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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. 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.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

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

    ERIC Educational Resources Information Center

    Power, Des

    2005-01-01

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

  11. 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.

  12. 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.

  13. Generalised Linear Modelling of daily rainfall in Southern England

    NASA Astrophysics Data System (ADS)

    Yang, C.; Chandler, R. E.; Isham, V. S.

    2003-04-01

    Recently published research has demonstrated the use of Generalised Linear Models (GLMs) for interpreting historical records of rainfall and other climate variables. Here, we present a case study illustrating the GLM approach to daily rainfall modelling, for a river catchment in the south of England. The area of interest is around 40km x 50km in size; data from 34 gauges are available, with record lengths ranging from 5 to 96 years. An initial modelling exercise revealed apparent spatial inconsistencies among the gauges, similar to those reported in other studies. However, it was subsequently found that these were mainly due to small rainfall values, and could be removed by thresholding the data prior to modelling. The capacity of GLMs for simulating realistic multi-site daily rainfall sequences is also demonstrated: a wide range of properties of observed rainfall sequences can be reproduced well using GLM simulations.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    USGS Publications Warehouse

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

    2011-01-01

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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. 10-daily soil erosion modelling over sub-Saharan Africa.

    PubMed

    Symeonakis, Elias; Drake, Nick

    2010-02-01

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

  5. The modeling of daily precipitation in Costa Rica

    NASA Astrophysics Data System (ADS)

    Harrison, John Michael

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

  6. 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

  7. 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

  8. 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.

  9. 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)

  10. Comparative analysis of CMIP3 and CMIP5 global climate models for simulating the daily mean, maximum, and minimum temperatures and daily precipitation over China

    NASA Astrophysics Data System (ADS)

    Sun, Qiaohong; Miao, Chiyuan; Duan, Qingyun

    2015-05-01

    This study assesses the simulations of the daily mean, maximum, and minimum temperatures and daily precipitation over China during the period 1990-1999, based on phase 3 and phase 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). Fourteen CMIP3 models and 14 CMIP5 models were investigated over eight regions across China. Skill scores quantifying the match between the simulated and observed probability density functions (PDFs) were applied to evaluate the performance of the models. For daily mean, maximum, and minimum temperatures, the results revealed that CMIP3 and CMIP5 models captured the basic pattern of the observed PDFs in all regions. However, the probabilities at lower values were overestimated in most models. In all regions except the west of Northwest China (region 7), all CMIP5 models captured more than 80% of the observed PDFs. Compared with performance at the annual time scale, the models tended to perform relatively worse over the period June to August. The performances of the CMIP5 and CMIP3 models were not as good for daily precipitation as for daily temperature, and the skill scores for precipitation were generally lower than 0.7 in all regions. The amount of drizzle (daily precipitation < 5 mm) was overestimated notably in all regions. The amount of very heavy precipitation (daily precipitation ≥ 20 mm) tended to be underestimated in humid regions but overestimated in arid regions. Compared with CMIP3, CMIP5 models showed some improvements in the simulation of daily mean, maximum, and minimum temperatures, but there was a lack of apparent improvement for simulation of daily precipitation.

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

    PubMed

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

    2014-11-01

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

  12. 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...

  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. 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...

  15. 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...

  16. 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.

  17. 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.

  18. 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...

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Massei, N.

    2013-12-01

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

  1. 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

  2. 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.

  3. 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

  4. Intermittent reservoir daily-inflow prediction using lumped and distributed data multi-linear regression models

    NASA Astrophysics Data System (ADS)

    Magar, R. B.; Jothiprakash, V.

    2011-12-01

    In this study, multi-linear regression (MLR) approach is used to construct intermittent reservoir daily inflow forecasting system. To illustrate the applicability and effect of using lumped and distributed input data in MLR approach, Koyna river watershed in Maharashtra, India is chosen as a case study. The results are also compared with autoregressive integrated moving average (ARIMA) models. MLR attempts to model the relationship between two or more independent variables over a dependent variable by fitting a linear regression equation. The main aim of the present study is to see the consequences of development and applicability of simple models, when sufficient data length is available. Out of 47 years of daily historical rainfall and reservoir inflow data, 33 years of data is used for building the model and 14 years of data is used for validating the model. Based on the observed daily rainfall and reservoir inflow, various types of time-series, cause-effect and combined models are developed using lumped and distributed input data. Model performance was evaluated using various performance criteria and it was found that as in the present case, of well correlated input data, both lumped and distributed MLR models perform equally well. For the present case study considered, both MLR and ARIMA models performed equally sound due to availability of large dataset.

  5. 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...

  6. 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…

  7. 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)

  8. 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%.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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).

  16. 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

  17. 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.

  18. 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.

  19. Modeling Cyclical Patterns in Daily College Drinking Data with Many Zeroes

    PubMed Central

    Huh, David; Kaysen, Debra L.; Atkins, David C.

    2015-01-01

    Daily college drinking data often have highly skewed distributions with many zeroes and a rising and falling pattern of use across the week. Alcohol researchers have typically relied on statistical models with dummy variables for either the weekend or all days of the week to handle weekly patterns of use. However, weekend vs. weekday categorizations may be too simplistic and saturated dummy variable models too unwieldy, particularly when covariates of weekly patterns are included. In the present study we evaluate the feasibility of cyclical (sine and cosine) covariates in a multilevel hurdle count model for evaluating daily college alcohol use data. Results showed that the cyclical parameterization provided a more parsimonious approach than multiple dummy variables. The number of drinks when drinking had a smoothly rising and falling pattern that was reasonably approximated by cyclical terms, but a saturated set of dummy variables was a better model for the probability of any drinking. Combining cyclical terms and multilevel hurdle models is a useful addition to the data analyst toolkit when modeling longitudinal drinking with high zero counts. However, drinking patterns were not perfectly sinusoidal in the current application, highlighting the need to consider multiple models and carefully evaluate model fit. PMID:26609877

  20. 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.

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-08-01

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

  3. 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 ...

  4. 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

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-11-01

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

  7. 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.

  8. 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

  9. A hierarchical stochastic model of large-scale atmospheric circulation patterns and multiple station daily precipitation

    NASA Astrophysics Data System (ADS)

    Wilson, Larry L.; Lettenmaier, Dennis P.; Skyllingstad, Eric

    1992-02-01

    A stochastic model of weather states and concurrent daily precipitation at multiple precipitation stations is described. Four algorithms are investigated for classification of daily weather states: k-means clustering, fuzzy clustering, principal components, and principal components coupled with k-means clustering. A semi-Markov model with a geometric distribution for within-class lengths of stay is used to describe the evolution of weather classes. A hierarchical modified Pólya urn model is used to simulate precipitation conditioned on the regional weather type. An information measure that considers both the probability of weather class occurrence and conditional precipitation probabilities is developed to quantify the extent to which each of the weather classification schemes discriminates the precipitation states (rain-no rain) at the precipitation stations. Evaluation of the four algorithms using the information measure shows that all methods performed equally well. The principal components method is chosen due to its ability to incorporate information from larger spatial fields. Precipitation amount distributions are assumed to be drawn from spatially correlated mixed exponential distributions, whose parameters varied by season and weather class. The model is implemented using National Meteorological Center historical atmospheric observations for the period 1964-1988 mapped to 5° × 5° grid cells over the eastern North Pacific, and three precipitation stations west of the Cascade mountain range in the state of Washington. Comparison of simulated weather class-station precipitation time series with observational data shows that the model preserved weather class statistics and mean daily precipitation quite well, especially for stations highest in the hierarchy. Precipitation amounts for the lowest precipitation station in the hierarchy, and for precipitation extremes, are not as well preserved.

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

    SciTech Connect

    Lobell, D; Bonfils, C; Duffy, P

    2006-11-09

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

  11. The effect of reproductive performance on the dairy cattle herd value assessed by integrating a daily dynamic programming model with a daily Markov chain model.

    PubMed

    Kalantari, A S; Cabrera, V E

    2012-10-01

    The objective of this study was to determine the effect of reproductive performance on dairy cattle herd value. Herd value was defined as the herd's average retention payoff (RPO). Individual cow RPO is the expected profit from keeping the cow compared with immediate replacement. First, a daily dynamic programming model was developed to calculate the RPO of all cow states in a herd. Second, a daily Markov chain model was applied to estimate the herd demographics. Finally, the herd value was calculated by aggregating the RPO of all cows in the herd. Cow states were described by 5 milk yield classes (76, 88, 100, 112, and 124% with respect to the average), 9 lactations, 750 d in milk, and 282 d in pregnancy. Five different reproductive programs were studied (RP1 to RP5). Reproductive program 1 used 100% timed artificial insemination (TAI; 42% conception rate for first TAI and 30% for second and later services) and the other programs combined TAI with estrus detection. The proportion of cows receiving artificial insemination after estrus detection ranged from 30 to 80%, and conception rate ranged from 25 to 35%. These 5 reproductive programs were categorized according to their 21-d pregnancy rate (21-d PR), which is an indication of the rate that eligible cows become pregnant every 21 d. The 21-d PR was 17% for RP1, 14% for RP2, 16% for RP3, 18% for RP4, and 20% for RP5. Results showed a positive relationship between 21-d PR and herd value. The most extreme herd value difference between 2 reproductive programs was $77/cow per yr for average milk yield (RP5 - RP2), $13/cow per yr for lowest milk yield (RP5 - RP1), and $160/cow per yr for highest milk yield (RP5 - RP2). Reproductive programs were ranked based on their calculated herd value. With the exception of the best reproductive program (RP5), all other programs showed some level of ranking change according to milk yield. The most dramatic ranking change was observed in RP1, which moved from being the worst ranked

  12. 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

  13. 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.

  14. 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.

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

    USGS Publications Warehouse

    Stanley, T.R.

    2000-01-01

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

  16. Daily air quality forecast (gases and aerosols) over Switzerland. Modeling tool description and first results analysis.

    NASA Astrophysics Data System (ADS)

    Couach, O.; Kirchner, F.; Porchet, P.; Balin, I.; Parlange, M.; Balin, D.

    2009-04-01

    Map3D, the acronym for "Mesoscale Air Pollution 3D modelling", was developed at the EFLUM laboratory (EPFL) and received an INNOGRANTS awards in Summer 2007 in order to move from a research phase to a professional product giving daily air quality forecast. It is intended to give an objective base for political decisions addressing the improvement of regional air quality. This tool is a permanent modelling system which provides daily forecast of the local meteorology and the air pollutant (gases and particles) concentrations. Map3D has been successfully developed and calculates each day at the EPFL site a three days air quality forecast over Europe and the Alps with 50 km and 15 km resolution, respectively (see http://map3d.epfl.ch). The Map3D user interface is a web-based application with a PostgreSQL database. It is written in object-oriented PHP5 on a MVC (Model-View-Controller) architecture. Our prediction system is operational since August 2008. A first validation of the calculations for Switzerland is performed for the period of August 2008 - January 2009 comparing the model results for O3, NO2 and particulates with the results of the Nabel measurements stations. The subject of air pollution regimes (NOX/VOC) and specific indicators application with the forecast will be also addressed.

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

    PubMed

    Chaib, Embarka; Moschandreas, Demetrios

    2008-03-01

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

  18. 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

  19. 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.

  20. Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach.

    PubMed

    Wesonga, Ronald; Nabugoomu, Fabian

    2016-01-01

    The study derives a framework for assessing airport efficiency through evaluating optimal arrival and departure delay thresholds. Assumptions of airport efficiency measurements, though based upon minimum numeric values such as 15 min of turnaround time, cannot be extrapolated to determine proportions of delay-days of an airport. This study explored the concept of delay threshold to determine the proportion of delay-days as an expansion of the theory of delay and our previous work. Data-driven approach using statistical modelling was employed to a limited set of determinants of daily delay at an airport. For the purpose of testing the efficacy of the threshold levels, operational data for Entebbe International Airport were used as a case study. Findings show differences in the proportions of delay at departure (μ = 0.499; 95 % CI = 0.023) and arrival (μ = 0.363; 95 % CI = 0.022). Multivariate logistic model confirmed an optimal daily departure and arrival delay threshold of 60 % for the airport given the four probable thresholds {50, 60, 70, 80}. The decision for the threshold value was based on the number of significant determinants, the goodness of fit statistics based on the Wald test and the area under the receiver operating curves. These findings propose a modelling framework to generate relevant information for the Air Traffic Management relevant in planning and measurement of airport operational efficiency. PMID:27441145

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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

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

    PubMed

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

    2013-07-01

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

  7. Modeling Daily Rainfall Conditional on Atmospheric Predictors: An application to Western Greece

    NASA Astrophysics Data System (ADS)

    Langousis, Andreas; Kaleris, Vassilios

    2013-04-01

    Due to its intermittent and highly variable character, daily precipitation is the least well reproduced hydrologic variable by both General Circulation Models (GCMs) and Limited Area Models (LAMs). To that extent, several statistical procedures (usually referred to as downscaling schemes) have been suggested to generate synthetic rainfall time series conditional on predictor variables that are descriptive of the atmospheric circulation at the mesoscale. In addition to be more accurately simulated by GCMs and LAMs, large-scale atmospheric predictors are important indicators of the local weather. Currently used downscaling methods simulate rainfall series using either stable statistical relationships (usually referred to as transfer functions) between certain characteristics of the rainfall process and mesoscale atmospheric predictor variables, or simple stochastic schemes (e.g. properly transformed autoregressive models) with parameters that depend on the large-scale atmospheric conditions. The latter are determined by classifying large-scale circulation patterns into broad categories of weather states, using empirical or theoretically based classification schemes, and modeled by resampling from those categories; a process usually referred to as weather generation. In this work we propose a statistical framework to generate synthetic rainfall timeseries at a daily level, conditional on large scale atmospheric predictors. The latter include the mean sea level pressure (MSLP), the magnitude and direction of upper level geostrophic winds, and the 500 hPa geopotential height, relative vorticity and divergence. The suggested framework operates in continuous time, avoiding the use of transfer functions, and weather classification schemes. The suggested downscaling approach is validated using atmospheric data from the ERA-Interim archive (see http://www.ecmwf.int/research/era/do/get/index), and daily rainfall data from Western Greece, for the 14-year period from 01 October

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  11. 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.

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  14. Distinguishing Ice from Snow for Melt Modeling Using Daily Observations from MODIS

    NASA Astrophysics Data System (ADS)

    Rittger, K.; Brodzik, M. J.; Racoviteanu, A.; Barrett, A. P.; Khalsa, S. J. S.; Painter, T. H.; Armstrong, R. L.; Burgess, A. B.

    2014-12-01

    In Earth's mountainous regions, melt from both seasonal snow and glacier ice contributes to streamflow. Few in-situ observations exist that can help distinguish between the two components of melt, particularly across large mountain ranges. In this study, we analyze daily time series of MODIS data products to distinguish ice from snow as the seasonal snowpack recedes revealing firn and glacier ice surfaces. We run a temperature index melt model for the Hunza, a sub-basin of the Upper Indus basin using the MODIS data to discriminate between glacier ice and snow and partition the corresponding streamflow. During the ablation period, this high elevation mid-latitude snowpack receives intense incoming solar radiation resulting in snow grain growth and surface albedo decreases. To explore snow grain growth, we use estimates of grain size from both the MODIS Snow Covered Area and Grain Size Model (MODSCAG) and MODIS Dust Radiative Forcing in Snow (MODDRFS). To explore albedo reduction we use 2 standard albedo products from MODIS, the Terra Daily Snow Cover algorithm (MOD10A1) and Surface Reflectance BRDF/Albedo (MOD43). We use a threshold on the grain size and albedo products to discriminate ice from snow. We test the ability of the 4 MODIS products to discriminate snow from glacier ice using higher resolution data from the Landsat 8 sensor from July 5th and July 21st, 2013 for a subset of the study area in the Karakoram region of the Himalaya that includes the Yazghil and Hopper Glaciers that drain north and northeast in the Shimshall Valley, part of the Hunza River basin. Snow and glacier ice are mapped using band ratio techniques, and are then separated on the basis of broadband albedo values calculated from Landsat bands for comparison with MODIS-derived snow and glacier ice pixels. We run a temperature index melt model that uses gap filled snow covered area from MODSCAG and interpolated station temperature data for the Hunza River basin. The model outputs daily melt

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  16. 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.

  17. A nonparametric kernel regression model for downscaling multisite daily precipitation in the Mahanadi basin

    NASA Astrophysics Data System (ADS)

    Kannan, S.; Ghosh, Subimal

    2013-03-01

    Hydrologic impacts of global climate change are usually assessed by downscaling large-scale climate variables, simulated by general circulation models (GCMs), to local-scale hydrometeorological variables. Conventional multisite statistical downscaling techniques often fail to capture spatial dependence of rainfall amounts as well as hydrometeorological extremes. To overcome these limitations, a downscaling algorithm is proposed, which first simulates the rainfall state of an entire study area/river basin, from large-scale climate variables, with classification and regression trees, and then projects multisite rainfall amounts using a nonparametric kernel regression estimator, conditioned on the estimated rainfall state. The concept of a common rainfall state for the entire study area, using it as an input for projections of rainfall amount, is found to be advantageous in capturing the cross correlation between rainfalls at different downscaling locations. Temporal variability and extremities of rainfall are captured in downscaling with multivariate kernel regression. The proposed model is applied for downscaling daily monsoon precipitation at eight locations in the Mahanadi River basin of eastern India. The model performance is compared, with a recently developed conditional random field based as well as with established multisite downscaling models, and is found to be superior. Analysis of future rainfall scenarios, projected with the developed downscaling model, reveals considerable changes in rainfall intensity and dry and wet spell lengths, among other things, at different locations. An increasing trend of rainfall is projected for the lower (southern) Mahanadi River basin, and a decreasing trend is observed in the upper (northern) Mahanadi River basin.

  18. 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.

  19. 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.

  20. 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

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

    PubMed Central

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Iwata, T.

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  4. A 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.

  5. Improved confidence in climate change projections of precipitation further evaluated using daily statistics from ENSEMBLES models

    NASA Astrophysics Data System (ADS)

    Boberg, Fredrik; Berg, Peter; Thejll, Peter; Gutowski, William J.; Christensen, Jens H.

    2010-12-01

    Probability density functions for daily precipitation data are used as a validation tool comparing station measurements to seven transient regional climate model runs, with a horizontal resolution of 25 km and driven by the SRES A1B scenario forcing, within the ENSEMBLES project. The validation is performed for the control period 1961-1990 for eight predefined European subregions, and a ninth region enclosing all eight subregions, with different climate characteristics. Models that best match the observations are then used for making climate change projections of precipitation distributions during the twenty-first century for each subregion separately. We find, compared to the control period, a distinct decrease in the contribution to the total precipitation for days with moderate precipitation and a distinct increase for days with more intense precipitation. This change in contribution to the total precipitation is found to amplify with time during all of the twenty-first century with an average rate of 1.1% K-1. Furthermore, the crossover point separating the decreasing from the increasing contributions does not show any significant change with time for any specific subregion. These results are a confirmation and a specification of the results from a previous study using the same station measurements but with a regional climate model ensemble within the PRUDENCE project.

  6. 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.

  7. Distinguishing ice from snow for melt modeling using daily observations from MODIS

    NASA Astrophysics Data System (ADS)

    Rittger, Karl; Bryant, Anne C.; Brodzik, Mary J.; Painter, Thomas H.; Armstrong, Richard

    2014-05-01

    In high mountainous regions of the Earth during melt periods, both seasonal snow and glacier ice melt may contribute to surface water and ground water feeding streams. In these regions there are often few in-situ observations that can help distinguish between the two components of melt, particularly across large mountain ranges. Understanding the contribution of melt water from the seasonal snow and glacier ice sources informs us about the current state of the water cycle and how a changing climate may alter the water cycle. In this study, we analyze daily time series of MODIS data products to distinguish ice from snow as the seasonal snowpack recedes, revealing melt over glacier ice surfaces. Broadband albedo increases as ice is exposed because of larger grain sizes and dust/debris on the glacier surface. To investigate the grain sizes we use estimates from the MODIS Snow Covered Area and Grain Size Model (MODSCAG) and MODIS Dust Radiative Forcing in Snow (MODDRFS) derived from MODIS surface reflectance (MOD09GA). MODSCAG uses the shape of the spectrum selected by a spectral mixture analysis model while MODDRFS uses the Normalized Difference Grain Size Index (NDGSI). Comparison of the grain sizes with grain sizes derived from the Airborne Visible/Infrared Imaging Spectrometer have demonstrated higher accuracy for the NDGSI approach. In addition to analysis of grain sizes, we use 2 standard albedo products from the MODIS, the Terra Daily Snow Cover algorithm (MOD10A1) that uses a narrow-to-broadband conversion scheme to create an integrated broadband albedo and Surface Reflectance BRDF/Albedo (MOD43) product that provides albedo in three broad bands. We focus on the Hunza River basin, in the Upper Indus located in Northern Pakistan. We use the annual minimum ice and snow from the MODICE Persistent Ice and Snow (MODICE) algorithm to identify glaciated regions for analysis. The methods (MODSCAG, MODDRFS, MOD10A1, MOD43) all show sensitivity to exposed glacier

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

    PubMed

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

    2015-02-01

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

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    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.

  11. 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.

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

    PubMed

    Yang, Zong-chang

    2014-01-01

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

  13. 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.

  14. 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.

  15. 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

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

    NASA Astrophysics Data System (ADS)

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

    2011-05-01

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

  17. 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...

  18. 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

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

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

    USGS Publications Warehouse

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

    2013-01-01

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

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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 ...

  6. 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...

  7. 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...

  8. Stochastic modelling of spatially and temporally consistent daily precipitation time-series over complex topography

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    There is a growing demand for high-resolution precipitation time-series at the local scale that are both consistent in time and in space. This is of high relevance for climate impact models that are sensitive to averaged rainfall amount over a specific region and over a multi-day period (e.g. for modeling river runoff regimes). In this regard, weather generators (WGs) calibrated at multiple sites, are an appealing technique that allow the simulation of synthetic series of unlimited length taking into account the spatio-temporal correlation structure. To date, only a few multi-site WGs have been documented in the literature and those that exist have rarely been tested for a topography as complex as the Alps. It is the aim of this study to fill this gap. Here, we present results from multi-site precipitation simulations with a generator that has been inspired by Wilks (1998). In essence, it is a Richardson-type WG that additionally takes into account the spatial correlation structure between all the station pairs. A first-order two-state Markov process is chosen to simulate daily precipitation occurrences, while precipitation amounts are re-sampled from a mixture model of two exponential distributions fitted at individual stations. Our multi-site WG is tested and evaluated here at the example of the hydrological catchment "Thur" in the Swiss Alps for the time-period 1961-2011 and on a monthly basis. In the catchment eight meteorological stations (from MeteoSwiss) are considered at which artificial time-series with the respective spatio-temporal dependence structure are simulated. The eight measurement sites are evenly distributed over the catchment, representing the complex topographical and associated precipitation characteristics. The study reveals first that our stochastic model is able to generate time-series that well represent the annual cycle of the precipitation statistics, such as mean wet day frequency and intensity as well as accumulated precipitation

  9. Hydrometeorological daily recharge assessment model (DREAM) for the Western Mountain Aquifer, Israel: Model application and effects of temporal patterns

    NASA Astrophysics Data System (ADS)

    Sheffer, N. A.; Dafny, E.; Gvirtzman, H.; Navon, S.; Frumkin, A.; Morin, E.

    2010-05-01

    Recharge is a critical issue for water management. Recharge assessment and the factors affecting recharge are of scientific and practical importance. The purpose of this study was to develop a daily recharge assessment model (DREAM) on the basis of a water balance principle with input from conventional and generally available precipitation and evaporation data and demonstrate the application of this model to recharge estimation in the Western Mountain Aquifer (WMA) in Israel. The WMA (area 13,000 km2) is a karst aquifer that supplies 360-400 Mm3 yr-1 of freshwater, which constitutes 20% of Israel's freshwater and is highly vulnerable to climate variability and change. DREAM was linked to a groundwater flow model (FEFLOW) to simulate monthly hydraulic heads and spring flows. The models were calibrated for 1987-2002 and validated for 2003-2007, yielding high agreement between calculated and measured values (R2 = 0.95; relative root-mean-square error = 4.8%; relative bias = 1.04). DREAM allows insights into the effect of intra-annual precipitation distribution factors on recharge. Although annual precipitation amount explains ˜70% of the variability in simulated recharge, analyses with DREAM indicate that the rainy season length is an important factor controlling recharge. Years with similar annual precipitation produce different recharge values as a result of temporal distribution throughout the rainy season. An experiment with a synthetic data set exhibits similar results, explaining ˜90% of the recharge variability. DREAM represents significant improvement over previous recharge estimation techniques in this region by providing near-real-time recharge estimates that can be used to predict the impact of climate variability on groundwater resources at high temporal and spatial resolution.

  10. 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

  11. 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.

  12. Daily affect and daily beliefs.

    PubMed

    Harris, Claire; Daniels, Kevin

    2005-10-01

    Human resource directorate employees of a large United Kingdom public hospital (N=36) completed an initial questionnaire and then participated in a daily diary study. The questionnaire included measures of affect and beliefs about high work demands' influence on affect and work performance. The diary included measures of affect, extent of high work demands, and daily beliefs, corresponding to those measured in the questionnaire. Participants were required to complete the diary twice daily, before and after work over a 2-week period. Measures of affect after work were associated with beliefs concerning work demands' influence on work performance and on affect measured after work. Beliefs about work demands measured in the questionnaire were associated with subsequent daily assessments of beliefs.

  13. Modeling of daily rainfall sequence and extremes based on a semiparametric Pareto tail approach at multiple locations

    NASA Astrophysics Data System (ADS)

    So, Byung-Jin; Kwon, Hyun-Han; Kim, Dongkyun; Lee, Seung Oh

    2015-10-01

    A stochastic generation framework for simulation of daily rainfall at multiple sites is presented in this study. The limitations of a Gamma distribution-based Markov chain model for reproducing high-order moments are well-known, and the problems have increased the uncertainties when the models are used in establishing water resource plans. In this regard, this study attempted to develop a semiparametric model based on a piecewise Kernel-Pareto distribution for simulation of daily rainfall in order to further improve the existing model in terms of reproducing extremes, and in addition, the algorithm to reproduce the spatial correlation was combined. The proposed model can essentially be seen as a piecewise distribution approach constructed by parametrically modeling the tails of the distribution using a generalized Pareto and the interior by kernel density estimation methods. As a result, a Kernel-Pareto distribution-based Markov chain model has been shown to perform well at reproducing most statistics, such as mean, standard deviation, skewness and kurtosis. The proposed model provided a significantly improved estimate of design rainfalls for all the stations.

  14. 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

  15. 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.

  16. 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...

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

    PubMed

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

    2016-10-01

    A major pathway for exposure to many pesticides is through diet. The objectives were to rank pesticides by comparing their calculated daily dietary exposure as determined by EPA's Stochastic Human Exposure and Dose Simulation (SHEDS) to single pesticides for different age groups to acceptable daily intakes (ADI), characterize pesticide trends in exposures over different time periods, and determine commodities contributing to pesticide exposures. SHEDS was applied, using Pesticide Data Program (PDP) (1991-2011) and pesticide usage data on crops from USDA combined with NHANES dietary consumption data, to generate exposure estimates by age group. ADI data collected from EPA, WHO, and other sources were used to rank pesticides based on relativeness of the dietary exposure potential to ADI by age groups. Sensitivity analysis provided trends in pesticide exposures. Within SHEDS, commodities contributing the majority of pesticides with greatest exposure potential were determined. The results indicated that the highest ranking pesticides were methamidophos and diazinon which exceeded 100% of the ADI. Sensitivity analysis indicated that exposure to methamidophos, diazinon, malathion, ethion and formetanate hydrochloride had a marked decrease from 1991-1999 to 2000-2011. Contributions analysis indicated that apples, mushroom, carrots, and lettuce contributed to diazinon exposure. Beans and pepper contributed to methamidophos exposure. PMID:27497764

  18. 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.

  19. 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

  20. 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

  1. 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

  2. Multiple trait model combining random regressions for daily feed intake with single measured performance traits of growing pigs

    PubMed Central

    Schnyder, Urs; Hofer, Andreas; Labroue, Florence; Künzi, Niklaus

    2002-01-01

    A random regression model for daily feed intake and a conventional multiple trait animal model for the four traits average daily gain on test (ADG), feed conversion ratio (FCR), carcass lean content and meat quality index were combined to analyse data from 1 449 castrated male Large White pigs performance tested in two French central testing stations in 1997. Group housed pigs fed ad libitum with electronic feed dispensers were tested from 35 to 100 kg live body weight. A quadratic polynomial in days on test was used as a regression function for weekly means of daily feed intake and to escribe its residual variance. The same fixed (batch) and random (additive genetic, pen and individual permanent environmental) effects were used for regression coefficients of feed intake and single measured traits. Variance components were estimated by means of a Bayesian analysis using Gibbs sampling. Four Gibbs chains were run for 550 000 rounds each, from which 50 000 rounds were discarded from the burn-in period. Estimates of posterior means of covariance matrices were calculated from the remaining two million samples. Low heritabilities of linear and quadratic regression coefficients and their unfavourable genetic correlations with other performance traits reveal that altering the shape of the feed intake curve by direct or indirect selection is difficult. PMID:11929625

  3. Multiple trait model combining random regressions for daily feed intake with single measured performance traits of growing pigs.

    PubMed

    Schnyder, Urs; Hofer, Andreas; Labroue, Florence; Künzi, Niklaus

    2002-01-01

    A random regression model for daily feed intake and a conventional multiple trait animal model for the four traits average daily gain on test (ADG), feed conversion ratio (FCR), carcass lean content and meat quality index were combined to analyse data from 1449 castrated male Large White pigs performance tested in two French central testing stations in 1997. Group housed pigs fed ad libitum with electronic feed dispensers were tested from 35 to 100 kg live body weight. A quadratic polynomial in days on test was used as a regression function for weekly means of daily feed intake and to describe its residual variance. The same fixed (batch) and random (additive genetic, pen and individual permanent environmental) effects were used for regression coefficients of feed intake and single measured traits. Variance components were estimated by means of a Bayesian analysis using Gibbs sampling. Four Gibbs chains were run for 550000 rounds each, from which 50000 rounds were discarded from the burn-in period. Estimates of posterior means of covariance matrices were calculated from the remaining two million samples. Low heritabilities of linear and quadratic regression coefficients and their unfavourable genetic correlations with other performance traits reveal that altering the shape of the feed intake curve by direct or indirect selection is difficult.

  4. 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

  5. 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

  6. Distinguishing snow and ice melt contributions using daily MODIS and a temperature index melt model in the Hunza River basin

    NASA Astrophysics Data System (ADS)

    Rittger, Karl; Brodzik, Mary J.; Racoviteanu, Adina; Barrett, Andrew; Jodha Kalsa, Siri; Armstrong, Richard

    2015-04-01

    In mountainous regions of High Asia, snow and ice both contribute to streamflow, but few in-situ observations exist that can help distinguish between the two components of melt. Our goal is to develop a melt model that can distinguish between seasonal snow and glacier ice melt at a continental scale. We use a combination of MODIS-derived data sets to distinguish three surface types at daily resolution: 1) exposed glacier ice, 2) snow over ice and 3) snow over land. We use MODICE to map glacier area and then distinguish areas of exposed ice from snow over ice using thresholds on MODIS-derived albedo or grain size products. We map snow over land using the daily MODSCAG fractional snow cover product, and use the time series of three surface types as input to a temperature index melt model. The model outputs melt volumes from exposed glacier ice, snow over ice and snow over land, respectively. To partition the glacier surface into exposed glacier ice versus snow over ice, we threshold MODIS albedo or grain size based on higher-resolution Landsat 8 imagery. During the ablation period, the high elevation mid-latitude snowpack receives intense incoming solar radiation resulting in surface albedo decreases and snow grain growth. We compare differences in modeled melt using two albedo products (Terra Daily Snow Cover algorithm (MOD10A1) and Surface Reflectance BRDF/Albedo (MCD43)) and two grain size products (MODIS Snow Covered Area and Grain Size Model (MODSCAG) and MODIS Dust Radiative Forcing in Snow (MODDRFS)). For the Hunza basin, a sub-basin of the Upper Indus basin, for the years 2001-2004, the modeled melt from exposed glacier ice accounts for: 26-44% (MOD10A1 albedo), 24-32% (MCD43 albedo), 17-28% (MODSCAG grain size) or 23-26% (MODDRFS grain size) of the combined melt from all three surface areas.

  7. 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

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

    PubMed

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

    2013-01-01

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

  9. 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.

  10. 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

  11. 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 ...

  12. 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...

  13. Adjustment of carbon fluxes to light conditions regulates the daily turnover of starch in plants: a computational model.

    PubMed

    Pokhilko, Alexandra; Flis, Anna; Sulpice, Ronan; Stitt, Mark; Ebenhöh, Oliver

    2014-03-01

    In the light, photosynthesis provides carbon for metabolism and growth. In the dark, plant growth depends on carbon reserves that were accumulated during previous light periods. Many plants accumulate part of their newly-fixed carbon as starch in their leaves in the day and remobilise it to support metabolism and growth at night. The daily rhythms of starch accumulation and degradation are dynamically adjusted to the changing light conditions such that starch is almost but not totally exhausted at dawn. This requires the allocation of a larger proportion of the newly fixed carbon to starch under low carbon conditions, and the use of information about the carbon status at the end of the light period and the length of the night to pace the rate of starch degradation. This regulation occurs in a circadian clock-dependent manner, through unknown mechanisms. We use mathematical modelling to explore possible diurnal mechanisms regulating the starch level. Our model combines the main reactions of carbon fixation, starch and sucrose synthesis, starch degradation and consumption of carbon by sink tissues. To describe the dynamic adjustment of starch to daily conditions, we introduce diurnal regulators of carbon fluxes, which modulate the activities of the key steps of starch metabolism. The sensing of the diurnal conditions is mediated in our model by the timer α and the "dark sensor"β, which integrate daily information about the light conditions and time of the day through the circadian clock. Our data identify the β subunit of SnRK1 kinase as a good candidate for the role of the dark-accumulated component β of our model. The developed novel approach for understanding starch kinetics through diurnal metabolic and circadian sensors allowed us to explain starch time-courses in plants and predict the kinetics of the proposed diurnal regulators under various genetic and environmental perturbations.

  14. 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.

  15. 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

  16. 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.

  17. Daily Water Temperature and River Discharge Modeling for Climate Change Impact Assessment in Large River Basins Globally

    NASA Astrophysics Data System (ADS)

    van Vliet, M. T.; Yearsley, J. R.; Franssen, W. H.; Ludwig, F.; Haddeland, I.; Lettenmaier, D. P.; Kabat, P.

    2010-12-01

    Recent and future changes in climate will affect hydrologic and thermal regimes, having a direct impact on water quality and in turn the growth rate and distribution of freshwater organisms. In addition, changes in river temperature and streamflow are of economic importance for water requirements for industry, electricity and drinking water production. Although integrated hydrological and deterministic water temperature modeling approaches have been successfully applied for small-scale catchments, much less work has been done at large scales. A computationally efficient modeling approach is needed to simulate water temperature and river discharge at large temporal and spatial scales, for purposes such as addressing climate change issues. In addition, realistic simulations of daily water temperature and discharge of rivers with different basin characteristics and anthropogenic impacts are needed to address large-scale water management issues. Here we use the Variable Infiltration Capacity (VIC) model and the computationally efficient 1D stream temperature model RBM to simulate river discharge and water temperature on a daily basis for selected large-scale river basins globally. The models were forced with a new global gridded 0.5° x 0.5° meteorological dataset provided by the EU FP6 Water and Global Change (WATCH) project. The performance of this modeling approach was tested for the period 1980-1999 and during warm, dry periods specifically when water temperatures and water availability are generally most critical for usage functions and freshwater ecosystems. In addition, the impact of climate change on water temperature and river discharge is assessed by forcing the models with bias corrected output of selected Global Climate Models.

  18. 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

  19. 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

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

    NASA Astrophysics Data System (ADS)

    Ababaei, Behnam; Sohrabi, Teymour; Mirzaei, Farhad

    2014-10-01

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

  1. 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.

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

    USGS Publications Warehouse

    Christiansen, Daniel E.

    2012-01-01

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

  3. 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.

  4. 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

  5. Temperature based daily incoming solar radiation modeling based on gene expression programming, neuro-fuzzy and neural network computing techniques.

    NASA Astrophysics Data System (ADS)

    Landeras, G.; López, J. J.; Kisi, O.; Shiri, J.

    2012-04-01

    The correct observation/estimation of surface incoming solar radiation (RS) is very important for many agricultural, meteorological and hydrological related applications. While most weather stations are provided with sensors for air temperature detection, the presence of sensors necessary for the detection of solar radiation is not so habitual and the data quality provided by them is sometimes poor. In these cases it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using Gene Expression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). Traditional temperature based solar radiation equations were also included in this study and compared with artificial intelligence based approaches. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SSRMSE), MAE-based skill score (SSMAE) and r2 criterion of Nash and Sutcliffe criteria were used to assess the models' performances. An ANN (a four-input multilayer perceptron with ten neurons in the hidden layer) presented the best performance among the studied models (2.93 MJ m-2 d-1 of RMSE). A four-input ANFIS model revealed as an interesting alternative to ANNs (3.14 MJ m-2 d-1 of RMSE). Very limited number of studies has been done on estimation of solar radiation based on ANFIS, and the present one demonstrated the ability of ANFIS to model solar radiation based on temperatures and extraterrestrial radiation. By the way this study demonstrated, for the first time, the ability of GEP models to model solar radiation based on daily atmospheric variables. Despite the accuracy of GEP models was slightly lower than the ANFIS and ANN models the genetic programming models (i.e., GEP) are superior to other artificial intelligence models in giving a simple explicit equation for the

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  7. 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

  8. 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.

  9. 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

  10. Beneficial effect of brewers' yeast extract on daily activity in a murine model of chronic fatigue syndrome.

    PubMed

    Takahashi, Takashi; Yu, Fei; Zhu, Shi-Jie; Moriya, Junji; Sumino, Hiroyuki; Morimoto, Shigeto; Yamaguchi, Nobuo; Kanda, Tsugiyasu

    2006-03-01

    The aim of this study was to assess the effect of Brewers' yeast extract (BYE) on daily activity in a mouse model of chronic fatigue syndrome (CFS). CFS was induced by repeated injection of Brucella abortus (BA) antigen every 2 weeks. BYE was orally administered to mice in a dose of 2 g per kg per day for 2 weeks before injecting BA and for 4 weeks thereafter. We evaluated daily running activity in mice receiving BYE as compared with that in untreated mice. Weekly variation of body weight (BW) and survival in both groups was monitored during the observation period. Spleen weight (SW), SW/BW ratio, percent splenic follicular area and expression levels of interferon-gamma (IFN-gamma) and interleukin-10 (IL-10) mRNA in spleen were determined in both groups at the time of sacrifice. The daily activity during 2 weeks after the second BA injection was significantly higher in the treated group than in the control. There was no difference in BW between both groups through the experimental course. Two mice in the control died 2 and 7 days after the second injection, whereas no mice in the treated group died. Significantly decreased SW and SW/BW ratio were observed in the treated mice together with elevation of splenic follicular area. There were suppressed IFN-gamma and IL-10 mRNA levels in spleens from the treated mice. Our results suggest that BYE might have a protective effect on the marked reduction in activity following repeated BA injection via normalization of host immune responses.

  11. 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...

  12. Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology.

    PubMed

    Allen, Jenica M; Terres, Maria A; Katsuki, Toshio; Iwamoto, Kojiro; Kobori, Hiromi; Higuchi, Hiroyoshi; Primack, Richard B; Wilson, Adam M; Gelfand, Alan; Silander, John A

    2014-04-01

    Understanding the drivers of phenological events is vital for forecasting species' responses to climate change. We developed flexible Bayesian survival regression models to assess a 29-year, individual-level time series of flowering phenology from four taxa of Japanese cherry trees (Prunus spachiana, Prunus × yedoensis, Prunus jamasakura, and Prunus lannesiana), from the Tama Forest Cherry Preservation Garden in Hachioji, Japan. Our modeling framework used time-varying (chill and heat units) and time-invariant (slope, aspect, and elevation) factors. We found limited differences among taxa in sensitivity to chill, but earlier flowering taxa, such as P. spachiana, were more sensitive to heat than later flowering taxa, such as P. lannesiana. Using an ensemble of three downscaled regional climate models under the A1B emissions scenario, we projected shifts in flowering timing by 2100. Projections suggest that each taxa will flower about 30 days earlier on average by 2100 with 2-6 days greater uncertainty around the species mean flowering date. Dramatic shifts in the flowering times of cherry trees may have implications for economically important cultural festivals in Japan and East Asia. The survival models used here provide a mechanistic modeling approach and are broadly applicable to any time-to-event phenological data, such as plant leafing, bird arrival time, and insect emergence. The ability to explicitly quantify uncertainty, examine phenological responses on a fine time scale, and incorporate conditions leading up to an event may provide future insight into phenologically driven changes in carbon balance and ecological mismatches of plants and pollinators in natural populations and horticultural crops.

  13. Revisiting a population-dynamic model of air pollution and daily mortality of the elderly in Philadelphia.

    PubMed

    Murray, Christian J; Lipfert, Frederick W

    2010-05-01

    Epidemiological studies find that elderly, susceptible, and previously impaired individuals are more sensitive to transient air pollution exposures than healthy persons. However, any associated changes in life expectancy remain largely unresolved. Murray and Nelson published a model of daily mortality and air pollution that addresses mortality displacement or harvesting by directly considering population dynamics on the basis of the assumption that a period of illness or frailty precedes most elderly deaths. The underlying concept is that a person's response to an environmental exposure also depends on his/her physiological ability to withstand stress at that time. They used Kalman filtering to estimate an unobservable quantity--the size of the frail subpopulation from which elderly (ages > or = 65 yr) nontraumatic deaths are assumed to derive. They found a small subpopulation, relatively robust to environmental variations over 14 yr, with remaining life expectancies of 8-31 days in this frail status. Here, this model and dataset are expanded to examine the ramifications in more detail (including seasonality), to consider peak ozone as an additional pollutant, and to consider remaining life expectancies of the this frail subpopulation on a daily basis. Previous studies of mortality displacement and of Philadelphia mortality-air-pollution associations are also summarized in general, and agreement with the Murray-Nelson model was found, thus supporting its validity. The estimated additional mortality associated with a given environmental exposure persists for a few days at most but is not always compensated by subsequent mortality deficits. It is concluded that the pollution-associated mortality increases of a few percent in this dataset are consistent with losses of remaining life expectancy of up to a few days. It is also recommended that a more complex population-dynamic model be implemented to examine the extent to which previous short-term environmental

  14. 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.

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

    ERIC Educational Resources Information Center

    Meister, Christine; Salls, Joyce

    2015-01-01

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

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

    PubMed

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

    2013-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

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

    USGS Publications Warehouse

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

    2015-10-14

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

  19. Synoptic weather modeling and estimates of the exposure-response relationship between daily mortality and particulate air pollution.

    PubMed Central

    Pope, C A; Kalkstein, L S

    1996-01-01

    This study estimated the association between particulate air pollution and daily mortality in Utah Valley using the synoptic climatological approach to control for potential weather effects. This approach was compared with alternative weather modeling approaches. Although seasonality explained a significant amount of variability in mortality, other weather variables explained only a very small amount of additional variability in mortality. The synoptic climatological approach performed as well or slightly better than alternative approaches to controlling for weather. However, the estimated effect of particulate pollution on mortality was mostly unchanged or slightly larger when synoptic categories were used to control for weather. Furthermore, the shape of the estimated dose-response relationship was similar when alternative approaches to controlling for weather were used. The associations between particulate pollution and daily mortality were not significantly different from a linear exposure-response relationship that extends throughout the full observed range of pollution. Images Figure 1. Figure 2. A Figure 2. B Figure 2. C Figure 2. D PMID:8732952

  20. A model for the spatial transmission of dengue with daily movement between villages and a city.

    PubMed

    Nevai, Andrew L; Soewono, Edy

    2014-06-01

    Dengue is a re-emergent vector-borne disease affecting large portions of the world's population living in the tropics and subtropics. The virus is transmitted through the bites of female Aedes aegypti mosquitoes, and it is widely believed that these bites occur primarily in the daytime. The transmission of dengue is a complicated process, and one of the main sources of this complexity is due to the movement of people, e.g. between home and their places of work. Hence, the mechanics of disease progression may also differ between day and night. A discrete-time multi-patch dengue transmission model which takes into account the mobility of people as well as processes of infection, recovery, recruitment, mortality, and outbound and return movements is considered here. One patch (the city) is connected to all other patches (the villages) in a spoke-like network. We obtain here the basic reproductive ratio (ℛ0) of the transmission model which represents a threshold for an epidemic to occur. Dynamical analysis for vector control, human treatment and vaccination, and different kinds of mobility are performed. It is shown that changes in human movement patterns can, in some situations, affect the ability of the disease to persist in a predictable manner. We conclude with biological implications for the prevention and control of dengue virus transmission.

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

    USGS Publications Warehouse

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

    2015-08-24

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

  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.

  3. [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

  4. 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

  5. A cross-cultural study of relationships between daily social interaction and the five-factor model of personality.

    PubMed

    Nezlek, John B; Schütz, Astrid; Schröder-Abé, Michela; Smith, C Veronica

    2011-08-01

    Two studies, one in the United States (N = 130) and another in Germany (N = 100), examined relationships between daily social interaction and the traits of the Five-Factor Model. In both studies, student participants described their social interactions for 2 weeks using the Rochester Interaction Record. In both countries, Agreeableness and Conscientiousness were positively related to reactions to social interaction, whereas Neuroticism was unrelated to reactions to interactions. In the United States, Extraversion and Openness were positively related to reactions to interactions, whereas these factors were not related to reactions to interactions in Germany. In the United States, Extraversion was positively related to how socially active participants were, whereas none of the FFM traits was related to amount of social interaction in the German sample. In both countries, Extraversion was positively related to percent of interactions involving friends. The results highlight the importance of taking into account the sociocultural milieus within which personality unfolds.

  6. A model for the distribution of daily number of births in obstetric clinics based on a descriptive retrospective study

    PubMed Central

    Gam, Christiane M B; Tanniou, Julien; Keiding, Niels; Løkkegaard, Ellen L

    2013-01-01

    Objective To test whether the relatively unpredictable nature of labour onset can be described by the Poisson distribution. Design A descriptive retrospective study. Setting From the Danish Birth Registry, we identified births from all seven obstetric clinics in the capital region of Denmark (n=211 290) between 2000 and the end of 2009. On each date, the number of births at each department was registered. Births are categorised based on whether an elective caesarean section or induction of labour has been performed, and among the remaining ‘non-elective births’, acute caesareans were registered. Methods After the exclusion of elective caesarean sections and births after induction of labour, only ‘non-elective’ births (n=171 009) were included for the main statistical analysis. Simple descriptive plots and one-way analysis of variance were used to analyse the distribution of ‘non-elective’ births for each day of the week. Main outcome measures The daily number of ‘non-elective’ births. Results The number of ‘non-elective’ births varies considerably over the days of the week and over the year for each obstetric clinic regardless of clinic size. However, for each fixed day of the week, the variation over the year is well described by a Poisson distribution, allowing simple prediction of the variability. For births at each fixed day of the week, the Poisson distribution is indistinguishable from a normal distribution. Conclusions The number of ‘non-elective’ births for each day of the week is well described by a Poisson distribution. Consequently, the Poisson model is suitable for estimating the variation in the daily number of ‘non-elective’ births and could be used for planning of staffing in obstetric clinics. The model can be used in smaller as well as larger clinics. PMID:23996815

  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

    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.

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

    PubMed Central

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

    2016-01-01

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

  11. 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

  12. 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.

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  15. 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.

  16. 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…

  17. 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.…

  18. 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.

  19. 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.

  20. 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 ...

  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. 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

  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.; 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

  4. Quantifying the effect of heat stress on daily milk yield and monitoring dynamic changes using an adaptive dynamic model.

    PubMed

    André, G; Engel, B; Berentsen, P B M; Vellinga, Th V; Lansink, A G J M Oude

    2011-09-01

    Automation and use of robots are increasingly being used within dairy farming and result in large amounts of real time data. This information provides a base for the new management concept of precision livestock farming. From 2003 to 2006, time series of herd mean daily milk yield were collected on 6 experimental research farms in the Netherlands. These time series were analyzed with an adaptive dynamic model following a Bayesian method to quantify the effect of heat stress. The effect of heat stress was quantified in terms of critical temperature above which heat stress occurred, duration of heat stress periods, and resulting loss in milk yield. In addition, dynamic changes in level and trend were monitored, including the estimation of a weekly pattern. Monitoring comprised detection of potential outliers and other deteriorations. The adaptive dynamic model fitted the data well; the root mean squared error of the forecasts ranged from 0.55 to 0.99 kg of milk/d. The percentages of potential outliers and signals for deteriorations ranged from 5.5 to 9.7%. The Bayesian procedure for time series analysis and monitoring provided a useful tool for process control. Online estimates (based on past and present only) and retrospective estimates (determined afterward from all data) of level and trend in daily milk yield showed an almost yearly cycle that was in agreement with the calving pattern: most cows calved in winter and early spring versus summer and autumn. Estimated weekly patterns in terms of weekday effects could be related to specific management actions, such as change of pasture during grazing. For the effect of heat stress, the mean estimated critical temperature above which heat stress was expected was 17.8±0.56°C. The estimated duration of the heat stress periods was 5.5±1.03 d, and the estimated loss was 31.4±12.2 kg of milk/cow per year. Farm-specific estimates are helpful to identify management factors like grazing, housing and feeding, that affect the

  5. Modeling daily gas exchange of a Douglas-fir forest: comparison of three stomatal conductance models with and without a soil water stress function.

    PubMed

    Van Wijk, M. T.; Dekker, S. C.; Bouten, W.; Bosveld, F. C.; Kohsiek, W.; Kramer, K.; Mohren, G. M. J.

    2000-01-01

    Modeling stomatal conductance is a key element in predicting tree growth and water use at the stand scale. We compared three commonly used models of stomatal conductance, the Jarvis-Loustau, Ball-Berry and Leuning models, for their suitability for incorporating soil water stress into their formulation, and for their performance in modeling forest ecosystem fluxes. We optimized the parameters of each of the three models with sap flow and soil water content data. The optimized Ball-Berry model showed clear relationships with air temperature and soil water content, whereas the optimized Leuning and Jarvis-Loustau models only showed a relationship with soil water content. We conclude that use of relative humidity instead of vapor pressure deficit, as in the Ball-Berry model, is not suitable for modeling daily gas exchange in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) in the Speulderbos forest near the village of Garderen, The Netherlands. Based on the calculated responses to soil water content, we linked a model of forest growth, FORGRO, with a model of soil water, SWIF, to obtain a forest water-balance model that satisfactorily simulated carbon and water (transpiration) fluxes and soil water contents in the Douglas-fir forest for 1995.

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

    PubMed

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

    2013-03-01

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

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

    USGS Publications Warehouse

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

    2012-01-01

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

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

    USGS Publications Warehouse

    Rounds, Stewart A.; Sullivan, Annett B.

    2013-01-01

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

  9. 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

  10. 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.

  11. 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

  12. Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

    PubMed

    de Gennaro, Gianluigi; Trizio, Livia; Di Gilio, Alessia; Pey, Jorge; Pérez, Noemi; Cusack, Michael; Alastuey, Andrés; Querol, Xavier

    2013-10-01

    An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies.

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

    PubMed

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

    2015-01-15

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

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

    USGS Publications Warehouse

    Rounds, Stewart A.; Sullivan, Annett B.

    2013-01-01

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

  15. 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.

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

    ERIC Educational Resources Information Center

    Gardner, Stephanie; Wolfe, Pamela

    2013-01-01

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

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

    ERIC Educational Resources Information Center

    Ohtake, Yoshihisa

    2015-01-01

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

  18. 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…

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  20. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  2. Daily evapotranspiration assessment by means of residual surface energy balance modeling: A critical analysis under a wide range of water availability

    NASA Astrophysics Data System (ADS)

    Cammalleri, C.; Ciraolo, G.; La Loggia, G.; Maltese, A.

    2012-07-01

    SummaryAn operational use of the actual evapotranspiration assessed by remote sensing approaches requires the integration of instantaneous fluxes to daily values. This is commonly achieved under the hypotheses of daytime self-preservation of evaporative fraction and negligible daily ground heat flux. The aim of this study is to evaluate the effect of these assumptions on estimate daily evapotranspiration over a full phenological cycle, including phases characterized by significant changes both in net radiation and vegetation cover. To assess the reliability of these hypotheses, the observations made by a flux tower, installed within a homogeneous field of cereal located in the valley part of the Imera Meridionale basin, were analyzed. Additionally, the widely-known SEBAL (Surface Energy Balance Algorithm for Land) model was applied on the same study area by means of four MODIS (MODerate-resolution Imaging Spectroradiometer) images selected across a three-rainfall events period in March-April 2007 with the aim to analyze the consistency of its estimates in an operational study case under different conditions of water availability. The analysis of in situ data highlights errors on 24-h evapotranspiration characterized by an average value of 20% due to daily soil heat flux neglecting; whereas, the hypothesis of evaporative fraction self-preservation causes an average error equal to -16%. Moreover, the analysis of the observations suggests that a compensation effect of the errors related to each hypothesis occurs in most cases (56%), and this makes suitable the approach for practical daily integration purposes. The application of the SEBAL model at basin scale shows a good capability to detect the increase of the actual 24-h evapotranspiration under the tested hypotheses, also in the case of instantaneous evaporative fraction and daily net radiation not derived form in situ observations.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  4. 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)

  5. 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.

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

    PubMed Central

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

    2016-01-01

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

  7. 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

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

    PubMed

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

    2016-08-01

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

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

    USGS Publications Warehouse

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

    2013-01-01

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

  10. Integrating Map Algebra and Statistical Modeling for Spatio-Temporal Analysis of Monthly Mean Daily Incident Photosynthetically Active Radiation (PAR) over a Complex Terrain

    PubMed Central

    Evrendilek, Fatih

    2007-01-01

    This study aims at quantifying spatio-temporal dynamics of monthly mean daily incident photosynthetically active radiation (PAR) over a vast and complex terrain such as Turkey. The spatial interpolation method of universal kriging, and the combination of multiple linear regression (MLR) models and map algebra techniques were implemented to generate surface maps of PAR with a grid resolution of 500 × 500 m as a function of five geographical and 14 climatic variables. Performance of the geostatistical and MLR models was compared using mean prediction error (MPE), root-mean-square prediction error (RMSPE), average standard prediction error (ASE), mean standardized prediction error (MSPE), root-mean-square standardized prediction error (RMSSPE), and adjusted coefficient of determination (R2adj.). The best-fit MLR- and universal kriging-generated models of monthly mean daily PAR were validated against an independent 37-year observed dataset of 35 climate stations derived from 160 stations across Turkey by the Jackknifing method. The spatial variability patterns of monthly mean daily incident PAR were more accurately reflected in the surface maps created by the MLR-based models than in those created by the universal kriging method, in particular, for spring (May) and autumn (November). The MLR-based spatial interpolation algorithms of PAR described in this study indicated the significance of the multifactor approach to understanding and mapping spatio-temporal dynamics of PAR for a complex terrain over meso-scales.

  11. Evaluating Southern Ocean biological production in two ocean biogeochemical models on daily to seasonal time-scales using satellite surface chlorophyll and O2/Ar observations

    NASA Astrophysics Data System (ADS)

    Jonsson, B. F.; Doney, S.; Dunne, J.; Bender, M. L.

    2014-06-01

    We assess the ability of ocean biogeochemical models to represent seasonal structures in biomass and net community production (NCP) in the Southern Ocean. Two models are compared to observations on daily to seasonal time scales in four different sections of the region. We use daily satellite fields of Chlorophyll (Chl) as a proxy for biomass, and in-situ observations of O2 and Ar supersaturation (ΔO2Ar) to estimate NCP. ΔO2Ar is converted to the flux of biologically generated O2 from sea to air ("O2 bioflux"). All data are aggregated to a climatological year with a daily resolution. To account for potential regional differences within the Southern Ocean, we conduct separate analyses of sections south of South Africa, around the Drake Passage, south of Australia, and south of New Zealand. We find that the models simulate the upper range of Chl concentrations well, underestimate spring levels significantly, and show differences in skill between early and late parts of the growing season. While there is a great deal of scatter in the bioflux observations in general, the four sectors each have distinct patterns that the models pick up. Neither model exhibit a significant distinction between the Australian and New Zealand sectors, and between the Drake Passage and African sectors. South of 60° S, the models fail to predict the observed extent of biological O2 undersaturation. We suggest that this shortcoming may be due either to problems with the ecosystem dynamics or problems with the vertical transport of oxygen. Overall, the bioflux observations are in general agreement with the seasonal structures in satellite chlorophyll, suggesting that this seasonality represent changes in carbon biomass and not Chl : C ratios. This agreement is shared in the models and allows us to interpret the seasonal structure of satellite chlorophyll as qualitatively reflecting the integral of biological production over time for the purposes of model assessment.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  14. Evaluating Southern Ocean biological production in two ocean biogeochemical models on daily to seasonal timescales using satellite chlorophyll and O2 / Ar observations

    NASA Astrophysics Data System (ADS)

    Jonsson, B. F.; Doney, S.; Dunne, J.; Bender, M. L.

    2015-02-01

    We assess the ability of ocean biogeochemical models to represent seasonal structures in biomass and net community production (NCP) in the Southern Ocean. Two models are compared to observations on daily to seasonal timescales in four different sections of the region. We use daily satellite fields of chlorophyll (Chl) as a proxy for biomass and in situ observations of O2 and Ar supersaturation (ΔO2 / Ar) to estimate NCP. ΔO2 / Ar is converted to the flux of biologically generated O2 from sea to air (O2 bioflux). All data are aggregated to a climatological year with a daily resolution. To account for potential regional differences within the Southern Ocean, we conduct separate analyses of sections south of South Africa, around the Drake Passage, south of Australia, and south of New Zealand. We find that the models simulate the upper range of Chl concentrations well, underestimate spring levels significantly, and show differences in skill between early and late parts of the growing season. While there is a great deal of scatter in the bioflux observations in general, the four sectors each have distinct patterns that the models pick up. Neither model exhibits a significant distinction between the Australian and New Zealand sectors and between the Drake Passage and African sectors. South of 60° S, the models fail to predict the observed extent of biological O2 undersaturation. We suggest that this shortcoming may be due either to problems with the ecosystem dynamics or problems with the vertical transport of oxygen.

  15. Genetic parameters of a random regression model for daily feed intake of performance tested French Landrace and Large White growing pigs

    PubMed Central

    Schnyder, Urs; Hofer, Andreas; Labroue, Florence; Künzi, Niklaus

    2001-01-01

    Daily feed intake data of 1 279 French Landrace (FL, 1 039 boars and 240 castrates) and 2 417 Large White (LW, 2 032 boars and 385 castrates) growing pigs were recorded with electronic feed dispensers in three French central testing stations from 1992–1994. Male (35 to 95 kg live body weight) or castrated (100 kg live body weight) group housed, ad libitum fed pigs were performance tested. A quadratic polynomial in days on test with fixed regressions for sex and batch, random regressions for additive genetic, pen, litter and individual permanent environmental effects was used, with two different models for the residual variance: constant in model 1 and modelled with a quadratic polynomial depending on the day on test dm as follows in model 2: . Variance components were estimated from weekly means of daily feed intake by means of a Bayesian analysis using Gibbs sampling. Posterior means of (co)variances were calculated using 800 000 samples from four chains (200 000 each). Heritability estimates of regression coefficients were 0.30 (FL model 1), 0.21 (FL model 2), 0.14 (LW1) and 0.14 (LW2) for the intercept, 0.04 (FL1), 0.04 (FL2), 0.11 (LW1) and 0.06 (LW2) for the linear, 0.03 (FL1), 0.04 (FL2) 0.11 (LW1) and 0.06 (LW2) for the quadratic term. Heritability estimates for weekly means of daily feed intake were the lowest in week 4 (FL1: 0.11, FL2: 0.11) and week 1 (LW1: 0.09, LW2: 0.10), and the highest in week 11 (FL1: 0.25, FL2: 0.24) and week 8 (LW1: 0.19, LW2: 0.18), respectively. Genetic eigenfunctions revealed that altering the shape of the feed intake curve by selection is difficult. PMID:11742633

  16. 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.

  17. Unravelling daily human mobility motifs.

    PubMed

    Schneider, Christian M; Belik, Vitaly; Couronné, Thomas; Smoreda, Zbigniew; González, Marta C

    2013-07-01

    Human mobility is differentiated by time scales. While the mechanism for long time scales has been studied, the underlying mechanism on the daily scale is still unrevealed. Here, we uncover the mechanism responsible for the daily mobility patterns by analysing the temporal and spatial trajectories of thousands of persons as individual networks. Using the concept of motifs from network theory, we find only 17 unique networks are present in daily mobility and they follow simple rules. These networks, called here motifs, are sufficient to capture up to 90 per cent of the population in surveys and mobile phone datasets for different countries. Each individual exhibits a characteristic motif, which seems to be stable over several months. Consequently, daily human mobility can be reproduced by an analytically tractable framework for Markov chains by modelling periods of high-frequency trips followed by periods of lower activity as the key ingredient.

  18. 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

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. Simulation of daily discharges for the upper Durance catchment (French Alps) using subgrid parameterization for topography and a forest canopy climate model

    NASA Astrophysics Data System (ADS)

    Strasser, Ulrich; Etchevers, Pierre

    2005-08-01

    This study describes the application of the coupled SAFRAN (meteorological variables), ISBA (soil-vegetation-atmosphere transfer) and CROCUS (snow cover evolution) models to simulate daily discharges for the upper Durance catchment (French Alps) from 1981 to 1994. The results are validated by comparison with measurements at three gauging stations located in the watershed. Previous investigations have shown a remarkable overestimation of the spring flood peak generated by the modelled snowmelt. It could be significantly improved by increasing the model resolution from 8 km to 1 km, thus more precisely considering the elevation-dependent snowmelt process. However, it is also possible to use subgrid parameterizations at the coarse grid resolution to improve simulations. This paper investigates the influence of a subgrid parameterization for topography, a subgrid parameterization for the snow cover in a forest canopy and a combination of the two on the simulated spring flood peak. Results show a significant improvement in the simulations by both subgrid parameterizations, in particular by their combination: the Nash-Sutcliffe efficiency of the daily discharges is improved from 0.73 (original experiment) to 0.77 (subgrid topography), to 0.75 (forest) and to 0.78 (combination of subgrid topography and forest).

  4. 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.

  5. The Impact of Sensory Processing Abilities on the Daily Lives of Young Children and Their Families: A Conceptual Model.

    ERIC Educational Resources Information Center

    Dunn, Winnie

    1997-01-01

    Describes a proposed model for considering sensory processing as an important factor in young children's performance. Discusses ways the model can be used to provide a framework for understanding various patterns of behavior; identify disabilities (poor registration, sensitivity to stimuli, sensation seeking, and sensation avoiding); and develop…

  6. 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.

  7. 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…

  8. 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

  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. 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

  11. 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.

  12. 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...

  13. Genetic parameters of a random regression model for daily feed intake of performance tested French Landrace and Large White growing pigs.

    PubMed

    Schnyder, U; Hofer, A; Labroue, F; Künzi, N

    2001-01-01

    Daily feed intake data of 1 279 French Landrace (FL, 1 039 boars and 240 castrates) and 2 417 Large White (LW, 2 032 boars and 385 castrates) growing pigs were recorded with electronic feed dispensers in three French central testing stations from 1992-1994. Male (35 to 95 kg live body weight) or castrated (100 kg live body weight) group housed, ad libitum fed pigs were performance tested. A quadratic polynomial in days on test with fixed regressions for sex and batch, random regressions for additive genetic, pen, litter and individual permanent environmental effects was used, with two different models for the residual variance: constant in model 1 and modelled with a quadratic polynomial depending on the day on test d(m) as follows in model 2: sigma(epsilon(m))(2) = exp (gamma(0) + gamma(1) d(m) + gamma(2) d(m)(2)). Variance components were estimated from weekly means of daily feed intake by means of a Bayesian analysis using Gibbs sampling. Posterior means of (co)variances were calculated using 800 000 samples from four chains (200 000 each). Heritability estimates of regression coefficients were 0.30 (FL model 1), 0.21 (FL model 2), 0.14 (LW1) and 0.14 (LW2) for the intercept, 0.04 (FL1), 0.04 (FL2), 0.11 (LW1) and 0.06 (LW2) for the linear, 0.03 (FL1), 0.04 (FL2) 0.11 (LW1) and 0.06 (LW2) for the quadratic term. Heritability estimates for weekly means of daily feed intake were the lowest in week 4 (FL1: 0.11, FL2: 0.11) and week 1 (LW1: 0.09, LW2: 0.10), and the highest in week 11 (FL1: 0.25, FL2: 0.24) and week 8 (LW1: 0.19, LW2: 0.18), respectively. Genetic eigenfunctions revealed that altering the shape of the feed intake curve by selection is difficult.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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...

  20. 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.

  1. Daily Supplementation of D-ribose Shows No Therapeutic Benefits in the MHC-I Transgenic Mouse Model of Inflammatory Myositis

    PubMed Central

    Coley, William; Rayavarapu, Sree; van der Meulen, Jack H.; Duba, Ayyappa S.; Nagaraju, Kanneboyina

    2013-01-01

    Background Current treatments for idiopathic inflammatory myopathies (collectively called myositis) focus on the suppression of an autoimmune inflammatory response within the skeletal muscle. However, it has been observed that there is a poor correlation between the successful suppression of muscle inflammation and an improvement in muscle function. Some evidence in the literature suggests that metabolic abnormalities in the skeletal muscle underlie the weakness that continues despite successful immunosuppression. We have previously shown that decreased expression of a purine nucleotide cycle enzyme, adenosine monophosphate deaminase (AMPD1), leads to muscle weakness in a mouse model of myositis and may provide a mechanistic basis for muscle weakness. One of the downstream metabolites of this pathway, D-ribose, has been reported to alleviate symptoms of myalgia in patients with a congenital loss of AMPD1. Therefore, we hypothesized that supplementing exogenous D-ribose would improve muscle function in the mouse model of myositis. We treated normal and myositis mice with daily doses of D-ribose (4 mg/kg) over a 6-week time period and assessed its effects using a battery of behavioral, functional, histological and molecular measures. Results Treatment with D-ribose was found to have no statistically significant effects on body weight, grip strength, open field behavioral activity, maximal and specific forces of EDL, soleus muscles, or histological features. Histological and gene expression analysis indicated that muscle tissues remained inflamed despite treatment. Gene expression analysis also suggested that low levels of the ribokinase enzyme in the skeletal muscle might prevent skeletal muscle tissue from effectively utilizing D-ribose. Conclusions Treatment with daily oral doses of D-ribose showed no significant effect on either disease progression or muscle function in the mouse model of myositis. PMID:23785461

  2. 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.

  3. 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

  4. 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

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

    PubMed Central

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

    2014-01-01

    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 (IVR) system. The statistical analysis results show that the effect of measurement reactivity may only be evident in the first week of IVR 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

  6. A model for predicting daily peak visitation and implications for recreation management and water quality: evidence from two rivers in Puerto Rico.

    PubMed

    Santiago, Luis E; Gonzalez-Caban, Armando; Loomis, John

    2008-06-01

    Visitor use surveys and water quality data indicates that high visitor use levels of two rivers in Puerto Rico does not appear to adversely affect several water quality parameters. Optimum visitor use to maximize visitor defined satisfaction is a more constraining limit on visitor use than water quality. Our multiple regression analysis suggests that visitor use of about 150 visitors per day yields the highest level of visitor reported satisfaction, a level that does not appear to affect turbidity of the river. This high level of visitor use may be related to the gregarious nature of Puerto Ricans and their tolerance for crowding on this densely populated island. The daily peak visitation model indicates that regulating the number of parking spaces may be the most effective way to keep visitor use within the social carrying capacity.

  7. Levofloxacin plus metronidazole administered once daily versus moxifloxacin monotherapy against a mixed infection of Escherichia coli and Bacteroides fragilis in an in vitro pharmacodynamic model.

    PubMed

    Hermsen, Elizabeth D; Hovde, Laurie B; Sprandel, Kelly A; Rodvold, Keith A; Rotschafer, John C

    2005-02-01

    Moxifloxacin has been suggested as an option for monotherapy of intra-abdominal infections. Recent data support the use of a once-daily metronidazole regimen. The purpose of this study was to investigate the activity of levofloxacin (750 mg every 24 h [q24h]) plus metronidazole (1,500 mg q24h) compared with that of moxifloxacin (400 mg q24h) monotherapy in a mixed-infection model. By using an in vitro pharmacodynamic model in duplicate, Escherichia coli and Bacteroides fragilis were exposed to peak concentrations of 8.5 mg of levofloxacin/liter q24h, 32 mg of metronidazole/liter q24h, and 2 mg for moxifloxacin/liter q24h for 24 h. The activities of levofloxacin, metronidazole, moxifloxacin, and levofloxacin plus metronidazole were evaluated against E. coli, B. fragilis, and E. coli plus B. fragilis. The targeted half-lives of levofloxacin, metronidazole, and moxifloxacin were 8, 8, and 12 h, respectively. Time-kill curves were analyzed for time to 3-log killing, slope, and regrowth. Pre- and postexposure MICs were determined. The preexposure levofloxacin, metronidazole, and moxifloxacin MICs for E. coli and B. fragilis were 0.5 and 1, >64 and 0.5, and 1 and 0.25 mg/liter, respectively. Levofloxacin and moxifloxacin achieved a 3-log killing against E. coli and B. fragilis in all experiments, as did metronidazole against B. fragilis. Metronidazole did not decrease the starting inoculum of E. coli. The area under the concentration-time curve/MIC ratios for E. coli and B. fragilis were 171.7 and 85.9, respectively, for levofloxacin and 26 and 103.9, respectively, for moxifloxacin. Levofloxacin plus metronidazole exhibited the fastest rates of killing. The levofloxacin and moxifloxacin MICs for B. fragilis increased 8- to 16-fold after the organism was exposed to moxifloxacin. No other changes in the postexposure MICs were found. Levofloxacin plus metronidazole administered once daily exhibited activity similar to that of moxifloxacin against the mixed E. coli and B

  8. 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.

  9. Time-dependent MHD modeling of the global solar corona for year 2007: Driven by daily-updated magnetic field synoptic data

    NASA Astrophysics Data System (ADS)

    Yang, L. P.; Feng, X. S.; Xiang, C. Q.; Liu, Yang; Zhao, Xuepu; Wu, S. T.

    2012-08-01

    In this paper, we develop a time-dependent MHD model driven by the daily-updated synoptic magnetograms (MHD-DUSM) to study the dynamic evolution of the global corona with the help of the 3D Solar-Interplanetary (SIP) adaptive mesh refinement (AMR) space-time conservation element and solution element (CESE) MHD model (SIP-AMR-CESE MHD Model). To accommodate the observations, the tangential component of the electric field at the lower boundary is specified to allow the flux evolution to match the observed changes of magnetic field. Meanwhile, the time-dependent solar surface boundary conditions derived from the method of characteristics and the mass flux limit are incorporated to couple the observation and the 3D MHD model. The simulated evolution of the global coronal structure during 2007 is compared with solar observations and solar wind measurements from both Ulysses and spacecrafts near the Earth. The MHD-DUSM model is also validated by comparisons with the standard potential field source surface (PFSS) model, the newly improved Wang-Sheeley-Arge (WSA) empirical formula, and the MHD simulation with a monthly synoptic magnetogram (MHD-MSM). Comparisons show that the MHD-DUSM results have good overall agreement with coronal and interplanetary structures, including the sizes and distributions of coronal holes, the positions and shapes of the streamer belts, and the transitions of the solar wind speeds and magnetic field polarities. The MHD-DUSM results also display many features different from those of the PFSS, the WSA, and the MHD-MSM models.

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

    PubMed

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

    1982-01-01

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

  11. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  13. 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.

  14. 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

  15. 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

  16. 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.

  17. Comparisons of corrected daily integrated erythemal UVR from the U.S. EPA/UGA network of Brewer spectroradiometers with model and satellite data

    NASA Astrophysics Data System (ADS)

    Sabburg, Jeff; Kimlin, Michael G.; Rives, John E.; Meltzer, Richard S.; Taylor, Thomas E.; Schmalzle, Gina; Zheng, Sherry; Huang, Nancy; Wilson, Andrew R.; Udelhofen, Petra M.

    2002-01-01

    A network of 21 Brewer spectroradiometers, owned by the U.S. Environmental Protection Agency and operated by the University of Georgia, is measuring UV spectral irradiances throughout the United States. Corrections to the raw data have now been implemented. These corrections include (1) 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 optical changes in the 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%. Application of these corrections brings the errors of the absolute irradiance values to approximately +/- 5 to 7% for all sources of error. Comparisons of corrected daily integrated erythemal UVR data (DUV) to model and TOMS- inferred values are performed for sites at Acadia National Park, Bigbend National Park, Everglades National Park and the Virgin Islands. All sites show very good agreement with the TUVSPEC model but comparison with TOMS-inferred DUV values indicate a 10-20% overestimate by TOMS for the four sites.

  18. 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.

  19. 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…

  20. 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

  1. 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 ...

  2. 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.…

  3. 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

  4. Treatment of chemotherapy-induced neutropenia in a rat model by using multiple daily doses of oral administration of G-CSF-containing nanoparticles.

    PubMed

    Su, Fang-Yi; Chuang, Er-Yuan; Lin, Po-Yen; Chou, Yi-Chun; Chen, Chiung-Tong; Mi, Fwu-Long; Wey, Shiaw-Pyng; Yen, Tzu-Chen; Lin, Kun-Ju; Sung, Hsing-Wen

    2014-04-01

    Chemotherapy-induced neutropenia often increases the likelihood of life-threatening infections. In this study, a nanoparticle (NP) system composed of chitosan and poly(γ-glutamic acid) conjugated with diethylene triamine pentaacetic acid (γPGA-DTPA) was prepared for oral delivery of granulocyte colony-stimulating factor (G-CSF), a hematopoietic growth factor. The therapeutic potential of this NP system for daily administration of G-CSF to treat neutropenia associated with chemotherapy was evaluated in a rat model. In vitro results indicate that the procedures of NP loading and release preserved the structural integrity and bioactivity of the G-CSF molecules adequately. Those results further demonstrated the enzymatic inhibition activity of γPGA-DTPA towards G-CSF against intestinal proteases. Additionally, the in vivo biodistribution study clearly identified accumulations of G-CSF in the heart, liver, bone marrow, and urinary bladder, an indication of systemic absorption of G-CSF; its relative bioavailability was approximately 13.6%. Moreover, significant glucose uptake was observed in bone marrow during G-CSF treatment, suggesting increased bone marrow metabolism and neutrophil production. Consequently, neutrophil count in the blood increased in a sustained manner; this fact may help a patient's immune system recover from the side effects of chemotherapy.

  5. 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.

  6. 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

  7. 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

  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. 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.

  10. 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.

  11. 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

  12. 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:  ...

  13. 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:  ...

  14. The effect of personality on daily life emotional processes.

    PubMed

    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.

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

    PubMed

    Thrush, M A; Peeler, E J

    2013-10-01

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

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

    PubMed

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

    2015-08-01

    High temperatures have negative effects on sperm quality leading to temporary or permanent sterility. The aim of the study was to assess the effect of long exposure to summer circadian heat stress cycles on sperm parameters and the motile subpopulation structure of epididymal sperm cells from rabbit bucks. Twelve White New Zealand rabbit bucks were exposed to a daily constant temperature of the thermoneutral zone (from 18 °C to 22 °C; control group) or exposed to a summer circadian heat stress cycles (30 °C, 3 h/day; heat stress group). Spermatozoa were flushed from the epididymis and assessed for sperm quality parameters at recovery. Sperm total motility and progressivity were negatively affected by high temperatures (P < 0.05), as were also specific motility parameters (curvilinear velocity, linear velocity, mean velocity, straightness coefficient, linearity coefficient, wobble coefficient, and frequency of head displacement; P < 0.05, but not the mean amplitude of lateral head displacement). Heat stress significantly increased the percentage of less-motile sperm subpopulations, although the percentage of the high-motile subpopulation was maintained, which is consistent with the fact that no effect was detected on fertility rates. However, prolificacy was reduced in females submitted to heat stress when inseminated by control bucks. In conclusion, our results suggest that environmental high temperatures are linked to changes in the proportion of motile sperm subpopulations of the epididymis, although fertility is still preserved despite the detrimental effects of heat stress. On the other hand, prolificacy seems to be affected by the negative effects of high temperatures, especially by altering female reproduction. PMID:25944779

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

    PubMed

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

    2015-08-01

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

  18. Daily rhythms of serotonin metabolism and the expression of clock genes in suprachiasmatic nucleus of rotenone-induced Parkinson's disease male Wistar rat model and effect of melatonin administration.

    PubMed

    Mattam, Ushodaya; Jagota, Anita

    2015-02-01

    The circadian system in suprachiasmatic nucleus (SCN) involves regulated serotonin levels and coordinated expression of various clock genes. To understand circadian disfunction in the age-related neurodegenerative disorder Parkinson's disease (PD), the rotenone-induced PD (RIPD) male Wistar rat model was used. The alterations in the rhythmic dynamic equilibrium of interactions between the various components of serotonin metabolism and the molecular clock were measured. There was significant decrease in the mean 24 h levels of tryptophan, 5-hydroxytryptophan (5-HTP), serotonin (5-HT), N-acetyl serotonin (NAS) and melatonin (MEL) by approximately 63, 51, 76 and 96% respectively ( p ≤ 0.05). However significant increase in 5-methoxy indole acetic acid (5-MIAA), 5-methoxy tryptophol (5-MTOH), 5-hydroxy tryptophol (5-HTOH) indicated increased serotonin catabolism with the abolition of daily rhythms of MEL, 5-HTP and 5-MIAA in RIPD. 24 h mean levels of rPer1, rCry1, rBmal1 reduced by about 0.5, 0.74 and 0.39-fold and increased for rPer2 by about 1.7-fold. The daily pulse of rPer2, rCry1, rCry2 and rBmal1 significantly decreased by 0.36, 0.6, 0.14, 0.1 and 0.2-fold. As melatonin, an antioxidant and an endogenous synchronizer of rhythm declined in RIPD male Wistar rat model, the effects of melatonin-administration on the rhythmic expression of various clock genes were studied. Interestingly, melatonin-administration resulted in restoration of the phase of rPer1 daily rhythm in RIPD indicating differential sensitivity of various clock components towards melatonin. The animals which were administered both rotenone and MEL for 48 days interestingly showed neuroprotective effects in dark phase on correlations between expression of various genes.

  19. 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.

  20. 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…

  1. 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

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

    PubMed

    Yao, Jiayun; Henderson, Sarah B

    2014-01-01

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

  3. 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

  4. 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…

  5. News Values and Country Non-Daily Reporting.

    ERIC Educational Resources Information Center

    Vines, Josie

    2001-01-01

    Suggests Australia's country, non-daily newspapers present journalism graduates with excellent opportunities to experience a wide range of journalistic responsibilities and compile an impressive portfolio. Argues the need for the news values of these newspapers to be integrated into pedagogical models. Documents the country non-daily's news…

  6. 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...

  7. 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...

  8. 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.

  9. Influence of climate model biases and daily-scale temperature and precipitation events on hydrological impacts assessment: A case study of the United States

    SciTech Connect

    Ashfaq, Moetasim; Bowling, Laura C.; Cherkauer, Keith; Pal, Jeremy; Diffenbaugh, Noah

    2010-01-01

    The Intergovernmental Panel on Climate Change's Fourth Assessment Report concludes that climate change is now unequivocal, and associated increases in evaporation and atmospheric water content could intensify the hydrological cycle. However, the biases and coarse spatial resolution of global climate models limit their usefulness in hydrological impact assessment. In order to reduce these limitations, we use a high-resolution regional climate model (RegCM3) to drive a hydrological model (variable infiltration capacity) for the full contiguous United States. The simulations cover 1961-1990 in the historic period and 2071-2100 in the future (A2) period. A quantile-based bias correction technique is applied to the times series of RegCM3-simulated precipitation and temperature. Our results show that biases in the RegCM3 fields not only affect the magnitude of hydrometeorological variables in the baseline hydrological simulation, but they also affect the response of hydrological variables to projected future anthropogenic increases in greenhouse forcing. Further, we find that changes in the intensity and occurrence of severe wet and hot events are critical in determining the sign of hydrologic change. These results have important implications for the assessment of potential future hydrologic changes, as well as for developing approaches for quantitative impacts assessment.

  10. A simple flow balance model for engineering design and daily operational use of sewage treatment lagoons at the Nevada Test Site

    SciTech Connect

    Lindstrom, F.T.; Bielawski, J.P.

    1994-07-01

    Thirteen waste-water lagoon treatment sites currently exist on the Nevada Test Site (NTS). These treatment and disposal sites were originally subjected to engineering criteria which were acceptable to the state of Nevada Division of Environmental Protection (NDEP). New requirements which mandate the implementation of a methodology which would protect the groundwater at each facility were recently established by the NDEP, even though vadose zones are anticipated to be several hundred feet in depth at all locations. A simple, but useful, near-surface hydrological and atmospheric flow balance model was constructed to aid in these and any future assessments. The major features of the model are: infiltration through the bottom and wetted sides of the treatment lagoon or disposal basin; evaporation from the surface of the treatment or disposal lagoon; time variant influent flow rates; and instantaneous time rate of change of volume of waste-water in the treatment or disposal lagoon. The underlying lagoon/basin geometry is that of an inverted frustum of a right tetrahedron whose wall slopes and bottom dimensions are user specified.

  11. 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…

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. The Sub-Daily Distribution of Snowmelt

    NASA Astrophysics Data System (ADS)

    Webb, R.; Gooseff, M. N.; Fassnacht, S. R.

    2015-12-01

    The hydrologic cycle in many mountainous headwaters around the world have snowmelt dominated hydrographs. In addition to water resources for communities and ecosystems, high rates of snowmelt can cause flooding that results in damages to infrastructure. The standard in the United States flood forecasting looks primarily at rainfall estimates but lacks estimates for high rates of snowmelt in regions such as the Southern Rocky Mountains. Recent studies have shown that events such as a 10 year 24 hour snowmelt event is as much as 45% greater than the same recurrence interval rain event. Additionally, this 24 hour snowmelt likely occurs over a much shorter time period due to snowmelt being primarily driven by solar radiation. This study presents and tests a sub-daily temporal distribution of snowmelt. The snowmelt distribution presented herein is tested against hourly data for known daily melt rates from snow telemetry (SNOTEL) stations, and then for conditions when weekly or bi-weekly snow loss is known. It is additionally utilized for modeling a one-dimensional soil profile for infiltration across the soil-snow interface. The intent of this study is to create a less computationally intensive method than the mass energy approach and improve upon the simple degree-day method for the representation of snowmelt at sub-daily time steps. This can be used for streamflow, groundwater recharge, soil moisture distribution, and other land surface modeling efforts. Results of the study display strong agreement with hourly SNOTEL data from Colorado Front Range stations for an assumed 8-hour melt period. Peak flow estimates from snowmelt driven floods could be estimated from long-term datasets to calculate frequency of these flood events. Further application of this sub-daily distribution of snowmelt could be for partially or fully glaciated watersheds with modifications for differences in latitude and/or elevation causing longer or shorter periods of melt per day.

  17. 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.

  18. 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

  19. 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.

  20. 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.

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

    PubMed

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

    2005-04-01

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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. Dapagliflozin twice daily or once daily: effect on pharmacokinetics and urinary glucose excretion in healthy subjects.

    PubMed

    Tang, W; Reele, S; Hamer-Maansson, J E; Parikh, S; de Bruin, T W A

    2015-04-01

    The primary objective of this single-centre, open-label crossover study (NCT01072578) was to assess the effect of dapagliflozin on the amount of glucose in the blood and urine in healthy volunteers when dapagliflozin was administered once a day (10 mg) versus twice a day (5 mg every 12 h) after 5 days of dosing. At steady state, the AUC(ss)₀₋₂₄ (area under the dapagliflozin curve (0-24 hours) at steady state), C(ss,av) (average concentration at steady state) between dapagliflozin 5 mg twice daily and 10 mg once daily were similar AUC(ss)₀₋₂₄ [5 mg bid, (458.0 (28.7)) and 10 mg qd, (470.0 (28.5))] and C(ss,av) [5 mg bid 18.8 (28.9)) and 10 mg qd, (19.6(28.5))], but minimum and maximum plasma levels of dapagliflozin differed significantly. Percent inhibition of renal glucose reabsorption (%IRGRA) and total urinary glucose excretion over 24 h were similar for both doses. The relationship between the mean dapagliflozin concentration and %IRGRA and the total urinary glucose excreted was well described by a maximum effect model. The results indicate that dapagliflozin may be used for either once daily or twice daily administration.

  11. Ruminative self-focus in daily life: associations with daily activities and depressive symptoms.

    PubMed

    Takano, Keisuke; Sakamoto, Shinji; Tanno, Yoshihiko

    2013-08-01

    The present study examined the situations and conditions in which ruminative self-focus is less likely to occur in daily life. Previous researchers have described a mood-brightening effect of depression, where depressed individuals exhibit greater positive emotional reactivity to positive daily events than do nondepressed individuals. To better understand this paradoxical effect, we investigated the moderating role of depression in the relationship between daily activities and ruminative thinking. Forty-one Japanese undergraduates (9 women and 32 men) recorded their thought contents and the type and subjective appraisals of activities that they engaged in 8 times a day for a week at semirandom intervals. Multilevel modeling analyses indicated that subjectively pleasant activities were associated with improved mood states and reduced ruminative thinking. However, some of these associations were moderated by depressive symptoms, suggesting that individuals with higher levels of depression showed a greater reduction of ruminative thinking during pleasant activities. These results imply that daily activities are important for reducing rumination, particularly for individuals with higher levels of depression, and that the brightening effect of depression is evident for cognitive as well as emotional activities. The cognitive basis of this paradoxical effect is discussed. PMID:23527502

  12. 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

  13. 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.

  14. 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.

  15. WAPA Daily Energy Accounting Activities

    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

  16. 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…

  17. A statistical analysis of the daily streamflow hydrograph

    NASA Astrophysics Data System (ADS)

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

    1984-03-01

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

  18. 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

  19. 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.

  20. 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) ...

  1. 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…

  2. The Daily Practices of Successful Principals

    ERIC Educational Resources Information Center

    Brock, Barbara L.; Grady, Marilyn L.

    2011-01-01

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

  3. 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

  4. 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...

  5. Ozone and daily mortality in Shanghai, China

    SciTech Connect

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

    2006-08-15

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

  6. 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

  7. Daily regulation of hormone profiles.

    PubMed

    Kalsbeek, Andries; Fliers, Eric

    2013-01-01

    The highly coordinated output of the hypothalamic biological clock does not only govern the daily rhythm in sleep/wake (or feeding/fasting) behaviour but also has direct control over many aspects of hormone release. In fact, a significant proportion of our current understanding of the circadian clock has its roots in the study of the intimate connections between the hypothalamic clock and multiple endocrine axes. This chapter will focus on the anatomical connections used by the mammalian biological clock to enforce its endogenous rhythmicity on the rest of the body, using a number of different hormone systems as a representative example. Experimental studies have revealed a highly specialised organisation of the connections between the mammalian circadian clock neurons and neuroendocrine as well as pre-autonomic neurons in the hypothalamus. These complex connections ensure a logical coordination between behavioural, endocrine and metabolic functions that will help the organism adjust to the time of day most efficiently. For example, activation of the orexin system by the hypothalamic biological clock at the start of the active phase not only ensures that we wake up on time but also that our glucose metabolism and cardiovascular system are prepared for this increased activity. Nevertheless, it is very likely that the circadian clock present within the endocrine glands plays a significant role as well, for instance, by altering these glands' sensitivity to specific stimuli throughout the day. In this way the net result of the activity of the hypothalamic and peripheral clocks ensures an optimal endocrine adaptation of the metabolism of the organism to its time-structured environment. PMID:23604480

  8. Generating Multiyear Gridded Daily Rainfall over New Zealand.

    NASA Astrophysics Data System (ADS)

    Tait, Andrew; Turner, Richard

    2005-09-01

    Daily rainfall totals are a key input for hydrological models that are designed to simulate water and pollutant flow through both soil and waterways. Within New Zealand there are large areas and many river catchments where no long-term rainfall observations exist. A method for estimating daily rainfall over the whole of New Zealand on a 5-km grid is described and tested over a period from January 1985 to April 2002. Improvement over a spatial interpolation method was gained by scaling high-elevation rainfall estimates using simulated mesoscale model rainfall surfaces that are generated for short periods in 1994 and 1996. This method is judged to produce reasonable and useful estimates of daily rainfall.

  9. 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

  10. 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

  11. Forecasting of daily air quality index in Delhi.

    PubMed

    Kumar, Anikender; Goyal, P

    2011-11-15

    As the impact of air pollutants on human health through ambient air address much attention in recent years, the air quality forecasting in terms of air pollution parameters becomes an important topic in environmental science. The Air Quality Index (AQI) can be estimated through a formula, based on comprehensive assessment of concentration of air pollutants, which can be used by government agencies to characterize the status of air quality at a given location. The present study aims to develop forecasting model for predicting daily AQI, which can be used as a basis of decision making processes. Firstly, the AQI has been estimated through a method used by US Environmental Protection Agency (USEPA) for different criteria pollutants as Respirable Suspended Particulate Matter (RSPM), Sulfur dioxide (SO2), Nitrogen dioxide (NO2) and Suspended Particulate Matter (SPM). However, the sub-index and breakpoint concentrations in the formula are made according to Indian National Ambient Air Quality Standard. Secondly, the daily AQI for each season is forecasted through three statistical models namely time series auto regressive integrated moving average (ARIMA) (model 1), principal component regression (PCR) (model 2) and combination of both (model 3) in Delhi. The performance of all three models are evaluated with the help of observed concentrations of pollutants, which reflects that model 3 agrees well with observed values, as compared to the values of model 1 and model 2. The same is supported by the statistical parameters also. The significance of meteorological parameters of model 3 has been assessed through principal component analysis (PCA), which indicates that daily rainfall, station level pressure, daily mean temperature, wind direction index are maximum explained in summer, monsoon, post-monsoon and winter respectively. Further, the variation of AQI during the weekends (holidays) and weekdays are found negligible. Therefore all the days of week are accounted same in

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

    ERIC Educational Resources Information Center

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

    2013-01-01

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

  13. 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.

  14. Techniques for Daily Living: Curriculum Guides.

    ERIC Educational Resources Information Center

    Wooldridge, Lillian; And Others

    Presented are specific guides concerning techniques for daily living which were developed by the child care staff at the Illinois Braille and Sight Saving School. The guides are designed for cottage parents of the children, who may have both visual and other handicaps, and show what daily living skills are necessary and appropriate for the…

  15. Daily Stressors in Primary Education Students

    ERIC Educational Resources Information Center

    Fernández-Baena, F. Javier; Trianes, María V.; Escobar, Milagros; Blanca, María J.; Muñoz, Ángela M.

    2015-01-01

    Daily stress can have a bearing on children's emotional and academic development. This study aimed to assess daily stressors and to determine their prevalence among primary education students, taking into account their gender, academic year, social adaptation, and the school location. A sample of 7,354 Spanish schoolchildren aged between 6…

  16. Daily Spiritual Experiences and Prosocial Behavior

    ERIC Educational Resources Information Center

    Einolf, Christopher J.

    2013-01-01

    This paper examines how the Daily Spiritual Experiences Scale (DSES) relates to range of prosocial behaviors, using a large, nationally representative U.S. data set. It finds that daily spiritual experiences are a statistically and substantively significant predictor of volunteering, charitable giving, and helping individuals one knows personally.…

  17. 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…

  18. 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....

  19. 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....

  20. 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....

  1. 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....

  2. 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....

  3. A daily diary assessment of female weight stigmatization.

    PubMed

    Seacat, Jason D; Dougal, Sarah C; Roy, Dooti

    2016-02-01

    Research focused on assessing weight stigmatization has typically been conducted using cross-sectional, retrospective designs. Such designs may impair the scientific understanding of this stigma by limiting participants' recall of frequencies and/or details about stigmatizing events. To address this, 50 overweight/obese women were recruited from public weight forums to complete week-long daily diaries. A total of 1077 weight-stigmatizing events were reported on the Stigmatizing Situations Inventory. Hierarchical linear modeling was used to investigate potential relationships between participant-level factors and reported stigmatization. Results indicate that body mass index, education, age, daily activities, and interpersonal interactions all may impact individuals' levels of stigmatization.

  4. 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

  5. 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.

  6. Daily rhythm of nociception in rats.

    PubMed

    Christina, AJM; Merlin, NJ; Vijaya, C; Jayaprakash, S; Murugesh, N

    2004-03-25

    BACKGROUND: Many behavioral and physiological variables exhibit daily rhythmicity. Few investigations of the daily rhythmicity in nociception have been conducted, and conflicting results have been obtained. The present study evaluated the daily rhythmicity in nociception in Wistar rats. METHODS: Nociception was investigated by Eddy's hot plate method, tail immersion method, and tail clip method. The latency between the noxious stimulus and the animal's response was recorded as reaction time. Separate groups of rats were tested in 4-hour intervals for 24 hours. RESULTS: There was clear daily variation in response latency. Reaction time was shortest a few hours before lights-on and longest at the light-dark transition. CONCLUSION: Nociception exhibits robust daily rhythmicity in rats. Sensitivity to pain is highest late in the dark phase of the light-dark cycle and lowest at the light-dark transition.

  7. Daily rhythm of nociception in rats

    PubMed Central

    Christina, AJM; Merlin, NJ; Vijaya, C; Jayaprakash, S; Murugesh, N

    2004-01-01

    Background Many behavioral and physiological variables exhibit daily rhythmicity. Few investigations of the daily rhythmicity in nociception have been conducted, and conflicting results have been obtained. The present study evaluated the daily rhythmicity in nociception in Wistar rats. Methods Nociception was investigated by Eddy's hot plate method, tail immersion method, and tail clip method. The latency between the noxious stimulus and the animal's response was recorded as reaction time. Separate groups of rats were tested in 4-hour intervals for 24 hours. Results There was clear daily variation in response latency. Reaction time was shortest a few hours before lights-on and longest at the light-dark transition. Conclusion Nociception exhibits robust daily rhythmicity in rats. Sensitivity to pain is highest late in the dark phase of the light-dark cycle and lowest at the light-dark transition. PMID:15043763

  8. 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.

  9. 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…

  10. 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

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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...

  16. REL3.0 SW DAILY UTC

    Atmospheric Science Data Center

    2016-10-05

    ... Active Radiation Flux Cloud Fraction Cosine Solar Zenith Angle From Satellite Cosine Solar Zenith Angle From Astronomy ... ISCCP Data Table SSE Renewable Energy Readme Files:  Readme_3.0_sw_daily ...

  17. REL3.0 SW DAILY LOCAL

    Atmospheric Science Data Center

    2016-10-05

    ... Active Radiation Flux Cloud Fraction Cosine Solar Zenith Angle From Satellite Cosine Solar Zenith Angle From Astronomy ... ISCCP Data Table SSE Renewable Energy Readme Files:  Readme_3.0_sw_daily ...

  18. [Daily life disability associated with dementia].

    PubMed

    Asada, Takashi

    2013-01-01

    Daily life disability associated with dementia including Alzheimer disease involves a series of difficulties in performing daily tasks. People with this disability have difficulty in being active individually, participating in society, and carrying out daily tasks. Evidence suggests that its causes are lesions in specific areas of the brain. For example, focal lesions appear to be specifically correlated with symptoms of apraxia and agnosia. In general, cognitive decline in the course of dementing illnesses worsens as brain lesions expand. This may be accompanied by the impairment of other organs. However, brain lesions appear to be the overall cause of daily life disability associated with dementia. There are three basic measures that can be taken in response to daily life disability : first, analysis of normal daily life activities ; next, the observation of how the activities of people with dementia deviate from the normal pattern ; and finally, collecting information on caregivers' effective practices to appropriately respond to these deviations. Care for daily life disability associated with dementia should aim to maximize the performance of people with dementia based on their existing abilities. To do this, it is important to recognize disruptions to the normal flow of activity, and understand clues pointing to the causes of these disruptions. In order to examine the daily life disability associated with dementia, we conducted preliminary experiments on the background brain activity. For this purpose, capsaicin derived from red pepper was used to stimulate taste bud receptors on the tongue. During this physiological process, we examined the response within the brain, and observed activity in specific brain regions. For further studies on the background of the disability, we will use fMRI and magnetoencephalography.

  19. Associations among Daily Stressors and Salivary Cortisol: Findings from the National Study of Daily Experiences

    PubMed Central

    Stawski, Robert S.; Cichy, Kelly E.; Piazza, Jennifer R.; Almeida, David M.

    2013-01-01

    While much research has focused on linking stressful experiences to emotional and biological reactions in laboratory settings, there is an emerging interest in extending these examinations to field studies of daily life. The current study examined day-to-day associations among naturally-occurring daily stressors and salivary cortisol in a national sample of adults from the second wave of the National Study of Daily Experiences (NSDE). A sample of 1,694 adults (Age=57, Range=33–84; 44% male) completed telephone interviews detailing their stressors and emotions on eight consecutive evenings. Participants also provided saliva samples upon waking, 30 minutes post-waking, before lunch and before bed, on four consecutive interview days resulting in 5,995 days of interview/cortisol data. Analyses revealed three main findings. First, cortisol AUC was significantly higher on stressor days compared to stressor-free days, particularly for arguments and overloads at home, suggesting that daily stressors are associated with increased cortisol output, but that not all daily stressors have such an influence. Second, individuals reporting a greater frequency of stressor days also exhibited a steeper diurnal cortisol slope. Finally, daily stressor-cortisol associations were unaltered after adjustment for daily negative affect and physical symptoms. Our discussion focuses on the influence of naturally-occurring daily stressors on daily cortisol and the role of daily diary approaches for studying healthy cortisol responses to psychosocial stressors outside of traditional laboratory settings. PMID:23856186

  20. 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

  1. 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.

  2. 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.

  3. Ethnic identity and the daily psychological well-being of adolescents from Mexican and Chinese backgrounds.

    PubMed

    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 over the 2-week study period. Ethnic regard moderated the daily association between normative stressful demands and happiness, and between stressful demands and happiness experienced 1 day after stressors occurred. Moderating effects were significant even after controlling for self-esteem. Although no buffering effects of ethnic centrality were found, the results point to the positive influence of ethnic regard in the daily lives of adolescents from ethnic minority backgrounds.

  4. Ethnic identity and the daily psychological well-being of adolescents from Mexican and Chinese backgrounds.

    PubMed

    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 over the 2-week study period. Ethnic regard moderated the daily association between normative stressful demands and happiness, and between stressful demands and happiness experienced 1 day after stressors occurred. Moderating effects were significant even after controlling for self-esteem. Although no buffering effects of ethnic centrality were found, the results point to the positive influence of ethnic regard in the daily lives of adolescents from ethnic minority backgrounds. PMID:16999802

  5. Relationship of Dyadic Closeness with Work-Related Stress: A Daily Diary Study

    ERIC Educational Resources Information Center

    Lavee, Yoav; Ben-Ari, Adital

    2007-01-01

    We examined the association between work-related stress of both spouses and daily fluctuations in their affective states and dyadic closeness. Daily diary data from 169 Israeli dual-earner couples were analyzed using multilevel modeling. The findings indicate that work stress has no direct effect on dyadic closeness but rather is mediated by the…

  6. 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…

  7. Seasonal Variation in Daily Temperature Ranges.

    NASA Astrophysics Data System (ADS)

    Ruschy, David L.; Baker, Donald G.; Skaggs, Richard H.

    1991-12-01

    Abrupt spring and autumnal changes in the daily temperature range, from low winter values to higher nonwinter values, were noted in the Minneapolis-St. Paul temperature record. Since this feature was even more evident in five rural and small town Minnesota stations, it can be accepted as real.The inverse relationship found between surface albedo and the daily temperature range indicated that the reduced winter temperature range is associated with snow cover. A second factor controlling the temperature range is cloud cover. This led to the conclusion that variation in net solar radiation is the primary factor.A strong statistical relationship between daily temperature range and the three variables considered (solar radiation, albedo, and cloud cover) was limited to the spring and fall. In March-April the statistically significant factors were solar radiation and albedo, while in October-November they were solar radiation and cloud cover. For the October-December period albedo was also statistically important.

  8. New daily persistent headache: an update.

    PubMed

    Rozen, Todd D

    2014-07-01

    New daily persistent headache is a primary headache disorder marked by a unique temporal profile which is daily from onset. For many sufferers this is their first ever headache. Very little is known about the pathogenesis of this condition. It might be a disorder of abnormal glial activation with persistent central nervous system inflammation and it may be a syndrome that occurs in individuals who have a history of cervical hypermobility. At present there is no known specific treatment and many patients go for years to decades without any improvement in their condition despite aggressive therapy. This article will present an up-to-date overview of new daily persistent headache on the topics of clinical presentation, treatment, diagnostic criteria, and presumed pathogenesis. It will also provide some of the authors own treatment suggestions based on recognized triggering events and some suggestions for future clinical trials. PMID:24820732

  9. Daily estimates of soil ingestion in children.

    PubMed Central

    Stanek, E J; Calabrese, E J

    1995-01-01

    Soil ingestion estimates play an important role in risk assessment of contaminated sites, and estimates of soil ingestion in children are of special interest. Current estimates of soil ingestion are trace-element specific and vary widely among elements. Although expressed as daily estimates, the actual estimates have been constructed by averaging soil ingestion over a study period of several days. The wide variability has resulted in uncertainty as to which method of estimation of soil ingestion is best. We developed a methodology for calculating a single estimate of soil ingestion for each subject for each day. Because the daily soil ingestion estimate represents the median estimate of eligible daily trace-element-specific soil ingestion estimates for each child, this median estimate is not trace-element specific. Summary estimates for individuals and weeks are calculated using these daily estimates. Using this methodology, the median daily soil ingestion estimate for 64 children participating in the 1989 Amherst soil ingestion study is 13 mg/day or less for 50% of the children and 138 mg/day or less for 95% of the children. Mean soil ingestion estimates (for up to an 8-day period) were 45 mg/day or less for 50% of the children, whereas 95% of the children reported a mean soil ingestion of 208 mg/day or less. Daily soil ingestion estimates were used subsequently to estimate the mean and variance in soil ingestion for each child and to extrapolate a soil ingestion distribution over a year, assuming that soil ingestion followed a log-normal distribution. Images Figure 1. Figure 2. Figure 3. Figure 4. PMID:7768230

  10. 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

  11. 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…

  12. 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…

  13. 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...

  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, 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...

  17. 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...

  18. The Case for Daily Physical Education

    ERIC Educational Resources Information Center

    Lynn, Susan

    2007-01-01

    According to a recent study, only 56 percent of high school students participate in physical education, and the percentage of schools requiring physical education has progressively dropped. The goal of providing daily physical education to all K-12 students in the United States presents challenges such as budgetary issues, less time for other…

  19. 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...

  20. 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.

  1. 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

  2. Daily patterns of CO2 in the lower atmosphere of a rural site

    NASA Astrophysics Data System (ADS)

    Pérez, Isidro A.; Sánchez, M. Luisa; García, M. Ángeles; Pardo, Nuria

    2015-10-01

    This paper investigates patterns of daily evolutions of CO2 in the lower atmosphere at a rural site over 2 years. The first part is devoted to observation analysis using a clustering procedure. However, direct application of the average-linkage method yielded undesirable results. In order to improve this procedure, data were previously processed using three smoothing procedures: the kernel smoothing method, the elliptical procedure, and the second-order cylindrical model. These procedures successfully revealed that clusters were based on daily concentration and range. However, the unequal distribution of frequencies in the clusters proved to be a noticeable disadvantage. Four alternative and simpler schemes for grouping observations were proposed in the second part of this paper. The first, comprising groups following fixed values of daily range and mean concentration, provided a sharp contrast between spring, with a marked daily cycle linked to the biological peak, and summer with a smooth daily cycle and low concentration when the biological minimum was reached. The second scheme is based on isopleth analysis and considers observation groups of similar frequencies following an increasing order of mean concentration and daily range. As a result, seasonal evolution was less marked. Straight lines were the borders for groups in the third scheme, which was similar and simpler than the second. The final scheme divided observations by means of equations of daily range as a quadratic function of daily concentration. The groups formed may be linked to seasons, with the group prevailing in summer presenting a noticeable daily range.

  3. A daily diary assessment of female weight stigmatization.

    PubMed

    Seacat, Jason D; Dougal, Sarah C; Roy, Dooti

    2016-02-01

    Research focused on assessing weight stigmatization has typically been conducted using cross-sectional, retrospective designs. Such designs may impair the scientific understanding of this stigma by limiting participants' recall of frequencies and/or details about stigmatizing events. To address this, 50 overweight/obese women were recruited from public weight forums to complete week-long daily diaries. A total of 1077 weight-stigmatizing events were reported on the Stigmatizing Situations Inventory. Hierarchical linear modeling was used to investigate potential relationships between participant-level factors and reported stigmatization. Results indicate that body mass index, education, age, daily activities, and interpersonal interactions all may impact individuals' levels of stigmatization. PMID:24648323

  4. 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.

  5. Heavy metals in common foodstuff: Daily intake

    SciTech Connect

    Tsoumbaris, P.; Tsoukali-Papadopoulou, H. )

    1994-07-01

    Lately, toxic effects of some heavy metals (Pb, Cd) as well as desirable ones of some others (Ni, Mn, Zn) have been a field of thorough investigation. The main way of human body fortification in metals is through foodchain depending on the kind and quantity of the consumed food, according to dietary habits. The purpose of this study is the calculation of metals daily intake through common foodstuff of Greek inhabitants. The calculation is based on results from quantitative analysis of Pb, Cd, Ni, Mn, and Zn in common foodstuff from the market of the city of Thessaloniki. The daily food consumption data is derived from three sources: (a) answers to a questionnaire distributed to families of the city of Thessaloniki, (b) nutrition data provided by the Agricultural Bank of Greece and (c) nutrition data according to international bibliography.

  6. Daily rhythms in plasma levels of homocysteine

    PubMed Central

    Lavie, Lena; Lavie, Peretz

    2004-01-01

    Background There is accumulated evidence that plasma concentration of the sulfur-containing amino-acid homocysteine (Hcy) is a prognostic marker for cardiovascular morbidity and mortality. Both fasting levels of Hcy and post methionine loading levels are used as prognostic markers. The aim of the present study was to investigate the existence of a daily rhythm in plasma Hcy under strictly controlled nutritional and sleep-wake conditions. We also investigated if the time during which methionine loading is performed, i.e., morning or evening, had a different effect on the resultant plasma Hcy concentration. Methods Six healthy men aged 23–26 years participated in 4 experiments. In the first and second experiments, the daily rhythm in Hcy as well as in other amino acids was investigated under a normal or an inverse sleep-wake cycle. In the third and fourth, Hcy concentrations were investigated after a morning and evening methionine loading. To standardize food consumption in the first two experiments, subjects received every 3 hours 150 ml of specially designed low-protein liquid food (Ensure® formula). Results In both the first and second experiments there was a significant daily rhythm in Hcy concentrations with a mid-day nadir and a nocturnal peak. Strikingly different 24-h patterns were observed in methionine, leucine, isoleucine and tyrosine. In all, the 24-h curves revealed a strong influence of both the sleep-wake cycle and the feeding schedule. Methionine loading resulted in increased plasma Hcy levels during both morning and evening experiments, which were not significantly different from each other. Conclusions There is a daily rhythm in plasma concentration of the amino acid Hcy, and this rhythm is independent of sleep-wake and food consumption. In view of the fact that increased Hcy concentrations may be associated with increased cardiovascular risks, these findings may have clinical implications for the health of rotating shift workers. PMID:15347422

  7. 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

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

    PubMed Central

    Moschetti, Alessandra; Fiorini, Laura; Esposito, Dario; Dario, Paolo; Cavallo, Filippo

    2016-01-01

    Recognition of activities of daily living plays an important role in monitoring elderly people and helping caregivers in controlling and detecting changes in daily behaviors. Thanks to the miniaturization and low cost of Microelectromechanical systems (MEMs), in particular of Inertial Measurement Units, in recent years body-worn activity recognition has gained popularity. In this context, the proposed work aims to recognize nine different gestures involved in daily activities using hand and wrist wearable sensors. Additionally, the analysis was carried out also considering different combinations of wearable sensors, in order to find the best combination in terms of unobtrusiveness and recognition accuracy. In order to achieve the proposed goals, an extensive experimentation was performed in a realistic environment. Twenty users were asked to perform the selected gestures and then the data were off-line analyzed to extract significant features. In order to corroborate the analysis, the classification problem was treated using two different and commonly used supervised machine learning techniques, namely Decision Tree and Support Vector Machine, analyzing both personal model and Leave-One-Subject-Out cross validation. The results obtained from this analysis show that the proposed system is able to recognize the proposed gestures with an accuracy of 89.01% in the Leave-One-Subject-Out cross validation and are therefore promising for further investigation in real life scenarios. PMID:27556473

  9. Smoking patterns and stimulus control in intermittent and daily smokers.

    PubMed

    Shiffman, Saul; Dunbar, Michael S; Li, Xiaoxue; Scholl, Sarah M; Tindle, Hilary A; Anderson, Stewart J; Ferguson, Stuart G

    2014-01-01

    Intermittent smokers (ITS) - who smoke less than daily - comprise an increasing proportion of adult smokers. Their smoking patterns challenge theoretical models of smoking motivation, which emphasize regular and frequent smoking to maintain nicotine levels and avoid withdrawal, but yet have gone largely unexamined. We characterized smoking patterns among 212 ITS (smoking 4-27 days per month) compared to 194 daily smokers (DS; smoking 5-30 cigarettes daily) who monitored situational antecedents of smoking using ecological momentary assessment. Subjects recorded each cigarette on an electronic diary, and situational variables were assessed in a random subset (n=21,539 smoking episodes); parallel assessments were obtained by beeping subjects at random when they were not smoking (n=26,930 non-smoking occasions). Compared to DS, ITS' smoking was more strongly associated with being away from home, being in a bar, drinking alcohol, socializing, being with friends and acquaintances, and when others were smoking. Mood had only modest effects in either group. DS' and ITS' smoking were substantially and equally suppressed by smoking restrictions, although ITS more often cited self-imposed restrictions. ITS' smoking was consistently more associated with environmental cues and contexts, especially those associated with positive or "indulgent" smoking situations. Stimulus control may be an important influence in maintaining smoking and making quitting difficult among ITS.

  10. Scenarios of daily extreme precipitation under climate change

    NASA Astrophysics Data System (ADS)

    Michael, Hofstätter; Christoph, Matulla; Jiafeng, Wang

    2010-05-01

    Daily extreme precipitation events under climate change conditions are the focus of research in our study. Such events can have considerable impacts on wealth and society by causing floodings or mudslides for example. In our study we used daily records of precipitation at 50 stations over Austria covering the period 1963-2006. To calculate the adequate timeseries for the future considering IPCC's climate change scenarios A1B and B1, we applied the analog method. Daily fields of Sea Level Pressure from the NCAR/NCEP1 Reanalysis within the region of Europe (20W-35E/30S-65N), served as the prime predictor between local scale observations and climate simulations out of the MPI-ECHAM5 model. Several return values were determined by fitting a GEV distribution to the timeseries consisting of the three most extreme, declustered events per year. The results reveal that future changes of 20y-return values are within +/-20% for most stations, whereby the signal of change is stronger for the first period (2007-2050) as compared to the later one (2051-2094). This is valid for both IPCC scenarios. We conclude, that even in the relatively small area of Austria both the sign and rate of change in future extreme precipitation, offers a clear diversity among climatological regions. This implies an important aspect for forthcoming studies.

  11. 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.

  12. 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

  13. 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.

  14. Associative and spontaneous appraisal processes independently contribute to anger elicitation in daily life.

    PubMed

    Wilkowski, Benjamin M; Robinson, Michael D

    2010-04-01

    There has been a great deal of debate concerning the antecedents of anger, with appraisal theorists emphasizing the role of hostile interpretations and cognitive neo-associationistic theorists emphasizing the role of more basic associative processes. Recently, theorists have sought to reconcile these views by acknowledging the role of both associative and inferential processes, and the current investigation drew upon recent social-cognitive research to test this compromise. Individual differences in hostile inferences and associations were assessed in an implicit cognitive paradigm, and relevant outcomes were assessed in a daily diary protocol. Implicit hostile inferences predicted both anger and aggression in daily life, and such relationships were mediated by propensities toward hostile interpretations in daily life. Hostile associations also predicted anger in daily life, but this relationship proved to be independent of daily hostile interpretations. Results therefore support a model that acknowledges the role of both associative and appraisal processes in anger elicitation.

  15. Loneliness, Daily Pain, and Perceptions of Interpersonal Events in Adults with Fibromyalgia

    PubMed Central

    Wolf, Laurie Dempsey; Davis, Mary C.

    2014-01-01

    Objective This study examined whether individual differences in loneliness and/or daily exacerbations in loneliness relate to daily pain and frequency and perception of interpersonal events among individuals with fibromyalgia (FM). Methods 118 participants with FM completed electronic diaries each evening for 21 days to assess the occurrence of positive and negative interpersonal events, event appraisals, and pain. Multilevel modeling was used to examine relations of chronic and transitory loneliness to daily life outcomes, controlling for daily depressive symptoms. Results Chronic and transitory loneliness were associated with more frequent reports of negative and less frequent reports of positive interpersonal daily events, higher daily stress ratings and lower daily enjoyment ratings, and higher daily pain levels. Neither chronic nor transitory loneliness moderated the relations between daily negative events and either stress appraisals or pain. However, both chronic and transitory loneliness moderated the relation between daily positive events and enjoyment appraisals. Specifically, on days of greater numbers of positive events than usual, lonely people had larger boosts in enjoyment than did nonlonely people. Similarly, days with greater than usual numbers of positive events were related to larger boosts in enjoyment if an individual was also experiencing higher than usual loneliness levels. Conclusions Chronic and transient episodes of loneliness are associated with more negative daily social relations and pain. However, boosts in positive events yield greater boosts in day-to-day enjoyment of social relations for lonely versus nonlonely individuals, and during loneliness episodes, a finding that can inform future interventions for individuals with chronic pain. PMID:25180546

  16. 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.

  17. 20 CFR 330.3 - Daily rate of compensation.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Daily rate of compensation. 330.3 Section 330... INSURANCE ACT DETERMINATION OF DAILY BENEFIT RATES § 330.3 Daily rate of compensation. (a) Definition. An employee's daily rate of compensation is his or her straight-time rate of pay, including any...

  18. Air pollution and daily mortality in Rome, Italy

    PubMed Central

    Michelozzi, P.; Forastiere, F.; Fusco, D.; Perucci, C. A.; Ostro, B.; Ancona, C.; Pallotti, G.

    1998-01-01

    OBJECTIVES: To assess the relation between several daily indicators of air pollution (particulates and gases) and daily mortality in the metropolitan area of Rome and in the central part of the city. METHODS: Time series analysis. The associations between daily concentrations of pollutants (particles, SO2, NO2, CO, O3) recorded by five fixed monitors and daily total mortality in the period from January 1992 to June 1995 were evaluated. The analysis included examination of the pollution effect on mortality by place of residence within the metropolitan area, by season, age, place of death (in and out a hospital), and cause of death (cardiovascular and respiratory disease). The Poisson model included loses smooth functions of the day of study, mean temperature, mean humidity, and indicator variables for day of the week and holidays. RESULTS: The mean daily number of deaths was 56.9 (44.8 among people > or = 65 years old). A mean of 36.3 deaths occurred in the city centre; 37.3 deaths a day were recorded in a hospital. Total mortality was significantly associated with a 10 micrograms/m3 increase in particles (0.4%) on that day (log 0), and with a 10 micrograms/m3 increase in NO2 at lag 1 (0.3%) and lag 2 (0.4%) (1 and 2 days before, respectively). The effect of particles (lag 0) and of NO2 (lag 2) on total mortality was higher among those living in the city centre (0.7% and 0.5%, respectively). The risk estimates were higher in the warmer season (1.0% and 1.1%, respectively), whereas no difference was found for those dying in or out of the hospital. The effect of particles was robust to a sensitivity analysis and to the inclusion of NO2 in the regression model. CONCLUSIONS: Increase in particulates and NO2, generated by the same mobile combustion sources, is associated with a short term increase in mortality in Rome. The effect is more evident among residents in the city centre, where the levels of exposure to pollutants recorded by fixed monitors are probably more

  19. 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

  20. 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.

  1. Difference in nephrotoxicity of vancomycin administered once daily and twice daily in rats.

    PubMed

    Konishi, Hiroki; Morita, Yukiko; Mizumura, Miyo; Iga, Ikumi; Nagai, Katsuhito

    2013-10-01

    We compared the degree of nephrotoxicity of vancomycin (VCM) administered once daily and twice daily in rats. VCM was intraperitoneally administered once daily to rats at a dose of 400 mg/kg (VCM-1-treated) or administered at a dose of 200 mg/kg twice daily at 12-hour intervals (VCM-2-treated) for 7 consecutive days. Creatinine clearance was decreased more markedly in VCM-1 rats relative to VCM-2 rats, although there was no significant difference in renal accumulation of VCM between the two groups. Renal superoxide dismutase activity was lower in VCM-1 rats than that in VCM-2 rats. The magnitude of histological change in kidney tissue was in agreement with the degree of alterations in the abovementioned biochemical values. These results suggest that the nephrotoxic effect of once-daily VCM administration is more pronounced than that of the twice-daily treatment. Our findings provide fundamental evidence for the advantage in choosing a divided VCM administration to attenuate nephrotoxicity.

  2. Parameterization of daily solar global ultraviolet irradiation.

    PubMed

    Feister, U; Jäkel, E; Gericke, K

    2002-09-01

    Daily values of solar global ultraviolet (UV) B and UVA irradiation as well as erythemal irradiation have been parameterized to be estimated from pyranometer measurements of daily global and diffuse irradiation as well as from atmospheric column ozone. Data recorded at the Meteorological Observatory Potsdam (52 degrees N, 107 m asl) in Germany over the time period 1997-2000 have been used to derive sets of regression coefficients. The validation of the method against independent data sets of measured UV irradiation shows that the parameterization provides a gain of information for UVB, UVA and erythemal irradiation referring to their averages. A comparison between parameterized daily UV irradiation and independent values of UV irradiation measured at a mountain station in southern Germany (Meteorological Observatory Hohenpeissenberg at 48 degrees N, 977 m asl) indicates that the parameterization also holds even under completely different climatic conditions. On a long-term average (1953-2000), parameterized annual UV irradiation values are 15% and 21% higher for UVA and UVB, respectively, at Hohenpeissenberg than they are at Potsdam. Daily global and diffuse irradiation measured at 28 weather stations of the Deutscher Wetterdienst German Radiation Network and grid values of column ozone from the EPTOMS satellite experiment served as inputs to calculate the estimates of the spatial distribution of daily and annual values of UV irradiation across Germany. Using daily values of global and diffuse irradiation recorded at Potsdam since 1937 as well as atmospheric column ozone measured since 1964 at the same site, estimates of daily and annual UV irradiation have been derived for this site over the period from 1937 through 2000, which include the effects of changes in cloudiness, in aerosols and, at least for the period of ozone measurements from 1964 to 2000, in atmospheric ozone. It is shown that the extremely low ozone values observed mainly after the eruption of Mt

  3. 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.

  4. 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.

  5. Daily associations among anger experience and intimate partner aggression within aggressive and nonaggressive community couples.

    PubMed

    Crane, Cory A; Testa, Maria

    2014-10-01

    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 (IPA) 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 (APIM) framework to analyze the daily associations between anger and partner-aggression perpetration among participating men and women, 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 both women who reported high levels of anger and men, regardless of their own anger experience. Increases in actor anger were associated with increases in daily partner aggression only among previously aggressive women. Previously aggressive men and women consistently reported greater perpetration than their nonaggressive counterparts on days of high levels of actors' anger experiences. 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.

  6. 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.

  7. 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

  8. The Gambro system for home daily dialysis.

    PubMed

    Ledebo, Ingrid; Fredin, Richard

    2004-01-01

    Safety and reliability have been the main emphasis when developing our system for home daily dialysis. The AK 95 is part of a comprehensive system of appropriate products consisting additionally of a silent water treatment module, an ultrafilter, and a range of dry disposables for dialysis fluid preparation and disinfection. The dialyzer can be selected from a family of synthetic, biocompatible filters, both low and high flux. To complete the system, a modern data management tool for online or off-line surveillance and multilingual training manuals in both conventional format as well as animated software are available.

  9. 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

  10. 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

  11. Diagnostic statistics of daily rainfall variability in an evolving climate

    NASA Astrophysics Data System (ADS)

    Panagoulia, D.; Bárdossy, A.; Lourmas, G.

    2006-06-01

    To investigate the character of daily rainfall variability under present and future climate described via global warming a suite of diagnostic statistics was used. The rainfall was modeled as a stochastic process coupled with atmospheric circulation. In this study we used an automated objective classification of daily patterns based on optimized fuzzy rules. This kind of classification method provided circulation patterns suitable for downscaling of General Circulation Model (GCM)-generated precipitation. The precipitation diagnostics included first and second order moments, wet and dry-day renewal process probabilities and spell lengths as well as low-frequency variability via the standard deviation of monthly totals. These descriptors were applied to nine elevation zones and entire area of the Mesochora mountainous catchment in Central Greece for observed, 1×CO2 and 2×CO2 downscaled precipitation. The statistics' comparison revealed significant differences in the most of the daily diagnostics (e.g. mean wet-day amount, 95th percentile of wet-day amount, dry to wet probability), spell statistics (e.g. mean wet/dry spell length), and low-frequency diagnostic (standard deviation of monthly precipitation total) between warm (2×CO2) and observed scenario in a progressive rate from lower to upper zone. The differences were very greater for the catchment area. In the light of these results, an increase in rainfall occurrence with diminished rainfall amount and a sequence of less consecutive dry days could describe the behaviour of a possible future climate on the examined catchment.

  12. Performance comparison of three predictor selection methods for statistical downscaling of daily precipitation

    NASA Astrophysics Data System (ADS)

    Yang, Chunli; Wang, Ninglian; Wang, Shijin; Zhou, Liang

    2016-10-01

    Predictor selection is a critical factor affecting the statistical downscaling of daily precipitation. This study provides a general comparison between uncertainties in downscaled results from three commonly used predictor selection methods (correlation analysis, partial correlation analysis, and stepwise regression analysis). Uncertainty is analyzed by comparing statistical indices, including the mean, variance, and the distribution of monthly mean daily precipitation, wet spell length, and the number of wet days. The downscaled results are produced by the artificial neural network (ANN) statistical downscaling model and 50 years (1961-2010) of observed daily precipitation together with reanalysis predictors. Although results show little difference between downscaling methods, stepwise regression analysis is generally the best method for selecting predictors for the ANN statistical downscaling model of daily precipitation, followed by partial correlation analysis and then correlation analysis.

  13. Simulation of daily energy budget and mean soil temperatures at an arid site

    NASA Astrophysics Data System (ADS)

    Matthias, A. D.

    1990-03-01

    Soil temperature is often inadequately based upon relatively few measurements at widely dispersed locations. Within arid regions, such as the desert southwestern United States, soils, microclimates, and thus soil temperature may be markedly heterogeneous. Because extensive measurement of soil temperature is often not feasible, models are needed that simulate soil temperature based on readily available soil survey and “above-ground” weather information. This paper describes a simple energy-budget based model for simulating daily mean temperatures within a bare arid land soil. The model requires basic information on soil physical properties, and daily weather data including air temperature, windspeed, rainfall, and solar radiation to calculate daily surface energy budget components and surface temperature. One of two alternative numerical methods is then used to calculated subsurface temperatures. Tests of the model using 1987 daily temperature data from an arid site at Yuma, Arizona resulted in root mean square deviations within 1.4°C between daily modeled and measured temperatures at both 0.05 and 0.10 m depths. Sensitivity analysis showed modeled temperatures at 0.05 m depth to be most sensitive to parameters affecting the surface energy balance such as air temperature and solar radiation. Modeled temperatures at 1.0m depth were relatively more sensitive to initial temperature conditions and to parameters affecting distribution of energy within the profile such as thermal conductivity.

  14. Chronic daily headache in the elderly.

    PubMed

    Özge, Aynur

    2013-12-01

    Disabling headache disorders are ubiquitous in all age groups, including the elderly, yet they are under-recognized, underdiagnosed and undertreated worldwide. Surveys and clinic-based research reports on headache disorders in elderly populations are extremely limited in number. Chronic daily headache (CDH) is an important and growing subtype of primary headache disorders, associated with increased burden and disruption to quality of life. CDH can be divided into two forms, based on headache duration. Common forms of primary headache disorders of long duration (>4 hours) were comprehensively defined in the third edition of the International Classification of Headache Disorders (ICHD-3 beta). These include chronic migraine, chronic tension-type headache, new daily persistent headache, and hemicrania continua. Rarer short-duration (<4 hours) forms of CDH are chronic cluster headache, chronic paroxysmal hemicrania, SUNCT, and hypnic headache. Accurate diagnosis, management, and relief of the burden of CDH in the elderly population present numerous unique challenges as the "aging world" continues to grow. In order to implement appropriate coping strategies for the elderly, it is essential to establish the correct diagnosis at each step and to exercise caution in differentiating from secondary causes, while always taking into consideration the unique needs and limitations of the aged body.

  15. 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

  16. 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

  17. Daily temperature extremes play an important role in predicting thermal effects.

    PubMed

    Ma, Gang; Hoffmann, Ary A; Ma, Chun-Sen

    2015-07-01

    Organisms in natural environments experience diel temperature fluctuations, including sporadic extreme conditions, rather than constant temperatures. Studies based mainly on model organisms have tended to focus on responses to average temperatures or short-term heat stress, which overlooks the potential impact of daily fluctuations, including stressful daytime periods and milder night-time periods. Here, we focus on daily maximum temperatures, while holding night-time temperatures constant, to specifically investigate the effects of high temperature on demographic parameters and fitness in the English grain aphid Sitobion avenae. We then compared the observed effects of different daily maximum temperatures with predictions from constant temperature-performance expectations. Moderate daily maximum temperatures depressed aphid performance while extreme conditions had dramatic effects, even when mean temperatures were below the critical maximum. Predictions based on daily average temperature underestimated negative effects of temperature on performance by ignoring daily maximum temperature, while predictions based on daytime maximum temperatures overestimated detrimental impacts by ignoring recovery under mild night-time temperatures. Our findings suggest that daily maximum temperature will play an important role in regulating natural population dynamics and should be considered in predictions. These findings have implications for natural population dynamics, particularly when considering the expected increase in extreme temperature events under climate change. PMID:26026043

  18. 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

  19. Plaque growth and removal with daily toothbrushing.

    PubMed

    De la Rosa, M; Zacarias Guerra, J; Johnston, D A; Radike, A W

    1979-12-01

    Dental plaque growth was observed among 180 teenage boys during a 28-day period following prophylaxis. During this period, subjects brushed their teeth under supervision for 2 minutes daily. Plaque levels were measured immediately after brushing and 24 hours after brushing. Both levels increased rapidly during the first 14 days and appeared to be leveled off at 28 days. Less than half of the plaque was removed with one brushing per day leaving about 60% after brushing to promote rapid regrowth. Regrowth rate after brushing on the 28th day was 0.032 plaque units per hour over a 24-hour period. The regrowth rate for the group brushing with dentifrice was 27% lower than for the group brushing without a dentifrice.

  20. 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

  1. 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.

  2. 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.

  3. Estimation of daily micronutrient intake of Filipinos.

    PubMed

    Natera, Erlinda; Trinidad, Trinidad; Valdez, Divina; Kawamura, Hisao; Palad, Lorna; Shiraishi, Kunio

    2002-09-01

    The Fourth National Nutrition Survey of the Food and Nutrition Research Institute conducted in 1993 showed an increasing prevalence of micronutrient-related diseases in various age groups. Hence, the daily diet consumed by the average Filipino was examined for its nutrient content. A total of 19 regional diet samples were collected and analyzed for phosphorous, iron, zinc, magnesium, manganese, calcium, potassium, and sodium by using inductively coupled plasma atomic emission spectrometry (ICP-AES). Iodine was determined by inductively coupled plasma mass spectrometry (ICP-MS). Benchmark data for the abovementioned micronutrients showed decreased intake values as compared to the recommended dietary allowance established in 1989. The information will be useful in assessing the existing nutritional status so that appropriate nutrient interventions can possibly be put in place. PMID:12362801

  4. 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.

  5. Pathological narcissism and interpersonal behavior in daily life.

    PubMed

    Roche, Michael J; Pincus, Aaron L; Conroy, David E; Hyde, Amanda L; Ram, Nilam

    2013-10-01

    The cognitive-affective processing system (CAPS) has been proposed as a useful metaframework for integrating contextual differences in situations with individual differences in personality pathology. In this article, we evaluated the potential of combining the CAPS metaframework and contemporary interpersonal theory to investigate how individual differences in pathological narcissism influenced interpersonal functioning in daily life. University students (N = 184) completed event-contingent reports about interpersonal interactions across a 7-day diary study. Using multilevel regression models, we found that combinations of narcissistic expression (grandiosity, vulnerability) were associated with different interpersonal behavior patterns reflective of interpersonal dysfunction. These results are among the first to empirically demonstrate the usefulness of the CAPS model to conceptualize personality pathology through the patterning of if-then interpersonal processes. PMID:23205698

  6. Allergists: Daily Bath OK for Kids with Eczema

    MedlinePlus

    ... medlineplus.gov/news/fullstory_159633.html Allergists: Daily Bath OK for Kids With Eczema The key is ... Although some doctors advise against giving a daily bath to kids with the skin condition eczema, a ...

  7. 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...

  8. 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.

  9. 27 CFR 19.740 - Daily storage 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 storage records. 19..., DEPARTMENT OF THE TREASURY LIQUORS DISTILLED SPIRITS PLANTS Records and Reports Storage Account § 19.740 Daily storage records. (a) General. Proprietors shall maintain daily records in the storage...

  10. 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...

  11. 19 CFR 159.35 - Certified daily rate.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... TREASURY (CONTINUED) LIQUIDATION OF DUTIES Conversion of Foreign Currency § 159.35 Certified daily rate. The daily buying rate of foreign currency which is determined by the Federal Reserve Bank of New York... 19 Customs Duties 2 2011-04-01 2011-04-01 false Certified daily rate. 159.35 Section...

  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. 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....

  14. 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....

  15. 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...

  16. 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...

  17. 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...

  18. 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....

  19. 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....

  20. 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...

  1. 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...

  2. 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....

  3. 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

  4. 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.

  5. 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

  6. Developing hourly weather data for locations having only daily weather data

    SciTech Connect

    Talbert, S.G.; Herold, K.E.; Jakob, F.E.; Lundstrom, D.K.

    1983-06-01

    A methodology was developed to modify an hourly TMY weather tape to be representative of a location for which only average daily weather parameters were avilable. Typical hourly and daily variations in solar flux, and other parameters, were needed to properly exercise a computer model to predict the transient performance of a solar controlled greenhouse being designed for Riyadh, Saudi Arabia. The starting point was a TMY tape for Yuma, Arizona, since the design temperatures for summer and winter are nearly identical for Yuma and Riyadh. After comparing six of the most important weather variables, the hourly values on the Yuma tape were individually adjusted to give the same overall daily average conditions as existed in the long-term Riyadh data. Finally, a statistical analysis was used to confirm quantitatively that the daily variations between the long term average values for Riyadh and the modified TMY weather tape for Yuma matched satisfactorily.

  7. 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.

  8. 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.

  9. Poorest countries experience earlier anthropogenic emergence of daily temperature extremes

    NASA Astrophysics Data System (ADS)

    Harrington, Luke J.; Frame, David J.; Fischer, Erich M.; Hawkins, Ed; Joshi, Manoj; Jones, Chris D.

    2016-05-01

    Understanding how the emergence of the anthropogenic warming signal from the noise of internal variability translates to changes in extreme event occurrence is of crucial societal importance. By utilising simulations of cumulative carbon dioxide (CO2) emissions and temperature changes from eleven earth system models, we demonstrate that the inherently lower internal variability found at tropical latitudes results in large increases in the frequency of extreme daily temperatures (exceedances of the 99.9th percentile derived from pre-industrial climate simulations) occurring much earlier than for mid-to-high latitude regions. Most of the world’s poorest people live at low latitudes, when considering 2010 GDP-PPP per capita; conversely the wealthiest population quintile disproportionately inhabit more variable mid-latitude climates. Consequently, the fraction of the global population in the lowest socio-economic quintile is exposed to substantially more frequent daily temperature extremes after much lower increases in both mean global warming and cumulative CO2 emissions.

  10. 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

  11. 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

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

    2013-05-01

    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.

  12. 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

  13. The Daily Curriculum Guide, Year II, Weeks 21-34. A Preschool Program for the Spanish-Speaking Child.

    ERIC Educational Resources Information Center

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

    Daily lesson plans for weeks 21 through 34 are provided in this guide, the third and last in the Year II sequence of the Daily Curriculum Guide preschool program for the Spanish-speaking child. The program is based on a language maintenance model in which Spanish is used as a means to develop basic concepts, skills and attitudes. Written in both…

  14. 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

  15. 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

  16. Daily cognitive appraisals, daily affect, and long-term depressive symptoms: the role of self-esteem and self-concept clarity in the stress process.

    PubMed

    Lee-Flynn, Sharon C; Pomaki, Georgia; Delongis, Anita; Biesanz, Jeremy C; Puterman, Eli

    2011-02-01

    The current study investigated how self-esteem and self-concept clarity are implicated in the stress process both in the short and long term. Initial and 2-year follow-up interviews were completed by 178 participants from stepfamily unions. In twice-daily structured diaries over 7 days, participants reported their main family stressor, cognitive appraisals (perceived stressor threat and stressor controllability), and negative affect. Results of multilevel modeling indicated that high self-esteem ameliorated the effect of daily negative cognitive appraisals on daily negative affect. Self-concept clarity also buffered the effect of low self-self-esteem on depressive symptoms 2 years later. Our findings point to the vulnerability of those having low self-esteem or low self-concept clarity in terms of both short- and long-term adaptation to stress. They indicate the need for the consideration of such individual differences in designing stress management interventions.

  17. Daily body energy balance in rats.

    PubMed

    Le Magnen, J; Devos, M

    1982-11-01

    The aim of the present study was to examine the balance between caloric intake and expenditures in successive 12 and 24 hour periods, for several consecutive days in rats. The simultaneous and continuous measurements of respiratory exchanges and of the spontaneous feeding pattern were performed in 6 rats during 38 days, in periods of 2 to 4 successive days. At night, caloric intake exceeded caloric expenditures by 32% on the average. In individual rats, the excess was positively correlated to meal size but not to meal number. During the daytime, caloric intake was 24% lower on the average than the concomitant energy expenditures. In individual subjects, these deficits were correlated to meal number but not to meal size. A nocturnal excess and the subsequent daytime deficit, and the diurnal deficit and the excess during the subsequent night were highly positively correlated. In fact, the 24 hour energy balance was either slightly positive (12% excess) or negative (4% deficit). The daily weight gain or loss was highly correlated to the residual excess and/or deficit with a mean caloric cost of 4.8 kcal per g of body weight. The absence of correlation between balances on successive days indicates that the body energy balance is regulated within 24 hr through 12/12 hr compensations and that no compensatory mechanisms are involved beyond 24 hr.

  18. 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

  19. 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.

  20. Mars Daily Global Maps and Animations

    NASA Astrophysics Data System (ADS)

    Wang, H.; Ingersoll, A. P.

    2000-10-01

    Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) has been taking global map swaths of Mars using its red and blue wide angle cameras every two hours since March 1999. We have processed the global map swaths taken from June to August 1999 which correspond to the end of the northern summer (150 < Ls < 185), and made them into daily global maps and animations with 2-hour and 1-day time steps for the polar regions. The south polar seasonal cap recession, the north polar dust and condensate cloud activity, and the condensate clouds over the Tharsis volcanos and Valles Marineris are clearly displayed. We will continue processing data as they become available. The north polar region stays relatively calm before Ls 160. Active dust storms and condensate clouds show up afterwards. Cloud tracked winds are typically about 15m/s in the north polar region during this season, and there are winds blowing onto and even across the cap. North of 65N, condensate clouds change shape quickly, suggesting transient waves in the atmosphere. Dust storms about 500km and larger usually have well developed cyclonic structure and have lifetime of several days. Dust storms often blow across the residual cap, especially in late summer (Ls 180). There are sometimes condensate clouds that seem to be associated with the dust storms. Dust storms usually show up at longitudes 0 +/- 90 around the north polar cap in this season, suggesting an asymmetric circulation.

  1. Kiwifruit: our daily prescription for health.

    PubMed

    Stonehouse, Welma; Gammon, Cheryl S; Beck, Kathryn L; Conlon, Cathryn A; von Hurst, Pamela R; Kruger, Rozanne

    2013-06-01

    Kiwifruit are unequalled, compared with other commonly consumed fruit, for their nutrient density, health benefits, and consumer appeal. Research into their health benefits has focussed on the cultivars Actinidia deliciosa 'Hayward' (green kiwifruit) and Actinidia chinensis 'Hort 16A', ZESPRI(®) (gold kiwifruit). Compared with other commonly consumed fruit, both green and gold kiwifruit are exceptionally high in vitamins C, E, K, folate, carotenoids, potassium, fibre, and phytochemicals acting in synergy to achieve multiple health benefits. Kiwifruit, as part of a healthy diet, may increase high-density lipoprotein cholesterol, and decrease triglycerides, platelet aggregation, and elevated blood pressure. Consuming gold kiwifruit with iron-rich meals improves poor iron status, and green kiwifruit aids digestion and laxation. As a rich source of antioxidants, they may protect the body from endogenous oxidative damage. Kiwifruit may support immune function and reduce the incidence and severity of cold or flu-like illness in at-risk groups such as older adults and children. However, kiwifruit are allergenic, and although symptoms in most susceptible individuals are mild, severe reactions have been reported. While many research gaps remain, kiwifruit with their multiple health benefits have the potential to become part of our "daily prescription for health."

  2. Estimating daily net radiation in the FAO Penman-Monteith method

    NASA Astrophysics Data System (ADS)<