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Sample records for modeling daily precipitationat

  1. 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.

  2. 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

  3. Modeling maximum daily temperature using a varying coefficient regression model

    NASA Astrophysics Data System (ADS)

    Li, Han; Deng, Xinwei; Kim, Dong-Yun; Smith, Eric P.

    2014-04-01

    Relationships between stream water and air temperatures are often modeled using linear or nonlinear regression methods. Despite a strong relationship between water and air temperatures and a variety of models that are effective for data summarized on a weekly basis, such models did not yield consistently good predictions for summaries such as daily maximum temperature. A good predictive model for daily maximum temperature is required because daily maximum temperature is an important measure for predicting survival of temperature sensitive fish. To appropriately model the strong relationship between water and air temperatures at a daily time step, it is important to incorporate information related to the time of the year into the modeling. In this work, a time-varying coefficient model is used to study the relationship between air temperature and water temperature. The time-varying coefficient model enables dynamic modeling of the relationship, and can be used to understand how the air-water temperature relationship varies over time. The proposed model is applied to 10 streams in Maryland, West Virginia, Virginia, North Carolina, and Georgia using daily maximum temperatures. It provides a better fit and better predictions than those produced by a simple linear regression model or a nonlinear logistic model.

  4. Time series ARIMA models for daily price of palm oil

    NASA Astrophysics Data System (ADS)

    Ariff, Noratiqah Mohd; Zamhawari, Nor Hashimah; Bakar, Mohd Aftar Abu

    2015-02-01

    Palm oil is deemed as one of the most important commodity that forms the economic backbone of Malaysia. Modeling and forecasting the daily price of palm oil is of great interest for Malaysia's economic growth. In this study, time series ARIMA models are used to fit the daily price of palm oil. The Akaike Infromation Criterion (AIC), Akaike Infromation Criterion with a correction for finite sample sizes (AICc) and Bayesian Information Criterion (BIC) are used to compare between different ARIMA models being considered. It is found that ARIMA(1,2,1) model is suitable for daily price of crude palm oil in Malaysia for the year 2010 to 2012.

  5. 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

  6. A nested multisite daily rainfall stochastic generation model

    NASA Astrophysics Data System (ADS)

    Srikanthan, Ratnasingham; Pegram, Geoffrey G. S.

    2009-06-01

    SummaryThis paper describes a nested multisite daily rainfall generation model which preserves the statistics at daily, monthly and annual levels of aggregation. A multisite two-part daily model is nested in multisite monthly, then annual models. A multivariate set of fourth order Markov chains is used to model the daily occurrence of rainfall; the daily spatial correlation in the occurrence process is handled by using suitably correlated uniformly distributed variates via a Normal Scores Transform (NST) obtained from a set of matched multinormal pseudo-random variates, following Wilks [Wilks, D.S., 1998. Multisite generalisation of a daily stochastic precipitation generation model. Journal of Hydrology 210, 178-191]; we call it a hidden covariance model. A spatially correlated two parameter gamma distribution is used to obtain the rainfall depths; these values are also correlated via a specially matched hidden multinormal process. For nesting, the generated daily rainfall sequences at all the sites are aggregated to monthly rainfall values and these values are modified by a set of lag-1 autoregressive multisite monthly rainfall models. The modified monthly rainfall values are aggregated to annual rainfall and these are then modified by a lag-1 autoregressive multisite annual model. This nesting process ensures that the daily, monthly and annual means and covariances are preserved. The model was applied to a region with 30 rainfall sites, one of the five sets reported by Srikanthan [Srikanthan, R., 2005. Stochastic Generation of Daily Rainfall Data at a Number of Sites. Technical Report 05/7, CRC for Catchment Hydrology. Monash University, 66p]. A comparison of the historical and generated statistics shows that the model preserves all the important characteristics of rainfall at the daily, monthly and annual time scales, including the spatial structure. There are some outstanding features that need to be improved: depths of rainfall on isolated wet days and

  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. 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.

  9. 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.

  10. Coupling SWAT and ANN models for enhanced daily streamflow prediction

    NASA Astrophysics Data System (ADS)

    Noori, Navideh; Kalin, Latif

    2016-02-01

    To improve daily flow prediction in unmonitored watersheds a hybrid model was developed by combining a quasi-distributed watershed model and artificial neural network (ANN). Daily streamflow data from 29 nearby watersheds in and around the city of Atlanta, Southeastern United States, with leave-one-site-out jackknifing technique were used to build the flow predictive models during warm and cool seasons. Daily streamflow was first simulated with the Soil and Water Assessment Tool (SWAT) and then the SWAT simulated baseflow and stormflow were used as inputs to ANN. Out of the total 29 test watersheds, 62% and 83% of them had Nash-Sutcliffe values above 0.50 during the cool and warm seasons, respectively (considered good or better). As the percent forest cover or the size of test watershed increased, the performances of the models gradually decreased during both warm and cool seasons. This indicates that the developed models work better in urbanized watersheds. In addition, SWAT and SWAT Calibration Uncertainty Procedure (SWAT-CUP) program were run separately for each station to compare the flow prediction accuracy of the hybrid approach to SWAT. Only 31% of the sites during the calibration and 34% of validation runs had ENASH values ⩾0.50. This study showed that coupling ANN with semi-distributed models can lead to improved daily streamflow predictions in ungauged watersheds.

  11. 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 results from the cochlear…

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

    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.

    2011-10-01

    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.

  18. Daily reservoir inflow forecasting combining QPF into ANNs model

    NASA Astrophysics Data System (ADS)

    Zhang, Jun; Cheng, Chun-Tian; Liao, Sheng-Li; Wu, Xin-Yu; Shen, Jian-Jian

    2009-01-01

    Daily reservoir inflow predictions with lead-times of several days are essential to the operational planning and scheduling of hydroelectric power system. The demand for quantitative precipitation forecasting (QPF) is increasing in hydropower operation with the dramatic advances in the numerical weather prediction (NWP) models. This paper presents a simple and an effective algorithm for daily reservoir inflow predictions which solicits the observed precipitation, forecasted precipitation from QPF as predictors and discharges in following 1 to 6 days as predicted targets for multilayer perceptron artificial neural networks (MLP-ANNs) modeling. An improved error back-propagation algorithm with self-adaptive learning rate and self-adaptive momentum coefficient is used to make the supervised training procedure more efficient in both time saving and search optimization. Several commonly used error measures are employed to evaluate the performance of the proposed model and the results, compared with that of ARIMA model, show that the proposed model is capable of obtaining satisfactory forecasting not only in goodness of fit but also in generalization. Furthermore, the presented algorithm is integrated into a practical software system which has been severed for daily inflow predictions with lead-times varying from 1 to 6 days of more than twenty reservoirs operated by the Fujian Province Grid Company, China.

  19. 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.

  20. 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.

  1. 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.

  2. A clonal selection algorithm model for daily rainfall data prediction.

    PubMed

    Noor Rodi, N S; Malek, M A; Ismail, Amelia Ritahani; Ting, Sie Chun; Tang, Chao-Wei

    2014-01-01

    This study applies the clonal selection algorithm (CSA) in an artificial immune system (AIS) as an alternative method to predicting future rainfall data. The stochastic and the artificial neural network techniques are commonly used in hydrology. However, in this study a novel technique for forecasting rainfall was established. Results from this study have proven that the theory of biological immune systems could be technically applied to time series data. Biological immune systems are nonlinear and chaotic in nature similar to the daily rainfall data. This study discovered that the proposed CSA was able to predict the daily rainfall data with an accuracy of 90% during the model training stage. In the testing stage, the results showed that an accuracy between the actual and the generated data was within the range of 75 to 92%. Thus, the CSA approach shows a new method in rainfall data prediction. PMID:25429452

  3. 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

  4. 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.

  5. Modelling sub-daily evaporation from a small reservoir.

    NASA Astrophysics Data System (ADS)

    McGloin, Ryan; McGowan, Hamish; McJannet, David; Burn, Stewart

    2013-04-01

    Accurate quantification of evaporation from small water storages is essential for water management and is also required as input in some regional hydrological and meteorological models. Global estimates of the number of small storages or lakes (< 0.1 kilometers) are estimated to be in the order of 300 million (Downing et al., 2006). However, direct evaporation measurements at small reservoirs using the eddy covariance or scintillometry techniques have been limited due to their expensive and complex nature. To correctly represent the effect that small water bodies have on the regional hydrometeorology, reliable estimates of sub-daily evaporation are necessary. However, evaporation modelling studies at small reservoirs have so far been limited to quantifying daily estimates. In order to ascertain suitable methods for accurately modelling hourly evaporation from a small reservoir, this study compares evaporation results measured by the eddy covariance method at a small reservoir in southeast Queensland, Australia, to results from several modelling approaches using both over-water and land-based meteorological measurements. Accurate predictions of hourly evaporation were obtained by a simple theoretical mass transfer model requiring only over-water measurements of wind speed, humidity and water surface temperature. An evaporation model that was recently developed for use in small reservoir environments by Granger and Hedstrom (2011), appeared to overestimate the impact stability had on evaporation. While evaporation predictions made by the 1-dimensional hydrodynamics model, DYRESM (Dynamic Reservoir Simulation Model) (Imberger and Patterson, 1981), showed reasonable agreement with measured values. DYRESM did not show any substantial improvement in evaporation prediction when inflows and out flows were included and only a slighter better correlation was shown when over-water meteorological measurements were used in place of land-based measurements. Downing, J. A., Y. T

  6. Modeling daily streamflow at ungauged catchments: What information is necessary?

    NASA Astrophysics Data System (ADS)

    Patil, S.; Stieglitz, M.

    2011-12-01

    Streamflow modeling at ungauged catchments involves transfer of information (viz., model structure and parameters) from gauged to ungauged catchments that are judged to be hydrologically similar. In this study, we focus on identifying: (1) what constitutes the critical information that needs to be transferred among hydrologically similar catchments to achieve good predictability using models at ungauged sites, and (2) which is the best approach for transferring this information from gauged to ungauged catchments. We develop a simple hydrologic model with minimal calibration requirement and implement it over 756 catchments located across the continental United States. The model computes water balance at a daily time-step and conceptualizes subsurface runoff through a storage-dependent exponential decline in saturated hydraulic conductivity. Snow accumulation and melt are modeled using the thermal degree-day concept. The calibrated model performs better in humid runoff-dominated regions than in the drier evapotranspiration-dominated regions. Results show that within a region, transfer of hydrograph recession information alone is sufficient for reliable streamflow predictions at ungauged catchments. Information transfer from spatially proximate gauged catchments provides better streamflow predictability at ungauged catchments than transfer from catchments identified as physically similar. When considering spatially proximate catchments, information transfer from multiple donor catchments is preferable to transfer from a single donor catchment.

  7. Estimating daily SWE from daily snow depth observations: a time series perspective on modeling snow bulk density

    NASA Astrophysics Data System (ADS)

    McCreight, J. L.; Small, E. E.; Larson, K. M.

    2013-12-01

    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 motivate and develop a new model of bulk density for the daily timestep and demonstrate its improved skill over the existing models. Snow depth and density are anticorrleated 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 time scales) and the observed positive and negative anomalies from the smoothed timeseries (short timescales) as separate terms. A climatology of fit is also included as a predictor variable. Over a half-million, daily observations of depth and SWE at 345 SNOTEL sites are used to train and evaluate model performance in over 3300 water years. For each location, we train the three models to the neighboring stations within 70km, transfer the parameters to the location to be modeled, and evaluate modeled timeseries 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 RMSE by 9.6% and 4.2% compared to previous models while increasing R2 from .46 to .52 to .56 across models. Removing the challenge of parameter transfer increases these R2 scores considerably to .58, .66, and .75. Our model shows general improvement over existing models when data are more frequent than once every 5 days and at least 3 stations are available for training. Results are applied to estimate SWE at over 100 locations on NSF's Earthscope Plate Boundary Observatory where geodetic grade GPS is currently used to measure snow depth. SWE and density observations

  8. A HIERARCHIAL STOCHASTIC MODEL OF LARGE SCALE ATMOSPHERIC CIRCULATION PATTERNS AND MULTIPLE STATION DAILY PRECIPITATION

    EPA Science Inventory

    A stochastic model of weather states and concurrent daily precipitation at multiple precipitation stations is described. our algorithms are invested for classification of daily weather states; k means, fuzzy clustering, principal components, and principal components coupled with ...

  9. 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

  10. Modeling daily soil temperature using data-driven models and spatial distribution

    NASA Astrophysics Data System (ADS)

    Kim, Sungwon; Singh, Vijay P.

    2014-11-01

    The objective of this study is to develop data-driven models, including multilayer perceptron (MLP) and adaptive neuro-fuzzy inference system (ANFIS), for estimating daily soil temperature at Champaign and Springfield stations in Illinois. The best input combinations (one, two, and three inputs) can be identified using MLP. The ANFIS is used to estimate daily soil temperature using the best input combinations (one, two, and three inputs). From the performance evaluation and scatter diagrams of MLP and ANFIS models, MLP 3 produces the best results for both stations at different depths (10 and 20 cm), and ANFIS 3 produces the best results for both stations at two different depths except for Champaign station at the 20 cm depth. Results of MLP are better than those of ANFIS for both stations at different depths. The MLP-based spatial distribution is used to estimate daily soil temperature using the best input combinations (one, two, and three inputs) at different depths below the ground. The MLP-based spatial distribution estimates daily soil temperature with high accuracy, but the results of MLP and ANFIS are better than those of the MLP-based spatial distribution for both stations at different depths. Data-driven models can estimate daily soil temperature successfully in this study.

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

    NASA Astrophysics Data System (ADS)

    Asadzadeh, Masoud; Leon, Luis; Yang, Wanhong; Bosch, David

    2016-03-01

    Hydrologic modeling literature illustrates that daily simulation models are incapable of accurately representing hydrograph timing due to relationships between precipitation and watershed hydrologic response that happen with a sub-daily time step in the real world. For watersheds with a time of concentration less than 24 h and a late day precipitation event, the observed hydrographic response frequently occurs one day after the precipitation peak while the model simulates a same day event. The analysis of sub-daily precipitation and runoff in this study suggests that, this one-day offset is inevitable in daily analysis of the precipitation-runoff relationship when the same 24-h time interval, e.g. the calendar day, is used to prepare daily precipitation and runoff datasets. Under these conditions, daily simulation models will fail to emulate this one-day offset issue (1dOI) and result in significant daily residuals between simulated and measured hydrographs. Results of this study show that the automatic calibration of such daily models will be misled by model performance metrics that are based on the aggregation of daily residuals to a solution that systematically underestimate the peak flow rates while trying to emulate the one-day lags. In this study, a novel algorithm called Shifting Hydrograph In order to Fix Timing (SHIFT) is developed to reduce the impact of this one-day offset issue (1dOI) on the parameter estimation of daily simulation models. Results show that with SHIFT the aforementioned automatic calibration finds a solution that accurately estimates the magnitude of daily peak flow rates and the shape of the rising and falling limbs of the daily hydrograph. Moreover, it is shown that this daily calibrated model performs quite well with an alternative daily precipitation dataset that has a minimal number of 1dOIs, concluding that SHIFT can minimize the impact of 1dOI on parameter estimation of daily simulation models.

  12. 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)

  13. 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.

  14. 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...

  15. Multilevel Factor Analysis and Structural Equation Modeling of Daily Diary Coping Data: Modeling Trait and State Variation

    ERIC Educational Resources Information Center

    Roesch, Scott C.; Aldridge, Arianna A.; Stocking, Stephanie N.; Villodas, Feion; Leung, Queenie; Bartley, Carrie E.; Black, Lisa J.

    2010-01-01

    This study used multilevel modeling of daily diary data to model within-person (state) and between-person (trait) components of coping variables. This application included the introduction of multilevel factor analysis (MFA) and a comparison of the predictive ability of these trait/state factors. Daily diary data were collected on a large (n =…

  16. 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...

  17. Modeling daily realized futures volatility with singular spectrum analysis

    NASA Astrophysics Data System (ADS)

    Thomakos, Dimitrios D.; Wang, Tao; Wille, Luc T.

    2002-09-01

    Using singular spectrum analysis (SSA), we model the realized volatility and logarithmic standard deviations of two important futures return series. The realized volatility and logarithmic standard deviations are constructed following the methodology of Andersen et al. [J. Am. Stat. Ass. 96 (2001) 42-55] using intra-day transaction data. We find that SSA decomposes the volatility series quite well and effectively captures both the market trend (accounting for about 34-38% of the total variance in the series) and, more importantly, a number of underlying market periodicities. Reliable identification of any periodicities is extremely important for options pricing and risk management and we believe that SSA can be a useful addition to the financial practitioners’ toolbox.

  18. The development of a regional geomagnetic daily variation model using neural networks

    NASA Astrophysics Data System (ADS)

    Sutcliffe, P. R.

    2000-01-01

    Global and regional geomagnetic field models give the components of the geomagnetic field as functions of position and epoch; most utilise a polynomial or Fourier series to map the input variables to the geomagnetic field values. The only temporal variation generally catered for in these models is the long term secular variation. However, there is an increasing need amongst certain users for models able to provide shorter term temporal variations, such as the geomagnetic daily variation. In this study, for the first time, artificial neural networks (ANNs) are utilised to develop a geomagnetic daily variation model. The model developed is for the southern African region; however, the method used could be applied to any other region or even globally. Besides local time and latitude, input variables considered in the daily variation model are season, sunspot number, and degree of geomagnetic activity. The ANN modelling of the geomagnetic daily variation is found to give results very similar to those obtained by the synthesis of harmonic coefficients which have been computed by the more traditional harmonic analysis of the daily variation.

  19. 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...

  20. Daily radiation model for use in the simulation of passive solar buildings

    SciTech Connect

    Sillman, S.; Wortman, D.

    1981-04-01

    A model is presented to characterize solar radiation with just three input parameters for each day. This compressed daily radiation data may be used in place of hourly data in simulations of passive solar buildings. This method is tested with the SUNCAT passive simulation. Global horizontal and direct normal radiation data are input using the compressed daily form instead of by hour. Simulation results are found to be comparable to results based on hourly radiation data.

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

    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 timestep 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 time scales) and the observed positive and negative anomalies from the smoothed timeseries (short timescales) as separate terms. A climatology of fit is also included as a predictor variable. Over a half-million, daily observations of depth and SWE at 345 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 timeseries 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 RMSE by 9.6% and 4.2% compared to previous models. Similarly, R2 increases from 0.46 to 0.52 to 0.56 across models. Removing the challenge of parameter transfer 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 the existing models when data are more frequent than once every 5 days and at least 3 stations are available for training.

  2. Wavelet and ANN combination model for prediction of daily suspended sediment load in rivers.

    PubMed

    Rajaee, Taher

    2011-07-01

    In this research, a new wavelet artificial neural network (WANN) model was proposed for daily suspended sediment load (SSL) prediction in rivers. In the developed model, wavelet analysis was linked to an artificial neural network (ANN). For this purpose, daily observed time series of river discharge (Q) and SSL in Yadkin River at Yadkin College, NC station in the USA were decomposed to some sub-time series at different levels by wavelet analysis. Then, these sub-time series were imposed to the ANN technique for SSL time series modeling. To evaluate the model accuracy, the proposed model was compared with ANN, multi linear regression (MLR), and conventional sediment rating curve (SRC) models. The comparison of prediction accuracy of the models illustrated that the WANN was the most accurate model in SSL prediction. Results presented that the WANN model could satisfactorily simulate hysteresis phenomenon, acceptably estimate cumulative SSL, and reasonably predict high SSL values. PMID:21546062

  3. 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...

  4. 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.

  5. Spatial temporal disaggregation of daily rainfall from a generalized linear model

    NASA Astrophysics Data System (ADS)

    Segond, M.-L.; Onof, C.; Wheater, H. S.

    2006-12-01

    SummaryThis paper describes a methodology for continuous simulation of spatially-distributed hourly rainfall, based on observed data from a daily raingauge network. Generalized linear models (GLMs), which can represent the spatial and temporal non-stationarities of multi-site daily rainfall (Chandler, R.E., Wheater, H.S., 2002. Analysis of rainfall variability using generalised linear models: a case study from the west of Ireland. Water Resources Research, 38 (10), 1192. doi:10.1029/2001WR000906), are combined with a single-site disaggregation model based on Poisson cluster processes (Koutsoyiannis, D., Onof, C., 2001. Rainfall disaggregation using adjusting procedures on a Poisson cluster model. Journal of Hydrology 246, 109-122). The resulting sub-daily temporal profile is then applied linearly to all sites over the catchment to reproduce the spatially-varying daily totals. The method is tested for the River Lee catchment, UK, a tributary of the Thames covering an area of 1400 km 2. Twenty simulations of 12 years of hourly rainfall are generated at 20 sites and compared with the historical series. The proposed model preserves most standard statistics but has some limitations in the representation of extreme rainfall and the correlation structure. The method can be extended to sites within the modelled region not used in the model calibration.

  6. 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.

  7. 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

  8. Estimation of instantaneous peak flow from daily data using the HBV model

    NASA Astrophysics Data System (ADS)

    Ding, Jie; Haberlandt, Uwe

    2015-04-01

    The length of the observed instantaneous peak flow (IPF) period has a great influence on the flood design whereas these high resolution flow data are not always available. Our previous research has shown that IPFs can be derived from the easier available observed long time series of mean daily flows (MDFs) using a multiple regression model. The primary aim here is to explore the possibility of deriving frequency distributions of IPFs using hydrological modelling with daily and hourly time steps in comparison. In the post-correction approach the rainfall-runoff model is operated on daily time steps , a flood frequency distribution is fitted to the simulated annual MDFs and the resulting daily quantiles are transferred into IPF quantiles using the multiple regression model. In the pre-processing approach, hourly rainfall is produced by disaggregation of daily data. Then the rainfall-runoff model is operated on hourly time steps resulting in a frequency distribution of IPFs. In addition, two calibrations strategies for the hydrological model using the hydrograph and using flow statistics, respectively, are applied for both approaches. Finally, the performances of estimating the IPFs from daily data using these two approaches are compared considering also the two different calibration strategies. The hydrological simulations are carried out with the HBV-IWW model and the case study is carried out for 18 catchments of the Aller-Leine-River basin in northern Germany. The results show that: (1) the multiple regression model is capable to predict IPFs with the simulated MDFs as well; (2) the estimation of extreme flow quantiles in summer is not as good as in winter; (3) both of the two approaches enable a reasonable estimation of IPFs; (4) if on hand the hydrological model is calibrated on the hydrograph the post-correction approach with daily simulations is superior and if on the other hand the model is calibrated on flow statistics the pre-processing with hourly

  9. 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.

  10. 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

  11. A comparison of modeling schemes for mapping daily evapotranspiration at high resolution using remote sensing

    NASA Astrophysics Data System (ADS)

    Ring, T.; Cuenca, R. H.; Anderson, M. C.; Hain, C.; Semmens, K. A.; Kustas, W. P.; Alfieri, J. G.

    2014-12-01

    Evapotranspiration (ET) is an important component of the hydrologic cycle that transfers large quantities of water vapor away from Earth's surface into the atmosphere. In addition to having water management applications in agriculture, including monitoring water rights compliance and irrigation scheduling, it is also important to be able to accurately measure water used by other landscapes for soil-vegetation-atmosphere-transfer (SVAT) models. This can only be done with large scale estimations which are most efficiently achieved with remote sensing. This research compares daily ET retrieved from two remote sensing modeling schemes: a) Reconstructed METRIC: Mapping EvapoTranspiration at high Resolution with Internalized Calibration; and b) ALEXI/DisALEXI: Atmosphere-Land EXchange Inverse /Disaggregated ALEXI, over two predominately forested landscapes. ET flux estimates are retrieved from ALEXI/DisALEXI using GOES (daily, 4km), MODIS (daily, 1km) and Landsat 8 (16 days, 30m) and from Reconstructed METRIC using Landsat 8. We develop daily Landsat scale ET maps for the summer months of 2013. The flux-tower footprint is calculated at each site to match the remotely sensed retrieval with that of the flux tower such that modeled output can be evaluated against ground based observations, taken from the AmeriFlux network. In addition, surface and evaporative fluxes retrieved from the two models are inter-compared over the different land cover types in the scenes. Differences in input and data processing requirements for each of the two methods will be also described

  12. 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…

  13. 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...

  14. 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)

  15. 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%.

  16. Influence of daily versus monthly fire emissions on atmospheric model applications in the tropics

    NASA Astrophysics Data System (ADS)

    Marlier, M. E.; Voulgarakis, A.; Faluvegi, G.; Shindell, D. T.; DeFries, R. S.

    2012-12-01

    Fires are widely used throughout the tropics to create and maintain areas for agriculture, but are also significant contributors to atmospheric trace gas and aerosol concentrations. However, the timing and magnitude of fire activity can vary strongly by year and ecosystem type. For example, frequent, low intensity fires dominate in African savannas whereas Southeast Asian peatland forests are susceptible to huge pulses of emissions during regional El Niño droughts. Despite the potential implications for modeling interactions with atmospheric chemistry and transport, fire emissions have commonly been input into global models at a monthly resolution. Recognizing the uncertainty that this can introduce, several datasets have parsed fire emissions to daily and sub-daily scales with satellite active fire detections. In this study, we explore differences between utilizing the monthly and daily Global Fire Emissions Database version 3 (GFED3) products as inputs into the NASA GISS-E2 composition climate model. We aim to understand how the choice of the temporal resolution of fire emissions affects uncertainty with respect to several common applications of global models: atmospheric chemistry, air quality, and climate. Focusing our analysis on tropical ozone, carbon monoxide, and aerosols, we compare modeled concentrations with available ground and satellite observations. We find that increasing the temporal frequency of fire emissions from monthly to daily can improve correlations with observations, predominately in areas or during seasons more heavily affected by fires. Differences between the two datasets are more evident with public health applications: daily resolution fire emissions increases the number of days exceeding World Health Organization air quality targets.

  17. 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.

  18. A Predictive Model of Daily Seismic Activity Induced by Mining, Developed with Data Mining Methods

    NASA Astrophysics Data System (ADS)

    Jakubowski, Jacek

    2014-12-01

    The article presents the development and evaluation of a predictive classification model of daily seismic energy emissions induced by longwall mining in sector XVI of the Piast coal mine in Poland. The model uses data on tremor energy, basic characteristics of the longwall face and mined output in this sector over the period from July 1987 to March 2011. The predicted binary variable is the occurrence of a daily sum of tremor seismic energies in a longwall that is greater than or equal to the threshold value of 105 J. Three data mining analytical methods were applied: logistic regression,neural networks, and stochastic gradient boosted trees. The boosted trees model was chosen as the best for the purposes of the prediction. The validation sample results showed its good predictive capability, taking the complex nature of the phenomenon into account. This may indicate the applied model's suitability for a sequential, short-term prediction of mining induced seismic activity.

  19. 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

  20. 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

  1. 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

  2. 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). PMID:26812150

  3. 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.

  4. Daily Care

    MedlinePlus

    ... to Know Online Tools Enhancing Daily Life Daily Plan Activities Communication Food & Eating Music & Art Personal Care Incontinence Bathing ... Tweet Email | Print Create a Daily Routine Daily Plan Activities Communication Food/Eating Get Tips on Personal Care Bathing ...

  5. Global forecast model to predict the daily dose of the solar erythemally effective UV radiation.

    PubMed

    Schmalwieser, Alois W; Schauberger, Günther; Janouch, Michal; Nunez, Manuel; Koskela, Tapani; Berger, Daniel; Karamanian, Gabriel

    2005-01-01

    A worldwide forecast of the erythemally effective ultraviolet (UV) radiation is presented. The forecast was established to inform the public about the expected amount of erythemally effective UV radiation for the next day. Besides the irradiance, the daily dose is forecasted to enable people to choose the appropriate sun protection tools. Following the UV Index as the measure of global erythemally effective irradiance, the daily dose is expressed in units of UV Index hours. In this study, we have validated the model and the forecast against measurements from broadband UV radiometers of the Robertson-Berger type. The measurements were made at four continents ranging from the northern polar circle (67.4 degrees N) to the Antarctic coast (61.1 degrees S). As additional quality criteria the frequency of underestimation was taken into account because the forecast is a tool of radiation protection and made to avoid overexposure. A value closer than one minimal erythemal dose for the most sensitive skin type 1 to the observed value was counted as hit and greater deviations as underestimation or overestimation. The Austrian forecast model underestimates the daily dose in 3.7% of all cases, whereas 1.7% results from the model and 2.0% from the assumed total ozone content. The hit rate could be found in the order of 40%. PMID:15453822

  6. Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, 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 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. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

  7. Development of Daily Maximum Flare-Flux Forecast Models for Strong Solar Flares

    NASA Astrophysics Data System (ADS)

    Shin, Seulki; Lee, Jin-Yi; Moon, Yong-Jae; Chu, Hyoungseok; Park, Jongyeob

    2016-03-01

    We have developed a set of daily maximum flare-flux forecast models for strong flares (M- and X-class) using multiple linear regression (MLR) and artificial neural network (ANN) methods. Our input parameters are solar-activity data from January 1996 to December 2013 such as sunspot area, X-ray maximum, and weighted total flare flux of the previous day, as well as mean flare rates of McIntosh sunspot group (Zpc) and Mount Wilson magnetic classifications. For a training dataset, we used 61 events each of C-, M-, and X-class from January 1996 to December 2004. For a testing dataset, we used all events from January 2005 to November 2013. A comparison between our maximum flare-flux models and NOAA model based on true skill statistics (TSS) shows that the MLR model for X-class and the average of all flares (M{+}X-class) are much better than the NOAA model. According to the hitting fraction (HF), which is defined as a fraction of events satisfying the condition that the absolute differences of predicted and observed flare flux on a logarithm scale are smaller than or equal to 0.5, our models successfully forecast the maximum flare flux of about two-thirds of the events for strong flares. Since all input parameters for our models are easily available, the models can be operated steadily and automatically on a daily basis for space-weather services.

  8. An Extended Version of the Richardson Model for Simulating Daily Weather Variables.

    NASA Astrophysics Data System (ADS)

    Parlange, Marc B.; Katz, Richard W.

    2000-05-01

    The Richardson model is a popular technique for stochastic simulation of daily weather variables, including precipitation amount, maximum and minimum temperature, and solar radiation. This model is extended to include two additional variables, daily mean wind speed and dewpoint, because these variables (or related quantities such as relative humidity) are required as inputs for certain ecological/vegetation response and agricultural management models. To allow for the positively skewed distribution of wind speed, a power transformation is applied. Solar radiation also is transformed to make the shape of its modeled distribution more realistic. A model identification criterion is used as an aid in determining whether the distributions of these two variables depend on precipitation occurrence. The approach can be viewed as an integration of what is known about the statistical properties of individual weather variables into a single multivariate model.As an application, this extended model is fitted to weather data in the Pacific Northwest. To aid in understanding how such a stochastic weather generator works, considerable attention is devoted to its statistical properties. In particular, marginal and conditional distributions of wind speed and solar radiation are examined, with the model being capable of representing relationships between variables in which the variance is not constant, as well as certain forms of nonlinearity.

  9. 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

  10. Fitting optimum order of Markov chain models for daily rainfall occurrences in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Deni, Sayang Mohd; Jemain, Abdul Aziz; Ibrahim, Kamarulzaman

    2009-06-01

    The analysis of the daily rainfall occurrence behavior is becoming more important, particularly in water-related sectors. Many studies have identified a more comprehensive pattern of the daily rainfall behavior based on the Markov chain models. One of the aims in fitting the Markov chain models of various orders to the daily rainfall occurrence is to determine the optimum order. In this study, the optimum order of the Markov chain models for a 5-day sequence will be examined in each of the 18 rainfall stations in Peninsular Malaysia, which have been selected based on the availability of the data, using the Akaike’s (AIC) and Bayesian information criteria (BIC). The identification of the most appropriate order in describing the distribution of the wet (dry) spells for each of the rainfall stations is obtained using the Kolmogorov-Smirnov goodness-of-fit test. It is found that the optimum order varies according to the levels of threshold used (e.g., either 0.1 or 10.0 mm), the locations of the region and the types of monsoon seasons. At most stations, the Markov chain models of a higher order are found to be optimum for rainfall occurrence during the northeast monsoon season for both levels of threshold. However, it is generally found that regardless of the monsoon seasons, the first-order model is optimum for the northwestern and eastern regions of the peninsula when the level of thresholds of 10.0 mm is considered. The analysis indicates that the first order of the Markov chain model is found to be most appropriate for describing the distribution of wet spells, whereas the higher-order models are found to be adequate for the dry spells in most of the rainfall stations for both threshold levels and monsoon seasons.

  11. 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

  12. Infilling Missing Daily Precipitation Data at Multiple Sites Using a Multivariate Truncated Normal Distribution Model

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

    Stochastic weather modeling is subject to a number of challenges including varied spatial-dependency and the existence of missing observations. Daily precipitation possesses unique statistical characteristics in distribution, such as the existence of high frequency of zero records and the high skewness of the distribution of precipitation amount. To address for these difficulties, a methodology based on the multivariate truncated Normal distribution model is proposed. The methodology transforms the skewed distribution of precipitation amounts at multiple sites into a multivariate Normal distribution model. The missing observations are then be estimated through the conditional mean and variance obtained from the multivariate Normal distribution model. The adequacy of the proposed model structure was first verified using a synthetic data set. Subsequently, 30 years of historical daily precipitation records from 10 Canadian meteorological stations were used to evaluate the performance of the model. The result of the evaluation shows that the proposed model reasonably can preserve the statistical characteristics of the historical records in estimated the missing records at multiple sites.

  13. 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. PMID:22029618

  14. Statistical Modeling of Spatio-Temporal Variability in Monthly Average Daily Solar Radiation over Turkey

    PubMed Central

    Evrendilek, Fatih; Ertekin, Can

    2007-01-01

    Though one of the most significant driving forces behind ecological processes such as biogeochemical cycles and energy flows, solar radiation data are limited or non-existent by conventional ground-based measurements, and thus, often estimated from other meteorological data through (geo)statistical models. In this study, spatial and temporal patterns of monthly average daily solar radiation on a horizontal surface at the ground level were quantified using 130 climate stations for the entire Turkey and its conventionally-accepted seven geographical regions through multiple linear regression (MLR) models as a function of latitude, longitude, altitude, aspect, distance to sea; minimum, maximum and mean air temperature and relative humidity, soil temperature, cloudiness, precipitation, pan evapotranspiration, day length, maximum possible sunshine duration, monthly average daily extraterrestrial solar radiation, and time (month), and universal kriging method. The resulting 20 regional best-fit MLR models (three MLR models for each region) based on parameterization datasets had R2adj values of 91.5% for the Central Anatolia region to 98.0% for the Southeast Anatolia region. Validation of the best-fit MLR models for each region led to R2 values of 87.7% for the Mediterranean region to 98.5% for the Southeast Anatolia region. The best-fit anisotropic semi-variogram models for universal kriging as a result of one-leave-out cross-validation gave rise to R2 values of 10.9% in July to 52.4% in November. Surface maps of monthly average daily solar radiation were generated over Turkey, with a grid resolution of 500 m × 500 m.

  15. 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.

  16. Neyman-Scott cluster model for daily rainfall processes in lower extremadura (Spain): Rainfall Generating Mechanisms

    NASA Astrophysics Data System (ADS)

    Marroquin, A.; Garcia, J. A.; Garrido, J.; Mateos, V. L.

    1995-09-01

    A Neyman-Scott cluster model was fitted to the daily rainfall data recorded at the observatory of Badajoz (southwestern Spain) for the period 1901 1990. The data were previously homogenized. The goodness of the fit that indicated the daily rainfall process follows some Rainfall Generating Mechanism (RGM). Having decided on the criteria that a block of rainfall must fulfill to be considered as a RGM, a method was proposed to classify the days that belong to RGMs according to the 500 hPa and the surface topography. In this method each day is characterized by a string of 22 alphanumeric characters. From the subsequent analysis, the structure of the synoptic patterns associated with each RGM was deduced.

  17. Statistical modeling of daily urban water consumption in Hong Kong: Trend, changing patterns, and forecast

    NASA Astrophysics Data System (ADS)

    Wong, Jefferson See; Zhang, Qiang; Chen, Yongqin David

    2010-03-01

    This study attempted to address statistical properties and forecast of daily urban water consumption in Hong Kong from 1990 to 2007. A statistical model was formulated to differentiate the effects of five factors on water use, i.e., trend, seasonality, climatic regression, calendar effect, and autoregression. The postulate of the statistical model is that total water use is made up of base, seasonal, and calendrical water use. Daily urban water consumption in Hong Kong from 1990 to 2001 was modeled and the developed statistical model explains 83% of the variance with six factors: trend (8%), seasonality (27%), climatic regression (2%), day-of-the-week effect (17%), holiday effect (17%), and autoregression (12%). The model was further validated using an independent data set from 2002 to 2007, yielding a R2 of 76%. The results indicated good performance of the developed statistical model in depicting the temporal variations of the urban water use in Hong Kong, offering an improved insight into urban utilization of water resources and acting as the theoretical support for effective urban water resource management in Hong Kong under the changing environment.

  18. The optimum order of a Markov chain model for daily rainfall in Nigeria

    NASA Astrophysics Data System (ADS)

    Jimoh, O. D.; Webster, P.

    1996-11-01

    Markov type models are often used to describe the occurrence of daily rainfall. Although models of Order 1 have been successfully employed, there remains uncertainty concerning the optimum order for such models. This paper is concerned with estimation of the optimum order of Markov chains and, in particular, the use of objective criteria of the Akaike and Bayesian Information Criteria (AIC and BIC, respectively). Using daily rainfall series for five stations in Nigeria, it has been found that the AIC and BIC estimates vary with month as well as the value of the rainfall threshold used to define a wet day. There is no apparent system to this variation, although AIC estimates are consistently greater than or equal to BIC estimates, with values of the latter limited to zero or unity. The optimum order is also investigated through generation of synthetic sequences of wet and dry days using the transition matrices of zero-, first- and second-order Markov chains. It was found that the first-order model is superior to the zero-order model in representing the characteristics of the historical sequence as judged using frequency duration curves. There was no discernible difference between the model performance for first- and second-order models. There was no seasonal varation in the model performance, which contrasts with the optimum models identified using AIC and BIC estimates. It is concluded that caution is needed with the use of objective criteria for determining the optimum order of the Markov model and that the use of frequency duration curves can provide a robust alternative method of model identification. Comments are also made on the importance of record length and non-stationarity for model identification

  19. Generating daily weather data for ecosystem modelling in the Congo River Basin

    NASA Astrophysics Data System (ADS)

    Petritsch, Richard; Pietsch, Stephan A.

    2010-05-01

    Daily weather data are an important constraint for diverse applications in ecosystem research. In particular, temperature and precipitation are the main drivers for forest ecosystem productivity. Mechanistic modelling theory heavily relies on daily values for minimum and maximum temperatures, precipitation, incident solar radiation and vapour pressure deficit. Although the number of climate measurement stations increased during the last centuries, there are still regions with limited climate data. For example, in the WMO database there are only 16 stations located in Gabon with daily weather measurements. Additionally, the available time series are heavily affected by measurement errors or missing values. In the WMO record for Gabon, on average every second day is missing. Monthly means are more robust and may be estimated over larger areas. Therefore, a good alternative is to interpolate monthly mean values using a sparse network of measurement stations, and based on these monthly data generate daily weather data with defined characteristics. The weather generator MarkSim was developed to produce climatological time series for crop modelling in the tropics. It provides daily values for maximum and minimum temperature, precipitation and solar radiation. The monthly means can either be derived from the internal climate surfaces or prescribed as additional inputs. We compared the generated outputs observations from three climate stations in Gabon (Lastourville, Moanda and Mouilla) and found that maximum temperature and solar radiation were heavily overestimated during the long dry season. This is due to the internal dependency of the solar radiation estimates to precipitation. With no precipitation a cloudless sky is assumed and thus high incident solar radiation and a large diurnal temperature range. However, in reality it is cloudy in the Congo River Basin during the long dry season. Therefore, we applied a correction factor to solar radiation and temperature range

  20. 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. PMID:26992392

  1. Development of Daily Solar Maximum Flare Flux Forecast Models for Strong Flares

    NASA Astrophysics Data System (ADS)

    Shin, Seulki; Chu, Hyoungseok

    2015-08-01

    We have developed a set of daily solar maximum flare flux forecast models for strong flares using Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) methods. We consider input parameters as solar activity data from January 1996 to December 2013 such as sunspot area, X-ray maximum flare flux and weighted total flux of the previous day, and mean flare rates of McIntosh sunspot group (Zpc) and Mount Wilson magnetic classification. For a training data set, we use the same number of 61 events for each C-, M-, and X-class from Jan. 1996 to Dec. 2004, while other previous models use all flares. For a testing data set, we use all flares from Jan. 2005 to Nov. 2013. The statistical parameters from contingency tables show that the ANN models are better for maximum flare flux forecasting than the MLR models. A comparison between our maximum flare flux models and the previous ones based on Heidke Skill Score (HSS) shows that our all models for X-class flare are much better than the other models. According to the Hitting Fraction (HF), which is defined as a fraction of events satisfying that the absolute differences of predicted and observed flare flux in logarithm scale are less than equal to 0.5, our models successfully forecast the maximum flare flux of about two-third events for strong flares. Since all input parameters for our models are easily available, the models can be operated steadily and automatically on daily basis for space weather service.

  2. Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models

    NASA Astrophysics Data System (ADS)

    Piani, C.; Weedon, G. P.; Best, M.; Gomes, S. M.; Viterbo, P.; Hagemann, S.; Haerter, J. O.

    2010-12-01

    SummaryA statistical bias correction methodology for global climate simulations is developed and applied to daily land precipitation and mean, minimum and maximum daily land temperatures. The bias correction is based on a fitted histogram equalization function. This function is defined daily, as opposed to earlier published versions in which they were derived yearly or seasonally at best, while conserving properties of robustness and eliminating unrealistic jumps at seasonal or monthly transitions. The methodology is tested using the newly available global dataset of observed hydrological forcing data of the last 50 years from the EU project WATCH (WATer and global CHange) and an initial conditions ensemble of simulations performed with the ECHAM5 global climate model for the same period. Bias corrections are derived from 1960 to 1969 observed and simulated data and then applied to 1990-1999 simulations. Results confirm the effectiveness of the methodology for all tested variables. Bias corrections are also derived using three other non-overlapping decades from 1970 to 1999 and all members of the ECHAM5 initial conditions ensemble. A methodology is proposed to use the resulting "ensemble of bias corrections" to quantify the error in simulated scenario projections of components of the hydrological cycle.

  3. Incorporating Daily Flood Control Objectives Into a Monthly Stochastic Dynamic Programing Model for a Hydroelectric Complex

    NASA Astrophysics Data System (ADS)

    Druce, Donald J.

    1990-01-01

    A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model establishes the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.

  4. Effect of Estimated Daily Global Solar Radiation Data on the Results of Crop Growth Models

    PubMed Central

    Trnka, Miroslav; Eitzinger, Josef; Kapler, Pavel; Dubrovský, Martin; Semerádová, Daniela; Žalud, Zden ěk; Formayer, Herbert

    2007-01-01

    The results of previous studies have suggested that estimated daily global radiation (RG) values contain an error that could compromise the precision of subsequent crop model applications. The following study presents a detailed site and spatial analysis of the RG error propagation in CERES and WOFOST crop growth models in Central European climate conditions. The research was conducted i) at the eight individual sites in Austria and the Czech Republic where measured daily RG values were available as a reference, with seven methods for RG estimation being tested, and ii) for the agricultural areas of the Czech Republic using daily data from 52 weather stations, with five RG estimation methods. In the latter case the RG values estimated from the hours of sunshine using the Ångström-Prescott formula were used as the standard method because of the lack of measured RG data. At the site level we found that even the use of methods based on hours of sunshine, which showed the lowest bias in RG estimates, led to a significant distortion of the key crop model outputs. When the Ångström-Prescott method was used to estimate RG, for example, deviations greater than ±10 per cent in winter wheat and spring barley yields were noted in 5 to 6 per cent of cases. The precision of the yield estimates and other crop model outputs was lower when RG estimates based on the diurnal temperature range and cloud cover were used (mean bias error 2.0 to 4.1 per cent). The methods for estimating RG from the diurnal temperature range produced a wheat yield bias of more than 25 per cent in 12 to 16 per cent of the seasons. Such uncertainty in the crop model outputs makes the reliability of any seasonal yield forecasts or climate change impact assessments questionable if they are based on this type of data. The spatial assessment of the RG data uncertainty propagation over the winter wheat yields also revealed significant differences within the study area. We found that RG estimates based on

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

    NASA Astrophysics Data System (ADS)

    Mandal, S.; Choudhury, B. U.

    2015-07-01

    Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.

  10. Operationalizing Pain Treatment in the Biopsychosocial Model: Take a Daily "SWEM"--Socialize, Work, Exercise, Meditate.

    PubMed

    Collen, Mark

    2015-09-01

    In the United States, chronic pain is often poorly treated at an exceedingly high cost. The use of the biomedical model to manage pain is frequently ineffective, and evidence suggests that the biopsychosocial (BPS) model is a better choice. A problem with the BPS model is that it has not been operationalized in terms of patient behavior. This commentary addresses that issue by suggesting that people with chronic pain and illness participate daily in four self-management health behaviors: socialize, work, exercise, and meditation, and discusses evidence that supports these recommendations. These self-management behaviors may decrease pain and thus reduce the need for pain medications and other medical interventions. Additional topics include patient adherence and health coaching. PMID:26367791

  11. Support of total maximum daily load programs using spatially referenced regression models

    USGS Publications Warehouse

    McMahon, G.; Alexander, R.B.; Qian, S.

    2003-01-01

    The spatially referenced regressions on watershed attributes modeling approach, as applied to predictions of total nitrogen flux in three North Carolina river basins, addresses several information needs identified by a National Research Council evaluation of the total maximum daily load program. The model provides reach-level predictions of the probability of exceeding water-quality criteria, and estimates of total nitrogen budgets. Model estimates of point- and diffuse-source contributions and nitrogen loss rates in streams and reservoirs compared moderately well with literature estimates. Maps of reach-level predictions of nutrient inputs and delivery provide an intuitive and spatially detailed summary of the origins and fate of nutrients within a basin.

  12. Space-time modeling of a rainfall field ; Application to daily rainfall in the Loire basin

    NASA Astrophysics Data System (ADS)

    Lepioufle, Jean-Marie; Leblois, Etienne; Creutin, Jean-Dominique

    2010-05-01

    Water resources management for a watershed necessitates to assess both high flow volumes and the impact of the management practice for different stakeholders (hydropower, irrigation, ecology...). To test different management strategies, hydrologists have developed hydrological distributed models incorporating several computational objects such as digital elevation model, sub-basins, and distances to the basin outlet. A good characterization of rainfall variability in space and time is crucial for the relevance of a hydrological model as a basis for the choice of water management strategy. Climatological references of rainfall hazard must be built from observation over decades. Daily rainfall measurements from raingauge networks are therefore still an invaluable source of information for a precise representation of precipitation hazard despite the recent availability of radar estimates. Based on either raingauge or radar observations, it is possible to mathematically model rainfall field as a space-time intermittent process (superposition of inner variability field and rainfall indicator field, both influenced by advection). Geostatistics enables to investigate the link between an instantaneous process space-time structure and the evolution of spatial structure with time aggregation.. A method is proposed to infer a relevant instantaneous process from observed rainfall statistics. After fitting the parameters of the instantaneous space-time variogram with the simplex method, spatial variograms for different duration respecting time aggregated variograms is calculated. With this basis, an avenue is open to simulate homogeneous rainfall fields which respect major statistical characteristics for hydrologists: expectation and variance of rainfall distribution and spatial variogram for different durations. Benefits and limits of this approach are investigated using daily rainfall data from the Loire basin in France. Two sub-regions are highlighted. A downstream zone

  13. 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

  14. Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis

    NASA Astrophysics Data System (ADS)

    Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav; Reeves, Geoffrey D.; Clilverd, Mark

    2016-04-01

    The daily maximum relativistic electron flux at geostationary orbit can be predicted well with a set of daily averaged predictor variables including previous day's flux, seed electron flux, solar wind velocity and number density, AE index, IMF Bz, Dst, and ULF and VLF wave power. As predictor variables are intercorrelated, we used multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Empirical models produced from regressions of flux on measured predictors from 1 day previous were reasonably effective at predicting novel observations. Adding previous flux to the parameter set improves the prediction of the peak of the increases but delays its anticipation of an event. Previous day's solar wind number density and velocity, AE index, and ULF wave activity are the most significant explanatory variables; however, the AE index, measuring substorm processes, shows a negative correlation with flux when other parameters are controlled. This may be due to the triggering of electromagnetic ion cyclotron waves by substorms that cause electron precipitation. VLF waves show lower, but significant, influence. The combined effect of ULF and VLF waves shows a synergistic interaction, where each increases the influence of the other on flux enhancement. Correlations between observations and predictions for this 1 day lag model ranged from 0.71 to 0.89 (average: 0.78). A path analysis of correlations between predictors suggests that solar wind and IMF parameters affect flux through intermediate processes such as ring current (Dst), AE, and wave activity.

  15. Ecological Interventionist Causal Models in Psychosis: Targeting Psychological Mechanisms in Daily Life.

    PubMed

    Reininghaus, Ulrich; Depp, Colin A; Myin-Germeys, Inez

    2016-03-01

    Integrated models of psychotic disorders have posited a number of putative psychological mechanisms that may contribute to the development of psychotic symptoms, but it is only recently that a modest amount of experience sampling research has provided evidence on their role in daily life, outside the research laboratory. A number of methodological challenges remain in evaluating specificity of potential causal links between a given psychological mechanism and psychosis outcomes in a systematic fashion, capitalizing on longitudinal data to investigate temporal ordering. In this article, we argue for testing ecological interventionist causal models that draw on real world and real-time delivered, ecological momentary interventions for generating evidence on several causal criteria (association, time order, and direction/sole plausibility) under real-world conditions, while maximizing generalizability to social contexts and experiences in heterogeneous populations. Specifically, this approach tests whether ecological momentary interventions can (1) modify a putative mechanism and (2) produce changes in the mechanism that lead to sustainable changes in intended psychosis outcomes in individuals' daily lives. Future research using this approach will provide translational evidence on the active ingredients of mobile health and in-person interventions that promote sustained effectiveness of ecological momentary interventions and, thereby, contribute to ongoing efforts that seek to enhance effectiveness of psychological interventions under real-world conditions. PMID:26707864

  16. 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.

  17. 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

  18. 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...

  19. Evaluation of NASA satellite- and assimilation model-derived long-term daily temperature date over the continental US

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agricultural research increasingly is expected to provide precise, quantitative information with an explicit geographic coverage. Limited availability of continuous daily meteorological records often constrains efforts to provide such information through integrated use of simulation models, spatial ...

  20. 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 ...

  1. 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. PMID:16428647

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

    PubMed

    Merz, Erin L; Roesch, Scott C

    2011-02-01

    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

  3. Autoregressive spatially varying coefficients model for predicting daily PM2.5 using VIIRS satellite AOT

    NASA Astrophysics Data System (ADS)

    Schliep, E. M.; Gelfand, A. E.; Holland, D. M.

    2015-12-01

    There is considerable demand for accurate air quality information in human health analyses. The sparsity of ground monitoring stations across the United States motivates the need for advanced statistical models to predict air quality metrics, such as PM2.5, at unobserved sites. Remote sensing technologies have the potential to expand our knowledge of PM2.5 spatial patterns beyond what we can predict from current PM2.5 monitoring networks. Data from satellites have an additional advantage in not requiring extensive emission inventories necessary for most atmospheric models that have been used in earlier data fusion models for air pollution. Statistical models combining monitoring station data with satellite-obtained aerosol optical thickness (AOT), also referred to as aerosol optical depth (AOD), have been proposed in the literature with varying levels of success in predicting PM2.5. The benefit of using AOT is that satellites provide complete gridded spatial coverage. However, the challenges involved with using it in fusion models are (1) the correlation between the two data sources varies both in time and in space, (2) the data sources are temporally and spatially misaligned, and (3) there is extensive missingness in the monitoring data and also in the satellite data due to cloud cover. We propose a hierarchical autoregressive spatially varying coefficients model to jointly model the two data sources, which addresses the foregoing challenges. Additionally, we offer formal model comparison for competing models in terms of model fit and out of sample prediction of PM2.5. The models are applied to daily observations of PM2.5 and AOT in the summer months of 2013 across the conterminous United States. Most notably, during this time period, we find small in-sample improvement incorporating AOT into our autoregressive model but little out-of-sample predictive improvement.

  4. A Modeling Study of Oceanic Response to Daily and Monthly Surface Forcing

    NASA Technical Reports Server (NTRS)

    Sui, Chung-Hsiung; Li, Xiao-Fan; Rienecker, Michele M.; Lau, William K.-M.; Einaudi, Franco (Technical Monitor)

    2001-01-01

    The goal of this study is to investigate the effect of high-frequency surface forcing (wind stresses and heat fluxes) on upper-ocean response. We use the reduced-gravity quasi-isopycnal ocean model by Schopf and Loughe (1995) for this study. Two experiments are performed: one with daily and the other with monthly surface forcing. The two experiments are referred to as DD and MM, respectively. The daily surface wind stress is produced from the SSM/I wind data (Atlas et al. 1991) using the drag coefficient of Large and Pond (1982). The surface latent and sensible heat fluxes are estimated using the atmospheric mixed layer model by Seager et al. (1995) with the time-varying air temperature and specific humidity from the NCEP-NCAR reanalysis (Kalnay et al. 1996). The radiation is based on climatological shortwave radiation from the Earth Radiation Budget Experiment (ERBE) [Harrison et al. 1993] and the daily GEWEX SRB data. The ocean model domain is restricted to the Pacific Ocean with realistic land boundaries. At the southern boundary the model temperature and salinity are relaxed to the Levitus (1994) climatology. The time-mean SST distribution from MM is close to the observed SST climatology while the mean SST field from DD is about 1.5 C cooler. To identify the responsible processes, we examined the mean heat budgets and the heat balance during the first year (when the difference developed) in the two experiments. The analysis reveals that this is contributed by two factors. One is the difference in latent heat flux. The other is the difference in mixing processes. To further evaluate the responsible processes, we repeated the DD experiment by reducing the based vertical diffusion from 1e-4 to 0.5e-5. The resultant SST field becomes quite closer to the observed SST field. SST variability from the two experiments is generally similar, but the equatorial SST differences between the two experiments show interannual variations. We are investigating the possible

  5. Enhancing fecal coliform total maximum daily load models through bacterial source tracking

    USGS Publications Warehouse

    Hyer, K.E.; Moyer, D.L.

    2004-01-01

    Surface water impairment by fecal coliform bacteria is a water quality issue of national scope and importance. In Virginia, more than 400 stream and river segments are on the Commonwealth's 2002 303(d) list because of fecal coliform impairment. Total maximum daily loads (TMDLs) will be developed for most of these listed streams and rivers. Information regarding the major fecal coliform sources that impair surface water quality would enhance the development of effective watershed models and improve TMDLs. Bacterial source tracking (BST) is a recently developed technology for identifying the sources of fecal coliform bacteria and it may be helpful in generating improved TMDLs. Bacterial source tracking was performed, watershed models were developed, and TMDLs were prepared for three streams (Accotink Creek, Christians Creek, and Blacks Run) on Virginia's 303(d) list of impaired waters. Quality assurance of the BST work suggests that these data adequately describe the bacteria sources that are impairing these streams. Initial comparison of simulated bacterial sources with the observed BST data indicated that the fecal coliform sources were represented inaccurately in the initial model simulation. Revised model simulations (based on BST data) appeared to provide a better representation of the sources of fecal coliform bacteria in these three streams. The coupled approach of incorporating BST data into the fecal coliform transport model appears to reduce model uncertainty and should result in an improved TMDL.

  6. 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

    2015-11-01

    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.

  7. 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

  8. Investigating daily summertime circulation and precipitation over West Africa with the WRF model: a regional climate model adaptation study

    NASA Astrophysics Data System (ADS)

    Noble, Erik Ulysses

    This dissertation a) evaluates the performance of the NCAR Weather and Research Forecasting (WRF) model as a West African Sahel regional-atmospheric model and b) investigates the utility of regional modeling to meeting user-needs. This work represents the beginning of an effort to adapt the model as a regional climate model (RCM) for the Sahel. Two independent studies test WRF sensitivity to 64 configurations of alternative parameterizations in a series of September simulations. In all, 104 12-day simulations during 11 consecutive years are examined. Simulated daily and mean circulation results are validated against NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and NCEP Reanalysis-2. Modeled daily and total precipitation results are validated against NASA's Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) data. Particular attention is given to westward-propagating precipitation maxima associated with transient African Easterly Waves (AEWs). A wide range of 700-hPa vorticity and daily precipitation validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve circulation correlations against reanalysis of 0.40-0.60 and realistic amplitudes of spatiotemporal variability for the 2006 focus year, but they get time-longitude precipitation correlations (against GPCP) of between 0.35-0.42. A parallel-benchmark-simulation by the NASA Regional Model-3 (RM3) achieves higher correlations but less realistic spatiotemporal variability. The largest favorable impact on WRF vorticity and precipitation validation is achieved by selecting the Grell-Devenyi cumulus convection scheme, resulting in higher correlations against reanalysis and GPCP than simulations using the Kain-Fritch convection. Other parameterizations have less-obvious impact. A comparison of reanalysis circulation against two NASA-radiosonde stations confirms that both reanalyses represent

  9. Ability in daily activities after early supported discharge models of stroke rehabilitation

    PubMed Central

    Taule, Tina; Strand, Liv Inger; Assmus, Jörg; Skouen, Jan Sture

    2015-01-01

    Abstract More knowledge is needed about how different rehabilitation models in the municipality influence stroke survivors’ ability in activities of daily living (ADL). Objectives: To compare three models of outpatient rehabilitation; early supported discharge (ESD) in a day unit, ESD at home and traditional treatment in the municipality (control group), regarding change in ADL ability during the first three months after stroke. Methods: A group comparison study was designed within a randomized controlled trial. Included participants were tested with the Assessment of Motor and Process Skills (AMPS) at baseline and discharged directly home. Primary and secondary outcomes were the AMPS and the modified Rankin Scale (mRS). Results and conclusions: Included were 154 participants (57% men, median age 73 years), and 103 participants completed the study. There were no significant group differences in pre–post changed ADL ability measured by the AMPS. To find the best rehabilitation model to improve the quality of stroke survivors’ motor and process skills needs further research. Patients participating in the ESD rehabilitation models were, compared with traditional treatment, significantly associated with improved ADL ability measured by the mRS when controlling for confounding factors, indicating that patients with social needs and physical impairment after stroke may benefit from ESD rehabilitation models. PMID:26005768

  10. 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

  11. Forecasting daily pollen concentrations using data-driven modeling methods in Thessaloniki, Greece

    NASA Astrophysics Data System (ADS)

    Voukantsis, Dimitris; Niska, Harri; Karatzas, Kostas; Riga, Marina; Damialis, Athanasios; Vokou, Despoina

    2010-12-01

    Airborne pollen have been associated with allergic symptoms in sensitized individuals, having a direct impact on the overall quality of life of a considerable fraction of the population. Therefore, forecasting elevated airborne pollen concentrations and communicating this piece of information to the public are key issues in prophylaxis and safeguarding the quality of life of the overall population. In this study, we adopt a data-oriented approach in order to develop operational forecasting models (1-7 days ahead) of daily average airborne pollen concentrations of the highly allergenic taxa: Poaceae, Oleaceae and Urticaceae. The models are developed using a representative dataset consisting of pollen and meteorological time-series recorded during the years 1987-2002, in the city of Thessaloniki, Greece. The input variables (features) of the models have been optimized by making use of genetic algorithms, whereas we evaluate the performance of three algorithms: i) multi-Layer Perceptron, ii) support vector regression and iii) regression trees originating from distinct domains of Computational Intelligence (CI), and compare the resulting models with traditional multiple linear regression models. Results show the superiority of CI methods, especially when forecasting several days ahead, compared to traditional multiple linear regression models. Furthermore, the CI models complement each other, resulting to a combined model that performs better than each one separately. The overall performance ranges, in terms of the index of agreement, from 0.85 to 0.93 clearly suggesting the potential operational use of the models. The latter ones can be utilized in provision of personalized and on-time information services, which can improve quality of life of sensitized citizens.

  12. Modelling soil water repellency at the daily scale in Portuguese burnt and unburnt eucalypt stands

    NASA Astrophysics Data System (ADS)

    Nunes, João Pedro; van der Slik, Bart; Marisa Santos, Juliana; Malvar Cortizo, Maruxa; Keizer, Jan Jacob

    2014-05-01

    Soil water repellency can impact soil hydrology, especially soil wetting. This creates a challenge for hydrological modelling in repellency-prone regions, since current models are generally unable to take it into account. This communication focuses on the development and evaluation of a daily water balance model which takes repellency into account, adapted for eucalypt forest plantations in the north-western Iberian Peninsula. The model was developed and tested using data from three eucalypt stands. Two were burnt in 2005, and the data included bi-weekly measurements of soil moisture and water repellency along a transect, during two years. The third was not burnt, and the data included both weekly measurements of soil water repellency and soil moisture along transects, and continuous measurements of soil moisture at one point, performed for one year between 2011 and 2012. All sites showed low repellency during the wet winter season (although less in the unburnt site, as the winter of 2011/12 was comparatively dry) and high repellency during the dry summer season; this seasonal pattern was strongly related with soil moisture fluctuations. The water balance model was based on the Thornthwaite-Mather method. Interception and tree potential evapotranspiration were estimated using satellite imagery (MODIS NDVI), the first by estimating LAI and applying the Gash interception model, and the second using the SAMIR approach. The model itself was modified by first estimating soil water repellency from soil moisture, using an empirical relation taking into account repellent and non-repellent moisture thresholds for each site; and afterwards using soil water repellency as a limiting factor on soil wettability, by limiting the fraction of infiltration which could replenish soil moisture. Results indicate that this simple approach to simulate repellency can provide adequate model performance and can be easily included in hydrological models.

  13. 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

  14. Global changes in seasonal means and extremes of precipitation from daily climate model data

    NASA Astrophysics Data System (ADS)

    Russo, Simone; Sterl, Andreas

    2012-01-01

    We investigate simulated changes of seasonal precipitation maxima and means in a future, warmer climate. We use data from the ESSENCE project, in which a 17-member ensemble of climate change simulations in response to the SRES A1b scenario has been carried out using the ECHAM5/MPI-OM climate model. The large size of the data set gives the opportunity to detect the changes of climate extremes and means with high statistical confidence. Daily precipitation data are used to calculate the seasonal precipitation maximum and the seasonal mean. Modeled precipitation data appear consistent with observation-based data from the Global Precipitation Climatology Project. The data are split into six time periods of 25 years to get independent time series. The seasonal peaks are modeled by using the generalized extreme value distribution, while empirical distributions are used to study changes of the seasonal precipitation mean. Finally, we use an empirical method to detect changes of occurrence of very wet and dry periods. Results from these model simulations indicate that over most of the world precipitation maxima will increase in the future. Seasonal means behave differently. In many regions they are decreasing or not increasing. The occurrence of very wet periods is strongly increasing during boreal winter in the extratropics and decreasing in the tropics. In summary, wet regions become wetter and dry regions become drier.

  15. Modeling daily discharge responses of a large karstic aquifer using soft computing methods: Artificial neural network and neuro-fuzzy

    NASA Astrophysics Data System (ADS)

    Kurtulus, Bedri; Razack, Moumtaz

    2010-02-01

    SummaryThis paper compares two methods for modeling karst aquifers, which are heterogeneous, highly non-linear, and hierarchical systems. There is a clear need to model these systems given the crucial role they play in water supply in many countries. In recent years, the main components of soft computing (fuzzy logic (FL), and Artificial Neural Networks, (ANNs)) have come to prevail in the modeling of complex non-linear systems in different scientific and technologic disciplines. In this study, Artificial Neural Networks and Adaptive Neuro-Fuzzy Interface System (ANFIS) methods were used for the prediction of daily discharge of karstic aquifers and their capability was compared. The approach was applied to 7 years of daily data of La Rochefoucauld karst system in south-western France. In order to predict the karst daily discharges, single-input (rainfall, piezometric level) vs. multiple-input (rainfall and piezometric level) series were used. In addition to these inputs, all models used measured or simulated discharges from the previous days with a specified delay. The models were designed in a Matlab™ environment. An automatic procedure was used to select the best calibrated models. Daily discharge predictions were then performed using the calibrated models. Comparing predicted and observed hydrographs indicates that both models (ANN and ANFIS) provide close predictions of the karst daily discharges. The summary statistics of both series (observed and predicted daily discharges) are comparable. The performance of both models is improved when the number of inputs is increased from one to two. The root mean square error between the observed and predicted series reaches a minimum for two-input models. However, the ANFIS model demonstrates a better performance than the ANN model to predict peak flow. The ANFIS approach demonstrates a better generalization capability and slightly higher performance than the ANN, especially for peak discharges.

  16. 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

  17. 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.

  18. Daily streamflow modelling and assessment based on the curve-number technique

    NASA Astrophysics Data System (ADS)

    Choi, Jin-Yong; Engel, Bernard A.; Chung, Ha Woo

    2002-11-01

    A cell-based long-term hydrological model (CELTHYM) that can be integrated with a geographical information system (GIS) was developed to predict continuous stream flow from small agricultural watersheds. The CELTHYM uses a cell-by-cell soil moisture balance approach. For surface runoff estimation, the curve number technique considering soil moisture on a daily basis was used, and release rate was used to estimate baseflow. Evapotranspiration was computed using the FAO modified Penman equation that considered land-use-based crop coefficients, soil moisture and the influence of topography on radiation. A rice paddy field water budget model was also adapted for the specific application of the model to East Asia. Model sensitivity analysis was conducted to obtain operational information about the model calibration parameters. The CELTHYM was calibrated and verified with measured runoff data from the WS#1 and WS#3 watersheds of the Seoul National University, Department of Agricultural Engineering, in Hwaseong County, Kyounggi Province, South Korea. The WS#1 watershed is comprised of about 35·4% rice paddy fields and 42·3% forest, whereas the WS#3 watershed is about 85·0% forest and 11·5% rice paddy fields. The CELTHYM was calibrated for the parameter release rate, K, and soil moisture storage coefficient, STC, and results were compared with the measured runoff data for 1986. The validation results for WS#1 considering all daily stream flow were poor with R2, E2 and RMSE having values of 0·40, -6·63 and 9·69 (mm), respectively, but validation results for days without rainfall were statistically significant (R2 = 0·66). Results for WS#3 showed good agreement with observed data for all days, and R2, E2 and RMSE were 0·92, 0·91 and 2·23 (mm), respectively, suggesting potential for CELTHYM application to other watersheds. The direct runoff and water balance components for watershed WS#1 with significant areas of paddy fields did not perform well, suggesting that

  19. Estimating the daily course of Konza Prairie latent Heat fluxes using a modified Tergra model

    NASA Astrophysics Data System (ADS)

    Hope, Allen S.

    1992-11-01

    The Tergra model simulates the daily course of water and energy flows through the soil-plantatmosphere system and was intended for use with remotely sensed data. In its original form, the model is not well suited to estimating spatial patterns of latent heat flux (λE) in the Konza Prairie since the determination of canopy resistance requires knowledge of vegetation height, and the defined relationship between leaf water potential and rc is specific to C3 plants. The canopy resistance component of Tergra was replaced by a routine that includes the calculation of minimum canopy resistance (rcm) from the normalized difference vegetation index (NDVI) and stress adjustment factors for leaf water potential and vapor pressure deficit to determine actual canopy resistance (rc). The relationship between rc and leaf water potential is defined for both C3 and C4 plants, and total λE is obtained from the sum of the proportional contributions from these two vegetation classes. The modified Tergra model (Tergra-2) was tested using input and flux data collected at four First ISLSCP Field Experiment (FIFE) sites during three periods characterized by different soil moisture conditions. Tergra-2 was found to be a good simulator of λE and in most cases gave substantially better results than those obtained using the original model. The greatest inaccuracy using Tergra-2 occurred under extremely dry soil moisture conditions, whereas absolute errors for both models tended to increase around solar noon. Leaf water potential was the dominant stress factor affecting modeled rc. It was concluded that vapor pressure deficit and leaf water potential should not be regarded as completely independent factors affecting rc. A brief comparison of modeled and observed canopy temperatures is presented and discussed.

  20. Models for obtaining daily global solar irradiation from air temperature data

    NASA Astrophysics Data System (ADS)

    Paulescu, M.; Fara, L.; Tulcan-Paulescu, E.

    2006-03-01

    The study presents a critical assessment of the possibility of global solar irradiation computation by using air temperature instead of sunshine duration with the classical Ångström equations. The reason for this approach comes from the fact that, although the air temperature is a worldwide measured meteorological parameter, this is rarely used in solar radiation estimation techniques. More than that, the literature is very silent concerning the testing of such models in Eastern Europe. Two new global solar irradiation models (to be called AEAT) related to solar irradiation under clear sky conditions and having the minimum and maximum daily air temperature as input parameters were tested and compared with others from the literature against data measured at five stations in Romania in the year 2000. The accuracy of AEAT is acceptable and comparable to that of the models which use sunshine duration or cloud amount as input parameters. Since temperature-based Ångström correlations are strongly sensitive to origin, the approach for AEAT as a tool for potential users is presented in detail. Additionally reported is a new method to increase the generality of AEAT concerning the extension of the geographical application area. Based on overall results it was concluded that air temperature successfully substitutes sunshine duration in the estimation of the available solar energy.

  1. 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.

  2. Analysis and modelling of spatio-temporal properties of daily rainfall over the Danube basin

    NASA Astrophysics Data System (ADS)

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

    Central and Eastern Europe are prone to severe floods due to heavy rainfall that cause societal and economic damages, ranging from agriculture to water resources, from the insurance/reinsurance sector to the energy industry. To improve the flood risk analysis, a better characterisation and modelling of the rainfall patterns over this area, which involves the Danube river watershed, is strategically important. In this study, we analyse the spatio-temporal properties of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe through different lagged and non-lagged indices of associations that quantify both the overall dependence and extreme dependence of pairwise observations. We also show that these measures are linked to each other and can be written in a unique and coherent notation within the copula framework. Moreover, the lagged version of these measures allows exploring some important spatio-temporal properties of the rainfall fields. The exploratory analysis is complemented by the preliminary results of a spatio-temporal rainfall simulation performed via a compound model based upon the Generalized Additive Models for Location, Scale and Shape (GAMLSS) and meta-elliptical multivariate distributions.

  3. Comparison of Daily GRACE Gravity Field and Numerical Water Storage Models for De-aliasing of Satellite Gravimetry Observations

    NASA Astrophysics Data System (ADS)

    Zenner, L.; Bergmann-Wolf, I.; Dobslaw, H.; Gruber, T.; Güntner, A.; Wattenbach, M.; Esselborn, S.; Dill, R.

    2014-11-01

    Reducing aliasing effects of insufficiently modelled high-frequent, non-tidal mass variations of the atmosphere, the oceans and the hydrosphere in gravity field models derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission is the topic of this study. The signal content of the daily GRACE gravity field model series (ITG-Kalman) is compared to high-frequency bottom pressure variability and terrestrially stored water variations obtained from recent numerical simulations from an ocean circulation model (OMCT) and two hydrological models (WaterGAP Global Hydrology Model, Land Surface Discharge Model). Our results show that daily estimates of ocean bottom pressure from the most recent OMCT simulations and the daily ITG-Kalman solutions are able to explain up to 40 % of extra-tropical sea-level variability in the Southern Ocean. In contrast to this, the daily ITG-Kalman series and simulated continental total water storage variability largely disagree at periods below 30 days. Therefore, as long as no adequate hydrological model will become available, the daily ITG-Kalman series can be regarded as a good initial proxy for high-frequency mass variations at a global scale. As a second result of this study, based on monthly solutions as well as daily observation residuals, it is shown that applying this GRACE-derived de-aliasing model supports the determination of the time-variable gravity field from GRACE data and the subsequent geophysical interpretation. This leads us to the recommendation that future satellite concepts for determining mass variations in the Earth system should be capable of observing higher frequeny signals with sufficient spatial resolution.

  4. Differential Associations and Daily Smoking of Adolescents: The Importance of Same-Sex Models

    ERIC Educational Resources Information Center

    Nofziger, Stacey; Lee, Hye-Ryeon

    2006-01-01

    This article examines whether the importance of parents, siblings, best friends, and romantic interests are sex-specific in predicting daily juvenile smoking. Juveniles who smoke daily are strongly influenced by prosmoking attitudes and behaviors of same-sex family members. However, peers remain the most important associations in predicting daily…

  5. 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…

  6. Crop yield monitoring based on a photosynthetic sterility model using NDVI and daily meteorological data

    NASA Astrophysics Data System (ADS)

    Kaneko, Daijiro

    2007-10-01

    This research is intended to develop a model to monitor rice yields using the photosynthetic yield index, which integrates solar radiation and air temperature effects on photosynthesis and grain-filling from heading to ripening. Monitoring crop production using remotely sensed and daily meteorological data can provide an important early warning of poor crop production to Asian countries, with their still-growing populations, and also to Japan, which produces insufficient grain for its population. The author improved a photosynthesis-and-sterility-based crop production CPI index to crop yield index CYI, which estimates rice yields, in place of the crop situation index CSI. The CSI gives a percentage of rice yields compared to normal annual production. The model calculates photosynthesis rates including biomass effects, lowtemperature sterility, and high-temperature injury by incorporating: solar radiation, effective air temperature, normalized difference vegetation index NDVI, and the effect of temperature on photosynthesis by grain plant leaves. The method is based on routine observation data, enabling automated monitoring of crop production at arbitrary regions without special observations. The method aims to quantity grain production at an early stage to raise the alarm in Asian countries, which are facing climate fluctuation through this century of global warming.

  7. 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.

    2016-02-01

    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.

  8. LAPSUS-D: testing a new daily sediment delivery model in a meso-scale Mediterranean catchment in Northern Israel

    NASA Astrophysics Data System (ADS)

    Keesstra, S.; Temme, A.; Wittenberg, L.; Greenbaum, N.

    2011-12-01

    LAPSUS-D is a new sediment delivery model that simulates sediment and water discharge at the temporal scale of one day and the spatial scale of a meso-scale catchment, using only generally available data, such as a DEM, a soil map, a land use map, daily discharge and precipitation data and a general idea of the soil depths in the catchment. The landscape evolution model LAPSUS (Schoorl, 2002) was adapted to model sediment yield on a daily basis instead of the original annual basis. LAPSUS-D uses the water balance per cell and for the entire catchment to calculate water and sediment transport and this feature enables calibration with measured daily discharge at the outlet. With this information the model can be calibrated for the water flow part which will give a good indication of the possibilities for sediment transport. First testing of the model in catchments with a temperate climate in SW Poland and SE Germany showed that the model is able to postdict the daily outflow well, when focusing on peak discharge characteristics. These hydrological features are the main determining factor for the generation of sediment outflow, and therefore most important to be able predict sediment delivery in a catchment well. In a Mediterranean catchment in Israel, Nahal Oren, the model was tested for this new climate setting. Moreover, the first testing of the models sediment module was conducted. This indicated that the model post-dicts the sediment yield within the right order of magnitude and has potential to function as a tool for catchment managers. Keywords: LAPSUS-D, daily sediment yield model, meso-scale catchment, Mediterranean climate, Nahal Oren, Israel

  9. Stochastic modelling of daily rainfall in Nigeria: intra-annual variation of model parameters

    NASA Astrophysics Data System (ADS)

    Jimoh, O. D.; Webster, P.

    1999-09-01

    A Markov model of order 1 may be used to describe the occurrence of wet and dry days in Nigeria. Such models feature two parameter sets; P01 to characterise the probability of a wet day following a dry day and P11 to characterise the probability of a wet day following a wet day. The model parameter sets, when estimated from historical records, are characterised by a distinctive seasonal behaviour. However, the comparison of this seasonal behaviour between rainfall stations is hampered by the noise reflecting the high variability of parameters on successive days. The first part of this article is concerned with methods for smoothing these inherently noisy parameter sets. Smoothing has been approached using Fourier series, averaging techniques, or a combination thereof. It has been found that different methods generally perform well with respect to estimation of the average number of wet events and the frequency duration curves of wet and dry events. Parameterisation of the P01 parameter set is more successful than the P11 in view of the relatively small number of wet events lasting two or more days. The second part of the article is concerned with describing the regional variation in smoothed parameter sets. There is a systematic variation in the P01 parameter set as one moves northwards. In contrast, there is limited regional variation in the P11 set. Although this regional variation in P01 appears to be related to the gradual movement of the Inter Tropical Convergence Zone, the contrasting behaviour of the two parameter sets is difficult to explain on physical grounds.

  10. 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.

  11. 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.

  12. Modified Daily Undulating Periodization Model Produces Greater Performance Than a Traditional Configuration in Powerlifters.

    PubMed

    Zourdos, Michael C; Jo, Edward; Khamoui, Andy V; Lee, Sang-Rok; Park, Bong-Sup; Ormsbee, Michael J; Panton, Lynn B; Contreras, Robert J; Kim, Jeong-Su

    2016-03-01

    The primary aim of this study was to compare 2 daily undulating periodization (DUP) models on one-repetition maximum (1RM) strength in the squat, bench press, deadlift, total volume (TV) lifted, and temporal hormone response. Eighteen male, college-aged (21.1 ± 1.9 years) powerlifters participated in this study and were assigned to one of 2 groups: (a) traditional DUP training with a weekly training order: hypertrophy-specific, strength-specific, and power-specific training (HSP, n = 9) or (b) modified DUP training with a weekly training order: hypertrophy-specific, power-specific, and strength-specific training (HPS, n = 9). Both groups trained 3 nonconsecutive days per week for 6 weeks and performed the squat, bench press, and deadlift exercises. During hypertrophy and power sessions, subjects performed a fixed number of sets and repetitions but performed repetitions until failure at a given percentage during strength sessions to compare TV. Testosterone and cortisol were measured at pretesting and posttesting and before each strength-specific day. Hypertrophy, power, and strength produced greater TV in squat and bench press (p ≤ 0.05) than HSP, but not for deadlift (p > 0.05). For squat and deadlift, there was no difference between groups for 1RM (p > 0.05); however, HPS exhibited greater increases in 1RM bench press than HSP (p ≤ 0.05). Effect sizes (ES) showed meaningful differences (ES > 0.50) in favor of HPS for squat and bench press 1RM. Testosterone decreased (p ≤ 0.05) at weeks 5 and 6 and cortisol decline at weeks 3 and 4. However, neither hormone was different at posttesting compared with pretesting (p > 0.05). Our findings suggest that an HPS configuration of DUP has enhanced performance benefits compared with HSP. PMID:26332783

  13. Evaluation of satellite-based, modeled-derived daily solar radiation data for the continental U.S.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 to...

  14. Evaluation of Once-Daily Vancomycin against Methicillin-Resistant Staphylococcus aureus in a Hollow-Fiber Infection Model

    PubMed Central

    Bulitta, Jürgen B.; Lodise, Thomas P.; D'Hondt, Rebecca E.; Kulawy, Robert; Louie, Arnold; Drusano, George L.

    2012-01-01

    For methicillin-resistant Staphylococcus aureus (MRSA) infections, data suggest that the clinical response is significantly better if the total vancomycin area under the concentration-time curve (AUC)/MIC ratio is ≥400. While the AUC/MIC ratio is the accepted pharmacokinetic/pharmacodynamic (PK/PD) index for vancomycin, this target has been achieved using multiple daily doses. We are unaware of a systematically designed dose fractionation study to compare the bactericidal activity of once-daily administration to that of traditional twice-daily administration. A dose fractionation study was performed with vancomycin in an in vitro hollow-fiber infection model against an MRSA USA300 strain (MIC of 0.75 μg/ml) using an inoculum of ∼106 CFU/ml. The three vancomycin regimens evaluated for 168 h were 2 g every 24 h (q24h) as a 1-h infusion, 1 g q12h as a 1-h infusion, and 2 g q24h as a continuous infusion. Free steady-state concentrations (assuming 45% binding) for a total daily AUC/MIC ratio of ≥400 were simulated for all regimens. A validated liquid chromatography-tandem mass spectrometry method was used to determine vancomycin concentrations. Although once-daily and twice-daily dosage regimens exhibited total trough concentrations of <15 μg/ml, all regimens achieved similar bactericidal activities between 24 and 168 h and suppressed the amplification of nonsusceptible subpopulations. No colonies were found on agar plates with 3× MIC for any of the treatment arms. Overall, the results suggest that once-daily vancomycin administration is feasible from a PK/PD perspective and merits further inquiry in the clinical arena. PMID:22083484

  15. 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

  16. 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. PMID:20352542

  17. 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.

  18. 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. ?? 2007 Elsevier B.V. All rights reserved.

  19. 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 ...

  20. 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...

  1. 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...

  2. A model-based approach for the evaluation of once daily dosing of lamivudine in HIV-infected children

    PubMed Central

    Piana, Chiara; Zhao, Wei; Adkison, Kimberly; Burger, David; Jacqz-Aigrain, Evelyne; Danhof, Meindert; Della Pasqua, Oscar

    2014-01-01

    Aim Little attention has been paid to the effects of compliance and prescription practice on treatment outcome in HIV-infected children. In this context, an evaluation of the role of covariates on pharmacokinetics is required to establish the impact of differences in dosing regimens. Here we investigate whether a once daily dosing regimen of lamivudine provides comparable exposure to the currently approved paediatric regimen. Methods A hypothetical group of 180 patients between 3 months and 12 years old was used to evaluate the impact of body weight on systemic exposure to lamivudine. Simulation scenarios were evaluated using AUC and Cmax as parameters of interest. The analysis was performed using a population pharmacokinetic model previously implemented in nonmem v.6.2. Results The simulations show that once daily dosing of lamivudine yields comparable exposure to historical values observed in children and adults, both for liquid and solid dosage forms. Simulated steady-state AUC(0–24 h) and Cmax values after once daily doses ranged respectively from 9.95 mg l−1 h and 1.9 mg l−1 for children lighter than 14 kg to 13.75 mg l−1 h and 3.0 mg l−1 for children heavier than 30 kg. These values are comparable or higher than historical values observed after once daily dosing in children and adults. Conclusions Our findings illustrate how dosing regimens can be evaluated taking into account the effects of developmental growth on drug disposition. Most importantly, they suggest that the reduction in dosing frequency to once daily leads to comparable lamivudine exposure, as observed after administration of a twice daily dosing regimen. PMID:24118047

  3. 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

  4. Daily and 3-hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide

    NASA Astrophysics Data System (ADS)

    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.

    2011-12-01

    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

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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. PMID:25207653

  11. 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. PMID:27497764

  12. 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...

  13. 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

  14. A count model to study the correlates of 60 min of daily physical activity in Portuguese children.

    PubMed

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

    2015-03-01

    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

  15. Optimal vitamin D3 daily intake of 2000IU inferred from modeled solar exposure of ancestral humans in Northern Tanzania.

    PubMed

    Krzyścin, Janusz W; Guzikowski, Jakub; Rajewska-Więch, Bonawentura

    2016-06-01

    Recently, high serum 25-hydroxyvitamin D concentration (~110nmol/L) was found in the Hadza tribe still keeping ancient hunter-gather life style. This level could serve as optimal vitamin D level that was built during millennia of human evolution. The personal vitamin D3 effective solar exposures of the Hadza adults are estimated using radiative model simulations with input from the satellite observations over lake Eyasi (3.7°S, 35.0°E). The calculations are carried out assuming the Hadza typical clothing habits and specific scenarios of the out-door activity comprising early morning and late afternoon working time in sun and prolonged midday siesta in the shade. The modeled doses received by the Hadza are converted to the vitamin D3 effective daily doses pertaining to the lighter skinned persons. We propose a novel formula to get adequate vitamin D level - exposure of 1/3 MED around local noon to 1/3 part of the whole body during warm sub-period of the year in the low- and mid-latitude regions. Such daily solar exposure is equivalent to ~2000IU of vitamin D3 taken orally. For many contemporary humans with limited out-door activity habit achieving such daily norm requires vitamin D3 supplementation of 2000IU throughout the whole year. PMID:27043260

  16. 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.

    2015-10-01

    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

  17. 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 ...

  18. 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. PMID:26717080

  19. 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...

  20. The Daily Erosion Project - lessons learned by expanding a statewide erosion and runoff model beyond state boundaries

    NASA Astrophysics Data System (ADS)

    Gelder, Brian; James, David; Herzmann, Daryl; Scott, Victoria; Cruse, Richard; Laflen, John; Flanagan, Dennis; Frankenberger, Jim; Opsomer, Jean

    2015-04-01

    The Daily Erosion Project (DEP) model is an extension of the Iowa Daily Erosion Project (IDEP) 2.0 model to additional states in the US, initially Kansas and Minnesota. DEP provides comprehensive and dynamic estimates of sediment delivery, soil erosion, and hill slope runoff for agricultural land areas across the area of interest. The integration of high spatial and temporal resolution precipitation and climate data, high resolution LiDAR topography, spatially variable soil properties from current SSURGO information, remotely sensed crop rotation and residue management data, provides increased spatial resolution of runoff and erosion estimates over IDEP 1.0, the previous version derived from land management survey data. The reasoning used to define a representative measurement unit, subcatchments of Hydrologic Unit Code (HUC) 12 watersheds (each approximately 1000 hectares) throughout the modeled area along with methods used to incorporate disparate LiDAR datasets as well as varying crop rotations and management practices and their effects on model accuracy will be discussed.

  1. El Niño-Southern Oscillation influence on winter maximum daily precipitation in California in a spatial model

    NASA Astrophysics Data System (ADS)

    Shang, Hongwei; Yan, Jun; Zhang, Xuebin

    2011-11-01

    Recent studies have found that the El Niño-Southern Oscillation (ENSO) has statistically significant influences on extreme precipitation. A limitation of most existing work is that a separate generalized extreme value (GEV) distribution is fitted for each individual site. Such models cannot address important questions that involve events jointly defined across multiple sites; for instance, what is the probability that the 50 year return levels of three sites in the vicinity of a city occur in the same season? With the latest statistical methodology for spatial extremes, we fit max-stable process models to winter maximum daily precipitation of 192 sites in California over 55 years. A composite likelihood approach is used since the full likelihood is unavailable either analytically or numerically. In addition to latitude, longitude, and elevation, the Southern Oscillation Index (SOI) is incorporated into the parameters of the marginal GEV models. We find that, in a spatial context, the ENSO has a significant influence on the extreme precipitation in California by shifting the location parameter of the GEV distributions, with higher values of the SOI corresponding to lower maximum winter daily precipitation. The joint spatial model is used to assess risks concerning joint extremal events at network of sites with spatial dependence properly accounted for. The probability of extremal events occurring at multiple sites in the same season is found to be much higher than what would be expected under the independence assumption.

  2. VT-1161 dosed once daily or once weekly exhibits potent efficacy in treatment of dermatophytosis in a guinea pig model.

    PubMed

    Garvey, E P; Hoekstra, W J; Moore, W R; Schotzinger, R J; Long, L; Ghannoum, M A

    2015-04-01

    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

  3. 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

  4. Daily uranium excretion in German peacekeeping personnel serving on the Balkans compared to ICRP model prediction.

    PubMed

    Oeh, U; Li, W B; Höllriegl, V; Giussani, A; Schramel, P; Roth, P; Paretzke, H G

    2007-01-01

    An investigation was performed to assess a possible health risk of depleted uranium (DU) for residents and German peacekeeping personnel serving on the Balkans. In order to evaluate a possible DU intake, the urinary uranium excretions of volunteers were collected and analysed using inductively coupled plasma mass spectrometry (ICP-MS). In total, more than 1300 urine samples from soldiers, civil servants and unexposed controls of different genders and ages were analysed to determine uranium excretion parameters. All participating volunteers, aged 3-92 y, were grouped according to their gender and age for evaluation. The results of the investigation revealed no significant difference between the unexposed controls and the peacekeeping personnel. In addition, the geometric means of the daily urinary excretion in peacekeeping personnel, ranging from 3 to 23 ng d(-1) for different age groups, fall toward the lower end of renal uranium excretion values published for unexposed populations in literature. The measured data were compared with the International Commission on Radiological Protection prediction for the intake of natural uranium by unexposed members of the public. The two data sets are in good agreement, indicating that no relevant intake of additional uranium, either natural or DU, has appeared for German peacekeeping personnel serving on the Balkans. PMID:17567762

  5. 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

  6. Age-related Changes in Respiratory Function and Daily Living. A Tentative Model Including Psychosocial Variables, Respiratory Diseases and Cognition.

    PubMed

    Facal, David; González-Barcala, Francisco-Javier

    2016-01-01

    Changes in respiratory function are common in older populations and affect quality of life, social relationships, cognitive function and functional capacity. This paper reviews evidence reported in medical and psychological journals between 2000 and 2014 concerning the impact of changes in respiratory function on daily living in older adults. A tentative model establishes relationships involving respiratory function, cognitive function and functional capacities. The conclusion stresses the need for both longitudinal studies, to establish causal pathways between respiratory function and psychosocial aspects in aging, and intervention studies. PMID:26593253

  7. Estimating the daily course of Konza Prairie latent heat fluxes using a modified Tergra model

    NASA Technical Reports Server (NTRS)

    Hope, Allen S.

    1992-01-01

    Experimental tests of the Tergra-2 model are based on data collected under moderately wet to wet and very dry soil moisture conditions. Further testing of the model under intermediate soil moisture conditions is required and additional testing under very dry conditions may lead to modifications that make the model more suitable to water-stressed conditions. Combining the Tergra model with a soil evaporation routine should enhance the accuracy of the model and allow it to be employed in situations where vapor fluxes are not almost solely attributable to transpiration.

  8. Adapting remotely sensed snow data for daily flow modeling on the Upper Humber River, Newfoundland and Labrador

    NASA Astrophysics Data System (ADS)

    Tom, Melissa

    This thesis investigated the use of remotely sensed snow information to help improve flood forecasting in western Newfoundland's Humber River Basin. Flood forecasting on the Humber River is important because of the large population settlements within the Humber Valley. In this research, two types of remotely sensed snow data were considered for analysis: (1) snow cover (or snow extent) and (2) snow water equivalent (SWE). The majority of this thesis focuses on the remotely sensed snow cover data. Moderate Resolution Imaging Spectroradiometer (MODIS) Terra snow cover images were acquired over the Humber Valley watershed throughout the snowmelt period, from March to June, for the years 2000 to 2009. MODIS is an optical sensor on NASA's (National Aeronautics and Space Administration) Earth Observing System (EOS) Terra and Aqua satellites. Its daily temporal data are advantageous and the data are free and easily accessible. Daily snow cover data were extracted from the National Snow and Ice Data Center (NSIDC) daily snow product, specifically MOD10A1: a product derived from MODIS data, using a custom EASI script run in PCI Geomatica. PCI Geomatica is a robust remote sensing and image processing software. One major obstacle, regarding the acquisition of MODIS imagery over the Humber Valley watershed, is the presence of over 50% cloud cover for 80% of the days on average from March to June every year. This was a concern for data collection: affecting the sample size of acquired data and the accuracy of the snow cover data. When cloud cover is high there is a greater chance that it may be misclassified as snow and/or snow is misclassified as cloud cover. For this reason, a cloud-cover threshold was determined. The Rango-Martinec snowmelt runoff model, a widely used degree-day model which incorporates snow cover data as a direct input, was evaluated. It was found that the next day's flow is highly dependent on the previous day's flow and less dependent on the

  9. 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. PMID:26853919

  10. 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.

  11. Artificial neural network models for prediction of daily fine particulate matter concentrations in Algiers.

    PubMed

    Chellali, M R; Abderrahim, H; Hamou, A; Nebatti, A; Janovec, J

    2016-07-01

    Neural network (NN) models were evaluated for the prediction of suspended particulates with aerodynamic diameter less than 10-μm (PM10) concentrations. The model evaluation work considered the sequential hourly concentration time series of PM10, which were measured at El Hamma station in Algiers. Artificial neural network models were developed using a combination of meteorological and time-scale as input variables. The results were rather satisfactory, with values of the coefficient of correlation (R (2)) for independent test sets ranging between 0.60 and 0.85 and values of the index of agreement (IA) between 0.87 and 0.96. In addition, the root mean square error (RMSE), the mean absolute error (MAE), the normalized mean squared error (NMSE), the absolute relative percentage error (ARPE), the fractional bias (FB), and the fractional variance (FS) were calculated to assess the performance of the model. It was seen that the overall performance of model 3 was better than models 1 and 2. PMID:27040548

  12. 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

  13. Daily Stress and Alcohol Consumption: Modeling Between-Person and Within-Person Ethnic Variation in Coping Behavior*

    PubMed Central

    Aldridge-Gerry, Arianna A.; Roesch, Scott C.; Villodas, Feion; McCabe, Cameron; Leung, Queenie K.; Da Costa, Morgan

    2011-01-01

    Objective: Using a daily diary approach, the current study evaluated the relationship between coping and alcohol consumption using a large, multiethnic sample. The primary goals of this study were to (a) identify coping strategies that are either protective or risk factors for alcohol consumption and (b) model between-ethnic and within-ethnic group variation for these relations. Method: College students (N = 365, 69.0% female) were recruited via flyers, course/club presentations, and university seminars. Participants completed Internet-based daily diaries over the course of 5 days and reported specifically on a target stressful event, how they coped with the stressful event, and the amount of alcohol consumed on a daily level. Results: Use of more avoidance-oriented coping strategies (minimization of stressor, emotional rumination) and social support were significantly associated with more alcohol consumption. Ethnicity, however, did moderate some coping—alcohol associations. Use of religious coping was associated with less alcohol consumption and minimization of the stressor was associated with more alcohol consumption in African Americans; use of social support was associated with more alcohol consumption in Asian Americans; and use of problem-focused coping was associated with less alcohol consumption in Whites. Conclusions: Three maladaptive or risky coping strategies with respect to alcohol consumption were identified using an ecologically valid methodology. However, ethnic-specific variation of these risky (and protective) coping factors was identified. The findings highlight the importance of considering both between-ethnic and within-ethnic group variation with respect to the stress/coping and alcohol consumption. PMID:21138719

  14. 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.

  15. Combination of spaceborne sensor(s) and 3-D aerosol models to assess global daily near-surface air quality

    NASA Astrophysics Data System (ADS)

    Kacenelenbogen, M.; Redemann, J.; Russell, P. B.

    2009-12-01

    Aerosol Particulate Matter (PM), measured by ground-based monitoring stations, is used as a standard by the EPA (Environmental Protection Agency) to evaluate daily air quality. PM monitoring is particularly important for human health protection because the exposure to suspended particles can contribute, among others, to lung and respiratory diseases and even premature death. However, most of the PM monitoring stations are located close to cities, leaving large areas without any operational data. Satellite remote sensing is well suited for a global coverage of the aerosol load and can provide an independent and supplemental data source to in situ monitoring. Nevertheless, PM at the ground cannot easily be determined from satellite AOD (Aerosol Optical Depth) without additional information on the optical/microphysical properties and vertical distribution of the aerosols. The objective of this study is to explore the efficacy and accuracy of combining a 3-D aerosol transport model and satellite remote sensing as a cost-effective approach for estimating ground-level PM on a global and daily basis. The estimation of the near-surface PM will use the vertical distribution (and, if possible, the physicochemical properties) of the aerosols inferred from a transport model and the measured total load of particles in the atmospheric column retrieved by satellite sensor(s). The first step is to select a chemical transport model (CTM) that provides “good” simulated aerosol vertical profiles. A few global (e.g., WRF-Chem-GOCART) or regional (e.g., MM5-CMAQ, PM-CAMx) CTM will be compared during selected airborne campaigns like ARCTAS-CARB (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites- California Air Resources Board). The next step will be to devise an algorithm that combines the satellite and model data to infer PM mass estimates at the ground, after evaluating different spaceborne instruments and possible multi-sensor combinations.

  16. 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...

  17. 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...

  18. 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.

    2015-01-01

    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.

  19. A spatial agent-based model for the simulation of adults' daily walking within a city.

    PubMed

    Yang, Yong; Diez Roux, Ana V; Auchincloss, Amy H; Rodriguez, Daniel A; Brown, Daniel G

    2011-03-01

    Environmental effects on walking behavior have received attention in recent years because of the potential for policy interventions to increase population levels of walking. Most epidemiologic studies describe associations of walking behavior with environmental features. These analyses ignore the dynamic processes that shape walking behaviors. A spatial agent-based model (ABM) was developed to simulate people's walking behaviors within a city. Each individual was assigned properties such as age, SES, walking ability, attitude toward walking and a home location. Individuals perform different activities on a regular basis such as traveling for work, for basic needs, and for leisure. Whether an individual walks and the amount she or he walks is a function of distance to different activities and her/his walking ability and attitude toward walking. An individual's attitude toward walking evolves over time as a function of past experiences, walking of others along the walking route, limits on distances walked per day, and attitudes toward walking of the other individuals within her/his social network. The model was calibrated and used to examine the contributions of land use and safety to socioeconomic differences in walking. With further refinement and validation, ABMs may help to better understand the determinants of walking and identify the most promising interventions to increase walking. PMID:21335269

  20. A Spatial Agent-Based Model for the Simulation of Adults’ Daily Walking Within a City

    PubMed Central

    Yang, Yong; Roux, Ana V. Diez; Auchincloss, Amy H.; Rodriguez, Daniel A.; Brown, Daniel G.

    2012-01-01

    Environmental effects on walking behavior have received attention in recent years because of the potential for policy interventions to increase population levels of walking. Most epidemiologic studies describe associations of walking behavior with environmental features. These analyses ignore the dynamic processes that shape walking behaviors. A spatial agent-based model (ABM) was developed to simulate peoples’ walking behaviors within a city. Each individual was assigned properties such as age, SES, walking ability, attitude toward walking and a home location. Individuals perform different activities on a regular basis such as traveling for work, for shopping, and for recreation. Whether an individual walks and the amount she or he walks is a function distance to different activities and her or his walking ability and attitude toward walking. An individual’s attitude toward walking evolves over time as a function of past experiences, walking of others along the walking route, limits on distances walked per day, and attitudes toward walking of the other individuals within her/his social network. The model was calibrated and used to examine the contributions of land use and safety to socioeconomic differences in walking. With further refinement and validation, ABMs may help to better understand the determinants of walking and identify the most promising interventions to increase walking. PMID:21335269

  1. Evaluating daily and extreme seasonal precipitations over continental Africa from a Regional Climate Model Simulation

    NASA Astrophysics Data System (ADS)

    Bamba Sylla, Mouhamadou; Mariotti, Laura; Coppola, Erika; Giorgi, Filippo

    2010-05-01

    Spatial and temporal variability of rainfall over Africa offers considerable challenges on climate change over the region. This is because of the complexity of regional climates in Africa and their associated geographic features. Adding to that complexity are deserts, vegetation variations, numerous mountain chains that can alter regional climate and weather patterns, the influence of the land-sea contrast due to the presence of several large lakes and the surrounding Indian and Atlantic Oceans. This leads to strong fluctuations of rainfall that may cause drought and flood in the region. Therefore, being able to simulate the spatial distribution of mean precipitation is quite important but also capturing their occurrences and intensities is critical for Africa whose economy relies on rain-fed agriculture. The International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM3), driven by the newly produced ERA-Interim reanalysis, is used to investigate this issue. Several indices, such as the number of wet days and their intensity, maximum dry and wet spells length and the frequency of heavy precipitation days, are used to characterize the spatial variability of seasonal extreme rainfall over continental Africa. Model results are compared to both TRMM and FEWS rainfall data. They indicate that although the model captures the location of longest and shortest wet and dry spells, it tends to extend slightly the wet spell length around mountainous regions and along the ITCZ and the dry spell length over northern and southern Africa during austral and boreal summer respectively. This is mainly visible when compared to FEWS. Extension of the wet spell length may be partly related to the overestimation of the number of wet days. As a result, the intensity due to the wet days only is slightly overpredicted in these regions. This is, in turn, linked to the tendency of the RegCM3 to produce more intense and convective rainfall events in the ITCZ and the ZAB as

  2. [Inversion Model and Daily Variation of Total Phosphorus Concentrations in Taihu Lake Based on GOCI Data].

    PubMed

    Du, Cheng-gong; Li, Yun-mei; Wang, Qiao; Zhu, Li; Lü, Heng

    2016-03-15

    The TP concentration is an important index of water quality and an important influencing factor of eutrophication and algae blooms. Remote sensing technology has advantages of wide scope and high time limited efficacy. Monitoring the concentration of TP by satellite remote sensing is important for the study of water quality and eutrophication. In situ datasets collected during the three times of experiments in Taihu Lake between 2013 and 2014 were used to develop the TP inversion model based on GOCI data. The GOCI data in spring, summer, autumn and winter in 2014 were selected to analyze the time and space changes of TP concentration in Taihu Lake. The results showed that the TP algorithm was built up based on the variables, which was to use the eight band combination of GOCI data as variable, and build model using Multi factor linear regression method. The algorithm achieved more accurate TP estimation with R² = 0.898, MAPE = 14.296%, RMSE = 0.026 mg · L⁻¹. Meantime, a analysis on the precision of the model by using the measured sample points and the synchronous satellite images with MAPE = 33.642%, 22.551%, RMSE = 0.076 mg · L⁻¹, 0.028 mg · L⁻¹ on August 5, 2014 and October 24, 2014. Through the analysis of the 30 images on the four days of the four seasons, it showed that the absolute concentration of total phosphorus was different in different seasons. But temporal and spatial distribution of total phosphorus concentration was similar in the morning and afternoon. In spatial distribution, the TP concentration in Meiliang Bay, Zhushan Bay, Gonghu Bay, Xiaomei Port and Changdou Port in the southwest coast was at a continuously high position. The TP concentration change in different regions was influenced by wind direction, wind speed and other factors. The TP concentration highest in the morning, and then gradually decreased, this phenomenon reflected that the TP concentration was affected by temperature and light. PMID:27337876

  3. 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

  4. 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.

    2016-02-01

    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.

  5. The perfectionism model of binge eating: testing unique contributions, mediating mechanisms, and cross-cultural similarities using a daily diary methodology.

    PubMed

    Sherry, Simon B; Sabourin, Brigitte C; Hall, Peter A; Hewitt, Paul L; Flett, Gordon L; Gralnick, Tara M

    2014-12-01

    The perfectionism model of binge eating (PMOBE) is an integrative model explaining the link between perfectionism and binge eating. This model proposes socially prescribed perfectionism confers risk for binge eating by generating exposure to 4 putative binge triggers: interpersonal discrepancies, low interpersonal esteem, depressive affect, and dietary restraint. The present study addresses important gaps in knowledge by testing if these 4 binge triggers uniquely predict changes in binge eating on a daily basis and if daily variations in each binge trigger mediate the link between socially prescribed perfectionism and daily binge eating. Analyses also tested if proposed mediational models generalized across Asian and European Canadians. The PMOBE was tested in 566 undergraduate women using a 7-day daily diary methodology. Depressive affect predicted binge eating, whereas anxious affect did not. Each binge trigger uniquely contributed to binge eating on a daily basis. All binge triggers except for dietary restraint mediated the relationship between socially prescribed perfectionism and change in daily binge eating. Results suggested cross-cultural similarities, with the PMOBE applying to both Asian and European Canadian women. The present study advances understanding of the personality traits and the contextual conditions accompanying binge eating and provides an important step toward improving treatments for people suffering from eating binges and associated negative consequences. PMID:25243835

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

    USGS Publications Warehouse

    Letcher, Benjamin; Hocking, Daniel; O'Neill, K.; 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.

  7. 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.

  8. 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. PMID:26966662

  9. 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

  10. Testing the perfectionism model of binge eating in mother-daughter dyads: a mixed longitudinal and daily diary study.

    PubMed

    Mushquash, Aislin R; Sherry, Simon B

    2013-04-01

    The perfectionism model of binge eating is an integrative model explaining why perfectionism is tied to binge eating. This study extended and tested this emerging model by proposing daughters' socially prescribed perfectionism (i.e., perceiving one's mother is harshly demanding perfection of oneself) and mothers' psychological control (i.e., a negative parenting style involving control and demandingness) contribute indirectly to daughters' binge eating by generating situations or experiences that trigger binge eating. These binge triggers include discrepancies (i.e., viewing oneself as falling short of one's mother's expectations), depressive affect (i.e., feeling miserable and sad), and dietary restraint (i.e., behaviors aimed at reduced caloric intake). This model was tested in 218 mother-daughter dyads studied using a mixed longitudinal and daily diary design. Daughters were undergraduate students. Results largely supported hypotheses, with bootstrapped tests of mediation suggesting daughters' socially prescribed perfectionism and mothers' psychological control contribute to binge eating through binge triggers. For undergraduate women who believe their mothers rigidly require them to be perfect and whose mothers are demanding and controlling, binge eating may provide a means of coping with or escaping from an unhealthy, unsatisfying mother-daughter relationship. PMID:23557815

  11. 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.

  12. 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.

  13. Sources of solar radiation estimates and their effect on daily potential evaporation for use in streamflow modeling

    NASA Astrophysics Data System (ADS)

    Lindsey, Scott D.; Farnsworth, Richard K.

    1997-12-01

    The accurate estimation of potential evaporation (PE), to in turn calculate evapotranspiration, is an important step in many hydrologic models. The National Weather Service (NWS) has used PE to obtain daily estimates of mean evapotranspiration in continuous rainfall-runoff models for river forecasting. The daily PE estimates are derived mainly from meteorological data gathered on a regular basis throughout the country. Solar radiation is one of the required input variables. Because of its widespread availability, sky cover is now used almost exclusively by NWS to estimate solar radiation. Over a period of time, a bias has developed between the long-term mean PE (computed using a combination of historical observed pan evaporation data and meteorological data) and PE estimated operationally using real-time meteorological data. This difference is a result of the use of sky cover based solar radiation estimates. These biased solar radiation estimates translate into long-term means of PE which are significantly lower than values using corresponding direct measurements of solar radiation or estimates of solar radiation using percent sunshine. A standard for PE has been established and verified to which long-term means can be compared. PE estimates derived from sky cover can be corrected to the standard using a ratio of long-term means. Many meteorological variables which have been measured or observed manually in the past are being converted to automatic observations. With the advent of automated sensors, which do not duplicate the manual sky cover observations, another source of solar radiation is necessary to model PE for use in river forecasting. Satellite estimates of solar radiation are compared with other means of measuring and estimating solar radiation. Available on a nationwide basis, satellite estimates produce values of solar radiation comparable to those obtained by direct measurement. Based on availability and accuracy, satellite estimates of solar radiation

  14. 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…

  15. 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.…

  16. 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. PMID:19636779

  17. 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

  18. 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.

  19. Daily data - obtain modeled daily data

    Atmospheric Science Data Center

    2016-02-19

    ... list Select one parameter of those just chosen from the "Plot one parameter" list. Select "Submit". The resulting page displays a plot of the selected parameter with an option to view the parameters chosen for ...

  20. 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

  1. Effect of lower-limb joint models on subject-specific musculoskeletal models and simulations of daily motor activities.

    PubMed

    Valente, Giordano; Pitto, Lorenzo; Stagni, Rita; Taddei, Fulvia

    2015-12-16

    Understanding the validity of using musculoskeletal models is critical, making important to assess how model parameters affect predictions. In particular, assumptions on joint models can affect predictions from simulations of movement, and the identification of image-based joints is unavoidably affected by uncertainty that can decrease the benefits of increasing model complexity. We evaluated the effect of different lower-limb joint models on muscle and joint contact forces during four motor tasks, and assessed the sensitivity to the uncertainties in the identification of anatomical four-bar-linkage joints. Three MRI-based musculoskeletal models having different knee and ankle joint models were created and used for the purpose. Model predictions were compared against a baseline model including simpler and widely-adopted joints. In addition, a probabilistic analysis was performed by perturbing four-bar-linkage joint parameters according to their uncertainty. The differences between models depended on the motor task analyzed, and there could be marked differences at peak loading (up to 2.40 BW at the knee and 1.54 BW at the ankle), although they were rather small over the motor task cycles (up to 0.59 BW at the knee and 0.31 BW at the ankle). The model including more degrees of freedom showed more discrepancies in predicted muscle activations compared to measured muscle activity. Further, including image-based four-bar-linkages was robust to simulate walking, chair rise and stair ascent, but not stair descent (peak standard deviation of 2.66 BW), suggesting that joint model complexity should be set according to the imaging dataset available and the intended application, performing sensitivity analyses. PMID:26506255

  2. Stochastic Downscaling of Daily Rainfall: Analysis of future hydroclimatic changes and their impact on the Pontinia plain using Nonhomogeneous Hidden Markov Model and Dynamic Hierarchical Bayesian Network Model.

    NASA Astrophysics Data System (ADS)

    Cioffi, Francesco; Devineni, Naresh; Monti, Alessandro; Lall, Upmanu

    2013-04-01

    The Nonhomogeneous Hidden Markov Model is an established technique that usually provides excellent results for the downscaling of multi-site precipitation. However, the selection of the number of states is subjective and results in a model that can be over parameterized and overfit leading to por performance in applications. A dynamic hierarchical Bayesian network model (DHBN) that is continuous and is not based on discretization into states is tested here and compared against NHMM for the downscaling of daily precipitation for Pontinia Plain. This región is a relevant example of coastal area particularly vulnerable to hydrological changes. The winter (October-March) wet season is considered. Weather states and atmospheric variables from CMIP5 GCM are used as exogenous predictors. The daily rainfall occurrence and amount at 32 stations over the region for the winters of 1916-2004 is used as the primary data. Rainfall variability is described in terms of occurrence of 'weather state' as classified by a Hidden Markov Model, and associated to variables representing the main characteristics of large scale atmospheric circulation as obtained by reanalysis data. A nonhomogeneous hidden Markov model (NHHM) and a DHBN model are used to make future projections of the downscaled precipitation as by using the GCM's simulations under different global warming scenarios.The spatial interaction between the sites is modeled through the underlying covariance function and the uncertainty in the model parameters is explicitly represented in their posterior distribution. Preliminary results show that the seasonal statistics are adequately captures for the 20th century runs. The structural differences between the two models are discussed.

  3. 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.

  4. Parameterizations of daily temperature standard deviation for modeling ice sheet mass balances using a temperature-index method under paleoclimate conditions

    NASA Astrophysics Data System (ADS)

    Erokhina, Olga; Rogozhina, Irina

    2016-04-01

    A number of recent studies have suggested time-dependent parameterizations of daily temperature standard deviation for modelling surface mass balances of ice sheets and glaciers using a temperature-index method. These have been inferred from in-situ measurements and climate reanalysis data, which are only available on yearly to decadal time scales. To date, the existing literature has not explored their applicability to climate conditions that are different from those of today. This study presents an ensemble of simulations of the Greenland Ice Sheet's history since the Last Glacial Maximum to assess the performance of existing parameterizations of daily temperature standard deviation on millennial time scales. To limit the influence of the uncertainties arising from poorly constrained external and internal factors we adopt climate strategies of different complexities and a sensitivity analysis of ice sheet model parameters. Our study reveals that previously proposed parameterizations of daily temperature standard deviation have a limited performance during the deglaciation stage, failing to simulate the retreat of ice masses as suggested by geological reconstructions. In contrast multiple studies that use constant values of daily temperature standard deviation within the range of 4 to 5°C receive support from our analysis, implying that either the ice sheet model used is missing the fundamental physics necessary to capture complex processes associated with rapid deglaciation or the values of daily temperature standard deviation suggested by parameterizations based on present-day observations are too low to ensure the consistent Wisconsin-to-Holocene ice sheet retreat.

  5. Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium

    NASA Astrophysics Data System (ADS)

    Ly, S.; Charles, C.; Degré, A.

    2011-07-01

    Spatial interpolation of precipitation data is of great importance for hydrological modelling. Geostatistical methods (kriging) are widely applied in spatial interpolation from point measurement to continuous surfaces. The first step in kriging computation is the semi-variogram modelling which usually used only one variogram model for all-moment data. The objective of this paper was to develop different algorithms of spatial interpolation for daily rainfall on 1 km2 regular grids in the catchment area and to compare the results of geostatistical and deterministic approaches. This study leaned on 30-yr daily rainfall data of 70 raingages in the hilly landscape of the Ourthe and Ambleve catchments in Belgium (2908 km2). This area lies between 35 and 693 m in elevation and consists of river networks, which are tributaries of the Meuse River. For geostatistical algorithms, seven semi-variogram models (logarithmic, power, exponential, Gaussian, rational quadratic, spherical and penta-spherical) were fitted to daily sample semi-variogram on a daily basis. These seven variogram models were also adopted to avoid negative interpolated rainfall. The elevation, extracted from a digital elevation model, was incorporated into multivariate geostatistics. Seven validation raingages and cross validation were used to compare the interpolation performance of these algorithms applied to different densities of raingages. We found that between the seven variogram models used, the Gaussian model was the most frequently best fit. Using seven variogram models can avoid negative daily rainfall in ordinary kriging. The negative estimates of kriging were observed for convective more than stratiform rain. The performance of the different methods varied slightly according to the density of raingages, particularly between 8 and 70 raingages but it was much different for interpolation using 4 raingages. Spatial interpolation with the geostatistical and Inverse Distance Weighting (IDW) algorithms

  6. 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. PMID:24798906

  7. 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 oscillation between…

  8. Validation of modeled daily erythemal exposure along tropical and subtropical shipping routes by ship-based and satellite-based measurements

    NASA Astrophysics Data System (ADS)

    Feister, Uwe; Meyer, Gabriele; Laschewski, Gudrun; Boettcher, Christopher

    2015-05-01

    The Personal ERythemal EXposure (PEREX) model for seafarers working on decks of vessels has been developed to be used for retrospective estimates of personal occupational erythemal exposure in dependence of work profile, time period, and sea route. Extremely high UV index values up to 22 and daily erythemal exposure up to 89 standard erythemal dose have been derived from ship-based measurements in tropical oceans. Worldwide climatological maps of daily solar erythemal exposure derived from 10 year (2004-2013) hourly grid point radiative transfer model calculations for both cloudless sky and cloudy sky serve as the database of PEREX. The PEREX database is compared with ship-based measurements taken along four routes of merchant vessels, continuous UV radiation measurements taken on the research vessel Meteor on its mainly tropical and subtropical routes for 2 years, daily cloudless-sky erythemal exposure derived from 10 min LibRadtran radiative transfer model calculations, and 2 years of satellite-based erythemal exposure data of the Ozone Monitoring Instrument on the Aura satellite along the ship routes. Systematic differences between PEREX model data, ship-based data, and satellite-based daily erythemal exposure for all-sky conditions are only 1 to 3%, while short-term variations of cloudiness result in standard deviations of differences around 30%. Measured ratios between cloudless-sky erythemal radiation at vertical to horizontal incidence decrease with decreasing solar zenith angle, while clouds flatten their diurnal course.

  9. 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

  10. Model-Based Once-Daily Darunavir/Ritonavir Dosing Recommendations in Pediatric HIV-1-Infected Patients Aged ≥3 to <12 Years.

    PubMed

    Brochot, A; Kakuda, T N; Van De Casteele, T; Opsomer, M; Tomaka, F L; Vermeulen, A; Vis, P

    2015-07-01

    An existing population pharmacokinetic model of darunavir in adults was updated using pediatric data from two studies evaluating weight-based, once-daily dosing of darunavir/ritonavir (ARIEL, NCT00919854 and DIONE, NCT00915655). The model was then used to provide once-daily dosing recommendations for darunavir/ritonavir in pediatric patients aged ≥3 to <12 years. The final model comprised two compartments with first-order absorption and apparent clearance dependent on the concentration of α1-acid glycoprotein. The recommended darunavir/ritonavir once-daily dosing regimens in children aged ≥3 to <12 years are: 35/7 mg/kg from 10 to <15 kg, 600/100 mg from 15 to <30 kg, 675/100 mg from 30 to <40 kg, and 800/100 mg for ≥40 kg. These doses should result in exposures similar to the adult exposure after treatment with darunavir/ritonavir 800/100 mg once daily, while minimizing pill burden and allowing a switch from suspension to tablet(s) as early as possible. PMID:26312164

  11. Model-Based Once-Daily Darunavir/Ritonavir Dosing Recommendations in Pediatric HIV-1-Infected Patients Aged ≥3 to <12 Years

    PubMed Central

    Brochot, A; Kakuda, TN; Van De Casteele, T; Opsomer, M; Tomaka, FL; Vermeulen, A; Vis, P

    2015-01-01

    An existing population pharmacokinetic model of darunavir in adults was updated using pediatric data from two studies evaluating weight-based, once-daily dosing of darunavir/ritonavir (ARIEL, NCT00919854 and DIONE, NCT00915655). The model was then used to provide once-daily dosing recommendations for darunavir/ritonavir in pediatric patients aged ≥3 to <12 years. The final model comprised two compartments with first-order absorption and apparent clearance dependent on the concentration of α1-acid glycoprotein. The recommended darunavir/ritonavir once-daily dosing regimens in children aged ≥3 to <12 years are: 35/7 mg/kg from 10 to <15 kg, 600/100 mg from 15 to <30 kg, 675/100 mg from 30 to <40 kg, and 800/100 mg for ≥40 kg. These doses should result in exposures similar to the adult exposure after treatment with darunavir/ritonavir 800/100 mg once daily, while minimizing pill burden and allowing a switch from suspension to tablet(s) as early as possible. PMID:26312164

  12. 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 ...

  13. Calibration procedure for a daily flow model of small watersheds with snowmelt runoff in the Green River coal region of Colorado

    USGS Publications Warehouse

    Norris, J.M.; Parker, R.S.

    1985-01-01

    A calibration procedure was developed for the U.S. Geological Survey 's Precipitation-Runoff Modeling System for watersheds in which snowmelt is the major contributor to runoff. The model uses daily values of air temperature and precipitation as input and the output is mean daily discharge. The procedure appears sufficient to calibrate both streamflow volume and the timing of mean daily discharge if other model parameters are reasonably estimated. Model structure and sensitivity analysis suggest that one of the most important parameters is the available water-holding capacity of the soil (SMAX). Changing this parameter through a series of iterations, the calibration procedure minimizes the error between observed and predicted annual discharge. The calibration suggests that the single parameter SMAX may be sufficient for optimizing both the volumes and the timing of runoff, assuming other model parameters are adequately estimated. Additional optimization on parameters sensitive to timing does not appear to improve prediction. This indicates that these parameters were estimated accurately prior to calibration. Further investigation is needed on more watersheds to determine SMAX 's ability to calibrate volume and timing with a constant set of other model parameter values. (USGS)

  14. Modeling Integrated Cave Drip Recharge Data using DReAM (Daily Recharge Assessment Model) in a Dry Eastern Mediterranean Area, Sif Cave - Israel

    NASA Astrophysics Data System (ADS)

    Anker, Y.; Sheffer, N. A.; Scanlon, B. R.; Gimburg, A.; Morin, E.

    2010-12-01

    Understanding recharge mechanisms and controls in karst regions is extremely important for managing water resources because of the dynamic nature of the system. To better understand this mechanism, a cave in the recharge area of the karstic Western Mountain Aquifer (WMA) of Israel was equipped to measure precipitation infiltration (2006-2008) by collecting integrated water drips from three areas in the cave (14, 46, and 52 m2 areas). Barrels equipped with pressure transducers record drip rate and volume for each of the three areas and enable estimation of recharge. A water budget model - DReAM (Daily Recharge Assessment Model) was used to quantify and predict infiltration behavior at the cave. DReAM includes calculations of all water cycle components - precipitation, evapotranspiration, runoff and recharge. The model was calibrated and validated using two independent sets of values, providing good agreement between calculated and observed data. Modeling results agree with previous studies that show: 1) three distinct flow paths (slow, intermediate, and fast flows) of water infiltrating at the cave; 2) a threshold of ~100 mm rain at the beginning of the rainy season for infiltration to begin; and 3) a decrease in lag time between rain events and infiltration response throughout the rainy season. This modeling tool and analysis approach can translate precipitation to groundwater recharge which will be very important for projecting future water resources in response to climate variability.

  15. Exposure-response modeling of average daily pain score, and dizziness and somnolence, for mirogabalin (DS-5565) in patients with diabetic peripheral neuropathic pain.

    PubMed

    Hutmacher, Matthew M; Frame, Bill; Miller, Raymond; Truitt, Kenneth; Merante, Domenico

    2016-01-01

    Mirogabalin (DS-5565) is an α2δ-1 ligand being developed for pain associated with diabetic peripheral neuropathy, fibromyalgia, and postherpetic neuralgia. Nonlinear mixed-effects analyses were performed on average daily pain and on the incidence of the adverse events dizziness and somnolence. These models were used to predict the dose of mirogabalin equivalent to pregabalin and the probability of meaningful reduction in pain compared with placebo and pregabalin. In addition, regimen effects were evaluated for reductions of adverse events. Mirogabalin was estimated to be 17-fold more potent than pregabalin. The effectiveness of 150 mg pregabalin, dosed twice daily, attenuated by week 5. Therefore, the estimated mechanism-based equivalent dose (ED) of 17.7 mg mirogabalin was higher than that predicted to achieve comparable pain reduction. If attenuation of the pregabalin effect is real, mirogabalin doses lower than the ED could yield comparable pain reduction, albeit with less differentiation in pain from placebo. The incidence rate of dizziness and somnolence decreased over time. Twice-daily dosing of mirogabalin was predicted to yield a lower incidence rate of dizziness than once-daily dosing; thus, titration of dosages should reduce adverse event rates. These model results were used to influence phase 3 dosing selection. PMID:26073181

  16. 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

  17. Non-Gaussian Winter Daily Minimum and Maximum Temperatures in a Regional Climate Model: Downscaling of Reanalysis, Historical Simulations and Future Projections for the Southeast United States

    NASA Astrophysics Data System (ADS)

    Stefanova, L. B.; Sura, P.; Griffin, M.; Chan, S.; Misra, V.

    2011-12-01

    There is a marked interest in possible changes of the climate variability under future emission scenarios, and, in particular, in the potential for changes of the statistics of extreme weather. One statistical measure of extreme events is the non-Gaussianity of the variable under consideration. For the Southeast US, the non-Gaussianity of the local wintertime temperature distributions is of considerable interest to agriculture, energy, and ecosystem management. Therefore, our goal is to evaluate the expected changes of wintertime daily minimum and maximum temperature distributions in regional climate change projections in response to increased radiative forcing. First, we assess the ability of the regional model that we use - the National Centers for Environmental Prediction (NCEP)/Experimental Climate Prediction Center (ECPC) Regional Spectral Model (RSM) - to represent the observed distributions and their response to the ENSO phase. This analysis is based on the daily minimum and maximum temperatures from the COAPS Land-Atmosphere Regional Reanalysis for the Southeast at 10-km resolution (CLARReS10) obtained by dynamically downscaling the NCEP - Department of Energy (DOE) Reanalysis II (R2) and the European Centre for Medium-Range Weather Forecast (ECMWF) 40-year Reanalysis (ERA40) with the Regional Spectral Model (RSM) over the Southeast United States at a horizontal resolution of 10 km for the period 1979-2001. We demonstrate that with the near-perfect lateral boundary conditions provided by the R2 or ERA40, RSM produces daily min/max temperature distributions and distributions' sensitivity to ENSO in very good agreement with station observations. We then assess the winter daily min/max temperatures distribution generated by dynamically downscaling with RSM the historical (1970-2000) and projected (2040-2070) coupled ocean-atmosphere climate model simulations from select models from the Coupled Model Intercomparison Project Phase 3 (CMIP3).

  18. 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

  19. 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., Jr.; 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.

  20. 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

  1. Daily exercise routines

    NASA Technical Reports Server (NTRS)

    Anderson, Patrick L.; Amoroso, Michael T.

    1990-01-01

    Viewgraphs on daily exercise routines are presented. Topics covered include: daily exercise and periodic stress testings; exercise equipment; physiological monitors; exercise protocols; physiological levels; equipment control; control systems; and fuzzy logic control.

  2. 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

  3. 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

  4. 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. PMID:26995031

  5. 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.

  6. 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. PMID:25889540

  7. 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

  8. 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

  9. 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

  10. 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…

  11. 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. PMID:27354194

  12. Daily modelling of total electron content with ionosonde observation to the benefit of the open source users

    NASA Astrophysics Data System (ADS)

    Tamara, Gulyaeva; Poustovalova, Ljubov; Stanislawska, Iwona

    It is clearly beneficial if the open source databases and models are available free for the users. However a newcomer needs a guidance concerning reliability/consistency of a suitable model and database. Such guidance is provided by the International Standardization Organization which has published Technical Specification, ISO TS16457 on "The Earth's ionosphere model: international reference ionosphere (IRI) model and extensions to the plasmasphere", 2009. One of the ISO TS16457 options is IRI-IZMIRAN ionosphere-plasmasphere model. This model is applied currently to generate vertical total electron content, TEC, at the altitude range [80:20,000] km at (http://www.izmiran.ru/services/iweather/). This approach uses solar activ-ity and geomagnetic activity driving the ionosphere-plasmasphere model, and the integration of electron density profile fitted to ionosonde observation of the F2 layer peak density and height. The paper provides validation of proposed technique and comparisons with GPS-TEC observations and topside ionospheric electron density extrapolation technique providing the ionospheric TEC.

  13. A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoff

    NASA Astrophysics Data System (ADS)

    Aqil, Muhammad; Kita, Ichiro; Yano, Akira; Nishiyama, Soichi

    2007-04-01

    SummaryModeling of rainfall-runoff dynamics is one of the most studied topics in hydrology due to its essential application to water resources management. Recently, artificial intelligence has gained much popularity for calibrating the nonlinear relationships inherent in the rainfall-runoff process. In this study, the advantages of artificial neural networks and neuro-fuzzy system in continuous modeling of the daily and hourly behaviour of runoff were examined. Three different adaptive techniques were constructed and examined namely, Levenberg-Marquardt feed forward neural network, Bayesian regularization feed forward neural network, and neuro-fuzzy. In addition, the effects of data transformation on model performance were also investigated. This was done by examining the performance of the three network architectures and training algorithms using both raw and transformed data. Through inspection of the results it was found that although the model built on transformed data outperforms the model built on raw data, no significant differences were found between the forecast accuracies of the three examined models. A detailed comparison of the overall performance indicated that the neuro-fuzzy model performed better than both the Levenberg-Marquardt-FFNN and the Bayesian regularization-FFNN. In order to enable users to process the data easily, a graphic user interface (GUI) was developed. This program allows users to process the rainfall-runoff data, to train/test the model using various input options and to visualize results.

  14. 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.

  15. 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.

  16. Utility of NASA's daily solar and meteorological data for regional level modeling of wheat phenology and yield potential

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Data products from the NASA Science Mission Directorate's Applied Science Energy Managed Program provide estimates of long-term meteorological conditions from assimilation models and surface solar energy fluxes derived from satellite observations. NASA's Prediction Of Worldwide Energy Resource (POWE...

  17. Managing Daily Life

    MedlinePlus

    ... To Cure MD PPMD Merchandise Host an Event Create a Personal Page My Donor Portfolio™ Sponsor Programs Other Ways to Help About Us Mission Financials History Staff & Board Media Awards Partners Contact Us Home / Care for Duchenne / Managing Daily Life Print Email Managing Daily Life Environmental ...

  18. Chronic daily headaches

    PubMed Central

    Ahmed, Fayyaz; Parthasarathy, Rajsrinivas; Khalil, Modar

    2012-01-01

    Chronic Daily Headache is a descriptive term that includes disorders with headaches on more days than not and affects 4% of the general population. The condition has a debilitating effect on individuals and society through direct cost to healthcare and indirectly to the economy in general. To successfully manage chronic daily headache syndromes it is important to exclude secondary causes with comprehensive history and relevant investigations; identify risk factors that predict its development and recognise its sub-types to appropriately manage the condition. Chronic migraine, chronic tension-type headache, new daily persistent headache and medication overuse headache accounts for the vast majority of chronic daily headaches. The scope of this article is to review the primary headache disorders. Secondary headaches are not discussed except medication overuse headache that often accompanies primary headache disorders. The article critically reviews the literature on the current understanding of daily headache disorders focusing in particular on recent developments in the treatment of frequent headaches. PMID:23024563

  19. 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. PMID:25066669

  20. Assessment and ground-based correction of the Level-3 MODIS daily aerosol optical depth: Implications in the context of surface solar radiation prediction and numerical weather modeling

    NASA Astrophysics Data System (ADS)

    Ruiz-Arias, J. A.; Dudhia, J.; Pozo-Vazquez, D.

    2012-12-01

    The Level-3 MODIS (L3M) aerosol optical depth (AOD) product offers interesting features for surface solar radiation and numerical weather modeling applications. However, most of the validation efforts so far have been focused on Level-2 (L2M) products and only rarely on L3M. We compare the Collection 5.1 L3M AOD (Terra dataset) available since 2000 against observed daily AOD values at 550 nm from more than 500 AERONET ground stations. The aim is to check the advisability of this dataset for surface solar radiation calculations using numerical weather models. Overall, the mean error (ME) is 0.03 (17%, relative to the mean observed AOD), with a root mean square error (RMSE) of 0.14 (73%), albeit these values are found highly dependent on geographical region. For AOD values above about 0.3 the expected error (EE) is found higher than that of the L2M product. We propose specific parameterizations for the EE of the L3M AOD, as well as for both its ME and its standard deviation. We also found that, roughly, half of the uncertainty of the L3M AOD dataset might be attributable to its sub-pixel variability. Finally, we used a radiative transfer model to investigate how the L3M AOD uncertainty propagates into the direct normal (DNI) and global horizontal (GHI) irradiances evaluation. Overall, for AODs smaller than 0.5, the induced uncertainty in DNI due to AOD alone is below 15% on average, and below 5% for GHI (for a solar zenith angle of 30 degrees). But the uncertainty in AOD is highly spatially variable, so is that in irradiance. These results suggest the necessity of a correction method to reduce the bias of the L3M AOD. Ground-based AOD measurements can be also used in a data fusion procedure. We present the results of a preliminary study using optimal interpolation of L3M daily AOD data based on daily AERONET AOD measurements in the US in the period since June to August 2009. The method removes the data gaps in the original dataset, assesses the spatial distribution

  1. Long-term prediction of solar and geomagnetic activity daily time series using singular spectrum analysis and fuzzy descriptor models

    NASA Astrophysics Data System (ADS)

    Mirmomeni, M.; Kamaliha, E.; Shafiee, M.; Lucas, C.

    2009-09-01

    Of the various conditions that affect space weather, Sun-driven phenomena are the most dominant. Cyclic solar activity has a significant effect on the Earth, its climate, satellites, and space missions. In recent years, space weather hazards have become a major area of investigation, especially due to the advent of satellite technology. As such, the design of reliable alerting and warning systems is of utmost importance, and international collaboration is needed to develop accurate short-term and long-term prediction methodologies. Several methods have been proposed and implemented for the prediction of solar and geomagnetic activity indices, but problems in predicting the exact time and magnitude of such catastrophic events still remain. There are, however, descriptor systems that describe a wider class of systems, including physical models and non-dynamic constraints. It is well known that the descriptor system is much tighter than the state-space expression for representing real independent parametric perturbations. In addition, the fuzzy descriptor models as a generalization of the locally linear neurofuzzy models are general forms that can be trained by constructive intuitive learning algorithms. Here, we propose a combined model based on fuzzy descriptor models and singular spectrum analysis (SSA) (FD/SSA) to forecast a number of geomagnetic activity indices in a manner that optimizes a fuzzy descriptor model for each of the principal components obtained from singular spectrum analysis and recombines the predicted values so as to transform the geomagnetic activity time series into natural chaotic phenomena. The method has been applied to predict two solar and geomagnetic activity indices: geomagnetic aa and solar wind speed (SWS) of the solar wind index. The results demonstrate the higher power of the proposed method-- compared to other methods -- for predicting solar activity.

  2. 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...

  3. Daily temperature changes and variability in ENSEMBLES regional models predictions: Evaluation and intercomparison for the Ebro Valley (NE Iberia)

    NASA Astrophysics Data System (ADS)

    El Kenawy, A.; López-Moreno, J. I.; McCabe, M. F.; Brunsell, N. A.; Vicente-Serrano, S. M.

    2015-03-01

    We employ a suite of regional climate models (RCMs) to assess future changes in summer (JJA) maximum temperature (Tmax) over the Ebro basin, the largest hydrological division in the Iberian Peninsula. Under the A1B emission scenario, future changes in both mean values and their corresponding time varying percentiles were examined by comparing the control period (1971-2000) with two future time slices: 2021-2050 and 2071-2100. Here, the rationale is to assess how lower/upper tails of temperature distributions will change in the future and whether these changes will be consistent with those of the mean. The model validation results demonstrate significant differences among the models in terms of their capability to representing the statistical characteristics (e.g., mean, skewness and asymmetry) of the observed climate. The results also indicate that the current substantial warming observed in the Ebro basin is expected to continue during the 21st century, with more intense warming occurring at higher altitudes and in areas with greater distance from coastlines. All models suggest that the region will experience significant positive changes in both the cold and warm tails of temperature distributions. However, the results emphasize that future changes in the lower and upper tails of the summer Tmax distribution may not follow the same warming rate as the mean condition. In particular, the projected changes in the warm tail of the summer Tmax are shown to be significantly larger than changes in both mean values and the cold tail, especially at the end of the 21st century. The finding suggests that much of the changes in the summer Tmax percentiles will be driven by a shift in the entire distribution of temperature rather than only changes in the central tendency. Better understanding of the possible implications of future climate systems provides information useful for vulnerability assessments and the development of local adaptation strategies for multi

  4. Subseasonal to multidecadal variability of northeast monsoon daily rainfall over Peninsular Malaysia using a hidden Markov model

    NASA Astrophysics Data System (ADS)

    Tan, Wei Lun; Yusof, Fadhilah; Yusop, Zulkifli

    2016-04-01

    This study involves the modelling of a homogeneous hidden Markov model (HMM) on the northeast rainfall monsoon using 40 rainfall stations in Peninsular Malaysia for the period of 1975 to 2008. A six hidden states HMM was selected based on Bayesian information criterion (BIC), and every hidden state has distinct rainfall characteristics. Three of the states were found to correspond by wet conditions; while the remaining three states were found to correspond to dry conditions. The six hidden states were found to correspond with the associated atmospheric composites. The relationships between El Niño-Southern Oscillation (ENSO) and the sea surface temperatures (SST) in the Pacific Ocean are found regarding interannual variability. The wet (dry) states were found to be well correlated with a Niño 3.4 index which was used to characterize the intensity of an ENSO event. This model is able to assess the behaviour of the rainfall characteristics with the large scale atmospheric circulation; the monsoon rainfall is well correlated with the El Niño-Southern Oscillation in Peninsular Malaysia.

  5. Impact of stratospheric volcanic aerosols on the daily temperature range (DTR) in Europe over the past 200 years: observations vs. model simulations

    NASA Astrophysics Data System (ADS)

    Auchmann, Renate; Wegmann, Martin; Arfeuille, Florian; Franke, Jörg; Barriendos, Mariano; Prohom, Marc; Sanchez-Lorenzo, Arturo; Bhend, Jonas; Wild, Martin; Folini, Doris; Stepanek, Petr; van der Schrier, Gerard; Brönnimann, Stefan

    2013-04-01

    Explosive tropical volcanic eruptions can affect climate and weather on many timescales and over large areas and are one of the major causes of natural climate variability. The dominant and best understood mechanism through which volcanic eruptions influence climate is the direct radiative perturbation through secondary sulfate aerosols in the stratosphere, enhancing the reflectance of solar radiation and as a consequence leading to a loss of energy at the Earth's surface. The decrease of shortwave radiation on the ground affects the energy balance during daytime only. During the night (and also during the day), even a slight increase in surface net radiation is expected due to the increase in downwelling longwave radiation. Overall, these changes in the energy balance may lead to an overall reduction of the daily temperature range (DTR). Hence, the DTR can be utilized as a quantitative measure of the radiative forcing impact through stratospheric volcanic aerosols. We analyze this impact over Europe using long-term daily and sub-daily station records. Eight stratospheric volcanic eruptions from the instrumental period (ca. 200 years) are investigated. Seasonal all-sky DTR anomalies after volcanic eruptions are compared to contemporary (ca. 20 year) reference periods. We further use clear-sky DTR anomalies to eliminate cloud effects and better estimate the signal from the direct radiative forcing of the volcanic aerosols. We find a stronger negative signal in the clear-sky DTR anomalies compared to the all-sky case. Although the all-sky and clear-sky anomalies for different stations, volcanic eruptions, and seasons show heterogenic signals in terms of magnitude and sign, the significantly negative DTR anomalies (e.g., for Tambora) are qualitatively consistent with other studies. We quantify the impact on clear-sky DTR through stratospheric volcanic forcing, by applying a weighted linear regression model to clear-sky DTR anomalies and radiative forcing. Our estimate

  6. Repeat topography surveys of geomorphic changes using digital surface models deriving from Formosat-2 daily revisit stereo pair with very narrow baseline

    NASA Astrophysics Data System (ADS)

    Liu, C.; Wen, H.; Liu, J.; Ko, M.; Yan, H.; Chang, L.

    2012-12-01

    translative offset between two similar images to be rapidly estimated. To meet the requirements in remote sensing and biomedical imaging, the technology of phase correlation has been extended to the sub-pixel level. Liu and Yan (2008) developed a robust phase correlation model using the based feature matching for image co-registration and DEM generation. Considering the fact that the Formosat-2 consecutive images are intrinsically stereo pairs with very narrow baselines, this innovative stereo-matching algorithm based on SPPC technique is employed to process Formosat-2 daily revisit stereo pairs with very narrow baselines. The detailed accuracy and efficiency analysis is investigated for the study area, Namasha, Kaohsiung, using the 50cm resolution aerial photo and the 2m resolution DEM derived from airborne LiDAR data. The archive of Formosat-2 images in Taiwan area collected from 2005 to 2012 was screened out, with the intention to select the consecutive pairs of those areas where major slope disasters occurred in the past eight years. This research encourages the repeated topography surveys of geomorphic changes using digital surface models deriving from Formosat-2 daily revisit stereo pair with very narrow baseline.

  7. Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality

    PubMed Central

    2012-01-01

    Background Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Methods Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton’s method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. Results In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. Conclusions GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies. PMID:23110601

  8. 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. PMID:25395042

  9. 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

  10. 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

  11. Effect of enriching the diet with menhaden oil or daily treatment with resolvin D1 on neuropathy in a mouse model of type 2 diabetes.

    PubMed

    Shevalye, Hanna; Yorek, Matthew S; Coppey, Lawrence J; Holmes, Amey; Harper, Matthew M; Kardon, Randy H; Yorek, Mark A

    2015-07-01

    The purpose of this study was to determine the effect of supplementing the diet of a mouse model of type 2 diabetes with menhaden (fish) oil or daily treatment with resolvin D1 on diabetic neuropathy. The end points evaluated included motor and sensory nerve conduction velocity, thermal sensitivity, innervation of sensory nerves in the cornea and skin, and the retinal ganglion cell complex thickness. Menhaden oil is a natural source for n-3 polyunsaturated fatty acids, which have been shown to have beneficial effects in other diseases. Resolvin D1 is a metabolite of docosahexaenoic acid and is known to have anti-inflammatory and neuroprotective properties. To model type 2 diabetes, mice were fed a high-fat diet for 8 wk followed by a low dosage of streptozotocin. After 8 wk of hyperglycemia, mice in experimental groups were treated for 6 wk with menhaden oil in the diet or daily injections of 1 ng/g body wt resolvin D1. Our findings show that menhaden oil or resolvin D1 did not improve elevated blood glucose, HbA1C, or glucose utilization. Untreated diabetic mice were thermal hypoalgesic, had reduced motor and sensory nerve conduction velocities, had decreased innervation of the cornea and skin, and had thinner retinal ganglion cell complex. These end points were significantly improved with menhaden oil or resolvin D1 treatment. Exogenously, resolvin D1 stimulated neurite outgrowth from primary cultures of dorsal root ganglion neurons from normal mice. These studies suggest that n-3 polyunsaturated fatty acids derived from fish oil could be an effective treatment for diabetic neuropathy. PMID:25925322

  12. 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.

  13. Effect of enriching the diet with menhaden oil or daily treatment with resolvin D1 on neuropathy in a mouse model of type 2 diabetes

    PubMed Central

    Shevalye, Hanna; Coppey, Lawrence J.; Holmes, Amey; Harper, Matthew M.; Kardon, Randy H.; Yorek, Mark A.

    2015-01-01

    The purpose of this study was to determine the effect of supplementing the diet of a mouse model of type 2 diabetes with menhaden (fish) oil or daily treatment with resolvin D1 on diabetic neuropathy. The end points evaluated included motor and sensory nerve conduction velocity, thermal sensitivity, innervation of sensory nerves in the cornea and skin, and the retinal ganglion cell complex thickness. Menhaden oil is a natural source for n-3 polyunsaturated fatty acids, which have been shown to have beneficial effects in other diseases. Resolvin D1 is a metabolite of docosahexaenoic acid and is known to have anti-inflammatory and neuroprotective properties. To model type 2 diabetes, mice were fed a high-fat diet for 8 wk followed by a low dosage of streptozotocin. After 8 wk of hyperglycemia, mice in experimental groups were treated for 6 wk with menhaden oil in the diet or daily injections of 1 ng/g body wt resolvin D1. Our findings show that menhaden oil or resolvin D1 did not improve elevated blood glucose, HbA1C, or glucose utilization. Untreated diabetic mice were thermal hypoalgesic, had reduced motor and sensory nerve conduction velocities, had decreased innervation of the cornea and skin, and had thinner retinal ganglion cell complex. These end points were significantly improved with menhaden oil or resolvin D1 treatment. Exogenously, resolvin D1 stimulated neurite outgrowth from primary cultures of dorsal root ganglion neurons from normal mice. These studies suggest that n-3 polyunsaturated fatty acids derived from fish oil could be an effective treatment for diabetic neuropathy. PMID:25925322

  14. 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

  15. 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

  16. 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.

  17. 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

  18. A field studies and modeling approach to develop organochlorine pesticide and PCB total maximum daily load calculations: case study for Echo Park Lake, Los Angeles, CA.

    PubMed

    Vasquez, V R; Curren, J; Lau, S-L; Stenstrom, M K; Suffet, I H

    2011-09-01

    Echo Park Lake is a small lake in Los Angeles, CA listed on the USA Clean Water Act Section 303(d) list of impaired water bodies for elevated levels of organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in fish tissue. A lake water and sediment sampling program was completed to support the development of total maximum daily loads (TMDL) to address the lake impairment. The field data indicated quantifiable levels of OCPs and PCBs in the sediments, but lake water data were all below detection levels. The field sediment data obtained may explain the contaminant levels in fish tissue using appropriate sediment-water partitioning coefficients and bioaccumulation factors. A partition-equilibrium fugacity model of the whole lake system was used to interpret the field data and indicated that half of the total mass of the pollutants in the system are in the sediments and the other half is in soil; therefore, soil erosion could be a significant pollutant transport mode into the lake. Modeling also indicated that developing and quantifying the TMDL depends significantly on the analytical detection level for the pollutants in field samples and on the choice of octanol-water partitioning coefficient and bioaccumulation factors for the model. PMID:21764423

  19. 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. PMID:25680241

  20. Daily Temperature Records in a Warming Climate

    NASA Astrophysics Data System (ADS)

    Meehl, G. A.; Tebaldi, C.

    2014-12-01

    The ratio of daily record high maximum temperatures to daily record low minimum temperatures in the first decade of the 21st century was about 2 to 1. Previous model simulations also showed a comparable ratio, with projections of an increase in that ratio in the 21st century. Here we relate record highs and record lows to changing surface conditions in 1 degree and 0.5 degree resolution global coupled climate models for 20th and 21st century climate to address the issue of model resolution in simulating past and future changes of temperature extremes as represented by daily record highs and lows.

  1. Performance of STICS model to predict rainfed corn evapotranspiration and biomass evaluated for 6 years between 1995 and 2006 using daily aggregated eddy covariance fluxes and ancillary measurements.

    NASA Astrophysics Data System (ADS)

    Pattey, Elizabeth; Jégo, Guillaume; Bourgeois, Gaétan

    2010-05-01

    Verifying the performance of process-based crop growth models to predict evapotranspiration and crop biomass is a key component of the adaptation of agricultural crop production to climate variations. STICS, developed by INRA, was part of the models selected by Agriculture and Agri-Food Canada to be implemented for environmental assessment studies on climate variations, because of its built-in ability to assimilate biophysical descriptors such as LAI derived from satellite imagery and its open architecture. The model prediction of shoot biomass was calibrated using destructive biomass measurements over one season, by adjusting six cultivar parameters and three generic plant parameters to define two grain corn cultivars adapted to the 1000-km long Mixedwood Plains ecozone. Its performance was then evaluated using a database of 40 years-sites of corn destructive biomass and yield. In this study we evaluate the temporal response of STICS evapotranspiration and biomass accumulation predictions against estimates using daily aggregated eddy covariance fluxes. The flux tower was located in an experimental farm south of Ottawa and measurements carried out over corn fields in 1995, 1996, 1998, 2000, 2002 and 2006. Daytime and nighttime fluxes were QC/QA and gap-filled separately. Soil respiration was partitioned to calculate the corn net daily CO2 uptake, which was converted into dry biomass. Out of the six growing seasons, three (1995, 1998, 2002) had water stress periods during corn grain filling. Year 2000 was cool and wet, while 1996 had heat and rainfall distributed evenly over the season and 2006 had a wet spring. STICS can predict evapotranspiration using either crop coefficients, when wind speed and air moisture are not available, or resistance. The first approach provided higher prediction for all the years than the resistance approach and the flux measurements. The dynamic of evapotranspiration prediction of STICS was very good for the growing seasons without

  2. 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…

  3. 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.

  4. Coal daily by fax

    SciTech Connect

    1998-03-01

    COAL Daily lets you quickly and easily track U.S. coal market developments, including spot coal prices and market and business news. The Btu-, quality- and location-specific prices and analyses reflect the large investment to systematically collect accurate coal market price data Fieldston has made.

  5. 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.…

  6. Tips for Daily Life

    MedlinePlus

    ... A Share Plus on Google Plus I Have Alzheimer's Disease alz.org | IHaveAlz I Have Alz Homepage Know ... others living with Alzheimer's back to top The Alzheimer's ... living with the disease, share their personal insights about the daily strategies ...

  7. 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

  8. REL3.0 LPSA DAILY

    Atmospheric Science Data Center

    2016-06-02

    ... Budget (SRB) Release 3.0 Langley Parameterized Shortwave Model Daily Data in Native grid binary format News:  LPSA ... Clouds Radiation Budget Spatial Coverage:  (-90, 90)(-180,180) Spatial Resolution:  ...

  9. 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

  10. 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.

  11. Comparisons of corrected daily integrated erythemal UVR data from the U.S. EPA/UGA network of Brewer spectroradiometers with model and TOMS-inferred data

    NASA Astrophysics Data System (ADS)

    Sabburg, J.; Rives, J. E.; Meltzer, R. S.; Taylor, T.; Schmalzle, G.; Zheng, S.; Huang, N.; Wilson, A.; Udelhofen, P. M.

    2002-12-01

    A network of 21 Brewer spectroradiometers, owned by the U.S. Environmental Protection Agency (U.S. EPA) and operated by the University of Georgia (UGA), is measuring ultraviolet (UV) spectral irradiances throughout the United States. Corrections to the raw data for 4 of the 21 Brewers have now been implemented. These corrections include (1) the stray light rejection, (2) the cosine errors associated with the full sky diffuser, (3) the temperature dependence of the response of the instruments, and (4) the temporal variation in the instrument response due to changes in the optical characteristics of the instruments. While for many sites the total corrections amount to less than 10%, for certain sites they are much larger, in some cases amounting to more than 25%. It is estimated that application of these corrections brings the uncertainty of the absolute irradiance of individual spectral scans to approximately 6% for all known major sources of error for all solar zenith angles. A comparison is presented of corrected daily integrated erythemal UV doses on clear days to both model and Total Ozone Mapping Spectrometer (TOMS) UV values. The TOMS retrievals show a positive bias with respect to the measured values that falls in the range of 12.5-1.4% with an average value of 5% for the four sites studied.

  12. 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

  13. 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

  14. Modelling the fate of nonylphenolic compounds in the Seine River--part 2: assessing the impact of global change on daily concentrations.

    PubMed

    Cladière, Mathieu; Bonhomme, Céline; Vilmin, Lauriane; Gasperi, Johnny; Flipo, Nicolas; Habets, Florence; Tassin, Bruno

    2014-01-15

    This study aims at modelling the daily concentrations of nonylphenolic compounds such as 4-nonylphenol (4-NP), nonylphenol monoethoxylate (NP1EO) and nonylphenoxy acetic acid (NP1EC) within the Seine River downstream of Paris City for over a year, firstly in the present state (year 2010) and for years 2050 and 2100 in order to assess the consequences of global change on the fate of nonylphenolic compounds in the Seine river. Concentrations were first simulated for the year 2010 and compared to monthly measured values downstream of Paris. To achieve this goal, the hydrodynamic and biogeochemical model, ProSe, was updated to simulate the fate of 4-NP, NP1EO and NP1EC. The Seine upstream and Oise River (tributaries of the Seine River) concentrations are estimated according to concentrations-flow relationships. For Seine Aval wastewater treatment plant (SA-WWTP), the concentrations are considered constant and the median values of 11 campaigns are used. The biodegradation kinetics of 4-NP, NP1EO and NP1EC in the Seine River were deduced from the results of the companion paper. The Nash-Sutcliffe coefficient indicates a good efficiency to simulate the concentrations of 4-NP, NP1EC and NP1EO over an entire year. Eight scenarios were built to forecast the impacts of global warming (flow decrease), population growth (SA-WWTP flow increase) and optimisation of wastewater treatment (improvement of the quality of effluents) on annual concentrations of 4-NP, NP1EO and NP1EC at Meulan by 2050 and 2100. As a result, global warming and population growth may increase the concentrations of 4-NP, NP1EC and NP1EO, especially during low-flow conditions, while the optimisation of wastewater treatment is an efficient solution to balance the global change by reducing WWTP outflows. PMID:24095968

  15. Multiple daily fractionation schedules

    SciTech Connect

    Peschel, R.E.; Fischer, J.J.

    1982-10-01

    Although conventional fractionation schedules have been satisfactory for the treatment of some tumors, there is reason to believe that the results of radiation therapy could be improved in some cases by appropriate alterations in treatment schedules. The pharmacological characteristics of some of the electron affinic radiation sensitizers have provided added incentive to investigate newer fractionation schemes, particularly ones which deliver the majority of the radiation dose in short periods of time. This editorial discusses three papers describing preliminary clinical studies using multi-daily fractionated (MDF) radiation therapy. Two of these studies also make use of the radiation sensitizer misonidazole. (KRM)

  16. A study on the reconstitution of daily PM10 and PM2.5 levels in Paris with a multivariate linear regression model

    NASA Astrophysics Data System (ADS)

    Dimitriou, Konstantinos; Kassomenos, Pavlos

    2014-12-01

    The amount of time air spends over a region is linearly related to the region's contribution in PM. The residence time of air masses over emission sources was the main criterion for the division in 15 regions-origins. Daily PM concentrations in Paris (France), were reconstituted by multiplying the air mass residence time for each-one of the 15 regions by a regression coefficient (Bk) expressing the ability of each region to enrich the daily PM concentrations. The comparison between observed and predicted values gave satisfactory results. Local regions contributed cumulatively more than 50% of PM2.5 and PM10 in an average daily basis, whereas the residing areas of air parcels were particularly located around the city. Due to the scarceness of eastern circulation, continental airflows were associated with few episodes of extreme aerosol contributions, whereas peak air mass residence time values were isolated above Germany.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. REL3.0 LPLA DAILY NC

    Atmospheric Science Data Center

    2016-06-02

    ... Budget (SRB) Release 3.0 Langley Parameterized Longwave Model daily Data in 1x1 Degree NetCDF Format News:  LPLA ... Clouds Radiation Budget Spatial Coverage:  (-90, 90)(-180,180) Spatial Resolution:  ...

  2. REL3.0 LPSA DAILY NC

    Atmospheric Science Data Center

    2016-06-02

    ... Budget (SRB) Release 3.0 Langley Parameterized Shortwave Model Daily Data in 1x1 Degree NetCDF Format News:  LPSA ... Clouds Radiation Budget Spatial Coverage:  (-90, 90)(-180,180) Spatial Resolution:  ...

  3. Statistical Analysis of daily mean temperatures

    NASA Technical Reports Server (NTRS)

    Ross, D. C.

    1980-01-01

    Data of daily mean temperatures recorded at the Kennedy Center during the period of 1957-1977 were analyzed to forecast daily mean temperatures and their thirty-day moving averages for a period of ten to fifteen days in a given month. Since it is found that the standard deviation is linear in the mean, a logarithmic transformation of the data is used for finding an integrated moving average process IMA by the Box-Jenkins aproach. The first differences of the transformed data seem to fit a moving average model with parameter value 2, MA(2). The consideration of seasonality factor makes the fit worse.

  4. Warmer daily temperatures since 1951

    NASA Astrophysics Data System (ADS)

    Bhattacharya, Atreyee

    2012-09-01

    Days and nights have indeed become warmer over the past 60 years, a new study finds. Although several observation-based studies have shown that daily average temperatures as well as daily maximum and minimum temperatures have increased over the past few decades, controversy has remained as to how the observed trends in extreme and average temperatures are related to each other: Are the warming trends in extreme temperatures a result of a shifting mean climate, or have temperatures become more variable? Using a global observational data set of daily temperatures, Donat and Alexander compared the probability distributions of daily maximum and minimum temperatures over two 30-year periods, 1951-1980 and 1981-2010. The authors show that the maximum and minimum daily temperatures all over the globe have significantly shifted toward higher values during the latter period. They further show that the distributions have become skewed toward the hotter part of the distribution; changes are greater for daily minimum (nighttime) temperatures than for the daily maximum (daytime) temperatures. The authors conclude that the distribution of global daily temperatures has indeed become “more extreme” compared to the middle of the twentieth century. (Geophysical Research Letters, doi:10.1029/2012GL052459, 2012)

  5. Inteligent estimation of daily evapotranspiration susing

    NASA Astrophysics Data System (ADS)

    Sharifan, H.; Dehghani, A. A.

    2009-04-01

    Evapotranspiration (ET) is one of the parameters in water resources management which is attractive for design of irrigation systems. Due to interaction between meteorology parameter, there are nonlinear relations for assessing the evapotraqnspiration. Artifical neural networks are innovative approaches for estimation and prediction by using learning concept. In this study, by using the daily data of Gorgan synoptical station in Golestan province/ Iran the multilayer perceptron with back propagation learning rule was trained. Five different ANN models comprision various combinations of daily climate variable, i. e. air temperature, sunshine, wind speed and humidity was developed to evaluate degree of effect of each input variables on ET. A comparison is made between the estimated provide by ANN models and ET-values estimated by FAO-Penman-Monteith (F-P-M) method. The results show that ANN models perform better than experimental relation. Keyword : Evapotranspiration, Artifical neural network, Penman-Manteith, Gorgan.

  6. 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. PMID:15617293

  7. Publishing Daily on the Web.

    ERIC Educational Resources Information Center

    Taylor, George

    1997-01-01

    Relates how a 16,000 circulation daily newspaper publishes on the Web. Discusses lessons learned about audience, content, design, interactivity, and making money. Muses about the effect new media will have on print. (PA)

  8. MyPlate Daily Checklist

    MedlinePlus

    ... what and how much to eat within your calorie allowance. Your food plan is personalized, based on ... Daily Checklists are available below. Cross reference the calorie level and the age group in the table ...

  9. Ethnic Identity and the Daily Psychological Well-Being of Adolescents from Mexican and Chinese Backgrounds

    ERIC Educational Resources Information Center

    Kiang, Lisa; Yip, Tiffany; Gonzales-Backen, Melinda; Witkow, Melissa; Fuligni, Andrew J.

    2006-01-01

    Protective effects of ethnic identity on daily psychological well-being were examined in a sample of 415 ninth graders from Mexican and Chinese backgrounds. Utilizing daily diary assessments and multilevel modeling, adolescents with a greater regard for their ethnic group exhibited greater levels of daily happiness and less daily anxiety averaged…

  10. 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

  11. 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…

  12. Development of the fecal coliform total maximum daily load using Loading Simulation Program C++ and tidal prism model in estuarine shellfish growing areas: a case study in the Nassawadox coastal embayment, Virginia.

    PubMed

    Shen, Jian; Sun, Shucun; Wang, Taiping

    2005-01-01

    In this study, a linked model system including the Loading Simulation Program C++ (LSPC) and the tidal prism water quality model (TPWQM) was proposed as an alternative tool for total maximum daily load (TMDL) studies. The feasibility of the model system was tested by a case study in the Nassawadox Creek, a Virginia tidal water shellfish growing area. The watershed model, driven by hourly precipitation, simulates hydrology and fecal coliform accumulation and transport processes in the watershed. The simulated surface runoff and subsurface flow as well as fecal coliform loads from the watershed are discharged to the tidal creek. The tidal prism model simulates fecal coliform transport in the Creek. The model results demonstrate the effectiveness in simulating hydrology and fecal coliform concentration in the watershed and its embayment. A series of sensitivity runs was conducted to estimate the load reduction necessary for fecal coliform concentration to meet the water quality standards. The model application to the Nassawadox Creek indicates that the model system is useful in developing fecal coliform TMDLs for estuarine shellfish growing areas. PMID:16134369

  13. 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

    2015-08-01

    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.

  14. Design of landfill daily cells.

    PubMed

    Panagiotakopoulos, D; Dokas, I

    2001-08-01

    The objective of this paper is to study the behaviour of the landfill soil-to-refuse (S/R) ratio when size, geometry and operating parameters of the daily cell vary over realistic ranges. A simple procedure is presented (1) for calculating the cell parameters values which minimise the S/R ratio and (2) for studying the sensitivity of this minimum S/R ratio to variations in cell size, final refuse density, working face length, lift height and cover thickness. In countries where daily soil cover is required, savings in landfill space could be realised following this procedure. The sensitivity of minimum S/R to variations in cell dimensions decreases with cell size. Working face length and lift height affect the S/R ratio significantly. This procedure also offers the engineer an additional tool for comparing one large daily cell with two or more smaller ones, at two different working faces within the same landfill. PMID:11720268

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

    PubMed Central

    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. PMID:24301352

  16. 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...

  17. 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...

  18. A multi-species, process based vegetation simulation module to simulate successional forest regrowth after forest disturbance in daily time step hydrological transport models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To accurately simulate watershed hydrology after forest harvest using SWAT, it is important to understand the factors that potentially make certain sites more sensitive to disturbance. The growth model in SWAT has been modified to provide a more precise description of forest growth dynamics, by int...

  19. Self-critical perfectionism, daily stress, and disclosure of daily emotional events.

    PubMed

    Richardson, Clarissa M E; Rice, Kenneth G

    2015-10-01

    Although disclosure of stressful events can alleviate distress, self-critical perfectionism may pose an especially strong impediment to disclosure during stress, likely contributing to poorer psychological well-being. In the current study, after completing a measure of self-critical perfectionism (the Discrepancy subscale of the Almost Perfect Scale--Revised; Slaney, Rice, Mobley, Trippi, & Ashby, 2001), 396 undergraduates completed measures of stress and disclosure at the end of each day for 1 week. Consistent with hypotheses and previous research, multilevel modeling results indicated significant intraindividual coupling of daily stress and daily disclosure where disclosure was more likely when experiencing high stress than low stress. As hypothesized, Discrepancy moderated the relationship between daily stress and daily disclosure. Individuals higher in self-critical perfectionism (Discrepancy) were less likely to engage in disclosure under high stress, when disclosure is often most beneficial, than those with lower Discrepancy scores. These results have implications for understanding the role of stress and coping in the daily lives of self-critical perfectionists. PMID:26167649

  20. 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…

  1. 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.

  2. Daily Physical Activity Survey Report

    ERIC Educational Resources Information Center

    Alberta Education, 2008

    2008-01-01

    The intent of the Daily Physical Activity (DPA) Survey was to gather school-level information from teachers and principals regarding their perceptions of DPA, thus providing a greater understanding of DPA implementation in grades 1 to 9. This study aimed to help identify the many variables that influence the attainment of the DPA outcomes and…

  3. 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

  4. 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.

  5. Which metric of ambient ozone to predict daily mortality?

    NASA Astrophysics Data System (ADS)

    Moshammer, Hanns; Hutter, Hans-Peter; Kundi, Michael

    2013-02-01

    It is well known that ozone concentration is associated with daily cause specific mortality. But which ozone metric is the best predictor of the daily variability in mortality? We performed a time series analysis on daily deaths (all causes, respiratory and cardiovascular causes as well as death in elderly 65+) in Vienna for the years 1991-2009. We controlled for seasonal and long term trend, day of the week, temperature and humidity using the same basic model for all pollutant metrics. We found model fit was best for same day variability of ozone concentration (calculated as the difference between daily hourly maximum and minimum) and hourly maximum. Of these the variability displayed a more linear dose-response function. Maximum 8 h moving average and daily mean value performed not so well. Nitrogen dioxide (daily mean) in comparison performed better when previous day values were assessed. Same day ozone and previous day nitrogen dioxide effect estimates did not confound each other. Variability in daily ozone levels or peak ozone levels seem to be a better proxy of a complex reactive secondary pollutant mixture than daily average ozone levels in the Middle European setting. If this finding is confirmed this would have implications for the setting of legally binding limit values.

  6. 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.

  7. 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.

  8. 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. PMID:26852665

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. Sub-Daily Runoff Simulations with Parameters Inferred at the Daily Time Scale

    NASA Astrophysics Data System (ADS)

    Reynolds, J. E.; Xu, C. Y.; Seibert, J.; Halldin, S.

    2015-12-01

    Concentration times in small and medium-sized watersheds (~100-1000 km2) are commonly less than 24 hours. Flood-forecasting models then require data at sub-daily time scales, but time-series of input and runoff data with sufficient lengths are often only available at the daily time scale, especially in developing countries. This has led to a search for time-scale relationships to infer parameter values at the time scales where they are needed from the time scales where they are available. In this study, time-scale dependencies in the HBV-light conceptual hydrological model were assessed within the generalized likelihood uncertainty estimation (GLUE) approach. It was hypothesised that the existence of such dependencies is a result of the numerical method or time-stepping scheme used in the models rather than a real time-scale-data dependence. Parameter values inferred showed a clear dependence on time scale when the explicit Euler method was used for modelling at the same time steps as the time scale of the input data (1 to 24 h). However, the dependence almost fully disappeared when the explicit Euler method was used for modelling in 1-hour time steps internally irrespectively of the time scale of the input data. In other words, it was found that when an adequate time-stepping scheme was implemented, parameter sets inferred at one time scale (e.g., daily) could be used directly for runoff simulations at other time scales (e.g., 3 h or 6 h) without any time scaling and this approach only resulted in a small (if any) model performance decrease, in terms of Nash-Sutcliffe and volume-error efficiencies. The overall results of this study indicated that as soon as sub-daily driving data can be secured, flood forecasting in watersheds with sub-daily concentration times is possible with model parameter values inferred from long time series of daily data, as long as an appropriate numerical method is used.

  14. 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.

  15. Awareness of Daily Life Activities

    NASA Astrophysics Data System (ADS)

    Metaxas, Georgios; Metin, Barbaros; Schneider, Jutta; Markopoulos, Panos; De Ruyter, Boris

    The well-publicized aging of Western societies has prompted a growing interest into technologies that support awareness in cross-generational families. The idea of supporting continual and partly automated flow of information between seniors living alone and their social intimates has been gaining ground among researchers but even among industries. It is anticipated that such an information flow can help bridge geographical distance, discrepant lifestyles, and daily routines, potentially providing peace of mind to both parties and feelings of being connected.

  16. 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....

  17. AB117. Efficacy and mechanism of combination therapy using Icariin and daily sildenafil citrate for the treatment of erectile dysfunction in a rat model of bilateral cavernous nerves injury

    PubMed Central

    Xu, Yongde; Guan, Ruili; Lei, Hongen; Yang, Yong; Xin, Zhongcheng

    2016-01-01

    The commonly utilized phosphodiesterase type 5 (PDE5) inhibitors does not lead to satisfactory penile erection after radical prostatectomy due to lack of nitric oxide (NO) released from the damaged cavernous nerves (CNs). Of particular interest is that Icariin (ICA) has been demonstrated to increase the expression of neuronal NO synthase (nNOS) in our previous work. In this study, the efficacy and mechanisms ICA in combination with daily sildenafil for the treatment of neurogenic erectile dysfunction (ED) was investigated in a rat model of bilateral CNs injury (BCNI). Sixty male Sprague-Dawley rats injected with 5-ethynyl-2-deoxyuridine (EdU; 50 mg/kg) at newborn were used to track endogenous stem cells (SCs). Fourty-eight rats of BCNI were randomized equally into gavage feeding of vehicle, sildenafil, ICA and sildenafil+ICA, respectively. Twelve sham-operated rats received vehicle treatment and served as control. Interestingly, ICA in combination with sildenafil resulted in better erectile function and effectively preserved the penile size compared with the control and sildenafil groups (P<0.05). In addition, the numbers of nNOS-positive nerves and EdU-positive cells coexpressing Schwann cell marker S100 in the ICA-treated groups were greater compared with the control group (P<0.05). These results indicate that ICA promotes endogenous SCs to differentiate into Schwann cells, which is essential for the regeneration of nNOS-positive nerves after BCNI; on this basis, sildenafil can then improve penile engorgement through the NO-activated smooth muscle relaxation. Therefore, the combined use of ICA and daily sildenafil may be a candidate for the treatment of neurogenic ED in the future.

  18. Challenges of daily data homogenization

    NASA Astrophysics Data System (ADS)

    Gruber, C.; Auer, I.; Mestre, O.

    2009-04-01

    In recent years the growing demand of extreme value studies has led to the development of methods for the homogenisation of daily data. The behaviour of some of these methods has been investigated: Two methods (HOM: Della-Marta and Wanner, 2006 and SPLIDHOM: Mestre et al., submitted) which adjust the whole distribution of the climate element (especially minimum and maximum temperature) have been compared to the simpler Vincent's method (Vincent et al., 2002) which interpolates monthly adjustment factors onto daily data. The results indicate that the behaviour of the methods HOM and SPLIDHOM is very similar, although the complexity of these methods is different. They can improve the results compared to the Vincent's method when inhomogeneities in higher order moments occur. However, their applicability is limited since highly correlated neighbour series are required. More over, more data in the intervals before and after breaks is needed if the whole distribution shall be adjusted instead of the mean only. Due to these limitations a combination of distribution dependent adjustment methods and the Vincent method seems to be necessary for the homogenization of many time series. A dataset of Austrian daily maximum and minimum temperature data is used to illustrate the challenges of distribution dependent homogenization methods. Emphasis is placed on the estimation of the (sampling) uncertainty of these methods. Therefore a bootstrap approach is used. The accuracy of the calculated adjustments varies mainly between about 0.5°C for mean temperatures and more than one degree Celsius for the margins of the distribution. These uncertainty estimates can be valuable for extreme value studies.

  19. Nonlinear optics in daily life.

    PubMed

    Garmire, Elsa

    2013-12-16

    An overview is presented of the impact of NLO on today's daily life. While NLO researchers have promised many applications, only a few have changed our lives so far. This paper categorizes applications of NLO into three areas: improving lasers, interaction with materials, and information technology. NLO provides: coherent light of different wavelengths; multi-photon absorption for plasma-materials interaction; advanced spectroscopy and materials analysis; and applications to communications and sensors. Applications in information processing and storage seem less mature. PMID:24514630

  20. Unsupervised daily routine and activity discovery in smart homes.

    PubMed

    Jie Yin; Qing Zhang; Karunanithi, Mohan

    2015-08-01

    The ability to accurately recognize daily activities of residents is a core premise of smart homes to assist with remote health monitoring. Most of the existing methods rely on a supervised model trained from a preselected and manually labeled set of activities, which are often time-consuming and costly to obtain in practice. In contrast, this paper presents an unsupervised method for discovering daily routines and activities for smart home residents. Our proposed method first uses a Markov chain to model a resident's locomotion patterns at different times of day and discover clusters of daily routines at the macro level. For each routine cluster, it then drills down to further discover room-level activities at the micro level. The automatic identification of daily routines and activities is useful for understanding indicators of functional decline of elderly people and suggesting timely interventions. PMID:26737536

  1. Daily lsa-saf evapotranspiration product

    NASA Astrophysics Data System (ADS)

    Arboleda Rodallega, Alirio; Ghilain, Nicolas; Meulenberghs, Francoise

    2010-05-01

    In the framework of the EUMETSAT's Satellite Application Facility on Land Surface Analysis (LSA-SAF), some models have been implemented in view to characterize continental surfaces by using information obtained from MSG and EPS satellites. In this context a method has been developed in order to monitor the flux of water (Evapotranspiration) between the land surface and the atmosphere. The method is based on a physical approach in which radiative data derived from Meteosat Second Generation (MSG) satellites together with land-cover information are used to constrain a physical model of energy exchange between the soil-vegetation system and the atmosphere. The implemented algorithm provides instantaneous ET estimates over four regions defined in the MSG FOV (the defined regions cover Europe, Africa and the west of south America), with MSG spatial resolution (3km at sub satellite point) and a temporal time step of 30 minutes. The scope of the method is limited to evaporation from terrestrial surfaces rather than from lakes or oceans. The instantaneous product has been validated over different vegetation cover and climatic conditions, providing evidence that the algorithm is able to reproduce ET estimates with accuracy equivalent to the accuracy of ET obtained from observations. In 2009 the instantaneous ET product has been declared pre-operational by EUMETSAT, allowing the product to be disseminated to a larger community of users (http://landsaf.meteo.pt). In some areas like agriculture, hydrology, water management, ecology and climate studies the main concern is not instantaneous but accumulated values over days, months or longer periods. To encompass the need for these community of users, a daily ET product in which daily evapotranspiration is obtained as temporal integration of instantaneous values has been developed. In this contribution we will present the methodology used to obtain instantaneous ET estimates and the procedure applied to derive daily

  2. 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…

  3. WAPA Daily Energy Accounting Activities

    Energy Science and Technology Software Center (ESTSC)

    1990-10-01

    ISA (Interchange, Scheduling, & Accounting) is the interchange scheduling system used by the DOE Western Area Power Administration to perform energy accounting functions associated with the daily activities of the Watertown Operations Office (WOO). The system's primary role is to provide accounting functions for scheduled energy which is exchanged with other power companies and power operating organizations. The system has a secondary role of providing a historical record of all scheduled interchange transactions. The followingmore » major functions are performed by ISA: scheduled energy accounting for received and delivered energy; generation scheduling accounting for both fossil and hydro-electric power plants; metered energy accounting for received and delivered totals; energy accounting for Direct Current (D.C.) Ties; regulation accounting; automatic generation control set calculations; accounting summaries for Basin, Heartland Consumers Power District, and the Missouri Basin Municipal Power Agency; calculation of estimated generation for the Laramie River Station plant; daily and monthly reports; and dual control areas.« less

  4. 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.

  5. 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…

  6. 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) ...

  7. Contrails reduce daily temperature range.

    PubMed

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

    2002-08-01

    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. PMID:12167846

  8. The Effect of Depressive Symptoms on Adherence to Daily Oral PrEP in Men who have Sex with Men and Transgender Women: A Marginal Structural Model Analysis of The iPrEx OLE Study.

    PubMed

    Mehrotra, Megha L; Glidden, David V; McMahan, Vanessa; Amico, K Rivet; Hosek, Sybil; Defechereux, Patricia; Mayer, Kenneth H; Veloso, Valdilea G; Bekker, Linda-Gail; Avelino-Silva, Vivian I; Schechter, Mauro; Grant, Robert M

    2016-07-01

    We assessed the role of depressive symptoms on adherence to daily oral FTC/TDF for HIV PrEP in cisgender men who have sex with men (MSM) and transgender women who have sex with men (TGW) using data from the iPrEx OLE study. A marginal structural logistic regression model was used to estimate the effect of time-varying CES-D scores on having protective levels of drug concentration, adjusting for confounding by sexual practices over time, prior adherence, and baseline demographic characteristics. We found a non-monotonic relationship between CES-D score and odds of protective FTC/TDF levels in MSM. We found evidence that the effect of depression on adherence varied between MSM and TGW, and that depressive symptoms did not contribute greatly to decreased adherence on a population scale. We recommend that depressive symptoms not preclude the prescription of PrEP, and that MSM and TGW be studied separately. PMID:27125241

  9. 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

  10. 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...

  11. On estimating total daily evapotranspiration from remote surface temperature measurements

    NASA Technical Reports Server (NTRS)

    Carlson, Toby N.; Buffum, Martha J.

    1989-01-01

    A method for calculating daily evapotranspiration from the daily surface energy budget using remotely sensed surface temperature and several meteorological variables is presented. Vaules of the coefficients are determined from simulations with a one-dimensional boundary layer model with vegetation cover. Model constants are obtained for vegetation and bare soil at two air temperature and wind speed levels over a range of surface roughness and wind speeds. A different means of estimating the daily evapotranspiration based on the time rate of increase of surface temperature during the morning is also considered. Both the equations using our model-derived constants and field measurements are evaluated, and a discussion of sources of error in the use of the formulation is given.

  12. Daily hassles reported by Dutch multiple sclerosis patients.

    PubMed

    van der Hiele, Karin; Spliethoff-Kamminga, Noëlle G; Ruimschotel, Rob P; Middelkoop, Huub A; Visser, Leo H

    2012-09-15

    There is growing evidence for the association between stress and relapse risk in multiple sclerosis (MS). The current study focuses on daily hassles, which by their chronic and accumulating nature can cause considerable psychosocial stress. The main aim was to investigate the frequency, associated distress and type of daily hassles encountered by Dutch MS patients from a large community-based sample. We further examined factors associated with high levels of psychosocial stress. Questionnaires concerning demographics, disease characteristics, physical functioning, daily hassles, fatigue, depression and anxiety were completed by 718 MS patients. Three patients younger than 18 were excluded, resulting in 715 patients. Compared with published norm data, more than 50% of the participants reported a high number of daily hassles (57.5%) and high levels of associated distress (55.7%). Frequently mentioned daily hassles concern personal functioning and social developments. A logistic regression model revealed that being female, being younger, having a higher educational level, using benzodiazepines, exhibiting more symptoms of anxiety, and a higher physical impact of fatigue were all independently associated with high levels of psychosocial stress. Our findings may alert clinicians of the high prevalence and impact of daily hassles in MS and underline the need to incorporate stress and anxiety management strategies in (psycho)therapeutic interventions. PMID:22795386

  13. 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.

  14. 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. PMID:26888661

  15. Clinical outcome of daily dialysis.

    PubMed

    Vos, P F; Zilch, O; Kooistra, M P

    2001-01-01

    Dialysis patients are prone to malnutrition, which may be counteracted by daily home hemodialysis (DHHD, 6 times a week) due to improved clinical outcome and quality of life. Eleven patients were treated with DHHD during 18 months, after a run-in period with three dialysis sessions a week. The total weekly dialysis dose was kept constant during the first 6 months of DHHD, whereupon it was allowed to increase. KT/V was 3.1 +/- 0.5 at baseline, 3.2 +/- 0.5 after 6 months and 4.0 +/- 0.8 at 18 months. Blood pressure decreased from 142 +/- 19/83 +/- 8 to 130 +/- 25/79 +/- 9 mmHg with a more than 50% reduction in antihypertensive medication. Potassium did not change, but potassium binding resins could be stopped almost completely. Bicarbonate increased from 20.6 +/- 3.3 to 23.1 +/- 2.6 mEq/L after 18 months. Patients with a protein intake of less than 1.0 g/kg/d showed a greater increase in body weight (62.3 +/- 6.0 to 65.5 +/- 3.7, P: < 0.05) and normalized protein catabolic rate (nPCR) (0.87 +/- 0.08 to 1.25 +/- 0.36, ns) than patients with acceptable protein intake (>/=1.0 g/kg/d). Phosphate decreased, though not significantly, especially in the latter group. Erythropoietin dose could be reduced from 6400 +/- 5400 U/L at baseline to 5100 +/- 4000 U/L at 18 months. Quality of life improved significantly, especially with to respect to physical condition and mental health. The DHHD markedly improves hemodynamic control and quality of life. Overall nutritional parameters did not change, except cholesterol. Patients with a low protein intake, however, showed a significant increase in body weight, and a greater rise in nPCR. PMID:11158871

  16. Patrol Officer Daily Noise Exposure.

    PubMed

    Gilbertson, Lynn R; Vosburgh, Donna J H

    2015-01-01

    established by the OSHA or ACGIH occupational exposure levels from the daily occupational tasks that were monitored. PMID:26011417

  17. 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

  18. Associations of Subjective Social Status with Nondaily and Daily Smoking

    PubMed Central

    Reitzel, Lorraine R.; Buchanan, Taneisha S.; Nguyen, Nga; Ahluwalia, Jasjit S.

    2013-01-01

    Objectives To explore associations between subjective social status (SSS) and smoking level among 2274 adult current smokers. Methods Associations were investigated using a covariate-adjusted proportional odds cumulative logit model. Moderation (via race/ethnicity or sex) and mediation (via depressive symptoms, social/emotional support, or life satisfaction) were explored in additional models. Results Higher SSS was associated with greater likelihood of nondaily versus light daily or moderate/ heavy daily smoking (p = .017). Life satisfaction partially mediated the association of SSS and smoking level (p = .003). Conclusions Higher SSS was associated with greater likelihood of nondaily relative to light daily or moderate to heavy smoking, potentially via greater life satisfaction. Additional studies are needed to confirm these findings. PMID:24629553

  19. College Students’ Daily-level Reasons for not Drinking

    PubMed Central

    O’Hara, Ross E.; Armeli, Stephen; Tennen, Howard

    2016-01-01

    Introduction and Aims Motivational models of alcohol use posit opposing approach and avoidance motives related to drinking, yet no micro-longitudinal study of college students has examined avoidance motives (i.e., reasons for not drinking [RNDs]). This exploratory study examined daily- and person-level correlates of students’ RNDs to identify factors that may inhibit alcohol use. Design and Methods College students (N = 1631; 54% female) participated in a 30-day daily diary study in which they reported RNDs for non-drinking evenings, as well as daily moods, global drinking motives, and alcohol expectancies. Results Daily sadness was positively associated with not drinking due to having nobody with whom to drink, but negatively associated with not drinking due to school work. Daily anxiety was negatively associated with not drinking due to lack of desire and positively associated with not drinking due to habit or having school or job responsibilities. At the person level, multiple RNDs were associated with both coping and conformity motives (but not social or enhancement motives), as well as positive (but not negative) alcohol expectancies. Discussion and Conclusions Results demonstrate the complexity of modelling mood-drinking contingencies proposed by motivational theories of alcohol use. Distinct moods may promote or inhibit drinking through various pathways, which could help explain the weak associations between daily mood and drinking level observed in previous studies. Measuring reasons both for and against drinking in micro-longitudinal studies (e.g., daily diaries) is recommended to better understand the processes underlying alcohol use and to inform future prevention efforts. PMID:24976084

  20. 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%. PMID:18843548

  1. Maximum Daily Discharge Prediction using Multi Layer Perceptron Network

    NASA Astrophysics Data System (ADS)

    Rezaeian Zadeh, M.; Abghari, H.; van de Giesen, N.; Nikian, A.; Niknia, N.

    2009-04-01

    Prediction of maximum daily flow is essential for planning of water resources systems. This study presents the use of an Artificial Neural Network (ANN) to maximum daily flow prediction in the Khosrow Shirin watershed, in north-west Fars province in Iran. Precipitation from four meteorological stations was used to develop a Multi Layer Perceptron (MLP) optimized with the Levenberg-Marquardt (MLP_LM) training algorithm and using a tangent sigmoid activation function. Different methods to construct the input vectors were considered during models development. In the first method the precipitation signal is imported separately as input vectors for training. In the second method area-weighted precipitation and related Hydrographs were used in MLP development. In addition to precipitation, in the last model three inputs were used that were base on antecedent flows with one and two days time lag. The performance of each of these models was investigated with the root mean square errors (RMSE) and correlation coefficient (R2). The results show that the second method with weighted precipitation has higher prediction efficiency. R2 and RMSE of training and validation phase for third the model with weighted precipitation were 0.98 and 0.96, respectively Addition of antecedent flow as input vector and use of weighted precipitation provide better results in maximum daily flow prediction. Keywords: Multi Layer Perceptron, Maximum Daily Flow Prediction, Weighted Precipitation, Antecedent flow, Levenberg-Marquardt Algorithm.

  2. Sub-Daily Runoff Simulations with Parameters Inferred at the Daily Time Scale: Impacts of the temporal distribution of rainfall in parameter inference.

    NASA Astrophysics Data System (ADS)

    Reynolds Puga, Jose Eduardo; Halldin, Sven; Xu, Chong-Yu; Seibert, Jan

    2016-04-01

    Flood forecasting at sub-daily time scales are commonly required in regions where sub-daily observational data are not available. This has led to approaches to estimate model parameters at sub-daily time scales from data with a lower time resolution. Reynolds et al. (2015) show that parameters inferred at one time scale (e.g., daily) may be used directly for runoff simulations at other time scales (e.g., 1 h) when the modelling time step is the same and sufficiently small during calibration and simulation periods. Their approach produced parameter distributions at daily and sub-daily time scales that were similar and relatively constant across the time scales. The transfer of parameter values across time scales resulted in small model-performance decrease as opposed to when the parameter sets inferred at their respective time scale were used. This decrease in performance may be attributed to the degree of information lost, in terms of the physical processes occurring at short time scales, when the rainfall-runoff data used during the parameter-inference phase become coarser. It is not yet fully understood how the aggregation (or disaggregation) of the rainfall-runoff data affects parameter inference. In this study we analyse the impacts of the temporal distribution of rainfall for inferring model parameters at a coarse time scale and their effects in model performance when they are used at finer time scales, where data may not be available for calibration. The motivation is to improve runoff predictions and model performance at sub-daily time scales when parameters inferred at the daily scale are used for simulating at these scales. First, we calibrated the HBV-light conceptual hydrological model at the daily scale, but modelled discharge internally in 1-h time steps using 3 disaggregation procedures of the rainfall data. This was done in an attempt to maximise the information content of the input data used for calibration at the daily scale. One disaggregation

  3. 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…

  4. REL3.0 SW DAILY LOCAL

    Atmospheric Science Data Center

    2016-06-02

    ... Budget (SRB) Release 3.0 GEWEX Shortwave Daily Local Time Data in Native grid binary format   News:  GEWEX ... Temporal Resolution:  Daily from 3-hourly Local Sun time values File Format:  BINARY Tools:  ...

  5. 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.…

  6. Daily Oral Language: Is It Effective?

    ERIC Educational Resources Information Center

    Whittingham, Jeff L.

    2007-01-01

    This study examines the Daily Oral Language (DOL) program aimed at helping students learn mechanics of writing through daily editing exercises. This nine-month study sought to determine if DOL improved editing skills and actual writing skills of seventy fourth-grade students. While the results of this study did not statistically demonstrate the…

  7. 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....

  8. 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....

  9. 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....

  10. 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....

  11. 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....

  12. 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.

  13. Predictors of Daily Relationship Quality in Mothers of Children with Autism Spectrum Disorder.

    PubMed

    Timmons, Lisa; Willis, Kelcie D; Pruitt, Megan M; Ekas, Naomi V

    2016-08-01

    Mothers of children with autism spectrum disorder (n = 70) completed online measures of global constructs (i.e., stable individual characteristics measured at time 1), which included resilience, depressive symptoms, and family functioning, followed by 14 daily questionnaires assessing relationship quality and affect on a given day. The global constructs were examined as predictors of daily relationship quality using multilevel modeling. Daily affect was examined in association with daily relationship factors (partner conflict, support from partner, and relationship happiness). Depressive symptoms and family flexibility predicted daily relationship quality. On a daily level, affect was associated with relationship quality. Results emphasize the potential of interventions to improve the quality of parents' relationships by addressing maternal mental health, family functioning, and daily affect. PMID:27097814

  14. DAILY SOCIAL EXCHANGES AND AFFECT IN MIDDLE AND LATER ADULTHOOD: THE IMPACT OF LONELINESS AND AGE*

    PubMed Central

    RUSSELL, ALISSA; BERGEMAN, C. S.; SCOTT, STACEY B.

    2013-01-01

    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. PMID:22950350

  15. 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. PMID:20685663

  16. A stochastic daily weather generator for skewed data

    NASA Astrophysics Data System (ADS)

    Flecher, C.; Naveau, P.; Allard, D.; Brisson, N.

    2010-07-01

    To simulate multivariate daily time series (minimum and maximum temperatures, global radiation, wind speed, and precipitation intensity), we propose a weather state approach with a multivariate closed skew-normal generator, WACS-Gen, that is able to accurately reproduce the statistical properties of these five variables. Our weather generator construction takes advantage of two elements. We first extend the classical wet and dry days dichotomy used in most past weather generators to the definition of multiple weather states using clustering techniques. The transitions among weather states are modeled by a first-order Markov chain. Second, the vector of our five daily variables of interest is sampled, conditionally on these weather states, from a closed skew-normal distribution. This class of distribution allows us to handle nonsymmetric behaviors. Our method is applied to the 20 years of daily weather measurements from Colmar, France. This example illustrates the advantages of our approach, especially improving the simulation of radiation and wind distributions.

  17. The effects of conscientiousness on the appraisals of daily stressors.

    PubMed

    Gartland, Nicola; O'Connor, Daryl B; Lawton, Rebecca

    2012-02-01

    Conscientiousness (C) is positively associated with health and longevity although the mechanisms underlying this relationship are not fully understood. Stress may play a role in explaining the C-longevity relationship. This study investigated whether C predicted the cognitive appraisals of daily stressors/hassles. Participants (N=102) completed measures of C and cognitive appraisal in relation to the most stressful hassle they had experienced in the last 7 days. Correlational analysis revealed that Total C, Order and Industriousness were positively correlated with primary appraisals, and Responsibility was positively correlated with secondary appraisals. The facets of C were then entered into hierarchical regression models, controlling for age and gender. This demonstrated that Order (β=0.27, p<0.05) and Industriousness (β=0.28, p<0.05) significantly predicted primary appraisals, accounting for 15.8% of the variance. Responsibility significantly predicted secondary appraisals (β=0.44, p<0.01), accounting for 16.3% of the variance. These findings indicate that higher Order and Industriousness are related to having a greater stake in daily stressors, whereas higher Responsibility is related to greater confidence in one's ability to deal with daily stressors. These results are the first demonstration that C is related to the appraisals of daily hassles and suggest that C may moderate the experience of stress in daily life. PMID:22259161

  18. The quality of experience in adolescents' daily lives: developmental perspectives.

    PubMed

    Delle Fave, A; Bassi, M

    2000-08-01

    The authors analyzed the pattern of experience fluctuation in adolescents' daily activities. Italian high school students (N = 120; 16-20 years of age) were tested with the experience sampling method, a technique based on on-line sampling of daily life and experience. A total of 4,794 forms were gathered and analyzed by means of a model for the study of experience fluctuations. Among daily activities, studying at home, doing classwork, watching television, and having structured leisure were selected as the focus of analysis on the basis of their frequency and meaning in the adolescents' lives. Results showed that (a) daily activities have unique experiential profiles, (b) engagement may be used as an index of long-term commitment to a given activity, (c) studying at home and doing classwork share this basic component and can foster behavioral development, (d) structured leisure can play an edifying role at the short-term level for a socially integrated transition to adulthood, and (e) watching television is associated with lack of goals and engagement and is a source of apathy. The results (a) shed light on the role of daily life experience in shaping individual development and (b) provide suggestions for educational and psychosocial intervention in adolescence. PMID:10950201

  19. Daily temperature variations on Mars

    NASA Technical Reports Server (NTRS)

    Ditteon, R.

    1982-01-01

    It is noted that for approximately 32% of the Martian surface area no values of thermal inertia or albedo can fit the thermal observations. These temperature anomalies do not correlate with elevation, geologic units, morphology, or atmospheric dust content. All regions having a Lambert albedo less than 0.18 can be well fit with the standard thermal model, but all areas with albedo greater than 0.28 are anomalous. A strong inverse correlation is seen between the magnitude of the anomaly and the thermal inertia. This correlation is seen as indicating that some surface property is responsible for the anomaly. In the anomalous region the temperatures are observed to be warmer in the morning and cooler late in the afternoon and to decrease more slowly during the night than the Viking model temperatures. It is believed that of all the physical processes likely to occur on Mars but not included in the Viking thermal model, only a layered soil can explain the observations. A possible explanation of the layering deduced from the infrared thermal mapper observations is a layer of aeolian deposited dust about one thermal skin depth thick (1 to 4 cm), covering a duricrust.

  20. Individual differences in vagal regulation moderate associations between daily affect and daily couple interactions.

    PubMed

    Diamond, Lisa M; Hicks, Angela M; Otter-Henderson, Kimberly D

    2011-06-01

    Previous research suggests that cardiac vagal regulation (indexed by respiratory sinus arrhythmia, or RSA) provides a physiological substrate for affect regulation, which presumably underlies adaptive interpersonal functioning.The authors tested these associations in the context of daily interactions between 68 cohabiting couples. Participants underwent a laboratory assessment of RSA during rest and also during a series of psychological stressors. Subsequently, they kept daily measures of affect and interaction quality for 21 days. Individual differences in baseline and stress levels of RSA moderated within-person associations between daily affect and the quality of couple interactions. The pattern of results differed for women versus men. Men with lower vagal tone or higher vagal reactivity had stronger associations between daily negative affect and daily negative interactions, and men with higher vagal tone had more positive daily interactions overall. Women with higher vagal tone had stronger associations between daily positive affect and daily positive interactions. PMID:21393615

  1. "Self-critical perfectionism, daily stress, and disclosure of daily emotional events": Correction to Richardson and Rice (2015).

    PubMed

    2016-01-01

    Reports an error in "Self-critical perfectionism, daily stress, and disclosure of daily emotional events" by Clarissa M. E. Richardson and Kenneth G. Rice (Journal of Counseling Psychology, 2015[Oct], Vol 62[4], 694-702). In the article, the labels of the two lines in Figure 1 were inadvertently transposed. The dotted line should be labeled High SCP and the solid line should be labeled Low SCP. The correct version is present in the erratum. (The following abstract of the original article appeared in record 2015-30890-001.) Although disclosure of stressful events can alleviate distress, self-critical perfectionism may pose an especially strong impediment to disclosure during stress, likely contributing to poorer psychological well-being. In the current study, after completing a measure of self-critical perfectionism (the Discrepancy subscale of the Almost Perfect Scale-Revised; Slaney, Rice, Mobley, Trippi, & Ashby, 2001), 396 undergraduates completed measures of stress and disclosure at the end of each day for 1 week. Consistent with hypotheses and previous research, multilevel modeling results indicated significant intraindividual coupling of daily stress and daily disclosure where disclosure was more likely when experiencing high stress than low stress. As hypothesized, Discrepancy moderated the relationship between daily stress and daily disclosure. Individuals higher in self-critical perfectionism (Discrepancy) were less likely to engage in disclosure under high stress, when disclosure is often most beneficial, than those with lower Discrepancy scores. These results have implications for understanding the role of stress and coping in the daily lives of self-critical perfectionists. (PsycINFO Database Record PMID:26751156

  2. 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.

  3. Stochastic Simulation of Daily Solar Radiation from Sunshine Duration

    NASA Astrophysics Data System (ADS)

    Lockart, N.; Kavetski, D.; Franks, S. W.

    2014-12-01

    Solar radiation is a key component of the energy balance used for estimating evaporation. As solar radiation is not widely measured, many empirical models have been developed to estimate solar radiation using sunshine hours (SSH) data. Most of these models only provide deterministic estimates of monthly solar radiation and do not provide an estimate of the uncertainty in the predictions. This study developed five stochastic models which use daily SSH data to produce probabilistic simulations of solar radiation, and can be used to estimate historical daily radiation. The predictive uncertainty due to the timing of the SSH during the day (estimated using Monte Carlo simulation), as well as due to external errors (such as the variability in cloud type and atmospheric composition), were considered. The developed models differ in their parameterisation of the direct and diffuse components of the solar radiation, using either no scaling, linear or quadratic scaling of the radiation by the daily SSH fraction to account for cloud attenuation. For each model the simulated solar radiation was compared with the observed radiation. The performance of the five models was compared and the models were found to perform similarly well, with an average error of approximately 9% for all locations studied. The results suggest that the uncertainty due to the timing of the SSH does not dominate predictive errors in global radiation. Rather the external uncertainty is the dominant source of predictive error in the radiation estimates.

  4. Adolescent Daily and General Maladjustment: Is There Reactivity to Daily Repeated Measures Methodologies?

    ERIC Educational Resources Information Center

    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…

  5. 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. PMID:26815039

  6. 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

  7. 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

  8. [Daily life activities following cerebrovascular infarct].

    PubMed

    Pradat-Diehl, Pascale; Peskine, Anne

    2006-09-15

    Cerebro-vascular disease is the first cause of handicap in France. Disabilities in daily life activities are due to motor, visual and cognitive impairments following a stroke. Difficulties arise while grooming, getting dressed, eating, moving around ... the WHO presents with a new classification of functioning, that has been followed by a recent law in France. The aim is to place the handicapped citizen in daily life and not just to list his/her deficiencies. Rehabilitation after stroke has to establish functional objectives early so as to include daily life goals in re-education. PMID:17002070

  9. Providing daily updated weather data for online risk assessment

    NASA Astrophysics Data System (ADS)

    Petritsch, R.; Hasenauer, H.

    2009-04-01

    Daily weather data are an important constraint for diverse applications in ecosystem research. In particular, temperature and precipitation are the main drivers for forest ecosystem productivity. Mechanistic modeling theory heavily relies on daily values for minimum and maximum temperatures, precipitation, incident solar radiation and vapor pressure. These data are usually provided by interpolation techniques using measured values from surrounding stations or weather generators based on monthly mean values. One well-known and frequently used software packages is DAYMET which was adapted and validated for Austrian purposes. The calculation includes the interpolation of maximum and minimum temperature and precipitation based on near-by measurements and the subsequent extrapolation of incident solar radiation and vapor pressure deficit based on the temperature and precipitation values. The Austrian version of DAYMET uses daily weather data from more than 400 measuring stations all over Austria from 1960 to 2005. Due to internal procedures of DAYMET daily values for a whole year are estimated together; thus, the update of the database may only be done with full year records. Whether this approach convenient for retrospective modeling studies risk assessment (e.g. drought stress, forest fire, insect outbreaks) needs a higher update frequency than a full year. At best the measurements would be available immediately after they are taken. In practice the update frequency is limited by the operational provision of daily weather data. The aim of this study is to implement a concept for providing daily updated weather data as it could be used for continuous risk assessment. First we built a new climate database containing all available daily measurements. It is based on a well-established Relational Database Management System (RDBMS) and may be accessed and extended using the Standard Query Language (SQL). Secondly, we re-implemented the interpolation logic for temperature

  10. 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.

  11. Monitoring Daily Evapotranspiration in California Vineyards Using Landsat 8

    NASA Astrophysics Data System (ADS)

    Anderson, M. C.; Semmens, K. A.; Kustas, W. P.; Gao, F.; Alfieri, J. G.; McKee, L.; Prueger, J. H.; Hain, C.; Cammalleri, C.

    2014-12-01

    In California's Central Valley, due to competing demands for limited water resources, it is critical to monitor evaporative water loss and crop conditions at both individual field scales and over larger areas in support of water management decisions. This is particularly important for viticulture because grape vines must be maintained under highly controlled conditions in order to maximize production of quality fruit. Thus, regular high resolution temporal monitoring of hundreds of acres is required, a task only efficiently achieved with satellite remote sensing, combining multiple earth observations. In this research, we evaluate the utility of a multi-scale system for monitoring evapotranspiration (ET) and crop water stress applied over two vineyard sites near Lodi, California during the 2013 growing season. The system employs a data fusion methodology (STARFM: Spatial and Temporal Adaptive Reflective Fusion Model) combined with multi-scale ET modeling (ALEXI: Atmosphere Land Exchange Inverse Model) to compute daily 30 m resolution ET. ALEXI ET fluxes (4 km resolution, daily) are integrated with ET fluxes from Landsat 8 thermal data (30 m resolution, ~16 day) and Moderate Resolution Imaging Spectroradiometer (MODIS) data (1 km resolution, daily). The high spatial resolution Landsat retrievals are then fused with high temporal frequency MODIS data using STARFM to produce daily estimates of crop water use that resolve within field variation in ET for individual vineyards. Estimates of daily ET generated in two fields of Pinot Noir vines of different maturity agreed well with ground-based flux measurements collected within each field with relative errors of about 15%. Spatial patterns of cumulative ET correspond to yield estimates and indicate areas of variable crop moisture, condition, and yield within the vineyards that could require additional management strategies due to variation in soil type/texture, nutrient conditions and other environmental factors.

  12. Americans Getting Adequate Water Daily, CDC Finds

    MedlinePlus

    ... medlineplus/news/fullstory_158510.html Americans Getting Adequate Water Daily, CDC Finds Men take in an average ... new government report finds most are getting enough water each day. The data, from the U.S. National ...

  13. 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...

  14. Americans Getting Adequate Water Daily, CDC Finds

    MedlinePlus

    ... gov/news/fullstory_158510.html Americans Getting Adequate Water Daily, CDC Finds Men take in an average ... new government report finds most are getting enough water each day. The data, from the U.S. National ...

  15. REL3.0 SW DAILY UTC

    Atmospheric Science Data Center

    2016-06-02

    ... 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 ...

  16. Products to Aid in Daily Living

    MedlinePlus

    ... Research In Your Community Advocate Get Involved Donate Products to Aid in Daily Living The materials and ... Check back for an update to this message. Product List Product/Services Topics Care Services Information and ...

  17. 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

  18. Personality pathology and daily aspects of marital functioning.

    PubMed

    South, Susan C

    2014-04-01

    Personality disorders (PDs) are associated with a host of interpersonal problems, including unstable and dysfunctional romantic relationships. In previous research, PD symptoms have been linked to one's own and spouse's self-reported level of marital satisfaction and marital conflict. The current study extends on this work by examining whether Diagnostic and Statistical Manual of Mental Disorders (DSM) PD criteria would predict aspects of daily marital functioning. A total of 99 newlywed couples (N = 198) recruited from the community were assessed for PD symptoms using a self-report measure and subsequently completed a 6-day diary protocol. Multilevel modeling was used to examine the association of PD symptoms with three major aspects of daily functioning: overall relationship sentiment, serious conflicts with one's spouse, and quality of interactions. Results indicated that PD symptoms significantly predicted aspects of all three measures of daily functioning. The individual PDs generally showed the greatest associations with aspects of conflict. Paranoid, schizoid, avoidant, and obsessive-compulsive PD scores were significantly negatively related to overall relationship sentiment whereas Cluster A and Cluster C PD scores negatively predicted various daily interaction behaviors. Findings provide insight into the mechanisms that might explain the associations between PD symptoms and overall measures of relationship functioning. PMID:24364502

  19. 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.

  20. Spatial interpolation of daily precipitation in China: 1951-2005

    NASA Astrophysics Data System (ADS)

    Chen, Deliang; Ou, Tinghai; Gong, Lebing; Xu, Chong-Yu; Li, Weijing; Ho, Chang-Hoi; Qian, Weihong

    2010-11-01

    Climate research relies heavily on good quality instrumental data; for modeling efforts gridded data are needed. So far, relatively little effort has been made to create gridded climate data for China. This is especially true for high-resolution daily data. This work, focuses on identifying an accurate method to produce gridded daily precipitation in China based on the observed data at 753 stations for the period 1951-2005. Five interpolation methods, including ordinary nearest neighbor, local polynomial, radial basis function, inverse distance weighting, and ordinary kriging, have been used and compared. Cross-validation shows that the ordinary kriging based on seasonal semi-variograms gives the best performance, closely followed by the inverse distance weighting with a power of 2. Finally the ordinary kriging is chosen to interpolate the station data to a 18 km× 18 km grid system covering the whole country. Precipitation for each 0.5° × 0.5° latitude-longitude block is then obtained by averaging the values at the grid nodes within the block. Owing to the higher station density in the eastern part of the country, the interpolation errors are much smaller than those in the west (west of 100°E). Excluding 145 stations in the western region, the daily, monthly, and annual relative mean absolute errors of the interpolation for the remaining 608 stations are 74%, 29%, and 16%, respectively. The interpolated daily precipitation has been made available on the internet for the scientific community.

  1. Comparison of mapping approaches of design annual maximum daily precipitation

    NASA Astrophysics Data System (ADS)

    Szolgay, J.; Parajka, J.; Kohnová, S.; Hlavčová, K.

    2009-05-01

    In this study 2-year and 100-year annual maximum daily precipitation for rainfall-runoff studies and estimating flood hazard were mapped. The daily precipitation measurements at 23 climate stations from 1961-2000 were used in the upper Hron basin in central Slovakia. The choice of data preprocessing and interpolation methods was guided by their practical applicability and acceptance in the engineering hydrologic community. The main objective was to discuss the quality and properties of maps of design precipitation with a given return period with respect to the expectations of the end user. Four approaches to the preprocessing of annual maximum 24-hour precipitation data were used, and three interpolation methods employed. The first approach is the direct mapping of at-site estimates of distribution function quantiles; the second is the direct mapping of local estimates of the three parameters of the GEV distribution. In the third, the daily precipitation totals were interpolated into a regular grid network, and then the time series of the maximum daily precipitation totals in each grid point of the selected region were statistically analysed. In the fourth, the spatial distribution of the design precipitation was modeled by quantiles predicted by regional precipitation frequency analysis using the Hosking and Wallis procedure. The three interpolation methods used were the inverse distance weighting, nearest neighbor and the kriging method. Visual inspection and jackknife cross-validation were used to compare the combination of approaches.

  2. 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.

  3. Socioeconomic Status and Health: A Micro-Level Analysis of Exposure and Vulnerability to Daily Stressors

    ERIC Educational Resources Information Center

    Grzywacz, Joseph G.; Almeida, David M.; Neupert, Shevaun D.; Ettner, Susan L.

    2004-01-01

    This study examines the interconnections among education--as a proxy for socioeconomic status--stress, and physical and mental health by specifying differential exposure and vulnerability models using data from The National Study of Daily Experiences (N = 1,031). These daily diary data allowed assessment of the social distribution of a…

  4. 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…

  5. Methods to improve neural network performance in daily flows prediction

    NASA Astrophysics Data System (ADS)

    Wu, C. L.; Chau, K. W.; Li, Y. S.

    2009-06-01

    SummaryIn this paper, three data-preprocessing techniques, moving average (MA), singular spectrum analysis (SSA), and wavelet multi-resolution analysis (WMRA), were coupled with artificial neural network (ANN) to improve the estimate of daily flows. Six models, including the original ANN model without data preprocessing, were set up and evaluated. Five new models were ANN-MA, ANN-SSA1, ANN-SSA2, ANN-WMRA1, and ANN-WMRA2. The ANN-MA was derived from the raw ANN model combined with the MA. The ANN-SSA1, ANN-SSA2, ANN-WMRA1 and ANN-WMRA2 were generated by using the original ANN model coupled with SSA and WMRA in terms of two different means. Two daily flow series from different watersheds in China (Lushui and Daning) were used in six models for three prediction horizons (i.e., 1-, 2-, and 3-day-ahead forecast). The poor performance on ANN forecast models was mainly due to the existence of the lagged prediction. The ANN-MA, among six models, performed best and eradicated the lag effect. The performances from the ANN-SSA1 and ANN-SSA2 were similar, and the performances from the ANN-WMRA1 and ANN-WMRA2 were also similar. However, the models based on the SSA presented better performance than the models based on the WMRA at all forecast horizons, which meant that the SSA is more effective than the WMRA in improving the ANN performance in the current study. Based on an overall consideration including the model performance and the complexity of modeling, the ANN-MA model was optimal, then the ANN model coupled with SSA, and finally the ANN model coupled with WMRA.

  6. 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

  7. 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…

  8. Sedentary Behavior as a Daily Process Regulated by Habits and Intentions

    PubMed Central

    Conroy, David E.; Maher, Jaclyn P.; Elavsky, Steriani; Hyde, Amanda L.; Doerksen, Shawna E.

    2014-01-01

    Objective Sedentary behavior is a health risk but little is known about the motivational processes that regulate daily sedentary behavior. This study was designed to test a dual-process model of daily sedentary behavior, with an emphasis on the role of intentions and habits in regulating daily sedentary behavior. Methods College students (N = 128) self-reported on their habit strength for sitting and completed a 14-day ecological momentary assessment study that combined daily diaries for reporting motivation and behavior with ambulatory monitoring of sedentary behavior using accelerometers. Results Less than half of the variance in daily sedentary behavior was attributable to between-person differences. People with stronger sedentary habits reported more sedentary behavior on average. People whose intentions for limiting sedentary behavior were stronger, on average, exhibited less self-reported sedentary behavior (and marginally less monitored sedentary behavior). Daily deviations in those intentions were negatively associated with changes in daily sedentary behavior (i.e., stronger than usual intentions to limit sedentary behavior were associated with reduced sedentary behavior). Sedentary behavior also varied within-people as a function of concurrent physical activity, the day of week, and the day in the sequence of the monitoring period. Conclusions Sedentary behavior was regulated by both automatic and controlled motivational processes. Interventions should target both of these motivational processes to facilitate and maintain behavior change. Links between sedentary behavior and daily deviations in intentions also indicate the need for ongoing efforts to support controlled motivational processes on a daily basis. PMID:23477579

  9. Associations between daily chronic pain intensity, daily anger expression, and trait anger expressiveness: An ecological momentary assessment study

    PubMed Central

    Bruehl, Stephen; Liu, Xiaoxia; Burns, John W.; Chont, Melissa; Jamison, Robert N.

    2013-01-01

    Links between elevated trait anger expressiveness (anger-out) and greater chronic pain intensity are well documented, but pain-related effects of expressive behaviors actually used to regulate anger when it is experienced have been little explored. This study used ecological momentary assessment methods to explore prospective associations between daily behavioral anger expression and daily chronic pain intensity. Forty-eight chronic low back pain (LBP) patients and 36 healthy controls completed electronic diary ratings of momentary pain and behavioral anger expression in response to random prompts 4 times daily for 7 days. Across groups, greater trait anger-out was associated with greater daily behavioral anger expression (P < 0.001). LBP participants showed higher levels of daily anger expression than controls (P < 0.001). Generalized estimating equation analyses in the LBP group revealed a lagged main effect of greater behavioral anger expression on increased chronic pain intensity in the subsequent assessment period (P < 0.05). Examination of a trait × situation model for anger-out revealed prospective associations between elevated chronic pain intensity and later increases in behavioral anger expression that were restricted largely to individuals low in trait anger-out (P < 0.001). Trait × situation interactions for trait anger suppression (anger-in) indicated similar influences of pain intensity on subsequent behavioral anger expression occurring among low anger-in persons (P < 0.001). Overlap with trait and state negative affect did not account for study findings. This study for the first time documents lagged within-day influences of behavioral anger expression on subsequent chronic pain intensity. Trait anger regulation style may moderate associations between behavioral anger expression and chronic pain intensity. PMID:22940462

  10. 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.

  11. Extreme event statistics of daily rainfall: dynamical systems approach

    NASA Astrophysics Data System (ADS)

    Cigdem Yalcin, G.; Rabassa, Pau; Beck, Christian

    2016-04-01

    We analyse the probability densities of daily rainfall amounts at a variety of locations on Earth. The observed distributions of the amount of rainfall fit well to a q-exponential distribution with exponent q close to q≈ 1.3. We discuss possible reasons for the emergence of this power law. In contrast, the waiting time distribution between rainy days is observed to follow a near-exponential distribution. A careful investigation shows that a q-exponential with q≈ 1.05 yields the best fit of the data. A Poisson process where the rate fluctuates slightly in a superstatistical way is discussed as a possible model for this. We discuss the extreme value statistics for extreme daily rainfall, which can potentially lead to flooding. This is described by Fréchet distributions as the corresponding distributions of the amount of daily rainfall decay with a power law. Looking at extreme event statistics of waiting times between rainy days (leading to droughts for very long dry periods) we obtain from the observed near-exponential decay of waiting times extreme event statistics close to Gumbel distributions. We discuss superstatistical dynamical systems as simple models in this context.

  12. 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...

  13. Autobiographical memory and daily schemas at work.

    PubMed

    Eldridge, M A; Barnard, P J; Bekerian, D A

    1994-03-01

    This exploratory study examines how daily schemas for work activities influence retrospective memory. Twelve subjects were asked to describe their 'typical day' at work, and to recall their work activities of yesterday and of the same day a week ago. The number of basic activities occurring in each description was counted, and the number of basic activities occurring in the typical day description was viewed as an index of the degree of elaboration of the schema. There were three major findings. First, people recalled fewer activities from last week than they did from yesterday, and those activities that were recalled from last week tended to be those that were in the daily schema. Second, there was a tendency for people with highly elaborated daily schemas to recall more activities from last week than people with poorly elaborated schemas. And third, there were more schematic references in the recalls from last week than in those from yesterday. Taken together, these findings indicate that there are strong schematic influences on the recall of activities from last week, but not on those from yesterday. The discussion points to a number of research issues, both applied and theoretical, which arise from this preliminary investigation of daily work schemas. PMID:7584285

  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. 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...

  17. 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...

  18. 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...

  19. Super 7: Daily Exercises in Problem Solving.

    ERIC Educational Resources Information Center

    Hamilton, Octavia

    This book is a year-long program of daily exercises in problem solving for 2nd and 3rd grade students that presents 144 lessons, each with seven problems. The problems cover number sense, computation, measurements, geometry, problem solving, and patterns. The material is presented in a sequential fashion with concepts repeated and expanded, and…

  20. 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,…

  1. 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…

  2. Comparisons of measured and theoretical thermospheric daily composition variations

    NASA Technical Reports Server (NTRS)

    Kasprzak, W. T.; Newton, G. P.

    1976-01-01

    A comparison of the diurnal component of the daily variation in the neutral composition data from the San Marco 3 Nace (Neutral Atmospheric Composition Experiment) mass spectrometer at 220, 250, and 280 km, the OGO-6 model data at 450 km, rocket measurements of nitrogen between 140 and 300 km, and the two-constituent theoretical model of Mayr and Volland (1973) gives good agreement for molecular nitrogen and atomic oxygen. The Nace and rocket measurements overlap in altitude, and there is good agreement in the amplitude and phase of the diurnal and semidiurnal components for molecular nitrogen. The helium diurnal amplitude and phase of the theoretical model are in fair agreement with the Nace results, while the amplitude from the OGO-6 model at 450 km is much larger than the model predicts, a result suggesting that the OGO-6 model diurnal amplitude may be overestimated as the result of an incomplete separation of local-time and seasonal effects.

  3. Daily mortality and air pollution in The Netherlands.

    PubMed

    Hoek, G; Brunekreef, B; Verhoeff, A; van Wijnen, J; Fischer, P

    2000-08-01

    We studied the association of daily mortality with short-term variations in the ambient concentrations of major gaseous pollutants and PM in the Netherlands. The magnitude of the association in the four major urban areas was compared with that in the remainder of the country. Daily cause-specific mortality counts, air quality, temperature, relative humidity, and influenza data were obtained from 1986 to 1994. The relationship between daily mortality and air pollution was modeled using Poisson regression analysis. We adjusted for potential confounding due to long-term and seasonal trends, influenza epidemics, ambient temperature and relative humidity, day of the week, and holidays, using generalized additive models. Influenza episodes were associated with increased mortality up to 3 weeks later. Daily mortality was significantly associated with the concentration of all air pollutants. An increase in the PM10 concentration by 100 micrograms/m3 was associated with a relative risk (RR) of 1.02 for total mortality. The largest RRs were found for pneumonia deaths. Ozone had the most consistent, independent association with mortality. Particulate air pollution (e.g., PM10, black smoke [BS]) was not more consistently associated with mortality than were the gaseous pollutants SO2 and NO2. Aerosol SO4(-2), NO3-, and BS were more consistently associated with total mortality than was PM10. The RRs for all pollutants were substantially larger in the summer months than in the winter months. The RR of total mortality for PM10 was 1.10 for the summer and 1.03 for the winter. There was no consistent difference between RRs in the four major urban areas and the more rural areas. PMID:11002600

  4. 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.

  5. Daily precipitation fields from climate change scenarios for Switzerland

    NASA Astrophysics Data System (ADS)

    Keller, Denise E.; Fischer, Andreas M.; Liniger, Mark A.; Appenzeller, Christof; Knutti, Reto

    2013-04-01

    Regional climate models (RCM) are useful tools to generate physically and spatially consistent information about possible future climate change at a horizontal scale of several tens of kilometers. However, RCM data often suffer from substantial biases and in light of effective climate adaptation planning, their spatial scale is often too coarse to model the impact of climate change at the local scale. Ideally, probabilistic projections of potential future weather situations should be available locally and at least in daily resolution. Statistical downscaling approaches based on weather generators are particularly appealing to generate large ensembles of local scenarios with reduced mean biases in the control period. However, they often do not guarantee temporal and spatial coherence of the downscaled weather variables and the dependencies between them. The spatial coherence is of particular importance over climatologically heterogeneous topographies such as the Swiss Alps. To meet some of the manifold needs of the impact community, we explore here the potential of a statistical downscaling approach for precipitation that combines a multi-site weather generator (WG) with a conditional resampling approach. This hybrid approach aims at generating future daily precipitation fields for Switzerland based on RCM simulations (from ENSEMBLES) and gridded, high-quality and high-resolution (~2 km x 2 km) observational data from MeteoSwiss. We present the underlying concept of this approach which is to apply the multi-site WG to aggregated regions in Switzerland in order to generate daily wet-dry patterns. The analysis of observed transition probabilities reveals a large spatial, seasonal and interannual variability. In general, the latter exceeds those of space and season, including both sampling uncertainty and changes from one year to another. There is also a clear distinction between high-elevated regions and the lowlands. RCM simulations reproduce altitude- and season

  6. 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. PMID:26108151

  7. Daily living skills in individuals with autism spectrum disorder from 2 to 21 years of age

    PubMed Central

    Hus Bal, Vanessa; Kim, So-Hyun; Cheong, Daniel; Lord, Catherine

    2016-01-01

    Daily living skills (DLS), such as personal hygiene, meal preparation, and money management, are important to independent living. Research suggests that many individuals with autism spectrum disorder exhibit impairments in daily living skills relative to their cognitive skills. This study examined predictors of daily living skills attainment and trajectories of daily living skills in a longitudinal sample referred for possible autism spectrum disorder and followed from 2 to 21 years of age. Consistent with previous studies, participants with autism spectrum disorder and nonspectrum diagnoses showed continual development of daily living skills throughout childhood and adolescence. Early childhood nonverbal mental age was the strongest predictor of daily living skills attainment for both diagnostic groups. Group-based modeling suggested two distinct trajectories of daily living skills development for participants with autism spectrum disorder. Skill levels for both groups of young adults with autism spectrum disorder remained considerably below age level expectations. Whereas the “High-DLS” group gained approximately 12 years in daily living skills from T2 to T21, the “Low-DLS” group’s daily living skills improved 3–4 years over the 16- to 19-year study period. Nonverbal mental age, receptive language, and social-communication impairment at 2 years predicted High- versus Low-DLS group membership. Receiving greater than 20 h of parent-implemented intervention before age 3 was also associated with daily living skills trajectory. Results suggest that daily living skills should be a focus of treatment plans for individuals with autism spectrum disorder, particularly adolescents transitioning to young adulthood. PMID:25922445

  8. 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. PMID:24621335

  9. Recognition of Daily Gestures with Wearable Inertial Rings and Bracelets.

    PubMed

    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

  10. 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.

  11. Continuous Blood Pressure Monitoring in Daily Life

    NASA Astrophysics Data System (ADS)

    Lopez, Guillaume; Shuzo, Masaki; Ushida, Hiroyuki; Hidaka, Keita; Yanagimoto, Shintaro; Imai, Yasushi; Kosaka, Akio; Delaunay, Jean-Jacques; Yamada, Ichiro

    Continuous monitoring of blood pressure in daily life could improve early detection of cardiovascular disorders, as well as promoting healthcare. Conventional ambulatory blood pressure monitoring (ABPM) equipment can measure blood pressure at regular intervals for 24 hours, but is limited by long measuring time, low sampling rate, and constrained measuring posture. In this paper, we demonstrate a new method for continuous real-time measurement of blood pressure during daily activities. Our method is based on blood pressure estimation from pulse wave velocity (PWV) calculation, which formula we improved to take into account changes in the inner diameter of blood vessels. Blood pressure estimation results using our new method showed a greater precision of measured data during exercise, and a better accuracy than the conventional PWV method.

  12. 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.

  13. 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. PMID:25462037

  14. 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. PMID:23918373

  15. Intraindividual Coupling of Daily Stress and Cognition

    PubMed Central

    Sliwinski, Martin J.; Smyth, Joshua M.; Hofer, Scott M.; Stawski, Robert S.

    2010-01-01

    Most psychological theories predict associations among processes that transpire within individuals. However, these theories are often tested by examining relationships at the between-persons (BP) rather than the within-persons (WP) level. The authors examined the WP and BP relationships between daily stress and daily variability in cognitive performance. Daily stress and cognitive performance were assessed on 6 occasions in 108 older adults and 68 young adults. WP variability in stress predicted WP variability in response times (RTs) on a 2-back working memory task in both younger and older adults. That is, RTs were slower on high-stress days compared with low-stress days. There was evidence of an amplified WP stress effect in the older adults on a serial attention task. There was no evidence of stress effects on simple versions of these tasks that placed minimal demands on working memory. These results are consistent with theories that postulate that stress-related cognitive interference competes for attentional resources. PMID:16953716

  16. Tracking daily land surface albedo and reflectance anisotropy with moderate-resolution imaging spectroradiometer (MODIS)

    NASA Astrophysics Data System (ADS)

    Shuai, Yanmin

    A new algorithm provides daily values of land surface albedo and angular reflectance at a 500-m spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments currently in orbit on NASA's Terra and Aqua satellite platforms. To overcome the day-to-day variance in observed surface reflectance induced by differences in view and solar illumination angles, the algorithm uses the RossThickLiSparse-Reciprocal bidirectional reflectance model, which is fitted to all MODIS observations of a 500-m resolution cell acquired during a 16-day moving window. Individual observations are weighted by their quality, observation coverage, and proximity to the production date of interest. Product quality is measured by (1) the root mean square error (RMSE) of observations against the best model fit; and (2) the ability of the angular sampling pattern of the observations at hand to determine reflectance model parameters accurately. A regional analysis of model fits to data from selected MODIS data tiles establishes the bounds of these quality measures for application in the daily algorithm. The algorithm, which is now available to users of direct broadcast satellite data from MODIS, allows daily monitoring of rapid surface radiation and land surface change phenomena such as crop development and forest foliage cycles. In two demonstrations, the daily algorithm captured rapid change in plant phenology. The growth phases of a winter wheat crop, as monitored at the Yucheng agricultural research station in Yucheng, China, matched MODIS daily multispectral reflectance data very well, especially during the flowering and heading stages. The daily algorithm also captured the daily change in autumn leaf color in New England, documenting the ability of the algorithm to work well over large regions with varying degrees of cloud cover and atmospheric conditions. Daily surface albedos measured using ground-based instruments on towers at the agricultural and

  17. Simulation of mosquitoes population dynamic based on rainfall and average daily temperature

    NASA Astrophysics Data System (ADS)

    Widayani, H.; Seprianus, Nuraini, N.; Arum, J.

    2014-02-01

    This paper proposed rainfall and average daily temperature approximation functions using least square method with trigonometry polynomial. Error value from this method is better than Fast Fourier Transform method. This approximation is used to accommodate climatic factors into deterministic model of mosquitoes population by constructing a carrying capacity function which contains rainfall and average daily temperature functions. We develop a mathematical model for mosquitoes population dynamic which formulated by Yang et al (2010) with dynamic parameter of a daily rainfall as well as temperature on that model. Two fixed points, trivial and non-trivial, are obtained when constant entomological parameters assumed. Basic offspring number, Q0 as mosquitoes reproduction parameter is constructed. Non-trivial fixed point is stable if and only if Q0 > 1. Numerical simulation shown the dynamics of mosquitoes population significantly affected by rainfall and average daily temperature function.

  18. Daily spatiotemporal precipitation simulation using latent and transformed Gaussian processes

    NASA Astrophysics Data System (ADS)

    Kleiber, William; Katz, Richard W.; Rajagopalan, Balaji

    2012-01-01

    A daily stochastic spatiotemporal precipitation generator that yields spatially consistent gridded quantitative precipitation realizations is described. The methodology relies on a latent Gaussian process to drive precipitation occurrence and a probability integral transformed Gaussian process for intensity. At individual locations, the model reduces to a Markov chain for precipitation occurrence and a gamma distribution for precipitation intensity, allowing statistical parameters to be included in a generalized linear model framework. Statistical parameters are modeled as spatial Gaussian processes, which allows for interpolation to locations where there are no direct observations via kriging. One advantage of such a model for the statistical parameters is that stochastic generator parameters are immediately available at any location, with the ability to adapt to spatially varying precipitation characteristics. A second advantage is that parameter uncertainty, generally unavailable with deterministic interpolators, can be immediately quantified at all locations. The methodology is illustrated on two data sets, the first in Iowa and the second over the Pampas region of Argentina. In both examples, the method is able to capture the local and domain aggregated precipitation behavior fairly well at a wide range of time scales, including daily, monthly, and annually.

  19. 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.

  20. 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.

  1. Daily Associations among Anger Experience and Intimate Partner Aggression within Aggressive and Nonaggressive Community Couples

    PubMed Central

    Crane, Cory A.; Testa, Maria

    2014-01-01

    Anger is an empirically established precipitant to aggressive responding toward intimate partners. The current investigation examined the effects of anger, as experienced by both partners, as well as gender and previous aggression, on in vivo intimate partner aggression using a prospective daily diary methodology. Participants (N = 118 couples) individually provided 56 consecutive, daily reports of affective experience and partner aggression. Multilevel models were estimated using the Actor Partner Interdependence Model framework to analyze the daily associations between anger and partner aggression perpetration among male and female participants as moderated by aggression history. Results revealed that both Actor and Partner anger were generally associated with subsequently reported daily conflict. Further, increases in daily Partner anger were associated with corresponding increases in partner aggression among females who reported high anger and males, regardless of their own anger experience. Increases in Actor anger were associated with increases in daily partner aggression only among previously aggressive females. Previously aggressive males and females consistently reported greater perpetration than their nonaggressive counterparts on days of high Actor anger experience. Results emphasize the importance of both Actor and Partner factors in partner aggression and suggest that female anger may be a stronger predictor of both female-to-male and male-to-female partner aggression than male anger, when measured at the daily level. PMID:24866529

  2. 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.

  3. Detection of daily clouds on Titan.

    PubMed

    Griffith, C A; Hall, J L; Geballe, T R

    2000-10-20

    We have discovered frequent variations in the near-infrared spectrum of Titan, Saturn's largest moon, which are indicative of the daily presence of sparse clouds covering less than 1% of the area of the satellite. The thermodynamics of Titan's atmosphere and the clouds' altitudes suggest that convection governs their evolutions. Their short lives point to the presence of rain. We propose that Titan's atmosphere resembles Earth's, with clouds, rain, and an active weather cycle, driven by latent heat release from the primary condensible species. PMID:11039930

  4. 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).

  5. Daily boron intake from the American diet.

    PubMed

    Rainey, C J; Nyquist, L A; Christensen, R E; Strong, P L; Culver, B D; Coughlin, J R

    1999-03-01

    Interest in boron as a naturally occurring trace element nutrient from the food supply is increasing. Mounting evidence suggests that boron is essential to human beings. This study explores the major food and beverage contributors of boron and estimates of daily boron intake from the American diet. Previous estimates in the literature of dietary boron consumption are based on limited foods and population segments. In this study we provide a more comprehensive assessment of boron consumption by the US population. A boron nutrient database of 1,944 individual foods was developed. These foods represent 95.3% by weight of all foods consumed in the US Department of Agriculture 1989-1991 Continuing Survey of Food Intakes by Individuals (1989-1991 CSFII). The Boron Nutrient Database (version 1.0) was then linked to the 3-day food records of 11,009 respondents to the 1989-1991 CSFII to generate the average daily boron intake for each person. The weighted 5th percentile, median, mean, and 95th percentile boron intakes, respectively, are 0.43, 1.02, 1.17 and 2.42 mg/day for men; 0.33, 0.83, 0.96 and 1.94 mg/day for women; and 0.40, 0.86, 1.01 and 2.18 mg/day for pregnant women. For vegetarian adults, these intakes are 0.46, 1.30, 1.47 and 2.74 mg/day for men and 0.33, 1.00, 1.29 and 4.18 mg/day for women. The top 2 boron contributors, coffee and milk, are low in boron, yet they make up 12% of the total boron intake by virtue of the volume consumed. Among the top 50 boron contributors, peanut butter, wine, raisins, peanuts, and other nuts are high in boron. As more data become available on daily boron requirements, the results of this study may be used to assess whether Americans' daily intake of boron is adequate. PMID:10076586

  6. 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

  7. Borderline personality features and instability of daily negative affect and self-esteem.

    PubMed

    Tolpin, Laura Hochschild; Gunthert, Kathleen Cimbolic; Cohen, Lawrence H; O'Neill, Suzanne C

    2004-02-01

    We used a daily process design and multilevel modeling to examine the role of borderline personality features in the day-to-day stability of college students' negative affect and self-esteem and their reactivity to interpersonal stressors. At the end of each day for two weeks, students completed a checklist of daily stressors and measures of state affect and self-esteem. We predicted that high scores on a measure of borderline features would be related to more daily interpersonal stressors, greater negative affective and self-esteem reactivity to these stressors, and less day-to-day carryover of negative mood and self-esteem. The first and third hypotheses were supported, but not the second. The findings demonstrate the utility of a daily process methodology and multilevel modeling to study the day-to-day functioning of individuals with borderline features. PMID:14686886

  8. Daily albedo estimation and comparison to MCD43 product

    NASA Astrophysics Data System (ADS)

    Franch, B.; Vermote, E.; Sobrino, J. A.

    2013-12-01

    Land surface broadband albedo is among the main radiative uncertainties in current climate modelling. An accuracy requirement of 5% and a daily temporal resolution is suggested by the Global Climate Observing System for albedo characterization at spatial and temporal scales compatible with climate studies. Satellite remote sensing provides the only practical way of producing high-quality global albedo data sets with high spatial and temporal resolutions. For view-ilumination geometries such as Moderate Resolution Imaging Spectroradiometer (MODIS), in order to retrieve the Bidirectional Reflectance Distribution Function (BRDF) parameters and, consequently, the albedo, a period of sequential measurement is needed to accumulate sufficient observations. This is used to derive the MODIS BRDF/Albedo product (MCD43), which consider a composite period of 16 days with a resulting temporal resolution of 8 days. Looking for an improvement in the albedo temporal resolution that mitigated the assumption of a stable target, Vermote et al. (2009) presented the VJB method that assumes that the BRDF shape variations throughout a year are limited and linked to the Normalized Difference Vegetation Index (NDVI). This method retains the highest temporal resolution (daily, cloud cover permitting). The purpose of this work is to compare the MCD43 product with the VJB method through the albedo. Additionally, we present and study a method based on the VJB assumption, the 5param Rsqr. In this study we focus our analysis on daily MODIS CMG Collection 6 data from both Aqua and Terra satellites over Europe from 2002 until 2011. Figure 1 shows the percentage of the total RMSE of the VJB and the 5param Rsqr method against the MCD43 product. They display that southern latitudes present lower errors while they increase for northern latitudes and mountainous areas. Comparing the methods, the VJB presents errors higher than 15% in 8.2% of total land pixels while they suppose 6.9% of pixels when

  9. Air pollution and daily mortality in Shenyang, China

    SciTech Connect

    Xu, Z.; Yu, D.; Jing, L.; Xu, X.

    2000-04-01

    The authors analyzed daily mortality data in Shenyang, China, for calendar year 1992 to identify possible associations with ambient sulfur dioxide and total suspended particulates. Both total suspended particulate concentrations and sulfur dioxide concentrations far exceeded the World Health Organizations' recommended criteria. An average of 45.5 persons died each day. The lagged moving averages of air-pollution levels, calculated as the mean of the nonmissing air-pollution levels of the concurrent and 3 preceding days, were used for all analyses. Locally weighted regression analysis, including temperature, humidity, day of week, and a time variable, showed a positive association between daily mortality and both total suspended particulates and sulfur dioxide. When the authors included total suspended particulates and sulfur dioxide separately in the model, both were highly significant predictors of daily mortality. The risk of all-cause mortality increased by an estimated 1.7% and 2.4% with a 100-{micro}g/m{sup 3} concomitant increase in total suspended particulate and sulfur dioxide, respectively. When the authors analyzed mortality separately by cause of death, the association with total suspended particulates was significant for cardiovascular disease, but not statistically significant for chronic obstructive pulmonary diseases. In contrast, the association with sulfur dioxide was significant for chronic obstructive pulmonary diseases, but not for cardiovascular disease. The mortality from cancer was not associated significantly with total suspended particles or with sulfur dioxide. The correlation between sulfur dioxide and total suspended particulates was high. When the authors included sulfur dioxide and total suspended particulates simultaneously in the model, the association between total suspended particulates and mortality from all causes and cardiovascular diseases remained significant. Sulfur dioxide was associated significantly with increased

  10. 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

  11. Some considerations of periodicity and persistence in daily rainfalls

    NASA Astrophysics Data System (ADS)

    Kottegoda, N. T.; Natale, L.; Raiteri, E.

    2004-08-01

    In formulating mathematical models for the evaluation of variability in daily rainfalls, periodicity and persistence are two of the main characteristics to consider. We review periodogram analysis ranging from the Whittaker-Robinson technique to the Schuster periodogram and recent practices such as the modified Daniell window and the autoregressive and entropy spectra. We also reconsider models of the Markovian type of dependence and methods of analysis. The objective is to demonstrate useful practical procedures with the aid of relevant graphical displays. Results from periodograms not based on sinusoids are shown to complement the findings from more conventional methods. Periodicity in rainfall is less effective than in other related phenomena but has wide climatic variations. Preference for the familiar two-state first-order Markov model is reconfirmed with a two-harmonic representation of the seasonal variation in the Markov parameters. Rainfall data from Italy and Sri Lanka are used with observations of temperatures and flow for comparison.

  12. A nonparametric stochastic method for generating daily climate-adjusted streamflows

    NASA Astrophysics Data System (ADS)

    Stagge, J. H.; Moglen, G. E.

    2013-10-01

    A daily stochastic streamflow generation model is presented, which successfully replicates statistics of the historical streamflow record and can produce climate-adjusted daily time series. A monthly climate model relates general circulation model (GCM)-scale climate indicators to discrete climate-streamflow states, which in turn control parameters in a daily streamflow generation model. Daily flow is generated by a two-state (increasing/decreasing) Markov chain, with rising limb increments randomly sampled from a Weibull distribution and the falling limb modeled as exponential recession. When applied to the Potomac River, a 38,000 km2 basin in the Mid-Atlantic United States, the model reproduces the daily, monthly, and annual distribution and dynamics of the historical streamflow record, including extreme low flows. This method can be used as part of water resources planning, vulnerability, and adaptation studies and offers the advantage of a parsimonious model, requiring only a sufficiently long historical streamflow record and large-scale climate data. Simulation of Potomac streamflows subject to the Special Report on Emissions Scenarios (SRES) A1b, A2, and B1 emission scenarios predict a slight increase in mean annual flows over the next century, with the majority of this increase occurring during the winter and early spring. Conversely, mean summer flows are projected to decrease due to climate change, caused by a shift to shorter, more sporadic rain events. Date of the minimum annual flow is projected to shift 2-5 days earlier by the 2070-2099 period.

  13. Urinary excretion and daily intake rates of diethyl phthalate in the general Canadian population.

    PubMed

    Saravanabhavan, Gurusankar; Walker, Mike; Guay, Mireille; Aylward, Lesa

    2014-12-01

    We have analyzed the trends in the body-weight-adjusted urinary monoethyl phthalate (MEP) concentrations and the diethyl ethyl phthalate (DEP) daily intake estimates in the general Canadian population (aged 6-49 years) using the Canadian Health Measures Survey 2007-2009 dataset. The creatinine correction approach, as well as the urine volume approach in a simple one compartment model were used to calculate the daily urinary MEP excretion rates and DEP intake rates in individual survey participants. Using multiple regression models, we have estimated least square geometric means (LSGMs) of body-weight-adjusted MEP concentration, daily excretion and intake rates among different age groups and sex. We observed that body weight affects the trends in the MEP concentrations significantly among children (aged 6-11 years), adolescents (aged 12-19 years) and adults (aged 20-49 years). The body-weight-adjusted MEP concentrations in children were significantly higher than those in adults. On the other hand the DEP daily intakes in children were significantly lower than those in adults. We did not observe any differences in the DEP daily intake rates between males and females. Although the urinary MEP concentrations are correlated well with DEP daily intake estimates in the overall population, one should be cautious when directly using the urinary concentrations to compare the intake trends in the sub-populations (e.g. children vs. adults) as these trends are governed by additional physiological factors. The DEP daily intake calculated using the creatinine approach and that using the urine volume approach were similar to each other. The estimated geometric mean and 95th percentile of DEP daily intake in the general Canadian population are 2 and 20 μg/kg-bw/day, respectively. These daily intake estimates are significantly lower than the US Environmental Protection Agency's oral reference dose of 800 μg/kg-bw/day. PMID:25217994

  14. Multivariate Non-Parametric Simulation of Daily Streamflows Considering Climate Change

    NASA Astrophysics Data System (ADS)

    Haberlandt, U.

    2014-12-01

    For the optimal planning and derivation of operation rules for multi-purpose reservoir systems very long time series of daily streamflows are required. Stochastic streamflow models can provide these data. While stochastic generation of monthly time series is state of the art, the synthesis of daily flows at multiple sites is still a challenging task. Recently, nonparametric k - nearest neighbor resampling techniques have been applied successfully for the generation of daily streamflows at multiple sites. The objective of this study to employ k-nn resampling for the simulation of multivariate daily streamflows under changed climate conditions. Observed daily streamflows are resampled conditioned on observed and simulated climate variables from regional climate models considering past and future scenarios. The resampling is done in a three step-procedure: 1) seasonal flows for an index station representing the flow sum over all considered gauges are generated; 2) the flow sum is spatially disaggregated by resampling station flow proportions from observed data; 3) the individual seasonal flows for all gauges are temporally disaggregated to daily data by resampling daily flow proportions. The method is applied for a reservoir system in the Harz mountains in Germany comprising five streamflow gauges with long daily observations. Climate data from observations and from the regional climate models REMO and WETTREG are used for conditioning. The method is parsimonious, easy to understand and very fast. It simulates all observed statistics well and provides significant change signals concerning future flows. Problems are the restricted ability of the technique to model values not seen in the observations, which concern on one hand single extreme values and possible future flow sequences not yet observed.

  15. Daily Rhythms in Mobile Telephone Communication.

    PubMed

    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

  16. [Daily difficulties associated with full conventional dentures].

    PubMed

    Machado, Flávia Christiane de Azevedo; da Costa, Anna Paula Serêjo; Pontes, Anna Lepríncia Bezerra; Lima, Kenio Costa; Ferreira, Maria Ângela Fernandes

    2013-10-01

    The effectiveness of health services can be evaluated from the quality of life (QOL) standpoint. Thus, this study evaluated rehabilitation services using full conventional dentures (FCD) of Specialized Dental Care Centers (SDCC) in Rio Grande do Norte (RN) regarding daily difficulties associated with these dentures made between 2007 and 2009. A cross-sectional study was conducted with 138 users of these FCD, collecting data by clinical examination and a questionnaire based on the Oral Impacts on Daily Performances index. The Fisher and chi-square tests were used to test the association between the variables. The result was that 42% of users reported difficulties in executing oral activities due to FCDs. These difficulties were more frequent and intense in the activities of eating, speaking and smiling. In general, 58.7% of users did not have functional teeth. In relation to the clinical evaluation of FCDs, 57.2% of upper and 9.2% of lower FCDs were satisfactory. There was an association between difficulty and the absence of functional teeth, but not with inadequate FCDs. Thus, the SDCCs were effective in upper FCD rehabilitation, since the difficulties encountered are within the standard limitations of this type of rehabilitation. On the other hand, the cost-benefit of rehabilitation of lower FCDs must be evaluated. PMID:24061036

  17. 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

  18. Choline magnesium trisalicylate: comparative pharmacokinetic study of once-daily and twice-daily dosages.

    PubMed

    Levitt, M J; Kann, J

    1984-07-01

    This randomized crossover study compared the pharmacokinetics of choline magnesium trisalicylate tablets administered once daily (3000 mg of salicylate) or twice daily (1500 mg of salicylate) for six d. Serum salicylate levels were measured by HPLC. Mean "trough" concentrations fell within the therapeutic range (5-30 mg/dL) with either regimen and were relatively constant, indicating that the steady state had been reached. The 24-h area under the salicylate curve (AUC0-24 h) after the final 3000-mg salicylate dose averaged about twice the mean 12-h AUC after the last 1500-mg dose, indicating that the two dosing regimens were equally bioavailable. Clinical observations and results of laboratory safety studies indicate that both dosage schedules of the drug are well tolerated. The present findings support the once-daily therapeutic use of choline magnesium trisalicylate. PMID:6470965

  19. MOS correction of GCM- and RCM-simulated daily precipitation

    NASA Astrophysics Data System (ADS)

    Eden, Jonathan; Widmann, Martin; Wong, Geraldine; Maraun, Douglas; Vrac, Mathieu; Kent, Thomas

    2013-04-01

    Understanding long-term changes in daily precipitation characteristics, particularly those associated with extreme events, is an important component of climate change science and impact assessment. Estimates of such changes are required at local scales where impacts are most keenly felt. However, the limited spatial resolution of General Circulation Models (GCMs) makes direct estimates of future daily precipitation unrealistic. A popular downscaling approach is to use GCMs to drive high-resolution Regional Climate Models (RCMs). Whilst able to simulate precipitation characteristics at smaller scales, RCMs do not represent local variables and remain limited by systematic errors and biases. It is possible to apply statistical corrections, known as Model Output Statistics (MOS), to RCM-simulated precipitation. The simplest form of MOS (including bias correction) follows a 'distribution-wise' approach in which the statistical link is derived between long-term distributions of simulated and observed variables. However, more sophisticated MOS methods may be performed 'event-wise' using, for example, multiple linear regression to derive links between simulated and observed sequences of day-to-day weather. This approach requires a fitting period in which the simulated temporal evolution of large-scale weather states matches that of the real world and is thus limited to either reanalysis-driven RCMs or nudged GCM simulations. It is unclear to what extent MOS can be used to correct daily precipitation directly from GCMs, thus removing the computationally challenging RCM step from the downscaling process. Here, we present and cross-validate a stochastic, event-wise MOS method for both GCM- and RCM-simulated precipitation. A 'mixture' model, combining gamma and generalised Pareto distributions, is used to represent the complete (extreme and non-extreme) precipitation distribution. This is combined with a vector generalised linear model (VGLM) in order to estimate the

  20. Productive and counterproductive job crafting: A daily diary study.

    PubMed

    Demerouti, Evangelia; Bakker, Arnold B; Halbesleben, Jonathon R B

    2015-10-01

    The present study aims to uncover the way daily job crafting influences daily job performance (i.e., task performance, altruism, and counterproductive work behavior). Job crafting was conceptualized as "seeking resources," "seeking challenges," and "reducing demands" and viewed as strategies individuals use to optimize their job characteristics. We hypothesized that daily job crafting relates to daily job demands and resources (work pressure and autonomy), which consequently relate to daily work engagement and exhaustion and ultimately to job performance. A sample of 95 employees filled in a quantitative diary for 5 consecutive working days (n occasions = 475). We predicted and found that daily seeking resources was positively associated with daily task performance because daily autonomy and work engagement increased. In contrast, daily reducing demands was detrimental for daily task performance and altruism, because employees lower their daily workload and consequently their engagement and exhaustion, respectively. Only daily seeking challenges was positively (rather than negatively) associated with daily counterproductive behavior. We conclude that employee job crafting can have both beneficial and detrimental effects on job performance. PMID:25798721

  1. 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

  2. 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

    Cohn, Amy; Hagman, Brett T; Moore, Kathleen; Mitchell, Jessica; Ehlke, Sarah

    2014-03-01

    The negative reinforcement model of addiction posits that individuals may use alcohol to reduce 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. Furthermore, 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 subtypes of female rape victims. PMID:24731112

  3. 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

  4. The Role of Daily Activities in Youths’ Stress Physiology

    PubMed Central

    McHale, Susan M.; Blocklin, Michelle K.; Walter, Kimberly N.; Davis, Kelly D.; Almeida, David M.; Klein, Laura Cousino

    2012-01-01

    Purpose This study examined links between diurnal patterns of the stress hormone, cortisol, and adolescents’ time in nine common daily activities. Method During eight consecutive nightly telephone interviews, 28 youths (n = 12 girls), 10-18 years of age, reported their day’s activities. On four days, four saliva samples also were collected and assayed for cortisol. Multilevel models assessed within- and between-person associations between time in each activity and cortisol Area Under the Curve (AUC), cortisol awakening response (CAR), morning peak (30 minutes after wake up) and daily decline (morning peak to bedtime). Results Links with AUC were found for most activities; significant associations with cortisol rhythms suggested that most effects were due to anticipation of the day’s activities. Specifically, on days when youths spent more time than usual on videogames and TV they had lower AUCs, with lower morning peaks. Youths who spent more time reading (within-person) and in computer activities (between-person) had higher AUCs, with stronger CARs (within-person). Youths who slept more had lower AUCs, with lower morning peaks on both the between- and within-person levels. Amounts of time spent in clubs, and for older adolescents, sports, were also linked to lower AUCs. Finally, youths who spent more time in school/schoolwork had lower AUCs, but on days when youths spent more time than usual in school, they had higher AUCs, stronger CARs, and steeper daily declines. Conclusion Beyond their known implications for psychological adjustment, youths’ everyday activities are linked to stress physiology. PMID:23174474

  5. 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

  6. The Revised Observed Tasks of Daily Living

    PubMed Central

    Diehl, Manfred; Marsiske, Michael; Horgas, Ann L.; Rosenberg, Adrienne; Saczynski, Jane S.; Willis, Sherry L.

    2007-01-01

    The Revised Observed Tasks of Daily Living (OTDL-R), a performance-based test of everyday problem solving, was administered to a sample of community-dwelling older adults. The OTDL-R included nine tasks, representing medication use, telephone use, and financial management. The OTDL-R had a desirable range of difficulty and satisfactory internal consistency and showed a relatively invariant pattern of relations between measured tasks and the underlying latent dimensions they represent across White and non-White subsamples. The OTDL-R also correlated significantly with age, education, self-rated health, a paper-and-pencil measure of everyday problem solving, and measures of basic cognitive functioning. Thus, the OTDL-R is a reliable and valid objective measure of everyday problem solving that has great practical utility for assessing performance in diverse populations. PMID:18160968

  7. Climatology: Contrails reduce daily temperature range

    NASA Astrophysics Data System (ADS)

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

    2002-08-01

    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.

  8. Thermoluminescence sensitivity of daily-use materials

    NASA Astrophysics Data System (ADS)

    Correcher, V.; Garcia-Guinea, J.; Rivera, T.

    The thermoluminescence (TL) response of silicon-rich daily-use materials, namely charoite (silicate gemstone), Spanish dental crown, phone chip and Spanish glass has been investigated. All the samples previously characterised by means of X-ray diffraction, electron microscopy associated with energy-dispersion and wavelength-dispersive spectrometry and X-ray fluorescence exhibit a reasonable sensitivity to ionising radiation. The preliminary results, based on their TL properties, allow us to speculate that these materials could be potentially of interest in situations where conventional dosimetric systems are not available. The dose dependence of the 400 nm TL emission of the studied samples displays a very good linearity in the range of 0.1-10 Gy.

  9. The magnetosphere of Neptune - Its response to daily rotation

    NASA Technical Reports Server (NTRS)

    Voigt, Gerd-Hannes; Ness, Norman F.

    1990-01-01

    The Neptunian magnetosphere periodically changes every eight hours between a pole-on magnetosphere with only one polar cusp and an earth-type magnetosphere with two polar cusps. In the pole-on configuration, the tail current sheet has an almost circular shape with plasma currents closing entirely within the magnetosphere. Eight hours later the tail current sheet assumes an almost flat shape with plasma currents touching the magnetotail boundary and closing over the tail magnetopause. Magnetic field and tail current sheet configurations have been calculated in a three-dimensional model, but the plasma- and thermodynamic conditions were investigated in a simplified two-dimensional MHD equilibrium magnetosphere. It was found that the free energy in the tail region of the two-dimensional model becomes independent of the dipole tilt angle. It is conjectured that the Neptunian magnetotail might assume quasi-static equilibrium states that make the free energy of the system independent of its daily rotation.

  10. 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.

  11. Verification of factors to estimate daily milk yield from one milking of cows milked twice daily

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The objective of this research was to verify factors to predict daily milk yield when milk is sampled once per d for cows milked twice (2x) per d. Milk weights for both milkings were recorded automatically by 30 herds and collected by Dairy Herd Improvement supervisors. Data was split into 2 subsets...

  12. 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…

  13. 27 CFR 19.732 - Details of daily records.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Details of daily records. 19.732 Section 19.732 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU, DEPARTMENT OF THE TREASURY LIQUORS DISTILLED SPIRITS PLANTS Records and Reports Records § 19.732 Details of daily records. The daily...

  14. 20 CFR 330.3 - Daily rate of compensation.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 20 Employees' Benefits 1 2013-04-01 2012-04-01 true 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....

  15. 27 CFR 19.736 - Daily production records.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Daily production records..., DEPARTMENT OF THE TREASURY LIQUORS DISTILLED SPIRITS PLANTS Records and Reports Production Account § 19.736 Daily production records. (a) Spirits production. Each proprietor shall maintain daily...

  16. 1 CFR 6.1 - Index to daily issues.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 1 General Provisions 1 2013-01-01 2012-01-01 true 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. 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...

  18. 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....

  19. 1 CFR 6.3 - Daily lists of parts affected.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 1 General Provisions 1 2013-01-01 2012-01-01 true 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...

  20. 1 CFR 6.1 - Index to daily issues.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 1 General Provisions 1 2012-01-01 2012-01-01 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....

  1. 1 CFR 6.3 - Daily lists of parts affected.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 1 General Provisions 1 2012-01-01 2012-01-01 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...

  2. 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...

  3. 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....

  4. 1 CFR 6.3 - Daily lists of parts affected.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 1 General Provisions 1 2014-01-01 2012-01-01 true 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...

  5. 1 CFR 6.1 - Index to daily issues.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 1 General Provisions 1 2014-01-01 2012-01-01 true 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....

  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. PMID:26356659

  7. 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.

  8. 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

  9. A space and time scale-dependent nonlinear geostatistical approach for downscaling daily precipitation and temperature

    NASA Astrophysics Data System (ADS)

    Jha, Sanjeev Kumar; Mariethoz, Gregoire; Evans, Jason; McCabe, Matthew F.; Sharma, Ashish

    2015-08-01

    A geostatistical framework is proposed to downscale daily precipitation and temperature. The methodology is based on multiple-point geostatistics (MPS), where a multivariate training image is used to represent the spatial relationship between daily precipitation and daily temperature over several years. Here the training image consists of daily rainfall and temperature outputs from the Weather Research and Forecasting (WRF) model at 50 and 10 km resolution for a 20 year period ranging from 1985 to 2004. The data are used to predict downscaled climate variables for the year 2005. The result, for each downscaled pixel, is daily time series of precipitation and temperature that are spatially dependent. Comparison of predicted precipitation and temperature against a reference data set indicates that both the seasonal average climate response together with the temporal variability are well reproduced. The explicit inclusion of time dependence is explored by considering the climate properties of the previous day as an additional variable. Comparison of simulations with and without inclusion of time dependence shows that the temporal dependence only slightly improves the daily prediction because the temporal variability is already well represented in the conditioning data. Overall, the study shows that the multiple-point geostatistics approach is an efficient tool to be used for statistical downscaling to obtain local-scale estimates of precipitation and temperature from General Circulation Models.

  10. A global survey on the seasonal variation of the marginal distribution of daily precipitation

    NASA Astrophysics Data System (ADS)

    Papalexiou, Simon Michael; Koutsoyiannis, Demetris

    2016-08-01

    To characterize the seasonal variation of the marginal distribution of daily precipitation, it is important to find which statistical characteristics of daily precipitation actually vary the most from month-to-month and which could be regarded to be invariant. Relevant to the latter issue is the question whether there is a single model capable to describe effectively the nonzero daily precipitation for every month worldwide. To study these questions we introduce and apply a novel test for seasonal variation (SV-Test) and explore the performance of two flexible distributions in a massive analysis of approximately 170,000 monthly daily precipitation records at more than 14,000 stations from all over the globe. The analysis indicates that: (a) the shape characteristics of the marginal distribution of daily precipitation, generally, vary over the months, (b) commonly used distributions such as the Exponential, Gamma, Weibull, Lognormal, and the Pareto, are incapable to describe "universally" the daily precipitation, (c) exponential-tail distributions like the Exponential, mixed Exponentials or the Gamma can severely underestimate the magnitude of extreme events and thus may be a wrong choice, and (d) the Burr type XII and the Generalized Gamma distributions are two good models, with the latter performing exceptionally well.

  11. Evaluating the Adequacy of Simulating Maximum and Minimum Daily Air Temperature with the Normal Distribution.

    NASA Astrophysics Data System (ADS)

    Harmel, R. D.; Richardson, C. W.; Hanson, C. L.; Johnson, G. L.

    2002-07-01

    Weather simulation models are commonly used to generate synthetic daily weather for use in studies of crop growth, water quality, water availability, soil erosion, climate change, and so on. Synthetic weather sequences are needed if long-term measured data are not available, measured data contain missing records, collection of actual data is cost or time prohibitive, or when necessary to simulate impacts of future climate scenarios. Most weather generators are capable of producing one or more components of weather such as precipitation, temperature, solar radiation, humidity, and wind speed. This study focused on one generation component, the procedure commonly used by weather simulation models to generate daily maximum and minimum temperature. The normal distribution is used by most weather generators (including USCLIMATE, WXGEN, LARS-WG, CLIMGEN, and CLIGEN) to generate daily maximum and minimum temperature values. The objective of this study was to analyze the adequacy of generating temperature data from the normal distribution. To accomplish this objective, the assumption of normality in measured daily temperatures was evaluated by testing the hypothesis that daily minimum and maximum temperature are normally distributed for each month. In addition, synthetic temperature records generated with the normal distribution were compared with measured temperature records. Based on these analyses, it was determined that measured daily maximum and minimum temperature are generally not normally distributed in each month but often are slightly skewed, which contradicts the assumption of normality used by most weather generators. In addition, generating temperature from the normal distribution resulted in several physically improbable values.

  12. Effectiveness of daily versus non-daily granulocyte colony-stimulating factors in patients with solid tumours undergoing chemotherapy: a multivariate analysis of data from current practice

    PubMed Central

    Almenar Cubells, D; Bosch Roig, C; Jiménez Orozco, E; Álvarez, R; Cuervo, JM; Díaz Fernández, N; Sánchez Heras, AB; Galán Brotons, A; Giner Marco, V; Codes M De Villena, M

    2013-01-01

    We conducted a multicentre, retrospective, observational study including patients with solid tumours (excluding breast cancer) that received granulocyte colony-stimulating factors (G-CSF) and chemotherapy. We investigated the effectiveness of daily vs. non-daily G-CSFs (pegfilgrastim) adjusting by potential confounders. The study included 391 patients (211 daily G-CSF; 180 pegfilgrastim), from whom 47.3% received primary prophylaxis (PP) (57.8% pegfilgrastim), 26.3% secondary prophylaxis (SP: initiation after cycle 1 and no reactive treatment in any cycle) (51.5% pegfilgrastim) and 26.3% reactive treatment (19.4% pegfilgrastim). Only 42.2% of patients with daily G-CSF and 46.2% with pegfilgrastim initiated prophylaxis within 72 h after chemotherapy, and only 10.5% of patients with daily G-CSF received it for ≥7 days. In the multivariate models, daily G-CSF was associated with higher risk of grade 3-4 neutropenia (G3-4N) vs. pegfilgrastim [odds ratio (OR): 1.73, 95% confidence interval (CI): 1.004–2.97]. Relative to SP, PP protected against G3-4N (OR for SP vs. PP: 6.0, 95%CI: 3.2–11.4) and febrile neutropenia (OR: 3.1, 95%CI: 1.1–8.8), and was associated to less chemotherapy dose delays and reductions (OR for relative dose intensity <85% for SP vs. PP: 3.1, 95%CI: 1.7–5.4) and higher response rate (OR: 2.1, 95%CI: 1.2–3.7). Data suggest that pegfilgrastim, compared with a daily G-CSF, and PP, compared with SP, could be more effective in preventing neutropenia and its related events in the clinical practice. PMID:23331323

  13. 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

  14. 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.

  15. 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

  16. Reactivity to stressor pile-up in adulthood: effects on daily negative and positive affect.

    PubMed

    Schilling, Oliver K; Diehl, Manfred

    2014-03-01

    This study used data from a 30-day diary study with 289 adults (age range 18-89 years) to model the effects of stressor pile-up on individuals' daily negative affect (NA) and positive affect (PA) and to test for age differences in these effects. Specifically, we developed a new approach to operationalize and model stressor pile-up and evaluated this approach using generalized mixed models, taking into account the gamma response distribution of the highly skewed daily NA data. Findings showed that pile-up of stressors over a 1-week period was significantly coupled with increases in individuals' daily NA above and beyond the effect of concurrent stressors. Findings also showed that the effects of stressor accumulation and concurrent stress were additive rather than multiplicative. Age interacted significantly with stressor accumulation so that a higher age was associated with less NA reactivity to stressor pile-up. Yet, we did not find such an age-related association for NA reactivity to concurrent daily stressors. Daily PA was not associated with daily stress or with stressor pile-up. The operational definition of stressor pile-up presented in this study contributes to the literature by providing a new approach to model the dynamic effects of stress, and by providing new ways of separating the effects of acute stressors from the effects of stressor pile-up. The age differences found in the present study suggest that older adults develop effective emotion regulation skills for handling stressor pile-up, but that they react to acute daily stressors in a similar way than younger adults. PMID:24660797

  17. Daily mood-drinking slopes as predictors: a new take on drinking motives and related outcomes.

    PubMed

    Mohr, Cynthia D; Brannan, Debi; Wendt, Staci; Jacobs, Laurie; Wright, Robert; Wang, Mo

    2013-12-01

    Motivational models of alcohol consumption have articulated the manner in which positive and negative experiences motivate drinking in unique social contexts (e.g., M. L. Cooper, M. R. Frone, M. Russell & P. Mudar, 1995, Drinking to regulate positive and negative emotions: A motivational model of alcohol use, Journal of Personality and Social Psychology, Vol. 69, pp. 990-1005). 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 by employing a daily-process study of nonclinical 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 hierarchical linear modeling 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 but 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 brief Michigan Alcoholism Screening Test scores

  18. Improving daily water yield estimates in the Little River Watershed: SWAT adjustments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Researchers are assessing the beneficial effects of conservation practices on water quality with hydrologic models. The assessments depend heavily on accurate simulation of water yield. This study was conducted to improve Soil and Water Assessment Tool (SWAT) hydrologic model daily water yield est...

  19. Investigation of daily covering material for biocells

    NASA Astrophysics Data System (ADS)

    Bendere, R.; Smigins, R.; Medne, O.; Berzina-Cimdina, L.; Rugele, K.

    2014-02-01

    Bioreactor landfilling, with the acceptance of landfill Directive 1999/31/EC has lost its actuality in European Union; at the same time, this method can still be used for acceleration of biowaste degradation and biogas production. One of the possibilities to reduce the disposal of biowaste is to use biocells for its anaerobic pre-treatment before landfilling. The daily filling up of such a cell requires isolation of the main volume to limit gas emissions, reduce smells, etc. Bioprocesses that are of the utmost importance for biocell treatment are often not taken into account in selection of materials to be used as daily landfill covers. Based on physical, chemical and biological methods the investigations have been carried out into different covering materials offered in the market, with identification of parameters that are the most important for daily covering the biocells. It is found that the materials fitted best this purpose should be of biological origin and consist of small bio-particles with large surface, without the inhibitors of anaerobic processes such as sulphuric compounds. Bioreaktoru pielietošana atkritumu uzglabāšanas sfērā, sakarā ar Direktīvas 1999/31/EC pieņemšanu, ir zaudējusi savu aktualitāti, taču šī metode vēl joprojām var tikt izmantota bioatkritumu noārdīšanai un biogāzes ražošanai. Viena no iespējām kā samazināt bioatkritumu izvietošanu ir biošūnu izmantošana bioatkritumu anaerobai pirmsapstrādei pirms to noglabāšanas. Šūnas piepildīšana ikdienā prasa nepieciešamību izolēt lielāko tās daļu, lai samazinātu gāzes emisiju, smakas, utt. Materiāli, kas ikdienā tiek izmantoti atkritumu pārklāšanai, nepietiekami ietekmē bioprocesus, kas pamatā ir galvenais biošūnas izmantošanas mērķis. Šajā sakarā ir veikta dažādu tirdzniecībā pieejamu pārklājuma materiālu izpēte, pielietojot virkni fizikālo, ķīmisko un bioloģisko metožu, un nosakot svarīgākos parametrus, kas ir b

  20. An approach for the forecasting of wind strength tailored to routine observational daily wind gust data

    NASA Astrophysics Data System (ADS)

    Valero, F.; Pascual, A.; Martín, M. L.

    2014-02-01

    Daily wind gusts observed over Spain have been estimated by means of the statistical downscaling analogue model ANPAF developed by the authors. The model diagnoses large-scale atmospheric circulation patterns and subsequently estimates wind probabilities. Several data sets have been used: daily 1000 geopotential height (Z1000) field over the North Atlantic and the observational daily wind gust (WGU). Next, to give an additional value to the ERA-Interim wind gust data base (ERI), wind gust estimations from the analogue model were obtained to compare them with the wind gust data set from the ERA-Interim. The analogue method is based on finding in the historic geopotential height data base, a principal component subset of geopotential height patterns that are the most akin to a geopotential height pattern used as an input. Then, once the analogues are determined associated wind gusts are estimated from them.

  1. 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.

  2. Evaluation of the effect-duration of once-daily enalapril compared with once-daily captopril.

    PubMed

    Germanò, G; Damiani, S; Germanò, U; Pecchioli, V; Pica, B; Antonini, P

    1990-01-01

    The extent and duration of the antihypertensive effect of enalapril and captopril, both given once daily, were evaluated in 12 mild-to-moderate essential hypertensives by 24-hour noninvasive blood pressure (BP) monitoring (Pressurometer IV-mod 1990-1991, Del Mar Avionics). Patients were randomized to a cross-over regimen either with enalapril, 10-20 mg, followed by captopril, 50-100 mg (first group), or with captopril followed by enalapril (second group). The dose was doubled if, at week 3 of each treatment, the diastolic BP remained at 90 mm Hg. Doubling of the 2 drugs was not required in 4 patients; in 7 patients the dose of both drugs was doubled; and in 1 patient the dose of only captopril was doubled. Two of the 7 patients who required doubling of both drugs were considered nonresponders to enalapril and captopril. The circadian rhythm was not altered by the treatments, and the drugs reduced BP mainly during the waking hours. However, the second peak of systolic BP in the late afternoon did not graphically appear to be modified by captopril administration. A periodic asymmetric model with 3 harmonics analysis carried out on 24-hour BP data justifies only the use of enalapril for once-daily administration. PMID:2189075

  3. Hibernation and daily torpor minimize mammalian extinctions

    NASA Astrophysics Data System (ADS)

    Geiser, Fritz; Turbill, Christopher

    2009-10-01

    Small mammals appear to be less vulnerable to extinction than large species, but the underlying reasons are poorly understood. Here, we provide evidence that almost all (93.5%) of 61 recently extinct mammal species were homeothermic, maintaining a constant high body temperature and thus energy expenditure, which demands a high intake of food, long foraging times, and thus exposure to predators. In contrast, only 6.5% of extinct mammals were likely heterothermic and employed multi-day torpor (hibernation) or daily torpor, even though torpor is widespread within more than half of all mammalian orders. Torpor is characterized by substantial reductions of body temperature and energy expenditure and enhances survival during adverse conditions by minimizing food and water requirements, and consequently reduces foraging requirements and exposure to predators. Moreover, because life span is generally longer in heterothermic mammals than in related homeotherms, heterotherms can employ a ‘sit-and-wait’ strategy to withstand adverse periods and then repopulate when circumstances improve. Thus, torpor is a crucial but hitherto unappreciated attribute of small mammals for avoiding extinction. Many opportunistic heterothermic species, because of their plastic energetic requirements, may also stand a better chance of future survival than homeothermic species in the face of greater climatic extremes and changes in environmental conditions caused by global warming.

  4. Egocentric daily activity recognition via multitask clustering.

    PubMed

    Yan, Yan; Ricci, Elisa; Liu, Gaowen; Sebe, Nicu

    2015-10-01

    Recognizing human activities from videos is a fundamental research problem in computer vision. Recently, there has been a growing interest in analyzing human behavior from data collected with wearable cameras. First-person cameras continuously record several hours of their wearers' life. To cope with this vast amount of unlabeled and heterogeneous data, novel algorithmic solutions are required. In this paper, we propose a multitask clustering framework for activity of daily living analysis from visual data gathered from wearable cameras. Our intuition is that, even if the data are not annotated, it is possible to exploit the fact that the tasks of recognizing everyday activities of multiple individuals are related, since typically people perform the same actions in similar environments, e.g., people working in an office often read and write documents). In our framework, rather than clustering data from different users separately, we propose to look for clustering partitions which are coherent among related tasks. In particular, two novel multitask clustering algorithms, derived from a common optimization problem, are introduced. Our experimental evaluation, conducted both on synthetic data and on publicly available first-person vision data sets, shows that the proposed approach outperforms several single-task and multitask learning methods. PMID:26067371

  5. 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

  6. 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.

  7. 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. PMID:25212526

  8. Spatial analysis of daily rainfall intensity and concentration index in Peninsular Malaysia

    NASA Astrophysics Data System (ADS)

    Suhaila, Jamaludin; Jemain, Abdul Aziz

    2012-04-01

    This study presents the spatial analysis of daily rainfall intensity and concentration index over Peninsular Malaysia. Daily rainfall data from 50 rainfall stations are used in this study. Due to the limited number of stations, the geostatistical method of ordinary kriging is used to compute the values of daily rainfall concentration and intensity and to map their spatial distribution. The resultant analysis of rainfall concentration indicated that the distribution of daily rainfall is more regular over the west, northwest and southwest regions compared to the east. Large areas of the eastern Peninsula display an irregularity in distribution of daily rainfall. In terms of number of rainy days, analysis of daily rainfall confirms that a large number of rainy days across the Peninsula arise from low-intensity events but only contribute a small percentage of total rain. On the other hand, a low frequency of rainy days with high-intensity events contributes the largest percentage of total rain. The results indicated that the total rain in eastern areas is mainly contributed by the high-intensity events. This finding explains the occurrence of a large number of floods and soil erosions in these areas. Therefore, precautionary measures should be taken earlier to prevent any massive destruction of property and loss of life due to the hazards. These research findings are of considerable importance in providing enough information to water resource management, climatologists and agriculturists as well as hydrologists for planning their activities and modelling processes.

  9. Analysis of daily rainfall processes in lower extremadura (Spain) and homogenization of the data

    NASA Astrophysics Data System (ADS)

    Garcia, J. A.; Marroquin, A.; Garrido, J.; Mateos, V. L.

    1995-03-01

    In this paper we analyze, from the point of view of stochastic processes, daily rainfall data recorded at the Badajoz Observatory (Southwestern Spain) since the beginning of the century. We attempt to identify any periodicities or trends in the daily rainfall occurrences and their dependence structure, and attempt to select the appropriate point stochastic model for the daily rainfall series. Standard regression analysis, graphical methods and the Cramer statistic show a rise in the number of cases of light rain (between 0.1 and 5 mm/d) and a decline in the number of cases of moderate to heavy rain (> 5 mm/d) in the daily rainfall at least at the 5% significance level. That the homogenization process was satisfactory is shown by the mean interarrival time of the homogenized series and the test of the rate of homogenized daily rainfall occurrences. Our analysis also shows that the behavior of the spectra of the homogenized daily rainfall counts is completely different from that of a Poisson process, so that the hypothesis of a non-homogeneous Poisson process is rejected.

  10. Changes in daily pollen concentratio