Sample records for modeling daily precipitationat

  1. Modelling of Sub-daily Hydrological Processes Using Daily Time-Step Models: A Distribution Function Approach to Temporal Scaling

    NASA Astrophysics Data System (ADS)

    Kandel, D. D.; Western, A. W.; Grayson, R. B.

    2004-12-01

    Mismatches in scale between the fundamental processes, the model and supporting data are a major limitation in hydrologic modelling. Surface runoff generation via infiltration excess and the process of soil erosion are fundamentally short time-scale phenomena and their average behaviour is mostly determined by the short time-scale peak intensities of rainfall. Ideally, these processes should be simulated using time-steps of the order of minutes to appropriately resolve the effect of rainfall intensity variations. However, sub-daily data support is often inadequate and the processes are usually simulated by calibrating daily (or even coarser) time-step models. Generally process descriptions are not modified but rather effective parameter values are used to account for the effect of temporal lumping, assuming that the effect of the scale mismatch can be counterbalanced by tuning the parameter values at the model time-step of interest. Often this results in parameter values that are difficult to interpret physically. A similar approach is often taken spatially. This is problematic as these processes generally operate or interact non-linearly. This indicates a need for better techniques to simulate sub-daily processes using daily time-step models while still using widely available daily information. A new method applicable to many rainfall-runoff-erosion models is presented. The method is based on temporal scaling using statistical distributions of rainfall intensity to represent sub-daily intensity variations in a daily time-step model. This allows the effect of short time-scale nonlinear processes to be captured while modelling at a daily time-step, which is often attractive due to the wide availability of daily forcing data. The approach relies on characterising the rainfall intensity variation within a day using a cumulative distribution function (cdf). This cdf is then modified by various linear and nonlinear processes typically represented in hydrological and

  2. 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

  3. Modeling Cortisol Daily Rhythms of Family Caregivers of Individuals With Dementia: Daily Stressors and Adult Day Services Use.

    PubMed

    Liu, Yin; Almeida, David M; Rovine, Michael J; Zarit, Steven H

    2018-03-02

    The study examined the typical diurnal cortisol trajectory and its differential associations with an intervention, the adult day services (ADS) use, among a sample of family caregivers who experienced high levels of daily stress. On hundred and sixty-five caregivers of individuals with dementia completed an 8-day diary on daily stressors, positive events, sleep quality, and ADS use. The caregivers also provided five saliva samples on each diary day. Daily cortisol trajectories were modeled as a function of time elapsed since awakening, and three spline growth curve models were fit to the cortisol data. Based on the best-fitting linear spline model, the effect of daily ADS use was examined at both daily and person levels. Covariates included daily experiences and other caregiving characteristics. On ADS days, caregivers had a steeper cortisol awakening response (CAR) slope and a steeper morning decline. ADS use remained significant after controlling for covariates at both daily and person levels. The findings suggested potential biophysiological benefits of daily ADS use for a sample that was under chronic stress and high levels of daily stress.

  4. Downscaler Model for predicting daily air pollution

    EPA Pesticide Factsheets

    This model combines daily ozone and particulate matter monitoring and modeling data from across the U.S. to provide improved fine-scale estimates of air quality in communities and other specific locales.

  5. 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.

  6. 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.

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

    EPA Pesticide Factsheets

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

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

    Treesearch

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

    2014-01-01

    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...

  9. Acute Brain Dysfunction: Development and Validation of a Daily Prediction Model.

    PubMed

    Marra, Annachiara; Pandharipande, Pratik P; Shotwell, Matthew S; Chandrasekhar, Rameela; Girard, Timothy D; Shintani, Ayumi K; Peelen, Linda M; Moons, Karl G M; Dittus, Robert S; Ely, E Wesley; Vasilevskis, Eduard E

    2018-03-24

    The goal of this study was to develop and validate a dynamic risk model to predict daily changes in acute brain dysfunction (ie, delirium and coma), discharge, and mortality in ICU patients. Using data from a multicenter prospective ICU cohort, a daily acute brain dysfunction-prediction model (ABD-pm) was developed by using multinomial logistic regression that estimated 15 transition probabilities (from one of three brain function states [normal, delirious, or comatose] to one of five possible outcomes [normal, delirious, comatose, ICU discharge, or died]) using baseline and daily risk factors. Model discrimination was assessed by using predictive characteristics such as negative predictive value (NPV). Calibration was assessed by plotting empirical vs model-estimated probabilities. Internal validation was performed by using a bootstrap procedure. Data were analyzed from 810 patients (6,711 daily transitions). The ABD-pm included individual risk factors: mental status, age, preexisting cognitive impairment, baseline and daily severity of illness, and daily administration of sedatives. The model yielded very high NPVs for "next day" delirium (NPV: 0.823), coma (NPV: 0.892), normal cognitive state (NPV: 0.875), ICU discharge (NPV: 0.905), and mortality (NPV: 0.981). The model demonstrated outstanding calibration when predicting the total number of patients expected to be in any given state across predicted risk. We developed and internally validated a dynamic risk model that predicts the daily risk for one of three cognitive states, ICU discharge, or mortality. The ABD-pm may be useful for predicting the proportion of patients for each outcome state across entire ICU populations to guide quality, safety, and care delivery activities. Copyright © 2018 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

  10. 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.

  11. Hospital daily outpatient visits forecasting using a combinatorial model based on ARIMA and SES models.

    PubMed

    Luo, Li; Luo, Le; Zhang, Xinli; He, Xiaoli

    2017-07-10

    Accurate forecasting of hospital outpatient visits is beneficial for the reasonable planning and allocation of healthcare resource to meet the medical demands. In terms of the multiple attributes of daily outpatient visits, such as randomness, cyclicity and trend, time series methods, ARIMA, can be a good choice for outpatient visits forecasting. On the other hand, the hospital outpatient visits are also affected by the doctors' scheduling and the effects are not pure random. Thinking about the impure specialty, this paper presents a new forecasting model that takes cyclicity and the day of the week effect into consideration. We formulate a seasonal ARIMA (SARIMA) model on a daily time series and then a single exponential smoothing (SES) model on the day of the week time series, and finally establish a combinatorial model by modifying them. The models are applied to 1 year of daily visits data of urban outpatients in two internal medicine departments of a large hospital in Chengdu, for forecasting the daily outpatient visits about 1 week ahead. The proposed model is applied to forecast the cross-sectional data for 7 consecutive days of daily outpatient visits over an 8-weeks period based on 43 weeks of observation data during 1 year. The results show that the two single traditional models and the combinatorial model are simplicity of implementation and low computational intensiveness, whilst being appropriate for short-term forecast horizons. Furthermore, the combinatorial model can capture the comprehensive features of the time series data better. Combinatorial model can achieve better prediction performance than the single model, with lower residuals variance and small mean of residual errors which needs to be optimized deeply on the next research step.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  13. 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

  14. 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.

  15. 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.

  16. [Comparison of three daily global solar radiation models].

    PubMed

    Yang, Jin-Ming; Fan, Wen-Yi; Zhao, Ying-Hui

    2014-08-01

    Three daily global solar radiation estimation models ( Å-P model, Thornton-Running model and model provided by Liu Ke-qun et al.) were analyzed and compared using data of 13 weather stations from 1982 to 2012 from three northeastern provinces and eastern Inner Mongolia. After cross-validation analysis, the result showed that mean absolute error (MAE) for each model was 1.71, 2.83 and 1.68 MJ x m(-2) x d(-1) respectively, showing that Å-P model and model provided by Liu Ke-qun et al. which used percentage of sunshine had an advantage over Thornton-Running model which didn't use percentage of sunshine. Model provided by Liu Ke-qun et al. played a good effect on the situation of non-sunshine, and its MAE and bias percentage were 18.5% and 33.8% smaller than those of Å-P model, respectively. High precision results could be obtained by using the simple linear model of Å-P. Å-P model, Thornton-Running model and model provided by Liu Ke-qun et al. overvalued daily global solar radiation by 12.2%, 19.2% and 9.9% respectively. MAE for each station varied little with the spatial change of location, and annual MAE decreased with the advance of years. The reason for this might be that the change of observation accuracy caused by the replacement of radiation instrument in 1993. MAEs for rainy days, non-sunshine days and warm seasons of the three models were greater than those for days without rain, sunshine days and cold seasons respectively, showing that different methods should be used for different weather conditions on estimating solar radiation with meteorological elements.

  17. Estimating daily climatologies for climate indices derived from climate model data and observations

    PubMed Central

    Mahlstein, Irina; Spirig, Christoph; Liniger, Mark A; Appenzeller, Christof

    2015-01-01

    Climate indices help to describe the past, present, and the future climate. They are usually closer related to possible impacts and are therefore more illustrative to users than simple climate means. Indices are often based on daily data series and thresholds. It is shown that the percentile-based thresholds are sensitive to the method of computation, and so are the climatological daily mean and the daily standard deviation, which are used for bias corrections of daily climate model data. Sample size issues of either the observed reference period or the model data lead to uncertainties in these estimations. A large number of past ensemble seasonal forecasts, called hindcasts, is used to explore these sampling uncertainties and to compare two different approaches. Based on a perfect model approach it is shown that a fitting approach can improve substantially the estimates of daily climatologies of percentile-based thresholds over land areas, as well as the mean and the variability. These improvements are relevant for bias removal in long-range forecasts or predictions of climate indices based on percentile thresholds. But also for climate change studies, the method shows potential for use. Key Points More robust estimates of daily climate characteristics Statistical fitting approach Based on a perfect model approach PMID:26042192

  18. The Effect of Improved Sub-Daily Earth Rotation Models on Global GPS Data Processing

    NASA Astrophysics Data System (ADS)

    Yoon, S.; Choi, K. K.

    2017-12-01

    Throughout the various International GNSS Service (IGS) products, strong periodic signals have been observed around the 14 day period. This signal is clearly visible in all IGS time-series such as those related to orbit ephemerides, Earth rotation parameters (ERP) and ground station coordinates. Recent studies show that errors in the sub-daily Earth rotation models are the main factors that induce such noise. Current IGS orbit processing standards adopted the IERS 2010 convention and its sub-daily Earth rotation model. Since the IERS convention had published, recent advances in the VLBI analysis have made contributions to update the sub-daily Earth rotation models. We have compared several proposed sub-daily Earth rotation models and show the effect of using those models on orbit ephemeris, Earth rotation parameters and ground station coordinates generated by the NGS global GPS data processing strategy.

  19. Daily pan evaporation modelling using a neuro-fuzzy computing technique

    NASA Astrophysics Data System (ADS)

    Kişi, Özgür

    2006-10-01

    SummaryEvaporation, as a major component of the hydrologic cycle, is important in water resources development and management. This paper investigates the abilities of neuro-fuzzy (NF) technique to improve the accuracy of daily evaporation estimation. Five different NF models comprising various combinations of daily climatic variables, that is, air temperature, solar radiation, wind speed, pressure and humidity are developed to evaluate degree of effect of each of these variables on evaporation. A comparison is made between the estimates provided by the NF model and the artificial neural networks (ANNs). The Stephens-Stewart (SS) method is also considered for the comparison. Various statistic measures are used to evaluate the performance of the models. Based on the comparisons, it was found that the NF computing technique could be employed successfully in modelling evaporation process from the available climatic data. The ANN also found to perform better than the SS method.

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

    PubMed

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

    2013-06-01

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

  1. Analysis and comparison of safety models using average daily, average hourly, and microscopic traffic.

    PubMed

    Wang, Ling; Abdel-Aty, Mohamed; Wang, Xuesong; Yu, Rongjie

    2018-02-01

    There have been plenty of traffic safety studies based on average daily traffic (ADT), average hourly traffic (AHT), or microscopic traffic at 5 min intervals. Nevertheless, not enough research has compared the performance of these three types of safety studies, and seldom of previous studies have intended to find whether the results of one type of study is transferable to the other two studies. First, this study built three models: a Bayesian Poisson-lognormal model to estimate the daily crash frequency using ADT, a Bayesian Poisson-lognormal model to estimate the hourly crash frequency using AHT, and a Bayesian logistic regression model for the real-time safety analysis using microscopic traffic. The model results showed that the crash contributing factors found by different models were comparable but not the same. Four variables, i.e., the logarithm of volume, the standard deviation of speed, the logarithm of segment length, and the existence of diverge segment, were positively significant in the three models. Additionally, weaving segments experienced higher daily and hourly crash frequencies than merge and basic segments. Then, each of the ADT-based, AHT-based, and real-time models was used to estimate safety conditions at different levels: daily and hourly, meanwhile, the real-time model was also used in 5 min intervals. The results uncovered that the ADT- and AHT-based safety models performed similar in predicting daily and hourly crash frequencies, and the real-time safety model was able to provide hourly crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. 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.

  3. 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...

  4. Advanced Daily Prediction Model for National Suicide Numbers with Social Media Data.

    PubMed

    Lee, Kyung Sang; Lee, Hyewon; Myung, Woojae; Song, Gil-Young; Lee, Kihwang; Kim, Ho; Carroll, Bernard J; Kim, Doh Kwan

    2018-04-01

    Suicide is a significant public health concern worldwide. Social media data have a potential role in identifying high suicide risk individuals and also in predicting suicide rate at the population level. In this study, we report an advanced daily suicide prediction model using social media data combined with economic/meteorological variables along with observed suicide data lagged by 1 week. The social media data were drawn from weblog posts. We examined a total of 10,035 social media keywords for suicide prediction. We made predictions of national suicide numbers 7 days in advance daily for 2 years, based on a daily moving 5-year prediction modeling period. Our model predicted the likely range of daily national suicide numbers with 82.9% accuracy. Among the social media variables, words denoting economic issues and mood status showed high predictive strength. Observed number of suicides one week previously, recent celebrity suicide, and day of week followed by stock index, consumer price index, and sunlight duration 7 days before the target date were notable predictors along with the social media variables. These results strengthen the case for social media data to supplement classical social/economic/climatic data in forecasting national suicide events.

  5. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    USGS Publications Warehouse

    Hwang, Y.; Clark, M.R.; 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.

  6. Daily Rainfall Simulation Using Climate Variables and Nonhomogeneous Hidden Markov Model

    NASA Astrophysics Data System (ADS)

    Jung, J.; Kim, H. S.; Joo, H. J.; Han, D.

    2017-12-01

    Markov chain is an easy method to handle when we compare it with other ones for the rainfall simulation. However, it also has limitations in reflecting seasonal variability of rainfall or change on rainfall patterns caused by climate change. This study applied a Nonhomogeneous Hidden Markov Model(NHMM) to consider these problems. The NHMM compared with a Hidden Markov Model(HMM) for the evaluation of a goodness of the model. First, we chose Gum river basin in Korea to apply the models and collected daily rainfall data from the stations. Also, the climate variables of geopotential height, temperature, zonal wind, and meridional wind date were collected from NCEP/NCAR reanalysis data to consider external factors affecting the rainfall event. We conducted a correlation analysis between rainfall and climate variables then developed a linear regression equation using the climate variables which have high correlation with rainfall. The monthly rainfall was obtained by the regression equation and it became input data of NHMM. Finally, the daily rainfall by NHMM was simulated and we evaluated the goodness of fit and prediction capability of NHMM by comparing with those of HMM. As a result of simulation by HMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.2076 and 10.8243/131.1304mm each. In case of NHMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.6652 and 10.5112/100.9865mm each. We could verify that the error of daily and monthly rainfall simulated by NHMM was improved by 2.89% and 22.99% compared with HMM. Therefore, it is expected that the results of the study could provide more accurate data for hydrologic analysis. Acknowledgements This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(2017R1A2B3005695)

  7. 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

  8. Advanced Daily Prediction Model for National Suicide Numbers with Social Media Data

    PubMed Central

    Lee, Kyung Sang; Lee, Hyewon; Myung, Woojae; Song, Gil-Young; Lee, Kihwang; Kim, Ho; Carroll, Bernard J.; Kim, Doh Kwan

    2018-01-01

    Objective Suicide is a significant public health concern worldwide. Social media data have a potential role in identifying high suicide risk individuals and also in predicting suicide rate at the population level. In this study, we report an advanced daily suicide prediction model using social media data combined with economic/meteorological variables along with observed suicide data lagged by 1 week. Methods The social media data were drawn from weblog posts. We examined a total of 10,035 social media keywords for suicide prediction. We made predictions of national suicide numbers 7 days in advance daily for 2 years, based on a daily moving 5-year prediction modeling period. Results Our model predicted the likely range of daily national suicide numbers with 82.9% accuracy. Among the social media variables, words denoting economic issues and mood status showed high predictive strength. Observed number of suicides one week previously, recent celebrity suicide, and day of week followed by stock index, consumer price index, and sunlight duration 7 days before the target date were notable predictors along with the social media variables. Conclusion These results strengthen the case for social media data to supplement classical social/economic/climatic data in forecasting national suicide events. PMID:29614852

  9. Development of a foraging model framework to reliably estimate daily food consumption by young fishes

    USGS Publications Warehouse

    Deslauriers, David; Rosburg, Alex J.; Chipps, Steven R.

    2017-01-01

    We developed a foraging model for young fishes that incorporates handling and digestion rate to estimate daily food consumption. Feeding trials were used to quantify functional feeding response, satiation, and gut evacuation rate. Once parameterized, the foraging model was then applied to evaluate effects of prey type, prey density, water temperature, and fish size on daily feeding rate by age-0 (19–70 mm) pallid sturgeon (Scaphirhynchus albus). Prey consumption was positively related to prey density (for fish >30 mm) and water temperature, but negatively related to prey size and the presence of sand substrate. Model evaluation results revealed good agreement between observed estimates of daily consumption and those predicted by the model (r2 = 0.95). Model simulations showed that fish feeding on Chironomidae or Ephemeroptera larvae were able to gain mass, whereas fish feeding solely on zooplankton lost mass under most conditions. By accounting for satiation and digestive processes in addition to handling time and prey density, the model provides realistic estimates of daily food consumption that can prove useful for evaluating rearing conditions for age-0 fishes.

  10. 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.

  11. 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.

  12. 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

  13. 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

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

    EPA Science Inventory

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

  15. 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)

  16. 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

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

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

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

    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.more » (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)« less

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

    USDA-ARS?s Scientific Manuscript database

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

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

    PubMed

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

    2016-06-01

    The present study examined whether and how stressor diversity, the extent to which stressor events are spread across multiple types of stressors, contributes to daily affective well-being through the adult life span. Stressor diversity was examined as a unique predictor of daily affect and as a moderator of stressor exposure and stressor reactivity effects. Analyses span 2 independent studies of daily stress: the National Study of Daily Experiences with N = 2,022 adults, aged 33 to 85 years, assessed over T = 8 days, and the Intraindividual Study of Affect, Health, and Interpersonal Behavior with N = 150 adults, aged 18 to 89 years, assessed over T = 63 days. Across both studies, older age was associated with less stressor diversity. Additionally, multivariate multilevel models indicated higher stressor diversity was linked with better affective well-being. Age, however, was not a consistent moderator of such associations. The combination of low stressor diversity and high stressor exposure is discussed as an operationalization of chronic stressors, and this combination was associated with particularly high negative affect and low positive affect. We believe further work will benefit from including both the frequency and diversity of stressor experiences in analyses in order to better characterize individuals' stressor experiences. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  20. Stressor Diversity: Introduction and Empirical Integration into the Daily Stress Model

    PubMed Central

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

    2016-01-01

    The present study examined if and how stressor diversity, the extent to which one’s stressor events are spread across multiple types of stressors, contributes to daily affective well-being through the adult life span. Stressor diversity was examined as a unique predictor of daily affect and as a moderator of stressor exposure and stressor reactivity effects. Analyses span two independent studies of daily stress: the National Study of Daily Experiences with N=2,022 adults, aged 33–85, assessed over T=8 days, and the Intraindividual Study of Affect, Health, and Interpersonal Behavior with N=150 adults, aged 18–89, assessed over T=63 days. Across both studies, older age was associated with less stressor diversity. Additionally, multivariate multilevel models indicated higher stressor diversity was linked with better affective well-being. Age, however, was not a consistent moderator of such associations. The combination of low stressor diversity and high stressor exposure is discussed as an operationalization of chronic stressors, and this combination was associated with particularly high negative affect and low positive affect. We believe further work will benefit from including both the frequency and diversity of stressor experiences in analyses in order to better characterize individuals’ stressor experiences. PMID:27294713

  1. Comparison of twice-daily vs once-daily deferasirox dosing in a gerbil model of iron cardiomyopathy

    PubMed Central

    Otto-Duessel, Maya; Aguilar, Michelle; Nick, Hanspeter; Moats, Rex; Wood, John C.

    2010-01-01

    Objective Despite the availability of deferoxamine chelation therapy for more than 20 years, iron cardiomyopathy remains the leading cause of death in thalassemia major patients. Effective chelation of cardiac iron is difficult; cardiac iron stores respond more slowly to chelation therapy and require a constant gradient of labile iron species between serum and myocytes. We have previously demonstrated the efficacy of once-daily deferasirox in removing previously stored cardiac iron in the gerbil, but changes in cardiac iron were relatively modest compared with hepatic iron. We postulated that daily divided dosing, by sustaining a longer labile iron gradient from myocytes to serum, would produce better cardiac iron chelation than a comparable daily dose. Methods Twenty-four 8- to 10-week-old female gerbils underwent iron dextran—loading for 10 weeks, followed by a 1-week iron equilibration period. Animals were divided into three treatment groups of eight animals each and were treated with deferasirox 100 mg/kg/day as a single dose, deferasirox 100 mg/kg/day daily divided dose, or sham chelation for a total of 12 weeks. Following euthanasia, organs were harvested for quantitative iron and tissue histology. Results Hepatic and cardiac iron contents were not statistically different between the daily single-dose and daily divided-dose groups. However, the ratio of cardiac to hepatic iron content was lower in the divided-dose group (0.78% vs 1.11%, p = 0.0007). Conclusion Daily divided dosing of deferasirox changes the relative cardiac and liver iron chelation profile compared with daily single dosing, trading improvements in cardiac iron elimination for less-effective hepatic chelation. PMID:17588475

  2. 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

  3. Evaluation of sub daily satellite rainfall estimates through flash flood modelling in the Lower Middle Zambezi Basin

    NASA Astrophysics Data System (ADS)

    Matingo, Thomas; Gumindoga, Webster; Makurira, Hodson

    2018-05-01

    Flash floods are experienced almost annually in the ungauged Mbire District of the Middle Zambezi Basin. Studies related to hydrological modelling (rainfall-runoff) and flood forecasting require major inputs such as precipitation which, due to shortage of observed data, are increasingly using indirect methods for estimating precipitation. This study therefore evaluated performance of CMORPH and TRMM satellite rainfall estimates (SREs) for 30 min, 1 h, 3 h and daily intensities through hydrologic and flash flood modelling in the Lower Middle Zambezi Basin for the period 2013-2016. On a daily timestep, uncorrected CMORPH and TRMM show Probability of Detection (POD) of 61 and 59 %, respectively, when compared to rain gauge observations. The best performance using Correlation Coefficient (CC) was 70 and 60 % on daily timesteps for CMORPH and TRMM, respectively. The best RMSE for CMORPH was 0.81 % for 30 min timestep and for TRMM was 2, 11 % on 3 h timestep. For the year 2014 to 2015, the HEC-HMS (Hydrological Engineering Centre-Hydrological Modelling System) daily model calibration Nash Sutcliffe efficiency (NSE) for Musengezi sub catchment was 59 % whilst for Angwa it was 55 %. Angwa sub-catchment daily NSE results for the period 2015-2016 was 61 %. HEC-RAS flash flood modeling at 100, 50 and 25 year return periods for Angwa sub catchment, inundated 811 and 867 ha for TRMM rainfall simulated discharge at 3 h and daily timesteps, respectively. For CMORPH generated rainfall, the inundation was 818, 876, 890 and 891 ha at daily, 3 h, 1 h and 30 min timesteps. The 30 min time step for CMORPH effectively captures flash floods with the measure of agreement between simulated flood extent and ground control points of 69 %. For TRMM, the 3 h timestep effectively captures flash floods with coefficient of 67 %. The study therefore concludes that satellite products are most effective in capturing localized hydrological processes such as flash floods for sub-daily rainfall

  4. Studying the effect of weather conditions on daily crash counts using a discrete time-series model.

    PubMed

    Brijs, Tom; Karlis, Dimitris; Wets, Geert

    2008-05-01

    In previous research, significant effects of weather conditions on car crashes have been found. However, most studies use monthly or yearly data and only few studies are available analyzing the impact of weather conditions on daily car crash counts. Furthermore, the studies that are available on a daily level do not explicitly model the data in a time-series context, hereby ignoring the temporal serial correlation that may be present in the data. In this paper, we introduce an integer autoregressive model for modelling count data with time interdependencies. The model is applied to daily car crash data, metereological data and traffic exposure data from the Netherlands aiming at examining the risk impact of weather conditions on the observed counts. The results show that several assumptions related to the effect of weather conditions on crash counts are found to be significant in the data and that if serial temporal correlation is not accounted for in the model, this may produce biased results.

  5. Daily spillover from family to work: A test of the work-home resources model.

    PubMed

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

    2018-04-01

    The present study examines a mediated moderation model of the day-level effects of family hassles and family-work spillover (affect and cognition) on the relationship between job resources and employees' flourishing at work. Based on the work-home resources model, the authors hypothesized that demands from one domain (family) induce repetitive thoughts or negative feelings about those problems, so that individuals are not able to function optimally and to make full use of contextual resources in the other domain (work). Multilevel analyses of 108 Chinese working parents' 366 daily surveys revealed that the relationship between morning job resources and afternoon flourishing was significantly positive when previous day family hassles were low; the relationship became nonsignificant when previous day family hassles were high. In addition, as predicted, daily rumination also attenuated the relationship between morning job resources and afternoon flourishing, whereas daily affect did not. Finally, the moderating effect of previous day family hassles was mediated by daily rumination. The findings contribute to spillover theories by revealing the roles of affective and cognitive spillover from family to work. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

    USDA-ARS?s Scientific Manuscript database

    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...

  7. The crossover of daily work engagement: test of an actor-partner interdependence model.

    PubMed

    Bakker, Arnold B; Xanthopoulou, Despoina

    2009-11-01

    This study of 62 dyads of employees (N = 124) examined the crossover of work engagement-a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication, and absorption. We hypothesized that work engagement crosses over from an employee (the actor) to his or her colleague (the partner) on a daily basis. The frequency of daily communication was expected to moderate the crossover of daily work engagement, which in turn would relate to colleagues' daily performance. Participants first filled in a general questionnaire and then completed a diary study over 5 consecutive workdays. The hypotheses were tested with multilevel analyses, using an actor-partner interdependence model. Results confirmed the crossover of daily work engagement, but only on days when employees within a dyad interacted more frequently than usual. Moreover, we found that actor's work engagement (particularly vigor), when frequently communicated, had a positive indirect relationship with partner's performance through partner's work engagement. Finally, results showed that actor's vigor was negatively related to partner's performance when communication was low. However, this negative effect was counteracted when mediated by the vigor of the partner.

  8. Cost analysis of once-daily ISMN versus twice-daily ISMN or transdermal patch for nitrate prophylaxis.

    PubMed

    Brown, R E; Kendall, M J; Halpern, M T

    1997-02-01

    To compare the costs and outcomes of treating exercise-induced angina with once- or twice-daily isosorbide mononitrate (ISMN) or transdermal patch. A decision-analytic model was designed based on published literature showing compliance and increasing symptoms and estimates from physicians on treatment patterns and worsening symptoms. Data show that patients are more compliant with once-daily ISMN (Imdur, Astra Hässle, Mölndal, Sweden) and patch regimens than with twice-daily dose. Based upon the assumption that more compliant patients are better controlled, the model found that fewer medical care resources were consumed by patients treated with the once-daily and the patch regimens. The unit cost of the twice-daily ISMN regimen is 40% of the unit cost of the once-daily. Annual costs of treating an exercise-induced angina patient are 248 pounds for Imdur compared to 250 pounds for the twice-daily ISMN and 299 pounds for the transdermal patch. Unit prices alone are not good indicators for estimating medical management costs.

  9. Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

    NASA Astrophysics Data System (ADS)

    Beranová, Romana; Kyselý, Jan; Hanel, Martin

    2018-04-01

    The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May-September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.

  10. 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.

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

    PubMed

    Pottie, Colin G; Ingram, Kathleen M

    2008-12-01

    This study used a repeated daily measurement design to examine the direct and moderating effects of coping on daily psychological distress and well-being in parents of children with Autism Spectrum Disorders (ASD). Twice weekly over a 12-week period, 93 parents provided reports of their daily stress, coping responses, and end-of-day mood. Multilevel modeling analyses identified 5 coping responses (e.g., seeking support, positive reframing) that predicted increased daily positive mood and 4 (e.g., escape, withdrawal) that were associated with decreased positive mood. Similarly, 2 coping responses were associated with decreased daily negative mood and 5 predicted increased negative mood. The moderating effects of gender and the 11 coping responses were also examined. Gender did not moderate the daily coping?mood relationship, however 3 coping responses (emotional regulation, social support, and worrying) were found to moderate the daily stress?mood relationship. Additionally, ASD symptomatology, and time since an ASD diagnosis were not found to predict daily parental mood. This study is perhaps the first to identify coping responses that enhance daily well-being and mitigate daily distress in parents of children with ASD. Copyright 2008 APA, all rights reserved.

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

    NASA Astrophysics Data System (ADS)

    Kurtulus, Bedri; Razack, Moumtaz

    2010-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

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

    PubMed

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

    2016-12-01

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

  15. Simulation of daily streamflow for 12 river basins in western Iowa using the Precipitation-Runoff Modeling System

    USGS Publications Warehouse

    Christiansen, Daniel E.; Haj, Adel E.; Risley, John C.

    2017-10-24

    The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa.The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed 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) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System

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

    PubMed

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

    2017-02-01

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

  17. Forecasting daily meteorological time series using ARIMA and regression models

    NASA Astrophysics Data System (ADS)

    Murat, Małgorzata; Malinowska, Iwona; Gos, Magdalena; Krzyszczak, Jaromir

    2018-04-01

    The daily air temperature and precipitation time series recorded between January 1, 1980 and December 31, 2010 in four European sites (Jokioinen, Dikopshof, Lleida and Lublin) from different climatic zones were modeled and forecasted. In our forecasting we used the methods of the Box-Jenkins and Holt- Winters seasonal auto regressive integrated moving-average, the autoregressive integrated moving-average with external regressors in the form of Fourier terms and the time series regression, including trend and seasonality components methodology with R software. It was demonstrated that obtained models are able to capture the dynamics of the time series data and to produce sensible forecasts.

  18. Modelling daily dissolved oxygen concentration using least square support vector machine, multivariate adaptive regression splines and M5 model tree

    NASA Astrophysics Data System (ADS)

    Heddam, Salim; Kisi, Ozgur

    2018-04-01

    In the present study, three types of artificial intelligence techniques, least square support vector machine (LSSVM), multivariate adaptive regression splines (MARS) and M5 model tree (M5T) are applied for modeling daily dissolved oxygen (DO) concentration using several water quality variables as inputs. The DO concentration and water quality variables data from three stations operated by the United States Geological Survey (USGS) were used for developing the three models. The water quality data selected consisted of daily measured of water temperature (TE, °C), pH (std. unit), specific conductance (SC, μS/cm) and discharge (DI cfs), are used as inputs to the LSSVM, MARS and M5T models. The three models were applied for each station separately and compared to each other. According to the results obtained, it was found that: (i) the DO concentration could be successfully estimated using the three models and (ii) the best model among all others differs from one station to another.

  19. LiveOcean: A Daily Forecast Model of Ocean Acidification for Shellfish Growers

    NASA Astrophysics Data System (ADS)

    MacCready, P.; Siedlecki, S. A.; McCabe, R. M.

    2016-12-01

    The coastal estuaries of the NE Pacific host a highly productive shellfish industry, but in the past decade they have suffered from many years in which no natural set of oysters occurred. It appears that coastal waters with low Aragonite saturation state may be the cause. This "acidified" water is the result of (i) upwelling of NE Pacific water from near the shelf break that is already low in pH, and (ii) further acidification of that water by productivity and remineralization on the shelf, and (iii) increasing atmospheric CO2. As part of a coordinated research response to this issue, we have developed the LiveOcean modeling system, which creates daily three-day forecasts of circulation and biogeochemical properties in Oregon-Washington-British Columbia coastal and estuarine waters. The system includes realistic tides, atmospheric forcing (from a regional WRF model), ocean boundary conditions (from HYCOM), and rivers (from USGS and Environment Canada). The model is also used for Harmful Algal Bloom prediction. There has been extensive validation of hindcast runs for currents and hydrography, and more limited validation of biogeochemical variables. Model results are pushed daily to the cloud, and made available to the public through the NANOOS Visualization System (NVS). NVS also includes automated model-data comparisons with real-time NDBC and OOI moorings. Future work will focus on optimizing the utility of this system for regional shellfish growers.

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

    PubMed

    Richardson, Clarissa M E; Rice, Kenneth G

    2015-10-01

    Although disclosure of stressful events can alleviate distress, self-critical perfectionism may pose an especially strong impediment to disclosure during stress, likely contributing to poorer psychological well-being. In the current study, after completing a measure of self-critical perfectionism (the Discrepancy subscale of the Almost Perfect Scale--Revised; Slaney, Rice, Mobley, Trippi, & Ashby, 2001), 396 undergraduates completed measures of stress and disclosure at the end of each day for 1 week. Consistent with hypotheses and previous research, multilevel modeling results indicated significant intraindividual coupling of daily stress and daily disclosure where disclosure was more likely when experiencing high stress than low stress. As hypothesized, Discrepancy moderated the relationship between daily stress and daily disclosure. Individuals higher in self-critical perfectionism (Discrepancy) were less likely to engage in disclosure under high stress, when disclosure is often most beneficial, than those with lower Discrepancy scores. These results have implications for understanding the role of stress and coping in the daily lives of self-critical perfectionists. (c) 2015 APA, all rights reserved).

  1. Determination of Semivariogram Models to Krige Hourly and Daily Solar Irradiance in Western Nebraska(.

    NASA Astrophysics Data System (ADS)

    Merino, G. G.; Jones, D.; Stooksbury, D. E.; Hubbard, K. G.

    2001-06-01

    In this paper, linear and spherical semivariogram models were determined for use in kriging hourly and daily solar irradiation for every season of the year. The data used to generate the models were from 18 weather stations in western Nebraska. The models generated were tested using cross validation. The performance of the spherical and linear semivariogram models were compared with each other and also with the semivariogram models based on the best fit to the sample semivariogram of a particular day or hour. There were no significant differences in the performance of the three models. This result and the comparable errors produced by the models in kriging indicated that the linear and spherical models could be used to perform kriging at any hour and day of the year without deriving an individual semivariogram model for that day or hour.The seasonal mean absolute errors associated with kriging, within the network, when using the spherical or the linear semivariograms models were between 10% and 13% of the mean irradiation for daily irradiation and between 12% and 20% for hourly irradiation. These errors represent an improvement of 1%-2% when compared with replacing data at a given site with the data of the nearest weather station.

  2. The role of patients' explanatory models and daily-lived experience in hypertension self-management.

    PubMed

    Bokhour, Barbara G; Cohn, Ellen S; Cortés, Dharma E; Solomon, Jeffrey L; Fix, Gemmae M; Elwy, A Rani; Mueller, Nora; Katz, Lois A; Haidet, Paul; Green, Alexander R; Borzecki, Ann M; Kressin, Nancy R

    2012-12-01

    Uncontrolled hypertension remains a significant problem for many patients. Few interventions to improve patients' hypertension self-management have had lasting effects. Previous work has focused largely on patients' beliefs as predictors of behavior, but little is understood about beliefs as they are embedded in patients' social contexts. This study aims to explore how patients' "explanatory models" of hypertension (understandings of the causes, mechanisms or pathophysiology, course of illness, symptoms and effects of treatment) and social context relate to their reported daily hypertension self-management behaviors. Semi-structured qualitative interviews with a diverse group of patients at two large urban Veterans Administration Medical centers. PARTICIPANTS (OR PATIENTS OR SUBJECTS): African-American, white and Latino Veterans Affairs (VA) primary care patients with uncontrolled blood pressure. We conducted thematic analysis using tools of grounded theory to identify key themes surrounding patients' explanatory models, social context and hypertension management behaviors. Patients' perceptions of the cause and course of hypertension, experiences of hypertension symptoms, and beliefs about the effectiveness of treatment were related to different hypertension self-management behaviors. Moreover, patients' daily-lived experiences, such as an isolated lifestyle, serious competing health problems, a lack of habits and routines, barriers to exercise and prioritizing lifestyle choices, also interfered with optimal hypertension self-management. Designing interventions to improve patients' hypertension self-management requires consideration of patients' explanatory models and their daily-lived experience. We propose a new conceptual model - the dynamic model of hypertension self-management behavior - which incorporates these key elements of patients' experiences.

  3. 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.

  4. Relationships Among Nightly Sleep Quality, Daily Stress, and Daily Affect

    PubMed Central

    Bergeman, Cindy S.; Whitehead, Brenda R.; Braun, Marcia E.; Payne, Jessic D.

    2017-01-01

    Abstract Objectives. We explored the prospective, microlevel relationship between nightly sleep quality (SQ) and the subsequent day’s stress on positive (PA) and negative affect (NA) as well as the moderating relationships between nightly SQ, subsequent stress, and subsequent PA on NA. We investigated whether age moderated these relationships. Method. We collected 56 days of sleep, stress, and affect data using daily diary questionnaires (N = 552). We used multilevel modeling to assess relationships at the between- and within-person levels. Results. Daily increases in SQ and decreases in stress interacted to predict higher daily PA and lower daily NA. Better SQ in older adults enhanced the benefits of PA on the stress–NA relationship more during times of low stress, whereas better sleep in younger adults enhanced the benefits of PA more during times of high stress. Between-person effects were stronger predictors of well-being outcomes than within-person variability. Discussion. The combination of good SQ and higher PA buffered the impact of stress on NA. The moderating impact of age suggests that sleep and stress play different roles across adulthood. Targeting intervention and prevention strategies to improve SQ and enhance PA could disrupt the detrimental relationship between daily stress and NA. PMID:26307483

  5. Changes and Attribution of Extreme Precipitation in Climate Models: Subdaily and Daily Scales

    NASA Astrophysics Data System (ADS)

    Zhang, W.; Villarini, G.; Scoccimarro, E.; Vecchi, G. A.

    2017-12-01

    Extreme precipitation events are responsible for numerous hazards, including flooding, soil erosion, and landslides. Because of their significant socio-economic impacts, the attribution and projection of these events is of crucial importance to improve our response, mitigation and adaptation strategies. Here we present results from our ongoing work.In terms of attribution, we use idealized experiments [pre-industrial control experiment (PI) and 1% per year increase (1%CO2) in atmospheric CO2] from ten general circulation models produced under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and the fraction of attributable risk to examine the CO2 effects on extreme precipitation at the sub-daily and daily scales. We find that the increased CO2 concentration substantially increases the odds of the occurrence of sub-daily precipitation extremes compared to the daily scale in most areas of the world, with the exception of some regions in the sub-tropics, likely in relation to the subsidence of the Hadley Cell. These results point to the large role that atmospheric CO2 plays in extreme precipitation under an idealized framework. Furthermore, we investigate the changes in extreme precipitation events with the Community Earth System Model (CESM) climate experiments using the scenarios consistent with the 1.5°C and 2°C temperature targets. We find that the frequency of annual extreme precipitation at a global scale increases in both 1.5°C and 2°C scenarios until around 2070, after which the magnitudes of the trend become much weaker or even negative. Overall, the frequency of global annual extreme precipitation is similar between 1.5°C and 2°C for the period 2006-2035, and the changes in extreme precipitation in individual seasons are consistent with those for the entire year. The frequency of extreme precipitation in the 2°C experiments is higher than for the 1.5°C experiment after the late 2030s, particularly for the period 2071-2100.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  7. Modelling daily water temperature from air temperature for the Missouri River.

    PubMed

    Zhu, Senlin; Nyarko, Emmanuel Karlo; Hadzima-Nyarko, Marijana

    2018-01-01

    The bio-chemical and physical characteristics of a river are directly affected by water temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex problem to accurately estimate water temperature. Modelling of river water temperature is usually based on a suitable mathematical model and field measurements of various atmospheric factors. In this article, the air-water temperature relationship of the Missouri River is investigated by developing three different machine learning models (Artificial Neural Network (ANN), Gaussian Process Regression (GPR), and Bootstrap Aggregated Decision Trees (BA-DT)). Standard models (linear regression, non-linear regression, and stochastic models) are also developed and compared to machine learning models. Analyzing the three standard models, the stochastic model clearly outperforms the standard linear model and nonlinear model. All the three machine learning models have comparable results and outperform the stochastic model, with GPR having slightly better results for stations No. 2 and 3, while BA-DT has slightly better results for station No. 1. The machine learning models are very effective tools which can be used for the prediction of daily river temperature.

  8. Estimating Daily Evapotranspiration Based on A Model of Evapotranspiration Fraction (EF) for Mixed Pixels

    NASA Astrophysics Data System (ADS)

    Xin, X.; Li, F.; Peng, Z.; Qinhuo, L.

    2017-12-01

    Land surface heterogeneities significantly affect the reliability and accuracy of remotely sensed evapotranspiration (ET), and it gets worse for lower resolution data. At the same time, temporal scale extrapolation of the instantaneous latent heat flux (LE) at satellite overpass time to daily ET are crucial for applications of such remote sensing product. The purpose of this paper is to propose a simple but efficient model for estimating daytime evapotranspiration considering heterogeneity of mixed pixels. In order to do so, an equation to calculate evapotranspiration fraction (EF) of mixed pixels was derived based on two key assumptions. Assumption 1: the available energy (AE) of each sub-pixel equals approximately to that of any other sub-pixels in the same mixed pixel within acceptable margin of bias, and as same as the AE of the mixed pixel. It's only for a simpification of the equation, and its uncertainties and resulted errors in estimated ET are very small. Assumption 2: EF of each sub-pixel equals to the EF of the nearest pure pixel(s) of same land cover type. This equation is supposed to be capable of correcting the spatial scale error of the mixed pixels EF and can be used to calculated daily ET with daily AE data.The model was applied to an artificial oasis in the midstream of Heihe River. HJ-1B satellite data were used to estimate the lumped fluxes at the scale of 300 m after resampling the 30-m resolution datasets to 300 m resolution, which was used to carry on the key step of the model. The results before and after correction were compare to each other and validated using site data of eddy-correlation systems. Results indicated that the new model is capable of improving accuracy of daily ET estimation relative to the lumped method. Validations at 12 sites of eddy-correlation systems for 9 days of HJ-1B overpass showed that the R² increased to 0.82 from 0.62; the RMSE decreased to 1.60 MJ/m² from 2.47MJ/m²; the MBE decreased from 1.92 MJ/m² to 1

  9. 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.

  10. 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.

  11. Relationships Among Nightly Sleep Quality, Daily Stress, and Daily Affect.

    PubMed

    Blaxton, Jessica M; Bergeman, Cindy S; Whitehead, Brenda R; Braun, Marcia E; Payne, Jessic D

    2017-05-01

    We explored the prospective, microlevel relationship between nightly sleep quality (SQ) and the subsequent day's stress on positive (PA) and negative affect (NA) as well as the moderating relationships between nightly SQ, subsequent stress, and subsequent PA on NA. We investigated whether age moderated these relationships. We collected 56 days of sleep, stress, and affect data using daily diary questionnaires (N = 552). We used multilevel modeling to assess relationships at the between- and within-person levels. Daily increases in SQ and decreases in stress interacted to predict higher daily PA and lower daily NA. Better SQ in older adults enhanced the benefits of PA on the stress-NA relationship more during times of low stress, whereas better sleep in younger adults enhanced the benefits of PA more during times of high stress. Between-person effects were stronger predictors of well-being outcomes than within-person variability. The combination of good SQ and higher PA buffered the impact of stress on NA. The moderating impact of age suggests that sleep and stress play different roles across adulthood. Targeting intervention and prevention strategies to improve SQ and enhance PA could disrupt the detrimental relationship between daily stress and NA. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  13. 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.

  14. Estimating daily minimum, maximum, and mean near surface air temperature using hybrid satellite models across Israel.

    PubMed

    Rosenfeld, Adar; Dorman, Michael; Schwartz, Joel; Novack, Victor; Just, Allan C; Kloog, Itai

    2017-11-01

    Meteorological stations measure air temperature (Ta) accurately with high temporal resolution, but usually suffer from limited spatial resolution due to their sparse distribution across rural, undeveloped or less populated areas. Remote sensing satellite-based measurements provide daily surface temperature (Ts) data in high spatial and temporal resolution and can improve the estimation of daily Ta. In this study we developed spatiotemporally resolved models which allow us to predict three daily parameters: Ta Max (day time), 24h mean, and Ta Min (night time) on a fine 1km grid across the state of Israel. We used and compared both the Aqua and Terra MODIS satellites. We used linear mixed effect models, IDW (inverse distance weighted) interpolations and thin plate splines (using a smooth nonparametric function of longitude and latitude) to first calibrate between Ts and Ta in those locations where we have available data for both and used that calibration to fill in neighboring cells without surface monitors or missing Ts. Out-of-sample ten-fold cross validation (CV) was used to quantify the accuracy of our predictions. Our model performance was excellent for both days with and without available Ts observations for both Aqua and Terra (CV Aqua R 2 results for min 0.966, mean 0.986, and max 0.967; CV Terra R 2 results for min 0.965, mean 0.987, and max 0.968). Our research shows that daily min, mean and max Ta can be reliably predicted using daily MODIS Ts data even across Israel, with high accuracy even for days without Ta or Ts data. These predictions can be used as three separate Ta exposures in epidemiology studies for better diurnal exposure assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. 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.

  16. 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

  17. The Hydrometeorological DREAM: A Daily REcharge Assessment Model, for the Israeli Western Mountain Aquifer

    NASA Astrophysics Data System (ADS)

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

    2008-05-01

    The western part of the Israeli Mountain Aquifer (WMA) supplies 360-400 MCM/y of fresh water to the Israeli water budget, which is approximately 20% of the total consumption. The annually recharge to the WMA is considered to be 25-35% of annual rainfall. The high variability in recharge to the WMA is due to spatial and temporal differences in the rain contributing to the aquifer. Different winters producing the same amount of rain may contribute differently to the aquifer due to the locations of the storms, intensity, duration, dry spells between successive rain events, etc. Moreover, besides the climatic-meteorological factors, the recharge is dependent also on geographical factors, such as lithology, pedology, land-use, slope gradient, slope direction etc. The need for a robust reliable Hydrometeorological Daily basis REcharge Assessment Model (Hydrometeorological DREAM) brought us to develop a model with a relatively high spatial and temporal resolution. The concept is based on a relatively simple water budget that states that rainfall over land is added to the soil, and removed later on by means of evapotranspiration, recharge and runoff. The method in use to date at the Hydrological Service for estimating recharge to the WMA is based on an annual regression curve that can be implemented only after the total annual rainfall is known. The DREAM is a near real time estimator of recharge to the WMA using daily rainfall and pan evaporation data. Comparison of the DREAM results with the annual regression curve show a high agreement on an annual basis. The improvements introduced by the DREAM are: 1) Near real time daily values of infiltration, as opposed to calculated annual values established after the rain season is over. 2) High spatial resolution. The DREAM produces daily recharge values in more than 3000 mesh points throughout the 2200 km2 of recharge area. By linking the DREAM output as input to a hydrogeological model (such as FEFLOW, MODFLOW etc.) a

  18. High-resolution spatial modeling of daily weather elements for a catchment in the Oregon Cascade Mountains, United States

    Treesearch

    Christopher Daly; Jonathan W. Smith; Joseph I. Smith; Robert B. McKane

    2007-01-01

    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 decisionmaking. This paper describes the development. application. and assessment of methods to construct daily high resolution (~50-m cell size) meteorological grids for the...

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

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

    PubMed Central

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

    2016-01-01

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

  1. Modelling daily PM2.5 concentrations at high spatio-temporal resolution across Switzerland.

    PubMed

    de Hoogh, Kees; Héritier, Harris; Stafoggia, Massimo; Künzli, Nino; Kloog, Itai

    2018-02-01

    Spatiotemporal resolved models were developed predicting daily fine particulate matter (PM 2.5 ) concentrations across Switzerland from 2003 to 2013. Relatively sparse PM 2.5 monitoring data was supplemented by imputing PM 2.5 concentrations at PM 10 sites, using PM 2.5 /PM 10 ratios at co-located sites. Daily PM 2.5 concentrations were first estimated at a 1 × 1km resolution across Switzerland, using Multiangle Implementation of Atmospheric Correction (MAIAC) spectral aerosol optical depth (AOD) data in combination with spatiotemporal predictor data in a four stage approach. Mixed effect models (1) were used to predict PM 2.5 in cells with AOD but without PM 2.5 measurements (2). A generalized additive mixed model with spatial smoothing was applied to generate grid cell predictions for those grid cells where AOD was missing (3). Finally, local PM 2.5 predictions were estimated at each monitoring site by regressing the residuals from the 1 × 1km estimate against local spatial and temporal variables using machine learning techniques (4) and adding them to the stage 3 global estimates. The global (1 km) and local (100 m) models explained on average 73% of the total,71% of the spatial and 75% of the temporal variation (all cross validated) globally and on average 89% (total) 95% (spatial) and 88% (temporal) of the variation locally in measured PM 2.5 concentrations. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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

    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 dailymore » temperature within TCR will be 97.8%.« less

  3. [Multilevel model analysis on the relevant factors influencing the total amount of drinking water consumed daily by Beijing residents].

    PubMed

    Zhao, Jinhui; Wei, Jianrong; Chen, Huajie; Liu, Yumin; Li, Tiantian; Sun, Qinghua; Liu, Qiaolan

    2012-09-01

    To investigate the influencing factors for daily water intake of Beijing residents. A multi-stage sampling method was constructed to interview 270 Beijing residents in the winter of 2009 and in the summer of 2010 by using a questionnaire to collect data on daily drinking water consumption. Multilevel models were used to analyze the variation and influencing factors for the amount of water intake. Multilevel model results showed that the average daily water intake of residents living in different villages or neighborhood committees was statistically significant (sigma2 mu0 = = 0.030 (0.009), P < 0.05). The individual variation in the same village or neighborhood committee was also significant (sigma2 e0 = 0.157 (0.010), P < 0.05). Season, gender, and body weight affected the daily water intake (P < 0.05). There were interaction between season and source of water supply. The average daily water intake of residents was affected by several factors. In the health risk assessment of drinking water, it needs considering not only the individual characteristics but also the differences of villages/neighborhood committees and the seasonal variation.

  4. 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.

  5. Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City.

    PubMed

    Chau, Tang-Tat; Wang, Kuo-Ying

    2016-01-01

    An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007-2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0-15 years old). Middle-aged people (16-65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8-1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place.

  6. Association between Daily Hospital Outpatient Visits for Accidents and Daily Ambient Air Temperatures in an Industrial City

    PubMed Central

    Chau, Tang-Tat; Wang, Kuo-Ying

    2016-01-01

    An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007–2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0–15 years old). Middle-aged people (16–65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8–1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place. PMID

  7. Randomized controlled trial comparing impact on platelet reactivity of twice-daily with once-daily aspirin in people with Type 2 diabetes.

    PubMed

    Bethel, M A; Harrison, P; Sourij, H; Sun, Y; Tucker, L; Kennedy, I; White, S; Hill, L; Oulhaj, A; Coleman, R L; Holman, R R

    2016-02-01

    Reduced aspirin efficacy has been demonstrated in people with Type 2 diabetes. Because increased platelet reactivity and/or turnover are postulated mechanisms, we examined whether higher and/or more frequent aspirin dosing might reduce platelet reactivity more effectively. Participants with Type 2 diabetes (n = 24) but without known cardiovascular disease were randomized in a three-way crossover design to 2-week treatment periods with aspirin 100 mg once daily, 200 mg once daily or 100 mg twice daily. The primary outcome was platelet reactivity, assessed using the VerifyNow(™) ASA method. Relationships between platelet reactivity and aspirin dosing were examined using generalized linear mixed models with random subject effects. Platelet reactivity decreased from baseline with all doses of aspirin. Modelled platelet reactivity was more effectively reduced with aspirin 100 mg twice daily vs. 100 mg once daily, but not vs. 200 mg once daily. Aspirin 200 mg once daily did not differ from 100 mg once daily. Aspirin 100 mg twice daily was also more effective than once daily as measured by collagen/epinephrine-stimulated platelet aggregation and urinary thromboxane levels, with a similar trend measured by serum thromboxane levels. No episodes of bleeding occurred. In Type 2 diabetes, aspirin 100 mg twice daily reduced platelet reactivity more effectively than 100 mg once daily, and numerically more than 200 mg once daily. Clinical outcome trials evaluating primary cardiovascular disease prevention with aspirin in Type 2 diabetes may need to consider using a more frequent dosing schedule. © 2015 The Authors. Diabetic Medicine © 2015 Diabetes UK.

  8. 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.

  9. 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

  10. 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.

  11. 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, Paul 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.

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

    PubMed Central

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

    2015-01-01

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

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

    USDA-ARS?s Scientific Manuscript database

    Many applications of simulation models and related decision support tools for agriculture and natural resource management require daily meteorological data as inputs. Availability and quality of such data, however, often constrain research and decision support activities that require use of these to...

  14. 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

  15. 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

  16. Jordan recurrent neural network versus IHACRES in modelling daily streamflows

    NASA Astrophysics Data System (ADS)

    Carcano, Elena Carla; Bartolini, Paolo; Muselli, Marco; Piroddi, Luigi

    2008-12-01

    SummaryA study of possible scenarios for modelling streamflow data from daily time series, using artificial neural networks (ANNs), is presented. Particular emphasis is devoted to the reconstruction of drought periods where water resource management and control are most critical. This paper considers two connectionist models: a feedforward multilayer perceptron (MLP) and a Jordan recurrent neural network (JNN), comparing network performance on real world data from two small catchments (192 and 69 km 2 in size) with irregular and torrential regimes. Several network configurations are tested to ensure a good combination of input features (rainfall and previous streamflow data) that capture the variability of the physical processes at work. Tapped delayed line (TDL) and memory effect techniques are introduced to recognize and reproduce temporal dependence. Results show a poor agreement when using TDL only, but a remarkable improvement can be obtained with JNN and its memory effect procedures, which are able to reproduce the system memory over a catchment in a more effective way. Furthermore, the IHACRES conceptual model, which relies on both rainfall and temperature input data, is introduced for comparative study. The results suggest that when good input data is unavailable, metric models perform better than conceptual ones and, in general, it is difficult to justify substantial conceptualization of complex processes.

  17. 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

  18. A computational cognitive model of self-efficacy and daily adherence in mHealth.

    PubMed

    Pirolli, Peter

    2016-12-01

    Mobile health (mHealth) applications provide an excellent opportunity for collecting rich, fine-grained data necessary for understanding and predicting day-to-day health behavior change dynamics. A computational predictive model (ACT-R-DStress) is presented and fit to individual daily adherence in 28-day mHealth exercise programs. The ACT-R-DStress model refines the psychological construct of self-efficacy. To explain and predict the dynamics of self-efficacy and predict individual performance of targeted behaviors, the self-efficacy construct is implemented as a theory-based neurocognitive simulation of the interaction of behavioral goals, memories of past experiences, and behavioral performance.

  19. Unravelling daily human mobility motifs

    PubMed Central

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

    2013-01-01

    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. PMID:23658117

  20. Never, non-daily, and daily smoking status and progression to daily cigarette smoking as correlates of major depressive episode in a national sample of youth: Results from the National Survey of Drug Use and Health 2013 to 2015.

    PubMed

    Cohn, Amy M

    2018-09-01

    Cigarette smoking is associated with depression, and new initiates who progress more quickly to daily smoking may be at enhanced risk. In a nationally representative sample of youth, this study examined the association between daily, non-daily, and never smoking with past-year and lifetime major depressive episode (MDE) and, among daily smokers, whether faster progression to daily smoking was associated with increased MDE risk. Data were from n = 44,921 youth aged 12-17 in the 2013-2015 National Survey on Drug Use and Health. Weighted adjusted multivariable logistic regression models were used to examine the association of smoking status (daily, non-daily, never) with lifetime and past-year MDE, and the association between progression from cigarette trial to daily smoking with MDE outcomes among daily smokers. Daily and non-daily smokers had similar rates of lifetime and past-year MDE; rates of MDE were approximately 50% lower among never smokers. Compared to never smokers, adjusted models showed that non-daily smokers had a higher risk of past-year and lifetime MDE, while daily smokers had a higher risk of past-year but not lifetime MDE. Daily smoking youth who progressed more quickly from cigarette trial to daily use had an increased risk of both lifetime and past-year MDE. Prevention programs should target factors associated with the shift from cigarette experimentation to regular use to curb deleterious consequences of use. Copyright © 2018. Published by Elsevier Ltd.

  1. Daily reservoir sedimentation model: Case study from the Fena Valley Reservoir, Guam

    USGS Publications Warehouse

    Marineau, Mathieu D.; Wright, Scott A.

    2017-01-01

    A model to compute reservoir sedimentation rates at daily timescales is presented. The model uses streamflow and sediment load data from nearby stream gauges to obtain an initial estimate of sediment yield for the reservoir’s watershed; it is then calibrated to the total deposition calculated from repeat bathymetric surveys. Long-term changes to reservoir trapping efficiency are also taken into account. The model was applied to the Fena Valley Reservoir, a water supply reservoir on the island of Guam. This reservoir became operational in 1951 and was recently surveyed in 2014. The model results show that the highest rate of deposition occurred during two typhoons (Typhoon Alice in 1953 and Typhoon Tingting in 2004); each storm decreased reservoir capacity by approximately 2–3% in only a few days. The presented model can be used to evaluate the impact of an extreme event, or it can be coupled with a watershed runoff model to evaluate potential impacts to storage capacity as a result of climate change or other hydrologic modifications.

  2. Evaluation of average daily gain predictions by the integrated farm system model for forage-finished beef steers

    USDA-ARS?s Scientific Manuscript database

    Representing the performance of cattle finished on an all forage diet in process-based whole farm system models has presented a challenge. To address this challenge, a study was done to evaluate average daily gain (ADG) predictions of the Integrated Farm System Model (IFSM) for steers consuming all-...

  3. A low free-parameter stochastic model of daily Forbush decrease indices

    NASA Astrophysics Data System (ADS)

    Patra, Sankar Narayan; Bhattacharya, Gautam; Panja, Subhash Chandra; Ghosh, Koushik

    2014-01-01

    Forbush decrease is a rapid decrease in the observed galactic cosmic ray intensity pattern occurring after a coronal mass ejection. In the present paper we have analyzed the daily Forbush decrease indices from January, 1967 to December, 2003 generated in IZMIRAN, Russia. First the entire indices have been smoothened and next we have made an attempt to fit a suitable stochastic model for the present time series by means of a necessary number of process parameters. The study reveals that the present time series is governed by a stationary autoregressive process of order 2 with a trace of white noise. Under the consideration of the present model we have shown that chaos is not expected in the present time series which opens up the possibility of validation of its forecasting (both short-term and long-term) as well as its multi-periodic behavior.

  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. 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

  6. A Daily Diary Approach to the Examination of Chronic Stress, Daily Hassles and Safety Perceptions in Hospital Nursing.

    PubMed

    Louch, Gemma; O'Hara, Jane; Gardner, Peter; O'Connor, Daryl B

    2017-12-01

    Stress is a significant concern for individuals and organisations. Few studies have explored stress, burnout and patient safety in hospital nursing on a daily basis at the individual level. This study aimed to examine the effects of chronic stress and daily hassles on safety perceptions, the effect of chronic stress on daily hassles experienced and chronic stress as a potential moderator. Utilising a daily diary design, 83 UK hospital nurses completed three end-of-shift diaries, yielding 324 person days. Hassles, safety perceptions and workplace cognitive failure were measured daily, and a baseline questionnaire included a measure of chronic stress. Hierarchical multivariate linear modelling was used to analyse the data. Higher chronic stress was associated with more daily hassles, poorer perceptions of safety and being less able to practise safely, but not more workplace cognitive failure. Reporting more daily hassles was associated with poorer perceptions of safety, being less able to practise safely and more workplace cognitive failure. Chronic stress did not moderate daily associations. The hassles reported illustrate the wide-ranging hassles nurses experienced. The findings demonstrate, in addition to chronic stress, the importance of daily hassles for nurses' perceptions of safety and the hassles experienced by hospital nurses on a daily basis. Nurses perceive chronic stress and daily hassles to contribute to their perceptions of safety. Measuring the number of daily hassles experienced could proactively highlight when patient safety threats may arise, and as a result, interventions could usefully focus on the management of daily hassles.

  7. Forecasting daily patient volumes in the emergency department.

    PubMed

    Jones, Spencer S; Thomas, Alun; Evans, R Scott; Welch, Shari J; Haug, Peter J; Snow, Gregory L

    2008-02-01

    Shifts in the supply of and demand for emergency department (ED) resources make the efficient allocation of ED resources increasingly important. Forecasting is a vital activity that guides decision-making in many areas of economic, industrial, and scientific planning, but has gained little traction in the health care industry. There are few studies that explore the use of forecasting methods to predict patient volumes in the ED. The goals of this study are to explore and evaluate the use of several statistical forecasting methods to predict daily ED patient volumes at three diverse hospital EDs and to compare the accuracy of these methods to the accuracy of a previously proposed forecasting method. Daily patient arrivals at three hospital EDs were collected for the period January 1, 2005, through March 31, 2007. The authors evaluated the use of seasonal autoregressive integrated moving average, time series regression, exponential smoothing, and artificial neural network models to forecast daily patient volumes at each facility. Forecasts were made for horizons ranging from 1 to 30 days in advance. The forecast accuracy achieved by the various forecasting methods was compared to the forecast accuracy achieved when using a benchmark forecasting method already available in the emergency medicine literature. All time series methods considered in this analysis provided improved in-sample model goodness of fit. However, post-sample analysis revealed that time series regression models that augment linear regression models by accounting for serial autocorrelation offered only small improvements in terms of post-sample forecast accuracy, relative to multiple linear regression models, while seasonal autoregressive integrated moving average, exponential smoothing, and artificial neural network forecasting models did not provide consistently accurate forecasts of daily ED volumes. This study confirms the widely held belief that daily demand for ED services is characterized by

  8. 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...

  9. Optimization of Large-Scale Daily Hydrothermal System Operations With Multiple Objectives

    NASA Astrophysics Data System (ADS)

    Wang, Jian; Cheng, Chuntian; Shen, Jianjian; Cao, Rui; Yeh, William W.-G.

    2018-04-01

    This paper proposes a practical procedure for optimizing the daily operation of a large-scale hydrothermal system. The overall procedure optimizes a monthly model over a period of 1 year and a daily model over a period of up to 1 month. The outputs from the monthly model are used as inputs and boundary conditions for the daily model. The models iterate and update when new information becomes available. The monthly hydrothermal model uses nonlinear programing (NLP) to minimize fuel costs, while maximizing hydropower production. The daily model consists of a hydro model, a thermal model, and a combined hydrothermal model. The hydro model and thermal model generate the initial feasible solutions for the hydrothermal model. The two competing objectives considered in the daily hydrothermal model are minimizing fuel costs and minimizing thermal emissions. We use the constraint method to develop the trade-off curve (Pareto front) between these two objectives. We apply the proposed methodology on the Yunnan hydrothermal system in China. The system consists of 163 individual hydropower plants with an installed capacity of 48,477 MW and 11 individual thermal plants with an installed capacity of 12,400 MW. We use historical operational records to verify the correctness of the model and to test the robustness of the methodology. The results demonstrate the practicability and validity of the proposed procedure.

  10. Daily life activity routine discovery in hemiparetic rehabilitation patients using topic models.

    PubMed

    Seiter, J; Derungs, A; Schuster-Amft, C; Amft, O; Tröster, G

    2015-01-01

    Monitoring natural behavior and activity routines of hemiparetic rehabilitation patients across the day can provide valuable progress information for therapists and patients and contribute to an optimized rehabilitation process. In particular, continuous patient monitoring could add type, frequency and duration of daily life activity routines and hence complement standard clinical scores that are assessed for particular tasks only. Machine learning methods have been applied to infer activity routines from sensor data. However, supervised methods require activity annotations to build recognition models and thus require extensive patient supervision. Discovery methods, including topic models could provide patient routine information and deal with variability in activity and movement performance across patients. Topic models have been used to discover characteristic activity routine patterns of healthy individuals using activity primitives recognized from supervised sensor data. Yet, the applicability of topic models for hemiparetic rehabilitation patients and techniques to derive activity primitives without supervision needs to be addressed. We investigate, 1) whether a topic model-based activity routine discovery framework can infer activity routines of rehabilitation patients from wearable motion sensor data. 2) We compare the performance of our topic model-based activity routine discovery using rule-based and clustering-based activity vocabulary. We analyze the activity routine discovery in a dataset recorded with 11 hemiparetic rehabilitation patients during up to ten full recording days per individual in an ambulatory daycare rehabilitation center using wearable motion sensors attached to both wrists and the non-affected thigh. We introduce and compare rule-based and clustering-based activity vocabulary to process statistical and frequency acceleration features to activity words. Activity words were used for activity routine pattern discovery using topic models

  11. Estimation of daily reference evapotranspiration (ETo) using artificial intelligence methods: Offering a new approach for lagged ETo data-based modeling

    NASA Astrophysics Data System (ADS)

    Mehdizadeh, Saeid

    2018-04-01

    Evapotranspiration (ET) is considered as a key factor in hydrological and climatological studies, agricultural water management, irrigation scheduling, etc. It can be directly measured using lysimeters. Moreover, other methods such as empirical equations and artificial intelligence methods can be used to model ET. In the recent years, artificial intelligence methods have been widely utilized to estimate reference evapotranspiration (ETo). In the present study, local and external performances of multivariate adaptive regression splines (MARS) and gene expression programming (GEP) were assessed for estimating daily ETo. For this aim, daily weather data of six stations with different climates in Iran, namely Urmia and Tabriz (semi-arid), Isfahan and Shiraz (arid), Yazd and Zahedan (hyper-arid) were employed during 2000-2014. Two types of input patterns consisting of weather data-based and lagged ETo data-based scenarios were considered to develop the models. Four statistical indicators including root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE) were used to check the accuracy of models. The local performance of models revealed that the MARS and GEP approaches have the capability to estimate daily ETo using the meteorological parameters and the lagged ETo data as inputs. Nevertheless, the MARS had the best performance in the weather data-based scenarios. On the other hand, considerable differences were not observed in the models' accuracy for the lagged ETo data-based scenarios. In the innovation of this study, novel hybrid models were proposed in the lagged ETo data-based scenarios through combination of MARS and GEP models with autoregressive conditional heteroscedasticity (ARCH) time series model. It was concluded that the proposed novel models named MARS-ARCH and GEP-ARCH improved the performance of ETo modeling compared to the single MARS and GEP. In addition, the external

  12. Adaptation to daily stress among mothers of children with an autism spectrum disorder: the role of daily positive affect.

    PubMed

    Ekas, Naomi V; Whitman, Thomas L

    2011-09-01

    Raising a child with an autism spectrum disorder is a challenging experience that can impact maternal well-being. Using a daily diary methodology, this study investigates (1) the relationship between stress and negative affect, and (2) the role of daily positive affect as a protective factor in the stress and negative affect relationship. Results from hierarchical linear models revealed that higher levels of stress were associated with decreased negative affect, both within and across days. Daily positive affect buffered the immediate and longer-lasting negative impact of stress on days of low to moderate levels of stress. Implications of the present study are discussed with regard to theoretical models of positive affect, the development of intervention programs, and directions for future research.

  13. 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.

  14. Modeling aspen and red pine shoot growth to daily weather variations.

    Treesearch

    Donald A. Perala

    1983-01-01

    Quantifies daily shoot growth of quaking aspen and red pine in response to daily variation in air temperature, soil moisture, solar radiation, evapotranspiration, and inherent seasonal plant growth rhythm. Discusses potential application of shoot growth equations to silvicultural problems related to microclimatic variation. Identifies limitations and areas for...

  15. Seasonal & Daily Amazon Column CO2 & CO Observations from Ground & Space Used to Evaluate Tropical Ecosystem Models

    NASA Astrophysics Data System (ADS)

    Dubey, M. K.; Parker, H. A.; Wennberg, P. O.; Wunch, D.; Jacobson, A. R.; Kawa, S. R.; Keppel-Aleks, G.; Basu, S.; O'Dell, C.; Frankenberg, C.; Michalak, A. M.; Baker, D. F.; Christofferson, B.; Restrepo-Coupe, N.; Saleska, S. R.; De Araujo, A. C.; Miller, J. B.

    2016-12-01

    The Amazon basin stores 150-200 PgC, exchanges 18 PgC with the atmosphere every year and has taken up 0.42-0.65 PgC/y over the past two decades. Despite its global significance, the response of the tropical carbon cycle to climate variability and change is ill constrained as evidenced by the large negative and positive feedbacks in future climate simulations. The complex interplay of radiation, water and ecosystem phenology remains unresolved in current tropical ecosystem models. We use high frequency regional scale TCCON observations of column CO2, CO and CH4 near Manaus, Brazil that began in October 2014 to understand the aforementioned interplay of processes in regulating biosphere-atmosphere exchange. We observe a robust daily column CO2 uptake of about 2 ppm (4 ppm to 0.5 ppm) over 8 hours and evaluate how it changes as we transition to the dry season. Back-trajectory calculations show that the daily CO2 uptake footprint is terrestrial and influenced by the heterogeneity of the Amazon rain forests. The column CO falls from above 120 ppb to below 80 ppb as we transition from the biomass burning to wet seasons. The daily mean column CO2 rises by 3 ppm from October through June. Removal of biomass burning, secular CO2 increase and variations from transport (by Carbon tracker simulations) implies an increase of 2.3 ppm results from tropical biospheric processes (respiration and photosynthesis). This is consistent with ground-based remote sensing and eddy flux observations that indicate that leaf development and demography drives the tropical carbon cycle in regions that are not water limited and is not considered in current models. We compare our observations with output from 7 CO2 inversion transport models with assimilated meteorology and find that while 5 models reproduce the CO2 seasonal cycle all of them under predict the daily drawdown of CO2 by a factor of 3. This indicates that the CO2 flux partitioning between photosynthesis and respiration is incorrect

  16. 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.

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

    USDA-ARS?s Scientific Manuscript database

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

  18. Non-Gaussian spatiotemporal simulation of multisite daily precipitation: downscaling framework

    NASA Astrophysics Data System (ADS)

    Ben Alaya, M. A.; Ouarda, T. B. M. J.; Chebana, F.

    2018-01-01

    Probabilistic regression approaches for downscaling daily precipitation are very useful. They provide the whole conditional distribution at each forecast step to better represent the temporal variability. The question addressed in this paper is: how to simulate spatiotemporal characteristics of multisite daily precipitation from probabilistic regression models? Recent publications point out the complexity of multisite properties of daily precipitation and highlight the need for using a non-Gaussian flexible tool. This work proposes a reasonable compromise between simplicity and flexibility avoiding model misspecification. A suitable nonparametric bootstrapping (NB) technique is adopted. A downscaling model which merges a vector generalized linear model (VGLM as a probabilistic regression tool) and the proposed bootstrapping technique is introduced to simulate realistic multisite precipitation series. The model is applied to data sets from the southern part of the province of Quebec, Canada. It is shown that the model is capable of reproducing both at-site properties and the spatial structure of daily precipitations. Results indicate the superiority of the proposed NB technique, over a multivariate autoregressive Gaussian framework (i.e. Gaussian copula).

  19. Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

    NASA Astrophysics Data System (ADS)

    Anand, Jasdeep S.; Monks, Paul S.

    2017-07-01

    Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

  20. Daily job demands and employee work engagement: The role of daily transformational leadership behavior.

    PubMed

    Breevaart, Kimberley; Bakker, Arnold B

    2018-07-01

    Using job demands-resources (JD-R) theory, the present study integrates the challenge stressor-hindrance stressor framework and leadership theory to investigate the relationship between daily transformational leadership behavior and employee work engagement. We hypothesized that daily transformational leadership behavior (a) sustains employee work engagement on days characterized by high challenge job demands, and (b) protects work engagement on days characterized by high hindrance job demands. Teachers filled out a short online questionnaire at the end of each workday during a 2-week period (N = 271 × 5.68 days = 1539). Results of latent moderated structural equation modeling showed that teachers' daily challenge demands (workload and cognitive demands) had a positive relationship with work engagement on the days transformational leadership was high (vs. low). In addition, teachers' daily hindrance demands (role-conflict, but not family to work conflict) had a negative relationship with work engagement on the days transformational leadership was low (vs. high). These findings show that the function of transformational leadership behavior changes from day to day, and depends on the type of job demand. We discuss the practical and theoretical implications of these findings. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  1. 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…

  2. Research on Daily Objects Detection Based on Deep Neural Network

    NASA Astrophysics Data System (ADS)

    Ding, Sheng; Zhao, Kun

    2018-03-01

    With the rapid development of deep learning, great breakthroughs have been made in the field of object detection. In this article, the deep learning algorithm is applied to the detection of daily objects, and some progress has been made in this direction. Compared with traditional object detection methods, the daily objects detection method based on deep learning is faster and more accurate. The main research work of this article: 1. collect a small data set of daily objects; 2. in the TensorFlow framework to build different models of object detection, and use this data set training model; 3. the training process and effect of the model are improved by fine-tuning the model parameters.

  3. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  5. Modelling nitrous oxide emissions from mown-grass and grain-cropping systems: Testing and sensitivity analysis of DailyDayCent using high frequency measurements.

    PubMed

    Senapati, Nimai; Chabbi, Abad; Giostri, André Faé; Yeluripati, Jagadeesh B; Smith, Pete

    2016-12-01

    The DailyDayCent biogeochemical model was used to simulate nitrous oxide (N 2 O) emissions from two contrasting agro-ecosystems viz. a mown-grassland and a grain-cropping system in France. Model performance was tested using high frequency measurements over three years; additionally a local sensitivity analysis was performed. Annual N 2 O emissions of 1.97 and 1.24kgNha -1 year -1 were simulated from mown-grassland and grain-cropland, respectively. Measured and simulated water filled pore space (r=0.86, ME=-2.5%) and soil temperature (r=0.96, ME=-0.63°C) at 10cm soil depth matched well in mown-grassland. The model predicted cumulative hay and crop production effectively. The model simulated soil mineral nitrogen (N) concentrations, particularly ammonium (NH 4 + ), reasonably, but the model significantly underestimated soil nitrate (NO 3 - ) concentration under both systems. In general, the model effectively simulated the dynamics and the magnitude of daily N 2 O flux over the whole experimental period in grain-cropland (r=0.16, ME=-0.81gNha -1 day -1 ), with reasonable agreement between measured and modelled N 2 O fluxes for the mown-grassland (r=0.63, ME=-0.65gNha -1 day -1 ). Our results indicate that DailyDayCent has potential for use as a tool for predicting overall N 2 O emissions in the study region. However, in-depth analysis shows some systematic discrepancies between measured and simulated N 2 O fluxes on a daily basis. The current exercise suggests that the DailyDayCent may need improvement, particularly the sub-module responsible for N transformations, for better simulating soil mineral N, especially soil NO 3 - concentration, and N 2 O flux on a daily basis. The sensitivity analysis shows that many factors such as climate change, N-fertilizer use, input uncertainty and parameter value could influence the simulation of N 2 O emissions. Sensitivity estimation also helped to identify critical parameters, which need careful estimation or site

  6. SDCLIREF - A sub-daily gridded reference dataset

    NASA Astrophysics Data System (ADS)

    Wood, Raul R.; Willkofer, Florian; Schmid, Franz-Josef; Trentini, Fabian; Komischke, Holger; Ludwig, Ralf

    2017-04-01

    Climate change is expected to impact the intensity and frequency of hydrometeorological extreme events. In order to adequately capture and analyze extreme rainfall events, in particular when assessing flood and flash flood situations, data is required at high spatial and sub-daily resolution which is often not available in sufficient density and over extended time periods. The ClimEx project (Climate Change and Hydrological Extreme Events) addresses the alteration of hydrological extreme events under climate change conditions. In order to differentiate between a clear climate change signal and the limits of natural variability, unique Single-Model Regional Climate Model Ensembles (CRCM5 driven by CanESM2, RCP8.5) were created for a European and North-American domain, each comprising 50 members of 150 years (1951-2100). In combination with the CORDEX-Database, this newly created ClimEx-Ensemble is a one-of-a-kind model dataset to analyze changes of sub-daily extreme events. For the purpose of bias-correcting the regional climate model ensembles as well as for the baseline calibration and validation of hydrological catchment models, a new sub-daily (3h) high-resolution (500m) gridded reference dataset (SDCLIREF) was created for a domain covering the Upper Danube and Main watersheds ( 100.000km2). As the sub-daily observations lack a continuous time series for the reference period 1980-2010, the need for a suitable method to bridge the gap of the discontinuous time series arouse. The Method of Fragments (Sharma and Srikanthan (2006); Westra et al. (2012)) was applied to transform daily observations to sub-daily rainfall events to extend the time series and densify the station network. Prior to applying the Method of Fragments and creating the gridded dataset using rigorous interpolation routines, data collection of observations, operated by several institutions in three countries (Germany, Austria, Switzerland), and the subsequent quality control of the observations

  7. 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.; hide

    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

  8. 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

  9. Modeling daily soil salinity dynamics in response to agricultural and environmental changes in coastal Bangladesh

    NASA Astrophysics Data System (ADS)

    Payo, Andrés.; Lázár, Attila N.; Clarke, Derek; Nicholls, Robert J.; Bricheno, Lucy; Mashfiqus, Salehin; Haque, Anisul

    2017-05-01

    Understanding the dynamics of salt movement in the soil is a prerequisite for devising appropriate management strategies for land productivity of coastal regions, especially low-lying delta regions, which support many millions of farmers around the world. At present, there are no numerical models able to resolve soil salinity at regional scale and at daily time steps. In this research, we develop a novel holistic approach to simulate soil salinization comprising an emulator-based soil salt and water balance calculated at daily time steps. The method is demonstrated for the agriculture areas of coastal Bangladesh (˜20,000 km2). This shows that we can reproduce the dynamics of soil salinity under multiple land uses, including rice crops, combined shrimp and rice farming, as well as non-rice crops. The model also reproduced well the observed spatial soil salinity for the year 2009. Using this approach, we have projected the soil salinity for three different climate ensembles, including relative sea-level rise for the year 2050. Projected soil salinity changes are significantly smaller than other reported projections. The results suggest that inter-season weather variability is a key driver of salinization of agriculture soils at coastal Bangladesh.

  10. Chronic and Daily Stressors Along With Negative Affect Interact to Predict Daily Tiredness.

    PubMed

    Hartsell, Elizabeth N; Neupert, Shevaun D

    2017-11-01

    The present study examines the within-person relationship of daily stressors and tiredness and whether this depends on daily negative affect and individual differences in chronic stress. One hundred sixteen older adult participants were recruited via Amazon's Mechanical Turk for a 9-day daily diary study. Daily tiredness, daily stressors, and negative affect were measured each day, and chronic stress was measured at baseline. Daily stressors, daily negative affect, and chronic stress interacted to predict daily tiredness. People with high chronic stress who experienced an increase in daily negative affect were the most reactive to daily stressors in terms of experiencing an increase in daily tiredness. We also found that people with low levels of chronic stress were the most reactive to daily stressors when they experienced low levels of daily negative affect. Our results highlight the need for individualized and contextualized approaches to combating daily tiredness in older adults.

  11. 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.

  12. College students' daily-level reasons for not drinking.

    PubMed

    O'Hara, Ross E; Armeli, Stephen; Tennen, Howard

    2014-07-01

    Motivational models of alcohol use posit opposing approach and avoidance motives related to drinking, yet no micro-longitudinal study of college students has examined avoidance motives [i.e. reasons for not drinking (RND)]. This exploratory study examined daily- and person-level correlates of students' RNDs to identify factors that may inhibit alcohol use. College students (n = 1631; 54% female) participated in a 30-day daily diary study in which they reported RNDs for non-drinking evenings, as well as daily moods, global drinking motives and alcohol expectancies. Daily sadness was positively associated with not drinking due to having nobody with whom to drink but negatively associated with not drinking due to school work. Daily anxiety was negatively associated with not drinking due to lack of desire and positively associated with not drinking due to habit or having school or job responsibilities. At the person level, multiple RNDs were associated with both coping and conformity motives (but not social or enhancement motives), as well as positive (but not negative) alcohol expectancies. Results demonstrate the complexity of modelling mood-drinking contingencies proposed by motivational theories of alcohol use. Distinct moods may promote or inhibit drinking through various pathways, which could help explain the weak associations between daily mood and drinking level observed in previous studies. Measuring reasons both for and against drinking in micro-longitudinal studies (e.g. daily diaries) is recommended to better understand the processes underlying alcohol use and to inform future prevention efforts. © 2014 Australasian Professional Society on Alcohol and other Drugs.

  13. Daily computer usage correlated with undergraduate students' musculoskeletal symptoms.

    PubMed

    Chang, Che-Hsu Joe; Amick, Benjamin C; Menendez, Cammie Chaumont; Katz, Jeffrey N; Johnson, Peter W; Robertson, Michelle; Dennerlein, Jack Tigh

    2007-06-01

    A pilot prospective study was performed to examine the relationships between daily computer usage time and musculoskeletal symptoms on undergraduate students. For three separate 1-week study periods distributed over a semester, 27 students reported body part-specific musculoskeletal symptoms three to five times daily. Daily computer usage time for the 24-hr period preceding each symptom report was calculated from computer input device activities measured directly by software loaded on each participant's primary computer. General Estimating Equation models tested the relationships between daily computer usage and symptom reporting. Daily computer usage longer than 3 hr was significantly associated with an odds ratio 1.50 (1.01-2.25) of reporting symptoms. Odds of reporting symptoms also increased with quartiles of daily exposure. These data suggest a potential dose-response relationship between daily computer usage time and musculoskeletal symptoms.

  14. Intrinsic Emotional Fluctuation in Daily Negative Affect across Adulthood.

    PubMed

    Liu, Yin; Bangerter, Lauren R; Rovine, Michael J; Zarit, Steven H; Almeida, David M

    2017-12-15

    The study explored daily negative affect (NA) fluctuation, its associations with age, and its developmental characteristics. The sample (n = 790) was drawn from the Midlife Development in the United States; participants completed two 8-day daily diaries 10 years apart. Multilevel models were estimated within each diary component, where two single daily NA (depression and nervousness) and daily NA diversity were predicted separately by daily stressor exposures, physical health symptoms, age, gender, education, and neuroticism. The variances of within-person residual were output for single NA and NA diversity as intrinsic emotion fluctuation (IEF) within each diary component (i.e., controlled for within- and between-person contextual factors). Then multilevel growth models were fit to explore the developmental characteristics of day-to-day IEF across 10 years. At the daily level, older age was associated with less IEF in depression and nervousness. Over time, IEF in depression decreased. Additionally, IEF in NA diversity increased for older participants longitudinally. IEF represents a new conceptualization of midlife individuals' daily emotional ups and downs, specifically, the intrinsic within-person volatility of emotions. The magnitude of IEF and its longitudinal dynamics may have implications for health and well-being of middle-aged adults. © The Author(s) 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  15. 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 ...

  16. 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

  17. 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

    2015-02-26

    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.

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

    NASA Technical Reports Server (NTRS)

    Carlson, Toby N.; Buffum, Martha J.

    1989-01-01

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

  19. A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments

    NASA Astrophysics Data System (ADS)

    Schepen, Andrew; Zhao, Tongtiegang; Wang, Quan J.; Robertson, David E.

    2018-03-01

    Rainfall forecasts are an integral part of hydrological forecasting systems at sub-seasonal to seasonal timescales. In seasonal forecasting, global climate models (GCMs) are now the go-to source for rainfall forecasts. For hydrological applications however, GCM forecasts are often biased and unreliable in uncertainty spread, and calibration is therefore required before use. There are sophisticated statistical techniques for calibrating monthly and seasonal aggregations of the forecasts. However, calibration of seasonal forecasts at the daily time step typically uses very simple statistical methods or climate analogue methods. These methods generally lack the sophistication to achieve unbiased, reliable and coherent forecasts of daily amounts and seasonal accumulated totals. In this study, we propose and evaluate a Rainfall Post-Processing method for Seasonal forecasts (RPP-S), which is based on the Bayesian joint probability modelling approach for calibrating daily forecasts and the Schaake Shuffle for connecting the daily ensemble members of different lead times. We apply the method to post-process ACCESS-S forecasts for 12 perennial and ephemeral catchments across Australia and for 12 initialisation dates. RPP-S significantly reduces bias in raw forecasts and improves both skill and reliability. RPP-S forecasts are also more skilful and reliable than forecasts derived from ACCESS-S forecasts that have been post-processed using quantile mapping, especially for monthly and seasonal accumulations. Several opportunities to improve the robustness and skill of RPP-S are identified. The new RPP-S post-processed forecasts will be used in ensemble sub-seasonal to seasonal streamflow applications.

  20. The benefits of daily data and scale up issues in hydrologic models-SWAT and CRAFT

    NASA Astrophysics Data System (ADS)

    Huang, Yumei; Quinn, Paul; Liang, Qiuhua; Adams, Russell

    2017-04-01

    When modelling the flow pathways for nutrient transport, the lack of good data and limitation of data resolution become the key cause of low quality output in various hydrologic models. The scale of catchment being studied would present the main issues of the sensitivity and uncertainty expected on the hydrologic modelling. Equally, the time step chosen is also important to nutrient dynamics. This study aims to evaluate the benefits of using both monthly and daily data in hydrologic models, and to address the issues of catchment scale when using the two hydrologic models, the Soil and Water Assessment Tool (SWAT), and Catchment Runoff Attenuation Flux Tool (CRAFT), by comparing the difference between SWAT and CRAFT in flow pathways and sediment transport. The models are different in terms of complexity, therefore the poster will discuss the strengths and weakness of the models. Also we can show the problems of calibration and how the models can be used to support catchment modelling.

  1. Comparing daily drivers of problem drinking among older and younger adults: An electronic daily diary study using smartphones.

    PubMed

    Kuerbis, Alexis; Treloar Padovano, Hayley; Shao, Sijing; Houser, Jessica; Muench, Frederick J; Morgenstern, Jon

    2018-02-01

    By 2030, numbers and proportions of older adults with substance-use problems are expected to increase. While risk factors for problem drinking in late life have been identified, it remains unknown whether these factors drive daily drinking among older problem drinkers. This study examined the daily drivers of drinking among problem drinkers, moderated by age, utilizing ecological momentary assessment (EMA). Participants (N = 139), ages 20-73, received daily EMA online surveys completed via a smartphone prior to initiation of treatment. Multilevel modeling tested the moderating impact of age on within- and between-person relationships between drinking and focal predictors (mood, loneliness, boredom, stress, poor sleep, social factors, alcohol salience, commitment and confidence not to drink heavily). Older adults reported greater alcohol consumption when daily boredom levels were higher. Heavier drinking among younger adults was associated with poorer sleep quality. Greater daily confidence, daily commitment and daily alcohol salience did not impact drinking to the same extent for older adults as for younger adults. Greater person-level commitment predicted reduced drinking equivalently across age, but low person-level commitment predicted greater drinking among older adults compared to their younger counterparts. Older adults may have unique daily drivers of drinking that are not fully realized in current research and intervention efforts. Addressing the growing substance-use treatment needs among this population will require identifying the unique drivers of drinking among older adults, such as boredom, when compared to younger adults. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. Intent to quit among daily and non-daily college student smokers

    PubMed Central

    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 category as it relates to readiness to quit among current smokers. Of the 4438 students at six Southeast colleges who completed an online survey, 69.7% (n = 3094) were non-smokers, 6.6% (n = 293) were quitters, 7.1% (n = 317) were native non-daily smokers, 6.4% (n = 283) were converted non-daily smokers and 10.2% (n = 451) were daily smokers. There were differences in sociodemographics, substance use (alcohol, marijuana, other tobacco products) in the past 30 days and psychosocial factors among these subgroups of students (P < 0.001). Among current smokers, there were differences in cigarettes smoked per day, recent quit attempts, self-identification as a smoker, self-efficacy and motivation to quit (P < 0.001). After controlling for important factors, converted non-daily smokers were more likely to be ready to quit in the next month versus native non-daily smokers (OR = 2.15, CI 1.32–3.49, P = 0.002). Understanding differences among young adults with different smoking patterns and histories is critical in developing interventions targeting psychosocial factors impacting cessation among this population. PMID:23197630

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

    PubMed

    2016-01-01

    Reports an error in "Self-critical perfectionism, daily stress, and disclosure of daily emotional events" by Clarissa M. E. Richardson and Kenneth G. Rice (Journal of Counseling Psychology, 2015[Oct], Vol 62[4], 694-702). In the article, the labels of the two lines in Figure 1 were inadvertently transposed. The dotted line should be labeled High SCP and the solid line should be labeled Low SCP. The correct version is present in the erratum. (The following abstract of the original article appeared in record 2015-30890-001.) Although disclosure of stressful events can alleviate distress, self-critical perfectionism may pose an especially strong impediment to disclosure during stress, likely contributing to poorer psychological well-being. In the current study, after completing a measure of self-critical perfectionism (the Discrepancy subscale of the Almost Perfect Scale-Revised; Slaney, Rice, Mobley, Trippi, & Ashby, 2001), 396 undergraduates completed measures of stress and disclosure at the end of each day for 1 week. Consistent with hypotheses and previous research, multilevel modeling results indicated significant intraindividual coupling of daily stress and daily disclosure where disclosure was more likely when experiencing high stress than low stress. As hypothesized, Discrepancy moderated the relationship between daily stress and daily disclosure. Individuals higher in self-critical perfectionism (Discrepancy) were less likely to engage in disclosure under high stress, when disclosure is often most beneficial, than those with lower Discrepancy scores. These results have implications for understanding the role of stress and coping in the daily lives of self-critical perfectionists. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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

    NASA Astrophysics Data System (ADS)

    Mandal, S.; Choudhury, B. U.

    2015-07-01

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

  5. The concentration-response relation between air pollution and daily deaths.

    PubMed Central

    Schwartz, J; Ballester, F; Saez, M; Pérez-Hoyos, S; Bellido, J; Cambra, K; Arribas, F; Cañada, A; Pérez-Boillos, M J; Sunyer, J

    2001-01-01

    Studies on three continents have reported associations between various measures of airborne particles and daily deaths. Sulfur dioxide has also been associated with daily deaths, particularly in Europe. Questions remain about the shape of those associations, particularly whether there are thresholds at low levels. We examined the association of daily concentrations of black smoke and SO(2) with daily deaths in eight Spanish cities (Barcelona, Bilbao, Castellón, Gijón, Oviedo, Valencia, Vitoria, and Zaragoza) with different climates and different environmental and social characteristics. We used nonparametric smoothing to estimate the shape of the concentration-response curve in each city and combined those results using a metasmoothing technique developed by Schwartz and Zanobetti. We extended their method to incorporate random variance components. Black smoke had a nearly linear association with daily deaths, with no evidence of a threshold. A 10 microg/m(3) increase in black smoke was associated with a 0.88% increase in daily deaths (95% confidence interval, 0.56%-1.20%). SO(2) had a less plausible association: Daily deaths increased at very low concentrations, but leveled off and then decreased at higher concentrations. These findings held in both one- and two-pollutant models and held whether we optimized our weather and seasonal model in each city or used the same smoothing parameters in each city. We conclude that the association with particle levels is more convincing than for SO(2), and without a threshold. Linear models provide an adequate estimation of the effect of particulate air pollution on mortality at low to moderate concentrations. PMID:11675264

  6. Documentation of a daily mean stream temperature module—An enhancement to the Precipitation-Runoff Modeling System

    USGS Publications Warehouse

    Sanders, Michael J.; Markstrom, Steven L.; Regan, R. Steven; Atkinson, R. Dwight

    2017-09-15

    A module for simulation of daily mean water temperature in a network of stream segments has been developed as an enhancement to the U.S. Geological Survey Precipitation Runoff Modeling System (PRMS). This new module is based on the U.S. Fish and Wildlife Service Stream Network Temperature model, a mechanistic, one-dimensional heat transport model. The new module is integrated in PRMS. Stream-water temperature simulation is activated by selection of the appropriate input flags in the PRMS Control File and by providing the necessary additional inputs in standard PRMS input files.This report includes a comprehensive discussion of the methods relevant to the stream temperature calculations and detailed instructions for model input preparation.

  7. Improved daily precipitation nitrate and ammonium concentration models for the Chesapeake Bay Watershed.

    PubMed

    Grimm, J W; Lynch, J A

    2005-06-01

    Daily precipitation nitrate and ammonium concentration models were developed for the Chesapeake Bay Watershed (USA) using a linear least-squares regression approach and precipitation chemistry data from 29 National Atmospheric Deposition Program/National Trends Network (NADP/NTN) sites. Only weekly samples that comprised a single precipitation event were used in model development. The most significant variables in both ammonium and nitrate models included: precipitation volume, the number of days since the last event, a measure of seasonality, latitude, and the proportion of land within 8km covered by forest or devoted to industry and transportation. Additional variables included in the nitrate model were the proportion of land within 0.8km covered by water and/or forest. Local and regional ammonia and nitrogen oxide emissions were not as well correlated as land cover. Modeled concentrations compared very well with event chemistry data collected at six NADP/AirMoN sites within the Chesapeake Bay Watershed. Wet deposition estimates were also consistent with observed deposition at selected sites. Accurately describing the spatial distribution of precipitation volume throughout the watershed is important in providing critical estimates of wet-fall deposition of ammonium and nitrate.

  8. [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.

  9. Four-factor justice and daily job satisfaction: a multilevel investigation.

    PubMed

    Loi, Raymond; Yang, Jixia; Diefendorff, James M

    2009-05-01

    This study examined the differential effects of 4 types of organizational justice on daily job satisfaction at between- and within-individual levels. Specifically, the authors predicted that interpersonal justice and informational justice would exhibit meaningful daily variations and would have direct impacts on individuals' job satisfaction on a daily basis. They further theorized that distributive justice and procedural justice at a between-person level would moderate the within-person relationships. The authors used hierarchical linear modeling to test their hypotheses with a sample of 231 full-time employees in Hong Kong over the course of 25 working days. The results showed that both daily interpersonal and informational justice were positively related to daily job satisfaction. As hypothesized, between-individual distributive justice moderated the relationship between daily interpersonal justice and daily job satisfaction, and between-individual procedural justice moderated the relationship between daily informational justice and daily job satisfaction. (c) 2009 APA, all rights reserved.

  10. Artificial Intelligence Techniques for Predicting and Mapping Daily Pan Evaporation

    NASA Astrophysics Data System (ADS)

    Arunkumar, R.; Jothiprakash, V.; Sharma, Kirty

    2017-09-01

    In this study, Artificial Intelligence techniques such as Artificial Neural Network (ANN), Model Tree (MT) and Genetic Programming (GP) are used to develop daily pan evaporation time-series (TS) prediction and cause-effect (CE) mapping models. Ten years of observed daily meteorological data such as maximum temperature, minimum temperature, relative humidity, sunshine hours, dew point temperature and pan evaporation are used for developing the models. For each technique, several models are developed by changing the number of inputs and other model parameters. The performance of each model is evaluated using standard statistical measures such as Mean Square Error, Mean Absolute Error, Normalized Mean Square Error and correlation coefficient (R). The results showed that daily TS-GP (4) model predicted better with a correlation coefficient of 0.959 than other TS models. Among various CE models, CE-ANN (6-10-1) resulted better than MT and GP models with a correlation coefficient of 0.881. Because of the complex non-linear inter-relationship among various meteorological variables, CE mapping models could not achieve the performance of TS models. From this study, it was found that GP performs better for recognizing single pattern (time series modelling), whereas ANN is better for modelling multiple patterns (cause-effect modelling) in the data.

  11. A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition

    PubMed Central

    Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

    2018-01-01

    Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijiang stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five

  12. A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition.

    PubMed

    Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

    2018-05-21

    Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijaing stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five

  13. Non-daily pre-exposure prophylaxis for HIV prevention

    PubMed Central

    Anderson, Peter L.; García-Lerma, J. Gerardo; Heneine, Walid

    2015-01-01

    Purpose of review To discuss non-daily pre-exposure prophylaxis (PrEP) modalities that may provide advantages compared with daily PrEP in cost and cumulative toxicity, but may have lower adherence forgiveness. Recent Findings Animal models have informed our understanding of early viral transmission events, which help guide event-driven PrEP dosing strategies. These models indicate early establishment of viral replication in rectal or cervicovaginal tissues, so event-driven PrEP should rapidly deliver high mucosal drug concentrations within hours of the potential exposure event. Macaque models have demonstrated the high biological efficacy for event-driven dosing of oral tenofovir disoproxil fumarate (TDF) and emtricitabine (FTC) against both vaginal and rectal virus transmission. In humans, the IPERGAY study demonstrated 86% efficacy for event-driven oral TDF/FTC dosing among men who have sex with men (MSM), while no similar efficacy data are available on women or heterosexual men. The HPTN 067 study showed that certain MSM populations adhere well to non-daily PrEP while other populations of women adhere more poorly to non-daily versus daily regimens. Pharmacokinetic studies following oral TDF/FTC dosing in humans, indicate that TFV-diphosphate (the active form of TFV) accumulates to higher concentrations in rectal versus cervicovaginal tissue but non-adherence in trials complicates the interpretation of differential mucosal drug concentrations. Summary Event-driven dosing for TFV-based PrEP has promise for HIV prevention in MSM. Future research of event-driven PrEP in women and heterosexual men should be guided by a better understanding of the importance of mucosal drug concentrations for PrEP efficacy and its sensitivity to adherence. PMID:26633641

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

    NASA Astrophysics Data System (ADS)

    Ferreira, Flávia Polati; Leite, Cristina

    2015-07-01

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

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

    DOE PAGES

    Wandera, Loise; Mallick, Kaniska; Kiely, Gerard; ...

    2017-01-11

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

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

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

    Wandera, Loise; Mallick, Kaniska; Kiely, Gerard

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

  17. Forecasting daily emergency department visits using calendar variables and ambient temperature readings.

    PubMed

    Marcilio, Izabel; Hajat, Shakoor; Gouveia, Nelson

    2013-08-01

    This study aimed to develop different models to forecast the daily number of patients seeking emergency department (ED) care in a general hospital according to calendar variables and ambient temperature readings and to compare the models in terms of forecasting accuracy. The authors developed and tested six different models of ED patient visits using total daily counts of patient visits to an ED in Sao Paulo, Brazil, from January 1, 2008, to December 31, 2010. The first 33 months of the data set were used to develop the ED patient visits forecasting models (the training set), leaving the last 3 months to measure each model's forecasting accuracy by the mean absolute percentage error (MAPE). Forecasting models were developed using three different time-series analysis methods: generalized linear models (GLM), generalized estimating equations (GEE), and seasonal autoregressive integrated moving average (SARIMA). For each method, models were explored with and without the effect of mean daily temperature as a predictive variable. The daily mean number of ED visits was 389, ranging from 166 to 613. Data showed a weekly seasonal distribution, with highest patient volumes on Mondays and lowest patient volumes on weekends. There was little variation in daily visits by month. GLM and GEE models showed better forecasting accuracy than SARIMA models. For instance, the MAPEs from GLM models and GEE models at the first month of forecasting (October 2012) were 11.5 and 10.8% (models with and without control for the temperature effect, respectively), while the MAPEs from SARIMA models were 12.8 and 11.7%. For all models, controlling for the effect of temperature resulted in worse or similar forecasting ability than models with calendar variables alone, and forecasting accuracy was better for the short-term horizon (7 days in advance) than for the longer term (30 days in advance). This study indicates that time-series models can be developed to provide forecasts of daily ED patient

  18. 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.; hide

    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.

  19. Early Parental Abuse and Daily Assistance to Aging Parents With Disability: Associations With the Middle-Aged Adults' Daily Well-being.

    PubMed

    Liu, Yin; Kong, Jooyoung; Bangerter, Lauren R; Zarit, Steven H; Almeida, David M

    2018-01-09

    The current study examined the within-person association between providing daily assistance to aging parents with disability and adult children's daily mood in the context of early relationship with parents. We used data from 782 participants and 5,758 daily interviews from the Midlife in the United States (MIDUS) Refresher, with 248 people self-reported providing daily assistance ranging from 1 to 8 days out of the entire daily-interview period. Multilevel models were fit to examine the moderating effect of physical and emotional abuse from parents in early life on the associations between daily assistance to parents today and yesterday and daily mood. Additional analyses were conducted to examine whether the moderating effect of parental abuse remained when the assistance was provided for other family members and friends. Providing assistance today and yesterday to parents had immediate and lagged associations with higher negative affect when adult children experienced childhood emotional abuse from parents. No significant findings were found for daily positive affect. The moderating effect of parental abuse became nonsignificant when the assistance was provided to other family members or friends. Daily assistance to parents with disability needs to be examined in the context of the relationship history with parents. The impact of childhood abuse can linger long after the actual incident. Frequent early emotional abuse from parents was associated with greater distress when the middle-aged provided daily assistance to their aging parents. © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  20. Disaggregating from daily to sub-daily rainfall under a future climate

    NASA Astrophysics Data System (ADS)

    Westra, S.; Evans, J.; Mehrotra, R.; Sharma, A.

    2012-04-01

    We describe an algorithm for disaggregating daily rainfall into sub-daily rainfall 'fragments' (continuous fine-resolution rainfall sequences whose total depth sums to the daily rainfall amount) under a future, warmer climate. The basis of the algorithm is re-sample sub-daily fragments from the historical record conditional on the total daily rainfall amount and a range of atmospheric predictors representative of the future climate. The logic is that as the atmosphere warms, future rainfall patterns will be more reflective of historical rainfall patterns which occurred on warmer days at the same location, or at locations which have an atmospheric profile more reflective of expected future conditions. When looking at the scaling from daily to sub-daily rainfall over the historical record, it was found that the relationship varied significantly by season and by location, with rainfall patterns on warmer seasons or at warmer locations typically showing more intense rain falling over shorter periods compared with cooler seasons and stations. Importantly, by regressing against atmospheric covariates such as temperature this effect was almost entirely eliminated, providing a basis for suggesting the approach may be valid when extrapolating sub-daily sequences to a future climate. The method of fragments algorithm was then applied to nine stations around Australia, and showed that when holding the total daily rainfall constant, the maximum intensity of a short duration (6 minute) rainfall increased by between 4.1% and 13.4% per degree change in temperature for the maximum six minute burst, between 3.1% and 6.8% for the maximum one hour burst, and between 1.5% and 3.5% for the fraction of the day with no rainfall. This highlights that a large proportion of the change to the distribution of precipitation in the future is likely to occur at sub-daily timescales, with significant implications for many hydrological systems.

  1. Twice-Daily versus Once-Daily Pramipexole Extended Release Dosage Regimens in Parkinson's Disease.

    PubMed

    Yun, Ji Young; Kim, Young Eun; Yang, Hui-Jun; Kim, Han-Joon; Jeon, Beomseok

    2017-01-01

    This open-label study aimed to compare once-daily and twice-daily pramipexole extended release (PER) treatment in Parkinson's disease (PD). PD patients on dopamine agonist therapy, but with unsatisfactory control, were enrolled. Existing agonist doses were switched into equivalent PER doses. Subjects were consecutively enrolled into either once-daily-first or twice-daily-first groups and received the prescribed amount in one or two, respectively, daily doses for 8 weeks. For the second period, subjects switched regimens in a crossover manner. The forty-four patients completed a questionnaire requesting preference during their last visit. We measured the UPDRS-III, Hoehn and Yahr stages (H&Y) in medication-on state, Parkinson's disease sleep scale (PDSS), and Epworth Sleepiness Scale. Eighteen patients preferred a twice-daily regimen, 12 preferred a once-daily regimen, and 14 had no preference. After the trial, 14 subjects wanted to be on a once-daily regimen, 25 chose a twice-daily regimen, and 5 wanted to maintain the prestudy regimen. Main reasons for choosing the twice-daily regimen were decreased off-duration, more tolerable off-symptoms, and psychological stability. The mean UPDRS-III, H&Y, and PDSS were not different. Daytime sleepiness was significantly high in the once-daily regimen, whereas nocturnal hallucinations were more common in the twice-daily. Multiple dosing should be considered if once-daily dosing is unsatisfactory. This study is registered as NCT01515774 at ClinicalTrials.gov.

  2. 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.

  3. 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 Central

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

    2016-01-01

    Daily diary and other intensive longitudinal methods are increasingly being used to investigate fluctuations in psychological and behavioral processes. To inform the development of this methodology, we sought to explore predictors of and patterns in diary compliance and behavioral reports. We used multilevel modeling to analyze data from an online daily diary study of 371 gay and bisexual men focused on sexual behavior and substance use. We found that greater education and older age as well as lower frequency of substance use were associated with higher compliance. Using polynomial and trigonometric functions, we found evidence for circaseptan patterns in compliance, sexual behavior, and substance use, as well as linear declines in compliance and behavior over time. The results suggest potential sources of non-random patterns of missing data and suggest that trigonometric terms provide a similar but more parsimonious investigation of circaseptan rhythms than do third-order polynomial terms. PMID:26992392

  4. Intergenerational Support in a Daily Context

    PubMed Central

    Fingerman, Karen L.; Kim, Kyungmin; Tennant, Patrick S.; Birditt, Kira S.; Zarit, Steven H.

    2016-01-01

    Purpose of the Study: Using retrospective global reports, studies have found that middle-aged adults in the United States provide intermittent support to their aging parents and more frequent support to grown children. To date, studies have not examined support middle-aged adults provide to different generations on a daily basis. Daily support may include mundane everyday exchanges that may (or may not) affect well-being. Design and Methods: Middle-aged adults (N = 191, mean age 55.93) completed a general interview regarding family ties, followed by interviews each day for 7 days (N = 1,261 days). Daily interviews assessed support (e.g., advice, emotional, practical help) participants provided each grown child (n = 454) and aging parent (n = 253). Participants also reported daily mood. Results: Most participants provided emotional support (80%), advice (87%), and practical help (69%) to a grown child and also provided emotional support (61%) and advice (61%) or practical help (43%) to a parent that week. Multilevel models confirmed generational differences; grown children were more likely to receive everyday support than parents. Providing support to grown children was associated with positive mood, whereas providing support to parents was associated with more negative mood. Implications: Daily intergenerational support was more common than studies using global reports of support have found. Some daily support may be fleeting and not stand out in memory. The findings were consistent with the intergenerational stake hypothesis, which suggests middle-aged adults are more invested in their grown children than in their parents. Nonetheless, middle-aged adults were highly involved with aging parents. PMID:26035892

  5. 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...

  6. Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

    NASA Astrophysics Data System (ADS)

    Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

    2017-12-01

    Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic

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

    PubMed Central

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

    2015-01-01

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

  8. 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

  9. Weekly Cycles in Daily Report Data: An Overlooked Issue.

    PubMed

    Liu, Yu; West, Stephen G

    2016-10-01

    Daily diaries and other everyday experience methods are increasingly used to study relationships between two time-varying variables X and Y. Although daily data potentially often have weekly cyclical patterns (e.g., stress may be higher on weekdays and lower on weekends), the majority of daily diary studies have ignored this possibility. In this study, we investigated the effect of ignoring existing weekly cycles. We reanalyzed an empirical dataset (stress and alcohol consumption) and performed Monte Carlo simulations to investigate the impact of omitting weekly cycles. In the empirical dataset, ignoring cycles led to the inference of a significant within-person X-Y relation whereas modeling cycles suggested that this relationship did not exist. Simulation results indicated that ignoring cycles that existed in both X and Y led to bias in the estimated within-person X-Y relationship. The amount and direction of bias depended on the magnitude of the cycles, magnitude of the true within-person X-Y relation, and synchronization of the cycles. We encourage researchers conducting daily diary studies to address potential weekly cycles in their data. We provide guidelines for detecting and modeling cycles to remove their influence and discuss challenges of causal inference in daily experience studies. © 2015 Wiley Periodicals, Inc.

  10. Adolescent daily and general maladjustment: is there reactivity to daily repeated measures methodologies?

    PubMed

    Nishina, Adrienne

    2012-01-01

    The present study examined whether repeated exposure to daily surveys about negative social experiences predicts changes in adolescents' daily and general maladjustment, and whether question content moderates these changes. Across a 2-week period, 6th-grade students (N = 215; mode age = 11) completed 5 daily reports tapping experienced or experienced and witnessed negative events, or they completed no daily reports. General maladjustment was measured in 2-week intervals before, at the end of, and 2 weeks after the daily report study. Daily maladjustment either decreased or did not change across the 5 daily report exposures. General maladjustment decreased across the three 2-week intervals. Combined, results indicate that short-term daily report studies do not place youth at risk for increased maladjustment. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

  11. Daily physical activity in stable heart failure patients.

    PubMed

    Dontje, Manon L; van der Wal, Martje H L; Stolk, Ronald P; Brügemann, Johan; Jaarsma, Tiny; Wijtvliet, Petra E P J; van der Schans, Cees P; de Greef, Mathieu H G

    2014-01-01

    Physical activity is the only nonpharmacological therapy that is proven to be effective in heart failure (HF) patients in reducing morbidity. To date, little is known about the levels of daily physical activity in HF patients and about related factors. The objectives of this study were to (a) describe performance-based daily physical activity in HF patients, (b) compare it with physical activity guidelines, and (c) identify related factors of daily physical activity. The daily physical activity of 68 HF patients was measured using an accelerometer (SenseWear) for 48 hours. Psychological characteristics (self-efficacy, motivation, and depression) were measured using questionnaires. To have an indication how to interpret daily physical activity levels of the study sample, time spent on moderate- to vigorous-intensity physical activities was compared with the 30-minute activity guideline. Steps per day was compared with the criteria for healthy adults, in the absence of HF-specific criteria. Linear regression analyses were used to identify related factors of daily physical activity. Forty-four percent were active for less than 30 min/d, whereas 56% were active for more than 30 min/d. Fifty percent took fewer than 5000 steps per day, 35% took 5000 to 10 000 steps per day, and 15% took more than 10 000 steps per day. Linear regression models showed that New York Heart Association classification and self-efficacy were the most important factors explaining variance in daily physical activity. The variance in daily physical activity in HF patients is considerable. Approximately half of the patients had a sedentary lifestyle. Higher New York Heart Association classification and lower self-efficacy are associated with less daily physical activity. These findings contribute to the understanding of daily physical activity behavior of HF patients and can help healthcare providers to promote daily physical activity in sedentary HF patients.

  12. 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

  13. 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

  14. 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…

  15. Daily Self-Disclosure and Sleep in Couples

    PubMed Central

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

    2014-01-01

    Objective An emerging literature provides evidence for the association between romantic relationship quality and sleep, an important factor in health and well-being. However, we still know very little about the specific relationship processes that affect sleep behavior. Therefore, the goal of this study was to examine how self-disclosure, an important relational process linked to intimacy, relationship satisfaction and health, is associated with sleep behavior. Method As part of a larger study of family processes, wives (n=46) and husbands (n=38) from 46 cohabiting families completed 56 days of daily diaries. Spouses completed evening diaries assessing daily self-disclosure, relationship satisfaction, and mood and morning diaries assessing the prior night's sleep. Multilevel modeling was used to explore the effects of both daily variation in and average levels across the 56 days of self-disclosure on sleep. Results Daily variation in self-disclosure predicted sleep outcomes for wives, but not for husbands. On days when wives self-disclosed more to their spouses than their average level, their subjective sleep quality and sleep efficiency that night improved. Furthermore, daily self-disclosure buffered the negative effect of daily negative mood on sleep latency for wives, but not husbands. In contrast, higher average levels of self-disclosure predicted less waking during the night for husbands, but not for wives. Conclusion The association between self-disclosure and sleep is one mechanism by which daily relationship functioning may influence health and well-being. Gender may play a role in how self-disclosure is associated with sleep. PMID:25068453

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

    ERIC Educational Resources Information Center

    Nofziger, Stacey; Lee, Hye-Ryeon

    2006-01-01

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

  17. Statistical models for estimating daily streamflow in Michigan

    USGS Publications Warehouse

    Holtschlag, D.J.; Salehi, Habib

    1992-01-01

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

  18. Intergenerational Support in a Daily Context.

    PubMed

    Fingerman, Karen L; Kim, Kyungmin; Tennant, Patrick S; Birditt, Kira S; Zarit, Steven H

    2016-10-01

    Using retrospective global reports, studies have found that middle-aged adults in the United States provide intermittent support to their aging parents and more frequent support to grown children. To date, studies have not examined support middle-aged adults provide to different generations on a daily basis. Daily support may include mundane everyday exchanges that may (or may not) affect well-being. Middle-aged adults (N = 191, mean age 55.93) completed a general interview regarding family ties, followed by interviews each day for 7 days (N = 1,261 days). Daily interviews assessed support (e.g., advice, emotional, practical help) participants provided each grown child (n = 454) and aging parent (n = 253). Participants also reported daily mood. Most participants provided emotional support (80%), advice (87%), and practical help (69%) to a grown child and also provided emotional support (61%) and advice (61%) or practical help (43%) to a parent that week. Multilevel models confirmed generational differences; grown children were more likely to receive everyday support than parents. Providing support to grown children was associated with positive mood, whereas providing support to parents was associated with more negative mood. Daily intergenerational support was more common than studies using global reports of support have found. Some daily support may be fleeting and not stand out in memory. The findings were consistent with the intergenerational stake hypothesis, which suggests middle-aged adults are more invested in their grown children than in their parents. Nonetheless, middle-aged adults were highly involved with aging parents. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

    DOE PAGES

    Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav; ...

    2016-04-07

    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 predictionmore » 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). Furthermore, 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.« less

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

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

    Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav

    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 predictionmore » 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). Furthermore, 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.« less

  1. A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

    NASA Astrophysics Data System (ADS)

    Danandeh Mehr, Ali; Kahya, Ercan

    2017-06-01

    Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

  2. Twice-daily versus once-daily applications of pimecrolimus cream 1% for the prevention of disease relapse in pediatric patients with atopic dermatitis.

    PubMed

    Ruer-Mulard, Mireille; Aberer, Werner; Gunstone, Anthony; Kekki, Outi-Maria; López Estebaranz, Jose Luis; Vertruyen, André; Guettner, Achim; Hultsch, Thomas

    2009-01-01

    The aim of this study is to compare twice-daily and once-daily applications of pimecrolimus cream 1% for prevention of atopic dermatitis relapses in pediatric patients. This multicenter trial enrolled 300 outpatients aged 2 to 17 years, with mild-to-severe atopic dermatitis. The patients were initially treated with twice-daily topical pimecrolimus until complete clearance or for up to 6 weeks (open-label period). Those who achieved a decrease of at least 1 point in the Investigator's Global Assessment score were then randomized to double-blind treatment with pimecrolimus cream 1% either twice daily or once daily for up to 16 weeks. Study medication was discontinued during periods of disease remission (Investigator's Global Assessment = 0). The primary efficacy end point of the double-blind phase was disease relapse (worsening requiring topical corticosteroids or additional/alternative therapy and confirmed by Investigator's Global Assessment score > or = 3 and pruritus score > or = 2). Of the 300 patients enrolled in the study, 268 were randomized to treatment with pimecrolimus cream 1% either twice daily or once daily (n = 134 in each group). The relapse rate was lower in the twice-daily dose group (9.9%) than that in the once-daily dose group (14.7%), but analysis of the time to disease relapse, using a Cox proportional model to adjust for confounding variables, did not show a statistically significant difference between treatment arms (hazard ratio: 0.64; 95% CI: 0.31-1.30). Treatment of active atopic dermatitis lesions with pimecrolimus cream 1% twice daily, followed by the once-daily dosing regimen, was sufficient to prevent subsequent atopic dermatitis relapses over 16 weeks in pediatric patients.

  3. Daily self-disclosure and sleep in couples.

    PubMed

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

    2014-08-01

    An emerging literature provides evidence for the association between romantic relationship quality and sleep, an important factor in health and well-being. However, we still know very little about the specific relationship processes that affect sleep behavior. Therefore, the goal of this study was to examine how self-disclosure, an important relational process linked to intimacy, relationship satisfaction, and health, is associated with sleep behavior. As part of a larger study of family processes, wives (n = 46) and husbands (n = 38) from 46 cohabiting families completed 56 days of daily diaries. Spouses completed evening diaries assessing daily self-disclosure, relationship satisfaction, and mood and morning diaries assessing the prior night's sleep. Multilevel modeling was used to explore the effects of both daily variation in and average levels across the 56 days of self-disclosure on sleep. Daily variation in self-disclosure predicted sleep outcomes for wives, but not for husbands. On days when wives self-disclosed more to their spouses than their average level, their subjective sleep quality and sleep efficiency that night improved. Furthermore, daily self-disclosure buffered the effect of high negative mood on sleep latency for wives, but not husbands. In contrast, higher average levels of self-disclosure predicted less waking during the night for husbands, but not for wives. The association between self-disclosure and sleep is one mechanism by which daily relationship functioning may influence health and well-being. Gender may play a role in how self-disclosure is associated with sleep.

  4. Daily Fluctuation in Negative Affect for Family Caregivers of Individuals With Dementia

    PubMed Central

    Liu, Yin; Kim, Kyungmin; Almeida, David M.; Zarit, Steven H.

    2017-01-01

    Objective The study examined associations of intrinsic fluctuation in daily negative affect (i.e., depression and anger) with adult day service (ADS) use, daily experiences, and other caregiving characteristics. Methods This was an 8-day diary of 173 family caregivers of individuals with dementia. Multilevel models with common within-person variance were fit first to show average associations between daily stressors and mean level of daily affect. Then multilevel models with heterogeneous within-person variance were fit to test the hypotheses on associations between ADS use, daily experiences, and intrinsic fluctuation in daily affect. Results The study showed that, when the sum of ADS days was greater than average, there was a stabilizing effect of ADS use on caregivers’ within-person fluctuation in negative affect. Moreover, fewer daily stressors and greater-than-average daily care-related stressors, more positive events, not being a spouse, greater-than-average duration of caregiving, and less-than-average dependency of individuals with dementia on activities of daily living were associated with less fluctuation. Better sleep quality was associated with less intrinsic fluctuation in anger; and younger age and more years of education were associated with less intrinsic fluctuation in daily depression. Conclusions Because emotional stability has been argued as an aspect of emotional well-being in the general populations, intrinsic fluctuation of emotional experience was suggested as an outcome of evidence-based interventions for family caregivers. PMID:25365414

  5. Daily Fluctuations in Everyday Cognition: Is It Meaningful?

    PubMed

    Gamaldo, Alyssa A; Allaire, Jason C

    2016-08-01

    This study examined whether there are daily fluctuations in everyday cognition that are consistent with daily fluctuations often observed in traditional measures of basic cognitive abilities. Two hundred six independently living older adults (age range = 60-91 years) were asked to complete a computerized cognitive battery over eight occasions within a 2- to 3-week period. Using multilevel model, significant within-person variability was observed across the Daily Everyday Cognition Assessment (DECA; 46%), with 54% between-person variability. At each occasion, better performance on the DECA was significantly associated with better performance on simple reaction time ( p < .01) and memory (Auditory Verbal Learning Task, p < .01) even after accounting for time, age, education, and performance on other cognitive measures. These findings demonstrate that within-person performance fluctuations can be observed for everyday cognition tasks, and these fluctuations are consistent with daily changes in basic cognitive abilities. © The Author(s) 2015.

  6. Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modelling heteroscedastic residual errors

    NASA Astrophysics Data System (ADS)

    David, McInerney; Mark, Thyer; Dmitri, Kavetski; George, Kuczera

    2017-04-01

    This study provides guidance to hydrological researchers which enables them to provide probabilistic predictions of daily streamflow with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality). Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. It is commonly known that hydrological model residual errors are heteroscedastic, i.e. there is a pattern of larger errors in higher streamflow predictions. Although multiple approaches exist for representing this heteroscedasticity, few studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating 8 common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter, lambda) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and USA, and two lumped hydrological models. We find the choice of heteroscedastic error modelling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with lambda of 0.2 and 0.5, and the log scheme (lambda=0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.

  7. 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

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

    USDA-ARS?s Scientific Manuscript database

    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...

  9. Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

    NASA Astrophysics Data System (ADS)

    Costa, Veber; Fernandes, Wilson

    2017-11-01

    Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods

  10. Daily stress, presleep arousal, and sleep in healthy young women: a daily life computerized sleep diary and actigraphy study.

    PubMed

    Winzeler, Katja; Voellmin, Annette; Schäfer, Valérie; Meyer, Andrea H; Cajochen, Christian; Wilhelm, Frank H; Bader, Klaus

    2014-03-01

    Our study aimed to further elucidate the mediating role of presleep arousal in the relationship between daily stress and sleep by investigating subjective sleep quality and actigraphy-assessed sleep efficiency (SE) on both within- and between-participant levels in a sample of healthy young women. Multilevel modeling was applied on electronically assessed data comprising 14 consecutive nights in 145 healthy young women to assess the relationship between daily stress, presleep (somatic and cognitive) arousal, and sleep on both levels between participants and within participants across days. Higher levels of daily stress were consistently and significantly associated with higher levels of somatic and cognitive arousal. Somatic arousal mediated the relationship between daily stress and worsened subjective sleep quality on the between-participant level, while cognitive arousal mediated the relationship between daily stress and worsened subjective sleep quality on the within-participants level. Unexpectedly, healthy young women showed higher SE following days with above-average stress with somatic arousal mediating this relationship. Our data corroborate the role of presleep arousal mediating the relationship between daily stress and subjective sleep quality. Interestingly this effect was restricted to somatic arousal being relevant on interindividual levels and cognitive arousal on intraindividual levels. For young and healthy individuals who experience high stress and arousal, well-established cognitive-behavioral techniques could be useful to regulate arousal and prevent worse subjective sleep quality. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Comparison of spatiotemporal prediction models of daily exposure of individuals to ambient nitrogen dioxide and ozone in Montreal, Canada.

    PubMed

    Buteau, Stephane; Hatzopoulou, Marianne; Crouse, Dan L; Smargiassi, Audrey; Burnett, Richard T; Logan, Travis; Cavellin, Laure Deville; Goldberg, Mark S

    2017-07-01

    In previous studies investigating the short-term health effects of ambient air pollution the exposure metric that is often used is the daily average across monitors, thus assuming that all individuals have the same daily exposure. Studies that incorporate space-time exposures of individuals are essential to further our understanding of the short-term health effects of ambient air pollution. As part of a longitudinal cohort study of the acute effects of air pollution that incorporated subject-specific information and medical histories of subjects throughout the follow-up, the purpose of this study was to develop and compare different prediction models using data from fixed-site monitors and other monitoring campaigns to estimate daily, spatially-resolved concentrations of ozone (O 3 ) and nitrogen dioxide (NO 2 ) of participants' residences in Montreal, 1991-2002. We used the following methods to predict spatially-resolved daily concentrations of O 3 and NO 2 for each geographic region in Montreal (defined by three-character postal code areas): (1) assigning concentrations from the nearest monitor; (2) spatial interpolation using inverse-distance weighting; (3) back-extrapolation from a land-use regression model from a dense monitoring survey, and; (4) a combination of a land-use and Bayesian maximum entropy model. We used a variety of indices of agreement to compare estimates of exposure assigned from the different methods, notably scatterplots of pairwise predictions, distribution of differences and computation of the absolute agreement intraclass correlation (ICC). For each pairwise prediction, we also produced maps of the ICCs by these regions indicating the spatial variability in the degree of agreement. We found some substantial differences in agreement across pairs of methods in daily mean predicted concentrations of O 3 and NO 2 . On a given day and postal code area the difference in the concentration assigned could be as high as 131ppb for O 3 and 108ppb

  12. Daily Streamflow Predictions in an Ungauged Watershed in Northern California Using the Precipitation-Runoff Modeling System (PRMS): Calibration Challenges when nearby Gauged Watersheds are Hydrologically Dissimilar

    NASA Astrophysics Data System (ADS)

    Dhakal, A. S.; Adera, S.

    2017-12-01

    Accurate daily streamflow prediction in ungauged watersheds with sparse information is challenging. The ability of a hydrologic model calibrated using nearby gauged watersheds to predict streamflow accurately depends on hydrologic similarities between the gauged and ungauged watersheds. This study examines daily streamflow predictions using the Precipitation-Runoff Modeling System (PRMS) for the largely ungauged San Antonio Creek watershed, a 96 km2 sub-watershed of the Alameda Creek watershed in Northern California. The process-based PRMS model is being used to improve the accuracy of recent San Antonio Creek streamflow predictions generated by two empirical methods. Although San Antonio Creek watershed is largely ungauged, daily streamflow data exists for hydrologic years (HY) 1913 - 1930. PRMS was calibrated for HY 1913 - 1930 using streamflow data, modern-day land use and PRISM precipitation distribution, and gauged precipitation and temperature data from a nearby watershed. The PRMS model was then used to generate daily streamflows for HY 1996-2013, during which the watershed was ungauged, and hydrologic responses were compared to two nearby gauged sub-watersheds of Alameda Creek. Finally, the PRMS-predicted daily flows between HY 1996-2013 were compared to the two empirically-predicted streamflow time series: (1) the reservoir mass balance method and (2) correlation of historical streamflows from 80 - 100 years ago between San Antonio Creek and a nearby sub-watershed located in Alameda Creek. While the mass balance approach using reservoir storage and transfers is helpful for estimating inflows to the reservoir, large discrepancies in daily streamflow estimation can arise. Similarly, correlation-based predicted daily flows which rely on a relationship from flows collected 80-100 years ago may not represent current watershed hydrologic conditions. This study aims to develop a method of streamflow prediction in the San Antonio Creek watershed by examining PRMS

  13. On the probability distribution of daily streamflow in the United States

    USGS Publications Warehouse

    Blum, Annalise G.; Archfield, Stacey A.; Vogel, Richard M.

    2017-01-01

    Daily streamflows are often represented by flow duration curves (FDCs), which illustrate the frequency with which flows are equaled or exceeded. FDCs have had broad applications across both operational and research hydrology for decades; however, modeling FDCs has proven elusive. Daily streamflow is a complex time series with flow values ranging over many orders of magnitude. The identification of a probability distribution that can approximate daily streamflow would improve understanding of the behavior of daily flows and the ability to estimate FDCs at ungaged river locations. Comparisons of modeled and empirical FDCs at nearly 400 unregulated, perennial streams illustrate that the four-parameter kappa distribution provides a very good representation of daily streamflow across the majority of physiographic regions in the conterminous United States (US). Further, for some regions of the US, the three-parameter generalized Pareto and lognormal distributions also provide a good approximation to FDCs. Similar results are found for the period of record FDCs, representing the long-term hydrologic regime at a site, and median annual FDCs, representing the behavior of flows in a typical year.

  14. 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

  15. Azelaic acid 15% gel once daily versus twice daily in papulopustular rosacea.

    PubMed

    Thiboutot, Diane M; Fleischer, Alan B; Del Rosso, James Q; Graupe, Klaus

    2008-06-01

    Twice-daily azelaic acid (AzA) is the conventional regimen for papulopustular rosacea, but once-daily AzA may be equally effective, with greater convenience and dosing flexibility. In order to test this hypothesis, an exploratory study was conducted. The evaluable efficacy population of this 12-week double-blind, parallel-group study included 72 patients and the population that was used to report safety results included 92 patients. Baseline characteristics were comparable between the once-daily and twice-daily study groups. Evaluations were performed at baseline and at weeks 4, 8, and 12. No significant difference was found between the once-daily and twice-daily groups at the end of study therapy in mean investigator global assessment (IGA) scores, treatment success, or treatment response. The mean number of inflammatory lesions, the intensity of erythema intensity, and the intensity of telangiectasia at treatment end were likewise not significantly different (P>.205 for all). More than 90% of subjects in each group rated cosmetic acceptability of this AzA gel as satisfactory or better. Based on these findings and those of prior studies, once-daily AzA 15% gel can therefore be utilized as a safe, effective, and economical dosing option for the treatment of mild-to-moderate papulopustular rosacea. Once-daily dosing of AzA 15% gel was well accepted by patients and can offer considerable dosing flexibility and convenience for the patient as well as for the dermatologist.

  16. Predicting daily use of urban forest recreation sites

    Treesearch

    John F. Dwyer

    1988-01-01

    A multiple linear regression model explains 90% of the variance in daily use of an urban recreation site. Explanatory variables include season, day of the week, and weather. The results offer guides for recreation site planning and management as well as suggestions for improving the model.

  17. Development and Validation of a Daily Pain Catastrophizing Scale.

    PubMed

    Darnall, Beth D; Sturgeon, John A; Cook, Karon F; Taub, Chloe J; Roy, Anuradha; Burns, John W; Sullivan, Michael; Mackey, Sean C

    2017-09-01

    To date, there is no validated measure for pain catastrophizing at the daily level. The Pain Catastrophizing Scale (PCS) is widely used to measure trait pain catastrophizing. We sought to develop and validate a brief, daily version of the PCS for use in daily diary studies to facilitate research on mechanisms of catastrophizing treatment, individual differences in self-regulation, and to reveal the nuanced relationships between catastrophizing, correlates, and pain outcomes. After adapting the PCS for daily use, we evaluated the resulting 14 items using 3 rounds of cognitive interviews with 30 adults with chronic pain. We refined and tested the final daily PCS in 3 independent, prospective, cross-sectional, observational validation studies conducted in a combined total of 519 adults with chronic pain who completed online measures daily for 14 consecutive days. For study 1 (N = 131), exploratory factor analysis revealed adequate fit and-unexpectedly-unidimensionality for item responses to the daily PCS. Study 2 (N = 177) correlations indicated adequate association with related constructs (anger, anxiety, pain intensity, depression). Similarly, results for study 3 (N = 211) revealed expected correlations for daily PCS and measures of daily constructs including physical activity, sleep, energy level, and positive affect. Results from complex/multilevel confirmatory factor analysis confirmed good fit to a unidimensional model. Scores on the daily PCS were statistically comparable with and more parsimonious than the full 14-item version. Next steps include evaluation of score validity in populations with medical diagnoses, greater demographic diversity, and in patients with acute pain. This article describes the development and validation of a daily PCS. This daily measure may facilitate research that aims to characterize pain mechanisms, individual differences in self-regulation, adaptation, and nuanced relationships between catastrophizing, correlates, and pain

  18. A comparison of daily evaporation downscaled using WRFDA model and GLEAM dataset over the Iberian Peninsula.

    NASA Astrophysics Data System (ADS)

    José González-Rojí, Santos; Sáenz, Jon; Ibarra-Berastegi, Gabriel

    2017-04-01

    GLEAM dataset was presented a few years ago and since that moment, it has just been used for validation of evaporation in a few places of the world (Australia and Africa). The Iberian Peninsula is composed of different soil types and it is affected by different weather regimes, with different climate regions. It is this feature which makes it a very interesting zone for the study of the meteorological cycle, including evaporation. For that purpose, a numerical downscaling exercise over the Iberian Peninsula was run nesting the WRF model inside ERA Interim. Two model configurations were tested in two experiments spanning the period 2010-2014 after a one-year spin-up (2009). In the first experiment (N), boundary conditions drive the model. The second experiment (D) is configured the same way as the N case, but 3DVAR data assimilation is run every six hours (00Z, 06Z, 12Z and 18Z) using observations obtained from the PREPBUFR dataset. For both N and D runs and ERA Interim, the evaporation of the model runs was compared to GLEAM v3.0b and v3.0c datasets over the Iberian Peninsula, both at the daily and monthly time scales. GLEAM v3.0a was not used for validation as it uses for forcing radiation and air temperature data from ERA Interim. Results show that the experiment with data assimilation (D) improve the results obtained for N experiment. Moreover, correlations values are comparable to the ones obtained with ERA Interim. However, some negative correlation values are observed at Portuguese and Mediterranean coasts for both WRF runs. All of these problematic points are considered as urban sites by the NOAH land surface model. Because of that, the model is not able to simulate a correct evaporation value. Even with these discrepancies, better results than for ERA Interim are observed for seasonal Biases and daily RMSEs over Iberian Peninsula, obtaining the best values inland. Minimal differences are observed for the two GLEAM datasets selected.

  19. 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

  20. Emotion regulation strategies in daily life: mindfulness, cognitive reappraisal and emotion suppression.

    PubMed

    Brockman, Robert; Ciarrochi, Joseph; Parker, Philip; Kashdan, Todd

    2017-03-01

    Most empirical studies of emotion regulation have relied on retrospective trait measures, and have not examined the link between daily regulatory strategies and every day emotional well-being. We used a daily diary methodology with multilevel modelling data analyses (n = 187) to examine the influence of three emotion regulation strategies (mindfulness, cognitive reappraisal and emotion suppression) on the experience of daily negative and positive affect. Our results suggested that daily mindfulness was associated with lower negative and higher positive affect whereas the converse pattern was found for daily emotion suppression; cognitive reappraisal was related to daily positive, but not negative affect. When daily mindfulness, suppression and reappraisal were included in the same models, these strategies predicted unique variance in emotional well-being. Random slope analyses revealed substantial variability in the utility of these strategies. Indeed the presumably "adaptive" cognitive reappraisal strategy seemed to confer no benefit to the regulation of negative affect in approximately half the sample. Additional analyses revealed that age moderates the effect of cognitive reappraisal on daily negative affect: Higher use of reappraisal was associated with more negative affect for adolescents (aged 17 to 19) but became associated with less negative affect with increasing age. We interpret these results in line with a contextual view of emotion regulation where no strategy is inherently "good" or "bad".

  1. Family and school spillover in adolescents' daily lives.

    PubMed

    Flook, Lisa; Fuligni, Andrew J

    2008-01-01

    This study examined spillover between daily family stressors and school problems among 589 ninth-grade students (mean age = 14.9 years) from Mexican, Chinese, and European backgrounds. Spillover was examined using a daily diary methodology in which adolescents reported on their school and family experiences each day for 2 weeks. Analyses using hierarchical linear modeling revealed reciprocal spillover effects between adolescents' daily functioning in the family and school domains that spanned several days. Longitudinal analyses indicated that spillover between family stressors and school problems also occurs across the high school years, from 9th to 12th grade, and that both are predictive of poorer academic performance in 12th grade. These findings have practical implications for adolescents' academic achievement trajectories and general well-being.

  2. 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

  3. 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.

  4. Relief of depression and pain improves daily functioning and quality of life in patients with major depressive disorder.

    PubMed

    Lin, Ching-Hua; Yen, Yung-Chieh; Chen, Ming-Chao; Chen, Cheng-Chung

    2013-12-02

    The objective of this study was to investigate the effects of depression relief and pain relief on the improvement in daily functioning and quality of life (QOL) for depressed patients receiving a 6-week treatment of fluoxetine. A total of 131 acutely ill inpatients with major depressive disorder (MDD) were enrolled to receive 20mg of fluoxetine daily for 6 weeks. Depression severity, pain severity, daily functioning, and health-related QOL were assessed at baseline and again at week 6. Depression severity, pain severity, and daily functioning were assessed using the 17-item Hamilton Depression Rating Scale, the Short-Form 36 (SF-36) Body Pain Index, and the Work and Social Adjustment Scale. Health-related QOL was assessed by three primary domains of the SF-36, including social functioning, vitality, and general health perceptions. Pearson's correlation and structural equation modeling were used to examine relationships among the study variables. Five models were proposed. In model 1, depression relief alone improved daily functioning and QOL. In model 2, pain relief alone improved daily functioning and QOL. In model 3, depression relief, mediated by pain relief, improved daily functioning and QOL. In model 4, pain relief, mediated by depression relief, improved daily functioning and QOL. In model 5, both depression relief and pain relief improved daily functioning and QOL. One hundred and six patients completed all the measures at baseline and at week 6. Model 5 was the most fitted structural equation model (χ(2) = 8.62, df = 8, p = 0.376, GFI = 0.975, AGFI = 0.935, TLI = 0.992, CFI = 0.996, RMSEA = 0.027). Interventions which relieve depression and pain improve daily functioning and QOL among patients with MDD. The proposed model can provide quantitative estimates of improvement in treating patients with MDD. © 2013 Elsevier Inc. All rights reserved.

  5. Occurrence analysis of daily rainfalls by using non-homogeneous Poissonian processes

    NASA Astrophysics Data System (ADS)

    Sirangelo, B.; Ferrari, E.; de Luca, D. L.

    2009-09-01

    In recent years several temporally homogeneous stochastic models have been applied to describe the rainfall process. In particular stochastic analysis of daily rainfall time series may contribute to explain the statistic features of the temporal variability related to the phenomenon. Due to the evident periodicity of the physical process, these models have to be used only to short temporal intervals in which occurrences and intensities of rainfalls can be considered reliably homogeneous. To this aim, occurrences of daily rainfalls can be considered as a stationary stochastic process in monthly periods. In this context point process models are widely used for at-site analysis of daily rainfall occurrence; they are continuous time series models, and are able to explain intermittent feature of rainfalls and simulate interstorm periods. With a different approach, periodic features of daily rainfalls can be interpreted by using a temporally non-homogeneous stochastic model characterized by parameters expressed as continuous functions in the time. In this case, great attention has to be paid to the parsimony of the models, as regards the number of parameters and the bias introduced into the generation of synthetic series, and to the influence of threshold values in extracting peak storm database from recorded daily rainfall heights. In this work, a stochastic model based on a non-homogeneous Poisson process, characterized by a time-dependent intensity of rainfall occurrence, is employed to explain seasonal effects of daily rainfalls exceeding prefixed threshold values. In particular, variation of rainfall occurrence intensity ? (t) is modelled by using Fourier series analysis, in which the non-homogeneous process is transformed into a homogeneous and unit one through a proper transformation of time domain, and the choice of the minimum number of harmonics is evaluated applying available statistical tests. The procedure is applied to a dataset of rain gauges located in

  6. Daily Autonomy Support and Sexual Identity Disclosure Predicts Daily Mental and Physical Health Outcomes.

    PubMed

    Legate, Nicole; Ryan, Richard M; Rogge, Ronald D

    2017-06-01

    Using a daily diary methodology, we examined how social environments support or fail to support sexual identity disclosure, and associated mental and physical health outcomes. Results showed that variability in disclosure across the diary period related to greater psychological well-being and fewer physical symptoms, suggesting potential adaptive benefits to selectively disclosing. A multilevel path model indicated that perceiving autonomy support in conversations predicted more disclosure, which in turn predicted more need satisfaction, greater well-being, and fewer physical symptoms that day. Finally, mediation analyses revealed that disclosure and need satisfaction explained why perceiving autonomy support in a conversation predicted greater well-being and fewer physical symptoms. That is, perceiving autonomy support in conversations indirectly predicted greater wellness through sexual orientation disclosure, along with feeling authentic and connected in daily interactions with others. Discussion highlights the role of supportive social contexts and everyday opportunities to disclose in affecting sexual minority mental and physical health.

  7. 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

  8. Particulate air pollution and daily mortality in Detroit.

    PubMed

    Schwartz, J

    1991-12-01

    Particulate air pollution has been associated with increased mortality during episodes of high pollution concentrations. The relationship at lower concentrations has been more controversial, as has the relative role of particles and sulfur dioxide. Replication has been difficult because suspended particle concentrations are usually measured only every sixth day in the U.S. This study used concurrent measurements of total suspended particulates (TSP) and airport visibility from every sixth day sampling for 10 years to fit a predictive model for TSP. Predicted daily TSP concentrations were then correlated with daily mortality counts in Poisson regression models controlling for season, weather, time trends, overdispersion, and serial correlation. A significant correlation (P less than 0.0001) was found between predicted TSP and daily mortality. This correlation was independent of sulfur dioxide, but not vice versa. The magnitude of the effect was very similar to results recently reported from Steubenville, Ohio (using actual TSP measurements), with each 100 micrograms/m3 increase in TSP resulting in a 6% increase in mortality. Graphical analysis indicated a dose-response relationship with no evidence of a threshold down to concentrations below half of the National Ambient Air Quality Standards for particulate matter.

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

    ERIC Educational Resources Information Center

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

    2006-01-01

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

  10. Occurrence analysis of daily rainfalls through non-homogeneous Poissonian processes

    NASA Astrophysics Data System (ADS)

    Sirangelo, B.; Ferrari, E.; de Luca, D. L.

    2011-06-01

    A stochastic model based on a non-homogeneous Poisson process, characterised by a time-dependent intensity of rainfall occurrence, is employed to explain seasonal effects of daily rainfalls exceeding prefixed threshold values. The data modelling has been performed with a partition of observed daily rainfall data into a calibration period for parameter estimation and a validation period for checking on occurrence process changes. The model has been applied to a set of rain gauges located in different geographical areas of Southern Italy. The results show a good fit for time-varying intensity of rainfall occurrence process by 2-harmonic Fourier law and no statistically significant evidence of changes in the validation period for different threshold values.

  11. Daily insufficient sleep and active duty status.

    PubMed

    Chapman, Daniel P; Liu, Yong; McKnight-Eily, Lela R; Croft, Janet B; Holt, James B; Balkin, Thomas J; Giles, Wayne H

    2015-01-01

    We assessed the relationship between active duty status and daily insufficient sleep in a telephone survey. U.S. military service status (recent defined as past 12 months and past defined as >12 months ago) and daily insufficient sleep in the past 30 days were assessed among 566,861 adults aged 18 to 64 years and 271,202 adults aged ≥ 65 years in the 2009 to 2010 Behavioral Risk Factor Surveillance System surveys. Among ages 18 to 64 years, 1.1% reported recent active duty and 7.1% had past service; among ages ≥ 65 years, 0.6% reported recent and 24.6% had past service. Among ages 18 to 64 years, prevalence of daily insufficient sleep was 13.7% among those reporting recent duty, 12.6% for those with past service, and 11.2% for those with no service. Insufficient sleep did not vary significantly with active duty status among ages ≥ 65 years. After adjustment for sociodemographic characteristics, health behaviors, and frequent mental distress in multivariate logistic regression models, respondents aged 18 to 64 years with recent active duty were 34% more likely and those with past service were 23% more likely to report daily insufficient sleep than those with no service (p < 0.05, both). Adults with either recent or past active duty have a greater risk for daily insufficient sleep. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

  12. 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…

  13. Solving Tomorrow's Problems Today? Daily Anticipatory Coping and Reactivity to Daily Stressors.

    PubMed

    Neupert, Shevaun D; Ennis, Gilda E; Ramsey, Jennifer L; Gall, Agnes A

    2016-07-01

    The present study examined the day-to-day fluctuation of state-like anticipatory coping (coping employed prior to stressors) and how these coping processes relate to important outcomes for older adults (i.e., physical health, affect, memory failures). Forty-three older adults aged 60-96 (M = 74.65, SD = 8.19) participated in an 8-day daily diary study of anticipatory coping, stressors, health, affect, and memory failures. Participants reported anticipatory coping behaviors on one day with respect to 6 distinct stressor domains that could occur the following day. Multilevel models indicated that anticipatory coping changes from day to day and within stressor domains. Lagged associations suggested that yesterday's anticipatory coping for potential upcoming arguments is related to today's physical health and affect. Increased stagnant deliberation is associated with reduced cognitive reactivity (i.e., fewer memory failures) to arguments the next day. Taken together, these findings suggest that anticipatory coping is dynamic and associated with important daily outcomes. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  14. Combining Radar and Daily Precipitation Data to Estimate Meaningful Sub-daily Precipitation Extremes

    NASA Astrophysics Data System (ADS)

    Pegram, G. G. S.; Bardossy, A.

    2016-12-01

    Short duration extreme rainfalls are important for design. The purpose of this presentation is not to improve the day by day estimation of precipitation, but to obtain reasonable statistics for the subdaily extremes at gauge locations. We are interested specifically in daily and sub-daily extreme values of precipitation at gauge locations. We do not employ the common procedure of using time series of control station to determine the missing data values in a target. We are interested in individual rare events, not sequences. The idea is to use radar to disaggregate daily totals to sub-daily amounts. In South Arica, an S-band radar operated relatively continuously at Bethlehem from 1998 to 2003, whose scan at 1.5 km above ground [CAPPI] overlapped a dense (10 km spacing) set of 45 pluviometers recording in the same 6-year period. Using this valuable set of data, we are only interested in rare extremes, therefore small to medium values of rainfall depth were neglected, leaving 12 days of ranked daily maxima in each set per year, whose sum typically comprised about 50% of each annual rainfall total. The method presented here uses radar for disaggregating daily gauge totals in subdaily intervals down to 15 minutes in order to extract the maxima of sub-hourly through to daily rainfall at each of 37 selected radar pixels [1 km square in plan] which contained one of the 45 pluviometers not masked out by the radar foot-print. The pluviometer data were aggregated to daily totals, to act as if they were daily read gauges; their only other task was to help in the cross-validation exercise. The extrema were obtained as quantiles by ordering the 12 daily maxima of each interval per year. The unusual and novel goal was not to obtain the reproduction of the precipitation matching in space and time, but to obtain frequency distributions of the gauge and radar extremes, by matching their ranks, which we found to be stable and meaningful in cross-validation tests. We provide and

  15. Daily Concordance between Parent and Adolescent Sleep Habits

    PubMed Central

    Fuligni, Andrew J.; Tsai, Kim M.; Krull, Jennifer L.; Gonzales, Nancy A.

    2014-01-01

    Purpose To assess the daily concordance between parent and adolescent daily sleep habits, how that concordance compares to other predictors of sleep, and whether the degree of concordance varies across families. Methods A total of 421 adolescents (Mage = 15.03 years) and their primary caregivers (Mage = 41.93 years) reported their sleep, bed, and wake times on a daily basis for a two-week period. Approximately 80% of the sample repeated the same protocol one year later. Results Multi-level modeling indicated a significant concordance between parent and adolescent sleep, bed, and wake times on a daily basis. Concordance existed independent of other predictors of sleep such as day of the week and adolescent study time. Larger families and those with higher levels of parent-adolescent support exhibited greater concordance. Conclusions Adolescent sleep is connected to the sleep habits of their parents, above and beyond commonly-known structural and experiential factors that can shape teenage sleep. Efforts to improve teenage sleep should pay greater attention to the sleep patterns of parents and potentially other family members. PMID:25620309

  16. Examination of Daily Weather in the NCAR CCM

    NASA Astrophysics Data System (ADS)

    Cocke, S. D.

    2006-05-01

    The NCAR CCM is one of the most extensively studied climate models in the scientific community. However, most studies focus primarily on the long term mean behavior, typically monthly or longer time scales. In this study we examine the daily weather in the GCM by performing a series of daily or weekly 10 day forecasts for one year at moderate (T63) and high (T126) resolution. The model is initialized with operational "AVN" and ECMWF analyses, and model performance is compared to that of major operational centers, using conventional skill scores used by the major centers. Such a detailed look at the CCM at shorter time scales may lead to improvements in physical parameterizations, which may in turn lead to improved climate simulations. One finding from this study is that the CCM has a significant drying tendency in the lower troposphere compared to the operational analyses. Another is that the large scale predictability of the GCM is competitive with most of the operational models, particularly in the southern hemisphere.

  17. Creating a global sub-daily precipitation dataset

    NASA Astrophysics Data System (ADS)

    Lewis, Elizabeth; Blenkinsop, Stephen; Fowler, Hayley

    2017-04-01

    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.

  18. Mesalamine once daily is more effective than twice daily in patients with quiescent ulcerative colitis.

    PubMed

    Dignass, Axel U; Bokemeyer, Bernd; Adamek, Henning; Mross, Michael; Vinter-Jensen, Lars; Börner, Norbert; Silvennoinen, Jouni; Tan, Gie; Pool, Marco Oudkerk; Stijnen, Theo; Dietel, Peter; Klugmann, Tobias; Vermeire, Severine; Bhatt, Aomesh; Veerman, Henri

    2009-07-01

    Oral mesalamine (5-aminosalicylate) is the current standard of care for mild-to-moderate ulcerative colitis. We investigated the efficacy and safety of once daily administration of prolonged-release mesalamine granules in maintenance of remission in patients with quiescent ulcerative colitis, compared with the well established twice daily dosing regimen. In this multicenter, randomized, single blind, noninferiority trial, 362 patients with quiescent ulcerative colitis were randomly assigned (1:1) to groups that were given oral mesalamine 2 g, once daily, or 1 g, twice daily, for 12 months. The primary objective was to compare remission rates at 1 year, based on the ulcerative colitis disease activity index score, using Kaplan-Meier methodology. At 1 year, 70.9% of the group given 2 g mesalamine once daily remained in remission vs 58.9% of the group given 1 g mesalamine twice daily; this difference was statistically significant (P = .024), indicating the increased efficacy of once daily, compared with twice daily, dosing. Self-reported adherence to therapy, measured by visual analog scale score after 4, 8, and 12 months, was significantly greater in the group given 2 g mesalamine once daily, compared with twice daily, at all but 1 study visit (P < .05). Compliance measured by medication taken was not significantly different between the groups. The difference between the 2 groups in overall incidence of adverse events was not statistically significant (P = .23). Patients with ulcerative colitis given prolonged-release oral mesalamine 2 g once daily had better remission rates, acceptability, and self-reported adherence to therapy compared with patients given oral mesalamine 1 g twice daily.

  19. Exploring the modeling of spatiotemporal variations in ambient air pollution within the land use regression framework: Estimation of PM10 concentrations on a daily basis.

    PubMed

    Alam, Md Saniul; McNabola, Aonghus

    2015-05-01

    Estimation of daily average exposure to PM10 (particulate matter with an aerodynamic diameter<10 μm) using the available fixed-site monitoring stations (FSMs) in a city poses a great challenge. This is because typically FSMs are limited in number when considering the spatial representativeness of their measurements and also because statistical models of citywide exposure have yet to be explored in this context. This paper deals with the later aspect of this challenge and extends the widely used land use regression (LUR) approach to deal with temporal changes in air pollution and the influence of transboundary air pollution on short-term variations in PM10. Using the concept of multiple linear regression (MLR) modeling, the average daily concentrations of PM10 in two European cities, Vienna and Dublin, were modeled. Models were initially developed using the standard MLR approach in Vienna using the most recently available data. Efforts were subsequently made to (i) assess the stability of model predictions over time; (ii) explores the applicability of nonparametric regression (NPR) and artificial neural networks (ANNs) to deal with the nonlinearity of input variables. The predictive performance of the MLR models of the both cities was demonstrated to be stable over time and to produce similar results. However, NPR and ANN were found to have more improvement in the predictive performance in both cities. Using ANN produced the highest result, with daily PM10 exposure predicted at R2=66% for Vienna and 51% for Dublin. In addition, two new predictor variables were also assessed for the Dublin model. The variables representing transboundary air pollution and peak traffic count were found to account for 6.5% and 12.7% of the variation in average daily PM10 concentration. The variable representing transboundary air pollution that was derived from air mass history (from back-trajectory analysis) and population density has demonstrated a positive impact on model performance

  20. Multisite stochastic simulation of daily precipitation from copula modeling with a gamma marginal distribution

    NASA Astrophysics Data System (ADS)

    Lee, Taesam

    2018-05-01

    Multisite stochastic simulations of daily precipitation have been widely employed in hydrologic analyses for climate change assessment and agricultural model inputs. Recently, a copula model with a gamma marginal distribution has become one of the common approaches for simulating precipitation at multiple sites. Here, we tested the correlation structure of the copula modeling. The results indicate that there is a significant underestimation of the correlation in the simulated data compared to the observed data. Therefore, we proposed an indirect method for estimating the cross-correlations when simulating precipitation at multiple stations. We used the full relationship between the correlation of the observed data and the normally transformed data. Although this indirect method offers certain improvements in preserving the cross-correlations between sites in the original domain, the method was not reliable in application. Therefore, we further improved a simulation-based method (SBM) that was developed to model the multisite precipitation occurrence. The SBM preserved well the cross-correlations of the original domain. The SBM method provides around 0.2 better cross-correlation than the direct method and around 0.1 degree better than the indirect method. The three models were applied to the stations in the Nakdong River basin, and the SBM was the best alternative for reproducing the historical cross-correlation. The direct method significantly underestimates the correlations among the observed data, and the indirect method appeared to be unreliable.

  1. Daily occupational stressors and marital behavior.

    PubMed

    Story, Lisa B; Repetti, Rena

    2006-12-01

    This study examined daily fluctuations in marital behavior (anger and withdrawal) as a function of same-day job stressors, using hierarchical linear modeling (HLM). Forty-three couples provided daily diary reports of their workload and negative social interactions at work on 5 consecutive days. Within-subject analyses demonstrate that husbands and wives reported greater marital anger and withdrawal following negative social interactions at work, and wives reported greater marital anger and withdrawal following days of heavy workload. Mediation analyses provide support for the negative mood spillover hypothesis (e.g., workload no longer predicted wives' marital anger when controlling for negative mood). Between-subjects analyses suggest that spouses in high-conflict families may be especially vulnerable to the effects of job stressors on marital interaction. (c) 2006 APA, all rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  3. Characterization and disaggregation of daily rainfall in the Upper Blue Nile Basin in Ethiopia

    NASA Astrophysics Data System (ADS)

    Engida, Agizew N.; Esteves, Michel

    2011-03-01

    SummaryIn Ethiopia, available rainfall records are mainly limited to daily time steps. Though rainfall data at shorter time steps are important for various purposes like modeling of erosion processes and flood hydrographs, they are hardly available in Ethiopia. The objectives of this study were (i) to study the temporal characteristics of daily rains at two stations in the region of the Upper Blue Nile Basin (UBNB) and (ii) to calibrate and evaluate a daily rainfall disaggregation model. The analysis was based on rainfall data of Bahir Dar and Gonder Meteorological Stations. The disaggregation model used was the Modified Bartlett-Lewis Rectangular Pulse Model (MBLRPM). The mean daily rainfall intensity varied from about 4 mm in the dry season to 17 mm in the wet season with corresponding variation in raindays of 0.4-26 days. The observed maximum daily rainfall varied from 13 mm in the dry month to 200 mm in the wet month. The average wet/dry spell length varied from 1/21 days in the dry season to 6/1 days in the rainy season. Most of the rainfall occurs in the afternoon and evening periods of the day. Daily rainfall disaggregation using the MBLRPM alone resulted in poor match between the disaggregated and observed hourly rainfalls. Stochastic redistribution of the outputs of the model using Beta probability distribution function improved the agreement between observed and calculated hourly rain intensities. In areas where convective rainfall is dominant, the outputs of MBLRPM should be redistributed using relevant probability distributions to simulate the diurnal rainfall pattern.

  4. Non-Linear Concentration-Response Relationships between Ambient Ozone and Daily Mortality.

    PubMed

    Bae, Sanghyuk; Lim, Youn-Hee; Kashima, Saori; Yorifuji, Takashi; Honda, Yasushi; Kim, Ho; Hong, Yun-Chul

    2015-01-01

    Ambient ozone (O3) concentration has been reported to be significantly associated with mortality. However, linearity of the relationships and the presence of a threshold has been controversial. The aim of the present study was to examine the concentration-response relationship and threshold of the association between ambient O3 concentration and non-accidental mortality in 13 Japanese and Korean cities from 2000 to 2009. We selected Japanese and Korean cities which have population of over 1 million. We constructed Poisson regression models adjusting daily mean temperature, daily mean PM10, humidity, time trend, season, year, day of the week, holidays and yearly population. The association between O3 concentration and mortality was examined using linear, spline and linear-threshold models. The thresholds were estimated for each city, by constructing linear-threshold models. We also examined the city-combined association using a generalized additive mixed model. The mean O3 concentration did not differ greatly between Korea and Japan, which were 26.2 ppb and 24.2 ppb, respectively. Seven out of 13 cities showed better fits for the spline model compared with the linear model, supporting a non-linear relationships between O3 concentration and mortality. All of the 7 cities showed J or U shaped associations suggesting the existence of thresholds. The range of city-specific thresholds was from 11 to 34 ppb. The city-combined analysis also showed a non-linear association with a threshold around 30-40 ppb. We have observed non-linear concentration-response relationship with thresholds between daily mean ambient O3 concentration and daily number of non-accidental death in Japanese and Korean cities.

  5. 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

  6. 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...

  7. An introduction to the Micrel Micropump MP Daily portable syringe driver.

    PubMed

    Groves, Karen E

    2003-11-01

    In this article the author describes the Micrel Micropump MP Daily (MP Daily) portable syringe driver. This follows the author's experience of a 4-month pilot of the device by an inpatient palliative care unit. Portable syringe drivers are commonly used to deliver continuous subcutaneous infusions in palliative care situations. Those in current use are not without problems and serious adverse events have occasionally been reported, mainly resulting from confusion between models. The MP Daily syringe driver addresses some of these issues while remaining small, lightweight and inexpensive, with a long battery life and fitting into the pocket of a shirt of pyjama jacket. Improvements over current models include an on/off button, the absence of facilities to set a zero rate or change the rate once the syringe driver is running, and the absence of a boost button. In addition, there are improved alarms, a message display system and a configuration menu. Although confusion remains a problem, and the ideal has not yet been reached, the MP Daily goes some considerable way towards reducing risks and opportunities for human error.

  8. Drawbacks of proactivity: Effects of daily proactivity on daily salivary cortisol and subjective well-being.

    PubMed

    Fay, Doris; Hüttges, Annett

    2017-10-01

    The benefit of proactive work behaviors for performance-related outcomes has been well established. However, this approach to studying proactivity has not yet acknowledged its potential implications for the actor's well-being. Drawing on the fact that resources at work are limited and that the workplace is a social system characterized by interdependencies, we proposed that daily proactivity could have a negative effect on daily well-being. We furthermore proposed that this effect should be mediated by work overload and negative affect. We conducted a daily diary study (N = 72) to test the potential negative effects of proactivity on daily well-being. Data was collected across 3 consecutive work days. During several daily measurement occasions, participants reported proactivity, work overload, negative affect, and fatigue. They also provided 4 saliva samples per day, from which cortisol was assayed. Based on the 4 samples, a measure of daily cortisol output was produced. Multilevel analyses showed that daily proactivity was positively associated with higher daily cortisol output. The positive association of daily proactivity with bedtime fatigue was marginally significant. There was no support for a mediating effect of work overload and negative affect. Implications for theory-building on the proactivity-well-being link are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  9. Associations among daily stressors and salivary cortisol: findings from the National Study of Daily Experiences.

    PubMed

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

    2013-11-01

    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 1694 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, 30min post-waking, before lunch and before bed, on four consecutive interview days resulting in 5995 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. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. 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

  11. Treatment of streptococcal pharyngitis with once-daily compared with twice-daily amoxicillin: a noninferiority trial.

    PubMed

    Clegg, Herbert W; Ryan, Amy G; Dallas, Steven D; Kaplan, Edward L; Johnson, Dwight R; Norton, H James; Roddey, Oliver F; Martin, Edward S; Swetenburg, Raymond L; Koonce, Elizabeth W; Felkner, Mary M; Giftos, P Michael

    2006-09-01

    Two relatively small previous studies comparing once-daily amoxicillin with conventional therapy for group A streptococcal (GAS) pharyngitis reported similar rates of bacteriologic success for each treatment group. The purpose of this study was to further evaluate once-daily amoxicillin for GAS pharyngitis in a larger study. In a single pediatric practice, from October through May for 2 consecutive years (2001-2003), we recruited children 3 to 18 years of age who had symptoms and signs suggestive of GAS pharyngitis. Patients with a positive rapid test for GAS were stratified by weight (<40 kg or >or=40 kg) and then randomly assigned to receive once-daily (750 mg or 1000 mg) or twice-daily (2 doses of 375 mg or 500 mg) amoxicillin for 10 days. We determined bacteriologic failure rates for GAS in the pharynx from subsequent swabs taken at 14 to 21 (visit 2) and 28 to 35 (visit 3) days after treatment initiation. We conducted a randomized, controlled, investigator-blinded, noninferiority trial to evaluate whether amoxicillin given once daily would have a bacteriologic failure rate no worse than that of amoxicillin given twice daily within a prespecified margin of 10%. GAS isolates were characterized to distinguish bacteriologic failures from new acquisitions. Adverse events were described and adherence was evaluated by review of returned daily logs and dosage bottles. Of 2139 potential study patients during the 2-year period, we enrolled 652 patients, 326 into each treatment group. Children in the 2 groups were comparable with respect to all demographic and clinical characteristics except that children <40 kg more often presented with rash in each treatment group. At visit 2, failure rates were 20.1% (59 of 294) for the once-daily group and 15.5% (46 of 296) for the twice-daily group (difference, 4.53%; 90% confidence interval [CI], -0.6 to 9.7). At visit 3, failure rates were 2.8% (6 of 216) for the once-daily group and 7.1% (16 of 225) for the twice-daily group

  12. Daily antecedents and consequences of nightly sleep.

    PubMed

    Lee, Soomi; Crain, Tori L; McHale, Susan M; Almeida, David M; Buxton, Orfeu M

    2017-08-01

    Sleep can serve as both cause and consequence of individuals' everyday experiences. We built upon prior studies of the correlates of sleep, which have relied primarily on cross-sectional data, to examine the antecedents and consequences of sleep using a daily diary design. Specifically, we assessed the temporal sequence between nightly sleep and daily psychosocial stressors. Parents employed in a US information technology company (n = 102) completed eight consecutive daily diaries at both baseline and 1 year later. In telephone interviews each evening, participants reported on the previous night's sleep hours, sleep quality and sleep latency. They also reported daily work-to-family conflict and time inadequacy (i.e. perceptions of not having enough time) for their child and for themselves to engage in exercise. Multi-level models testing lagged and non-lagged effects simultaneously revealed that sleep hours and sleep quality were associated with next-day consequences of work-to-family conflict and time inadequacy, whereas psychosocial stressors as antecedents did not predict sleep hours or quality that night. For sleep latency, the opposite temporal order emerged: on days with more work-to-family conflict or time inadequacy for child and self than usual, participants reported longer sleep latencies than usual. An exception to this otherwise consistent pattern was that time inadequacy for child also preceded shorter sleep hours and poorer sleep quality that night. The results highlight the utility of a daily diary design for capturing the temporal sequences linking sleep and psychosocial stressors. © 2016 European Sleep Research Society.

  13. Personal Risk and Resilience Factors in the Context of Daily Stress

    PubMed Central

    Diehl, Manfred; Hay, Elizabeth L.; Chui, Helena

    2012-01-01

    This chapter focuses on the role that personal risk and resilience factors play as adults of all ages cope with the stressors encountered in everyday life. Theorists have suggested that researchers should focus on the effects of daily stress and coping rather than focusing exclusively on major life events and chronic stress and have proposed that understanding how adults cope with daily stress is a key aspect of understanding long-term well-being and adaptation in adulthood. After presenting a conceptual model outlining the major components of the daily stress process, the chapter reviews the existing empirical literature on personal risk and resilience factors in the context of daily stress. This research clearly suggests that there is no universal generalization that can be made regarding whether chronological age, in and of itself, confers greater vulnerability or resilience onto adults. Instead, we argue that researchers should ask when and under what conditions is age associated with greater vulnerability to daily stress and when and under what conditions is age associated with greater resilience to daily stress. Age differences in reactivity to daily stress are clearly embedded within a complex system of factors—structural, individual, and situational—that influence stress reactivity and stress recovery in several ways. This complexity should not be taken to mean that stress reactivity and recovery cannot be charted or understood. Researchers, however, will need to approach this complexity with a great deal of theoretical, methodological, and statistical rigor to move our understanding of the importance of age in shaping risk and resilience to daily stress forward. The final section of the chapter outlines several directions for future research in the area of aging and resilience. In particular, we argue that a focus on personal risk and resilience factors in the context of daily stress, in combination with the application of sophisticated statistical

  14. 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

  15. Daily emotional and physical reactivity to stressors among widowed and married older adults.

    PubMed

    Hahn, Elizabeth A; Cichy, Kelly E; Small, Brent J; Almeida, David M

    2014-01-01

    Widowhood may result in declines in health and potentially stressful changes to daily routines. However, little research has examined how daily stressors contribute to physical and emotional well-being in widowhood. The objectives of the current study were to examine daily stressor exposure and reactivity in widowed versus married older adults. Participants included all 100 widowed and 342 married adults aged 65 and older from the National Study of Daily Experiences, a daily diary study from the second wave of the Midlife in the United States. Daily stressors were measured using the Daily Inventory of Stressful Events; multilevel modeling assessed daily reactivity to stressors using daily negative affect (emotional reactivity) and daily physical symptoms (physical reactivity) as outcomes. Married participants reported more stressors in general, and specifically more interpersonal stressors (e.g., arguments). Both married and widowed participants were reactive to daily stressors. Married participants were physically and emotionally reactive to interpersonal stressors. Widowed participants were more physically reactive to home-related stressors. Attention to the types of daily stressors that widowed older adults experience in daily life and the potential physical effects of daily stressors during widowhood may help to alleviate some of the physical distress that widowed older adults may experience.

  16. Daily Emotional and Physical Reactivity to Stressors Among Widowed and Married Older Adults

    PubMed Central

    2014-01-01

    Objectives. Widowhood may result in declines in health and potentially stressful changes to daily routines. However, little research has examined how daily stressors contribute to physical and emotional well-being in widowhood. The objectives of the current study were to examine daily stressor exposure and reactivity in widowed versus married older adults. Method. Participants included all 100 widowed and 342 married adults aged 65 and older from the National Study of Daily Experiences, a daily diary study from the second wave of the Midlife in the United States. Daily stressors were measured using the Daily Inventory of Stressful Events; multilevel modeling assessed daily reactivity to stressors using daily negative affect (emotional reactivity) and daily physical symptoms (physical reactivity) as outcomes. Results. Married participants reported more stressors in general, and specifically more interpersonal stressors (e.g., arguments). Both married and widowed participants were reactive to daily stressors. Married participants were physically and emotionally reactive to interpersonal stressors. Widowed participants were more physically reactive to home-related stressors. Discussion. Attention to the types of daily stressors that widowed older adults experience in daily life and the potential physical effects of daily stressors during widowhood may help to alleviate some of the physical distress that widowed older adults may experience. PMID:23685921

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

    PubMed Central

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

    2013-01-01

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

  18. Daily minority stress and affect among gay and bisexual men: A 30-day diary study.

    PubMed

    Eldahan, Adam I; Pachankis, John E; Jonathon Rendina, H; Ventuneac, Ana; Grov, Christian; Parsons, Jeffrey T

    2016-01-15

    This study examined the time-variant association between daily minority stress and daily affect among gay and bisexual men. Tests of time-lagged associations allow for a stronger causal examination of minority stress-affect associations compared with static assessments. Multilevel modeling allows for comparison of associations between minority stress and daily affect when minority stress is modeled as a between-person factor and a within-person time-fluctuating state. 371 gay and bisexual men in New York City completed a 30-day daily diary, recording daily experiences of minority stress and positive affect (PA), negative affect (NA), and anxious affect (AA). Multilevel analyses examined associations between minority stress and affect in both same-day and time-lagged analyses, with minority stress assessed as both a between-person factor and a within-person state. Daily minority stress, modeled as both a between-person and within-person construct, significantly predicted lower PA and higher NA and AA. Daily minority stress also predicted lower subsequent-day PA and higher subsequent-day NA and AA. Self-report assessments and the unique sample may limit generalizability of this study. The time-variant association between sexual minority stress and affect found here substantiates the basic tenet of minority stress theory with a fine-grained analysis of gay and bisexual men's daily experience. Time-lagged effects suggest a potentially causal pathway between minority stress as a social determinant of mood and anxiety disorder symptoms among gay and bisexual men. When modeled as both a between-person factor and within-person state, minority stress demonstrated expected patterns with affect. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Daily Minority Stress and Affect among Gay and Bisexual Men: A 30-day Diary Study

    PubMed Central

    Eldahan, Adam I.; Pachankis, John E.; Rendina, H. Jonathon; Ventuneac, Ana; Grov, Christian; Parsons, Jeffrey T.

    2015-01-01

    Background This study examined the time-variant association between daily minority stress and daily affect among gay and bisexual men. Tests of time-lagged associations allow for a stronger causal examination of minority stress-affect associations compared with static assessments. Multilevel modeling allows for comparison of associations between minority stress and daily affect when minority stress is modeled as a between-person factor and a within-person time-fluctuating state. Methods 371 gay and bisexual men in New York City completed a 30-day daily diary, recording daily experiences of minority stress and positive affect (PA), negative affect (NA), and anxious affect (AA). Multilevel analyses examined associations between minority stress and affect in both same-day and time-lagged analyses, with minority stress assessed as both a between-person factor and a within-person state. Results Daily minority stress, modeled as both a between-person and within-person construct, significantly predicted lower PA and higher NA and AA. Daily minority stress also predicted lower subsequent-day PA and higher subsequent-day NA and AA. Limitations Self-report assessments and the unique sample may limit generalizability of this study. Conclusions The time-variant association between sexual minority stress and affect found here substantiates the basic tenet of minority stress theory with a fine-grained analysis of gay and bisexual men’s daily experience. Time-lagged effects suggest a potentially causal pathway between minority stress as a social determinant of mood and anxiety disorder symptoms among gay and bisexual men. When modeled as both a between-person factor and within-person state, minority stress demonstrated expected patterns with affect. PMID:26625095

  20. Daily river flow prediction based on Two-Phase Constructive Fuzzy Systems Modeling: A case of hydrological - meteorological measurements asymmetry

    NASA Astrophysics Data System (ADS)

    Bou-Fakhreddine, Bassam; Mougharbel, Imad; Faye, Alain; Abou Chakra, Sara; Pollet, Yann

    2018-03-01

    Accurate daily river flow forecast is essential in many applications of water resources such as hydropower operation, agricultural planning and flood control. This paper presents a forecasting approach to deal with a newly addressed situation where hydrological data exist for a period longer than that of meteorological data (measurements asymmetry). In fact, one of the potential solutions to resolve measurements asymmetry issue is data re-sampling. It is a matter of either considering only the hydrological data or the balanced part of the hydro-meteorological data set during the forecasting process. However, the main disadvantage is that we may lose potentially relevant information from the left-out data. In this research, the key output is a Two-Phase Constructive Fuzzy inference hybrid model that is implemented over the non re-sampled data. The introduced modeling approach must be capable of exploiting the available data efficiently with higher prediction efficiency relative to Constructive Fuzzy model trained over re-sampled data set. The study was applied to Litani River in the Bekaa Valley - Lebanon by using 4 years of rainfall and 24 years of river flow daily measurements. A Constructive Fuzzy System Model (C-FSM) and a Two-Phase Constructive Fuzzy System Model (TPC-FSM) are trained. Upon validating, the second model has shown a primarily competitive performance and accuracy with the ability to preserve a higher day-to-day variability for 1, 3 and 6 days ahead. In fact, for the longest lead period, the C-FSM and TPC-FSM were able of explaining respectively 84.6% and 86.5% of the actual river flow variation. Overall, the results indicate that TPC-FSM model has provided a better tool to capture extreme flows in the process of streamflow prediction.

  1. Daily concordance between parent and adolescent sleep habits.

    PubMed

    Fuligni, Andrew J; Tsai, Kim M; Krull, Jennifer L; Gonzales, Nancy A

    2015-02-01

    To assess the daily concordance between parent and adolescent daily sleep habits, how that concordance compares to other predictors of sleep, and whether the degree of concordance varies across families. A total of 421 adolescents (Mage = 15.03 years) and their primary caregivers (Mage = 41.93 years) reported their sleep, bed, and wake times on a daily basis for a 2-week period. Approximately 80% of the sample repeated the same protocol 1 year later. Multilevel modeling indicated a significant concordance between parent and adolescent sleep, bed, and wake times on a daily basis. Concordance existed independent of other predictors of sleep such as day of the week and adolescent study time. Larger families and those with higher levels of parent-adolescent support exhibited greater concordance. Adolescent sleep is connected to the sleep habits of their parents, above and beyond commonly known structural and experiential factors that can shape teenage sleep. Efforts to improve teenage sleep should pay greater attention to the sleep patterns of parents and potentially other family members. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  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. Extracting aerobic system dynamics during unsupervised activities of daily living using wearable sensor machine learning models.

    PubMed

    Beltrame, Thomas; Amelard, Robert; Wong, Alexander; Hughson, Richard L

    2018-02-01

    Physical activity levels are related through algorithms to the energetic demand, with no information regarding the integrity of the multiple physiological systems involved in the energetic supply. Longitudinal analysis of the oxygen uptake (V̇o 2 ) by wearable sensors in realistic settings might permit development of a practical tool for the study of the longitudinal aerobic system dynamics (i.e., V̇o 2 kinetics). This study evaluated aerobic system dynamics based on predicted V̇o 2 data obtained from wearable sensors during unsupervised activities of daily living (μADL). Thirteen healthy men performed a laboratory-controlled moderate exercise protocol and were monitored for ≈6 h/day for 4 days (μADL data). Variables derived from hip accelerometer (ACC HIP ), heart rate monitor, and respiratory bands during μADL were extracted and processed by a validated random forest regression model to predict V̇o 2 . The aerobic system analysis was based on the frequency-domain analysis of ACC HIP and predicted V̇o 2 data obtained during μADL. Optimal samples for frequency domain analysis (constrained to ≤0.01 Hz) were selected when ACC HIP was higher than 0.05 g at a given frequency (i.e., participants were active). The temporal characteristics of predicted V̇o 2 data during μADL correlated with the temporal characteristics of measured V̇o 2 data during laboratory-controlled protocol ([Formula: see text] = 0.82, P < 0.001, n = 13). In conclusion, aerobic system dynamics can be investigated during unsupervised activities of daily living by wearable sensors. Although speculative, these algorithms have the potential to be incorporated into wearable systems for early detection of changes in health status in realistic environments by detecting changes in aerobic response dynamics. NEW & NOTEWORTHY The early detection of subclinical aerobic system impairments might be indicative of impaired physiological reserves that impact the capacity for physical activity

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

    USGS Publications Warehouse

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

    2016-01-01

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

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

    USGS Publications Warehouse

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

    2015-10-14

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

  6. Predictive model accuracy in estimating last Δ9-tetrahydrocannabinol (THC) intake from plasma and whole blood cannabinoid concentrations in chronic, daily cannabis smokers administered subchronic oral THC.

    PubMed

    Karschner, Erin L; Schwope, David M; Schwilke, Eugene W; Goodwin, Robert S; Kelly, Deanna L; Gorelick, David A; Huestis, Marilyn A

    2012-10-01

    Determining time since last cannabis/Δ9-tetrahydrocannabinol (THC) exposure is important in clinical, workplace, and forensic settings. Mathematical models calculating time of last exposure from whole blood concentrations typically employ a theoretical 0.5 whole blood-to-plasma (WB/P) ratio. No studies previously evaluated predictive models utilizing empirically-derived WB/P ratios, or whole blood cannabinoid pharmacokinetics after subchronic THC dosing. Ten male chronic, daily cannabis smokers received escalating around-the-clock oral THC (40-120 mg daily) for 8 days. Cannabinoids were quantified in whole blood and plasma by two-dimensional gas chromatography-mass spectrometry. Maximum whole blood THC occurred 3.0 h after the first oral THC dose and 103.5h (4.3 days) during multiple THC dosing. Median WB/P ratios were THC 0.63 (n=196), 11-hydroxy-THC 0.60 (n=189), and 11-nor-9-carboxy-THC (THCCOOH) 0.55 (n=200). Predictive models utilizing these WB/P ratios accurately estimated last cannabis exposure in 96% and 100% of specimens collected within 1-5h after a single oral THC dose and throughout multiple dosing, respectively. Models were only 60% and 12.5% accurate 12.5 and 22.5h after the last THC dose, respectively. Predictive models estimating time since last cannabis intake from whole blood and plasma cannabinoid concentrations were inaccurate during abstinence, but highly accurate during active THC dosing. THC redistribution from large cannabinoid body stores and high circulating THCCOOH concentrations create different pharmacokinetic profiles than those in less than daily cannabis smokers that were used to derive the models. Thus, the models do not accurately predict time of last THC intake in individuals consuming THC daily. Published by Elsevier Ireland Ltd.

  7. Predictive model accuracy in estimating last Δ9-tetrahydrocannabinol (THC) intake from plasma and whole blood cannabinoid concentrations in chronic, daily cannabis smokers administered subchronic oral THC*

    PubMed Central

    Karschner, Erin L.; Schwope, David M.; Schwilke, Eugene W.; Goodwin, Robert S.; Kelly, Deanna L.; Gorelick, David A.; Huestis, Marilyn A.

    2012-01-01

    Background Determining time since last cannabis/Δ9-tetrahydrocannabinol (THC) exposure is important in clinical, workplace, and forensic settings. Mathematical models calculating time of last exposure from whole blood concentrations typically employ a theoretical 0.5 whole blood-to-plasma (WB/P) ratio. No studies previously evaluated predictive models utilizing empirically-derived WB/P ratios, or whole blood cannabinoid pharmacokinetics after subchronic THC dosing. Methods Ten male chronic, daily cannabis smokers received escalating around-the-clock oral THC (40-120 mg daily) for 8 days. Cannabinoids were quantified in whole blood and plasma by two-dimensional gas chromatography-mass spectrometry. Results Maximum whole blood THC occurred 3.0 h after the first oral THC dose and 103.5 h (4.3 days) during multiple THC dosing. Median WB/P ratios were THC 0.63 (n=196), 11-hydroxy-THC 0.60 (n=189), and 11-nor-9-carboxy-THC (THCCOOH) 0.55 (n=200). Predictive models utilizing these WB/P ratios accurately estimated last cannabis exposure in 96% and 100% of specimens collected within 1-5 h after a single oral THC dose and throughout multiple dosing, respectively. Models were only 60% and 12.5% accurate 12.5 and 22.5 h after the last THC dose, respectively. Conclusions Predictive models estimating time since last cannabis intake from whole blood and plasma cannabinoid concentrations were inaccurate during abstinence, but highly accurate during active THC dosing. THC redistribution from large cannabinoid body stores and high circulating THCCOOH concentrations create different pharmacokinetic profiles than those in less than daily cannabis smokers that were used to derive the models. Thus, the models do not accurately predict time of last THC intake in individuals consuming THC daily. PMID:22464363

  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. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Comparison of once-daily versus twice-daily combination of ropinirole prolonged release in Parkinson's disease.

    PubMed

    Yun, Ji Young; Kim, Han-Joon; Lee, Jee-Young; Kim, Young Eun; Kim, Ji Seon; Kim, Jong-Min; Jeon, Beom S

    2013-09-02

    Ropinirole prolonged release (RPR) is a once-daily formulation. However, there may be individual pharmacokinetic differences so that multiple dosing may be preferred in some individuals. This study compares once-daily and twice-daily RPR in patients with Parkinson's disease. This study was an open-label crossover study. We enrolled Parkinson's disease patients on dopamine agonist therapy with unsatisfactory control such as motor fluctuation, dyskinesia and sleep-related problems. Agonists were switched into equivalent dose of RPR. Subjects were consecutively enrolled into either once-daily first or twice-daily first groups, and received the same amount of RPR in a single and two divided dosing for 8 weeks respectively in a crossover manner without a washout period.The primary outcome was a questionnaire of the preference completed by patients in the last visit. The secondary outcome measures included the Unified Parkinson's Disease Rating Scale part 3 (mUPDRS), Hoehn and Yahr stage (H&Y); sleep questionnaire including overall quality of sleep, nocturnal off symptoms and early morning symptoms; Epworth Sleep Scale (ESS); compliances and patient global impression (PGI). A total of 82 patients were enrolled and 61 completed the study. 31 patients preferred twice-daily regimen, 17 preferred the once-daily regimen, and 13 had no preference. Their mean mUPDRS, H&Y, ESS, sleep quality, compliance and adverse events were not statistically different in both regimens. PGI-improvement on wearing off defined was better in twice-daily dosing regimen. RPR is a once-daily formulation, but multiple dosing was preferred in many patients. Multiple dosing of RPR might be a therapeutic option if once-daily dosing is unsatisfactory.

  10. Estimation of the ARNO model baseflow parameters using daily streamflow data

    NASA Astrophysics Data System (ADS)

    Abdulla, F. A.; Lettenmaier, D. P.; Liang, Xu

    1999-09-01

    An approach is described for estimation of baseflow parameters of the ARNO model, using historical baseflow recession sequences extracted from daily streamflow records. This approach allows four of the model parameters to be estimated without rainfall data, and effectively facilitates partitioning of the parameter estimation procedure so that parsimonious search procedures can be used to estimate the remaining storm response parameters separately. Three methods of optimization are evaluated for estimation of four baseflow parameters. These methods are the downhill Simplex (S), Simulated Annealing combined with the Simplex method (SA) and Shuffled Complex Evolution (SCE). These estimation procedures are explored in conjunction with four objective functions: (1) ordinary least squares; (2) ordinary least squares with Box-Cox transformation; (3) ordinary least squares on prewhitened residuals; (4) ordinary least squares applied to prewhitened with Box-Cox transformation of residuals. The effects of changing the seed random generator for both SA and SCE methods are also explored, as are the effects of the bounds of the parameters. Although all schemes converge to the same values of the objective function, SCE method was found to be less sensitive to these issues than both the SA and the Simplex schemes. Parameter uncertainty and interactions are investigated through estimation of the variance-covariance matrix and confidence intervals. As expected the parameters were found to be correlated and the covariance matrix was found to be not diagonal. Furthermore, the linearized confidence interval theory failed for about one-fourth of the catchments while the maximum likelihood theory did not fail for any of the catchments.

  11. Time-Series Approaches for Forecasting the Number of Hospital Daily Discharged Inpatients.

    PubMed

    Ting Zhu; Li Luo; Xinli Zhang; Yingkang Shi; Wenwu Shen

    2017-03-01

    For hospitals where decisions regarding acceptable rates of elective admissions are made in advance based on expected available bed capacity and emergency requests, accurate predictions of inpatient bed capacity are especially useful for capacity reservation purposes. As given, the remaining unoccupied beds at the end of each day, bed capacity of the next day can be obtained by examining the forecasts of the number of discharged patients during the next day. The features of fluctuations in daily discharges like trend, seasonal cycles, special-day effects, and autocorrelation complicate decision optimizing, while time-series models can capture these features well. This research compares three models: a model combining seasonal regression and ARIMA, a multiplicative seasonal ARIMA (MSARIMA) model, and a combinatorial model based on MSARIMA and weighted Markov Chain models in generating forecasts of daily discharges. The models are applied to three years of discharge data of an entire hospital. Several performance measures like the direction of the symmetry value, normalized mean squared error, and mean absolute percentage error are utilized to capture the under- and overprediction in model selection. The findings indicate that daily discharges can be forecast by using the proposed models. A number of important practical implications are discussed, such as the use of accurate forecasts in discharge planning, admission scheduling, and capacity reservation.

  12. 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

  13. A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

    PubMed Central

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

    2017-01-01

    Background The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM2.5) 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. Methods 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 PM2.5 at a 1×1km 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 1×1 km grid predictions. We used mixed models regressing PM2.5 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. Results Our model performance was excellent (mean out-of-sample R2=0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R2=0.87, R2=0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Conclusion Our daily model results show high predictive accuracy at high spatial resolutions

  14. A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data.

    PubMed

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

    2014-10-01

    The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM 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 2.5 at a 1×1km 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 1×1 km grid predictions. We used mixed models regressing PM 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 2 =0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R 2 =0.87, R 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 and will be useful in

  15. 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.

  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. Reciprocal feedback between self-concept and goal pursuit in daily life.

    PubMed

    Wong, Alexander E; Vallacher, Robin R

    2018-06-01

    We hypothesized that self-knowledge and goal perseverance are mutually reinforcing because of the roles of self-knowledge in directing goal pursuit, and of goal pursuit in structuring the self-concept. To test this hypothesis, we used a daily diary design with 97 college-aged participants for 40 days to assess whether daily self-concept clarity and grit predict one another's next-day levels. Data were analyzed using multilevel cross-lagged panel modeling. Results indicated that daily self-concept clarity and grit had positive and symmetric associations with each other across time, while controlling for their respective previous values. Similar crossed results were also found when testing the model using individual daily self-concept clarity and grit items. The results are the first to indicate the existence of reinforcing feedback loops between self-concept clarity and grit, such that fluctuations in the clarity of self-knowledge are associated with fluctuations in goal resolve, and vice versa. Discussion centers on the implications of these results for the functional link between mind and action and on the study's heuristic value for subsequent research. © 2017 Wiley Periodicals, Inc.

  18. Affective reactivity to daily stressors is associated with elevated inflammation.

    PubMed

    Sin, Nancy L; Graham-Engeland, Jennifer E; Ong, Anthony D; Almeida, David M

    2015-12-01

    Inflammation increases the risk of chronic diseases, but the links between emotional responses to daily events and inflammation are unknown. We examined individual differences in affective reactivity to daily stressors (i.e., changes in positive and negative affect in response to stressors) as predictors of inflammatory markers interleukin-6 (IL-6) and C-reactive protein (CRP). A cross-sectional sample of 872 adults from the National Study of Daily Experiences (substudy of Midlife in the United States II) reported daily stressors and affect during telephone interviews for 8 days. Blood samples were obtained at a separate clinic visit and assayed for inflammatory markers. Multilevel models estimated trait affective reactivity slopes for each participant, which were inputted into regression models to predict inflammation. People who experienced greater decreases in positive affect on days when stressors occurred (i.e., positive affect reactivity) had elevated log IL-6, independent of demographic, physical, psychological, and behavioral factors (B = 1.12, SE = 0.45, p = .01). Heightened negative affect reactivity was associated with higher log CRP among women (p = .03) but not men (p = .57); health behaviors accounted for this association in women. Adults who fail to maintain positive affect when faced with minor stressors in everyday life appear to have elevated levels of IL-6, a marker of inflammation. Women who experience increased negative affect when faced with minor stressors may be at particular risk of elevated inflammation. These findings add to growing evidence regarding the health implications of affective reactivity to daily stressors. (c) 2015 APA, all rights reserved).

  19. Affective reactivity to daily stressors is associated with elevated inflammation

    PubMed Central

    Sin, Nancy L.; Graham-Engeland, Jennifer E.; Ong, Anthony D.; Almeida, David M.

    2015-01-01

    Objective Inflammation increases the risk of chronic diseases, but the links between emotional responses to daily events and inflammation are unknown. We examined individual differences in affective reactivity to daily stressors (i.e., changes in positive and negative affect in response to stressors) as predictors of inflammatory markers interleukin-6 (IL-6) and C-reactive protein (CRP). Methods A cross-sectional sample of 872 adults from the National Study of Daily Experiences (sub-study of Midlife in the United States II) reported daily stressors and affect during telephone interviews for 8 days. Blood samples were obtained at a separate clinic visit and assayed for inflammatory markers. Multilevel models estimated trait affective reactivity slopes for each participant, which were inputted into regression models to predict inflammation. Results People who experienced greater decreases in positive affect on days when stressors occurred (i.e, positive affect reactivity) had elevated log IL-6, independent of demographic, physical, psychological, and behavioral factors (B = 1.12, SE = 0.45, p = 0.01). Heightened negative affect reactivity was associated with higher log CRP among women (p = 0.03) but not men (p = 0.57); health behaviors accounted for this association in women. Conclusions Adults who fail to maintain positive affect when faced with minor stressors in everyday life appear to have elevated levels of IL-6, a marker of inflammation. Women who experience increased negative affect when faced with minor stressors may be at particular risk of elevated inflammation. These findings add to growing evidence regarding the health implications of affective reactivity to daily stressors. PMID:26030309

  20. Estimating stage-specific daily survival probabilities of nests when nest age is unknown

    USGS Publications Warehouse

    Stanley, T.R.

    2004-01-01

    Estimation of daily survival probabilities of nests is common in studies of avian populations. Since the introduction of Mayfield's (1961, 1975) estimator, numerous models have been developed to relax Mayfield's assumptions and account for biologically important sources of variation. Stanley (2000) presented a model for estimating stage-specific (e.g. incubation stage, nestling stage) daily survival probabilities of nests that conditions on “nest type” and requires that nests be aged when they are found. Because aging nests typically requires handling the eggs, there may be situations where nests can not or should not be aged and the Stanley (2000) model will be inapplicable. Here, I present a model for estimating stage-specific daily survival probabilities that conditions on nest stage for active nests, thereby obviating the need to age nests when they are found. Specifically, I derive the maximum likelihood function for the model, evaluate the model's performance using Monte Carlo simulations, and provide software for estimating parameters (along with an example). For sample sizes as low as 50 nests, bias was small and confidence interval coverage was close to the nominal rate, especially when a reduced-parameter model was used for estimation.

  1. The stress of food allergy issues in daily life.

    PubMed

    Peniamina, Rana L; Mirosa, Miranda; Bremer, Philip; Conner, Tamlin S

    2016-06-01

    Food allergies are a growing health concern, but their implications for daily psychological functioning are unknown. This micro-longitudinal study investigated the daily frequency of food allergy issues and how this related to experiences of stress, mood and physical energy. One hundred and eight adults with physician-diagnosed food allergies completed an initial Internet survey followed by a 2-week Internet daily diary survey. The initial survey collected socio-demographic and food allergy information. The daily survey collected information about the participants' experiences of stress, mood, physical energy and food allergy issues during that day. Commonly experienced allergy issues included negative physical symptoms, higher food prices, anxiety about safety of food, trouble maintaining a healthy diet and anxiety/stress at social occasions. Furthermore, multilevel modelling analyses showed that stress and negative mood were significantly higher on days with more allergy issues. Older adults experienced lower positive mood and physical energy on days with more issues. This is the first study to incorporate near to real-time tracking to examine the frequency of food allergy issues and the implications for daily psychological functioning. Targeting the issues we identified could reduce stress in patients with food allergies and improve their overall quality of life.

  2. Beneficial Effect of Brewers' Yeast Extract on Daily Activity in a Murine Model of Chronic Fatigue Syndrome

    PubMed Central

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

    2006-01-01

    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-γ (IFN-γ) 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-γ 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. PMID:16550231

  3. Psychological control in daily parent-child interactions increases children's negative emotions.

    PubMed

    Aunola, Kaisa; Tolvanen, Asko; Viljaranta, Jaana; Nurmi, Jari-Erik

    2013-06-01

    The aim of the present study was to investigate the temporal dynamics between parental behaviors in daily interactions with their offspring, that is, affection and psychological control, and children's negative emotions. The participants were 152 Finnish families with a 6- to 7-year-old child. Children's negative emotions and parental affection and psychological control in interactions with their child were measured daily using diary questionnaires filled in by the mothers and fathers over 7 successive days. The results of multilevel modeling showed that psychological control applied by mothers and fathers in daily interactions with their child leads to an increase in negative emotions in the child. Parental affection in daily interactions with their child was not associated with the child's negative emotions. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  4. Accuracy evaluation of ClimGen weather generator and daily to hourly disaggregation methods in tropical conditions

    NASA Astrophysics Data System (ADS)

    Safeeq, Mohammad; Fares, Ali

    2011-12-01

    Daily and sub-daily weather data are often required for hydrological and environmental modeling. Various weather generator programs have been used to generate synthetic climate data where observed climate data are limited. In this study, a weather data generator, ClimGen, was evaluated for generating information on daily precipitation, temperature, and wind speed at four tropical watersheds located in Hawai`i, USA. We also evaluated different daily to sub-daily weather data disaggregation methods for precipitation, air temperature, dew point temperature, and wind speed at Mākaha watershed. The hydrologic significance values of the different disaggregation methods were evaluated using Distributed Hydrology Soil Vegetation Model. MuDRain and diurnal method performed well over uniform distribution in disaggregating daily precipitation. However, the diurnal method is more consistent if accurate estimates of hourly precipitation intensities are desired. All of the air temperature disaggregation methods performed reasonably well, but goodness-of-fit statistics were slightly better for sine curve model with 2 h lag. Cosine model performed better than random model in disaggregating daily wind speed. The largest differences in annual water balance were related to wind speed followed by precipitation and dew point temperature. Simulated hourly streamflow, evapotranspiration, and groundwater recharge were less sensitive to the method of disaggregating daily air temperature. ClimGen performed well in generating the minimum and maximum temperature and wind speed. However, for precipitation, it clearly underestimated the number of extreme rainfall events with an intensity of >100 mm/day in all four locations. ClimGen was unable to replicate the distribution of observed precipitation at three locations (Honolulu, Kahului, and Hilo). ClimGen was able to reproduce the distributions of observed minimum temperature at Kahului and wind speed at Kahului and Hilo. Although the weather

  5. Downscaling of daily precipitation using a hybrid model of Artificial Neural Network, Wavelet, and Quantile Mapping in Gharehsoo River Basin, Iran

    NASA Astrophysics Data System (ADS)

    Taie Semiromi, M.; Koch, M.

    2017-12-01

    Although linear/regression statistical downscaling methods are very straightforward and widely used, and they can be applied to a single predictor-predictand pair or spatial fields of predictors-predictands, the greatest constraint is the requirement of a normal distribution of the predictor and the predictand values, which means that it cannot be used to predict the distribution of daily rainfall because it is typically non-normal. To tacked with such a limitation, the current study aims to introduce a new developed hybrid technique taking advantages from Artificial Neural Networks (ANNs), Wavelet and Quantile Mapping (QM) for downscaling of daily precipitation for 10 rain-gauge stations located in Gharehsoo River Basin, Iran. With the purpose of daily precipitation downscaling, the study makes use of Second Generation Canadian Earth System Model (CanESM2) developed by Canadian Centre for Climate Modeling and Analysis (CCCma). Climate projections are available for three representative concentration pathways (RCPs) namely RCP 2.6, RCP 4.5 and RCP 8.5 for up to 2100. In this regard, 26 National Centers for Environmental Prediction (NCEP) reanalysis large-scale variables which have potential physical relationships with precipitation, were selected as candidate predictors. Afterwards, predictor screening was conducted using correlation, partial correlation and explained variance between predictors and predictand (precipitation). Depending on each rain-gauge station between two and three predictors were selected which their decomposed details (D) and approximation (A) obtained from discrete wavelet analysis were fed as inputs to the neural networks. After downscaling of daily precipitation, bias correction was conducted using quantile mapping. Out of the complete time series available, i.e. 1978-2005, two third of which namely 1978-1996 was used for calibration of QM and the reminder, i.e. 1997-2005 was considered for the validation. Result showed that the proposed

  6. 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…

  7. Impacts of Daily Bag Limit Reductions on Angler Effort in Wisconsin Walleye Lakes

    USGS Publications Warehouse

    Beard, T.D.; Cox, S.P.; Carpenter, S.R.

    2003-01-01

    Angler effort is an important factor affecting recreational fisheries. However, angler responses are rarely incorporated into recreational fisheries regulations or predictions. Few have attempted to examine how daily bag limit regulations affect total angling pressure and subsequent stock densities. Our paper develops a theoretical basis for predicting angler effort and harvest rate based on stock densities and bag limit regulations. We examined data from a management system that controls the total exploitation of walleyes Sander vitreus (formerly Stizostedion vitreum) in northern Wisconsin lakes and compared these empirical results with the predictions from a theoretical effort and harvest rate response model. The data indicated that higher general angler effort occurs on lakes regulated with a 5-walleye daily limit than on lakes regulated with either a 2- or 3-walleye daily limit. General walleye catch rates were lower on lakes with a 5-walleye limit than on lakes with either a 2- or 3-walleye daily limit. An effort response model predicted a logarithmic relationship between angler effort and adult walleye density and that an index of attractiveness would be greater on lakes with high bag limits. Predictions from the harvest rate model with constant walleye catchability indicated that harvest rates increased nonlinearly with increasing density. When the effort model was fitted to data from northern Wisconsin, we found higher lake attractiveness at 5-walleye-limit lakes. We conclude that different groups of anglers respond differently to bag limit changes and that reliance on daily bag limits may not be sufficient to maintain high walleye densities in some lakes in this region.

  8. Routine assistance to parents: effects on daily mood and other stressors.

    PubMed

    Savla, Jyoti; Almeida, David M; Davey, Adam; Zarit, Steven H

    2008-05-01

    The present study examined the association of providing assistance to older parents amid everyday circumstances and short-term psychological consequences for adult children providing assistance. We explored this association using 824 daily diary interviews of 119 adult children providing assistance in the National Study of Daily Experiences by using a left-censored random effects tobit regression model that accounted for the clustered data and floor effects in reported psychological distress. Psychological distress was higher on days adult children provided assistance to their parent (b = 0.88, p <.05) even after we controlled for situational variables such as time spent on daily paid work, time spent on leisure activities, and assistance provided to individuals other than parents. Demographic and psychosocial variables such as having resident children (b = 2.14, p <.01), less education (b = -0.54, p <.05), and neuroticism (b = 2.08, p <.05), also predicted daily psychological distress. Even after we controlled for within-person (daily situational variables) and between-person factors (background characteristics), the act of providing assistance itself had immediate associations with daily mood for helpers, particularly for those with fewer resources and greater demands on time. Feasibility and success of programs that provide respite and relief services to older adults and their children should be assessed in light of daily living.

  9. Psychometric schizotypy predicts psychotic-like, paranoid, and negative symptoms in daily life.

    PubMed

    Barrantes-Vidal, Neus; Chun, Charlotte A; Myin-Germeys, Inez; Kwapil, Thomas R

    2013-11-01

    Positive and negative schizotypy exhibit differential patterns of impairment in social relations, affect, and functioning in daily life. However, studies have not examined the association of schizotypy with real-world expression of psychotic-like, paranoid, and negative symptoms. The present study employed experience-sampling methodology (ESM) to assess positive and negative schizotypy in daily life in a nonclinical sample of 206 Spanish young adults. Participants were prompted randomly 8 times daily for 1 week to complete assessments of their current symptoms and experiences. Positive schizotypy was associated with psychotic-like and paranoid symptoms in daily life. Negative schizotypy was associated with a subset of these symptoms and with negative symptoms in daily life. Momentary stress was associated with psychotic-like and paranoid symptoms, but only for those high in positive schizotypy. Social stress predicted momentary psychotic-like symptoms in both positive and negative schizotypy. Time-lagged analyses indicated that stress at the preceding signal predicted psychotic-like symptoms at the current assessment, but only for individuals high in positive schizotypy. The results are consistent with models linking stress sensitivity with the experience of psychotic symptoms. The findings provide cross-cultural support for the multidimensional model of schizotypy and schizophrenia. Furthermore, the findings demonstrate that ESM is an effective method for predicting the experience of psychotic-like symptoms, as well as their precursors, in daily life. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  10. Combination of radar and daily precipitation data to estimate meaningful sub-daily point precipitation extremes

    NASA Astrophysics Data System (ADS)

    Pegram, Geoff; Bardossy, Andras; Sinclair, Scott

    2017-04-01

    The use of radar measurements for the space time estimation of precipitation has for many decades been a central topic in hydro-meteorology. In this presentation we are interested specifically in daily and sub-daily extreme values of precipitation at gauged or ungauged locations which are important for design. The purpose of the presentation is to develop a methodology to combine daily precipitation observations and radar measurements to estimate sub-daily extremes at point locations. Radar data corrected using precipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities of correcting systematic errors using the daily observations are investigated. Observed gauged daily amounts are interpolated to un-sampled points and subsequently disaggregated using the sub-daily values obtained by the radar. Different corrections based on the spatial variability and the sub-daily entropy of scaled rainfall distributions are used to provide unbiased corrections of short duration extremes. In addition, a statistical procedure not based on a matching day by day correction is tested. In this last procedure, as we are only interested in rare extremes, low to medium values of rainfall depth were neglected leaving 12 days of ranked daily maxima in each set per year, whose sum typically comprises about 50% of each annual rainfall total. The sum of these 12 day maxima is first interpolated using a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbour procedure. The daily sums are then disaggregated by using the relative values of the biggest 12 radar based days in each year. Of course, the timings of radar and gauge maxima can be different, so the new method presented here uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract the maxima of sub-hourly through to daily rainfall. The methodologies were tested in South Africa, where an S-band radar operated

  11. Computation of rainfall erosivity from daily precipitation amounts.

    PubMed

    Beguería, Santiago; Serrano-Notivoli, Roberto; Tomas-Burguera, Miquel

    2018-10-01

    Rainfall erosivity is an important parameter in many erosion models, and the EI30 defined by the Universal Soil Loss Equation is one of the best known erosivity indices. One issue with this and other erosivity indices is that they require continuous breakpoint, or high frequency time interval, precipitation data. These data are rare, in comparison to more common medium-frequency data, such as daily precipitation data commonly recorded by many national and regional weather services. Devising methods for computing estimates of rainfall erosivity from daily precipitation data that are comparable to those obtained by using high-frequency data is, therefore, highly desired. Here we present a method for producing such estimates, based on optimal regression tools such as the Gamma Generalised Linear Model and universal kriging. Unlike other methods, this approach produces unbiased and very close to observed EI30, especially when these are aggregated at the annual level. We illustrate the method with a case study comprising more than 1500 high-frequency precipitation records across Spain. Although the original records have a short span (the mean length is around 10 years), computation of spatially-distributed upscaling parameters offers the possibility to compute high-resolution climatologies of the EI30 index based on currently available, long-span, daily precipitation databases. Copyright © 2018 Elsevier B.V. All rights reserved.

  12. Combination of radar and daily precipitation data to estimate meaningful sub-daily point precipitation extremes

    NASA Astrophysics Data System (ADS)

    Bárdossy, András; Pegram, Geoffrey

    2017-01-01

    The use of radar measurements for the space time estimation of precipitation has for many decades been a central topic in hydro-meteorology. In this paper we are interested specifically in daily and sub-daily extreme values of precipitation at gauged or ungauged locations which are important for design. The purpose of the paper is to develop a methodology to combine daily precipitation observations and radar measurements to estimate sub-daily extremes at point locations. Radar data corrected using precipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities of correcting systematic errors using the daily observations are investigated. Observed gauged daily amounts are interpolated to unsampled points and subsequently disaggregated using the sub-daily values obtained by the radar. Different corrections based on the spatial variability and the subdaily entropy of scaled rainfall distributions are used to provide unbiased corrections of short duration extremes. Additionally a statistical procedure not based on a matching day by day correction is tested. In this last procedure as we are only interested in rare extremes, low to medium values of rainfall depth were neglected leaving a small number of L days of ranked daily maxima in each set per year, whose sum typically comprises about 50% of each annual rainfall total. The sum of these L day maxima is first iterpolated using a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbour procedure. The daily sums are then disaggregated by using the relative values of the biggest L radar based days. Of course, the timings of radar and gauge maxima can be different, so the method presented here uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract the maxima of sub-hourly through to daily rainfall. The methodologies were tested in South Africa, where an S-band radar operated relatively continuously at

  13. 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.

  14. Daily Deviations in Anger, Guilt, and Sympathy: A Developmental Diary Study of Aggression.

    PubMed

    Colasante, Tyler; Zuffianò, Antonio; Malti, Tina

    2016-11-01

    With a diary study of 4- and 8-year-olds, we tested the association between daily deviations in anger and aggressive behavior, and whether this link was moderated by feelings of guilt and sympathy. Caregivers reported their children's anger and aggression for 10 consecutive days (470 records; N = 80, 53 % girls). To calculate daily anger deviations from average anger levels, we subtracted each child's average anger score (i.e., across 10 days) from his/her daily anger scores. Children reported their guilty feelings in response to vignettes depicting intentional harm, as well as their dispositional sympathy levels. Multilevel modeling indicated that within-child spikes in daily anger were associated with more aggression, above and beyond between-child differences in average anger levels. However, this association was weaker for children who reported higher levels of guilt. Sympathy did not moderate the anger-aggression link. We discuss potential implications for affective-developmental models of aggression and interventions that target anger-related aggression.

  15. 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.

  16. A comparison of methods to estimate future sub-daily design rainfall

    NASA Astrophysics Data System (ADS)

    Li, J.; Johnson, F.; Evans, J.; Sharma, A.

    2017-12-01

    Warmer temperatures are expected to increase extreme short-duration rainfall due to the increased moisture-holding capacity of the atmosphere. While attention has been paid to the impacts of climate change on future design rainfalls at daily or longer time scales, the potential changes in short duration design rainfalls have been often overlooked due to the limited availability of sub-daily projections and observations. This study uses a high-resolution regional climate model (RCM) to predict the changes in sub-daily design rainfalls for the Greater Sydney region in Australia. Sixteen methods for predicting changes to sub-daily future extremes are assessed based on different options for bias correction, disaggregation and frequency analysis. A Monte Carlo cross-validation procedure is employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It is found that bias correction significantly improves the accuracy of the design rainfall estimated for the current climate. For 1 h events, bias correcting the hourly annual maximum rainfall simulated by the RCM produces design rainfall closest to observations, whereas for multi-hour events, disaggregating the daily rainfall total is recommended. This suggests that the RCM fails to simulate the observed multi-duration rainfall persistence, which is a common issue for most climate models. Despite the significant differences in the estimated design rainfalls between different methods, all methods lead to an increase in design rainfalls across the majority of the study region.

  17. 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.

  18. Estimating wheat and maize daily evapotranspiration using artificial neural network

    NASA Astrophysics Data System (ADS)

    Abrishami, Nazanin; Sepaskhah, Ali Reza; Shahrokhnia, Mohammad Hossein

    2018-02-01

    In this research, artificial neural network (ANN) is used for estimating wheat and maize daily standard evapotranspiration. Ten ANN models with different structures were designed for each crop. Daily climatic data [maximum temperature (T max), minimum temperature (T min), average temperature (T ave), maximum relative humidity (RHmax), minimum relative humidity (RHmin), average relative humidity (RHave), wind speed (U 2), sunshine hours (n), net radiation (Rn)], leaf area index (LAI), and plant height (h) were used as inputs. For five structures of ten, the evapotranspiration (ETC) values calculated by ETC = ET0 × K C equation (ET0 from Penman-Monteith equation and K C from FAO-56, ANNC) were used as outputs, and for the other five structures, the ETC values measured by weighing lysimeter (ANNM) were used as outputs. In all structures, a feed forward multiple-layer network with one or two hidden layers and sigmoid transfer function and BR or LM training algorithm was used. Favorite network was selected based on various statistical criteria. The results showed the suitable capability and acceptable accuracy of ANNs, particularly those having two hidden layers in their structure in estimating the daily evapotranspiration. Best model for estimation of maize daily evapotranspiration is «M»ANN1 C (8-4-2-1), with T max, T min, RHmax, RHmin, U 2, n, LAI, and h as input data and LM training rule and its statistical parameters (NRMSE, d, and R2) are 0.178, 0.980, and 0.982, respectively. Best model for estimation of wheat daily evapotranspiration is «W»ANN5 C (5-2-3-1), with T max, T min, Rn, LAI, and h as input data and LM training rule, its statistical parameters (NRMSE, d, and R 2) are 0.108, 0.987, and 0.981 respectively. In addition, if the calculated ETC used as the output of the network for both wheat and maize, higher accurate estimation was obtained. Therefore, ANN is suitable method for estimating evapotranspiration of wheat and maize.

  19. 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.

  20. Nicotine Metabolism in Young Adult Daily Menthol and Nonmenthol Smokers

    PubMed Central

    Pokhrel, Pallav; Herzog, Thaddeus A.; Pagano, Ian S.; Franke, Adrian A.; Clanton, Mark S.; Alexander, Linda A.; Trinidad, Dennis R.; Sakuma, Kari-Lyn K.; Johnson, Carl A.; Moolchan, Eric T.

    2016-01-01

    Introduction: Menthol cigarette smoking may increase the risk for tobacco smoke exposure and inhibit nicotine metabolism in the liver. Nicotine metabolism is primarily mediated by the enzyme CYP2A6 and the nicotine metabolite ratio (NMR = trans 3′ hydroxycotinine/cotinine) is a phenotypic proxy for CYP2A6 activity. No studies have examined differences in this biomarker among young adult daily menthol and nonmenthol smokers. This study compares biomarkers of tobacco smoke exposure among young adult daily menthol and nonmenthol smokers. Methods: Saliva cotinine and carbon monoxide were measured in a multiethnic sample of daily smokers aged 18–35 (n = 186). Nicotine, cotinine, the cotinine/cigarette per day ratio, trans 3′ hydroxycotinine, the NMR, and expired carbon monoxide were compared. Results: The geometric means for nicotine, cotinine, and the cotinine/cigarette per day ratio did not significantly differ between menthol and nonmenthol smokers. The NMR was significantly lower among menthol compared with nonmenthol smokers after adjusting for race/ethnicity, gender, body mass index, and cigarette smoked per day (0.19 vs. 0.24, P = .03). White menthol smokers had significantly higher cotinine/cigarettes per day ratio than white nonmenthol smokers in the adjusted model. White menthol smokers had a lower NMR in the unadjusted model (0.24 vs. 0.31, P = .05) and the differences remained marginally significant in the adjusted model (0.28 vs. 0.34, P = .06). We did not observe these differences in Native Hawaiians and Filipinos. Conclusions: Young adult daily menthol smokers have slower rates of nicotine metabolism than nonmenthol smokers. Studies are needed to determine the utility of this biomarker for smoking cessation treatment assignments. PMID:25995160

  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. Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange

    NASA Astrophysics Data System (ADS)

    Takaishi, Tetsuya

    2018-06-01

    The realized stochastic volatility model has been introduced to estimate more accurate volatility by using both daily returns and realized volatility. The main advantage of the model is that no special bias-correction factor for the realized volatility is required a priori. Instead, the model introduces a bias-correction parameter responsible for the bias hidden in realized volatility. We empirically investigate the bias-correction parameter for realized volatilities calculated at various sampling frequencies for six stocks on the Tokyo Stock Exchange, and then show that the dynamic behavior of the bias-correction parameter as a function of sampling frequency is qualitatively similar to that of the Hansen-Lunde bias-correction factor although their values are substantially different. Under the stochastic diffusion assumption of the return dynamics, we investigate the accuracy of estimated volatilities by examining the standardized returns. We find that while the moments of the standardized returns from low-frequency realized volatilities are consistent with the expectation from the Gaussian variables, the deviation from the expectation becomes considerably large at high frequencies. This indicates that the realized stochastic volatility model itself cannot completely remove bias at high frequencies.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  4. Daily propranolol prevents prolonged mobilization of hematopoietic progenitor cells in a rat model of lung contusion, hemorrhagic shock, and chronic stress.

    PubMed

    Bible, Letitia E; Pasupuleti, Latha V; Gore, Amy V; Sifri, Ziad C; Kannan, Kolenkode B; Mohr, Alicia M

    2015-09-01

    Propranolol has been shown previously to decrease the mobilization of hematopoietic progenitor cells (HPCs) after acute injury in rodent models; however, this acute injury model does not reflect the prolonged period of critical illness after severe trauma. Using our novel lung contusion/hemorrhagic shock/chronic restraint stress model, we hypothesize that daily administration of propranolol will decrease prolonged mobilization of HPCs without worsening lung healing. Male Sprague-Dawley rats underwent 6 days of restraint stress after undergoing lung contusion or lung contusion/hemorrhagic shock. Restraint stress consisted of a daily 2-hour period of restraint interrupted every 30 minutes by alarms and repositioning. Each day after the period of restraint stress, the rats received intraperitoneal propranolol (10 mg/kg). On day 7, peripheral blood was analyzed for granulocyte-colony stimulating factor (G-CSF) and stromal cell-derived factor 1 via enzyme-linked immunosorbent assay and for mobilization of HPCs using c-kit and CD71 flow cytometry. The lungs were examined histologically to grade injury. Seven days after lung contusion and lung contusion/hemorrhagic shock, the addition of chronic restraint stress significantly increased the mobilization of HPC, which was associated with persistently increased levels of G-CSF and increased lung injury scores. The addition of propranolol to lung contusion/chronic restraint stress and lung contusion/hemorrhagic shock/chronic restraint stress models greatly decreased HPC mobilization and restored G-CSF levels to that of naïve animals without worsening lung injury scores. The daily administration of propranolol after both lung contusion and lung contusion/hemorrhagic shock subjected to chronic restraint stress decreased the prolonged mobilization of HPC from the bone marrow and decreased plasma G-CSF levels. Despite the decrease in mobilization of HPC, lung healing did not worsen. Alleviating chronic stress with propranolol

  5. On the impacts of computing daily temperatures as the average of the daily minimum and maximum temperatures

    NASA Astrophysics Data System (ADS)

    Villarini, Gabriele; Khouakhi, Abdou; Cunningham, Evan

    2017-12-01

    Daily temperature values are generally computed as the average of the daily minimum and maximum observations, which can lead to biases in the estimation of daily averaged values. This study examines the impacts of these biases on the calculation of climatology and trends in temperature extremes at 409 sites in North America with at least 25 years of complete hourly records. Our results show that the calculation of daily temperature based on the average of minimum and maximum daily readings leads to an overestimation of the daily values of 10+ % when focusing on extremes and values above (below) high (low) thresholds. Moreover, the effects of the data processing method on trend estimation are generally small, even though the use of the daily minimum and maximum readings reduces the power of trend detection ( 5-10% fewer trends detected in comparison with the reference data).

  6. 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

  7. Daily affect variability and context-specific alcohol consumption.

    PubMed

    Mohr, Cynthia D; Arpin, Sarah; McCabe, Cameron T

    2015-11-01

    Research explored the effects of variability in negative and positive affect on alcohol consumption, specifying daily fluctuation in affect as a critical form of emotion dysregulation. Using daily process methodology allows for a more objective calculation of affect variability relative to traditional self-reports. The present study models within-person negative and positive affect variabilities as predictors of context-specific consumption (i.e. solitary vs. social drinking), controlling for mean levels of affect. A community sample of moderate-to-heavy drinkers (n = 47; 49% women) from a US metropolitan area reported on affect and alcohol consumption thrice daily for 30 days via a handheld electronic interviewer. Within-person affect variability was calculated using daily standard deviations in positive and negative affect. Within person, greater negative and positive variabilities are related to greater daily solitary and social consumption. Across study days, mean levels of negative and positive affect variabilities related to greater social consumption between persons; yet, aggregated negative affect variability was related to less solitary consumption. Results affirm affect variability as a unique predictor of alcohol consumption, independent of mean affect levels. Yet, it is important to differentiate social context of consumption, as well as type of affect variability, particularly at the between-person level. These distinctions help clarify inconsistencies in the self-medication literature regarding associations between average levels of affect and consumption. Importantly, consistent within-person relationships for both variabilities support arguments that both negative and positive affect variabilities are detrimental and reflect an inability to regulate emotional experience. © 2015 Australasian Professional Society on Alcohol and other Drugs.

  8. Sex in Its Daily Relational Context.

    PubMed

    Dewitte, Marieke; Van Lankveld, Jacques; Vandenberghe, Sjouke; Loeys, Tom

    2015-12-01

    The present study measured the daily correlates of sexual behavior in an ecologically valid context by relying on a daily diary approach. Examining the dyadic and multicomponent nature of sexual behavior is essential to create valid models of sexual responding that are better aligned with the day-to-day context of having sex in a relationship. During 3 weeks, heterosexual couples completed, two times a day, an electronic diary to report on mood, own and perceived partner behavior, relational feelings (in the evening), sexual activity, physical intimacy, and masturbation (in the morning). This design allowed testing bidirectional temporal associations between daily context and different types of sexual behavior. Positive mood, displays of positive partner behavior, perceived positive partner behavior, and positive relational feelings predicted more sexual activity and intimacy in men, which then further increased their positive mood, perceived positive partner behavior, and positive feelings about the relationship on the following day. Women showed a similar pattern of predictors regarding sexual activity as men, though the effect of sexual behavior on next-day feelings and behavior was more relationship-oriented rather than affecting personal mood. Intimacy was related to almost all daily variables in women, but related only to own and perceived positive partner behavior and positive relational feelings the next day. Several partner effects also reached significance, and these were more influential in predicting male than female intimacy. Solitary sexual activity showed a different pattern of results than dyadic sexual activity, with men experiencing masturbation as negatively in the context of their relationship. These results confirm the regulatory function of sex and intimacy in maintaining a positive relational climate and indicate that the quality of the everyday relational context is important to get partners in the mood to act in a sexual way. © 2015

  9. Routine Assistance to Parents: Effects on Daily Mood and Other Stressors

    PubMed Central

    Savla, Jyoti; Almeida, David M.; Davey, Adam; Zarit, Steven H.

    2012-01-01

    Objectives The present study examines the association of providing assistance to older parents amidst everyday circumstances and short-term psychological consequences for adult children providing assistance. Methods We explore this association using 824 daily diary interviews of 119 adult children providing assistance in the National Study of Daily Experiences by using a left-censored random effects tobit regression model that accounts for the clustered data and floor effects in reported psychological distress. Results Psychological distress was higher on days adult children provided assistance to their parent (b=0.88, p<0.05) even after controlling for situational variables such as time spent on daily paid work, leisure activities and assistance provided to individuals other than parents. Demographic and psychosocial variables such as having resident children (b=2.14, p<0.01), education (b=−0.54, p<0.05) and neuroticism (b=2.08, p<0.05) also predicted daily psychological distress. Discussion Even after controlling for within-person (daily situational variables) and between-person factors (background characteristics), the act of providing assistance itself has immediate associations with daily mood for helpers, particularly for those with fewer resources and greater demands on time. Feasibility and success of programs that provide respite and relief services to older adults and their children should be assessed in light of daily living. PMID:18559690

  10. ONCE DAILY RISPERIDONE IN TREATMENT OF SCHIZOPHRENIA

    PubMed Central

    Agarwal, Vivek; Chadda, Rakesh K.

    2001-01-01

    Forty four schizophrenic patients were randomly assigned to receive risperidone in 4-8 mg doses either once daily or twice daily for 8 weeks. An open trial was conducted to determine the efficacy of once daily administration of risperidone as compared to twice daily administration. Assessment were done on Positive and Negative Syndrome Scale (PANSS) and Clinical Global Impression (CGI) scale Eighty two percent of the once daily patients and 79% of the twice daily patients showed a significant treatment response. No significant differences were observed between the two groups in response pattern and adverse effects at the end point. Risperidone given once daily was as effective as twice daily administration. PMID:21407835

  11. Investigating daily fatigue scores during two-week offshore day shifts.

    PubMed

    Riethmeister, Vanessa; Bültmann, Ute; Gordijn, Marijke; Brouwer, Sandra; de Boer, Michiel

    2018-09-01

    This study examined daily scores of fatigue and circadian rhythm markers over two-week offshore day shift periods. A prospective cohort study among N = 60 offshore day-shift workers working two-week offshore shifts was conducted. Offshore day shifts lasted from 07:00 - 19:00 h. Fatigue was measured objectively with pre- and post-shift scores of the 3-minute psychomotor vigilance tasks (PVT-B) parameters (reaction times, number of lapses, errors and false starts) and subjectively with pre- and post-shift Karolinska Sleepiness Scale (KSS) ratings. Evening saliva samples were collected on offshore days 2,7 and 13 to measure circadian rhythm markers such as dim-light melatonin onset times and cortisol. Generalized and linear mixed model analyses were used to examine daily fatigue scores over time. Complete data from N = 42 offshore day shift workers was analyzed. Daily parameters of objective fatigue, PVT-B scores (reaction times, average number of lapses, errors and false starts), remained stable over the course of the two-week offshore day shifts. Daily subjective post-shift fatigue scores significantly increased over the course of the two-week offshore shifts. Each day offshore was associated with an increased post-shift subjective fatigue score of 0.06 points (95%CI: .03 - .09 p < .001). No significant statistical differences in subjective pre-shift fatigue scores were found. Neither a circadian rhythm phase shift of melatonin nor an effect on the pattern and levels of evening cortisol was found. Daily parameters of objective fatigue scores remained stable over the course of the two-week offshore day shifts. Daily subjective post-shift fatigue scores significantly increased over the course of the two-week offshore shifts. No significant changes in circadian rhythm markers were found. Increased post-shift fatigue scores, especially during the last days of an offshore shift, should be considered and managed in (offshore) fatigue risk management programs and fatigue

  12. Daily Stress, Coping, and Negative and Positive Affect in Depression: Complex Trigger and Maintenance Patterns.

    PubMed

    Dunkley, David M; Lewkowski, Maxim; Lee, Ihno A; Preacher, Kristopher J; Zuroff, David C; Berg, Jody-Lynn; Foley, J Elizabeth; Myhr, Gail; Westreich, Ruta

    2017-05-01

    Major depressive disorder is characterized by emotional dysfunction, but mood states in daily life are not well understood. This study examined complex explanatory models of daily stress and coping mechanisms that trigger and maintain daily negative affect and (lower) positive affect in depression. Sixty-three depressed patients completed perfectionism measures, and then completed daily questionnaires of stress appraisals, coping, and affect for 7 consecutive days. Multilevel structural equation modeling (MSEM) demonstrated that, across many stressors, when the typical individual with depression perceives more criticism than usual, he/she uses more avoidant coping and experiences higher event stress than usual, and this is connected to daily increases in negative affect as well as decreases in positive affect. In parallel, results showed that perceived control, less avoidant coping, and problem-focused coping commonly operate together when daily positive affect increases. MSEM also showed that avoidant coping tendencies and ongoing stress, in combination, explain why people with depression and higher self-critical perfectionism maintain daily negative affect and lower positive affect. These findings advance a richer and more detailed understanding of specific stress and coping patterns to target in order to more effectively accomplish the two predominant therapy goals of decreasing patients' distress and strengthening resilience. Copyright © 2016. Published by Elsevier Ltd.

  13. Seasonal and daily snowmelt runoff estimates utilizing satellite data. [Wind River Mountains, Wyoming

    NASA Technical Reports Server (NTRS)

    1980-01-01

    Methods using snowcovered area to update seasonal forecasts as snowmelt progresses are also being used in quasi-operational situations. The input of snowcovered area to snowmelt models for short term perdictions was attempted in two ways; namely, the modification of existing hydrologic models and/or the use of models that were specifically designed to use snowcovered area. A daily snowmelt runoff model was used with LANDSAT data to simulate discharge on remote basins in the Wind River Mountains of Wyoming. Daily predicted and actual flows compare closely, and, summarized over the entire snowmelt season (April 1 - September 30), the average difference is only three percent. The model and snowcovered area data are currently being tested on additional watersheds to determine the method's transferability.

  14. Negative affective spillover from daily events predicts early response to cognitive therapy for depression.

    PubMed

    Cohen, Lawrence H; Gunthert, Kathleen C; Butler, Andrew C; Parrish, Brendt P; Wenze, Susan J; Beck, Judith S

    2008-12-01

    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 compute each patient's within-day relationship between daily stressors and daily NA (within-day reactivity), as well as the relationship between daily stressors and next-day NA (next-day reactivity; affective spillover). In growth model analyses, the authors evaluated the predictive role of patients' NA reactivity in their early (Sessions 1-4) and late (Sessions 5-12) response to CT. Within-day NA reactivity did not predict early or late response to CT. However, next-day reactivity predicted early response to CT, such that patients who had greater NA spillover in response to negative events had a slower rate of symptom change during the first 4 sessions. Affective spillover did not influence later response to CT. The findings suggest that depressed patients who have difficulty bouncing back the next day from their NA reactions to a relative increase in daily negative events will respond less quickly to the early sessions of CT.

  15. Depression Among Non-Daily Smokers Compared to Daily Smokers and Never-Smokers in the United States: An Emerging Problem.

    PubMed

    Weinberger, Andrea H; Gbedemah, Misato; Wall, Melanie M; Hasin, Deborah S; Zvolensky, Michael J; Chaiton, Michael; Goodwin, Renee D

    2017-09-01

    Depression is strongly associated with daily smoking. Yet, little is known about the association between depression and non-daily smoking. The aim of this study was to investigate the prevalence of past-year depression and changes in past-year depression over time among non-daily smokers, compared to daily smokers and never-smokers, overall and stratified by age, gender, income, nicotine dependence, and cigarettes per day. Data were drawn from the National Household Survey on Drug Use (NSDUH), an annual cross-sectional study of persons aged 12 and over (total study population N = 496 805). The prevalence of past-year depression was examined annually among non-daily smokers, daily smokers, and never-smokers from 2005 to 2013 using linear trend analyses. Past-year depression was common among 10.10% of non-daily smokers, common among 10.78% of daily smokers, and 5.51% of never-smokers in 2013. The prevalence of depression increased from 2005 to 2013 among non-daily smokers (9.06% vs. 10.10%; p = .034) while there was no significant change in depression over time among daily smokers. Increases in depression among non-daily smokers occurred for both men and women and appear most pronounced youth, those smoking fewer cigarettes, and those without nicotine dependence. The prevalence of depression among non-daily smokers was equivalent to daily smokers and nearly twice that among nonsmokers. Depression appears to be increasing over time in non-daily smokers especially among youth, those who smoke less, and those without nicotine dependence. More work on the mental health of non-daily smokers is needed as this is an increasing and understudied group. This is the first study to investigate changes in the prevalence of depression among non-daily smokers compared to daily smokers and never-smokers over the past decade in a nationally representative sample of the United States. The results suggest an increase in depression among non-daily smokers over time that did not

  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. Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

    NASA Astrophysics Data System (ADS)

    Sommer, Philipp; Kaplan, Jed

    2016-04-01

    Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

  18. Estimation of body temperature rhythm based on heart activity parameters in daily life.

    PubMed

    Sooyoung Sim; Heenam Yoon; Hosuk Ryou; Kwangsuk Park

    2014-01-01

    Body temperature contains valuable health related information such as circadian rhythm and menstruation cycle. Also, it was discovered from previous studies that body temperature rhythm in daily life is related with sleep disorders and cognitive performances. However, monitoring body temperature with existing devices during daily life is not easy because they are invasive, intrusive, or expensive. Therefore, the technology which can accurately and nonintrusively monitor body temperature is required. In this study, we developed body temperature estimation model based on heart rate and heart rate variability parameters. Although this work was inspired by previous research, we originally identified that the model can be applied to body temperature monitoring in daily life. Also, we could find out that normalized Mean heart rate (nMHR) and frequency domain parameters of heart rate variability showed better performance than other parameters. Although we should validate the model with more number of subjects and consider additional algorithms to decrease the accumulated estimation error, we could verify the usefulness of this approach. Through this study, we expect that we would be able to monitor core body temperature and circadian rhythm from simple heart rate monitor. Then, we can obtain various health related information derived from daily body temperature rhythm.

  19. Harmful effects behind the daily supplementation of a fixed vegetarian blend in the rat model.

    PubMed

    Bonamassa, Barbara; Canistro, Donatella; Sapone, Andrea; Vivarelli, Fabio; Vornoli, Andrea; Longo, Vincenzo; Paolini, Moreno

    2016-11-01

    Fruit and vegetables (FV) have long been considered a panacea against major chronic diseases, including cancer. However, there is no convincing epidemiological, clinical or experimental evidence supporting FV chemopreventive ability. A daily mono-supplementation of lyophilized onion, tomato, peach, black grape or lettuce was compared with the daily combined administration of the same FV (5 a day-like diet). Ten days post-treatment, the phase-I/II xenobiotic metabolizing and antioxidant enzyme activities, protein and mRNA levels were investigated. As a marker of oxidative stress, the level of hydroperoxides was measured in rat serum samples. Here we show that a blend of FV orally administered to rats not only potentially manipulates metabolism but also disrupts systemic oxidative homeostasis. A daily combination of the five servings remarkably down-regulates the catalytic activity, protein and mRNA levels of a cohort of hepatic metabolizing enzymes, suggesting a possible depressed clearance upon exposure to ubiquitous carcinogens. Strikingly, we observed an impairment of antioxidant enzymes with a boost in systemic hydroperoxide levels. Our study identifies new potential factors of cancer risk connected with the persistent consumption of fixed servings of FV, suggesting that dietary guidance should rely on a "daily diversification" of FV. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Multi-site Stochastic Simulation of Daily Streamflow with Markov Chain and KNN Algorithm

    NASA Astrophysics Data System (ADS)

    Mathai, J.; Mujumdar, P.

    2017-12-01

    A key focus of this study is to develop a method which is physically consistent with the hydrologic processes that can capture short-term characteristics of daily hydrograph as well as the correlation of streamflow in temporal and spatial domains. In complex water resource systems, flow fluctuations at small time intervals require that discretisation be done at small time scales such as daily scales. Also, simultaneous generation of synthetic flows at different sites in the same basin are required. We propose a method to equip water managers with a streamflow generator within a stochastic streamflow simulation framework. The motivation for the proposed method is to generate sequences that extend beyond the variability represented in the historical record of streamflow time series. The method has two steps: In step 1, daily flow is generated independently at each station by a two-state Markov chain, with rising limb increments randomly sampled from a Gamma distribution and the falling limb modelled as exponential recession and in step 2, the streamflow generated in step 1 is input to a nonparametric K-nearest neighbor (KNN) time series bootstrap resampler. The KNN model, being data driven, does not require assumptions on the dependence structure of the time series. A major limitation of KNN based streamflow generators is that they do not produce new values, but merely reshuffle the historical data to generate realistic streamflow sequences. However, daily flow generated using the Markov chain approach is capable of generating a rich variety of streamflow sequences. Furthermore, the rising and falling limbs of daily hydrograph represent different physical processes, and hence they need to be modelled individually. Thus, our method combines the strengths of the two approaches. We show the utility of the method and improvement over the traditional KNN by simulating daily streamflow sequences at 7 locations in the Godavari River basin in India.

  1. Bursts of Self-Conscious Emotions in the Daily Lives of Emerging Adults.

    PubMed

    Conroy, David E; Ram, Nilam; Pincus, Aaron L; Rebar, Amanda L

    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.

  2. 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

  3. Validation of daily increments periodicity in otoliths of spotted gar

    USGS Publications Warehouse

    Snow, Richard A.; Long, James M.; Frenette, Bryan D.

    2017-01-01

    Accurate age and growth information is essential in successful management of fish populations and for understanding early life history. We validated daily increment deposition, including the timing of first ring formation, for spotted gar (Lepisosteus oculatus) through 127 days post hatch. Fry were produced from hatchery-spawned specimens, and up to 10 individuals per week were sacrificed and their otoliths (sagitta, lapillus, and asteriscus) removed for daily age estimation. Daily age estimates for all three otolith pairs were significantly related to known age. The strongest relationships existed for measurements from the sagitta (r2 = 0.98) and the lapillus (r2 = 0.99) with asteriscus (r2 = 0.95) the lowest. All age prediction models resulted in a slope near unity, indicating that ring deposition occurred approximately daily. Initiation of ring formation varied among otolith types, with deposition beginning 3, 7, and 9 days for the sagitta, lapillus, and asteriscus, respectively. Results of this study suggested that otoliths are useful to estimate daily age of spotted gar juveniles; these data may be used to back calculate hatch dates, estimate early growth rates, and correlate with environmental factor that influence spawning in wild populations. is early life history information will be valuable in better understanding the ecology of this species. 

  4. Nicotine Metabolism in Young Adult Daily Menthol and Nonmenthol Smokers.

    PubMed

    Fagan, Pebbles; Pokhrel, Pallav; Herzog, Thaddeus A; Pagano, Ian S; Franke, Adrian A; Clanton, Mark S; Alexander, Linda A; Trinidad, Dennis R; Sakuma, Kari-Lyn K; Johnson, Carl A; Moolchan, Eric T

    2016-04-01

    Menthol cigarette smoking may increase the risk for tobacco smoke exposure and inhibit nicotine metabolism in the liver. Nicotine metabolism is primarily mediated by the enzyme CYP2A6 and the nicotine metabolite ratio (NMR = trans 3' hydroxycotinine/cotinine) is a phenotypic proxy for CYP2A6 activity. No studies have examined differences in this biomarker among young adult daily menthol and nonmenthol smokers. This study compares biomarkers of tobacco smoke exposure among young adult daily menthol and nonmenthol smokers. Saliva cotinine and carbon monoxide were measured in a multiethnic sample of daily smokers aged 18-35 (n = 186). Nicotine, cotinine, the cotinine/cigarette per day ratio, trans 3' hydroxycotinine, the NMR, and expired carbon monoxide were compared. The geometric means for nicotine, cotinine, and the cotinine/cigarette per day ratio did not significantly differ between menthol and nonmenthol smokers. The NMR was significantly lower among menthol compared with nonmenthol smokers after adjusting for race/ethnicity, gender, body mass index, and cigarette smoked per day (0.19 vs. 0.24, P = .03). White menthol smokers had significantly higher cotinine/cigarettes per day ratio than white nonmenthol smokers in the adjusted model. White menthol smokers had a lower NMR in the unadjusted model (0.24 vs. 0.31, P = .05) and the differences remained marginally significant in the adjusted model (0.28 vs. 0.34, P = .06). We did not observe these differences in Native Hawaiians and Filipinos. Young adult daily menthol smokers have slower rates of nicotine metabolism than nonmenthol smokers. Studies are needed to determine the utility of this biomarker for smoking cessation treatment assignments. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. 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.

  6. A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0

    NASA Astrophysics Data System (ADS)

    Sommer, Philipp S.; Kaplan, Jed O.

    2017-10-01

    While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.

  7. 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…

  8. Daily Life Satisfaction in Older Adults as a Function of (In)Activity.

    PubMed

    Maher, Jaclyn P; Conroy, David E

    2017-07-01

    This 14-day daily diary study tested the between-person and within-person associations between sedentary behavior, physical activity, and life satisfaction in community-dwelling older adults. Older adults (n = 100) wore ActivPAL3 activity monitors for 14 days and, at the end of each day, answered questions regarding their health behaviors and life satisfaction. Separate multilevel models were tested for self-reported and objectively measured behavioral data. In the model using objectively measured behavioral data, life satisfaction was (a) negatively associated with sedentary behavior at the within-person level and unassociated with sedentary behavior at the between-person level and (b) unassociated with physical activity at either the between-person or within-person level. In the model using self-reported behavioral data, life satisfaction was (a) unassociated with sedentary behavior at either the between-person or within-person level and (2) positively associated with physical activity at the within-person, but not at the between-person, level. Results indicated that daily deviations in objectively measured sedentary behavior and self-reported physical activity have implications for older adults' well-being. Interventions designed to enhance well-being and quality of life in older adults should consider targeting daily changes in total sedentary behavior and daily changes in the volume or frequency of physical activity. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  9. Psychological Detachment Mediating the Daily Relationship between Workload and Marital Satisfaction

    PubMed Central

    Germeys, Lynn; De Gieter, Sara

    2017-01-01

    Scholars already demonstrated that psychologically detaching from work after workhours can diminish or avoid the negative effects of job demands on employees' well-being. In this study, we examined a curvilinear relationship between workload and psychological detachment. Moreover, we investigated the moderating influence of an employee's work-home segmentation preference on the relation between detachment and marital satisfaction. In addition, we applied and extended the stressor-detachment model by examining detachment as a mediator of the relation between workload and marital satisfaction. A total of 136 employees participated in our daily diary survey study during 10 consecutive working days. The results of the Bayesian 2-level path analyses revealed a negative linear and curvilinear relationship between workload and psychological detachment on a daily basis. Daily detachment positively related to marital satisfaction, with one's preference to segment work from home reinforcing this relationship. Moreover, psychological detachment fully mediated the daily relationship between workload and marital satisfaction. Implications for practice and suggestions for future research are discussed. PMID:28101076

  10. Associations between ambient air pollution and daily mortality in a cohort of congestive heart failure: Case-crossover and nested case-control analyses using a distributed lag nonlinear model.

    PubMed

    Buteau, Stephane; Goldberg, Mark S; Burnett, Richard T; Gasparrini, Antonio; Valois, Marie-France; Brophy, James M; Crouse, Dan L; Hatzopoulou, Marianne

    2018-04-01

    Persons with congestive heart failure may be at higher risk of the acute effects related to daily fluctuations in ambient air pollution. To meet some of the limitations of previous studies using grouped-analysis, we developed a cohort study of persons with congestive heart failure to estimate whether daily non-accidental mortality were associated with spatially-resolved, daily exposures to ambient nitrogen dioxide (NO 2 ) and ozone (O 3 ), and whether these associations were modified according to a series of indicators potentially reflecting complications or worsening of health. We constructed the cohort from the linkage of administrative health databases. Daily exposure was assigned from different methods we developed previously to predict spatially-resolved, time-dependent concentrations of ambient NO 2 (all year) and O 3 (warm season) at participants' residences. We performed two distinct types of analyses: a case-crossover that contrasts the same person at different times, and a nested case-control that contrasts different persons at similar times. We modelled the effects of air pollution and weather (case-crossover only) on mortality using distributed lag nonlinear models over lags 0 to 3 days. We developed from administrative health data a series of indicators that may reflect the underlying construct of "declining health", and used interactions between these indicators and the cross-basis function for air pollutant to assess potential effect modification. The magnitude of the cumulative as well as the lag-specific estimates of association differed in many instances according to the metric of exposure. Using the back-extrapolation method, which is our preferred exposure model, we found for the case-crossover design a cumulative mean percentage changes (MPC) in daily mortality per interquartile increment in NO 2 (8.8 ppb) of 3.0% (95% CI: -0.9, 6.9%) and for O 3 (16.5 ppb) 3.5% (95% CI: -4.5, 12.1). For O 3 there was strong confounding by weather

  11. 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…

  12. Exercise and sleep predict personal resources in employees' daily lives.

    PubMed

    Nägel, Inga J; Sonnentag, Sabine

    2013-11-01

    The present study investigates the interaction of exercise and sleep on state-like personal resources in employees' daily lives. Further, the study examines the association between state-like personal resources and emotional exhaustion. We conducted a diary study over five consecutive working days (total of 443 days) with 144 employees who answered daily online surveys after work and before bedtime. Multilevel modeling showed that exercise after work was positively related to the next day's personal resources when sleep duration during the night time was longer compared to other nights. Furthermore, personal resources positively related to lower emotional exhaustion after work on the next day. This study demonstrates that exercise and sleep may help to renew personal resources. Results stress the importance of balancing exercise and sleep in daily life. © 2013 The International Association of Applied Psychology.

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

    PubMed Central

    Crane, Cory A.; Testa, Maria

    2014-01-01

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

  14. Intermittent and daily smokers: two different socioeconomic patterns, and diverging influence of social participation

    PubMed Central

    Lindstrom, M.; Ostergren, P.

    2001-01-01

    OBJECTIVE—To investigate socioeconomic differences in intermittent and daily smoking, and to assess the association between social participation and these two smoking behaviours.
DESIGN/SETTING/PARTICIPANTS/MEASUREMENTS—A population of 11 837 individuals interviewed in 1992-94, aged 45-64 years, was investigated in this cross sectional study. A multivariate logistic regression model was used to assess socioeconomic differences in daily and intermittent smoking, adjusting for age, country of origin, previous/current diseases, and marital status. Finally, social participation as a measure of social capital was introduced in the multivariate model.
RESULTS—When unskilled manual workers were compared to high level non-manual employees, odds ratios of 2.3 (95% confidence interval (CI) 1.7 to 3.0) for men and 1.9 (95% CI 1.4 to 2.5) for women were found in regard to daily smoking, but odd ratios of only 0.7 (95% CI 0.4 to 1.2) for men and 1.3 (95% CI 0.7 to 2.4) for women were found in regard to intermittent smoking. A decrease in the daily smoking odds ratios was found when social participation was introduced in the model, while the odds ratios regarding intermittent smoking were unaffected.
CONCLUSIONS—There were no socioeconomic differences in intermittent smoking and no association with social participation, a result that contrasts sharply with the patterns of daily smoking. These findings have important implications for the discussion concerning social capital and preventive measures.


Keywords: intermittent smoking; daily smoking; socioeconomic status; social participation; social capital PMID:11544391

  15. 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

  16. Quantifying daily physical activity and determinants in sedentary patients with Parkinson's disease.

    PubMed

    Dontje, M L; de Greef, M H G; Speelman, A D; van Nimwegen, M; Krijnen, W P; Stolk, R P; Kamsma, Y P T; Bloem, B R; Munneke, M; van der Schans, C P

    2013-10-01

    Although physical activity is beneficial for Parkinson's disease (PD) patients, many do not meet the recommended levels. The range of physical activity among sedentary PD patients is unknown, as are factors that determine this variability. Hence, we aimed to (1) assess daily physical activity in self-identified sedentary PD patients; (2) compare this with criteria of a daily physical activity guideline; and (3) identify determinants of daily physical activity. Daily physical activity of 586 self-identified sedentary PD patients was measured with a tri-axial accelerometer for seven consecutive days. Physical fitness and demographic, disease-specific, and psychological characteristics were assessed. Daily physical activity was compared with the 30-min activity guideline. A linear mixed-effects model was estimated to identify determinants of daily physical activity. Accelerometer data of 467 patients who fulfilled all criteria revealed that >98% of their day was spent on sedentary to light-intensity activities. Eighty-two percent of the participants were 'physically inactive' (0 days/week of 30-min activity); 17% were 'semi-active' (1-4 days/week of 30-min activity). Age, gender, physical fitness, and scores on the Unified Parkinson's Disease Rating Scale explained 69% of the variability in daily physical activity. Performance-based measurements confirmed that most self-identified sedentary PD patients are 'physically inactive'. However, the variance in daily physical activity across subjects was considerable. Higher age, being female, and lower physical capacity were the most important determinants of reduced daily physical activity. Future therapeutic interventions should aim to improve daily physical activity in these high-risk patients, focusing specifically on modifiable risk factors. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. 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…

  18. The Combined Effects of Daily Stressors and Major Life Events on Daily Subjective Ages.

    PubMed

    Bellingtier, Jennifer A; Neupert, Shevaun D; Kotter-Grühn, Dana

    2017-07-01

    Stressors may be a contributing factor in determining how old an individual feels, looks, or would like to be. Currently, little research has been devoted to understanding the relationship between stressors and subjective age in older adults. We focus on the combined impact of major life-event stressors and daily stressors on multiple indicators of subjective age: felt age, ideal age, and look age. Furthermore, we examine the process by which daily stressors relate to subjective ages by testing whether positive affect, control, and negative affect mediate this relationship. Using a daily-diary design, the current study measured older adults' (60-96 years old) stressors, subjective ages, personal control, and affect. Felt, ideal, and look ages each demonstrated a unique pattern of interactions between daily stressors and major life-event stressors. Furthermore, our findings suggest that on the daily level, the relationship between stressors and felt age is mediated by negative affect but not by control and positive affect. Findings indicate the need to consider the broader contextual picture of stressors, as well as their differential impact on multiple indicators of subjective age. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. Psychosocial work conditions, social capital, and daily smoking: a population based study.

    PubMed

    Lindström, M

    2004-09-01

    To investigate the associations between psychosocial conditions at work, social capital/social participation, and daily smoking. The 2000 public health survey in Scania is a cross sectional postal questionnaire study with a 59% participation rate. A total of 5180 persons aged 18-64 years that belonged to the work force and the unemployed were included in this study. Logistic regression models were used to investigate the associations between psychosocial factors at work/unemployment, social participation, and daily smoking. Psychosocial conditions at work were defined according to the Karasek-Theorell demand-control/decision latitudes into relaxed, active, passive, and jobstrain categories. The multivariate analyses included age, country of origin, education and economic stress. 17.2% proportion of all men and 21.9% of all women were daily smokers. The jobstrain (high demands/low control) and unemployed categories had significantly higher odds ratios of daily smoking among both men and women compared to the relaxed (low demands/high control) reference category. The passive (low demands/low control), jobstrain, and unemployed categories were also significantly associated with low social participation. Low social participation was significantly and positively associated with daily smoking within each of the psychosocial work conditions and unemployed categories. The positive association between low social capital/low social participation and daily smoking is well known. However, both social participation and daily smoking are associated with psychosocial work conditions and unemployment. Psychosocial work conditions and unemployment may affect daily smoking both directly and through a pathway including social participation.

  20. 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.

  1. 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…

  2. Can We Predict Daily Adherence to Warfarin?

    PubMed Central

    Platt, Alec B.; Localio, A. Russell; Brensinger, Colleen M.; Cruess, Dean G.; Christie, Jason D.; Gross, Robert; Parker, Catherine S.; Price, Maureen; Metlay, Joshua P.; Cohen, Abigail; Newcomb, Craig W.; Strom, Brian L.; Laskin, Mitchell S.

    2010-01-01

    Background: Warfarin is the primary therapy to prevent stroke and venous thromboembolism. Significant periods of nonadherence frequently go unreported by patients and undetected by providers. Currently, no comprehensive screening tool exists to help providers assess the risk of nonadherence at the time of initiation of warfarin therapy. Methods: This article reports on a prospective cohort study of adults initiating warfarin therapy at two anticoagulation clinics (university- and Veterans Affairs-affiliated). Nonadherence, defined by failure to record a correct daily pill bottle opening, was measured daily by electronic pill cap monitoring. A multivariable logistic regression model was used to develop a point system to predict daily nonadherence to warfarin. Results: We followed 114 subjects for a median of 141 days. Median nonadherence of the participants was 14.4% (interquartile range [IQR], 5.8-33.8). A point system, based on nine demographic, clinical, and psychosocial factors, distinguished those demonstrating low vs high levels of nonadherence: four points or fewer, median nonadherence 5.8% (IQR, 2.3-14.1); five points, 9.1% (IQR, 5.9-28.6); six points, 14.5% (IQR, 7.1-24.1); seven points, 14.7% (IQR, 7.0-34.7); and eight points or more, 29.3% (IQR, 15.5-41.9). The model produces a c-statistic of 0.66 (95% CI, 0.61-0.71), suggesting modest discriminating ability to predict day-level warfarin nonadherence. Conclusions: Poor adherence to warfarin is common. A screening tool based on nine demographic, clinical, and psychosocial factors, if further validated in other patient populations, may help to identify groups of patients at lower risk for nonadherence so that intensified efforts at increased monitoring and intervention can be focused on higher-risk patients. PMID:19903973

  3. Single Daily Icodextrin Exchange as Initial and Solitary Therapy.

    PubMed

    Agar, Baris U; Sloand, James A

    2018-01-01

    Incremental dialysis utilizes gradually increasing dialysis doses in response to declines in residual kidney function, and it is the preferred renal replacement therapy for patients who have just transitioned to end-stage renal disease (ESRD). Incremental peritoneal dialysis (PD) may impose fewer restrictions on patients' lifestyle, help attenuate lifetime peritoneal and systemic exposure to glucose and its degradation products, and minimize connections that could compromise the sterile fluid path. In this study, we utilized a 3-pore kinetic model to assess fluid and solute removal during single daily icodextrin treatments for patients with varying glomerular filtration rates (GFR). Single icodextrin exchanges of 8 to 16 hours using 2- and 2.5-L bag volumes were simulated for different patient transport types (i.e., high to low) to predict daily peritoneal ultrafiltration (UF), daily peritoneal sodium removal, and weekly total (peritoneal + residual kidney) Kt/V (Kt/V Total ) for patients with residual renal GFRs ranging from 0 to 15 mL/min/1.73 m 2 . Daily peritoneal UF varied from 359 to 607 mL, and daily peritoneal Na removal varied from 52 to 87 mEq depending on length of icodextrin exchange and bag volume. Both were effectively independent of patient transport type. All but very large patients (total body water [TBW] > 60 L) were predicted to achieve adequate dialysis (Kt/V Total ≥ 1.7) with a GFR of 10 mL/min/1.73 m 2 , and small patients (TBW: 30 L) were predicted to achieve adequate dialysis with a GFR of 6 mL/min/1.73 m 2 . A single daily icodextrin exchange can be tailored to augment urea, UF, and Na removal in patients with sufficient residual kidney function (RKF). A solitary icodextrin exchange may therefore be reasonable initial therapy for some incident ESRD patients. Copyright © 2018 International Society for Peritoneal Dialysis.

  4. Simulating daily soil water under foothills fescue grazing with the soil and water assessment tool model (Alberta, Canada)

    NASA Astrophysics Data System (ADS)

    Mapfumo, Emmanuel; Chanasyk, David S.; Willms, Walter D.

    2004-10-01

    Grazing is common in the foothills fescue grasslands and may influence the seasonal soil-water patterns, which in turn determine range productivity. Hydrological modelling using the soil and water assessment tool (SWAT) is becoming widely adopted throughout North America especially for simulation of stream flow and runoff in small and large basins. Although applications of the SWAT model have been wide, little attention has been paid to the model's ability to simulate soil-water patterns in small watersheds. Thus a daily profile of soil water was simulated with SWAT using data collected from the Stavely Range Sub-station in the foothills of south-western Alberta, Canada. Three small watersheds were established using a combination of natural and artificial barriers in 1996-97. The watersheds were subjected to no grazing (control), heavy grazing (2.4 animal unit months (AUM) per hectare) or very heavy grazing (4.8 AUM ha-1). Soil-water measurements were conducted at four slope positions within each watershed (upper, middle, lower and 5 m close to the collector drain), every 2 weeks annually from 1998 to 2000 using a downhole CPN 503 neutron moisture meter. Calibration of the model was conducted using 1998 soil-water data and resulted in Nash-Sutcliffe coefficient (EF or R2) and regression coefficient of determination (r2) values of 0.77 and 0.85, respectively. Model graphical and statistical evaluation was conducted using the soil-water data collected in 1999 and 2000. During the evaluation period, soil water was simulated reasonably with an overall EF of 0.70, r2 of 0.72 and a root mean square error (RMSE) of 18.01. The model had a general tendency to overpredict soil water under relatively dry soil conditions, but to underpredict soil water under wet conditions. Sensitivity analysis indicated that absolute relative sensitivity indices of input parameters in soil-water simulation were in the following order; available water capacity > bulk density > runoff curve

  5. Incidence of deep vein thrombosis is increased with 30 mg twice daily dosing of enoxaparin compared with 40 mg daily.

    PubMed

    Riha, Gordon M; Van, Philbert Y; Differding, Jerome A; Schreiber, Martin A

    2012-05-01

    The purpose of this study was to analyze whether 2 standard dosing regimens of enoxaparin (30 mg twice daily vs 40 mg once daily) would result in different deep vein thrombosis (DVT) rates and anti-factor Xa activity (anti-Xa) in surgical patients. Patients who required enoxaparin for prophylaxis were followed prospectively. Demographics were recorded. Patients underwent standardized duplex screening. Peak anti-Xa levels were drawn on 4 consecutive days. Sixty-three patients were followed up (28 patients on 30 mg twice daily, 35 patients on 40 mg once daily). There was no significant difference in demographics between groups. Twenty-five percent of patients on 30 mg twice daily developed a DVT, whereas 2.9% of patients on 40 mg once daily developed a DVT. Patients on 30 mg twice daily had significantly lower anti-Xa levels. The incidence of DVT is increased in surgical patients who receive 30 mg twice daily dosing of enoxaparin compared with 40 mg daily. Dosing of 40 mg once daily results in significantly higher peak anti-Xa levels compared with 30 mg twice daily. Copyright © 2012 Elsevier Inc. All rights reserved.

  6. Daily tornado frequency distributions in the United States

    NASA Astrophysics Data System (ADS)

    Elsner, J. B.; Jagger, T. H.; Widen, H. M.; Chavas, D. R.

    2014-01-01

    The authors examine daily tornado counts in the United States over the period 1994-2012 and find strong evidence for a power-law relationship in the distribution frequency. The scaling exponent is estimated at 1.64 (0.019 s.e.) giving a per tornado-day probability of 0.014% (return period of 71 years) that a tornado day produces 145 tornadoes as was observed on 27 April 2011. They also find that the total number of tornadoes by damage category on days with at least one violent tornado follows an exponential rule. On average, the daily number of tornadoes in the next lowest damage category is approximately twice the number in the current category. These findings are important and timely for tornado hazard models and for seasonal and sub-seasonal forecasts of tornado activity.

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

    PubMed

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

    2012-02-01

    Conscientiousness (C) is positively associated with health and longevity although the mechanisms underlying this relationship are not fully understood. Stress may play a role in explaining the C-longevity relationship. This study investigated whether C predicted the cognitive appraisals of daily stressors/hassles. Participants (N=102) completed measures of C and cognitive appraisal in relation to the most stressful hassle they had experienced in the last 7 days. Correlational analysis revealed that Total C, Order and Industriousness were positively correlated with primary appraisals, and Responsibility was positively correlated with secondary appraisals. The facets of C were then entered into hierarchical regression models, controlling for age and gender. This demonstrated that Order (β=0.27, p<0.05) and Industriousness (β=0.28, p<0.05) significantly predicted primary appraisals, accounting for 15.8% of the variance. Responsibility significantly predicted secondary appraisals (β=0.44, p<0.01), accounting for 16.3% of the variance. These findings indicate that higher Order and Industriousness are related to having a greater stake in daily stressors, whereas higher Responsibility is related to greater confidence in one's ability to deal with daily stressors. These results are the first demonstration that C is related to the appraisals of daily hassles and suggest that C may moderate the experience of stress in daily life. Copyright © 2011 John Wiley & Sons, Ltd.

  8. The role of perfectionism in daily self-esteem, attachment, and negative affect.

    PubMed

    Dunkley, David M; Berg, Jody-Lynn; Zuroff, David C

    2012-06-01

    This study of university students (64 men, 99 women) examined the role of self-critical (SC) and personal standards (PS) higher order dimensions of perfectionism in daily self-esteem, attachment, and negative affect. Participants completed questionnaires at the end of the day for 7 consecutive days. Trait and situational influences were found in the daily reports of self-esteem, attachment, and affect. In contrast to PS perfectionism, SC perfectionism was strongly related to aggregated daily reports of low self-esteem, attachment fears (fear of closeness, fear of dependency, fear of loss), and negative affect as well as instability indexes of daily self-esteem, attachment, and negative affect. Multilevel modeling indicated that both SC and PS perfectionists were emotionally reactive to decreases in self-esteem, whereas only SC perfectionists were emotionally reactive to increases in fear of closeness with others. These results demonstrate the dispositional and moderating influences of perfectionism dimensions on daily self-esteem, attachment, and negative affect. © 2011 The Authors. Journal of Personality © 2011, Wiley Periodicals, Inc.

  9. 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.

  10. Daily stressor reactivity during adolescence: The buffering role of parental warmth.

    PubMed

    Lippold, Melissa A; Davis, Kelly D; McHale, Susan M; Buxton, Orfeu M; Almeida, David M

    2016-09-01

    This study examined youth stressor reactivity in the form of links between daily stressors and adolescents' negative affect, physical health symptoms, and cortisol patterns. We also tested whether youth gender and parental warmth moderated these linkages. Participants were the children of employees in the information technology division of a large company (N = 132, mean age = 13.39 years, 55% female). Youth completed daily diary telephone interviews on 8 consecutive evenings and provided saliva samples at 4 time points over 4 days to assess daily stressors and youth physiological and affective functioning. Parental warmth was assessed during in-home interviews. Multilevel modeling was used to account for interdependencies in the data. Youth who experienced more daily stressors, on average, reported more negative affect and physical health symptoms, on average. Furthermore, on days youth reported more stressors than usual (compared to their own across-day average), they also exhibited more physical health symptoms, reduced evening cortisol decline (e.g., flatter slopes), higher bedtime cortisol, and more negative affect. Girls had stronger within-person linkages between daily stressors and daily negative affect than boys. Parental warmth moderated these within-person linkages: Youth who experienced more parental warmth had lower negative affect and steeper cortisol decline than usual on less stressful days. However, youth who experienced less parental warmth had higher negative affect and their cortisol levels declined less, even on days with lower-than-usual stress. Daily stressors are associated with youth's affective and physiological functioning, but parental warmth can support youth's stress recovery. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  11. Daily Stressor Reactivity during Adolescence: The Buffering Role of Parental Warmth

    PubMed Central

    Lippold, Melissa; Davis, Kelly D.; McHale, Susan M.; Buxton, Orfeu; Almeida, David M.

    2016-01-01

    Objective This study examined youth stressor reactivity in the form of links between daily stressors and adolescents’ negative affect, physical health symptoms, and cortisol patterns. We also tested whether youth gender and parental warmth moderated these linkages. Method Participants were the children of employees in the Information Technology division of a large company (N = 132, mean age = 13.39 years, 55% female). Youth completed daily diary telephone interviews on 8 consecutive evenings and provided saliva samples at 4 time points over 4 days to assess daily stressors and youth physiological and affective functioning. Parental warmth was assessed during in-home interviews. Multi-level modeling was used to account for interdependencies in the data. Results Youth who experienced more daily stressors, on average, reported more negative affect and physical health symptoms, on average. Further, on days youth reported more stressors than usual (compared to their own across-day average), they also exhibited more physical health symptoms, reduced evening cortisol decline (e.g., flatter slopes), higher bedtime cortisol, and more negative affect. Girls had stronger within-person linkages between daily stressors and daily negative affect than boys. Parental warmth moderated these within-person linkages: Youth who experienced more parental warmth had lower negative affect and steeper cortisol decline than usual on less stressful days. Yet, youth who experienced less parental warmth had higher negative affect and their cortisol levels declined less, even on days with lower-than-usual stress. Conclusions Daily stressors are associated with youth's affective and physiological functioning, but parental warmth can support youth's stress recovery. PMID:27175577

  12. Military mental health: the role of daily hassles while deployed.

    PubMed

    Heron, Elizabeth A; Bryan, Craig J; Dougherty, Craig A; Chapman, William G

    2013-12-01

    This study sought to identify factors contributing to symptoms of depression and posttraumatic stress disorder (PTSD) in recently deployed combat veterans. A sample of 168 active duty military personnel completed measures of combat exposure, deployment-related daily hassles, depression symptoms, and PTSD symptoms at six time points across their deployment: predeployment and 1, 3, 6, and 12 months postdeployment. Mixed-effects linear modeling with repeated measures was used to identify factors associated with depression and PTSD severity over time. Postdeployment depression severity did not change over time, but PTSD severity decreased slightly over time after returning home. Postdeployment depression severity was predicted by past (but not recent) combat exposure, daily hassles, and concurrent PTSD symptoms. Postdeployment PTSD severity was predicted by past and recent combat exposure, concurrent depression symptoms, and male sex. Depression severity mediated the relationship between daily hassles and postdeployment PTSD severity.

  13. Trend analysis for daily rainfall series of Barcelona

    NASA Astrophysics Data System (ADS)

    Ortego, M. I.; Gibergans-Báguena, J.; Tolosana-Delgado, R.; Egozcue, J. J.; Llasat, M. C.

    2009-09-01

    Frequency analysis of hydrological series is a key point to acquire an in-depth understanding of the behaviour of hydrologic events. The occurrence of extreme hydrologic events in an area may imply great social and economical impacts. A good understanding of hazardous events improves the planning of human activities. A useful model for hazard assessment of extreme hydrologic events in an area is the point-over-threshold (POT) model. Time-occurrence of events is assumed to be Poisson distributed, and the magnitude X of each event is modeled as an arbitrary random variable, whose excesses over the threshold x0, Y = X - x0, given X > x0, have a Generalized Pareto Distribution (GPD), ( ? )- 1? FY (y|β,?) = 1 - 1+ βy , 0 ? y < ysup , where ysup = +? if ? 0, and ysup = -β? ? if ? < 0. The limiting distribution for ? = 0 is an exponential one. Independence between this magnitude and occurrence in time is assumed, as well as independence from event to event. In order to take account for uncertainty of the estimation of the GPD parameters, a Bayesian approach is chosen. This approach allows to include necessary conditions on the parameters of the distribution for our particular phenomena, as well as propagate adequately the uncertainty of estimations to the hazard parameters, such as return periods. A common concern is to know whether magnitudes of hazardous events have changed in the last decades. Long data series are very appreciated in order to properly study these issues. The series of daily rainfall in Barcelona (1854-2006) has been selected. This is one of the longer european daily rainfall series available. Daily rainfall is better described using a relative scale and therefore it is suitably treated in a log-scale. Accordingly, log-precipitation is identified with X. Excesses over a threshold are modeled by a GPD with a limited maximum value. An additional assumption is that the distribution of the excesses Y has limited upper tail and, therefore, ? < 0, ysup

  14. Forecasting Daily Volume and Acuity of Patients in the Emergency Department.

    PubMed

    Calegari, Rafael; Fogliatto, Flavio S; Lucini, Filipe R; Neyeloff, Jeruza; Kuchenbecker, Ricardo S; Schaan, Beatriz D

    2016-01-01

    This study aimed at analyzing the performance of four forecasting models in predicting the demand for medical care in terms of daily visits in an emergency department (ED) that handles high complexity cases, testing the influence of climatic and calendrical factors on demand behavior. We tested different mathematical models to forecast ED daily visits at Hospital de Clínicas de Porto Alegre (HCPA), which is a tertiary care teaching hospital located in Southern Brazil. Model accuracy was evaluated using mean absolute percentage error (MAPE), considering forecasting horizons of 1, 7, 14, 21, and 30 days. The demand time series was stratified according to patient classification using the Manchester Triage System's (MTS) criteria. Models tested were the simple seasonal exponential smoothing (SS), seasonal multiplicative Holt-Winters (SMHW), seasonal autoregressive integrated moving average (SARIMA), and multivariate autoregressive integrated moving average (MSARIMA). Performance of models varied according to patient classification, such that SS was the best choice when all types of patients were jointly considered, and SARIMA was the most accurate for modeling demands of very urgent (VU) and urgent (U) patients. The MSARIMA models taking into account climatic factors did not improve the performance of the SARIMA models, independent of patient classification.

  15. Forecasting Daily Volume and Acuity of Patients in the Emergency Department

    PubMed Central

    Fogliatto, Flavio S.; Neyeloff, Jeruza; Kuchenbecker, Ricardo S.; Schaan, Beatriz D.

    2016-01-01

    This study aimed at analyzing the performance of four forecasting models in predicting the demand for medical care in terms of daily visits in an emergency department (ED) that handles high complexity cases, testing the influence of climatic and calendrical factors on demand behavior. We tested different mathematical models to forecast ED daily visits at Hospital de Clínicas de Porto Alegre (HCPA), which is a tertiary care teaching hospital located in Southern Brazil. Model accuracy was evaluated using mean absolute percentage error (MAPE), considering forecasting horizons of 1, 7, 14, 21, and 30 days. The demand time series was stratified according to patient classification using the Manchester Triage System's (MTS) criteria. Models tested were the simple seasonal exponential smoothing (SS), seasonal multiplicative Holt-Winters (SMHW), seasonal autoregressive integrated moving average (SARIMA), and multivariate autoregressive integrated moving average (MSARIMA). Performance of models varied according to patient classification, such that SS was the best choice when all types of patients were jointly considered, and SARIMA was the most accurate for modeling demands of very urgent (VU) and urgent (U) patients. The MSARIMA models taking into account climatic factors did not improve the performance of the SARIMA models, independent of patient classification. PMID:27725842

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  17. 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.

  18. 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.

  19. A comparison of daily precipitation metrics downscaled using SDSM and WRF + WRFDA models over the Iberian Peninsula.

    NASA Astrophysics Data System (ADS)

    José González-Rojí, Santos; Wilby, Robert L.; Sáenz, Jon; Ibarra-Berastegi, Gabriel

    2017-04-01

    Downscaling via the Statistical DownScaling Model (SDSM) version 5.2 and two different configurations of the dynamical WRF model (with and without 3DVAR data assimilation) was evaluated for the estimation of daily precipitation over 21 sites across the Iberian Peninsula during the period 2010-2014. Six different strategies were used to calibrate the SDSM model. These options cover (1) use of NCEP/NCAR R1 Reanalysis and (2) ERA Interim data for downscaling predictor variables calibrated with data from periods (3) 1948-2009 (NCEP/NCAR R1) and (4) 1979-2009 (NCEP/NCAR R1 and ERA Interim). Additionally, for the ERA Interim case, two different grid resolutions have been used, (5) 2.5° and (6) 0.75°. On the other side, for the NCEP/NCAR R1 case, only the 2.5° resolution has been used. Configuring the SDSM model in this way allows testing the sensitivity of the results to different origins of the predictors, fit to different calibration periods and use of different reanalysis resolutions. On the other hand, ERA Interim data at the highest resolution was used as the initial/boundary conditions to run WRF simulations with a 15 km x 15 km horizontal resolution over the Iberian Peninsula, for two different configurations. The first experiment (N) was run using the same configuration typically used for numerical downscaling, with information being fed through the boundaries of the domain. The second experiment (D) was run using 3DVAR data assimilation at 00UTC, 06UTC, 12UTC and 18UTC. In both cases, WRF simulations were run over the period 2009-2014, using the first year (2009) as spin-up for the soil model. Results from the WRF N and D runs and comparable SDSM set up for the period 2010-2014 were evaluated using observations from ECA and E-OBS datasets. In each case, model skill was assessed using seven daily precipitation metrics (absolute mean, wet-day intensity, 90th percentile, maximum 5-day total, maximum number of consecutive dry days, fraction of total from heavy

  20. Air pollution and daily mortality in Erfurt, east Germany, 1980-1989.

    PubMed

    Spix, C; Heinrich, J; Dockery, D; Schwartz, J; Völksch, G; Schwinkowski, K; Cöllen, C; Wichmann, H E

    1993-11-01

    In Erfurt, Germany, unfavorable geography and emissions from coal burning lead to very high ambient pollution (up to about 4000 micrograms/m3 SO2 in 1980-89). To assess possible health effects of these exposures, total daily mortality was obtained for this same period. A multivariate model was fitted, including corrections for long-term fluctuations, influenza epidemics, and meterology, before analyzing the effect of pollution. The best fit for pollution was obtained for log (SO2 daily mean) with a lag of 2 days. Daily mortality increased by 10% for an increase in SO2 from 23 to 929 micrograms/m3 (5% quantile to 95% quantile). A harvesting effect (fewer people die on a given day if more deaths occurred in the last 15 days) may modify this by +/- 2%. The effect for particulates (SP, 1988-89 only) was stronger than the effect of SO2. Log SP (daily mean) increasing from 15 micrograms/m3 to 331 micrograms/m3 (5% quantile to 95% quantile) was associated with a 22% increase in mortality. Depending on harvesting, the observable effect may lie between 14% and 27%. There is no indication of a threshold or synergism. The effects of air pollution are smaller than the effects of influenza epidemics and are of the same size as meterologic effects. The results for the lower end of the dose range are in agreement with linear models fitted in studies of moderate air pollution and episode studies.

  1. Self-Control, Daily Negative Affect and Blood Glucose Control in Adolescents with Type 1 Diabetes

    PubMed Central

    Lansing, Amy Hughes; Berg, Cynthia A.; Butner, Jonathan; Wiebe, Deborah J.

    2016-01-01

    Objective For adolescents with type 1 diabetes, maintaining optimal daily blood glucose control is a complex self-regulatory process that likely requires self-control. This study examined whether higher self-control was associated with lower daily negative affect about diabetes and, in turn, better daily blood glucose control, i.e., lower mean daily blood glucose (MBG) and smaller standard deviations of daily blood glucose (SDBG), through two paths: 1) self-control maintaining lower mean level of negative affect and 2) self-control buffering the association of the number of daily diabetes problems with daily negative affect. Methods Adolescents (M age=12.87 years) with type 1 diabetes (n=180) completed an initial survey containing a self-report measure of self-control. Nightly electronic diaries were completed for 14 days where adolescents reported daily problems with and negative affect about diabetes, and used a study-provided blood glucose meter. Results Hypotheses were examined through multilevel modeling. Lower mean levels of daily negative affect partially mediated the relation between higher adolescent self-control and lower MBG. Adolescent self-control also buffered the association of the number of daily problems with daily negative affect, and smaller fluctuations in daily negative affect were associated with lower SDBG. Conclusions Adolescent self-control is associated with daily affect regulatory processes that may influence MBG. However, fluctuations in daily negative affect about diabetes may represent a unique within-person daily process associated with SDBG. These findings suggest that studies examining daily disease processes and interventions targeting daily affect regulation may be important to improving health in adolescents with type 1 diabetes. PMID:26914647

  2. Patterns of daily duration and frequency of breastfeeding among exclusively breastfed infants in Shiraz, Iran, a 6-month follow-up study using Bayesian generalized linear mixed models.

    PubMed

    Saki, Azadeh; Eshraghian, Mohammad Reza; Tabesh, Hamed

    2012-12-19

    Despite numerous studies on the benefits of exclusive breastfeeding during the first half year of life, little information is available on actual breastfeeding practices in terms of daily duration and frequency of suckling. This study proposes to determine daily breastfeeding patterns among exclusively breastfed infants from birth to six months. An observational prospective follow-up study of daily feeding practices among exclusively breastfed infants was conducted in 2007/2008. Mothers were recruited and interviewed during their first month postpartum health center visit. A total of 287 mothers were recruited into the study. Primary outcome measures were suckling duration and frequency of breastfeeding during daytime and nighttime. Mothers were asked at each healthcare visit to report the daily duration in minutes and the daily number of breastfeeding sessions. Mixed models were used to determine breastfeeding patterns and predictors. Of 287 mothers selected for this study, 174 (61%) exclusively breastfeeding until six months after delivery. Mixed modeling showed that as the infant's age increased duration of one suckling, cumulative duration and frequency of breastfeeding during daytime, nighttime and a twenty four hour period all gradually decreased. Infants gender and receiving professional advice about breastfeeding were also significant factors in breastfeeding patterns (p<0.05). The one suckling duration and frequency of feeds in this study population were considerably higher than values reported in other populations. The variation of feeding patterns between exclusively breastfed infants was very wide. The distributions of one suckling duration, frequency of breastfeeding and cumulative duration of feeds were right-skewed. The current professional advices about breastfeeding are not appropriate because they do not consider unique condition within specific populations.

  3. Psychosocial work conditions, social capital, and daily smoking: a population based study

    PubMed Central

    Lindstrom, M

    2004-01-01

    Objective: To investigate the associations between psychosocial conditions at work, social capital/social participation, and daily smoking. Design/setting/participants/measurements: The 2000 public health survey in Scania is a cross sectional postal questionnaire study with a 59% participation rate. A total of 5180 persons aged 18–64 years that belonged to the work force and the unemployed were included in this study. Logistic regression models were used to investigate the associations between psychosocial factors at work/unemployment, social participation, and daily smoking. Psychosocial conditions at work were defined according to the Karasek-Theorell demand–control/decision latitudes into relaxed, active, passive, and jobstrain categories. The multivariate analyses included age, country of origin, education and economic stress. Results: 17.2% proportion of all men and 21.9% of all women were daily smokers. The jobstrain (high demands/low control) and unemployed categories had significantly higher odds ratios of daily smoking among both men and women compared to the relaxed (low demands/high control) reference category. The passive (low demands/low control), jobstrain, and unemployed categories were also significantly associated with low social participation. Low social participation was significantly and positively associated with daily smoking within each of the psychosocial work conditions and unemployed categories. Conclusions: The positive association between low social capital/low social participation and daily smoking is well known. However, both social participation and daily smoking are associated with psychosocial work conditions and unemployment. Psychosocial work conditions and unemployment may affect daily smoking both directly and through a pathway including social participation. PMID:15333886

  4. Factors associated with short-term transitions of non-daily smokers: socio-demographic characteristics and other tobacco product use.

    PubMed

    Wang, Yingning; Sung, Hai-Yen; Yao, Tingting; Lightwood, James; Max, Wendy

    2017-05-01

    To examine the transitions in smoking status among non-daily smokers who transitioned to daily or former smokers or remained as non-daily smokers during a 12-month period. We analyzed factors associated with these transitions, including the use of cigars and smokeless tobacco (SLT). Secondary data analyses using pooled data from the 2003, 2006/07 and 2010/11 Tobacco Use Supplements to the Current Population Survey (TUS-CPS). United States. Self-respondents aged 18+ who have smoked for more than 5 years and were non-daily smokers 12 months before the interview (n = 13 673, or 14.5% of current smokers). Multinomial logistic regression model to determine the correlates of non-daily to daily, stable non-daily and non-daily to former smoking transitions among non-daily smokers at baseline. The model controlled for socio-demographic factors and the use of cigars and SLT. Of the adults in our sample, 2.6% were non-daily smokers at baseline. Among these, 69.7% remained non-daily smokers (stable non-daily smokers), 18.4% became daily smokers (non-daily to daily smokers) and 11.9% quit smoking (non-daily to former smokers) after 12 months. The non-daily to daily versus stable non-daily smoking transition was less likely among those who were aged 65+ (P = 0.018), male (P < 0.001), Hispanic (P < 0.001), with an income of $25 000-49 999 or ≥$75 000 and current users of SLT (P = 0.003), but more likely among those without a college degree compared with the appropriate reference group. The non-daily to former versus stable non-daily smoking transition was less likely among those aged 25+, male (P = 0.013), non-Hispanic Asian (P = 0.032), without a college degree, widowed/divorced/separated (P = 0.013) or never married (P = 0.011) and current users of cigars (P = 0.003) compared with the appropriate reference group. While more than two-thirds of non-daily smokers in the United States remain as such after 12 months, others become daily smokers or

  5. Forecasting daily attendances at an emergency department to aid resource planning

    PubMed Central

    Sun, Yan; Heng, Bee Hoon; Seow, Yian Tay; Seow, Eillyne

    2009-01-01

    Background Accurate forecasting of emergency department (ED) attendances can be a valuable tool for micro and macro level planning. Methods Data for analysis was the counts of daily patient attendances at the ED of an acute care regional general hospital from July 2005 to Mar 2008. Patients were stratified into three acuity categories; i.e. P1, P2 and P3, with P1 being the most acute and P3 being the least acute. The autoregressive integrated moving average (ARIMA) method was separately applied to each of the three acuity categories and total patient attendances. Independent variables included in the model were public holiday (yes or no), ambient air quality measured by pollution standard index (PSI), daily ambient average temperature and daily relative humidity. The seasonal components of weekly and yearly periodicities in the time series of daily attendances were also studied. Univariate analysis by t-tests and multivariate time series analysis were carried out in SPSS version 15. Results By time series analyses, P1 attendances did not show any weekly or yearly periodicity and was only predicted by ambient air quality of PSI > 50. P2 and total attendances showed weekly periodicities, and were also significantly predicted by public holiday. P3 attendances were significantly correlated with day of the week, month of the year, public holiday, and ambient air quality of PSI > 50. After applying the developed models to validate the forecast, the MAPE of prediction by the models were 16.8%, 6.7%, 8.6% and 4.8% for P1, P2, P3 and total attendances, respectively. The models were able to account for most of the significant autocorrelations present in the data. Conclusion Time series analysis has been shown to provide a useful, readily available tool for predicting emergency department workload that can be used to plan staff roster and resource planning. PMID:19178716

  6. Power-law scaling in daily rainfall patterns and consequences in urban stream discharges

    NASA Astrophysics Data System (ADS)

    Park, Jeryang; Krueger, Elisabeth H.; Kim, Dongkyun; Rao, Suresh C.

    2016-04-01

    Poissonian rainfall has been frequently used for modelling stream discharge in a catchment at the daily scale. Generally, it is assumed that the daily rainfall depth is described by memoryless exponential distribution which is transformed to stream discharge, resulting in an analytical pdf for discharge [Gamma distribution]. While it is true that catchment hydrological filtering processes (censored by constant rate ET losses, and first-order recession) increases "memory", reflected in 1/f noise in discharge time series. Here, we show that for urban watersheds in South Korea: (1) the observation of daily rainfall depths follow power-law pdfs, and spectral slopes range between 0.2 ~ 0.4; and (2) the stream discharge pdfs have power-law tails. These observation results suggest that multiple hydro-climatic factors (e.g., non-stationarity of rainfall patterns) and hydrologic filtering (increasing impervious area; more complex urban drainage networks) influence the catchment hydrologic responses. We test the role of such factors using a parsimonious model, using different types of daily rainfall patterns (e.g., power-law distributed rainfall depth with Poisson distribution in its frequency) and urban settings to reproduce patterns similar to those observed in empirical records. Our results indicate that fractality in temporally up-scaled rainfall, and the consequences of large extreme events are preserved as high discharge events in urbanizing catchments. Implications of these results to modeling urban hydrologic responses and impacts on receiving waters are discussed.

  7. Total daily physical activity and the risk of AD and cognitive decline in older adults

    PubMed Central

    Boyle, P.A.; Yu, L.; Shah, R.C.; Wilson, R.S.; Bennett, D.A.

    2012-01-01

    Objective: Studies examining the link between objective measures of total daily physical activity and incident Alzheimer disease (AD) are lacking. We tested the hypothesis that an objective measure of total daily physical activity predicts incident AD and cognitive decline. Methods: Total daily exercise and nonexercise physical activity was measured continuously for up to 10 days with actigraphy (Actical®; Philips Healthcare, Bend, OR) from 716 older individuals without dementia participating in the Rush Memory and Aging Project, a prospective, observational cohort study. All participants underwent structured annual clinical examination including a battery of 19 cognitive tests. Results: During an average follow-up of about 4 years, 71 subjects developed clinical AD. In a Cox proportional hazards model adjusting for age, sex, and education, total daily physical activity was associated with incident AD (hazard ratio = 0.477; 95% confidence interval 0.273–0.832). The association remained after adjusting for self-report physical, social, and cognitive activities, as well as current level of motor function, depressive symptoms, chronic health conditions, and APOE allele status. In a linear mixed-effect model, the level of total daily physical activity was associated with the rate of global cognitive decline (estimate 0.033, SE 0.012, p = 0.007). Conclusions: A higher level of total daily physical activity is associated with a reduced risk of AD. PMID:22517108

  8. Total daily physical activity and the risk of AD and cognitive decline in older adults.

    PubMed

    Buchman, A S; Boyle, P A; Yu, L; Shah, R C; Wilson, R S; Bennett, D A

    2012-04-24

    Studies examining the link between objective measures of total daily physical activity and incident Alzheimer disease (AD) are lacking. We tested the hypothesis that an objective measure of total daily physical activity predicts incident AD and cognitive decline. Total daily exercise and nonexercise physical activity was measured continuously for up to 10 days with actigraphy (Actical®; Philips Healthcare, Bend, OR) from 716 older individuals without dementia participating in the Rush Memory and Aging Project, a prospective, observational cohort study. All participants underwent structured annual clinical examination including a battery of 19 cognitive tests. During an average follow-up of about 4 years, 71 subjects developed clinical AD. In a Cox proportional hazards model adjusting for age, sex, and education, total daily physical activity was associated with incident AD (hazard ratio = 0.477; 95% confidence interval 0.273-0.832). The association remained after adjusting for self-report physical, social, and cognitive activities, as well as current level of motor function, depressive symptoms, chronic health conditions, and APOE allele status. In a linear mixed-effect model, the level of total daily physical activity was associated with the rate of global cognitive decline (estimate 0.033, SE 0.012, p = 0.007). A higher level of total daily physical activity is associated with a reduced risk of AD.

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

    PubMed

    Levitt, M J; Kann, J

    1984-07-01

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

  10. [Adolescent daily smoking, negative mood-states and the role of family communication].

    PubMed

    Martínez-Hernáez, Ángel; Marí-Klose, Marga; Julià, Albert; Escapa, Sandra; Marí-Klose, Pau; DiGiacomo, Susan

    2012-01-01

    To determine whether negative mood states constitute a risk factor for daily smoking during adolescence, and to specify the role of familial factors in the association between the two variables. Cross-sectional study of a representative sample (second wave, Panel of Families and Childhood) of Catalan adolescents between 14 and 18 years of age. Six logistic regression models were used for girls (n = 1,442) and six for boys (n =1,100) in order to determine whether negative mood states constitute a risk factor for daily cigarette consumption, and to what extent this effect is attributable to familial factors. The prevalence of daily smoking at ages 17-18 is 3.8% for girls and 3.6 for boys. Feelings of sadness constitute a risk factor for daily cigarette consumption (odds ratio [OR] = 1.633), and communication with the father cancels out this effect. Parental pressure is a risk factor for daily smoking in both sexes (girls, OR = 2.064; boys, OR = 1.784). When parental communication is controlled for, this effect is reduced but not canceled out. Living in a reconstituted family is a risk factor for daily cigarette consumption among boys (OR = 2.988). Intergenerational communication decreases the risk of daily tobacco use among adolescents independently of their mood state. Anti-smoking interventions designed in accordance with these findings may be more effective. Copyright © 2011 SESPAS. Published by Elsevier Espana. All rights reserved.

  11. Daily Spouse Responsiveness Predicts Longer-Term Trajectories of Physical Function

    PubMed Central

    Wilson, Stephanie J.; Martire, Lynn M.; Sliwinski, Martin J.

    2017-01-01

    Everyday interpersonal experiences may underlie the well-established link between close relationships and physical health, but multitemporal designs necessary for strong conclusions about temporal sequence are rare. The current study of 145 knee osteoarthritis patients and their spouses focused on a novel pattern in everyday interactions, daily spouse responsiveness—the degree to which spouse responses are calibrated to changes in patients’ everyday verbal pain expression. Using couple-level slopes, multilevel latent-variable growth models tested associations between three types of daily spouse responsiveness (empathic, solicitous, and punishing), as measured during a 3-week experience-sampling study, and change in patient physical function across 18 months. As predicted, patients whose spouses were more empathically responsive to their pain expression showed better physical function over time compared to those whose spouses were less empathically responsive. This study points to daily responsiveness, a theoretically rooted operationalization of spouse sensitivity, as important for long-term changes in objective physical function. PMID:28459650

  12. Perceived health status and daily activity participation of older Malaysians.

    PubMed

    Ng, Sor Tho; Tengku-Aizan, Hamid; Tey, Nai Peng

    2011-07-01

    This article investigates the influence of perceived health status on the daily activity participation of older Malaysians. Data from the Survey on Perceptions of Needs and Problems of the Elderly, which was conducted in 1999, were used. The negative binomial regression results show that older persons with good perceived health status reported more varieties of daily activity participation, especially among the uneducated and those with below-average self-esteem. The multinomial logistic regression model suggests that older persons with good perceived health status tended to engage daily in paid work only or with leisure activities, whereas those perceived to have poor health were more likely to engage in leisure activities only or leisure and family role activities. Promotion of a healthy lifestyle at a younger age encourages every person to monitor and take responsibility for their own health, which is a necessary strategy to ensure active participation at an older age, and thus improve their well-being.

  13. Negative Aging Attitudes Predict Greater Reactivity to Daily Stressors in Older Adults.

    PubMed

    Bellingtier, Jennifer A; Neupert, Shevaun D

    2016-08-03

    In order to understand conflicting findings regarding the emotional reactions of older adults to daily stressors, we examined the possibility that negative aging attitudes could function as an important individual differences factor related to stressor reactivity. Using a daily dairy design, we examined the aging attitudes of 43 older adults reporting on 380 total days. Participants reported their aging attitudes on Day 1, followed by their stressor exposure and negative affect on Days 2-9. Covariates included age, gender, education, and personality. Using multilevel modeling, our results suggest that individuals with more positive aging attitudes report consistent levels of affect across study days regardless of stressors, whereas those with more negative aging attitudes reported increased emotional reactivity to daily stressors. Positive aging attitudes may serve as a resource that helps buffer reactions to daily stressors. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  14. 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

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

    Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.

    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 centralmore » 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

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

    DOE PAGES

    Halder, Subhadeep; Saha, Subodh K.; Dirmeyer, Paul A.; ...

    2016-05-10

    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 centralmore » 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

  16. 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.…

  17. 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

  18. Daily supplementation of D-ribose shows no therapeutic benefits in the MHC-I transgenic mouse model of inflammatory myositis.

    PubMed

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

    2013-01-01

    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. 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. 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.

  19. [Chronic daily headache: clinical presentation].

    PubMed

    Krymchantowski, A V; Moreira Filho, P F

    2000-06-01

    Chronic daily headache (CDH) represents a group of any headache disorder that occurs on a daily or near daily basis, for longer than 6 months. Even though it is a common problem, it is not a well defined disorder, resulting in controversies regarding its identification, description and approach. Three hundred patients, 232 women and 68 men, ages 16 to 86 (mean 38 years old for the women and 42 for the men), attending a headache center and fulfilling the proposed criteria for CDH (Silberstein et al.) and presenting headache 28 days per month were retrospectively studied. The clinical features allowed the primary headache diagnosis, before the transformation into daily presentation as: transformed migraine (TM ) in 271 patients (90,3%), chronic tension-type headache (CTTH) in 26 patients (8,7%) and new daily persistent headache (NDPH) in 3 patients (1%). Among the TM patients, the most observed presentation was pressure or tightening, bilateral fronto-temporal, moderate non-continuous headache, with a progressive onset. The association with nausea and phonophobia was demonstrated in 60% and 32% of the patients respectively. The association with photophobia and sleep disturbances, as well as the occurrence of intermittent headache attacks, was different among male and female patients. With regard to the CTTH patients, pressure or tightening, bilateral fronto-temporal, moderate non-continuous headache, with sleep disturbances and no associated symptoms, was the predominant presentation.

  20. The effects of employment status and daily stressors on time spent on daily household chores in middle-aged and older adults.

    PubMed

    Wong, Jen D; Almeida, David M

    2013-02-01

    This study examines how employment status (worker vs. retiree) and life course influences (age, gender, and marital status) are associated with time spent on daily household chores. Second, this study assesses whether the associations between daily stressors and time spent on daily household chores differ as a function of employment status and life course influences. Men and women aged 55-74 from the National Study of Daily Experiences (N = 268; 133 workers and 135 retirees), a part of the National Survey of Midlife in the United States (MIDUS), completed telephone interviews regarding their daily experiences across 8 consecutive evenings. Working women spent more than double the amount of time on daily household chores than working men. Unmarried retirees spent the most time on daily household chores in comparison to their counterparts. There was a trend toward significance for the association between home stressors from the previous day and time spent on daily household chores as a function of employment and marital status. These findings highlight the importance of gender and marital status in the associations between employment status and time spent on daily household chores and the role that daily stressors, in particular home stressful events, have on daily household chore participation.

  1. Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

    NASA Astrophysics Data System (ADS)

    Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

    2015-01-01

    Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

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

    PubMed

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

    2015-10-01

    The present study aims to uncover the way daily job crafting influences daily job performance (i.e., task performance, altruism, and counterproductive work behavior). Job crafting was conceptualized as "seeking resources," "seeking challenges," and "reducing demands" and viewed as strategies individuals use to optimize their job characteristics. We hypothesized that daily job crafting relates to daily job demands and resources (work pressure and autonomy), which consequently relate to daily work engagement and exhaustion and ultimately to job performance. A sample of 95 employees filled in a quantitative diary for 5 consecutive working days (n occasions = 475). We predicted and found that daily seeking resources was positively associated with daily task performance because daily autonomy and work engagement increased. In contrast, daily reducing demands was detrimental for daily task performance and altruism, because employees lower their daily workload and consequently their engagement and exhaustion, respectively. Only daily seeking challenges was positively (rather than negatively) associated with daily counterproductive behavior. We conclude that employee job crafting can have both beneficial and detrimental effects on job performance. (c) 2015 APA, all rights reserved).

  3. Air pollution and daily mortality in Erfurt, east Germany, 1980-1989.

    PubMed Central

    Spix, C; Heinrich, J; Dockery, D; Schwartz, J; Völksch, G; Schwinkowski, K; Cöllen, C; Wichmann, H E

    1993-01-01

    In Erfurt, Germany, unfavorable geography and emissions from coal burning lead to very high ambient pollution (up to about 4000 micrograms/m3 SO2 in 1980-89). To assess possible health effects of these exposures, total daily mortality was obtained for this same period. A multivariate model was fitted, including corrections for long-term fluctuations, influenza epidemics, and meterology, before analyzing the effect of pollution. The best fit for pollution was obtained for log (SO2 daily mean) with a lag of 2 days. Daily mortality increased by 10% for an increase in SO2 from 23 to 929 micrograms/m3 (5% quantile to 95% quantile). A harvesting effect (fewer people die on a given day if more deaths occurred in the last 15 days) may modify this by +/- 2%. The effect for particulates (SP, 1988-89 only) was stronger than the effect of SO2. Log SP (daily mean) increasing from 15 micrograms/m3 to 331 micrograms/m3 (5% quantile to 95% quantile) was associated with a 22% increase in mortality. Depending on harvesting, the observable effect may lie between 14% and 27%. There is no indication of a threshold or synergism. The effects of air pollution are smaller than the effects of influenza epidemics and are of the same size as meterologic effects. The results for the lower end of the dose range are in agreement with linear models fitted in studies of moderate air pollution and episode studies. Images Figure 1. Figure 2. PMID:8137781

  4. Chronic Daily Headaches

    MedlinePlus

    ... headache New daily persistent headache Hemicrania continua Chronic migraine This type typically occurs in people with a history of episodic migraines. Chronic migraines tend to: Affect one side or ...

  5. Social participation, social capital and daily tobacco smoking: a population-based multilevel analysis in Malmö, Sweden.

    PubMed

    Lindström, Martin; Moghaddassi, Mahnaz; Bolin, Kristian; Lindgren, Björn; Merlo, Juan

    2003-01-01

    The aim of this study was to investigate the influence of contextual and individual factors on daily tobacco smoking. The public-health survey in Malmö 1994 is a cross-sectional study. A total of 5600 individuals aged 20-80 years were invited to answer a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. We analysed the effect (intra-area correlation, cross-level modification and odds ratios) of individual and neighbourhood factors on smoking after adjustment for individual factors. Neighbourhood factors accounted for 2.5% of the crude total variance in daily tobacco smoking. This effect was significantly reduced when the individual factors such as education were included in the model. However, individual social capital, measured by social participation, only marginally affected the total neighbourhood variance in daily tobacco smoking. In fact, no significant variance in daily tobacco smoking remained after the introduction of the individual factors other than individual social capital in the model. In Malmö, the neighbourhood variance in daily tobacco smoking is mainly affected by individual factors other than individual social capital, especially socioeconomic status measured as level of education.

  6. Intraindividual change and variability in daily stress processes: Findings from two measurement-burst diary studies

    PubMed Central

    Sliwinski, Martin J.; Almeida, David M.; Smyth, Joshua; Stawski, Robert S.

    2010-01-01

    There is little longitudinal information on aging-related changes in emotional responses to negative events. The present manuscript examined intraindividual change and variability in the within-person coupling of daily stress and negative affect (NA) using data from two-measurement burst daily diary studies. Three main findings emerged. First, average reactivity to daily stress increased longitudinally, and this increase was evident across most the adult lifespan. Second, individual differences in emotional reactivity to daily stress exhibited long-term temporal stability, but this stability was greatest in midlife and decreased in old age. And third, reactivity to daily stress varied reliably within-persons (across-time), with individual exhibiting higher levels of reactivity during times when reporting high levels of global subject stress in previous month. Taken together, the present results emphasize the importance of modeling dynamic psychosocial and aging processes that operate across different time scales for understanding age-related changes in daily stress processes. PMID:20025399

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

    NASA Technical Reports Server (NTRS)

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

  8. Social capital, economic conditions, marital status and daily smoking: a population-based study.

    PubMed

    Lindström, Martin

    2010-02-01

    To investigate the association between marital status and daily smoking, adjusting for economic conditions and trust. Cross-sectional study. In total, 27,757 individuals aged 18-80 years answered a postal questionnaire, which represents 59% of the random sample. A logistic regression model was used to investigate the association between marital status and daily smoking, adjusting for economic (material) conditions and trust. A multivariate analysis was performed to investigate the importance of possible confounders concerning the differences in daily smoking according to marital status. Smoking prevalence was 14.9% among men and 18.1% among women. The odds ratios of daily smoking for middle-aged respondents, born abroad, medium/low education, problems paying bills, low trust, and unmarried and (particularly) divorced respondents were significantly higher than those for their reference groups. Low trust was significantly higher among divorced and unmarried respondents compared with married/cohabitating respondents. Adjustment for economic conditions reduced the odds ratios of daily smoking among divorced subjects; this was not seen following adjustment for trust. Never-married subjects and (particularly) divorced subjects showed a significantly higher prevalence of daily smoking than married/cohabitating respondents. Economic conditions have a significant effect on the association between marital status and daily smoking, but this was not seen for trust. Copyright 2010 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  9. Measuring Daily Stress in Children.

    ERIC Educational Resources Information Center

    Parfenoff, Sheila H.; Jose, Paul E.

    A study of school-age children was designed to: (1) identify hassles that children experience in their families, among peers, and at school; (2) determine the ability of hassles to predict unhealthy psychological and physical functioning; and (3) explore the effect of daily hassles on school behavior. A measure of children's daily stress that used…

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

    PubMed Central

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

    2013-01-01

    Although daily social exchanges are important for well-being, it is unclear how different types of exchanges affect daily well-being, as well as which factors influence the way in which individuals react to their daily social encounters. The present study included a sample of 705 adults aged 31 to 91, and using Multilevel Modeling analyses investigated whether loneliness or age moderate the relationship between daily affect and daily social exchanges with family and friends. Results indicated differences between events involving family and those involving friends. Furthermore, lonelier individuals benefitted more from positive events than less lonely adults but were not more negatively reactive to negative events. Moreover, results suggested that older adults’ affect is more independent of both positive and negative social events compared to younger people. Implications are discussed for the importance of daily social exchanges, daily social stress vulnerability, and the influences of loneliness across middle and later adulthood. PMID:22950350

  11. 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.

  12. Comparison of daily and weekly precipitation sampling efficiencies using automatic collectors

    USGS Publications Warehouse

    Schroder, L.J.; Linthurst, R.A.; Ellson, J.E.; Vozzo, S.F.

    1985-01-01

    Precipitation samples were collected for approximately 90 daily and 50 weekly sampling periods at Finley Farm, near Raleigh, North Carolina from August 1981 through October 1982. Ten wet-deposition samplers (AEROCHEM METRICS MODEL 301) were used; 4 samplers were operated for daily sampling, and 6 samplers were operated for weekly-sampling periods. This design was used to determine if: (1) collection efficiences of precipitation are affected by small distances between the Universal (Belfort) precipitation gage and collector; (2) measurable evaporation loss occurs and (3) pH and specific conductance of precipitation vary significantly within small distances. Average collection efficiencies were 97% for weekly sampling periods compared with the rain gage. Collection efficiencies were examined by seasons and precipitation volume. Neither factor significantly affected collection efficiency. No evaporation loss was found by comparing daily sampling to weekly sampling at the collection site, which was classified as a subtropical climate. Correlation coefficients for pH and specific conductance of daily samples and weekly samples ranged from 0.83 to 0.99.Precipitation samples were collected for approximately 90 daily and 50 weekly sampling periods at Finley farm, near Raleigh, North Carolina from August 1981 through October 1982. Ten wet-deposition samplers were used; 4 samplers were operated for daily sampling, and 6 samplers were operated for weekly-sampling periods. This design was used to determine if: (1) collection efficiencies of precipitation are affected by small distances between the University (Belfort) precipitation gage and collector; (2) measurable evaporation loss occurs and (3) pH and specific conductance of precipitation vary significantly within small distances.

  13. The Effects of Adult Day Services on Family Caregivers’ Daily Stress, Affect, and Health: Outcomes From the Daily Stress and Health (DaSH) Study

    PubMed Central

    Zarit, Steven H.; Kim, Kyungmin; Femia, Elia E.; Almeida, David M.; Klein, Laura C.

    2014-01-01

    Purpose: We examine the effects of use of adult day service (ADS) by caregivers of individuals with dementia (IWD) on daily stressors, affect, and health symptoms. Participants were interviewed for 8 consecutive days. On some days, the IWD attended an ADS program and on the other days caregivers provide most or all of the care at home. Methods: Participants were 173 family caregivers of IWDs using an ADS program. Daily telephone interviews assessed care-related stressors, noncare stressors, positive events, affect, and health symptoms. Multilevel models with data nested within persons were used to examine effects of ADS use on daily stressor exposure, affect, and health symptoms. Results: Caregivers had lower exposure to care-related stressors on ADS days, more positive experiences, and more noncare stressors. ADS use lowered anger and reduced the impact of noncare stressors on depressive symptoms. Implications: The findings demonstrate that stressors on caregivers are partly lowered, and affect is improved on ADS days, which may provide protection against the effects of chronic stress associated with caregiving. PMID:23690056

  14. Maintenance of heartburn relief after step-down from twice-daily proton pump inhibitor to once-daily dexlansoprazole modified release.

    PubMed

    Fass, Ronnie; Inadomi, John; Han, Cong; Mody, Reema; O'Neil, Janet; Perez, M Claudia

    2012-03-01

    Many patients with gastroesophageal reflux disease (GERD) take a proton pump inhibitor (PPI) twice daily to control symptoms. Once-daily dexlansoprazole modified release (MR) has a dual-delayed release formulation, making it attractive for step-down management of patients whose symptoms are well controlled on twice-daily PPIs. We investigated whether step-down to once-daily dexlansoprazole controls heartburn in patients with GERD who were receiving twice-daily PPI therapy. Patients 18 years and older taking a twice-daily PPI for symptom control were enrolled (n = 178) in a single-blind, multicenter study; 163 patients completed the study and 142 patients met criteria for the efficacy analysis. During the 6-week screening and treatment periods, patients recorded the presence of heartburn symptoms twice daily in electronic diaries. Patients' heartburn was considered well controlled if they had an average of 1 symptom or fewer per week during the last 4 weeks of screening and treatment. After screening, qualified patients were switched to masked dexlansoprazole MR 30 mg and placebo for 6 weeks. The primary efficacy end point was the proportion of patients whose heartburn remained well controlled after step-down. GERD-related symptoms and quality of life (QOL) also were evaluated using the Patient Assessment of Upper Gastrointestinal Disorders Symptom Severity Index (PAGI-SYM) and the PAGI-QOL questionnaires, respectively. After step-down to once-daily dexlansoprazole MR 30 mg, heartburn remained well controlled in 88% of patients (125 of 142). These patients were able to maintain their GERD-related symptom severity and QOL, indicated by marginal changes in the PAGI-SYM and PAGI-QOL total and subscale scores, respectively. Most patients with GERD who take twice-daily PPI to control heartburn are able to successfully step down to once-daily dexlansoprazole 30 mg. Copyright © 2012 AGA Institute. Published by Elsevier Inc. All rights reserved.

  15. 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. Copyright © 2015 by the American Occupational Therapy Association, Inc.

  16. Conversion from twice-daily tacrolimus to once-daily extended release tacrolimus (LCPT): the phase III randomized MELT trial.

    PubMed

    Bunnapradist, S; Ciechanowski, K; West-Thielke, P; Mulgaonkar, S; Rostaing, L; Vasudev, B; Budde, K

    2013-03-01

    Phase III noninferiority trial examining efficacy and safety of converting stable renal transplant recipients from twice-daily tacrolimus to a novel extended-release once-daily tacrolimus formulation (LCPT) with a controlled agglomeration technology. Controls maintained tacrolimus twice daily. The primary efficacy endpoint was proportion of patients with efficacy failures (death, graft failure, locally read biopsy-proven acute rejection [BPAR], or loss to follow-up) within 12 months. Starting LCPT dose was 30% lower (15% for blacks) than preconversion tacrolimus dose; target trough levels were 4-15 ng/mL. A total of 326 patients were randomized; the mITT population (n = 162 each group) was similar demographically in the two groups. Mean daily dose of LCPT was significantly (p < 0.0001) lower than preconversion tacrolimus dose at each visit; mean trough levels between groups were similar. There were four efficacy failures in each group; safety outcomes were similar between groups. Frequency of premature study drug discontinuation was LCPT: 12% versus tacrolimus twice daily: 5% (p = 0.028). LCPT demonstrated noninferiority to tacrolimus twice daily in efficacy failure rates. LCPT may offer a safe and effective alternative for converting patients to a once-daily formulation. Compared to currently available tacrolimus formulation, LCPT requires lower doses to achieve target trough levels. © Copyright 2012 The American Society of Transplantation and the American Society of Transplant Surgeons.

  17. 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 account...

  18. 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

  19. A global dataset of sub-daily rainfall indices

    NASA Astrophysics Data System (ADS)

    Fowler, H. J.; Lewis, E.; Blenkinsop, S.; Guerreiro, S.; Li, X.; Barbero, R.; Chan, S.; Lenderink, G.; Westra, S.

    2017-12-01

    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. A new global sub-daily precipitation dataset has been constructed (data collection is ongoing). Metadata for each station has been calculated, detailing record lengths, missing data, station locations. A set of global hydroclimatic indices have been produced based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. This will provide a unique global data resource on sub-daily precipitation whose derived indices will be freely available to the wider scientific community.

  20. A Daily Analysis of Physical Activity and Satisfaction with Life in Emerging Adults

    PubMed Central

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

    2014-01-01

    Objective Subjective well-being has well-established positive health consequences. During emerging adulthood, from ages 18 to 25 years, people’s global evaluations of their well-being (i.e., satisfaction with life [SWL]) appear to worsen more than any other time in the adult lifespan, indicating that this population would benefit from strategies to enhance SWL. In these studies, we investigated top-down (i.e., time-invariant, trait-like) and bottom-up (i.e., time-varying, state-like) influences of physical activity (PA) on daily SWL. Methods Two daily diary studies lasting 8 days (N = 190) and 14 days (N = 63) were conducted with samples of emerging adults enrolled in college to evaluate relations between daily PA and SWL while controlling for established and plausible top-down and bottom-up influences on SWL. Results In both studies, multilevel models indicated that people reported greater SWL on days when they were more active (a within-person, bottom-up effect). Top-down effects of PA were not significant in either study. These findings were robust when we controlled for competing top-down influences (e.g., sex, personality traits, self-esteem, body mass index, mental health symptoms, fatigue) and bottom-up influences (e.g., daily self-esteem, daily mental health symptoms, daily fatigue). Conclusions We concluded that SWL was impacted by people’s daily PA rather than their trait level of PA over time. These findings extend evidence that PA is a health behavior with important consequences for daily well-being and should be considered when developing national policies to enhance SWL. PMID:23088171

  1. A STUDY ON TEMPORAL DISTRIBUTION OF FREIGHT TRANSPORTATION IN CONSIDERATION OF DAILY WORK-LIFE CYCLE

    NASA Astrophysics Data System (ADS)

    Kitaoka, Daiki; Hara, Hidetaka; Oeda, Yoshinao; Sumi, Tomonori

    As advanced freight service is demanded, the time related requirements fo r freight transportation becomes more and more significant. This study, focusing on temporal distribution of freight transportation responding to the travel time, developed a shipment departure time decision model for each item, aiming at quantitatively grasping social requirement in the time domain. The model takes account of the daily work cycle of both work cy cles of shippers and carriers along with the travel time. The proposed model has a similar structure as that derived from the previous studies taking account of the daily living cycle of individuals. This model properly reproduced temporal distribution of shipment departure time that changes depending on the length of necessary lead time for each item.

  2. Inferring frail life expectancies in Chicago from daily fluctuations in elderly mortality.

    PubMed

    Murray, Christian J; Lipfert, Frederick W

    2013-07-01

    Susceptible sub-populations with existing disease have exhibited stronger relationships between air quality and mortality in time-series studies, but their associated life expectancies have largely been overlooked. Murray and Nelson developed a new time-series model that estimated a small unobserved (frail) sub-population and their resulting life expectancies in Philadelphia, including environment relationships. As a further example in a different geographic area, we used this model with 1987-2000 daily mortality data in Chicago and found a stable frail population at risk of ∼900 persons with a mean life expectancy of ∼11 days; fewer than two daily deaths were associated with air pollution. We considered daily concentrations of CO, NO₂, O₃, PM₁₀ and SO₂, and found PM₁₀ and O₃ to have stronger associations with frail mortality. Our estimates of life expectancy and air pollution and temperature relationships are similar to those found in other studies that used different methods. Temperature was more important than air pollution during the 1995 heat wave, when mortality risks increased dramatically after 2 d exposure and life expectancies decreased to 3-5 d. Modeling this event separately had substantial effects on lagged mortality--air pollution relationships and the population at risk. The premises of the Murray-Nelson model were supported by simultaneously considering an additional subgroup of non-frail individuals; they contributed only ∼1% of total elderly deaths. We conclude that frail life expectancies estimated by the Murray-Nelson model are robust, and that under these conditions non-frail persons have little risk of acute mortality, with or without contributions from air pollution.

  3. Estimation of daily protein intake based on spot urine urea nitrogen concentration in chronic kidney disease patients.

    PubMed

    Kanno, Hiroko; Kanda, Eiichiro; Sato, Asako; Sakamoto, Kaori; Kanno, Yoshihiko

    2016-04-01

    Determination of daily protein intake in the management of chronic kidney disease (CKD) requires precision. Inaccuracies in recording dietary intake occur, and estimation from total urea excretion presents hurdles owing to the difficulty of collecting whole urine for 24 h. Spot urine has been used for measuring daily sodium intake and urinary protein excretion. In this cross-sectional study, we investigated whether urea nitrogen (UN) concentration in spot urine can be used to predict daily protein intake instead of the 24-h urine collection in 193 Japanese CKD patients (Stages G1-G5). After patient randomization into 2 datasets for the development and validation of models, bootstrapping was used to develop protein intake estimation models. The parameters for the candidate multivariate regression models were male gender, age, body mass index (BMI), diabetes mellitus, dyslipidemia, proteinuria, estimated glomerular filtration rate, serum albumin level, spot urinary UN and creatinine level, and spot urinary UN/creatinine levels. The final model contained BMI and spot urinary UN level. The final model was selected because of the higher correlation between the predicted and measured protein intakes r = 0.558 (95 % confidence interval 0.400, 0.683), and the smaller distribution of the difference between the measured and predicted protein intakes than those of the other models. The results suggest that UN concentration in spot urine may be used to estimate daily protein intake and that a prediction formula would be useful for nutritional control in CKD patients.

  4. A data fusion approach for mapping daily evapotranspiration at field scale

    USDA-ARS?s Scientific Manuscript database

    The capability for mapping water consumption over cropped landscapes on a daily and seasonal basis is increasingly relevant given forecasted scenarios of reduced water availability. Prognostic modeling of water losses to the atmosphere, or evapotranspiration (ET), at field or finer scales in agricul...

  5. Daily Mood Patterns and Bulimic Behaviors in the Natural Environment

    PubMed Central

    Crosby, Ross D.; Wonderlich, Stephen A.; Engel, Scott G.; Simonich, Heather; Smyth, Joshua; Mitchell, James E.

    2009-01-01

    Objective Negative affect has been purported to play an important role in the etiology and maintenance of bulimic behaviors. The objective of this study was to identify daily mood patterns in the natural environment exhibited by individuals with bulimia nervosa and to examine the relationship between these patterns and bulimic behaviors. Method One hundred thirty-three women aged 18–55 meeting DSM-IV criteria for bulimia nervosa were recruited through clinical referrals and community advertisements. Ecological momentary assessment was used to collect multiple ratings of negative affect, binge eating and purging each day for a two-week period using palmtop computers. Latent growth mixture modeling was used to identify daily mood patterns. Results Nine distinct daily mood patterns were identified. The highest rates of binge eating and purging episodes occurred on days characterized by stable high negative affect or increasing negative affect over the course of the day. Conclusions These findings support the conclusion that negative mood states are intimately tied to bulimic behaviors and may in fact precipitate such behavior. PMID:19152874

  6. New daily persistent headache.

    PubMed

    Rozen, Todd D

    2010-01-01

    New daily persistent headache (NDPH) is a unique form of chronic daily headache (CDH) which is marked by a daily headache from onset, typically occurring in individuals without a significant prior history of headaches. There are two subforms of NDPH: one which is self-limited and normally goes away without therapy, and a more chronic refractory form which is unresponsive to typical headache treatment strategies. The pathogenesis of NDPH is unknown but recent observations suggest a connection with cervical spine hypermobility and elevation of proinflammatory cytokines in the cerebrospinal fluid (CSF). Recognized triggers for NDPH include infection, stressful life events, and surgical procedures. Clinically, NDPH is characterized by continuous head pain of mild to severe intensity. Migrainous symptoms are common. The syndrome appears to affect women in their teens and 20s, while males develop NDPH later in life in their 50s or 60s. There are no recognized treatments for this condition, although treatment options will be discussed. Secondary mimics of NDPH will also be touched upon in this chapter. Copyright © 2011 Elsevier B.V. All rights reserved.

  7. Short daily exposure to hand-arm vibrations in Swedish car mechanics.

    PubMed

    Barregård, Lars

    2003-01-01

    The aim of the study was to examine the daily exposure times to hand-arm vibrations in Swedish car mechanics, to test a method for estimating the exposure time without observing the workers for whole days, and to use the results for predicting the prevalence of vibration-induced white fingers (VWF) by the ISO 5349-model. Six garages were surveyed. In each garage, 5-10 car mechanics were observed in random order every 30 seconds throughout working days. The daily exposure time for each mechanic was estimated from the fraction of the observations that the mechanic was exposed. A total of 51 mechanics were observed, most of them on two different working days, yielding estimates for 95 days. The median effective exposure time was 10 minutes per day (95% confidence interval 5-15 minutes, arithmetic mean 14 minutes, maximum 80 minutes), and most of the exposure time was attributable to fastening and loosening nuts. The within-worker and between-worker variability was high (total sigma2 0.99, geometric standard deviation of 2.7). Using the observed exposure time and data on vibration levels of the main tools in Swedish car mechanics (average weighted acceleration level of 3.5 m/s2), the model in ISO-standard 5349 would predict that only three percent of the car mechanics will suffer from VWF after 20 years of exposure. In contrast, a recent survey of VWF showed the prevalence to be 25 percent. The precision of the observation method was estimated and was found to be good for the group daily mean. On the individual level the precision was only acceptable if the daily exposure time was > or = 40 minutes. In conclusion, the daily exposure time was short and the vibration level was limited. Nevertheless, hand-arm vibrations cause VWF in a significant number of car mechanics. The method of observing workers intermittently seemed to work well.

  8. Accuracy assessment of NOAA gridded daily reference evapotranspiration for the Texas High Plains

    USGS Publications Warehouse

    Moorhead, Jerry; Gowda, Prasanna H.; Hobbins, Michael; Senay, Gabriel; Paul, George; Marek, Thomas; Porter, Dana

    2015-01-01

    The National Oceanic and Atmospheric Administration (NOAA) provides daily reference evapotranspiration (ETref) maps for the contiguous United States using climatic data from North American Land Data Assimilation System (NLDAS). This data provides large-scale spatial representation of ETref, which is essential for regional scale water resources management. Data used in the development of NOAA daily ETref maps are derived from observations over surfaces that are different from short (grass — ETos) or tall (alfalfa — ETrs) reference crops, often in nonagricultural settings, which carries an unknown discrepancy between assumed and actual conditions. In this study, NOAA daily ETos and ETrs maps were evaluated for accuracy, using observed data from the Texas High Plains Evapotranspiration (TXHPET) network. Daily ETos, ETrs and the climatic data (air temperature, wind speed, and solar radiation) used for calculating ETref were extracted from the NOAA maps for TXHPET locations and compared against ground measurements on reference grass surfaces. NOAA ETrefmaps generally overestimated the TXHPET observations (1.4 and 2.2 mm/day ETos and ETrs, respectively), which may be attributed to errors in the NLDAS modeled air temperature and wind speed, to which reference ETref is most sensitive. Therefore, a bias correction to NLDAS modeled air temperature and wind speed data, or adjustment to the resulting NOAA ETref, may be needed to improve the accuracy of NOAA ETref maps.

  9. Monitoring daily and sub-daily variations in crustal strain with seismic arrays

    NASA Astrophysics Data System (ADS)

    Mao, S.; Campillo, M.; van der Hilst, R. D.; Brenguier, F.; Hillers, G.

    2017-12-01

    We demonstrate that we can monitor deformation of the shallow crust (with hourly temporal resolution) directly with seismic waves, by measuring relative seismic wave speed changes (dv/v) due to relatively known periodical forcing (tides and changes in atmospheric temperature) at Piton de la Fournaise Volcano (PdF), La Réunion. We use ambient seismic noise recorded (for one month) at VolcArray, an experiment with three arrays of 49 vertical-component geophones deployed on a 7x7 grid of approximately 80 m spacing. Through noise-based coda wave interferometry we infer for each array the average relative changes in propagation speed of seismic waves (dv/v) as a function of time, which relate to temporal changes in medium properties within 100m depth. The variations in dv/v ( 0.05%) on time-scales longer than a day are best explained by effects of precipitation on pore pressure. In contrast, the (weaker) daily and sub-daily fluctuations of dv/v ( 0.01%) are likely to be caused by tidal and thermal effects. We verify that the inferred variations of dv/v are unrelated to spatiotemporal changes of noise wavefields. We further compare the power spectrum of dv/v with spectra of simulated tide-induced volumetric strain, temperature records, very broadband (VBB) seismograms, and borehole tilt records. In all five types of data, dominant peaks are found at around diurnal, semi-diurnal, and ter-diurnal frequencies. A comparison of phase and spectra of the data suggests that the tidal and thermal effects on dv/v are of similar magnitude but vary with frequency. Theoretical modeling of tide- and temperature-induced strain in different frequency bands agrees with the relative magnitude of the two effects on dv/v from passive monitoring.

  10. Variations in Daily Sleep Quality and Type 1 Diabetes Management in Late Adolescents

    PubMed Central

    Queen, Tara L.; Butner, Jonathan; Wiebe, Deborah; Berg, Cynthia A.

    2016-01-01

    Objective To determine how between- and within-person variability in perceived sleep quality were associated with adolescent diabetes management. Methods A total of 236 older adolescents with type 1 diabetes reported daily for 2 weeks on sleep quality, self-regulatory failures, frequency of blood glucose (BG) checks, and BG values. Average, inconsistent, and daily deviations in sleep quality were examined. Results Hierarchical linear models indicated that poorer average and worse daily perceived sleep quality (compared with one’s average) was each associated with more self-regulatory failures. Sleep quality was not associated with frequency of BG checking. Poorer average sleep quality was related to greater risk of high BG. Furthermore, inconsistent and daily deviations in sleep quality interacted to predict higher BG, with more consistent sleepers benefitting more from a night of high-quality sleep. Conclusions Good, consistent sleep quality during late adolescence may benefit diabetes management by reducing self-regulatory failures and risk of high BG. PMID:26994852

  11. Aging Parents' Daily Support Exchanges With Adult Children Suffering Problems.

    PubMed

    Huo, Meng; Graham, Jamie L; Kim, Kyungmin; Birditt, Kira S; Fingerman, Karen L

    2017-06-17

    When adult children incur life problems (e.g., divorce, job loss, health problems), aging parents generally report providing more frequent support and experiencing poorer well-being. Yet, it is unclear how adult children's problems may influence aging parents' daily support exchanges with these children or the parents' daily mood. Aging parents from the Family Exchanges Study Wave 2 (N = 207, Mage = 79.86) reported providing and receiving emotional support, practical support, and advice from each adult child each day for 7 days. Parents also rated daily positive and negative mood. Multilevel models showed that aging parents were more likely to provide emotional and practical support to adult children incurring life problems than children not suffering problems. Parents were also more likely to receive emotional support and advice from these children with problems. Further, parents reported less negative mood on days when providing practical support to children with problems. Examining daily support exchanges adds to our understanding of how children's problems influence parent-child ties in late life. Prior research suggests that children's problems upset parents. In this study, however, it appears that supporting adult children who suffer problems may alleviate aging parents' distress regarding such children. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. Prediction equation for estimating total daily energy requirements of special operations personnel.

    PubMed

    Barringer, N D; Pasiakos, S M; McClung, H L; Crombie, A P; Margolis, L M

    2018-01-01

    Special Operations Forces (SOF) engage in a variety of military tasks with many producing high energy expenditures, leading to undesired energy deficits and loss of body mass. Therefore, the ability to accurately estimate daily energy requirements would be useful for accurate logistical planning. Generate a predictive equation estimating energy requirements of SOF. Retrospective analysis of data collected from SOF personnel engaged in 12 different SOF training scenarios. Energy expenditure and total body water were determined using the doubly-labeled water technique. Physical activity level was determined as daily energy expenditure divided by resting metabolic rate. Physical activity level was broken into quartiles (0 = mission prep, 1 = common warrior tasks, 2 = battle drills, 3 = specialized intense activity) to generate a physical activity factor (PAF). Regression analysis was used to construct two predictive equations (Model A; body mass and PAF, Model B; fat-free mass and PAF) estimating daily energy expenditures. Average measured energy expenditure during SOF training was 4468 (range: 3700 to 6300) Kcal·d- 1 . Regression analysis revealed that physical activity level ( r  = 0.91; P  < 0.05) and body mass ( r  = 0.28; P  < 0.05; Model A), or fat-free mass (FFM; r  = 0.32; P  < 0.05; Model B) were the factors that most highly predicted energy expenditures. Predictive equations coupling PAF with body mass (Model A) and FFM (Model B), were correlated ( r  = 0.74 and r  = 0.76, respectively) and did not differ [mean ± SEM: Model A; 4463 ± 65 Kcal·d - 1 , Model B; 4462 ± 61 Kcal·d - 1 ] from DLW measured energy expenditures. By quantifying and grouping SOF training exercises into activity factors, SOF energy requirements can be predicted with reasonable accuracy and these equations used by dietetic/logistical personnel to plan appropriate feeding regimens to meet SOF nutritional requirements

  13. Reciprocal associations between family and peer conflict in adolescents' daily lives.

    PubMed

    Chung, Grace H; Flook, Lisa; Fuligni, Andrew J

    2011-01-01

    Using a daily diary method, this study assessed daily episodes of family and peer conflict among 578 adolescents in the 9th grade to examine potential bidirectional associations between the family and peer domains. Adolescents completed a daily diary checklist at the end of each day over a 14-day period to report events of conflict and their emotional states for a given day. Overall, the within-person models provided evidence for the bidirectional nature of family peer linkages across gender and ethnicity. Adolescents experienced more peer conflict on days in which they argued with parents or other family members, and vice versa. Effect of family conflict further spilled over into peer relationships the next day and 2 days later, whereas peer conflict predicted only the following day family conflict. Adolescents' emotional distress partially explained these short-term spillovers between family and peer conflict. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.

  14. Effect of Hochu-ekki-to (TJ-41), a Japanese Herbal Medicine, on Daily Activity in a Murine Model of Chronic Fatigue Syndrome

    PubMed Central

    2004-01-01

    We aimed to evaluate the effect of a Japanese herbal medicine, Hochu-ekki-to (TJ-41), on daily activity in a murine model of chronic fatigue syndrome (CFS). CFS was induced by repeated injection of Brucella abortus (BA) antigen every 2 weeks. TJ-41 was orally administered to mice in a dose of 500 mg/kg/day for 1 week before injecting BA and for 4 weeks thereafter. We evaluated daily running activity in mice receiving TJ-41 as compared with that in untreated mice. Survival of both mouse groups was also monitored during the observation period. Body weight (BW), spleen weight (SW), SW/ BW ratio and expression levels of interleukin-10 (IL-10) mRNA in spleen were determined in both groups at the time of sacrifice. The daily activity was significantly higher in the treated group than in the control. Two mice in the untreated group died 2 days after the second injection of BA, whereas no mice in the group treated with TJ-41 died. The SW and SW/BW ratio were significantly lower in the treated mice than in the control. Suppressed IL-10 mRNA levels were observed in the spleens of the mice treated with TJ-41. Our data suggest that Hochu-ekki-to might possess an inhibitory effect on the marked decrease in running activity following BA injection. PMID:15480446

  15. Improving fire season definition by optimized temporal modelling of daily human-caused ignitions.

    PubMed

    Costafreda-Aumedes, S; Vega-Garcia, C; Comas, C

    2018-07-01

    Wildfire suppression management is usually based on fast control of all ignitions, especially in highly populated countries with pervasive values-at-risk. To minimize values-at-risk loss by improving response time of suppression resources it is necessary to anticipate ignitions, which are mainly caused by people. Previous studies have found that human-ignition patterns change spatially and temporally depending on socio-economic activities, hence, the deployment of suppression resources along the year should consider these patterns. However, full suppression capacity is operational only within legally established fire seasons, driven by past events and budgets, which limits response capacity and increases damages out of them. The aim of this study was to assess the temporal definition of fire seasons from the perspective of human-ignition patterns for the case study of Spain, where people cause over 95% of fires. Humans engage in activities that use fire as a tool in certain periods within a year, and in locations linked to specific spatial factors. Geographic variables (population, infrastructures, physiography and land uses) were used as explanatory variables for human-ignition patterns. The changing influence of these geographic variables on occurrence along the year was analysed with day-by-day logistic regression models. Daily models were built for all the municipal units in the two climatic regions in Spain (Atlantic and Mediterranean Spain) from 2002 to 2014, and similar models were grouped within continuous periods, designated as ignition-based seasons. We found three ignition-based seasons in the Mediterranean region and five in the Atlantic zones, not coincidental with calendar seasons, but with a high degree of agreement with current legally designated operational fire seasons. Our results suggest that an additional late-winter-early-spring fire season in the Mediterranean area and the extension of this same season in the Atlantic zone should be re

  16. Estimated Short-Term Effects of Coarse Particles on Daily Mortality in Stockholm, Sweden

    PubMed Central

    Johansson, Christer; Forsberg, Bertil

    2011-01-01

    Background: Although serious health effects associated with particulate matter (PM) with aerodynamic diameter ≤ 10 μm (PM10) and ≤ 2.5 μm (PM2.5; fine fraction) are documented in many studies, the effects of coarse PM (PM2.5–10) are still under debate. Objective: In this study, we estimated the effects of short-term exposure of PM2.5–10 on daily mortality in Stockholm, Sweden. Method: We collected data on daily mortality for the years 2000 through 2008. Concentrations of PM10, PM2.5, ozone, and carbon monoxide were measured simultaneously in central Stockholm. We used additive Poisson regression models to examine the association between daily mortality and PM2.5–10 on the day of death and the day before. Effect estimates were adjusted for other pollutants (two-pollutant models) during different seasons. Results: We estimated a 1.68% increase [95% confidence interval (CI): 0.20%, 3.15%] in daily mortality per 10-μg/m3 increase in PM2.5–10 (single-pollutant model). The association with PM2.5–10 was stronger for November through May, when road dust is most important (1.69% increase; 95% CI: 0.21%, 3.17%), compared with the rest of the year (1.31% increase; 95% CI: –2.08%, 4.70%), although the difference was not statistically significant. When adjusted for other pollutants, particularly PM2.5, the effect estimates per 10 μg/m3 for PM2.5–10 decreased slightly but were still higher than corresponding effect estimates for PM2.5. Conclusions: Our analysis shows an increase in daily mortality associated with elevated urban background levels of PM2.5–10. Regulation of PM2.5–10 should be considered, along with actions to specifically reduce PM2.5–10 emissions, especially road dust suspension, in cities. PMID:22182596

  17. Daily Living Resources

    MedlinePlus

    ... PPMD. Click here to review PPMD’s policy on corporate support . Daily Living Resources PPMD Resource Fair Participants ... About PPMD ❯ Mission & Impact Staff & Board News History Finance & Operations Partners Media Contact us Get Involved ❯ Donate ...

  18. Access to cigarettes by daily smokers in Florida's public middle schools and high schools.

    PubMed

    Saunders, Charles

    2011-07-01

    Youth who smoke daily have diverse methods for obtaining cigarettes, which range from commercial sources to essentially black market transactions. This study examines access to cigarettes, attitudes toward tobacco, and the demographic characteristics of youth who are daily cigarette smokers. Biennial data from the Florida Youth Tobacco Survey, a representative sample of Florida public middle- and high-school students, were used. Daily smoking was categorized into ordinal categories of increasing intensity. Analysis was done with a logistic partial proportional odds model, which allowed the effects of the independent predictors to vary according to smoking intensity. The multivariate analysis revealed that males and females have different methods of obtaining cigarettes. Moreover, certain modes of access to cigarettes were related to daily smoking intensity. Males who obtained cigarettes from their parents or stole them from a store were much more likely to have a higher intensity of daily smoking. Females who gave someone money to buy their cigarettes or bought them from a person were more likely to smoke more cigarettes per day. Males, but not females, also perceived that increasing the number of cigarettes smoked per day provides social benefits in the form of more friends. Understanding how daily youth smokers obtain cigarettes is necessary if effective antitobacco policies are to be developed for these individuals. Daily youth smokers are at increased risk of becoming addicted to nicotine, making them more likely to transition to daily adult smoking.

  19. 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.

  20. Mitigating effects of vaccination on influenza outbreaks given constraints in stockpile size and daily administration capacity

    PubMed Central

    2011-01-01

    Background Influenza viruses are a major cause of morbidity and mortality worldwide. Vaccination remains a powerful tool for preventing or mitigating influenza outbreaks. Yet, vaccine supplies and daily administration capacities are limited, even in developed countries. Understanding how such constraints can alter the mitigating effects of vaccination is a crucial part of influenza preparedness plans. Mathematical models provide tools for government and medical officials to assess the impact of different vaccination strategies and plan accordingly. However, many existing models of vaccination employ several questionable assumptions, including a rate of vaccination proportional to the population at each point in time. Methods We present a SIR-like model that explicitly takes into account vaccine supply and the number of vaccines administered per day and places data-informed limits on these parameters. We refer to this as the non-proportional model of vaccination and compare it to the proportional scheme typically found in the literature. Results The proportional and non-proportional models behave similarly for a few different vaccination scenarios. However, there are parameter regimes involving the vaccination campaign duration and daily supply limit for which the non-proportional model predicts smaller epidemics that peak later, but may last longer, than those of the proportional model. We also use the non-proportional model to predict the mitigating effects of variably timed vaccination campaigns for different levels of vaccination coverage, using specific constraints on daily administration capacity. Conclusions The non-proportional model of vaccination is a theoretical improvement that provides more accurate predictions of the mitigating effects of vaccination on influenza outbreaks than the proportional model. In addition, parameters such as vaccine supply and daily administration limit can be easily adjusted to simulate conditions in developed and developing

  1. Changes in daily pollen concentration based on meteorological data and days after seasonal initiation - a case study for Japanese hop

    NASA Astrophysics Data System (ADS)

    Choe, H.; Kim, K. R.; Kim, M.; Han, M. J.; Cho, C.; Choi, B. C.

    2014-12-01

    Pollinosis causes various allergy symptoms such as seasonal rhinitis, asthma, and conjunctivitis (Min, 1991). Japanese hop (Humulus japonicus) is a major allergen in southern Gyonggi-do during the fall seasons (Park, 1998). So that it is needed to forecast the concentration of its pollens.For the germination of Japanese hop, a period of low temperature (<5C) followed by warm (~20C) and humid conditions is needed (Growing and Protecting New Zealand(2010)). The daily concentration of the pollens increases rapidly then decreases a few days afterward. In this study, the changes in daily pollen concentration were analyzed to yield a prediction model.As a result, a regression model was produced to forecast daily pollen concentration. It can be integrated into the daily pollinosis warning system of the Korea Meteorological Administration (KMA) and provide more accurate daily risk information.

  2. The impact of irritable bowel syndrome on daily functioning: Characterizing and understanding daily consequences of IBS.

    PubMed

    Ballou, S; Keefer, L

    2017-04-01

    Despite the well-documented economic and psychosocial burden of irritable bowel syndrome (IBS), few studies have focused on the impact of IBS on daily activities. This study aims to quantitate impairment in daily activities among IBS patients and to evaluate the relationship between impairment, IBS, quality of life, and psychiatric symptoms. A total of 179 participants meeting ROME-III criteria for IBS completed an online research survey evaluating the following variables: (i) the impact of IBS on daily activities, (ii) comorbid psychiatric diagnoses, (iii) symptom severity, (iv) quality of life, and (v) symptom-specific cognitive affective factors related to IBS. This sample reported a high degree of impairment due to IBS, with 76% of the sample reporting some degree of IBS-related impairment in at least five different domains of daily life. Rates of impairment were significantly higher for participants who met criteria for anxiety, depression, and/or panic disorder. This study contributes to existing literature by demonstrating a high level of daily impairment among patients with IBS, particularly those who meet criteria for anxiety, depression, and panic disorder. These findings support the importance of integrated psychosocial and medical care for IBS patients, and highlight the utility of evaluation and intervention for behavioral avoidance/impairment especially among those who exhibit signs or symptoms of psychiatric diagnoses. © 2016 John Wiley & Sons Ltd.

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

    PubMed

    Mushquash, Aislin R; Sherry, Simon B

    2013-04-01

    The perfectionism model of binge eating is an integrative model explaining why perfectionism is tied to binge eating. This study extended and tested this emerging model by proposing daughters' socially prescribed perfectionism (i.e., perceiving one's mother is harshly demanding perfection of oneself) and mothers' psychological control (i.e., a negative parenting style involving control and demandingness) contribute indirectly to daughters' binge eating by generating situations or experiences that trigger binge eating. These binge triggers include discrepancies (i.e., viewing oneself as falling short of one's mother's expectations), depressive affect (i.e., feeling miserable and sad), and dietary restraint (i.e., behaviors aimed at reduced caloric intake). This model was tested in 218 mother-daughter dyads studied using a mixed longitudinal and daily diary design. Daughters were undergraduate students. Results largely supported hypotheses, with bootstrapped tests of mediation suggesting daughters' socially prescribed perfectionism and mothers' psychological control contribute to binge eating through binge triggers. For undergraduate women who believe their mothers rigidly require them to be perfect and whose mothers are demanding and controlling, binge eating may provide a means of coping with or escaping from an unhealthy, unsatisfying mother-daughter relationship. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Daily magnesium intake and serum magnesium concentration among Japanese people.

    PubMed

    Akizawa, Yoriko; Koizumi, Sadayuki; Itokawa, Yoshinori; Ojima, Toshiyuki; Nakamura, Yosikazu; Tamura, Tarou; Kusaka, Yukinori

    2008-01-01

    The vitamins and minerals that are deficient in the daily diet of a normal adult remain unknown. To answer this question, we conducted a population survey focusing on the relationship between dietary magnesium intake and serum magnesium level. The subjects were 62 individuals from Fukui Prefecture who participated in the 1998 National Nutrition Survey. The survey investigated the physical status, nutritional status, and dietary data of the subjects. Holidays and special occasions were avoided, and a day when people are most likely to be on an ordinary diet was selected as the survey date. The mean (+/-standard deviation) daily magnesium intake was 322 (+/-132), 323 (+/-163), and 322 (+/-147) mg/day for men, women, and the entire group, respectively. The mean (+/-standard deviation) serum magnesium concentration was 20.69 (+/-2.83), 20.69 (+/-2.88), and 20.69 (+/-2.83) ppm for men, women, and the entire group, respectively. The distribution of serum magnesium concentration was normal. Dietary magnesium intake showed a log-normal distribution, which was then transformed by logarithmic conversion for examining the regression coefficients. The slope of the regression line between the serum magnesium concentration (Y ppm) and daily magnesium intake (X mg) was determined using the formula Y = 4.93 (log(10)X) + 8.49. The coefficient of correlation (r) was 0.29. A regression line (Y = 14.65X + 19.31) was observed between the daily intake of magnesium (Y mg) and serum magnesium concentration (X ppm). The coefficient of correlation was 0.28. The daily magnesium intake correlated with serum magnesium concentration, and a linear regression model between them was proposed.

  5. Treatment of Hypertension: Favourable Effect of the Twice-Daily Compared to the Once-Daily (Evening) Administration of Perindopril and Losartan.

    PubMed

    Szauder, Ipoly; Csajági, Eszter; Major, Zsuzsanna; Pavlik, Gabor; Ujhelyi, Gabriella

    2015-01-01

    Little is known about the effect of twice daily administration of same dose of ACE inhibitor and ARB on the diurnal/nocturnal blood pressure (BP) ratio. We aimed to assess the effect of two widely used long-acting drugs: perindopril and losartan in the treatment of hypertension comparing the once-daily (evening) vs. twice-daily (morning and evening) administration with the same daily doses. Untreated primary hypertensive patients without complaints (a total of 164: 65 men, 99 women, 55.7 ± 13.7 years of age, 41-41 patients per treated groups) were selected with non-dipper phenomenon, estimated by diurnal index (DI) <10%. The effect of evening (8 mg perindopril or 100 mg losartan) vs morning and evening (4-4 mg perindopril or 50-50 mg losartan) administration was determined on a 14-day treatment by ABPM. The mean BP, the percent time elevation index, and the hyperbaric impact decreased in both drug groups. Significant difference was observed in the DI in the case of twice-daily administration vs once-daily evening dosing. The twice-daily administration with the same daily dose of perindopril or losartan seems to be more effective compared to the once daily evening administration in eliminating the non-dipper phenomenon. According to some authors the non-dipping phenomenon increases cardiovascular risk, while others are of the opinion that the association of non-dipping with cardiovascular events does not necessarily mean that selective treatment of non-dipping improves cardiovascular outcomes. © 2015 S. Karger AG, Basel.

  6. The effects of adult day services on family caregivers' daily stress, affect, and health: outcomes from the Daily Stress and Health (DaSH) study.

    PubMed

    Zarit, Steven H; Kim, Kyungmin; Femia, Elia E; Almeida, David M; Klein, Laura C

    2014-08-01

    We examine the effects of use of adult day service (ADS) by caregivers of individuals with dementia (IWD) on daily stressors, affect, and health symptoms. Participants were interviewed for 8 consecutive days. On some days, the IWD attended an ADS program and on the other days caregivers provide most or all of the care at home. Participants were 173 family caregivers of IWDs using an ADS program. Daily telephone interviews assessed care-related stressors, noncare stressors, positive events, affect, and health symptoms. Multilevel models with data nested within persons were used to examine effects of ADS use on daily stressor exposure, affect, and health symptoms. Caregivers had lower exposure to care-related stressors on ADS days, more positive experiences, and more noncare stressors. ADS use lowered anger and reduced the impact of noncare stressors on depressive symptoms. The findings demonstrate that stressors on caregivers are partly lowered, and affect is improved on ADS days, which may provide protection against the effects of chronic stress associated with caregiving. © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. An improved bias correction method of daily rainfall data using a sliding window technique for climate change impact assessment

    NASA Astrophysics Data System (ADS)

    Smitha, P. S.; Narasimhan, B.; Sudheer, K. P.; Annamalai, H.

    2018-01-01

    Regional climate models (RCMs) are used to downscale the coarse resolution General Circulation Model (GCM) outputs to a finer resolution for hydrological impact studies. However, RCM outputs often deviate from the observed climatological data, and therefore need bias correction before they are used for hydrological simulations. While there are a number of methods for bias correction, most of them use monthly statistics to derive correction factors, which may cause errors in the rainfall magnitude when applied on a daily scale. This study proposes a sliding window based daily correction factor derivations that help build reliable daily rainfall data from climate models. The procedure is applied to five existing bias correction methods, and is tested on six watersheds in different climatic zones of India for assessing the effectiveness of the corrected rainfall and the consequent hydrological simulations. The bias correction was performed on rainfall data downscaled using Conformal Cubic Atmospheric Model (CCAM) to 0.5° × 0.5° from two different CMIP5 models (CNRM-CM5.0, GFDL-CM3.0). The India Meteorological Department (IMD) gridded (0.25° × 0.25°) observed rainfall data was considered to test the effectiveness of the proposed bias correction method. The quantile-quantile (Q-Q) plots and Nash Sutcliffe efficiency (NSE) were employed for evaluation of different methods of bias correction. The analysis suggested that the proposed method effectively corrects the daily bias in rainfall as compared to using monthly factors. The methods such as local intensity scaling, modified power transformation and distribution mapping, which adjusted the wet day frequencies, performed superior compared to the other methods, which did not consider adjustment of wet day frequencies. The distribution mapping method with daily correction factors was able to replicate the daily rainfall pattern of observed data with NSE value above 0.81 over most parts of India. Hydrological

  8. Pharmacokinetic study of once–daily versus twice-daily abacavir and lamivudine in HIV type-1-infected children aged 3–<36 months

    PubMed Central

    2013-01-01

    Background Once-daily dosing of abacavir and lamivudine has been approved for adults, but paediatric data are insufficient. We conducted a pharmacokinetic study of once-daily and twice-daily abacavir and lamivudine in children aged 3–<36 months. Methods Children with stable HIV type-1 (HIV-1) RNA levels after 12 weeks treatment with twice-daily abacavir (8 mg/kg) with or without lamivudine (4 mg/kg) underwent plasma pharmacokinetic sampling. Children then switched to once-daily abacavir (16 mg/kg) with or without lamivudine (8 mg/kg), and sampling was repeated 4 weeks later. The area under the plasma concentration–time curve over 24 h (AUC0–24) and the maximum concentration (Cmax) were compared using geometric mean ratios (GMRs); 90% confidence intervals (CIs) within the range of 0.80–1.25 were considered bioequivalent. Results A total of 18 children (4, 6 and 8 in the 3–<12, 12–<24 and 24–<36 month age ranges, respectively) provided pharmacokinetic data for abacavir (17 for lamivudine). The GMR of AUC0–24, once-daily versus twice-daily, was 1.07 (90% CI 0.92–1.23) for abacavir and 0.91 (90% CI 0.79–1.06) for lamivudine. Cmax almost doubled on once-daily versus twice-daily dosing: abacavir and lamivudine GMRs were 2.04 (90% CI 1.73–2.42) and 1.78 (90% CI 1.52–2.09), respectively. At baseline, 12, 24 and 48 weeks, 89%, 94%, 100% and 89% of children had HIV-1 RNA<400 copies/ml, respectively. Conclusions Bioequivalence was demonstrated on AUC0–24 between twice-daily and once-daily abacavir; very similar AUC0–24 values were seen for twice-daily and once-daily lamivudine. Given that viral load suppression rates were maintained, these data suggest that once-daily abacavir and lamivudine might be an option for children aged 3–<36 months. PMID:20516550

  9. Impact of daily mood, work hours, and iso-strain variables on self-reported health behaviors.

    PubMed

    Jones, Fiona; O'Connor, Daryl B; Conner, Mark; McMillan, Brian; Ferguson, Eamonn

    2007-11-01

    Four hundred and twenty-two employees completed daily diaries measuring positive affect, negative affect, work hours, and health behaviors (snacking, smoking, exercise, alcohol, caffeine consumption) on work days over a 4-week period. In addition, measures of job demands, job control, and social support (iso-strain variables) were completed on 1 occasion. Multilevel random coefficient modeling was used to examine relationships between the job characteristics, daily work variables, and self-reported health behaviors. Results indicated a more important role for within-person daily fluctuations than for between-persons variations in predicting health behaviors. Whereas negative affect was negatively related to health behavior for both men and women, work hours had negative impacts for women only. Iso-strain variables showed few main effects and a modest number of interactions with daily variables (mainly for men). Findings point to the limited impact of stable features of work design compared to the effects of daily work stressors on health behaviors. (c) 2007 APA

  10. Epidemiology of chronic daily headache.

    PubMed

    Pascual, J; Colás, R; Castillo, J

    2001-12-01

    Daily or near-daily headache is a widespread problem in clinical practice. The general term of chronic daily headache (CDH) encompasses those primary headaches presenting more than 15 days per month and lasting more than 4 hours per day. CDH includes transformed migraine (TM), chronic tension-type headache (CTTH), new daily persistent headache (NDPH), and hemicrania continua (HC). Around 40% of patients attending a specialized headache clinic meet CDH diagnostic criteria, of which 80% are women. In these clinics about 60% of patients suffer from TM, 20% from CTTH, and 20% meet NDPH criteria. Most, some 80%, overuse symptomatic medications. One should be very cautious on extrapolating these numbers to the general population. CDH prevalence in the general population seems to be around 4% to 5% (up to 8% to 9% for women). Regarding the prevalence of CDH subtypes, NDPH is rare (0.1%), whereas the prevalence of TM (1.5% to 2%) and CTTH (2.5% to 3%) is clearly higher. In contrast to data from specialized clinics, only around a quarter of CDH subjects in the general population overuse analgesics; the prevalence of CDH subjects with analgesic overuse being 1.1% to 1.9% of the general population. Most of these patients with analgesic overuse are TM patients.

  11. Temporal Relations in Daily-Reported Maternal Mood and Disruptive Child Behavior

    ERIC Educational Resources Information Center

    Elgar, Frank J.; Waschbusch, Daniel A.; McGrath, Patrick J.; Stewart, Sherry H.; Curtis, Lori J.

    2004-01-01

    Examined temporal relations between maternal mood and disruptive child behaviour using daily assessments of 30 mother-child dyads carried out over 8 consecutive weeks (623 pooled observations). Pooled time-series analyses showed synchronous fluctuation in child behaviour and maternal distress. Time-lagged models showed temporal relations between…

  12. Depression and pain impair daily functioning and quality of life in patients with major depressive disorder.

    PubMed

    Lin, Ching-Hua; Yen, Yung-Chieh; Chen, Ming-Chao; Chen, Cheng-Chung

    2014-09-01

    Depression and pain frequently occur together. The objective of this study was to investigate the effects of depression and pain on the impairment of daily functioning and quality of life (QOL) of depressed patients. We enrolled 131 acutely ill inpatients with major depressive disorder. Depression, pain, and daily functioning were assessed using the 17-item Hamilton Depression Rating Scale, the Short-Form 36 (SF-36) Body Pain Index, and the Work and Social Adjustment Scale. Health-related QOL was assessed using three primary domains of the SF-36: social functioning, vitality, and general health perceptions. Pearson׳s correlation and structural equation modeling were used to examine relationships among the study variables. Five models were proposed. In all, 129 patients completed all the measures. Model 5, both depression and pain impaired daily functioning and QOL, was the most fitted structural equation model (χ(2)=9.2, df=8, p=0.33, GFI=0.98, AGFI=0.94, TLI=0.99, CFI=0.99, RMSEA=0.03). The correlation between pain and depression was weak (r=-0.27, z=-2.95, p=0.003). This was a cross-sectional study with a small sample size. Depression and pain exert a direct influence on the impairment of daily functioning and QOL of depressed patients; this impairment could be expected regardless of increased pain, depression, or both pain and depression. Pain had a somewhat separate entity from depression. Copyright © 2014. Published by Elsevier B.V.

  13. [Risk of deaths from cardiovascular diseases in Polish urban population associated with changes in maximal daily temperature].

    PubMed

    Rabczenko, Daniel; Wojtyniak, Bogdan; Kuchcik, Magdalena; Seroka, Wojciech

    2009-01-01

    The paper presents results of analysis of short-term effect of changes in maximal daily temperature on daily mortality from cardiovascular diseases in warm season in years 1999-2006. Analysis was carried out in six large Polish cities--Katowice, Kraków, Łódź, Poznań, Warszawa and Wrocław. Generalized additive models were used in the analysis. Potential confounding factors--long term changes of mortality, day of week and other meteorological factors (atmospheric pressure, humidity, mean wind speed) were taken into account during model building process. Analysis was done for two age groups--0-69 and 70 years and older. Significant, positive association between daily maximal temperature and risk of death from cardiovascular diseases was found only in older age group.

  14. Service workers' chain reactions to daily customer mistreatment: Behavioral linkages, mechanisms, and boundary conditions.

    PubMed

    Chi, Nai-Wen; Yang, Jixia; Lin, Chia-Ying

    2018-01-01

    Drawing on the stressor-emotion model, we examine how customer mistreatment can evoke service workers' passive forms of deviant behaviors (i.e., work withdrawal behavior [WWB]) and negative impacts on their home life (i.e., work-family conflict [WFC]), and whether individuals' core self-evaluations and customer service training can buffer the negative effects of customer mistreatment. Using the experience sampling method, we collect daily data from 77 customer service employees for 10 consecutive working days, yielding 546 valid daily responses. The results show that daily customer mistreatment increases service workers' daily WWB and WFC through negative emotions. Furthermore, employees with high core self-evaluations and employees who received customer service training are less likely to experience negative emotions when faced with customer mistreatment, and thus are less likely to engage in WWB or provoke WFC. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

    NASA Astrophysics Data System (ADS)

    Hiebl, Johann; Frei, Christoph

    2018-04-01

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

  16. Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

    NASA Astrophysics Data System (ADS)

    Leonarduzzi, Elena; Molnar, Peter; McArdell, Brian W.

    2017-08-01

    A high-resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity-duration ID curves and validated their performance. The best predictive performance was obtained by the intensity-duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country-wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high-quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack-knife and cross-validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

  17. Realization of daily evapotranspiration in arid ecosystems based on remote sensing techniques

    NASA Astrophysics Data System (ADS)

    Elhag, Mohamed; Bahrawi, Jarbou A.

    2017-03-01

    Daily evapotranspiration is a major component of water resources management plans. In arid ecosystems, the quest for an efficient water budget is always hard to achieve due to insufficient irrigational water and high evapotranspiration rates. Therefore, monitoring of daily evapotranspiration is a key practice for sustainable water resources management, especially in arid environments. Remote sensing techniques offered a great help to estimate the daily evapotranspiration on a regional scale. Existing open-source algorithms proved to estimate daily evapotranspiration comprehensively in arid environments. The only deficiency of these algorithms is the course scale of the used remote sensing data. Consequently, the adequate downscaling algorithm is a compulsory step to rationalize an effective water resources management plan. Daily evapotranspiration was estimated fairly well using an Advance Along-Track Scanner Radiometer (AATSR) in conjunction with (MEdium Resolution Imaging Spectrometer) MERIS data acquired in July 2013 with 1 km spatial resolution and 3 days of temporal resolution under a surface energy balance system (SEBS) model. Results were validated against reference evapotranspiration ground truth values using standardized Penman-Monteith method with R2 of 0.879. The findings of the current research successfully monitor turbulent heat fluxes values estimated from AATSR and MERIS data with a temporal resolution of 3 days only in conjunction with reliable meteorological data. Research verdicts are necessary inputs for a well-informed decision-making processes regarding sustainable water resource management.

  18. Progress report on daily flow-routing simulation for the Carson River, California and Nevada

    USGS Publications Warehouse

    Hess, G.W.

    1996-01-01

    A physically based flow-routing model using Hydrological Simulation Program-FORTRAN (HSPF) was constructed for modeling streamflow in the Carson River at daily time intervals as part of the Truckee-Carson Program of the U.S. Geological Survey (USGS). Daily streamflow data for water years 1978-92 for the mainstem river, tributaries, and irrigation ditches from the East Fork Carson River near Markleeville and West Fork Carson River at Woodfords down to the mainstem Carson River at Fort Churchill upstream from Lahontan Reservoir were obtained from several agencies and were compiled into a comprehensive data base. No previous physically based flow-routing model of the Carson River has incorporated multi-agency streamflow data into a single data base and simulated flow at a daily time interval. Where streamflow data were unavailable or incomplete, hydrologic techniques were used to estimate some flows. For modeling purposes, the Carson River was divided into six segments, which correspond to those used in the Alpine Decree that governs water rights along the river. Hydraulic characteristics were defined for 48 individual stream reaches based on cross-sectional survey data obtained from field surveys and previous studies. Simulation results from the model were compared with available observed and estimated streamflow data. Model testing demonstrated that hydraulic characteristics of the Carson River are adequately represented in the models for a range of flow regimes. Differences between simulated and observed streamflow result mostly from inadequate data characterizing inflow and outflow from the river. Because irrigation return flows are largely unknown, irrigation return flow percentages were used as a calibration parameter to minimize differences between observed and simulated streamflows. Observed and simulated streamflow were compared for daily periods for the full modeled length of the Carson River and for two major subreaches modeled with more detailed input data

  19. 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.…

  20. Measurement of time processing ability and daily time management in children with disabilities.

    PubMed

    Janeslätt, Gunnel; Granlund, Mats; Kottorp, Anders

    2009-01-01

    Improvement is needed in methods for planning and evaluating interventions designed to facilitate daily time management for children with intellectual disability, Asperger syndrome, or other developmental disorders. The aim of this study was to empirically investigate the hypothesized relation between children's time processing ability (TPA), daily time management, and self-rated autonomy. Such a relationship between daily time management and TPA may support the idea that TPA is important for daily time management and that children with difficulties in TPA might benefit from intervention aimed at improving daily time management. Participants were children aged 6 to 11 years with dysfunctions such as attention-deficit/hyperactivity disorder, autism, or physical or intellectual disabilities (N = 118). TPA was measured with the instrument KaTid. All data were transformed to interval measures using applications of Rasch models and then further analysed with correlation and regression analysis. The results demonstrate a moderate significant relation between the parents' ratings of daily time management and TPA of the children, and between the self-rating of autonomy and TPA. There was also a significant relation between self-ratings of autonomy and the parents' rating of the children's daily time management. Parents' ratings of their children's daily time management explain 25% of the variation in TPA, age of the children explains 22%, while the child's self-rating of autonomy can explain 9% of the variation in TPA. The three variables together explain 38% of the variation in TPA. The results indicate the viability of the instrument for assessing TPA also in children with disabilities and that the ability measured by KaTid is relevant for daily time management. TPA seems to be a factor for children's daily time management that needs to be taken into consideration when planning and evaluating interventions designed to facilitate everyday functioning for children with

  1. Elections Have Consequences for Student Mental Health: An Accidental Daily Diary Study.

    PubMed

    Roche, Michael J; Jacobson, Nicholas C

    2018-01-01

    Polling suggested that the 2016 United States presidential election affected citizens' mood and stress levels. Yet, polling often fails to employ repeated measurement designs that can capture pre- and post-levels of change within the same person. In this study, undergraduate students ( N = 85) completed a 14-day daily diary where mood, stress, and mental health outcomes were assessed before and after the election. Multilevel modeling revealed an immediate upsurge in anxiety, stress, and poor sleep quality the day after the election, followed by a recovery period indicating these effects were short-lived. Other reactions (anger, fear, marginalization, and experiencing discrimination) evidenced a significant upsurge without a significant recovery. We consider how daily diary research designs like this one could be integrated into college settings to inform counseling center resource allocation, and we also comment on the promise of the daily diary methodology for political research.

  2. Reciprocal Associations between Family and Peer Conflict in Adolescents’ Daily Lives1

    PubMed Central

    Chung, Grace H.; Fuligni, Andrew J.

    2012-01-01

    Using a daily diary method, this study assessed daily episodes of family and peer conflict among 578 adolescents in the ninth grade in order to examine potential bidirectional associations between the family and peer domains. Adolescents completed a daily diary checklist at the end of each day over a fourteen day period to report events of conflict and their emotional states for a given day. Overall, our within-person models provided evidence for the bidirectional nature of family-peer linkages across gender and ethnicity. Adolescents experienced more peer conflict on days in which they argued with parents or other family members, and vice versa. Effect of family conflict further spilled over into peer relationships the next day and two days later, whereas peer conflict predicted only the following day family conflict. Adolescents’ emotional distress partially explained these short term spillovers between family and peer conflict. PMID:21793820

  3. Self-Regulatory Strategies in Daily Life: Selection, Optimization, and Compensation and Everyday Memory Problems

    PubMed Central

    Stephanie, Robinson; Margie, Lachman; Elizabeth, Rickenbach

    2015-01-01

    The effective use of self-regulatory strategies, such as selection, optimization, and compensation (SOC) requires resources. However, it is theorized that SOC use is most advantageous for those experiencing losses and diminishing resources. The present study explored this seeming paradox within the context of limitations or constraints due to aging, low cognitive resources, and daily stress in relation to everyday memory problems. We examined whether SOC usage varied by age and level of constraints, and if the relationship between resources and memory problems was mitigated by SOC usage. A daily diary paradigm was used to explore day-to-day fluctuations in these relationships. Participants (n=145, ages 22 to 94) completed a baseline interview and a daily diary for seven consecutive days. Multilevel models examined between- and within-person relationships between daily SOC use, daily stressors, cognitive resources, and everyday memory problems. Middle-aged adults had the highest SOC usage, although older adults also showed high SOC use if they had high cognitive resources. More SOC strategies were used on high stress compared to low stress days. Moreover, the relationship between daily stress and memory problems was buffered by daily SOC use, such that on high-stress days, those who used more SOC strategies reported fewer memory problems than participants who used fewer SOC strategies. The paradox of resources and SOC use can be qualified by the type of resource-limitation. Deficits in global resources were not tied to SOC usage or benefits. Conversely, under daily constraints tied to stress, the use of SOC increased and led to fewer memory problems. PMID:26997686

  4. 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

  5. Daily disposable contact lens prescribing around the world.

    PubMed

    Efron, Nathan; Morgan, Philip B; Helland, Magne; Itoi, Motozumi; Jones, Deborah; Nichols, Jason J; van der Worp, Eef; Woods, Craig A

    2010-10-01

    Daily disposable contact lenses were introduced into the market 16 years ago. Data that we have gathered from annual contact lens fitting surveys conducted in Australia, Canada, Japan, The Netherlands, Norway, the UK and the USA between 2000 and 2008 indicates an overall increase in daily disposable lens fitting during this period. Daily disposable lenses are especially popular in Japan, Norway and the UK. There is a trend for these lenses to be fitted on a part-time basis. Males are over-represented in daily disposable lens fitting-a trend that is especially evident in Canada. Daily disposable lens wearers are about two years younger than wearers of reusable lenses in Japan and The Netherlands. The convenience and health benefits of daily disposable lenses are expected to fuel continued growth in this sector. Copyright (c) 2010 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.

  6. Forecasting daily lake levels using artificial intelligence approaches

    NASA Astrophysics Data System (ADS)

    Kisi, Ozgur; Shiri, Jalal; Nikoofar, Bagher

    2012-04-01

    Accurate prediction of lake-level variations is important for planning, design, construction, and operation of lakeshore structures and also in the management of freshwater lakes for water supply purposes. In the present paper, three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals. The measurements at the Lake Iznik in Western Turkey, for the period of January 1961-December 1982, were used for training, testing, and validating the employed models. The results obtained by the GEP approach indicated that it performs better than ANFIS and ANNs in predicting lake-level variations. A comparison was also made between these artificial intelligence approaches and convenient autoregressive moving average (ARMA) models, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models.

  7. Feeling old today? Daily health, stressors, and affect explain day-to-day variability in subjective age.

    PubMed

    Kotter-Grühn, Dana; Neupert, Shevaun D; Stephan, Yannick

    2015-01-01

    Subjective age is an important correlate of health, well-being, and longevity. So far, little is known about short-term variability in subjective age and the circumstances under which individuals feel younger/older in daily life. This study examined whether (a) older adults' felt age fluctuates on a day-to-day basis, (b) daily changes in health, stressors, and affect explain fluctuations in felt age, and (c) the daily associations between felt age and health, stressors, or affect are time-ordered. Using an eight-day daily diary approach, N = 43 adults (60-96 years, M = 74.65, SD = 8.19) filled out daily questionnaires assessing subjective age, health, daily stressors, and affect. Data were analysed using multilevel modelling. Subjective age, health, daily stressors, affect. Intra-individual variability in felt age was not explained by time but by short-term variability in other variables. Specifically, on days when participants experienced more than average health problems, stress, or negative affect they felt older than on days with average health, stress, or negative affect. No time-ordered effects were found. Bad health, many stressors, and negative affective experiences constitute circumstances under which older adults feel older than they typically do. Thus, daily measures of subjective age could be markers of health and well-being.

  8. An alternative method for determining daily bladder perception.

    PubMed

    Erdem, Erim; Karazindiyanoglu, Sinan; Ulger, Suleyman

    2010-01-01

    To avoid the unphysiologic nature of cystometry, we searched a new tool for evaluating bladder perceptions. The study group consisted of 25 (14 girls and 11 boys) primary monosymptomatic enuretic children with a mean age of 11 (range 8-16). Four children were excluded due to neuromuscular dysfunctions of the bladder, which was demonstrated with the help of cystometry. All children filled a voiding chart 3 times daily to record the duration elapsed till normal desire (ND(daily)) and strong desire (SD(daily)). During cystometry, the amounts of infused medium (cystometric ND(ml) and cystometric SD(ml)) and the duration (cystometric ND(sec) and cystometric SD(sec)), till ND and SD were perceived and recorded. Mean cystometric ND(ml) was 209.9 +/- 107.2 and ND(sec), 318.1 +/- 135.5, whereas mean cystometric SD(ml) was 273.0 +/- 103.1 and SD(sec), 415.7 +/- 136.8. To evaluate the reliability of elapsed time instead of milliliters, as a parameter, cystometric ND/SD values were calculated and a strong correlation was found between the 2 (ND/SD(sec) = 0.77 +/- 0.19 and ND/SD(ml) = 0.77 +/- 0.19, r = 0.9795, P = .000). Although there was a strong correlation between 3 ND(daily) (r = 0.9576, P = .000), between 3 SD(daily) (r = 0.9706, P = .000), and 3 ND/SD(daily) (r = 0.8706, P = .000), no significant correlation was determined between mean ND(daily) and cystometric ND(sec) (r = 0.3410, P = .2032), and also between mean SD(daily) and cystometric SD(sec) (r = 0.2740, P = .2402). Daily durations of sensations do not correlate with those perceived during cystometry. However, as the results of 3 consecutive daily recordings have a strong correlation, comparison of the reliability of these methods is still needed. 2010 Elsevier Inc. All rights reserved.

  9. Indirect effect of financial strain on daily cortisol output through daily negative to positive affect index in the Coronary Artery Risk Development in Young Adults Study.

    PubMed

    Puterman, Eli; Haritatos, Jana; Adler, Nancy E; Sidney, Steve; Schwartz, Joseph E; Epel, Elissa S

    2013-12-01

    Daily affect is important to health and has been linked to cortisol. The combination of high negative affect and low positive affect may have a bigger impact on increasing HPA axis activity than either positive or negative affect alone. Financial strain may both dampen positive affect as well as increase negative affect, and thus provides an excellent context for understanding the associations between daily affect and cortisol. Using random effects mixed modeling with maximum likelihood estimation, we examined the relationship between self-reported financial strain and estimated mean daily cortisol level (latent cortisol variable), based on six salivary cortisol assessments throughout the day, and whether this relationship was mediated by greater daily negative to positive affect index measured concurrently in a sample of 776 Coronary Artery Risk Development in Young Adults (CARDIA) Study participants. The analysis revealed that while no total direct effect existed for financial strain on cortisol, there was a significant indirect effect of high negative affect to low positive affect, linking financial strain to elevated cortisol. In this sample, the effects of financial strain on cortisol through either positive affect or negative affect alone were not significant. A combined affect index may be a more sensitive and powerful measure than either negative or positive affect alone, tapping the burden of chronic financial strain, and its effects on biology. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. 1 CFR 5.6 - Daily publication.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 1 General Provisions 1 2011-01-01 2011-01-01 false Daily publication. 5.6 Section 5.6 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER GENERAL § 5.6 Daily publication. There shall be an edition of the Federal Register published for each official Federal working day...

  11. 1 CFR 5.6 - Daily publication.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 1 General Provisions 1 2010-01-01 2010-01-01 false Daily publication. 5.6 Section 5.6 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER GENERAL § 5.6 Daily publication. There shall be an edition of the Federal Register published for each official Federal working day...

  12. Children's Daily Routines during Kindergarten Transition

    ERIC Educational Resources Information Center

    Wildenger, Leah K.; McIntyre, Laura Lee; Fiese, Barbara H.; Eckert, Tanya L.

    2008-01-01

    Routines are an important feature of family life and functioning in families with young children. Common daily routines such as dinnertime, bedtime, and waking activities are powerful organizers of family behavior and may be instrumental to children and families during times of transition, such as elementary school entry. Daily routines were…

  13. 1 CFR 5.6 - Daily publication.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 1 General Provisions 1 2013-01-01 2012-01-01 true Daily publication. 5.6 Section 5.6 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER GENERAL § 5.6 Daily publication. There shall be an edition of the Federal Register published for each official Federal working day...

  14. 1 CFR 5.6 - Daily publication.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 1 General Provisions 1 2012-01-01 2012-01-01 false Daily publication. 5.6 Section 5.6 General Provisions ADMINISTRATIVE COMMITTEE OF THE FEDERAL REGISTER THE FEDERAL REGISTER GENERAL § 5.6 Daily publication. There shall be an edition of the Federal Register published for each official Federal working day...

  15. 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...

  16. Is standard deviation of daily PM2.5 concentration associated with respiratory mortality?

    PubMed

    Lin, Hualiang; Ma, Wenjun; Qiu, Hong; Vaughn, Michael G; Nelson, Erik J; Qian, Zhengmin; Tian, Linwei

    2016-09-01

    Studies on health effects of air pollution often use daily mean concentration to estimate exposure while ignoring daily variations. This study examined the health effects of daily variation of PM2.5. We calculated daily mean and standard deviations of PM2.5 in Hong Kong between 1998 and 2011. We used a generalized additive model to estimate the association between respiratory mortality and daily mean and variation of PM2.5, as well as their interaction. We controlled for potential confounders, including temporal trends, day of the week, meteorological factors, and gaseous air pollutants. Both daily mean and standard deviation of PM2.5 were significantly associated with mortalities from overall respiratory diseases and pneumonia. Each 10 μg/m(3) increment in daily mean concentration at lag 2 day was associated with a 0.61% (95% CI: 0.19%, 1.03%) increase in overall respiratory mortality and a 0.67% (95% CI: 0.14%, 1.21%) increase in pneumonia mortality. And a 10 μg/m(3) increase in standard deviation at lag 1 day corresponded to a 1.40% (95% CI: 0.35%, 2.46%) increase in overall respiratory mortality, and a 1.80% (95% CI: 0.46%, 3.16%) increase in pneumonia mortality. We also observed a positive but non-significant synergistic interaction between daily mean and variation on respiratory mortality and pneumonia mortality. However, we did not find any significant association with mortality from chronic obstructive pulmonary diseases. Our study suggests that, besides mean concentration, the standard deviation of PM2.5 might be one potential predictor of respiratory mortality in Hong Kong, and should be considered when assessing the respiratory effects of PM2.5. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Wildfire air pollution and daily mortality in a large urban area.

    PubMed

    Vedal, Sverre; Dutton, Steven J

    2006-09-01

    Unusual air pollution episodes, such as when smoke from wildfires covers a large urban area, can be used to attempt to detect associations between short-term increases in particulate matter (PM) concentrations and subsequent mortality without relying on the sophisticated statistical models that are typically required in the absence of such episodes. The objective of this study was to explore whether acute increases in PM concentrations from wildfire smoke cause acute increases in daily mortality. The temporal patterns of daily nonaccidental deaths and daily cardiorespiratory deaths for June of 2002 in the Denver metropolitan area were examined and compared to those in two nearby counties in Colorado that were not affected by the wildfire smoke and to daily deaths in Denver in June of 2001. Abrupt increases in PM concentrations in Denver occurred on 2 days in June of 2002 as a result of wildfire smoke drifting over the Denver area. Small peaks in mortality corresponded to both of the PM peaks, but the first mortality peak also corresponded to a peak of mortality in the control counties, and cardiorespiratory deaths began to increase on the day before the second peak. Further, there was no detectable increase in cardiorespiratory deaths in the hours immediately following the PM peaks. Although the findings from this study do not rule out the possibility of small increases in mortality due to abrupt and dramatic increases in PM concentrations from wildfire smoke, in a population of over 2 million people no perceptible increases in daily mortality could be attributed to such events.

  18. Daily Weather and Children's Physical Activity Patterns.

    PubMed

    Remmers, Teun; Thijs, Carel; Timperio, Anna; Salmon, J O; Veitch, Jenny; Kremers, Stef P J; Ridgers, Nicola D

    2017-05-01

    Understanding how the weather affects physical activity (PA) may help in the design, analysis, and interpretation of future studies, especially when investigating PA across diverse meteorological settings and with long follow-up periods. The present longitudinal study first aims to examine the influence of daily weather elements on intraindividual PA patterns among primary school children across four seasons, reflecting day-to-day variation within each season. Second, we investigate whether the influence of weather elements differs by day of the week (weekdays vs weekends), gender, age, and body mass index. PA data were collected by ActiGraph accelerometers for 1 wk in each of four school terms that reflect each season in southeast Australia. PA data from 307 children (age range 8.7-12.8 yr) were matched to daily meteorological variables obtained from the Australian Government's Bureau of Meteorology (maximum temperature, relative humidity, solar radiation, day length, and rainfall). Daily PA patterns and their association with weather elements were analyzed using multilevel linear mixed models. Temperature was the strongest predictor of moderate and vigorous PA, followed by solar radiation and humidity. The relation with temperature was curvilinear, showing optimum PA levels at temperatures between 20°C and 22°C. Associations between weather elements on PA did not differ by gender, child's age, or body mass index. This novel study focused on the influence of weather elements on intraindividual PA patterns in children. As weather influences cannot be controlled, knowledge of its effect on individual PA patterns may help in the design of future studies, interpretation of their results, and translation into PA promotion.

  19. Modelling average maximum daily temperature using r largest order statistics: An application to South African data

    PubMed Central

    2018-01-01

    Natural hazards (events that may cause actual disasters) are established in the literature as major causes of various massive and destructive problems worldwide. The occurrences of earthquakes, floods and heat waves affect millions of people through several impacts. These include cases of hospitalisation, loss of lives and economic challenges. The focus of this study was on the risk reduction of the disasters that occur because of extremely high temperatures and heat waves. Modelling average maximum daily temperature (AMDT) guards against the disaster risk and may also help countries towards preparing for extreme heat. This study discusses the use of the r largest order statistics approach of extreme value theory towards modelling AMDT over the period of 11 years, that is, 2000–2010. A generalised extreme value distribution for r largest order statistics is fitted to the annual maxima. This is performed in an effort to study the behaviour of the r largest order statistics. The method of maximum likelihood is used in estimating the target parameters and the frequency of occurrences of the hottest days is assessed. The study presents a case study of South Africa in which the data for the non-winter season (September–April of each year) are used. The meteorological data used are the AMDT that are collected by the South African Weather Service and provided by Eskom. The estimation of the shape parameter reveals evidence of a Weibull class as an appropriate distribution for modelling AMDT in South Africa. The extreme quantiles for specified return periods are estimated using the quantile function and the best model is chosen through the use of the deviance statistic with the support of the graphical diagnostic tools. The Entropy Difference Test (EDT) is used as a specification test for diagnosing the fit of the models to the data.

  20. Daily positive events and diurnal cortisol rhythms: Examination of between-person differences and within-person variation.

    PubMed

    Sin, Nancy L; Ong, Anthony D; Stawski, Robert S; Almeida, David M

    2017-09-01

    Growing evidence from field studies has linked daily stressors to dysregulated patterns of diurnal cortisol. Less is known about whether naturally-occurring positive events in everyday life are associated with diurnal cortisol. The objectives of this study were to evaluate daily positive events as predictors of between-person differences and within-person (day-to-day) variations in diurnal cortisol parameters, in addition to daily positive events as buffers against the associations between daily stressors and cortisol. In the National Study of Daily Experiences, 1657 adults ages 33-84 (57% female) reported daily experiences during telephone interviews on 8 consecutive evenings. Saliva samples were collected 4 times per day on 4 interview days and assayed for cortisol. Multilevel models were used to estimate associations of daily positive events with cortisol awakening response (CAR), diurnal cortisol slope, and area under the curve (AUC). At the between-person level, people who experienced more frequent positive events exhibited a steeper diurnal cortisol slope, controlling for daily stressors, daily affect, and other covariates. At the within-person level, positive events in the morning (but not prior-night or afternoon/evening events) predicted steeper decline in cortisol across that day; positive events were also marginally associated with lower same-day AUC. Associations were not mediated by daily positive affect, and positive events did not buffer against stressor-related cortisol alterations. These findings indicate that individual differences and day-to-day variations in daily positive events are associated with diurnal cortisol patterns, independent of stressors and affect. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Comparing 3-month recall to daily reporting of sexual behaviours.

    PubMed

    Mark, Kristen P; Smith, Rachel V; Young, April M; Crosby, Richard

    2017-05-01

    This study aimed to examine discrepancies between self-report methods and methodological issues related to sexual risk taking. We examined sexual behaviour assessed via 3-month electronic recall and by daily electronic reporting among a large cohort of patients attending STI clinics. STI clinic attenders (N= 628) aged 15 to 60 years reported on demographic information (at baseline), penile-vaginal sex acts, condom-unprotected penile-vaginal sex and STI history using 3-month recall and daily reports. Additionally, interviewer-participant match related to race and gender, as well as study site were considered as covariates. Concordance between recall and daily reports on penile-vaginal sex was moderately strong (Spearman's r (rs)=0.62; p<0.001). Comparison for reports for condom-unprotected penile-vaginal sex resulted in a correlation coefficient of 0.61 (p<0.001), also indicating moderately strong agreement between the two methods. Two generalised logit models were conducted to explain lack of strong concordance in penile-vaginal sex acts and condom-unprotected penile-vaginal sex. The odds of a female reporting higher frequency of sex in daily reports compared with recall were more than two times that of a male. Every five person increase in the number of lifetime sexual partners was associated with five times the odds of a discrepancy in reporting methods. Age was also significantly associated with unequal daily versus recall sex frequency reporting. Shifting focus to methodological considerations of technological reports can help ensure better investment of resources into sexual health research due to greater understanding of the methodological properties of data collection methods. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  2. Daily Magnesium Intake and Serum Magnesium Concentration among Japanese People

    PubMed Central

    Akizawa, Yoriko; Koizumi, Sadayuki; Itokawa, Yoshinori; Ojima, Toshiyuki; Nakamura, Yosikazu; Tamura, Tarou; Kusaka, Yukinori

    2008-01-01

    Background The vitamins and minerals that are deficient in the daily diet of a normal adult remain unknown. To answer this question, we conducted a population survey focusing on the relationship between dietary magnesium intake and serum magnesium level. Methods The subjects were 62 individuals from Fukui Prefecture who participated in the 1998 National Nutrition Survey. The survey investigated the physical status, nutritional status, and dietary data of the subjects. Holidays and special occasions were avoided, and a day when people are most likely to be on an ordinary diet was selected as the survey date. Results The mean (±standard deviation) daily magnesium intake was 322 (±132), 323 (±163), and 322 (±147) mg/day for men, women, and the entire group, respectively. The mean (±standard deviation) serum magnesium concentration was 20.69 (±2.83), 20.69 (±2.88), and 20.69 (±2.83) ppm for men, women, and the entire group, respectively. The distribution of serum magnesium concentration was normal. Dietary magnesium intake showed a log-normal distribution, which was then transformed by logarithmic conversion for examining the regression coefficients. The slope of the regression line between the serum magnesium concentration (Y ppm) and daily magnesium intake (X mg) was determined using the formula Y = 4.93 (log10X) + 8.49. The coefficient of correlation (r) was 0.29. A regression line (Y = 14.65X + 19.31) was observed between the daily intake of magnesium (Y mg) and serum magnesium concentration (X ppm). The coefficient of correlation was 0.28. Conclusion The daily magnesium intake correlated with serum magnesium concentration, and a linear regression model between them was proposed. PMID:18635902

  3. Estimating missing daily temperature extremes in Jaffna, Sri Lanka

    NASA Astrophysics Data System (ADS)

    Thevakaran, A.; Sonnadara, D. U. J.

    2018-04-01

    The accuracy of reconstructing missing daily temperature extremes in the Jaffna climatological station, situated in the northern part of the dry zone of Sri Lanka, is presented. The adopted method utilizes standard departures of daily maximum and minimum temperature values at four neighbouring stations, Mannar, Anuradhapura, Puttalam and Trincomalee to estimate the standard departures of daily maximum and minimum temperatures at the target station, Jaffna. The daily maximum and minimum temperatures from 1966 to 1980 (15 years) were used to test the validity of the method. The accuracy of the estimation is higher for daily maximum temperature compared to daily minimum temperature. About 95% of the estimated daily maximum temperatures are within ±1.5 °C of the observed values. For daily minimum temperature, the percentage is about 92. By calculating the standard deviation of the difference in estimated and observed values, we have shown that the error in estimating the daily maximum and minimum temperatures is ±0.7 and ±0.9 °C, respectively. To obtain the best accuracy when estimating the missing daily temperature extremes, it is important to include Mannar which is the nearest station to the target station, Jaffna. We conclude from the analysis that the method can be applied successfully to reconstruct the missing daily temperature extremes in Jaffna where no data is available due to frequent disruptions caused by civil unrests and hostilities in the region during the period, 1984 to 2000.

  4. Corneal inflammatory events with daily silicone hydrogel lens wear.

    PubMed

    Szczotka-Flynn, Loretta; Jiang, Ying; Raghupathy, Sangeetha; Bielefeld, Roger A; Garvey, Matthew T; Jacobs, Michael R; Kern, Jami; Debanne, Sara M

    2014-01-01

    This study aimed to determine the probability and risk factors for developing a corneal inflammatory event (CIE) during daily wear of lotrafilcon A silicone hydrogel contact lenses. Eligible participants (n = 218) were fit with lotrafilcon A lenses for daily wear and followed up for 12 months. Participants were randomized to either a polyhexamethylene biguanide-preserved multipurpose solution or a one-step peroxide disinfection system. The main exposures of interest were bacterial contamination of lenses, cases, lid margins, and ocular surface. Kaplan-Meier (KM) plots were used to estimate the cumulative unadjusted probability of remaining free from a CIE, and multivariate Cox proportional hazards regression was used to model the hazard of experiencing a CIE. The KM unadjusted cumulative probability of remaining free from a CIE for both lens care groups combined was 92.3% (95% confidence interval [CI], 88.1 to 96.5%). There was one participant with microbial keratitis, five participants with asymptomatic infiltrates, and seven participants with contact lens peripheral ulcers, providing KM survival estimates of 92.8% (95% CI, 88.6 to 96.9%) and 98.1% (95% CI, 95.8 to 100.0%) for remaining free from noninfectious and symptomatic CIEs, respectively. The presence of substantial (>100 colony-forming units) coagulase-negative staphylococci bioburden on lid margins was associated with about a five-fold increased risk for the development of a CIE (p = 0.04). The probability of experiencing a CIE during daily wear of lotrafilcon A contact lenses is low, and symptomatic CIEs are rare. Patient factors, such as high levels of bacterial bioburden on lid margins, contribute to the development of noninfectious CIEs during daily wear of silicone hydrogel lenses.

  5. 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.

  6. Making Each Other’s Daily Life: Nurse Assistants’ Experiences and Knowledge on Developing a Meaningful Daily Life in Nursing Homes

    PubMed Central

    James, Inger; Fredriksson, Carin; Wahlström, Catrin; Kihlgren, Annica; Blomberg, Karin

    2014-01-01

    Background: In a larger action research project, guidelines were generated for how a meaningful daily life could be developed for older persons. In this study, we focused on the nurse assistants’ (NAs) perspectives, as their knowledge is essential for a well-functioning team and quality of care. The aim was to learn from NAs’ experiences and knowledge about how to develop a meaningful daily life for older persons in nursing homes and the meaning NAs ascribe to their work. Methods: The project is based on Participatory and Appreciative Action and Reflection. Data were generated through interviews, participating observations and informal conversations with 27 NAs working in nursing homes in Sweden, and a thematic analysis was used. Result: NAs developed a meaningful daily life by sensing and finding the “right” way of being (Theme 1). They sense and read the older person in order to judge how the person was feeling (Theme 2). They adapt to the older person (Theme 3) and share their daily life (Theme 4). NAs use emotional involvement to develop a meaningful daily life for the older person and meaning in their own work (Theme 5), ultimately making each other’s daily lives meaningful. Conclusion: It was obvious that NAs based the development of a meaningful daily life on different forms of knowledge: the oreticaland practical knowledge, and practical wisdom, all of which are intertwined. These results could be used within the team to constitute a meaningful daily life for older persons in nursing homes. PMID:25246997

  7. Eldercare responsibilities, interrole conflict, and employee absence: a daily study.

    PubMed

    Hepburn, C G; Barling, J

    1996-07-01

    A model was developed specifying that the number of hours employees spend providing care to or interacting with elderly parents predicts conflict between the roles of employee and caregiver. Interrole conflict was subsequently expected to predict partial absence from work (e.g., arriving late). Seventeen employed eldercare providers completed a daily questionnaire for 20 work days. The data were standardized and pooled, and the proposed model was tested by using structural equation modeling. The proposed model provided a good fit to the data. A competing model that added the direct effects of hours of interacting with and hours of providing care to parents on partial absence provided a significantly better fit. The potential impact of the findings on employees and organizations is discussed.

  8. Development and Evaluation of a Cloud-Gap-Filled MODIS Daily Snow-Cover Product

    NASA Technical Reports Server (NTRS)

    Hall, Dorothy K.; Riggs, George A.; Foster, James L.; Kumar, Sujay V.

    2010-01-01

    The utility of the Moderate Resolution Imaging Spectroradiometer (MODIS) snow-cover products is limited by cloud cover which causes gaps in the daily snow-cover map products. We describe a cloud-gap-filled (CGF) daily snowcover map using a simple algorithm to track cloud persistence, to account for the uncertainty created by the age of the snow observation. Developed from the 0.050 resolution climate-modeling grid daily snow-cover product, MOD10C1, each grid cell of the CGF map provides a cloud-persistence count (CPC) that tells whether the current or a prior day was used to make the snow decision. Percentage of grid cells "observable" is shown to increase dramatically when prior days are considered. The effectiveness of the CGF product is evaluated by conducting a suite of data assimilation experiments using the community Noah land surface model in the NASA Land Information System (LIS) framework. The Noah model forecasts of snow conditions, such as snow-water equivalent (SWE), are updated based on the observations of snow cover which are obtained either from the MOD1 OC1 standard product or the new CGF product. The assimilation integrations using the CGF maps provide domain averaged bias improvement of -11 %, whereas such improvement using the standard MOD1 OC1 maps is -3%. These improvements suggest that the Noah model underestimates SWE and snow depth fields, and that the assimilation integrations contribute to correcting this systematic error. We conclude that the gap-filling strategy is an effective approach for increasing cloud-free observations of snow cover.

  9. Once vs twice-daily abacavir and lamivudine in African children.

    PubMed

    Musiime, Victor; Kasirye, Philip; Naidoo-James, Bethany; Nahirya-Ntege, Patricia; Mhute, Tawanda; Cook, Adrian; Mugarura, Lincoln; Munjoma, Marshall; Thoofer, Navdeep K; Ndashimye, Emmanuel; Nankya, Immaculate; Spyer, Moira J; Thomason, Margaret J; Snowden, Wendy; Gibb, Diana M; Walker, Ann Sarah

    2016-07-17

    Antiretroviral therapy (ART) adherence is critical for successful HIV treatment outcomes. Once-daily dosing could improve adherence. Plasma concentrations of once-daily vs twice-daily abacavir + lamivudine are bioequivalent in children, but no randomized trial has compared virological outcomes. Children taking abacavir + lamivudine-containing first-line regimens twice daily for more than 36 weeks in the ARROW trial (NCT02028676, ISRCTN24791884) were randomized to continue twice-daily vs move to once-daily abacavir + lamivudine (open-label). Co-primary outcomes were viral load suppression at week 48 (12% noninferiority margin, measured retrospectively) and lamivudine or abacavir-related grade 3/4 adverse events. Six hundred and sixty-nine children (median 5 years, range 1-16) were randomized to twice daily (n = 333) vs once daily (n = 336) after median 1.8 years on twice-daily abacavir + lamivudine-containing first-line ART. Children were followed for median 114 weeks. At week 48, 242/331 (73%) twice daily vs 236/330 (72%) once daily had viral load less than 80 copies/ml [difference -1.6% (95% confidence interval -8.4,+5.2%) P = 0.65]; 79% twice daily vs 78% once daily had viral load less than 400 copies/ml (P = 0.76) (week 96 results similar). One grade 3/4 adverse event was judged uncertainly related to abacavir + lamivudine (hepatitis; once daily). At week 48, 9% twice daily vs 10% once daily reported missing one or more ART pills in the last 4 weeks (P = 0.74) and 8 vs 8% at week 96 (P = 0.90). Carers strongly preferred once-daily dosing. There was no difference between randomized groups in postbaseline drug-resistance mutations or drug-susceptibility; WHO 3/4 events; ART-modifying, grade 3/4 or serious adverse events; CD4% or weight-for-age/height-for-age (all P > 0.15). Once-daily abacavir + lamivudine was noninferior to twice daily in viral load suppression, with similar resistance, adherence, clinical

  10. 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…

  11. Daily Stressors in Primary Education Students

    ERIC Educational Resources Information Center

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

    2015-01-01

    Daily stress can have a bearing on children's emotional and academic development. This study aimed to assess daily stressors and to determine their prevalence among primary education students, taking into account their gender, academic year, social adaptation, and the school location. A sample of 7,354 Spanish schoolchildren aged between 6 and 13…

  12. Demographic, socioeconomic and nutritional determinants of daily versus non-daily sugar-sweetened and artificially sweetened beverage consumption.

    PubMed

    Mullie, P; Aerenhouts, D; Clarys, P

    2012-02-01

    The aim of this study was to determine the impact of demographic, socioeconomic and nutritional determinants on daily versus non-daily sugar-sweetened and artificially sweetened beverage consumption. Cross-sectional design in 1852 military men. Using mailed questionnaires, sugar-sweetened and artificially sweetened beverage consumption was recorded. Principal component analysis was used for dietary pattern analysis. Sugar-sweetened and artificially sweetened beverages were consumed daily by 36.3% and 33.2% of the participants, respectively. Age, body mass index (BMI), non-smoking and income were negatively related to sugar-sweetened beverage consumption. High BMI and trying to lose weight were related to artificially sweetened beverages consumption. Three major patterns were obtained from principal component analysis: first, the 'meat pattern', was loaded for red meats and processed meats; second, the 'healthy pattern', was loaded for tomatoes, fruit, whole grain, vegetables, fruit, fish, tea and nuts; finally, the 'sweet pattern' was loaded for sweets, desserts, snacks, high-energy drinks, high-fat dairy products and refined grains. The sugar-sweetened beverage consumption was strongly related with both the meat and sweet dietary patterns and inversely related to the healthy dietary pattern. The artificially sweetened beverage consumption was strongly related with the sweet and healthy dietary pattern. Daily consumption of sugar-sweetened beverages was inversely associated with a healthy dietary pattern. Daily consumption of artificially sweetened beverages was clearly associated with weight-loss intention.

  13. Father's occupational group and daily smoking during adolescence: patterns and predictors.

    PubMed

    Droomers, Mariël; Schrijvers, Carola T M; Casswell, Sally; Mackenbach, Johan P

    2005-04-01

    We investigated the relationship among father's occupational group, daily smoking, and smoking determinants in a cohort of New Zealand adolescents. The longitudinal Multidisciplinary Health and Development Study provided information on adolescents' self-reported smoking behavior and potential predictors of smoking, such as social and material factors, personality characteristics, educational achievement, and individual attitudes and beliefs regarding smoking. Longitudinal logistic generalized estimating equation analyses were used. Adolescents whose fathers were classified in the lowest-status occupational group were twice as likely as those whose fathers occupied the highest-status occupational group to be daily smokers. This high risk of daily smoking among the adolescents from the lowest occupational group was largely predicted by their lower intelligence scores and by the higher prevalence of smoking among fathers and friends. To prevent socioeconomic differences in smoking, school-based interventions should seek to prevent smoking uptake among adolescents, particularly those of lower socioeconomic status. Programs need to provide positive, nonsmoking role models consonant with the culture and norms of lower-socioeconomic-status groups. Adolescents need to acquire resistance skills and protective behaviors against social pressure and influences.

  14. Assessing Daily Stress Processes in Social Surveys by Combining Stressor Exposure and Salivary Cortisol

    PubMed Central

    Almeida, David M.; McGonagle, Katherine; King, Heather

    2010-01-01

    This paper presents a research method for assessing stress and mental health in ongoing population-based social surveys that combines self-reports of naturally occurring daily stressors with a primary marker of stress physiology, salivary cortisol. We first discuss the relevance of stress processes to mental health and introduce a model for examining daily stress processes, which highlights multiple components of daily stressor exposure. A primary aim of this approach is to capture variability across stressful situations, between persons of different groups, or within persons over a period of time. Next, we describe how the assessment of diurnal salivary cortisol is a promising approach to examining naturally occurring stress physiology in large social surveys. We then present findings from the National Study of Daily Experiences (a substudy of the Midlife in the United States Study) that document the feasibility and reliability of the collection of daily stressors and salivary diurnal cortisol and provide examples of research findings linking stressor exposure to diurnal cortisol. The final portion of the paper describes ways that this approach can leverage the strengths of various features of longitudinal social surveys to extend research on stress and mental health. PMID:20183906

  15. Daily Couple Experiences and Parent Affect in Families of Children with versus without Autism

    PubMed Central

    Hartley, Sigan L.; DaWalt, Leann Smith; Schultz, Haley M.

    2017-01-01

    We examined daily couple experiences in 174 couples who had a child with autism spectrum disorder (ASD) relative to 179 couples who had a child without disabilities and their same-day association with parent affect. Parents completed a 14-day daily diary in which they reported time with partner, partner support, partner closeness, and positive and negative couple interactions and level of positive and negative affect. One-way multivariate analyses of covariance and dyadic multilevel models were conducted. Parents of children with ASD reported less time with partner, lower partner closeness, and fewer positive couple interactions than the comparison group. Daily couple experiences were more strongly associated with parent affect in the ASD than comparison group. Findings have implications for programs and supports. PMID:28275928

  16. Daily Couple Experiences and Parent Affect in Families of Children with Versus Without Autism.

    PubMed

    Hartley, Sigan L; DaWalt, Leann Smith; Schultz, Haley M

    2017-06-01

    We examined daily couple experiences in 174 couples who had a child with autism spectrum disorder (ASD) relative to 179 couples who had a child without disabilities and their same-day association with parent affect. Parents completed a 14-day daily diary in which they reported time with partner, partner support, partner closeness, and positive and negative couple interactions and level of positive and negative affect. One-way multivariate analyses of covariance and dyadic multilevel models were conducted. Parents of children with ASD reported less time with partner, lower partner closeness, and fewer positive couple interactions than the comparison group. Daily couple experiences were more strongly associated with parent affect in the ASD than comparison group. Findings have implications for programs and supports.

  17. 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.

  18. Associations among sleep, daily experiences, and loneliness in adolescence: evidence of moderating and bidirectional pathways.

    PubMed

    Doane, Leah D; Thurston, Emily C

    2014-02-01

    The present study examined the dynamic associations among daily stress levels, affect, and objective sleep quality in adolescence. We also explored loneliness as a potential moderator of these associations. Seventy-eight adolescents participated over three days. They completed diary reports of stressful experiences and affect five times a day while wearing an actigraph to obtain objective measurement of sleep. They also provided self-reports of loneliness. High daily stress was associated with shorter sleep duration. Models testing bidirectional associations indicated that prior day stress was associated with shorter sleep duration, but poor sleep duration and sleep efficiency were also associated with greater stress the next day. Loneliness was a significant moderator of the associations between daily stress and sleep duration and latency such that lonely individuals had shorter sleep durations and sleep latencies after particularly stressful days. Results suggest daily dynamic associations among loneliness, daily stress, and objective measures of adolescent sleep. Copyright © 2013 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2010-12-01

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

  20. 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. ...

  1. 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. ...

  2. 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. ...

  3. 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. ...

  4. 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. ...

  5. New daily persistent headache: An evolving entity.

    PubMed

    Uniyal, Ravi; Paliwal, Vimal Kumar; Anand, Sucharita; Ambesh, Paurush

    2018-01-01

    New daily persistent headache (NDPH) is characterized by an abrupt onset of headache that becomes a daily entity, is unremitting and continuous from the onset, and lasts for more than 3 months. Dr Walter Vanast first described NDPH in the year 1986. Originally, it was proposed as a chronic daily headache but it was placed under "other primary headaches" in the International Classification of Headache Disorder Second Edition (ICHD 2nd edition). However, with evolving literature and better understanding of its clinical characteristics, it was classified as a "chronic daily headache" in the ICHD 3 rd edition beta. There are still many knowledge-gaps regarding the underlying cause, pathophysiology, natural history and treatment of NDPH. This review tries to revisit the entity and discusses the current status of understanding regarding NDPH.

  6. Protocol for the CONVERT trial-Concurrent ONce-daily VErsus twice-daily RadioTherapy: an international 2-arm randomised controlled trial of concurrent chemoradiotherapy comparing twice-daily and once-daily radiotherapy schedules in patients with limited stage small cell lung cancer (LS-SCLC) and good performance status.

    PubMed

    Faivre-Finn, Corinne; Falk, Sally; Ashcroft, Linda; Bewley, Michelle; Lorigan, Paul; Wilson, Elena; Groom, Nicki; Snee, Michael; Fournel, Pierre; Cardenal, Felipe; Bezjak, Andrea; Blackhall, Fiona

    2016-01-20

    Concurrent ONce-daily VErsus twice-daily RadioTherapy (CONVERT) is the only multicentre, international, randomised, phase III trial open in Europe and Canada looking at optimisation of chemoradiotherapy (RT) in limited stage small cell lung cancer (LS-SCLC). Following on from the Turrisi trial of once-daily versus twice-daily (BD) concurrent chemoradiotherapy, there is a real need for a new phase III trial using modern conformal RT techniques and investigating higher once-daily radiation dose. This trial has the potential to define a new standard chemo-RT regimen for patients with LS-SCLC and good performance status. 447 patients with histologically or cytologically proven diagnosis of SCLC were recruited from 74 centres in eight countries between 2008 and 2013. Patients were randomised to receive either concurrent twice-daily RT(45 Gy in 30 twice-daily fractions over 3 weeks) or concurrent once-daily RT(66 Gy in 33 once-daily fractions over 6.5 weeks) both starting on day 22 of cycle 1. Patients are followed up until death. The primary end point of the study is overall survival and secondary end points include local progression-free survival, metastasis-free survival, acute and late toxicity based on the Common Terminology Criteria for Adverse Events V.3.0, chemotherapy and RTdose intensity. The trial received ethical approval from NRES Committee North West-Greater Manchester Central (07/H1008/229). There is a trial steering committee, including independent members and an independent data monitoring committee. Results will be published in a peer-reviewed journal and presented at international conferences. ISRCTN91927162; Pre-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  7. DYNAMIC ELECTRICITY GENERATION FOR ADDRESSING DAILY AIR QUALITY EXCEEDANCES IN THE US

    EPA Science Inventory

    We will design, demonstrate, and evaluate a dynamic management system for managing daily air quality, exploring different elements of the design of this system such as how air quality forecasts can best be used, and decision rules for the electrical dispatch model. We will ...

  8. Reconstructing missing daily precipitation data using regression trees and artificial neural networks

    USDA-ARS?s Scientific Manuscript database

    Incomplete meteorological data has been a problem in environmental modeling studies. The objective of this work was to develop a technique to reconstruct missing daily precipitation data in the central part of Chesapeake Bay Watershed using regression trees (RT) and artificial neural networks (ANN)....

  9. Reconstructing missing daily precipitation data using regression trees and artificial neural networks

    USDA-ARS?s Scientific Manuscript database

    Missing meteorological data have to be estimated for agricultural and environmental modeling. The objective of this work was to develop a technique to reconstruct the missing daily precipitation data in the central part of the Chesapeake Bay Watershed using regression trees (RT) and artificial neura...

  10. 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.

  11. The Relationships between Weather-Related Factors and Daily Outdoor Physical Activity Counts on an Urban Greenway

    PubMed Central

    Wolff, Dana; Fitzhugh, Eugene C.

    2011-01-01

    The purpose of this study was to examine relationships between weather and outdoor physical activity (PA). An online weather source was used to obtain daily max temperature [DMT], precipitation, and wind speed. An infra-red trail counter provided data on daily trail use along a greenway, over a 2-year period. Multiple regression analysis was used to examine associations between PA and weather, while controlling for day of the week and month of the year. The overall regression model explained 77.0% of the variance in daily PA (p < 0.001). DMT (b = 10.5), max temp-squared (b = −4.0), precipitation (b = −70.0), and max wind speed (b = 1.9) contributed significantly. Conclusion: Aggregated daily data can detect relationships between weather and outdoor PA. PMID:21556205

  12. Estimating Causal Effects of Local Air Pollution on Daily Deaths: Effect of Low Levels.

    PubMed

    Schwartz, Joel; Bind, Marie-Abele; Koutrakis, Petros

    2017-01-01

    Although many time-series studies have established associations of daily pollution variations with daily deaths, there are fewer at low concentrations, or focused on locally generated pollution, which is becoming more important as regulations reduce regional transport. Causal modeling approaches are also lacking. We used causal modeling to estimate the impact of local air pollution on mortality at low concentrations. Using an instrumental variable approach, we developed an instrument for variations in local pollution concentrations that is unlikely to be correlated with other causes of death, and examined its association with daily deaths in the Boston, Massachusetts, area. We combined height of the planetary boundary layer and wind speed, which affect concentrations of local emissions, to develop the instrument for particulate matter ≤ 2.5 μm (PM2.5), black carbon (BC), or nitrogen dioxide (NO2) variations that were independent of year, month, and temperature. We also used Granger causality to assess whether omitted variable confounding existed. We estimated that an interquartile range increase in the instrument for local PM2.5 was associated with a 0.90% increase in daily deaths (95% CI: 0.25, 1.56). A similar result was found for BC, and a weaker association with NO2. The Granger test found no evidence of omitted variable confounding for the instrument. A separate test confirmed the instrument was not associated with mortality independent of pollution. Furthermore, the association remained when all days with PM2.5 concentrations > 30 μg/m3 were excluded from the analysis (0.84% increase in daily deaths; 95% CI: 0.19, 1.50). We conclude that there is a causal association of local air pollution with daily deaths at concentrations below U.S. EPA standards. The estimated attributable risk in Boston exceeded 1,800 deaths during the study period, indicating that important public health benefits can follow from further control efforts. Citation: Schwartz J, Bind MA

  13. 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 ...

  14. The Effects of Employment Status and Daily Stressors on Time Spent on Daily Household Chores in Middle-Aged and Older Adults

    ERIC Educational Resources Information Center

    Wong, Jen D.; Almeida, David M.

    2013-01-01

    Purpose of the study: This study examines how employment status (worker vs. retiree) and life course influences (age, gender, and marital status) are associated with time spent on daily household chores. Second, this study assesses whether the associations between daily stressors and time spent on daily household chores differ as a function of…

  15. Examining the Dynamic Structure of Daily Internalizing and Externalizing Behavior at Multiple Levels of Analysis

    PubMed Central

    Wright, Aidan G. C.; Beltz, Adriene M.; Gates, Kathleen M.; Molenaar, Peter C. M.; Simms, Leonard J.

    2015-01-01

    Psychiatric diagnostic covariation suggests that the underlying structure of psychopathology is not one of circumscribed disorders. Quantitative modeling of individual differences in diagnostic patterns has uncovered several broad domains of mental disorder liability, of which the Internalizing and Externalizing spectra have garnered the greatest support. These dimensions have generally been estimated from lifetime or past-year comorbidity patters, which are distal from the covariation of symptoms and maladaptive behavior that ebb and flow in daily life. In this study, structural models are applied to daily diary data (Median = 94 days) of maladaptive behaviors collected from a sample (N = 101) of individuals diagnosed with personality disorders (PDs). Using multilevel and unified structural equation modeling, between-person, within-person, and person-specific structures were estimated from 16 behaviors that are encompassed by the Internalizing and Externalizing spectra. At the between-person level (i.e., individual differences in average endorsement across days) we found support for a two-factor Internalizing–Externalizing model, which exhibits significant associations with corresponding diagnostic spectra. At the within-person level (i.e., dynamic covariation among daily behavior pooled across individuals) we found support for a more differentiated, four-factor, Negative Affect-Detachment-Hostility-Disinhibition structure. Finally, we demonstrate that the person-specific structures of associations between these four domains are highly idiosyncratic. PMID:26732546

  16. Daily stressors, war experiences, and mental health in Afghanistan.

    PubMed

    Miller, Kenneth E; Omidian, Patricia; Rasmussen, Andrew; Yaqubi, Aziz; Daudzai, Haqmal

    2008-12-01

    Working in Afghanistan's capital city of Kabul, the authors assessed the relative contribution of daily stressors and war-related experiences of violence and loss to levels of depression, PTSD, impaired functioning, and a culturally specific measure of general psychological distress. For women, daily stressors were a better predictor than war experiences of all mental health outcomes except for PTSD; for men, daily stressors were a better predictor of depression and functional impairment, while war experiences and daily stressors were similarly predictive of general distress. For men, daily stressors moderated the relationship between war experiences and PTSD, which was significant only under conditions of low daily stress. The study's implications for research and intervention in conflict and post-conflict settings are considered.

  17. Daily stressors as antecedents, correlates, and consequences of alcohol and drug use and cravings in community-based offenders.

    PubMed

    Neupert, Shevaun D; Desmarais, Sarah L; Gray, Julie S; Cohn, Amy M; Doherty, Stephen; Knight, Kevin

    2017-05-01

    Justice-involved individuals with alcohol and drug use problems reoffend at higher rates than their nonusing counterparts, with alcohol and drug use serving as an important vector to recidivism. At the daily level, exposure to stressors may exacerbate problematic alcohol and drug use; at the individual level, prior treatment experiences may mitigate substance use as individuals adapt to and learn new coping mechanisms. We conducted a daily diary study using Interactive Voice Response technology over 14 consecutive days with 117 men on probation or parole participating in a community-based treatment program (n = 860 calls) and referred to medication-assisted treatment. Participants reported daily stressors, craving for alcohol and illegal drugs, and use of alcohol and illegal drugs 1 time each day. Results of multilevel models showed significant day-to-day fluctuation in alcohol and drug craving and use. In concurrent models, increases in daily stressors were associated with increases in cravings and use of illegal drugs. Prior treatment experience modified many of these relationships, and additional lagged models revealed that those with less treatment experience reported an increase in next-day alcohol craving when they experienced increases in stressors on the previous day compared to those with more treatment experience. Collectively, these findings highlight the importance of tailoring treatment as a function of individual differences, including prior treatment experiences, and targeting daily stressors and subsequent cravings among justice-involved adults with alcohol and drug use problems. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  18. Daily Stressors as Antecedents, Correlates, and Consequences of Alcohol and Drug Use and Cravings in Community-Based Offenders

    PubMed Central

    Neupert, Shevaun D.; Desmarais, Sarah L.; Gray, Julie S.; Cohn, Amy M.; Doherty, Stephen; Knight, Kevin

    2017-01-01

    Justice-involved individuals with alcohol and drug use problems reoffend at higher rates than their non-using counterparts, with alcohol and drug use serving as an important vector to recidivism. At the daily level, exposure to stressors may exacerbate problematic alcohol and drug use; at the individual-level, prior treatment experiences may mitigate substance use as individuals adapt to and learn new coping mechanisms. We conducted a daily diary study using Interactive Voice Response (IVR) technology over 14 consecutive days with 117 men on probation or parole participating in a community-based treatment program (n = 860 calls) and referred to medication-assisted treatment. Participants reported daily stressors, craving for alcohol and illegal drugs, and use of alcohol and illegal drugs one time each day. Results of multilevel models showed significant day-to-day fluctuation in alcohol and drug craving and use. In concurrent models, increases in daily stressors were associated with increases in cravings and use of illegal drugs. Prior treatment experience modified many of these relationships, and additional lagged models revealed that those with less treatment experience reported an increase in next-day alcohol craving when they experienced increases in stressors on the previous day compared to those with more treatment experience. Collectively, these findings highlight the importance of tailoring treatment as a function of individual differences, including prior treatment experiences, and targeting daily stressors and subsequent cravings among justice-involved adults with alcohol and drug use problems. PMID:28383933

  19. Pathological Narcissism and Interpersonal Behavior in Daily Life

    PubMed Central

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

    2014-01-01

    The Cognitive-Affective Processing System (CAPS) has been proposed as a useful meta-framework for integrating contextual differences in situations with individual differences in personality pathology. In this article, we evaluated the potential of combining the CAPS meta-framework 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

  20. Passive wireless sensor systems can recognize activites of daily living.

    PubMed

    Urwyler, Prabitha; Stucki, Reto; Muri, Rene; Mosimann, Urs P; Nef, Tobias

    2015-08-01

    The ability to determine what activity of daily living a person performs is of interest in many application domains. It is possible to determine the physical and cognitive capabilities of the elderly by inferring what activities they perform in their houses. Our primary aim was to establish a proof of concept that a wireless sensor system can monitor and record physical activity and these data can be modeled to predict activities of daily living. The secondary aim was to determine the optimal placement of the sensor boxes for detecting activities in a room. A wireless sensor system was set up in a laboratory kitchen. The ten healthy participants were requested to make tea following a defined sequence of tasks. Data were collected from the eight wireless sensor boxes placed in specific places in the test kitchen and analyzed to detect the sequences of tasks performed by the participants. These sequence of tasks were trained and tested using the Markov Model. Data analysis focused on the reliability of the system and the integrity of the collected data. The sequence of tasks were successfully recognized for all subjects and the averaged data pattern of tasks sequences between the subjects had a high correlation. Analysis of the data collected indicates that sensors placed in different locations are capable of recognizing activities, with the movement detection sensor contributing the most to detection of tasks. The central top of the room with no obstruction of view was considered to be the best location to record data for activity detection. Wireless sensor systems show much promise as easily deployable to monitor and recognize activities of daily living.

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

    NASA Astrophysics Data System (ADS)

    Tatsumi, Kenichi; Oizumi, Tsutao; Yamashiki, Yosuke

    2015-04-01

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

  2. A method for continuous monitoring of the Ground Reaction Force during daily activity

    NASA Technical Reports Server (NTRS)

    Whalen, Robert; Quintana, Jason; Emery, Jeff

    1993-01-01

    Theoretical models and experimental studies of bone remodeling have identified peak cyclic force levels (or cyclic tissue strain energy density), number of daily loading cycles, and load (strain) rate as possible contributors to bone modeling and remodeling stimulus. To test our theoretical model and further investigate the influence of mechanical forces on bone density, we have focused on the calcaneus as a model site loaded by calcaneal surface tractions which are predominantly determined by the magnitude of the external ground reaction force (GRF).

  3. Exponential approximation for daily average solar heating or photolysis. [of stratospheric ozone layer

    NASA Technical Reports Server (NTRS)

    Cogley, A. C.; Borucki, W. J.

    1976-01-01

    When incorporating formulations of instantaneous solar heating or photolytic rates as functions of altitude and sun angle into long range forecasting models, it may be desirable to replace the time integrals by daily average rates that are simple functions of latitude and season. This replacement is accomplished by approximating the integral over the solar day by a pure exponential. This gives a daily average rate as a multiplication factor times the instantaneous rate evaluated at an appropriate sun angle. The accuracy of the exponential approximation is investigated by a sample calculation using an instantaneous ozone heating formulation available in the literature.

  4. Oral impacts on daily performances and recent use of dental services in schoolchildren.

    PubMed

    Monsantofils, Monica; Bernabé, Eduardo

    2014-11-01

    To explore whether oral impacts on daily performances are related to recent use of dental services among children and whether oral impacts on specific daily performances are more strongly related to recent use of dental services. Data from a cross-sectional survey, including 805 11-12-year-old children attending four randomly selected schools in Lima (Peru), were used. The child version of the oral impacts on daily performances (Child-OIDP) was used to assess prevalence, intensity, and extent of oral impacts. Use of dental services was assessed by self-reports of last dental visit and reason for the visit. Associations of the prevalence, intensity, and extent of oral impacts with use of dental services were tested in logistic regression models. Children with oral impacts were 1.99 (95% CI: 1.17-3.37) times more likely to have used dental services recently than their counterparts. The intensity and extent of oral impacts were linearly associated with children's use of dental services. Difficulties in eating were the only type of oral impacts on daily performances associated with use of dental services, independent of children's demographic characteristics, and impacts on other performances. Oral impacts on daily performances were related to recent use of dental services among these schoolchildren. © 2013 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  5. Association of total daily physical activity with disability in community-dwelling older persons: a prospective cohort study

    PubMed Central

    2012-01-01

    Background Based on findings primarily using self-report measures, physical activity has been recommended to reduce disability in old age. Collecting objective measures of total daily physical activity in community-dwelling older adults is uncommon, but might enhance the understanding of the relationship of physical activity and disability. We examined whether greater total daily physical activity was associated with less report of disability in the elderly. Methods Data were from the Rush Memory and Aging Project, a longitudinal prospective cohort study of common, age-related, chronic conditions. Total daily physical activity was measured in community-dwelling participants with an average age of 82 using actigraphy for approximately 9 days. Disability was measured via self-reported basic activities of daily living (ADL). The odds ratio and 95% Confidence Interval (CI) were determined for the baseline association of total daily physical activity and ADL disability using a logistic regression model adjusted for age, education level, gender and self-report physical activity. In participants without initial report of ADL disability, the hazard ratio and 95% CI were determined for the relationship of baseline total daily physical activity and the development of ADL disability using a discrete time Cox proportional hazard model adjusted for demographics and self-report physical activity. Results In 870 participants, the mean total daily physical activity was 2. 9 × 105 counts/day (range in 105 counts/day = 0.16, 13. 6) and the mean hours/week of self-reported physical activity was 3.2 (SD = 3.6). At baseline, 718 (82.5%) participants reported being independent in all ADLs. At baseline, total daily physical activity was protective against disability (OR per 105 counts/day difference = 0.55; 95% CI = 0.47, 0.65). Of the participants without baseline disability, 584 were followed for 3.4 years on average. Each 105 counts/day additional total daily physical activity

  6. 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.

  7. Perceived ability to perform daily hand activities after stroke and associated factors: a cross-sectional study.

    PubMed

    Ekstrand, Elisabeth; Rylander, Lars; Lexell, Jan; Brogårdh, Christina

    2016-11-02

    Despite that disability of the upper extremity is common after stroke, there is limited knowledge how it influences self-perceived ability to perform daily hand activities. The aim of this study was to describe which daily hand activities that persons with mild to moderate impairments of the upper extremity after stroke perceive difficult to perform and to evaluate how several potential factors are associated with the self-perceived performance. Seventy-five persons (72 % male) with mild to moderate impairments of the upper extremity after stroke (4 to 116 months) participated. Self-perceived ability to perform daily hand activities was rated with the ABILHAND Questionnaire. The perceived ability to perform daily hand activities and the potentially associated factors (age, gender, social and vocational situation, affected hand, upper extremity pain, spasticity, grip strength, somatosensation of the hand, manual dexterity, perceived participation and life satisfaction) were evaluated by linear regression models. The activities that were perceived difficult or impossible for a majority of the participants were bimanual tasks that required fine manual dexterity of the more affected hand. The factor that had the strongest association with perceived ability to perform daily hand activities was dexterity (p < 0.001), which together with perceived participation (p = 0.002) explained 48 % of the variance in the final multivariate model. Persons with mild to moderate impairments of the upper extremity after stroke perceive that bimanual activities requiring fine manual dexterity are the most difficult to perform. Dexterity and perceived participation are factors specifically important to consider in the rehabilitation of the upper extremity after stroke in order to improve the ability to use the hands in daily life.

  8. Daily hassles, their antecedents and outcomes among professional first responders: A systematic literature review.

    PubMed

    Larsson, Gerry; Berglund, Anna Karin; Ohlsson, Alicia

    2016-08-01

    Occupational groups such as firefighters, military officers, paramedics and police officers are exposed to a combination of acute, severe and accumulated everyday stress. Drawing on the daily hassles perspective on stress, the aim was to synthesize existing research on daily hassles in professional first responder settings into a theoretical model. A systematic mixed studies review with an integrated design was undertaken. The selection process resulted in 40 articles meeting the inclusion criteria. The selected papers represented two literature reviews, one qualitative study, eight longitudinal studies and 29 cross-sectional studies. Five superior categories emerged in the analysis: Individual antecedent and continuously framing factors, Environmental antecedent and continuously framing factors, Appraisal and coping processes, Daily hassles and Outcome. Suggestions for future research are presented. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  9. Sexual orientation, social capital and daily tobacco smoking: a population-based study.

    PubMed

    Lindström, Martin; Axelsson, Jakob; Modén, Birgit; Rosvall, Maria

    2014-06-06

    Studies have suggested poorer health in the homosexual and bisexual groups compared to heterosexuals. Tobacco smoking, which is a health-related behavior associated with psychosocial stress, may be one explanation behind such health differences. Social capital, i.e. the generalized trust in other people and social participation/social networks which decreases the costs of social interaction, has been suggested to affect health through psychosocial pathways and through norms connected with health related behaviours, The aim of this study is to investigate the association between sexual orientation and daily tobacco smoking, taking social capital into account and analyzing the attenuation of the logit after the introduction of social participation, trust and their combination in the models. In 2008 a cross-sectional public health survey was conducted in southern Sweden with a postal questionnaire with 28,198 participants aged 18-80 (55% participation rate). This study was restricted to 24,348 participants without internally missing values on all included variables. Associations between sexual orientation and tobacco smoking were analyzed with logistic regression analysis. Overall, 11.9% of the men and 14.8% of the women were daily tobacco smokers. Higher and almost unaltered odds ratios of daily smoking compared to heterosexuals were observed for bisexual men and women, and for homosexual men throughout the analyses. The odds ratios of daily smoking among homosexual women were not significant. Only for the "other" sexual orientation group the odds ratios of daily smoking were reduced to not significant levels among both men and women, with a corresponding 54% attenuation of the logit in the "other" group among men and 31.5% among women after the inclusion of social participation and trust. In addition, only the "other" sexual orientation group had higher odds ratios of low participation than heterosexuals. Bisexual men and women and homosexual men, but not homosexual

  10. Modeling daily soil temperature over diverse climate conditions in Iran—a comparison of multiple linear regression and support vector regression techniques

    NASA Astrophysics Data System (ADS)

    Delbari, Masoomeh; Sharifazari, Salman; Mohammadi, Ehsan

    2018-02-01

    The knowledge of soil temperature at different depths is important for agricultural industry and for understanding climate change. The aim of this study is to evaluate the performance of a support vector regression (SVR)-based model in estimating daily soil temperature at 10, 30 and 100 cm depth at different climate conditions over Iran. The obtained results were compared to those obtained from a more classical multiple linear regression (MLR) model. The correlation sensitivity for the input combinations and periodicity effect were also investigated. Climatic data used as inputs to the models were minimum and maximum air temperature, solar radiation, relative humidity, dew point, and the atmospheric pressure (reduced to see level), collected from five synoptic stations Kerman, Ahvaz, Tabriz, Saghez, and Rasht located respectively in the hyper-arid, arid, semi-arid, Mediterranean, and hyper-humid climate conditions. According to the results, the performance of both MLR and SVR models was quite well at surface layer, i.e., 10-cm depth. However, SVR performed better than MLR in estimating soil temperature at deeper layers especially 100 cm depth. Moreover, both models performed better in humid climate condition than arid and hyper-arid areas. Further, adding a periodicity component into the modeling process considerably improved the models' performance especially in the case of SVR.

  11. Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events

    DOE PAGES

    Shiogama, Hideo; Imada, Yukiko; Mori, Masato; ...

    2016-08-07

    Here, we describe two unprecedented large (100-member), longterm (61-year) ensembles based on MRI-AGCM3.2, which were driven by historical and non-warming climate forcing. These ensembles comprise the "Database for Policy Decision making for Future climate change (d4PDF)". We compare these ensembles to large ensembles based on another climate model, as well as to observed data, to investigate the influence of anthropogenic activities on historical changes in the numbers of record-breaking events, including: the annual coldest daily minimum temperature (TNn), the annual warmest daily maximum temperature (TXx) and the annual most intense daily precipitation event (Rx1day). These two climate model ensembles indicatemore » that human activity has already had statistically significant impacts on the number of record-breaking extreme events worldwide mainly in the Northern Hemisphere land. Specifically, human activities have altered the likelihood that a wider area globally would suffer record-breaking TNn, TXx and Rx1day events than that observed over the 2001- 2010 period by a factor of at least 0.6, 5.4 and 1.3, respectively. However, we also find that the estimated spatial patterns and amplitudes of anthropogenic impacts on the probabilities of record-breaking events are sensitive to the climate model and/or natural-world boundary conditions used in the attribution studies.« less

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

    PubMed

    Evrendilek, Fatih

    2007-12-12

    This study aims at quantifying spatio-temporal dynamics of monthly mean dailyincident photosynthetically active radiation (PAR) over a vast and complex terrain such asTurkey. The spatial interpolation method of universal kriging, and the combination ofmultiple linear regression (MLR) models and map algebra techniques were implemented togenerate surface maps of PAR with a grid resolution of 500 x 500 m as a function of fivegeographical and 14 climatic variables. Performance of the geostatistical and MLR modelswas 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 adjustedcoefficient of determination (R² adj. ). The best-fit MLR- and universal kriging-generatedmodels of monthly mean daily PAR were validated against an independent 37-year observeddataset of 35 climate stations derived from 160 stations across Turkey by the Jackknifingmethod. The spatial variability patterns of monthly mean daily incident PAR were moreaccurately reflected in the surface maps created by the MLR-based models than in thosecreated by the universal kriging method, in particular, for spring (May) and autumn(November). The MLR-based spatial interpolation algorithms of PAR described in thisstudy indicated the significance of the multifactor approach to understanding and mappingspatio-temporal dynamics of PAR for a complex terrain over meso-scales.

  13. 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.

  14. Induction of testicular damage by daily methamphetamine administration in rats.

    PubMed

    Lin, Ji-Fan; Lin, Yi-Hsuan; Liao, Po-Cheng; Lin, Yi-Chia; Tsai, Te-Fu; Chou, Kuang-Yu; Chen, Hung-En; Tsai, Shiow-Chwen; Hwang, Thomas I-Sheng

    2014-02-28

    Methamphetamine (METH)-induced brain damage and apoptosis within the central nervous system are well documented. This study was conducted to investigate the toxic effects of daily METH administration on the testes in a rat model. Male Sprague-Dawley rats (5 weeks old, ~100 g, n = 64) were divided into two groups and treated with vehicle (saline, control) or METH (10 mg/kg) for 15, 30, 60 and 90 days. The results showed that daily administration of METH decreased the body, testicular and epididymis weights as well as the serum levels of total testosterone. The increased apoptotic index (Bad/Bcl2 expression ratio) and levels of cleaved caspase-3 indicated that apoptosis had occurred in the testes of the METH-treated rats. The oxidative stress levels increased as the reduced and oxidized glutathione (GSH/GSSG) ratio decreased. The overall sperm counts decreased at 15 and 90 days, where- as morphologically abnormal sperm counts increased at 30, 60 and 90 days in the METH-treated rats. This study demonstrates that daily exposure to METH significantly reduced the number and quality of sperm in rats. The underlying pathophysiological mechanisms likely include the reduction of serum testosterone levels and the increase of oxidative stress and apoptosis in the rat testes.

  15. Probing Resilience: Daily Environmental Mastery, Self-Esteem, and Stress Appraisal.

    PubMed

    Montpetit, Mignon A; Tiberio, Stacey S

    2016-10-01

    The current study explores one way the process of resilience arises by investigating the underlying process of stress appraisal. In particular, the analyses examine how resilience resources function each day to attenuate the extent to which life experiences are perceived as threatening, and how trait-like resilience resources shape the appraisal process. Daily diary and questionnaire data from 96 participants of Successful Aging in Context: The Macroenvironment and Daily Lived Experience (SAIC; MAge = 67 years, SDAge = 4.9 years; range: 58-86 years) were analyzed using multilevel random coefficient modeling to investigate how individuals' daily perceptions of control and self-esteem impacted perceived stress on a given day. Results suggested that both self-esteem and environmental mastery help mitigate the experience of stress; furthermore, dispositional resilience and self-esteem stability predict differences between individuals in the extent to which self-esteem tempers the perception of stress each day. The results inform theoretical and empirical work on the nature of resilience, especially regarding how the process arises in ordinary life. From an application perspective, results imply that augmenting environmental mastery and self-esteem, both of which are malleable, can facilitate resilience by helping elders challenge their perceptions of stress each day. © The Author(s) 2016.

  16. Short-Term Effect of Coarse Particles on Daily Mortality Rate in A Tropical City, Kaohsiung, Taiwan.

    PubMed

    Tsai, Shang-Shyue; Weng, Yi-Hao; Chiu, Ya-Wen; Yang, Chun-Yuh

    2015-01-01

    Many studies examined the short-term effects of air pollution on frequency of daily mortality over the past two decades. However, information on the relationship between exposure to levels of coarse particles (PM(2.5-10)) and daily mortality rate is relatively sparse due to limited availability of monitoring data and findings are inconsistent. This study was undertaken to determine whether an association exists between PM(2.5-10) levels and rate of daily mortality in Kaohsiung, Taiwan, a large industrial city with a tropical climate. Daily mortality rate, air pollution parameters, and weather data for Kaohsiung were obtained for the period 2006-2008. The relative risk (RR) of daily mortality occurrence was estimated using a time-stratified case-crossover approach, controlling for (1) weather variables, (2) day of the week, (3) seasonality, and (4) long-term time trends. For the single-pollutant model without adjustment for other pollutants, PM(2.5-10) exposure levels showed significant correlation with total mortality rate both on warm and cool days, with an interquartile range increase associated with a 14% (95% CI = 5-23%) and 12% (95% CI = 5-20%) rise in number of total deaths, respectively. In two-pollutant models, PM(2.5-10) exerted significant influence on total mortality frequency after inclusion of sulfur dioxide (SO(2)) on warm days. On cool days, PM(2.5-10) induced significant elevation in total mortality rate when SO(2) or ozone (O(3)) was added in the regression model. There was no apparent indication of an association between PM(2.5-10) exposure and deaths attributed to respiratory and circulatory diseases. This study provided evidence of correlation between short-term exposure to PM(2.5-10) and increased risk of death for all causes.

  17. Daily torpor and hibernation in birds and mammals

    PubMed Central

    RUF, THOMAS; GEISER, FRITZ

    2014-01-01

    Many birds and mammals drastically reduce their energy expenditure during times of cold exposure, food shortage, or drought, by temporarily abandoning euthermia, i.e., the maintenance of high body temperatures. Traditionally, two different types of heterothermy, i.e., hypometabolic states associated with low body temperatures (torpor), have been distinguished: Daily torpor, which lasts less than 24 h and is accompanied by continued foraging, versus hibernation, with torpor bouts lasting consecutive days to several weeks in animals that usually do not forage but rely on energy stores, either food caches or body energy reserves. This classification of torpor types has been challenged however, suggesting that these phenotypes may merely represent the extremes in a continuum of traits. Here, we investigate whether variables of torpor in 214 species, 43 birds and 171 mammals form a continuum or a bimodal distribution. We use Gaussian-mixture cluster analysis as well as phylogenetically informed regressions to quantitatively assess the distinction between hibernation and daily torpor and to evaluate the impact of body mass and geographical distribution of species on torpor traits. Cluster analysis clearly confirmed the classical distinction between daily torpor and hibernation. Overall, heterothermic endotherms are small on average, but hibernators are significantly heavier than daily heterotherms and also are distributed at higher average latitudes (~35°) than daily heterotherms (~25°). Variables of torpor for an average 30-g heterotherm differed significantly between daily heterotherms and hibernators. Average maximum torpor bout duration was >30-fold longer, and mean torpor bout duration >25-fold longer in hibernators. Mean minimum body temperature differed by ~13°C, and the mean minimum torpor metabolic rate was ~35% of the BMR in daily heterotherms but only 6% of basal metabolic rate in hibernators. Consequently, our analysis strongly supports the view that

  18. Parametric vs. non-parametric daily weather generator: validation and comparison

    NASA Astrophysics Data System (ADS)

    Dubrovsky, Martin

    2016-04-01

    As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series

  19. A simple approach to estimate daily loads of total, refractory, and labile organic carbon from their seasonal loads in a watershed.

    PubMed

    Ouyang, Ying; Grace, Johnny M; Zipperer, Wayne C; Hatten, Jeff; Dewey, Janet

    2018-05-22

    Loads of naturally occurring total organic carbons (TOC), refractory organic carbon (ROC), and labile organic carbon (LOC) in streams control the availability of nutrients and the solubility and toxicity of contaminants and affect biological activities through absorption of light and complex metals with production of carcinogenic compounds. Although computer models have become increasingly popular in understanding and management of TOC, ROC, and LOC loads in streams, the usefulness of these models hinges on the availability of daily data for model calibration and validation. Unfortunately, these daily data are usually insufficient and/or unavailable for most watersheds due to a variety of reasons, such as budget and time constraints. A simple approach was developed here to calculate daily loads of TOC, ROC, and LOC in streams based on their seasonal loads. We concluded that the predictions from our approach adequately match field measurements based on statistical comparisons between model calculations and field measurements. Our approach demonstrates that an increase in stream discharge results in increased stream TOC, ROC, and LOC concentrations and loads, although high peak discharge did not necessarily result in high peaks of TOC, ROC, and LOC concentrations and loads. The approach developed herein is a useful tool to convert seasonal loads of TOC, ROC, and LOC into daily loads in the absence of measured daily load data.

  20. Types of Family Caregiving and Daily Experiences in Midlife and Late Adulthood: The Moderating Influences of Marital Status and Age.

    PubMed

    Wong, Jen D; Shobo, Yetunde

    2017-07-01

    Guided by the life-course perspective, this study contributes to the family caregiving, aging, and disability literature by examining the daily experiences of three types of family caregivers in midlife and late adulthood. A sample of 162 caregivers from the National Survey of Midlife in the United States study completed interviews, questionnaires, and a Daily Diary Study. Multilevel models showed the patterns of daily time use did not differ by caregiver types. Caregivers of sons/daughters with developmental disabilities (DD) experienced more daily stressors than caregivers of parents with health conditions (HC) and caregivers of spouses with HC. Unmarried caregivers of sons/daughters with DD reported spending more time on daily leisure activities and exhibited greater daily stressor exposure than other family caregivers. Age did not moderate the associations between caregiver types and daily experiences. Findings highlight the important consideration of the caregivers' characteristics to better determine the quality of their daily experiences in midlife and late adulthood.