran. The uncertainty is integrated into TMDL allocations using a robust genetic algorithm model linked with a response matrix approach. The developed robust optimization model is demonstrated using a case study based on the Moore's Creek fecal coliform TMDL study. The trade-offs between reliability levels and total load reductions of allocation scenarios are evaluated, and the optimized load reduction scenarios are compared with the scenario generated by a trial-and-error approach and approved by the U.S. Environmental Protection Agency. The results show that the optimized load reduction scenario requires 30% less load reductions than the scenario approved by the U.S. Environmental Protection Agency at the same reliability level.

  6. The Experience of Daily Hassles, Cardiovascular Reactivity and Adolescent Risk Taking and Self-Esteem

    ERIC Educational Resources Information Center

    Vermeersch, Hans; T'Sjoen, Guy; Kaufman, Jean-Marc; Vincke, John; Bracke, Piet

    2010-01-01

    Based on Boyce and Ellis's model on "context" and "biological sensitivity to the context", this article analyzes the interaction between the experience of daily hassles and experimentally induced cardiovascular reactivity as an indicator of stress reactivity, in explaining risk