Argentina corn yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate corn yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the corn-growing area. Predictor variables for the model were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. A trend variable was included for the years 1965 to 1980 since an increasing trend in yields due to technology was observed between these years.

A New Flow-Diverter (the FloWise): In-Vivo Evaluation in an Elastase-Induced Rabbit Aneurysm Model.

PubMed

Kim, Byung Moon; Kim, Dong Joon; Kim, Dong Ik

2016-01-01

We aimed to evaluate the efficacy and safety of a newly developed, partially retrievable flow-diverter (the FloWise) in an elastase-induced rabbit aneurysm model. We developed a partially retrievable flow diverter composed of 48 strands of Nitinol and platinum wire. The FloWise is compatible with any microcatheter of 0.027-inch inner diameter, and is retrievable up to 70% deployment. The efficacy and safety of the FloWise were evaluated in the elastase-induced rabbit aneurysm model. The rate of technical success (full coverage of aneurysm neck) and assessment of aneurysm occlusion and stent patency was conducted by angiograms and histologic examinations at the 1-month, 3-month, and 6-month follow-up. The patency of small arterial branches (intercostal or lumbar arteries) covered by the FloWise were also assessed in the 5 subjects. We attempted FloWise insertion in a total of 32 aneurysm models. FloWise placement was successful in 31 subjects (96.9%). Two stents (6.2%) were occluded at the 3-month follow-up, but there was no evidence of in-stent stenosis in other subjects. All stented aneurysms showed progressive occlusion: grade I (complete aneurysm occlusion) in 44.4% and grade II (aneurysm occlusion > 90%) in 55.6% at 1 month; grade I in 90% and II in 10% at 3 months; and grade I in 90% and II in 10% at 6 months. All small arterial branches covered by the FloWise remained patent. A newly developed, partially retrievable flow-diverter seems to be a safe and effective tool of aneurysm occlusion, as evaluated in the rabbit aneurysm model.

Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: A case study in endemic districts of Bhutan

PubMed Central

2010-01-01

Background Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX. Methods This study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VDCP) and the meteorological data from Meteorological Unit, Department of Energy, Ministry of Economic Affairs. Time series analysis was performed on monthly malaria cases, from 1994 to 2008, in seven malaria endemic districts. The time series models derived from a multiplicative seasonal autoregressive integrated moving average (ARIMA) was deployed to identify the best model using data from 1994 to 2006. The best-fit model was selected for each individual district and for the overall endemic area was developed and the monthly cases from January to December 2009 and 2010 were forecasted. In developing the prediction model, the monthly reported malaria cases and the meteorological factors from 1996 to 2008 of the seven districts were analysed. The method of ARIMAX modelling was employed to determine predictors of malaria of the subsequent month. Results It was found that the ARIMA (p, d, q) (P, D, Q)s model (p and P representing the auto regressive and seasonal autoregressive; d and D representing the non-seasonal differences and seasonal differencing; and q and Q the moving average parameters and seasonal moving average parameters, respectively and s representing the length of the seasonal period) for the overall endemic districts was (2,1,1)(0,1,1)12; the modelling data from each district revealed two most common ARIMA models including (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The forecasted monthly malaria cases from January to December 2009 and 2010 varied from 15 to 82 cases in 2009 and 67 to 149 cases in 2010, where population in 2009 was 285,375 and the expected population of 2010 to be 289,085. The ARIMAX model of monthly cases and climatic factors showed considerable variations among the different districts. In general, the mean maximum temperature lagged at one month was a strong positive predictor of an increased malaria cases for four districts. The monthly number of cases of the previous month was also a significant predictor in one district, whereas no variable could predict malaria cases for two districts. Conclusions The ARIMA models of time-series analysis were useful in forecasting the number of cases in the endemic areas of Bhutan. There was no consistency in the predictors of malaria cases when using ARIMAX model with selected lag times and climatic predictors. The ARIMA forecasting models could be employed for planning and managing malaria prevention and control programme in Bhutan. PMID:20813066

Monthly hydroclimatology of the continental United States

NASA Astrophysics Data System (ADS)

Petersen, Thomas; Devineni, Naresh; Sankarasubramanian, A.

2018-04-01

Physical/semi-empirical models that do not require any calibration are of paramount need for estimating hydrological fluxes for ungauged sites. We develop semi-empirical models for estimating the mean and variance of the monthly streamflow based on Taylor Series approximation of a lumped physically based water balance model. The proposed models require mean and variance of monthly precipitation and potential evapotranspiration, co-variability of precipitation and potential evapotranspiration and regionally calibrated catchment retention sensitivity, atmospheric moisture uptake sensitivity, groundwater-partitioning factor, and the maximum soil moisture holding capacity parameters. Estimates of mean and variance of monthly streamflow using the semi-empirical equations are compared with the observed estimates for 1373 catchments in the continental United States. Analyses show that the proposed models explain the spatial variability in monthly moments for basins in lower elevations. A regionalization of parameters for each water resources region show good agreement between observed moments and model estimated moments during January, February, March and April for mean and all months except May and June for variance. Thus, the proposed relationships could be employed for understanding and estimating the monthly hydroclimatology of ungauged basins using regional parameters.

Time-series modeling and prediction of global monthly absolute temperature for environmental decision making

NASA Astrophysics Data System (ADS)

Ye, Liming; Yang, Guixia; Van Ranst, Eric; Tang, Huajun

2013-03-01

A generalized, structural, time series modeling framework was developed to analyze the monthly records of absolute surface temperature, one of the most important environmental parameters, using a deterministicstochastic combined (DSC) approach. Although the development of the framework was based on the characterization of the variation patterns of a global dataset, the methodology could be applied to any monthly absolute temperature record. Deterministic processes were used to characterize the variation patterns of the global trend and the cyclic oscillations of the temperature signal, involving polynomial functions and the Fourier method, respectively, while stochastic processes were employed to account for any remaining patterns in the temperature signal, involving seasonal autoregressive integrated moving average (SARIMA) models. A prediction of the monthly global surface temperature during the second decade of the 21st century using the DSC model shows that the global temperature will likely continue to rise at twice the average rate of the past 150 years. The evaluation of prediction accuracy shows that DSC models perform systematically well against selected models of other authors, suggesting that DSC models, when coupled with other ecoenvironmental models, can be used as a supplemental tool for short-term (˜10-year) environmental planning and decision making.

Development of a predictive model for 6 month survival in patients with venous thromboembolism and solid malignancy requiring IVC filter placement.

PubMed

Huang, Steven Y; Odisio, Bruno C; Sabir, Sharjeel H; Ensor, Joe E; Niekamp, Andrew S; Huynh, Tam T; Kroll, Michael; Gupta, Sanjay

2017-07-01

Our purpose was to develop a predictive model for short-term survival (i.e. <6 months) following inferior vena cava filter placement in patients with venous thromboembolism (VTE) and solid malignancy. Clinical and laboratory parameters were retrospectively reviewed for patients with solid malignancy who received a filter between January 2009 and December 2011 at a tertiary care cancer center. Multivariate Cox proportional hazards modeling was used to assess variables associated with 6 month survival following filter placement in patients with VTE and solid malignancy. Significant variables were used to generate a predictive model. 397 patients with solid malignancy received a filter during the study period. Three variables were associated with 6 month survival: (1) serum albumin [hazard ratio (HR) 0.496, P < 0.0001], (2) recent or planned surgery (<30 days) (HR 0.409, P < 0.0001), (3) TNM staging (stage 1 or 2 vs. stage 4, HR 0.177, P = 0.0001; stage 3 vs. stage 4, HR 0.367, P = 0.0002). These variables were used to develop a predictive model to estimate 6 month survival with an area under the receiver operating characteristic curve of 0.815, sensitivity of 0.782, and specificity of 0.715. Six month survival in patients with VTE and solid malignancy requiring filter placement can be predicted from three patient variables. Our predictive model could be used to help physicians decide whether a permanent or retrievable filter may be more appropriate as well as to assess the risks and benefits for filter retrieval within the context of survival longevity in patients with cancer.

Children’s development of intonation during the first year of cochlear implant experience

PubMed Central

Snow, David P.; Ertmer, David J.

2012-01-01

This article describes the longitudinal development of intonation in 18 deaf children who received cochlear implants (CIs) before the age of three years and 12 infants with typical development (TD) who served as controls. At the time their implants were activated, the children with CIs ranged in age from 9 to 36 months. Cross-group comparisons were made when the children had equivalent amounts of robust hearing experience but different chronological ages. This paper reports the results for the 6-month period ending 9 months after activation of the child’s device for children with CIs, and the 6-month period ending at 12 months of age for TD infants. The findings were compared to a model of early intonation development in children with normal hearing. The results indicated that all groups progressed through 1 or more of the stages predicted by the normative model. At the end of the study period, however, children who had received a cochlear implant later than 24 months reached a more mature stage of intonation development than younger CI-recipients. Moreover, the older CI group reached the same stage of development as the TD infants who had 3 additional months of language listening experience. The findings suggest that the developmental advantage which older children had previously demonstrated shortly after activation of their CIs is maintained throughout most or all of the first year of cochlear implant use. PMID:21728834

A Poisson regression approach to model monthly hail occurrence in Northern Switzerland using large-scale environmental variables

NASA Astrophysics Data System (ADS)

Madonna, Erica; Ginsbourger, David; Martius, Olivia

2018-05-01

In Switzerland, hail regularly causes substantial damage to agriculture, cars and infrastructure, however, little is known about its long-term variability. To study the variability, the monthly number of days with hail in northern Switzerland is modeled in a regression framework using large-scale predictors derived from ERA-Interim reanalysis. The model is developed and verified using radar-based hail observations for the extended summer season (April-September) in the period 2002-2014. The seasonality of hail is explicitly modeled with a categorical predictor (month) and monthly anomalies of several large-scale predictors are used to capture the year-to-year variability. Several regression models are applied and their performance tested with respect to standard scores and cross-validation. The chosen model includes four predictors: the monthly anomaly of the two meter temperature, the monthly anomaly of the logarithm of the convective available potential energy (CAPE), the monthly anomaly of the wind shear and the month. This model well captures the intra-annual variability and slightly underestimates its inter-annual variability. The regression model is applied to the reanalysis data back in time to 1980. The resulting hail day time series shows an increase of the number of hail days per month, which is (in the model) related to an increase in temperature and CAPE. The trend corresponds to approximately 0.5 days per month per decade. The results of the regression model have been compared to two independent data sets. All data sets agree on the sign of the trend, but the trend is weaker in the other data sets.

Forecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997–2003

PubMed Central

Gomez-Elipe, Alberto; Otero, Angel; van Herp, Michel; Aguirre-Jaime, Armando

2007-01-01

Background The objective of this work was to develop a model to predict malaria incidence in an area of unstable transmission by studying the association between environmental variables and disease dynamics. Methods The study was carried out in Karuzi, a province in the Burundi highlands, using time series of monthly notifications of malaria cases from local health facilities, data from rain and temperature records, and the normalized difference vegetation index (NDVI). Using autoregressive integrated moving average (ARIMA) methodology, a model showing the relation between monthly notifications of malaria cases and the environmental variables was developed. Results The best forecasting model (R2adj = 82%, p < 0.0001 and 93% forecasting accuracy in the range ± 4 cases per 100 inhabitants) included the NDVI, mean maximum temperature, rainfall and number of malaria cases in the preceding month. Conclusion This model is a simple and useful tool for producing reasonably reliable forecasts of the malaria incidence rate in the study area. PMID:17892540

Mapping monthly rainfall erosivity in Europe.

PubMed

Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

2017-02-01

Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha -1 h -1 ) compared to winter (87MJmmha -1 h -1 ). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R 2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

GPP in Loblolly Pine: A Monthly Comparison of Empirical and Process Models

Treesearch

Christopher Gough; John Seiler; Kurt Johnsen; David Arthur Sampson

2002-01-01

Monthly and yearly gross primary productivity (GPP) estimates derived from an empirical and two process based models (3PG and BIOMASS) were compared. Spatial and temporal variation in foliar gas photosynthesis was examined and used to develop GPP prediction models for fertilized nine-year-old loblolly pine (Pinus taeda) stands located in the North...

Modeling and projection of dengue fever cases in Guangzhou based on variation of weather factors.

PubMed

Li, Chenlu; Wang, Xiaofeng; Wu, Xiaoxu; Liu, Jianing; Ji, Duoying; Du, Juan

2017-12-15

Dengue fever is one of the most serious vector-borne infectious diseases, especially in Guangzhou, China. Dengue viruses and their vectors Aedes albopictus are sensitive to climate change primarily in relation to weather factors. Previous research has mainly focused on identifying the relationship between climate factors and dengue cases, or developing dengue case models with some non-climate factors. However, there has been little research addressing the modeling and projection of dengue cases only from the perspective of climate change. This study considered this topic using long time series data (1998-2014). First, sensitive weather factors were identified through meta-analysis that included literature review screening, lagged analysis, and collinear analysis. Then, key factors that included monthly average temperature at a lag of two months, and monthly average relative humidity and monthly average precipitation at lags of three months were determined. Second, time series Poisson analysis was used with the generalized additive model approach to develop a dengue model based on key weather factors for January 1998 to December 2012. Data from January 2013 to July 2014 were used to validate that the model was reliable and reasonable. Finally, future weather data (January 2020 to December 2070) were input into the model to project the occurrence of dengue cases under different climate scenarios (RCP 2.6 and RCP 8.5). Longer time series analysis and scientifically selected weather variables were used to develop a dengue model to ensure reliability. The projections suggested that seasonal disease control (especially in summer and fall) and mitigation of greenhouse gas emissions could help reduce the incidence of dengue fever. The results of this study hope to provide a scientifically theoretical basis for the prevention and control of dengue fever in Guangzhou. Copyright © 2017 Elsevier B.V. All rights reserved.

Validated Risk Score for Predicting 6-Month Mortality in Infective Endocarditis.

PubMed

Park, Lawrence P; Chu, Vivian H; Peterson, Gail; Skoutelis, Athanasios; Lejko-Zupa, Tatjana; Bouza, Emilio; Tattevin, Pierre; Habib, Gilbert; Tan, Ren; Gonzalez, Javier; Altclas, Javier; Edathodu, Jameela; Fortes, Claudio Querido; Siciliano, Rinaldo Focaccia; Pachirat, Orathai; Kanj, Souha; Wang, Andrew

2016-04-18

Host factors and complications have been associated with higher mortality in infective endocarditis (IE). We sought to develop and validate a model of clinical characteristics to predict 6-month mortality in IE. Using a large multinational prospective registry of definite IE (International Collaboration on Endocarditis [ICE]-Prospective Cohort Study [PCS], 2000-2006, n=4049), a model to predict 6-month survival was developed by Cox proportional hazards modeling with inverse probability weighting for surgery treatment and was internally validated by the bootstrapping method. This model was externally validated in an independent prospective registry (ICE-PLUS, 2008-2012, n=1197). The 6-month mortality was 971 of 4049 (24.0%) in the ICE-PCS cohort and 342 of 1197 (28.6%) in the ICE-PLUS cohort. Surgery during the index hospitalization was performed in 48.1% and 54.0% of the cohorts, respectively. In the derivation model, variables related to host factors (age, dialysis), IE characteristics (prosthetic or nosocomial IE, causative organism, left-sided valve vegetation), and IE complications (severe heart failure, stroke, paravalvular complication, and persistent bacteremia) were independently associated with 6-month mortality, and surgery was associated with a lower risk of mortality (Harrell's C statistic 0.715). In the validation model, these variables had similar hazard ratios (Harrell's C statistic 0.682), with a similar, independent benefit of surgery (hazard ratio 0.74, 95% CI 0.62-0.89). A simplified risk model was developed by weight adjustment of these variables. Six-month mortality after IE is ≈25% and is predicted by host factors, IE characteristics, and IE complications. Surgery during the index hospitalization is associated with lower mortality but is performed less frequently in the highest risk patients. A simplified risk model may be used to identify specific risk subgroups in IE. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Crop weather models of barley and spring wheat yield for agrophysical units in North Dakota

NASA Technical Reports Server (NTRS)

Leduc, S. (Principal Investigator)

1982-01-01

Models based on multiple regression were developed to estimate barley yield and spring wheat yield from weather data for Agrophysical units(APU) in North Dakota. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for Crop Reporting Districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU models show sight improvements in some of the statistics of the models, e.g., explained variation. These models are to be independently evaluated and compared to the previously evaluated CRD models. The comparison will indicate the preferred model area for this application, i.e., APU or CRD.

Development of predictive weather scenarios for early prediction of rice yield in South Korea

NASA Astrophysics Data System (ADS)

Shin, Y.; Cho, J.; Jung, I.

2017-12-01

International grain prices are becoming unstable due to frequent occurrence of abnormal weather phenomena caused by climate change. Early prediction of grain yield using weather forecast data is important for stabilization of international grain prices. The APEC Climate Center (APCC) is providing seasonal forecast data based on monthly climate prediction models for global seasonal forecasting services. The 3-month and 6-month seasonal forecast data using the multi-model ensemble (MME) technique are provided in their own website, ADSS (APCC Data Service System, http://adss.apcc21.org/). The spatial resolution of seasonal forecast data for each individual model is 2.5°×2.5°(about 250km) and the time scale is created as monthly. In this study, we developed customized weather forecast scenarios that are combined seasonal forecast data and observational data apply to early rice yield prediction model. Statistical downscale method was applied to produce meteorological input data of crop model because field scale crop model (ORYZA2000) requires daily weather data. In order to determine whether the forecasting data is suitable for the crop model, we produced spatio-temporal downscaled weather scenarios and evaluated the predictability by comparison with observed weather data at 57 ASOS stations in South Korea. The customized weather forecast scenarios can be applied to various application fields not only early rice yield prediction. Acknowledgement This work was carried out with the support of "Cooperative Research Program for Agriculture Science and Technology Development (Project No: PJ012855022017)" Rural Development Administration, Republic of Korea.

Short-term droughts forecast using Markov chain model in Victoria, Australia

NASA Astrophysics Data System (ADS)

Rahmat, Siti Nazahiyah; Jayasuriya, Niranjali; Bhuiyan, Muhammed A.

2017-07-01

A comprehensive risk management strategy for dealing with drought should include both short-term and long-term planning. The objective of this paper is to present an early warning method to forecast drought using the Standardised Precipitation Index (SPI) and a non-homogeneous Markov chain model. A model such as this is useful for short-term planning. The developed method has been used to forecast droughts at a number of meteorological monitoring stations that have been regionalised into six (6) homogenous clusters with similar drought characteristics based on SPI. The non-homogeneous Markov chain model was used to estimate drought probabilities and drought predictions up to 3 months ahead. The drought severity classes defined using the SPI were computed at a 12-month time scale. The drought probabilities and the predictions were computed for six clusters that depict similar drought characteristics in Victoria, Australia. Overall, the drought severity class predicted was quite similar for all the clusters, with the non-drought class probabilities ranging from 49 to 57 %. For all clusters, the near normal class had a probability of occurrence varying from 27 to 38 %. For the more moderate and severe classes, the probabilities ranged from 2 to 13 % and 3 to 1 %, respectively. The developed model predicted drought situations 1 month ahead reasonably well. However, 2 and 3 months ahead predictions should be used with caution until the models are developed further.

Brazil soybean yield covariance model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the seven soybean-growing states of Brazil. The meteorological data of these seven states were pooled and the years 1975 to 1980 were used to model since there was no technological trend in the yields during these years. Predictor variables were derived from monthly total precipitation and monthly average temperature.

The Development of Empathic Concern in Siblings: A Reciprocal Influence Model.

PubMed

Jambon, Marc; Madigan, Sheri; Plamondon, André; Daniel, Ella; Jenkins, Jennifer M

2018-02-20

This study utilized actor-partner interdependence modeling to examine the bidirectional effects of younger (M age  = 18 months) and older siblings (M age  = 48 months) on later empathy development in a large (n = 452 families), diverse (42% immigrant) Canadian sample. Controlling for parenting, demographic characteristics, sibling relationship quality, and within-child stability in empathic concern, both younger and older siblings' observed empathic concern uniquely predicted relative increases in the other's empathy over a period of 18 months. The strength of the partner effects did not differ by birth order. Sex composition moderated the younger sibling partner effect, whereas age gap moderated the older sibling partner effect. This study highlights the important role that siblings play in enhancing the development of care and concern for others. © 2018 The Authors. Child Development © 2018 Society for Research in Child Development, Inc.

Clinical Prediction Rule for Declines in Activities of Daily Living at 6 Months After Surgery for Hip Fracture Repair.

PubMed

Tanaka, Ryo; Umehara, Takuya; Fujimura, Takafumi; Ozawa, Junya

2016-12-01

To develop and assess a clinical prediction rule (CPR) to predict declines in activities of daily living (ADL) at 6 months after surgery for hip fracture repair. Prospective, cohort study. From hospital to home. Patients (N=104) with hip fractures after surgery. Not applicable. ADL were assessed using the Barthel Index at 6 months after surgery. At 6 months after surgery, 86 patients (82.6%) were known to be alive, 1 patient (1.0%) had died, and 17 (16.3%) were lost to follow-up. Thirty-two patients (37.2%) did not recover their ADL at 6 months after surgery to levels before fracture. The classification and regression trees methodology was used to develop 2 models to predict a decline in ADL: (1) model 1 included age, type of fracture, and care level before fracture (sensitivity=75.0%, specificity=81.5%, positive predictive value=70.6%, positive likelihood ratio=4.050); and (2) model 2 included the degree of independence 2 weeks postsurgery for ADL chair transfer, ADL ambulation, and age (sensitivity=65.6%, specificity=87.0%, positive predictive value=75.0%, positive likelihood ratio=5.063). The areas under the receiver operating characteristic curves of both CPR models were .825 (95% confidential interval, .728-.923) and .790 (95% confidence interval, .683-.897), respectively. CPRs with moderate accuracy were developed to predict declines in ADL at 6 months after surgery for hip fracture repair. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Development and validation of a set of six adaptable prognosis prediction (SAP) models based on time-series real-world big data analysis for patients with cancer receiving chemotherapy: A multicenter case crossover study

PubMed Central

Kanai, Masashi; Okamoto, Kazuya; Yamamoto, Yosuke; Yoshioka, Akira; Hiramoto, Shuji; Nozaki, Akira; Nishikawa, Yoshitaka; Yamaguchi, Daisuke; Tomono, Teruko; Nakatsui, Masahiko; Baba, Mika; Morita, Tatsuya; Matsumoto, Shigemi; Kuroda, Tomohiro; Okuno, Yasushi; Muto, Manabu

2017-01-01

Background We aimed to develop an adaptable prognosis prediction model that could be applied at any time point during the treatment course for patients with cancer receiving chemotherapy, by applying time-series real-world big data. Methods Between April 2004 and September 2014, 4,997 patients with cancer who had received systemic chemotherapy were registered in a prospective cohort database at the Kyoto University Hospital. Of these, 2,693 patients with a death record were eligible for inclusion and divided into training (n = 1,341) and test (n = 1,352) cohorts. In total, 3,471,521 laboratory data at 115,738 time points, representing 40 laboratory items [e.g., white blood cell counts and albumin (Alb) levels] that were monitored for 1 year before the death event were applied for constructing prognosis prediction models. All possible prediction models comprising three different items from 40 laboratory items (40C3 = 9,880) were generated in the training cohort, and the model selection was performed in the test cohort. The fitness of the selected models was externally validated in the validation cohort from three independent settings. Results A prognosis prediction model utilizing Alb, lactate dehydrogenase, and neutrophils was selected based on a strong ability to predict death events within 1–6 months and a set of six prediction models corresponding to 1,2, 3, 4, 5, and 6 months was developed. The area under the curve (AUC) ranged from 0.852 for the 1 month model to 0.713 for the 6 month model. External validation supported the performance of these models. Conclusion By applying time-series real-world big data, we successfully developed a set of six adaptable prognosis prediction models for patients with cancer receiving chemotherapy. PMID:28837592

A new approach for monthly updates of anthropogenic sulfur dioxide emissions from space: Application to China and implications for air quality forecasts

NASA Astrophysics Data System (ADS)

Wang, Yi; Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Wang, Yuxuan; Qu, Zhen

2016-09-01

SO2 emissions, the largest source of anthropogenic aerosols, can respond rapidly to economic and policy driven changes. However, bottom-up SO2 inventories have inherent limitations owing to 24-48 months latency and lack of month-to-month variation in emissions (especially in developing countries). This study develops a new approach that integrates Ozone Monitoring Instrument (OMI) SO2 satellite measurements and GEOS-Chem adjoint model simulations to constrain monthly anthropogenic SO2 emissions. The approach's effectiveness is demonstrated for 14 months in East Asia; resultant posterior emissions not only capture a 20% SO2 emission reduction in Beijing during the 2008 Olympic Games but also improve agreement between modeled and in situ surface measurements. Further analysis reveals that posterior emissions estimates, compared to the prior, lead to significant improvements in forecasting monthly surface and columnar SO2. With the pending availability of geostationary measurements of tropospheric composition, we show that it may soon be possible to rapidly constrain SO2 emissions and associated air quality predictions at fine spatiotemporal scales.

Development of prediction models of stress and long-term disability among claimants to injury compensation systems: a cohort study

PubMed Central

Spittal, Matthew J; Grant, Genevieve; O’Donnell, Meaghan; McFarlane, Alexander C; Studdert, David M

2018-01-01

Objectives We sought to develop prognostic risk scores for compensation-related stress and long-term disability using markers collected within 3 months of a serious injury. Design Cohort study. Predictors were collected at baseline and at 3 months postinjury. Outcome data were collected at 72 months postinjury. Setting Hospitalised patients with serious injuries recruited from four major trauma hospitals in Australia. Participants 332 participants who made claims for compensation for their injuries to a transport accident scheme or a workers’ compensation scheme. Primary outcome measures 12-item WHO Disability Assessment Schedule and 6 items from the Claims Experience Survey. Results Our model for long-term disability had four predictors (unemployed at the time of injury, history of a psychiatric disorder at time of injury, post-traumatic stress disorder symptom severity at 3 months and disability at 3 months). This model had good discrimination (R2=0.37) and calibration. The disability risk score had a score range of 0–180, and at a threshold of 80 had sensitivity of 56% and specificity of 86%. Our model for compensation-related stress had five predictors (intensive care unit admission, discharged to home, number of traumatic events prior to injury, depression at 3 months and not working at 3 months). This model also had good discrimination (area under the curve=0.83) and calibration. The compensation-related stress risk score had score range of 0–220 and at a threshold of 100 had sensitivity of 74% and specificity of 75%. By combining these two scoring systems, we were able to identify the subgroup of claimants at highest risk of experiencing both outcomes. Conclusions The ability to identify at an early stage claimants at high risk of compensation-related stress and poor recovery is potentially valuable for claimants and the compensation agencies that serve them. The scoring systems we developed could be incorporated into the claims-handling processes to guide prevention-oriented interventions. PMID:29705763

Mathematical skills in 3- and 5-year-olds with spina bifida and their typically developing peers: a longitudinal approach.

PubMed

Barnes, Marcia A; Stubbs, Allison; Raghubar, Kimberly P; Agostino, Alba; Taylor, Heather; Landry, Susan; Fletcher, Jack M; Smith-Chant, Brenda

2011-05-01

Preschoolers with spina bifida (SB) were compared to typically developing (TD) children on tasks tapping mathematical knowledge at 36 months (n = 102) and 60 months of age (n = 98). The group with SB had difficulty compared to TD peers on all mathematical tasks except for transformation on quantities in the subitizable range. At 36 months, vocabulary knowledge, visual-spatial, and fine motor abilities predicted achievement on a measure of informal math knowledge in both groups. At 60 months of age, phonological awareness, visual-spatial ability, and fine motor skill were uniquely and differentially related to counting knowledge, oral counting, object-based arithmetic skills, and quantitative concepts. Importantly, the patterns of association between these predictors and mathematical performance were similar across the groups. A novel finding is that fine motor skill uniquely predicted object-based arithmetic abilities in both groups, suggesting developmental continuity in the neurocognitive correlates of early object-based and later symbolic arithmetic problem solving. Models combining 36-month mathematical ability and these language-based, visual-spatial, and fine motor abilities at 60 months accounted for considerable variance on 60-month informal mathematical outcomes. Results are discussed with reference to models of mathematical development and early identification of risk in preschoolers with neurodevelopmental disorder.

Mathematical Skills in 3- and 5-Year-Olds with Spina Bifida and Their Typically Developing Peers: A Longitudinal Approach

PubMed Central

Barnes, Marcia A.; Stubbs, Allison; Raghubar, Kimberly P.; Agostino, Alba; Taylor, Heather; Landry, Susan; Fletcher, Jack M.; Smith-Chant, Brenda

2011-01-01

Preschoolers with spina bifida (SB) were compared to typically developing (TD) children on tasks tapping mathematical knowledge at 36 months (n = 102) and 60 months of age (n = 98). The group with SB had difficulty compared to TD peers on all mathematical tasks except for transformation on quantities in the subitizable range. At 36 months, vocabulary knowledge, visual–spatial, and fine motor abilities predicted achievement on a measure of informal math knowledge in both groups. At 60 months of age, phonological awareness, visual–spatial ability, and fine motor skill were uniquely and differentially related to counting knowledge, oral counting, object-based arithmetic skills, and quantitative concepts. Importantly, the patterns of association between these predictors and mathematical performance were similar across the groups. A novel finding is that fine motor skill uniquely predicted object-based arithmetic abilities in both groups, suggesting developmental continuity in the neurocognitive correlates of early object-based and later symbolic arithmetic problem solving. Models combining 36-month mathematical ability and these language-based, visual–spatial, and fine motor abilities at 60 months accounted for considerable variance on 60-month informal mathematical outcomes. Results are discussed with reference to models of mathematical development and early identification of risk in preschoolers with neurodevelopmental disorder. PMID:21418718

Associations of maternal long-chain polyunsaturated fatty acids, methyl mercury, and infant development in the Seychelles Child Development Nutrition Study.

PubMed

Strain, J J; Davidson, Philip W; Bonham, Maxine P; Duffy, Emeir M; Stokes-Riner, Abbie; Thurston, Sally W; Wallace, Julie M W; Robson, Paula J; Shamlaye, Conrad F; Georger, Lesley A; Sloane-Reeves, Jean; Cernichiari, Elsa; Canfield, Richard L; Cox, Christopher; Huang, Li Shan; Janciuras, Joanne; Myers, Gary J; Clarkson, Thomas W

2008-09-01

Fish consumption during gestation can provide the fetus with long-chain polyunsaturated fatty acids (LCPUFA) and other nutrients essential for growth and development of the brain. However, fish consumption also exposes the fetus to the neurotoxicant, methyl mercury (MeHg). We studied the association between these fetal exposures and early child development in the Seychelles Child Development Nutrition Study (SCDNS). Specifically, we examined a priori models of Omega-3 and Omega-6 LCPUFA measures in maternal serum to test the hypothesis that these LCPUFA families before or after adjusting for prenatal MeHg exposure would reveal associations with child development assessed by the BSID-II at ages 9 and 30 months. There were 229 children with complete outcome and covariate data available for analysis. At 9 months, the PDI was positively associated with total Omega-3 LCPUFA and negatively associated with the ratio of Omega-6/Omega-3 LCPUFA. These associations were stronger in models adjusted for prenatal MeHg exposure. Secondary models suggested that the MeHg effect at 9 months varied by the ratio of Omega-6/Omega-3 LCPUFA. There were no significant associations between LCPUFA measures and the PDI at 30 months. There were significant adverse associations, however, between prenatal MeHg and the 30-month PDI when the LCPUFA measures were included in the regression analysis. The BSID-II mental developmental index (MDI) was not associated with any exposure variable. These data support the potential importance to child development of prenatal availability of Omega-3 LCPUFA present in fish and of LCPUFA in the overall diet. Furthermore, they indicate that the beneficial effects of LCPUFA can obscure the determination of adverse effects of prenatal MeHg exposure in longitudinal observational studies.

Associations of maternal long chain polyunsaturated fatty acids, methyl mercury, and infant development in the Seychelles Child Development Nutrition Study

PubMed Central

Strain, J.J.; Davidson, Philip W.; Bonham, Maxine P.; Duffy, Emeir M.; Stokes-Riner, Abbie; Thurston, Sally W.; Wallace, Julie M.W.; Robson, Paula J.; Shamlaye, Conrad F.; Georger, Lesley A.; Sloane-Reeves, Jean; Cernichiari, Elsa; Canfield, Richard L.; Cox, Christopher; Huang, Li Shan; Janciuras, Joanne; Myers, Gary J.; Clarkson, Thomas W.

2008-01-01

Fish consumption during gestation can provide the fetus with long chain polyunsaturated fatty acids (LCPUFA) and other nutrients essential for growth and development of the brain. However, fish consumption also exposes the fetus to the neurotoxicant, methyl mercury (MeHg). We studied the association between these fetal exposures and early child development in the Seychelles Child Development Nutrition Study (SCDNS). Specifically, we examined a priori models of Ω-3 and Ω-6 LCPUFA measures in maternal serum to test the hypothesis that these LCPUFA families before or after adjusting for prenatal MeHg exposure would reveal associations with child development assessed by the BSID-II at ages 9 and 30 months. There were 229 children with complete outcome and covariate data available for analysis. At 9 months, the PDI was positively associated with total Ω-3 LCPUFA and negatively associated with the ratio of Ω-6/Ω-3 LCPUFA. These associations were stronger in models adjusted for prenatal MeHg exposure. Secondary models suggested that the MeHg effect at 9 months varied by the ratio of Ω-6/Ω-3 LCPUFA. There were no significant associations between LCPUFA measures and the PDI at 30 months. There were significant adverse associations, however, between prenatal MeHg and the 30 month PDI when the LCPUFA measures were included in the regression analysis. The BSID-II Mental Developmental Index (MDI) was not associated with any exposure variable. These data support the potential importance to child development of prenatal availability of Ω-3 LCPUFA present in fish and of LCPUFA in the overall diet. Furthermore, they indicate that the beneficial effects of LCPUFA can obscure the determination of adverse effects of prenatal MeHg exposure in longitudinal observational studies. PMID:18590765

Predicting 6- and 12-Month Risk of Mortality in Patients With Platinum-Resistant Advanced-Stage Ovarian Cancer: Prognostic Model to Guide Palliative Care Referrals.

PubMed

Foote, Jonathan; Lopez-Acevedo, Micael; Samsa, Gregory; Lee, Paula S; Kamal, Arif H; Alvarez Secord, Angeles; Havrilesky, Laura J

2018-02-01

Predictive models are increasingly being used in clinical practice. The aim of the study was to develop a predictive model to identify patients with platinum-resistant ovarian cancer with a prognosis of less than 6 to 12 months who may benefit from immediate referral to hospice care. A retrospective chart review identified patients with platinum-resistant epithelial ovarian cancer who were treated at our institution between 2000 and 2011. A predictive model for survival was constructed based on the time from development of platinum resistance to death. Multivariate logistic regression modeling was used to identify significant survival predictors and to develop a predictive model. The following variables were included: time from diagnosis to platinum resistance, initial stage, debulking status, number of relapses, comorbidity score, albumin, hemoglobin, CA-125 levels, liver/lung metastasis, and the presence of a significant clinical event (SCE). An SCE was defined as a malignant bowel obstruction, pleural effusion, or ascites occurring on or before the diagnosis of platinum resistance. One hundred sixty-four patients met inclusion criteria. In the regression analysis, only an SCE and the presence of liver or lung metastasis were associated with poorer short-term survival (P < 0.001). Nine percent of patients with an SCE or liver or lung metastasis survived 6 months or greater and 0% survived 12 months or greater, compared with 85% and 67% of patients without an SCE or liver or lung metastasis, respectively. Patients with platinum-resistant ovarian cancer who have experienced an SCE or liver or lung metastasis have a high risk of death within 6 months and should be considered for immediate referral to hospice care.

Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models.

PubMed

Ji, Ruijun; Du, Wanliang; Shen, Haipeng; Pan, Yuesong; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Zhao, Xingquan; Wang, Yongjun

2014-11-25

Acute ischemic stroke (AIS) is one of the leading causes of death and adult disability worldwide. In the present study, we aimed to develop a web-based risk model for predicting dynamic functional status at discharge, 3-month, 6-month, and 1-year after acute ischemic stroke (Dynamic Functional Status after Acute Ischemic Stroke, DFS-AIS). The DFS-AIS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Good functional outcome was defined as modified Rankin Scale (mRS) score ≤ 2 at discharge, 3-month, 6-month, and 1-year after AIS, respectively. Independent predictors of each outcome measure were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and plot of observed and predicted risk were used to assess model discrimination and calibration. A total of 12,026 patients were included and the median age was 67 (interquartile range: 57-75). The proportion of patients with good functional outcome at discharge, 3-month, 6-month, and 1-year after AIS was 67.9%, 66.5%, 66.9% and 66.9%, respectively. Age, gender, medical history of diabetes mellitus, stroke or transient ischemic attack, current smoking and atrial fibrillation, pre-stroke dependence, pre-stroke statins using, admission National Institutes of Health Stroke Scale score, admission blood glucose were identified as independent predictors of functional outcome at different time points after AIS. The DFS-AIS was developed from sets of predictors of mRS ≤ 2 at different time points following AIS. The DFS-AIS demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.837-0.845). Plots of observed versus predicted likelihood showed excellent calibration in the derivation and validation cohorts (all r = 0.99, P < 0.001). When compared to 8 existing models, the DFS-AIS showed significantly better discrimination for good functional outcome and mortality at discharge, 3-month, 6-month, and 1-year after AIS (all P < 0.0001). The DFS-AIS is a valid risk model to predict functional outcome at discharge, 3-month, 6-month, and 1-year after AIS.

Prediction of two month modified Rankin Scale with an ordinal prediction model in patients with aneurysmal subarachnoid haemorrhage

PubMed Central

2010-01-01

Background Aneurysmal subarachnoid haemorrhage (aSAH) is a devastating event with a frequently disabling outcome. Our aim was to develop a prognostic model to predict an ordinal clinical outcome at two months in patients with aSAH. Methods We studied patients enrolled in the International Subarachnoid Aneurysm Trial (ISAT), a randomized multicentre trial to compare coiling and clipping in aSAH patients. Several models were explored to estimate a patient's outcome according to the modified Rankin Scale (mRS) at two months after aSAH. Our final model was validated internally with bootstrapping techniques. Results The study population comprised of 2,128 patients of whom 159 patients died within 2 months (8%). Multivariable proportional odds analysis identified World Federation of Neurosurgical Societies (WFNS) grade as the most important predictor, followed by age, sex, lumen size of the aneurysm, Fisher grade, vasospasm on angiography, and treatment modality. The model discriminated moderately between those with poor and good mRS scores (c statistic = 0.65), with minor optimism according to bootstrap re-sampling (optimism corrected c statistic = 0.64). Conclusion We presented a calibrated and internally validated ordinal prognostic model to predict two month mRS in aSAH patients who survived the early stage up till a treatment decision. Although generalizability of the model is limited due to the selected population in which it was developed, this model could eventually be used to support clinical decision making after external validation. Trial Registration International Standard Randomised Controlled Trial, Number ISRCTN49866681 PMID:20920243

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 visits, and forecasting ability was dependent on the type of model employed and the length of the time horizon being predicted. In this setting, GLM and GEE models showed better accuracy than SARIMA models. Including information about ambient temperature in the models did not improve forecasting accuracy. Forecasting models based on calendar variables alone did in general detect patterns of daily variability in ED volume and thus could be used for developing an automated system for better planning of personnel resources. © 2013 by the Society for Academic Emergency Medicine.

Using remote sensing environmental data to forecast malaria incidence at a rural district hospital in Western Kenya.

PubMed

Sewe, Maquins Odhiambo; Tozan, Yesim; Ahlm, Clas; Rocklöv, Joacim

2017-06-01

Malaria surveillance data provide opportunity to develop forecasting models. Seasonal variability in environmental factors correlate with malaria transmission, thus the identification of transmission patterns is useful in developing prediction models. However, with changing seasonal transmission patterns, either due to interventions or shifting weather seasons, traditional modelling approaches may not yield adequate predictive skill. Two statistical models,a general additive model (GAM) and GAMBOOST model with boosted regression were contrasted by assessing their predictive accuracy in forecasting malaria admissions at lead times of one to three months. Monthly admission data for children under five years with confirmed malaria at the Siaya district hospital in Western Kenya for the period 2003 to 2013 were used together with satellite derived data on rainfall, average temperature and evapotranspiration(ET). There was a total of 8,476 confirmed malaria admissions. The peak of malaria season changed and malaria admissions reduced overtime. The GAMBOOST model at 1-month lead time had the highest predictive skill during both the training and test periods and thus can be utilized in a malaria early warning system.

Estimating natural monthly streamflows in California and the likelihood of anthropogenic modification

USGS Publications Warehouse

Carlisle, Daren M.; Wolock, David M.; Howard, Jeannette K.; Grantham, Theodore E.; Fesenmyer, Kurt; Wieczorek, Michael

2016-12-12

Because natural patterns of streamflow are a fundamental property of the health of streams, there is a critical need to quantify the degree to which human activities have modified natural streamflows. A requirement for assessing streamflow modification in a given stream is a reliable estimate of flows expected in the absence of human influences. Although there are many techniques to predict streamflows in specific river basins, there is a lack of approaches for making predictions of natural conditions across large regions and over many decades. In this study conducted by the U.S. Geological Survey, in cooperation with The Nature Conservancy and Trout Unlimited, the primary objective was to develop empirical models that predict natural (that is, unaffected by land use or water management) monthly streamflows from 1950 to 2012 for all stream segments in California. Models were developed using measured streamflow data from the existing network of streams where daily flow monitoring occurs, but where the drainage basins have minimal human influences. Widely available data on monthly weather conditions and the physical attributes of river basins were used as predictor variables. Performance of regional-scale models was comparable to that of published mechanistic models for specific river basins, indicating the models can be reliably used to estimate natural monthly flows in most California streams. A second objective was to develop a model that predicts the likelihood that streams experience modified hydrology. New models were developed to predict modified streamflows at 558 streamflow monitoring sites in California where human activities affect the hydrology, using basin-scale geospatial indicators of land use and water management. Performance of these models was less reliable than that for the natural-flow models, but results indicate the models could be used to provide a simple screening tool for identifying, across the State of California, which streams may be experiencing anthropogenic flow modification.

Neurodevelopment in Early Childhood Affected by Prenatal Lead Exposure and Iron Intake.

PubMed

Shah-Kulkarni, Surabhi; Ha, Mina; Kim, Byung-Mi; Kim, Eunjeong; Hong, Yun-Chul; Park, Hyesook; Kim, Yangho; Kim, Bung-Nyun; Chang, Namsoo; Oh, Se-Young; Kim, Young Ju; Kimʼs, Young Ju; Lee, Boeun; Ha, Eun-Hee

2016-01-01

No safe threshold level of lead exposure in children has been recognized. Also, the information on shielding effect of maternal dietary iron intake during pregnancy on the adverse effects of prenatal lead exposure on children's postnatal neurocognitive development is very limited. We examined the association of prenatal lead exposure and neurodevelopment in children at 6, 12, 24, and 36 months and the protective action of maternal dietary iron intake against the impact of lead exposure. The study participants comprise 965 pregnant women and their subsequent offspring of the total participants enrolled in the Mothers and Children's environmental health study: a prospective birth cohort study. Generalized linear model and linear mixed model analysis were performed to analyze the effect of prenatal lead exposure and mother's dietary iron intake on children's cognitive development at 6, 12, 24, and 36 months. Maternal late pregnancy lead was marginally associated with deficits in mental development index (MDI) of children at 6 months. Mothers having less than 75th percentile of dietary iron intake during pregnancy showed significant increase in the harmful effect of late pregnancy lead exposure on MDI at 6 months. Linear mixed model analyses showed the significant detrimental effect of prenatal lead exposure in late pregnancy on cognitive development up to 36 months in children of mothers having less dietary iron intake during pregnancy. Thus, our findings imply importance to reduce prenatal lead exposure and have adequate iron intake for better neurodevelopment in children.

Neurodevelopment in Early Childhood Affected by Prenatal Lead Exposure and Iron Intake

PubMed Central

Shah-Kulkarni, Surabhi; Ha, Mina; Kim, Byung-Mi; Kim, Eunjeong; Hong, Yun-Chul; Park, Hyesook; Kim, Yangho; Kim, Bung-Nyun; Chang, Namsoo; Oh, Se-Young; Kim, Young Ju; Lee, Boeun; Ha, Eun-Hee

2016-01-01

Abstract No safe threshold level of lead exposure in children has been recognized. Also, the information on shielding effect of maternal dietary iron intake during pregnancy on the adverse effects of prenatal lead exposure on children's postnatal neurocognitive development is very limited. We examined the association of prenatal lead exposure and neurodevelopment in children at 6, 12, 24, and 36 months and the protective action of maternal dietary iron intake against the impact of lead exposure. The study participants comprise 965 pregnant women and their subsequent offspring of the total participants enrolled in the Mothers and Children's environmental health study: a prospective birth cohort study. Generalized linear model and linear mixed model analysis were performed to analyze the effect of prenatal lead exposure and mother's dietary iron intake on children's cognitive development at 6, 12, 24, and 36 months. Maternal late pregnancy lead was marginally associated with deficits in mental development index (MDI) of children at 6 months. Mothers having less than 75th percentile of dietary iron intake during pregnancy showed significant increase in the harmful effect of late pregnancy lead exposure on MDI at 6 months. Linear mixed model analyses showed the significant detrimental effect of prenatal lead exposure in late pregnancy on cognitive development up to 36 months in children of mothers having less dietary iron intake during pregnancy. Thus, our findings imply importance to reduce prenatal lead exposure and have adequate iron intake for better neurodevelopment in children. PMID:26825887

Beyond Brain Growth: Other Factors Affecting Cognitive Development.

ERIC Educational Resources Information Center

Stefanich, Greg; Aldridge, Mary Nan

The intellectual model of Jean Piaget asserts that individuals pass through a series of various intellectual stages as they mature. Human development is categorized into four basic stages: (1) sensory motor stage, which lasts from birth to about eighteen months; (2) preoperational stage, lasting from eighteen months to about seven years; (3)…

Modeling Prosocial Behavior Increases Helping in 16-Month-Olds.

PubMed

Schuhmacher, Nils; Köster, Moritz; Kärtner, Joscha

2018-04-17

In two experiments, the imitation of helping behavior in 16-month-olds was investigated. In Study 1 (N = 31), infants either observed an adult model helping or not helping another individual before they had the opportunity to assist an unfamiliar experimenter. In one of two tasks, more children helped in the prosocial model condition than in the no model control condition. In Study 2 (N = 60), a second control condition was included to test whether infants imitated the prosocial intention (no neediness control). Children in the prosocial model condition helped more readily than children in the no model condition, with the second control condition falling in between. These findings propose that modeling provides a critical learning mechanism in early prosocial development. © 2018 Society for Research in Child Development.

Improving groundwater predictions utilizing seasonal precipitation forecasts from general circulation models forced with sea surface temperature forecasts

USGS Publications Warehouse

Almanaseer, Naser; Sankarasubramanian, A.; Bales, Jerad

2014-01-01

Recent studies have found a significant association between climatic variability and basin hydroclimatology, particularly groundwater levels, over the southeast United States. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater-level forecasts based on the precipitation forecasts from ECHAM 4.5 General Circulation Model Forced with Sea Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater Climate Response Network and Hydro-Climatic Data Network were selected to represent groundwater and surface water flows, respectively, having minimal anthropogenic influences within the Flint River Basin in Georgia, United States. The writers employ two low-dimensional models [principle component regression (PCR) and canonical correlation analysis (CCA)] for predicting groundwater and streamflow at both seasonal and monthly timescales. Three modeling schemes are considered at the beginning of January to predict winter (January, February, and March) and spring (April, May, and June) streamflow and groundwater for the selected sites within the Flint River Basin. The first scheme (model 1) is a null model and is developed using PCR for every streamflow and groundwater site using previous 3-month observations (October, November, and December) available at that particular site as predictors. Modeling schemes 2 and 3 are developed using PCR and CCA, respectively, to evaluate the role of precipitation forecasts in improving monthly and seasonal groundwater predictions. Modeling scheme 3, which employs a CCA approach, is developed for each site by considering observed groundwater levels from nearby sites as predictands. The performance of these three schemes is evaluated using two metrics (correlation coefficient and relative RMS error) by developing groundwater-level forecasts based on leave-five-out cross-validation. Results from the research reported in this paper show that using precipitation forecasts in climate models improves the ability to predict the interannual variability of winter and spring streamflow and groundwater levels over the basin. However, significant conditional bias exists in all the three modeling schemes, which indicates the need to consider improved modeling schemes as well as the availability of longer time-series of observed hydroclimatic information over the basin.

Development of a database-driven system for simulating water temperature in the lower Yakima River main stem, Washington, for various climate scenarios

USGS Publications Warehouse

Voss, Frank; Maule, Alec

2013-01-01

A model for simulating daily maximum and mean water temperatures was developed by linking two existing models: one developed by the U.S. Geological Survey and one developed by the Bureau of Reclamation. The study area included the lower Yakima River main stem between the Roza Dam and West Richland, Washington. To automate execution of the labor-intensive models, a database-driven model automation program was developed to decrease operation costs, to reduce user error, and to provide the capability to perform simulations quickly for multiple management and climate change scenarios. Microsoft© SQL Server 2008 R2 Integration Services packages were developed to (1) integrate climate, flow, and stream geometry data from diverse sources (such as weather stations, a hydrologic model, and field measurements) into a single relational database; (2) programmatically generate heavily formatted model input files; (3) iteratively run water temperature simulations; (4) process simulation results for export to other models; and (5) create a database-driven infrastructure that facilitated experimentation with a variety of scenarios, node permutations, weather data, and hydrologic conditions while minimizing costs of running the model with various model configurations. As a proof-of-concept exercise, water temperatures were simulated for a "Current Conditions" scenario, where local weather data from 1980 through 2005 were used as input, and for "Plus 1" and "Plus 2" climate warming scenarios, where the average annual air temperatures used in the Current Conditions scenario were increased by 1degree Celsius (°C) and by 2°C, respectively. Average monthly mean daily water temperatures simulated for the Current Conditions scenario were compared to measured values at the Bureau of Reclamation Hydromet gage at Kiona, Washington, for 2002-05. Differences ranged between 1.9° and 1.1°C for February, March, May, and June, and were less than 0.8°C for the remaining months of the year. The difference between current conditions and measured monthly values for the two warmest months (July and August) were 0.5°C and 0.2°C, respectively. The model predicted that water temperature generally becomes less sensitive to air temperature increases as the distance from the mouth of the river decreases. As a consequence, the difference between climate warming scenarios also decreased. The pattern of decreasing sensitivity is most pronounced from August to October. Interactive graphing tools were developed to explore the relative sensitivity of average monthly and mean daily water temperature to increases in air temperature for model output locations along the lower Yakima River main stem.

Statistical model for forecasting monthly large wildfire events in western United States

Treesearch

Haiganoush K. Preisler; Anthony L. Westerling

2006-01-01

The ability to forecast the number and location of large wildfire events (with specified confidence bounds) is important to fire managers attempting to allocate and distribute suppression efforts during severe fire seasons. This paper describes the development of a statistical model for assessing the forecasting skills of fire-danger predictors and producing 1-month-...

A Wavelet Support Vector Machine Combination Model for Singapore Tourist Arrival to Malaysia

NASA Astrophysics Data System (ADS)

Rafidah, A.; Shabri, Ani; Nurulhuda, A.; Suhaila, Y.

2017-08-01

In this study, wavelet support vector machine model (WSVM) is proposed and applied for monthly data Singapore tourist time series prediction. The WSVM model is combination between wavelet analysis and support vector machine (SVM). In this study, we have two parts, first part we compare between the kernel function and second part we compare between the developed models with single model, SVM. The result showed that kernel function linear better than RBF while WSVM outperform with single model SVM to forecast monthly Singapore tourist arrival to Malaysia.

Artificial neural network with backpropagation learning to predict mean monthly total ozone in Arosa, Switzerland

NASA Astrophysics Data System (ADS)

Chattopadhyay, Surajit; Bandyopadhyay, Goutami

2007-01-01

Present study deals with the mean monthly total ozone time series over Arosa, Switzerland. The study period is 1932-1971. First of all, the total ozone time series has been identified as a complex system and then Artificial Neural Networks models in the form of Multilayer Perceptron with back propagation learning have been developed. The models are Single-hidden-layer and Two-hidden-layer Perceptrons with sigmoid activation function. After sequential learning with learning rate 0.9 the peak total ozone period (February-May) concentrations of mean monthly total ozone have been predicted by the two neural net models. After training and validation, both of the models are found skillful. But, Two-hidden-layer Perceptron is found to be more adroit in predicting the mean monthly total ozone concentrations over the aforesaid period.

Differential effects of parenting in preterm and full-term children on developmental outcomes.

PubMed

Maupin, Angela N; Fine, Jodene Goldenring

2014-12-01

To examine the relations between preterm birth, parenting behavior during early childhood, cognitive development, and social-emotional outcomes at Kindergarten entry, and to determine whether parenting behavior differentially influences this developing system in children born preterm compared to children born full-term. The nationally representative sample comprised 3600 full-term and 1300 preterm children born in the US in the year 2001. All children who entered Kindergarten and who participated in data collection at 9 months, 24 months, and Kindergarten entry were included in the study. Measures of parenting behavior were collected at 9 and 24 months and cognitive development at 24 months via home visits. Social-emotional outcomes were assessed at Kindergarten entry via parent and teacher report. Multiple-sample Structural Equation Modeling was used to analyze group differences in a model whereby early childhood parenting behavior predicted cognitive outcomes, and social-emotional outcomes at Kindergarten entry, and indirectly predicted social-emotional outcomes via early cognitive processes. The full sample developmental model indicated excellent fit to the data. Preterm birth status indirectly influenced social-emotional outcomes at Kindergarten entry via its effect on early childhood parenting behavior and cognitive development. The multi-sample model revealed significant differences in the way in which early parenting behavior exerted its influence on outcomes at Kindergarten entry in preterm children compared to full-term children. For preterm children, parenting indirectly influenced social-emotional outcomes via early cognitive functioning. Findings highlight the importance of early identification and targeted parenting programs to support early cognitive development in preterm children. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Growth of Tense Productivity

ERIC Educational Resources Information Center

Rispoli, Matthew; Hadley, Pamela A.; Holt, Janet K.

2009-01-01

Purpose: This study tests empirical predictions of a maturational model for the growth of tense in children younger than 36 months using a type-based productivity measure. Method: Caregiver-child language samples were collected from 20 typically developing children every 3 months from 21 to 33 months of age. Growth in the productivity of tense…

Monthly gravity field solutions based on GRACE observations generated with the Celestial Mechanics Approach

NASA Astrophysics Data System (ADS)

Meyer, Ulrich; Jäggi, Adrian; Beutler, Gerhard

2012-09-01

The main objective of the Gravity Recovery And Climate Experiment (GRACE) satellite mission consists of determining the temporal variations of the Earth's gravity field. These variations are captured by time series of gravity field models of limited resolution at, e.g., monthly intervals. We present a new time series of monthly models, which was computed with the so-called Celestial Mechanics Approach (CMA), developed at the Astronomical Institute of the University of Bern (AIUB). The secular and seasonal variations in the monthly models are tested for statistical significance. Calibrated errors are derived from inter-annual variations. The time-variable signal can be extracted at least up to degree 60, but the gravity field coefficients of orders above 45 are heavily contaminated by noise. This is why a series of monthly models is computed up to a maximum degree of 60, but only a maximum order of 45. Spectral analysis of the residual time-variable signal shows a distinctive peak at a period of 160 days, which shows up in particular in the C20 spherical harmonic coefficient. Basic filter- and scaling-techniques are introduced to evaluate the monthly models. For this purpose, the variability over the oceans is investigated, which serves as a measure for the noisiness of the models. The models in selected regions show the expected seasonal and secular variations, which are in good agreement with the monthly models of the Helmholtz Centre Potsdam, German Research Centre for Geosciences (GFZ). The results also reveal a few small outliers, illustrating the necessity for improved data screening. Our monthly models are available at the web page of the International Centre for Global Earth Models (ICGEM).

Modeling temporal and spatial variability of leaf wetness duration in Brazil

NASA Astrophysics Data System (ADS)

Alvares, Clayton Alcarde; de Mattos, Eduardo Moré; Sentelhas, Paulo Cesar; Miranda, Aline Cristina; Stape, José Luiz

2015-05-01

Leaf wetness duration (LWD) is recognized as a very important conditioner of crops and forests diseases, but clearly, there is a considerable gap in literature on temporal models for prediction of LWD in broad regions from standard meteorological data. The objective of this study was to develop monthly LWD models based on the relationship between hours of relative humidity (RH) ≥ 90 % and average RH for Brazil and based on these models to characterize the temporal and spatial LWD variability across the country. Two different relative humidity databases, being one in an hourly basis (RHh) and another in a monthly basis (RHm), were used. To elaborate the LWD models, 58 automatic weather stations distributed across the country were selected. Monthly LWD maps for the entire country were prepared, and for that, the RHm from the 358 conventional weather stations were interpolated using geostatistical techniques. RHm and LWD showed sigmoidal relationship with determination coefficient above 0.84 and were highly significant ( p < 0.0001). In relation to the validation of the LWD monthly models, a very good performance for all months was obtained, with very high precision with r between 0.92 and 0.96. Regarding the errors, mean error showed a slight tendency of overestimation during February (0.29 h day-1), May (0.31 h day-1), July (0.14 h day-1), and August (0.34 h day-1), whereas for the other months, the tendency was of underestimation like January (-0.27 h day-1) and March (-0.25 h day-1). Even as a first approach, the results presented here represent a great advance in the climatology of LWD for Brazil and will allow the development of studies related to crop and forest diseases control plans.

Scaling uncertainties in estimating canopy foliar maintenance respiration for black spruce ecosystems in Alaska

USGS Publications Warehouse

Zhang, X.; McGuire, A.D.; Ruess, Roger W.

2006-01-01

A major challenge confronting the scientific community is to understand both patterns of and controls over spatial and temporal variability of carbon exchange between boreal forest ecosystems and the atmosphere. An understanding of the sources of variability of carbon processes at fine scales and how these contribute to uncertainties in estimating carbon fluxes is relevant to representing these processes at coarse scales. To explore some of the challenges and uncertainties in estimating carbon fluxes at fine to coarse scales, we conducted a modeling analysis of canopy foliar maintenance respiration for black spruce ecosystems of Alaska by scaling empirical hourly models of foliar maintenance respiration (Rm) to estimate canopy foliar Rm for individual stands. We used variation in foliar N concentration among stands to develop hourly stand-specific models and then developed an hourly pooled model. An uncertainty analysis identified that the most important parameter affecting estimates of canopy foliar Rm was one that describes R m at 0??C per g N, which explained more than 55% of variance in annual estimates of canopy foliar Rm. The comparison of simulated annual canopy foliar Rm identified significant differences between stand-specific and pooled models for each stand. This result indicates that control over foliar N concentration should be considered in models that estimate canopy foliar Rm of black spruce stands across the landscape. In this study, we also temporally scaled the hourly stand-level models to estimate canopy foliar Rm of black spruce stands using mean monthly temperature data. Comparisons of monthly Rm between the hourly and monthly versions of the models indicated that there was very little difference between the estimates of hourly and monthly models, suggesting that hourly models can be aggregated to use monthly input data with little loss of precision. We conclude that uncertainties in the use of a coarse-scale model for estimating canopy foliar Rm at regional scales depend on uncertainties in representing needle-level respiration and on uncertainties in representing the spatial variability of canopy foliar N across a region. The development of spatial data sets of canopy foliar N represents a major challenge in estimating canopy foliar maintenance respiration at regional scales. ?? Springer 2006.

Breakthrough seizures—Further analysis of the Standard versus New Antiepileptic Drugs (SANAD) study

PubMed Central

Powell, Graham A.; Tudur Smith, Catrin; Marson, Anthony G.

2017-01-01

Objectives To develop prognostic models for risk of a breakthrough seizure, risk of seizure recurrence after a breakthrough seizure, and likelihood of achieving 12-month remission following a breakthrough seizure. A breakthrough seizure is one that occurs following at least 12 months remission whilst on treatment. Methods We analysed data from the SANAD study. This long-term randomised trial compared treatments for participants with newly diagnosed epilepsy. Multivariable Cox models investigated how clinical factors affect the probability of each outcome. Best fitting multivariable models were produced with variable reduction by Akaike’s Information Criterion. Risks associated with combinations of risk factors were calculated from each multivariable model. Results Significant factors in the multivariable model for risk of a breakthrough seizure following 12-month remission were number of tonic-clonic seizures by achievement of 12-month remission, time taken to achieve 12-month remission, and neurological insult. Significant factors in the model for risk of seizure recurrence following a breakthrough seizure were total number of drugs attempted to achieve 12-month remission, time to achieve 12-month remission prior to breakthrough seizure, and breakthrough seizure treatment decision. Significant factors in the model for likelihood of achieving 12-month remission after a breakthrough seizure were gender, age at breakthrough seizure, time to achieve 12-month remission prior to breakthrough, and breakthrough seizure treatment decision. Conclusions This is the first analysis to consider risk of a breakthrough seizure and subsequent outcomes. The described models can be used to identify people most likely to have a breakthrough seizure, a seizure recurrence following a breakthrough seizure, and to achieve 12-month remission following a breakthrough seizure. The results suggest that focussing on achieving 12-month remission swiftly represents the best therapeutic aim to reduce the risk of a breakthrough seizure and subsequent negative outcomes. This will aid individual patient risk stratification and the design of future epilepsy trials. PMID:29267375

Argentina soybean yield model

NASA Technical Reports Server (NTRS)

Callis, S. L.; Sakamoto, C.

1984-01-01

A model based on multiple regression was developed to estimate soybean yields for the country of Argentina. A meteorological data set was obtained for the country by averaging data for stations within the soybean growing area. Predictor variables for the model were derived from monthly total precipitation and monthly average temperature. A trend variable was included for the years 1969 to 1978 since an increasing trend in yields due to technology was observed between these years.

Predictors of survival in patients with recurrent ovarian cancer undergoing secondary cytoreductive surgery based on the pooled analysis of an international collaborative cohort

PubMed Central

Zang, R Y; Harter, P; Chi, D S; Sehouli, J; Jiang, R; Tropé, C G; Ayhan, A; Cormio, G; Xing, Y; Wollschlaeger, K M; Braicu, E I; Rabbitt, C A; Oksefjell, H; Tian, W J; Fotopoulou, C; Pfisterer, J; du Bois, A; Berek, J S

2011-01-01

Background: This study aims to identify prognostic factors and to develop a risk model predicting survival in patients undergoing secondary cytoreductive surgery (SCR) for recurrent epithelial ovarian cancer. Methods: Individual data of 1100 patients with recurrent ovarian cancer of a progression-free interval at least 6 months who underwent SCR were pooled analysed. A simplified scoring system for each independent prognostic factor was developed according to its coefficient. Internal validation was performed to assess the discrimination of the model. Results: Complete SCR was strongly associated with the improvement of survival, with a median survival of 57.7 months, when compared with 27.0 months in those with residual disease of 0.1–1 cm and 15.6 months in those with residual disease of >1 cm, respectively (P<0.0001). Progression-free interval (⩽23.1 months vs >23.1 months, hazard ratio (HR): 1.72; score: 2), ascites at recurrence (present vs absent, HR: 1.27; score: 1), extent of recurrence (multiple vs localised disease, HR: 1.38; score: 1) as well as residual disease after SCR (R1 vs R0, HR: 1.90, score: 2; R2 vs R0, HR: 3.0, score: 4) entered into the risk model. Conclusion: This prognostic model may provide evidence to predict survival benefit from secondary cytoreduction in patients with recurrent ovarian cancer. PMID:21878937

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

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

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.

2014-09-12

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressivemore » Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.« less

Medium term municipal solid waste generation prediction by autoregressive integrated moving average

NASA Astrophysics Data System (ADS)

Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

2014-09-01

Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

Sensitivity of Regional Hydropower Generation to the Projected Changes in Future Watershed Hydrology

NASA Astrophysics Data System (ADS)

Kao, S. C.; Naz, B. S.; Gangrade, S.

2015-12-01

Hydropower is a key contributor to the renewable energy portfolio due to its established development history and the diverse benefits it provides to the electric power systems. With the projected change in the future watershed hydrology, including shift of snowmelt timing, increasing occurrence of extreme precipitation, and change in drought frequencies, there is a need to investigate how the regional hydropower generation may change correspondingly. To evaluate the sensitivity of watershed storage and hydropower generation to future climate change, a lumped Watershed Runoff-Energy Storage (WRES) model is developed to simulate the annual and seasonal hydropower generation at various hydropower areas in the United States. For each hydropower study area, the WRES model use the monthly precipitation and naturalized (unregulated) runoff as inputs to perform a runoff mass balance calculation for the total monthly runoff storage in all reservoirs and retention facilities in the watershed, and simulate the monthly regulated runoff release and hydropower generation through the system. The WRES model is developed and calibrated using the historic (1980-2009) monthly precipitation, runoff, and generation data, and then driven by a large set of dynamically- and statistically-downscaled Coupled Model Intercomparison Project Phase 5 climate projections to simulate the change of watershed storage and hydropower generation under different future climate scenarios. The results among different hydropower regions, storage capacities, emission scenarios, and timescales are compared and discussed in this study.

Land use regression models to assess air pollution exposure in Mexico City using finer spatial and temporal input parameters.

PubMed

Son, Yeongkwon; Osornio-Vargas, Álvaro R; O'Neill, Marie S; Hystad, Perry; Texcalac-Sangrador, José L; Ohman-Strickland, Pamela; Meng, Qingyu; Schwander, Stephan

2018-05-17

The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM 2.5 , PM 10 , O 3 , NO 2 , CO and SO 2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO). Hourly traffic density was included as a temporal variable besides meteorological and holiday variables. Models of hourly, daily, monthly, 6-monthly and annual averages were developed and evaluated using traditional and novel indices. The developed spatiotemporal LUR models yielded predicted concentrations with good spatial and temporal agreements with measured pollutant levels except for the hourly PM 2.5 , PM 10 and SO 2 . Most of the LUR models met performance goals based on the standardized indices. LUR models with temporal scales greater than one hour were successfully developed using mixed effect models with LASSO and showed superior model performance compared to earlier LUR models, especially for time scales of a day or longer. The newly developed LUR models will be further refined with ongoing Mexico City air pollution sampling campaigns to improve personal exposure assessments. Copyright © 2018. Published by Elsevier B.V.

Building more realistic reservoir optimization models using data mining - A case study of Shelbyville Reservoir

NASA Astrophysics Data System (ADS)

Hejazi, Mohamad I.; Cai, Ximing

2011-06-01

In this paper, we promote a novel approach to develop reservoir operation routines by learning from historical hydrologic information and reservoir operations. The proposed framework involves a knowledge discovery step to learn the real drivers of reservoir decision making and to subsequently build a more realistic (enhanced) model formulation using stochastic dynamic programming (SDP). The enhanced SDP model is compared to two classic SDP formulations using Lake Shelbyville, a reservoir on the Kaskaskia River in Illinois, as a case study. From a data mining procedure with monthly data, the past month's inflow ( Qt-1 ), current month's inflow ( Qt), past month's release ( Rt-1 ), and past month's Palmer drought severity index ( PDSIt-1 ) are identified as important state variables in the enhanced SDP model for Shelbyville Reservoir. When compared to a weekly enhanced SDP model of the same case study, a different set of state variables and constraints are extracted. Thus different time scales for the model require different information. We demonstrate that adding additional state variables improves the solution by shifting the Pareto front as expected while using new constraints and the correct objective function can significantly reduce the difference between derived policies and historical practices. The study indicates that the monthly enhanced SDP model resembles historical records more closely and yet provides lower expected average annual costs than either of the two classic formulations (25.4% and 4.5% reductions, respectively). The weekly enhanced SDP model is compared to the monthly enhanced SDP, and it shows that acquiring the correct temporal scale is crucial to model reservoir operation for particular objectives.

Lung Inflammatory Effects, Tumorigenesis, and Emphysema Development in a Long-Term Inhalation Study with Cigarette Mainstream Smoke in Mice

PubMed Central

Stabbert, Regina

2013-01-01

Cigarette smoking is the leading cause of lung cancer and chronic obstructive pulmonary disease, yet there is little mechanistic information available in the literature. To improve this, laboratory models for cigarette mainstream smoke (MS) inhalation–induced chronic disease development are needed. The current study investigated the effects of exposing male A/J mice to MS (6h/day, 5 days/week at 150 and 300mg total particulate matter per cubic meter) for 2.5, 5, 10, and 18 months in selected combinations with postinhalation periods of 0, 4, 8, and 13 months. Histopathological examination of step-serial sections of the lungs revealed nodular hyperplasia of the alveolar epithelium and bronchioloalveolar adenoma and adenocarcinoma. At 18 months, lung tumors were found to be enhanced concentration dependently (up to threefold beyond sham exposure), irrespective of whether MS inhalation had been performed for the complete study duration or was interrupted after 5 or 10 months and followed by postinhalation periods. Morphometric analysis revealed an increase in the extent of emphysematous changes after 5 months of MS inhalation, which did not significantly change over the following 13 months of study duration, irrespective of whether MS exposure was continued or not. These changes were found to be accompanied by a complex pattern of transient and sustained pulmonary inflammatory changes that may contribute to the observed pathogeneses. Data from this study suggest that the A/J mouse model holds considerable promise as a relevant model for investigating smoking-related emphysema and adenocarcinoma development. PMID:23104432

Monthly monsoon rainfall forecasting using artificial neural networks

NASA Astrophysics Data System (ADS)

Ganti, Ravikumar

2014-10-01

Indian agriculture sector heavily depends on monsoon rainfall for successful harvesting. In the past, prediction of rainfall was mainly performed using regression models, which provide reasonable accuracy in the modelling and forecasting of complex physical systems. Recently, Artificial Neural Networks (ANNs) have been proposed as efficient tools for modelling and forecasting. A feed-forward multi-layer perceptron type of ANN architecture trained using the popular back-propagation algorithm was employed in this study. Other techniques investigated for modeling monthly monsoon rainfall include linear and non-linear regression models for comparison purposes. The data employed in this study include monthly rainfall and monthly average of the daily maximum temperature in the North Central region in India. Specifically, four regression models and two ANN model's were developed. The performance of various models was evaluated using a wide variety of standard statistical parameters and scatter plots. The results obtained in this study for forecasting monsoon rainfalls using ANNs have been encouraging. India's economy and agricultural activities can be effectively managed with the help of the availability of the accurate monsoon rainfall forecasts.

Development of prediction models of stress and long-term disability among claimants to injury compensation systems: a cohort study.

PubMed

Spittal, Matthew J; Grant, Genevieve; O'Donnell, Meaghan; McFarlane, Alexander C; Studdert, David M

2018-04-28

We sought to develop prognostic risk scores for compensation-related stress and long-term disability using markers collected within 3 months of a serious injury. Cohort study. Predictors were collected at baseline and at 3 months postinjury. Outcome data were collected at 72 months postinjury. Hospitalised patients with serious injuries recruited from four major trauma hospitals in Australia. 332 participants who made claims for compensation for their injuries to a transport accident scheme or a workers' compensation scheme. 12-item WHO Disability Assessment Schedule and 6 items from the Claims Experience Survey. Our model for long-term disability had four predictors (unemployed at the time of injury, history of a psychiatric disorder at time of injury, post-traumatic stress disorder symptom severity at 3 months and disability at 3 months). This model had good discrimination (R 2 =0.37) and calibration. The disability risk score had a score range of 0-180, and at a threshold of 80 had sensitivity of 56% and specificity of 86%. Our model for compensation-related stress had five predictors (intensive care unit admission, discharged to home, number of traumatic events prior to injury, depression at 3 months and not working at 3 months). This model also had good discrimination (area under the curve=0.83) and calibration. The compensation-related stress risk score had score range of 0-220 and at a threshold of 100 had sensitivity of 74% and specificity of 75%. By combining these two scoring systems, we were able to identify the subgroup of claimants at highest risk of experiencing both outcomes. The ability to identify at an early stage claimants at high risk of compensation-related stress and poor recovery is potentially valuable for claimants and the compensation agencies that serve them. The scoring systems we developed could be incorporated into the claims-handling processes to guide prevention-oriented interventions. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Hydrological time series modeling: A comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques

NASA Astrophysics Data System (ADS)

Lohani, A. K.; Kumar, Rakesh; Singh, R. D.

2012-06-01

SummaryTime series modeling is necessary for the planning and management of reservoirs. More recently, the soft computing techniques have been used in hydrological modeling and forecasting. In this study, the potential of artificial neural networks and neuro-fuzzy system in monthly reservoir inflow forecasting are examined by developing and comparing monthly reservoir inflow prediction models, based on autoregressive (AR), artificial neural networks (ANNs) and adaptive neural-based fuzzy inference system (ANFIS). To take care the effect of monthly periodicity in the flow data, cyclic terms are also included in the ANN and ANFIS models. Working with time series flow data of the Sutlej River at Bhakra Dam, India, several ANN and adaptive neuro-fuzzy models are trained with different input vectors. To evaluate the performance of the selected ANN and adaptive neural fuzzy inference system (ANFIS) models, comparison is made with the autoregressive (AR) models. The ANFIS model trained with the input data vector including previous inflows and cyclic terms of monthly periodicity has shown a significant improvement in the forecast accuracy in comparison with the ANFIS models trained with the input vectors considering only previous inflows. In all cases ANFIS gives more accurate forecast than the AR and ANN models. The proposed ANFIS model coupled with the cyclic terms is shown to provide better representation of the monthly inflow forecasting for planning and operation of reservoir.

Comparative studies using the Morris water maze to assess spatial memory deficits in two transgenic mouse models of Alzheimer's disease.

PubMed

Edwards, Stephen R; Hamlin, Adam S; Marks, Nicola; Coulson, Elizabeth J; Smith, Maree T

2014-10-01

Evaluation of the efficacy of novel therapeutics for potential treatment of Alzheimer's disease (AD) requires an animal model that develops age-related cognitive deficits reproducibly between independent groups of investigators. Herein we assessed comparative temporal changes in spatial memory function in two commercially available transgenic mouse models of AD using the Morris water maze (MWM), incorporating both visible and hidden platform training. Individual cohorts of cDNA-based 'line 85'-derived double-transgenic mice coexpressing the 'Swedish' mutation of amyloid precursor protein (APPSwe) and the presenillin 1 (PS1) 'dE9' mutation were assessed in the MWM at mean ages of 3.6, 9.3 and 14.8 months. We found significant deficits in spatial memory retention in APPSwe/PS1dE9 mice aged 3.6 months and robust deficits in spatial memory acquisition and retention in APPSwe/PS1dE9 mice aged 9.3 months, with a further significant decline by age 14.8 months. β-Amyloid deposits were present in brain sections by 7.25 months of age. In contrast, MWM studies with individual cohorts (aged 4-21 months) of single-transgenic genomic-based APPSwe mice expressing APPSwe on a yeast artificial chromosomal (YAC) construct showed no significant deficits in spatial memory acquisition until 21 months of age. There were no significant deficits in spatial memory retention up to 21 months of age and β-amyloid deposits were not present in brain sections up to 24 months of age. These data, generated using comprehensive study designs, show that APPSwe/PS1dE9 but not APPSwe YAC mice appear to provide a suitably robust model of AD for efficacy assessment of novel AD treatments in development. © 2014 Wiley Publishing Asia Pty Ltd.

Empirical and modeled synoptic cloud climatology of the Arctic Ocean

NASA Technical Reports Server (NTRS)

Barry, R. G.; Newell, J. P.; Schweiger, A.; Crane, R. G.

1986-01-01

A set of cloud cover data were developed for the Arctic during the climatically important spring/early summer transition months. Parallel with the determination of mean monthly cloud conditions, data for different synoptic pressure patterns were also composited as a means of evaluating the role of synoptic variability on Arctic cloud regimes. In order to carry out this analysis, a synoptic classification scheme was developed for the Arctic using an objective typing procedure. A second major objective was to analyze model output of pressure fields and cloud parameters from a control run of the Goddard Institue for Space Studies climate model for the same area and to intercompare the synoptic climatatology of the model with that based on the observational data.

Statistical forecast of seasonal discharge in Central Asia using observational records: development of a generic linear modelling tool for operational water resource management

NASA Astrophysics Data System (ADS)

Apel, Heiko; Abdykerimova, Zharkinay; Agalhanova, Marina; Baimaganbetov, Azamat; Gavrilenko, Nadejda; Gerlitz, Lars; Kalashnikova, Olga; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Gafurov, Abror

2018-04-01

The semi-arid regions of Central Asia crucially depend on the water resources supplied by the mountainous areas of the Tien Shan and Pamir and Altai mountains. During the summer months the snow-melt- and glacier-melt-dominated river discharge originating in the mountains provides the main water resource available for agricultural production, but also for storage in reservoirs for energy generation during the winter months. Thus a reliable seasonal forecast of the water resources is crucial for sustainable management and planning of water resources. In fact, seasonal forecasts are mandatory tasks of all national hydro-meteorological services in the region. In order to support the operational seasonal forecast procedures of hydro-meteorological services, this study aims to develop a generic tool for deriving statistical forecast models of seasonal river discharge based solely on observational records. The generic model structure is kept as simple as possible in order to be driven by meteorological and hydrological data readily available at the hydro-meteorological services, and to be applicable for all catchments in the region. As snow melt dominates summer runoff, the main meteorological predictors for the forecast models are monthly values of winter precipitation and temperature, satellite-based snow cover data, and antecedent discharge. This basic predictor set was further extended by multi-monthly means of the individual predictors, as well as composites of the predictors. Forecast models are derived based on these predictors as linear combinations of up to four predictors. A user-selectable number of the best models is extracted automatically by the developed model fitting algorithm, which includes a test for robustness by a leave-one-out cross-validation. Based on the cross-validation the predictive uncertainty was quantified for every prediction model. Forecasts of the mean seasonal discharge of the period April to September are derived every month from January until June. The application of the model for several catchments in Central Asia - ranging from small to the largest rivers (240 to 290 000 km2 catchment area) - for the period 2000-2015 provided skilful forecasts for most catchments already in January, with adjusted R2 values of the best model in the range of 0.6-0.8 for most of the catchments. The skill of the prediction increased every following month, i.e. with reduced lead time, with adjusted R2 values usually in the range 0.8-0.9 for the best and 0.7-0.8 on average for the set of models in April just before the prediction period. The later forecasts in May and June improve further due to the high predictive power of the discharge in the first 2 months of the snow melt period. The improved skill of the set of forecast models with decreasing lead time resulted in narrow predictive uncertainty bands at the beginning of the snow melt period. In summary, the proposed generic automatic forecast model development tool provides robust predictions for seasonal water availability in Central Asia, which will be tested against the official forecasts in the upcoming years, with the vision of operational implementation.

Exploring the Relation Between Memory, Gestural Communication, and the Emergence of Language in Infancy: A Longitudinal Study

PubMed Central

Heimann, Mikael; Strid, Karin; Smith, Lars; Tjus, Tomas; Ulvund, Stein Erik; Meltzoff, Andrew N.

2006-01-01

The relationship between recall memory, visual recognition memory, social communication, and the emergence of language skills was measured in a longitudinal study. Thirty typically developing Swedish children were tested at 6, 9 and 14 months. The result showed that, in combination, visual recognition memory at 6 months, deferred imitation at 9 months and turn-taking skills at 14 months could explain 41% of the variance in the infants’ production of communicative gestures as measured by a Swedish variant of the MacArthur Communicative Development Inventories (CDI). In this statistical model, deferred imitation stood out as the strongest predictor. PMID:16886041

Maternal mental health and childrearing context in the development of children at 6, 18 and 36 months: a Taiwan birth cohort pilot study.

PubMed

Lung, F-W; Shu, B-C; Chiang, T-L; Lin, S-J

2011-03-01

This study investigated a possible pathway of the childrearing context and maternal mental health at 6 months, and how these factors influence children's development at 6, 18 and 36 months. Using random sampling, 2048 children and mothers were selected. The mother's health status was evaluated using the Taiwanese version of the 36-Item Short Form Health Survey (SF-36), and infant development was assessed using the high reliable Taiwan birth cohort study instrument. All data were collected using parental self-report, and were analysed using multiple linear regression analysis and further pathway using structural equation modelling. This study showed that 12 factors effected children's development at 6 months, and some dissipated with growth. Of these, maternal education had an enduring effect on different domains of child development, and this effect intensified as the child grew older. Children who grew up in a family with more siblings would show a delay in language development at 6 months; they have a delay in motor and social development at 18 and 36 months. Additionally, maternal mental health effected the children's fine motor development at 6 months. However, this effect disappeared at 18 months, and influenced children's social development at 36 months. This study demonstrated that the development of children at as young as 6 months is affected by various factors. These factors may dissipate, continue to influence child development up to 3 years of age, turn from being disadvantageous to beneficial, or affect different domains of child development. Also, parental self-report instrument might be has its limitation and could be contributed by several confounding factors. Thus, continuous longitudinal follow-up on changes in maternal conditions, family factors, and environmental factors is vital to understand how these early infantile factors affect each other and influence the developmental trajectories of children into early childhood. © 2010 Blackwell Publishing Ltd.

Incorporation of habitat information in the development of indices of larval bluefin tuna (Thunnus thynnus) in the Western Mediterranean Sea (2001-2005 and 2012-2013)

NASA Astrophysics Data System (ADS)

Ingram, G. Walter; Alvarez-Berastegui, Diego; Reglero, Patricia; Balbín, Rosa; García, Alberto; Alemany, Francisco

2017-06-01

Fishery independent indices of bluefin tuna larvae in the Western Mediterranean Sea are presented utilizing ichthyoplankton survey data collected from 2001 through 2005 and 2012 through 2013. Indices were developed using larval catch rates collected using two different types of bongo sampling, by first standardizing catch rates by gear/fishing-style and then employing a delta-lognormal modeling approach. The delta-lognormal models were developed three ways: 1) a basic larval index including the following covariates: time of day, a systematic geographic area variable, month and year; 2) a standard environmental larval index including the following covariates: mean water temperature over the mixed layer depth, mean salinity over the mixed layer depth, geostrophic velocity, time of day, a systematic geographic area variable, month and year; and 3) a habitat-adjusted larval index including the following covariates: a potential habitat variable, time of day, a systematic geographic area variable, month and year. Results indicated that all three model-types had similar precision in index values. However, the habitat-adjusted larval index demonstrated a high correlation with estimates of spawning stock biomass from the previous stock assessment model, and, therefore, is recommended as a tuning index in future stock assessment models.

Effects of an energy and micronutrient supplement on growth and development in undernourished children in Indonesia: methods.

PubMed

Pollitt, E; Durnin, J V; Husaini, M; Jahari, A

2000-05-01

To describe the methodologies of a clinical trial on the effects of an energy and micronutrient supplement on the growth and development of undernourished children. This trial included two cohorts of children classified as nutritionally-at-risk who were randomly assigned to three treatments (condensed milk + micronutrients (E); skimmed milk + micronutrients (M); skimmed milk (S)). Supplements were given for a period up to 12 months. Six tea plantations in Pangalengan, West Java were the site for this study. A 12-month-old (N=53) and an 18-month-old (N=83) cohort were recruited from 24 day-care-centers (DCC). Twenty children that received the S supplement were part of the 12- and 18 month-old cohort. Criteria for case inclusion were absence of chronic disease; length-for-age < or = -1 standard deviation (s.d.) and weight-for-length between -1 and -2 s.d. of the median of the reference of the World Health Organization. Social variables included assessment of health facilities, childcare, housing, income and parental education. Nutrition and growth variables included dietary intake measured over a 24 hr period every 2 months; hemoglobin and three iron indicators measured at baseline, 6 and 12 months; anthropometry measured every 2 months and skeletal maturation measured every 6 months. Cognition and behavior included the assessment of mental and motor development and the behavior of the child under natural conditions. An ANOVA was the statistic most frequently used to test inter-group differences and structural equation modeling was used to test the internal validity of the conceptual model of the study.

Challenges in the development of chronic pulmonary hypertension models in large animals

PubMed Central

Rothman, Abraham; Wiencek, Robert G.; Davidson, Stephanie; Evans, William N.; Restrepo, Humberto; Sarukhanov, Valeri; Mann, David

2017-01-01

Pulmonary hypertension (PH) results in significant morbidity and mortality. Chronic PH animal models may advance the study of PH’s mechanisms, evolution, and therapy. In this report, we describe the challenges and successes in developing three models of chronic PH in large animals: two models (one canine and one swine) utilized repeated infusions of ceramic microspheres into the pulmonary vascular bed, and the third model employed a surgical aorto-pulmonary shunt. In the canine model, seven dogs underwent microsphere infusions that resulted in progressive elevation of pulmonary arterial pressure over a few months. In this model, pulmonary endoarterial tissue was obtained for histology. In the aorto-pulmonary shunt swine model, 17 pigs developed systemic level pulmonary pressures after 2–3 months. In this model, pulmonary endoarterial tissue was sequentially obtained to assess for changes in gene and microRNA expression. In the swine microsphere infusion model, three pigs developed only a modest chronic increase in pulmonary arterial pressure, despite repeated infusions of microspheres (up to 40 in one animal). The main purpose of this model was for vasodilator testing, which was performed successfully immediately after acute microsphere infusions. Chronic PH in large animal models can be successfully created; however, a model’s characteristics need to match the investigational goals. PMID:28680575

Frontolimbic Neural Circuitry at 6 Months Predicts Individual Differences in Joint Attention at 9 Months

ERIC Educational Resources Information Center

Elison, Jed T.; Wolff, Jason J.; Heimer, Debra C.; Paterson, Sarah J.; Gu, Hongbin; Hazlett, Heather C.; Styner, Martin; Gerig, Guido; Piven, Joseph

2013-01-01

Elucidating the neural basis of joint attention in infancy promises to yield important insights into the development of language and social cognition, and directly informs developmental models of autism. We describe a new method for evaluating responding to joint attention performance in infancy that highlights the 9- to 10-month period as a time…

A land-use regression model for estimating microenvironmental diesel exposure given multiple addresses from birth through childhood.

PubMed

Ryan, Patrick H; Lemasters, Grace K; Levin, Linda; Burkle, Jeff; Biswas, Pratim; Hu, Shaohua; Grinshpun, Sergey; Reponen, Tiina

2008-10-01

The Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is a prospective birth cohort whose purpose is to determine if exposure to high levels of diesel exhaust particles (DEP) during early childhood increases the risk for developing allergic diseases. In order to estimate exposure to DEP, a land-use regression (LUR) model was developed using geographic data as independent variables and sampled levels of a marker of DEP as the dependent variable. A continuous wind direction variable was also created. The LUR model predicted 74% of the variability in sampled values with four variables: wind direction, length of bus routes within 300 m of the sample site, a measure of truck intensity within 300 m of the sampling site, and elevation. The LUR model was subsequently applied to all locations where the child had spent more than eight hours per week from through age three. A time-weighted average (TWA) microenvironmental exposure estimate was derived for four time periods: 0-6 months, 7-12 months, 13-24 months, 25-36 months. By age two, one third of the children were spending significant time at locations other than home and by 36 months, 39% of the children had changed their residential addresses. The mean cumulative DEP exposure estimate increased from age 6 to 36 months from 70 to 414 microg/m3-days. Findings indicate that using birth addresses to estimate a child's exposure may result in exposure misclassification for some children who spend a significant amount of time at a location with high exposure to DEP.

Formulation development of retrocyclin 1 analog RC-101 as an anti-HIV vaginal microbicide product.

PubMed

Sassi, A B; Cost, M R; Cole, A L; Cole, A M; Patton, D L; Gupta, P; Rohan, L C

2011-05-01

RC-101 is a synthetic microbicide analog of retrocyclin, which has shown in vitro activity against X4 and R5 HIV-1. In an effort to develop a safe and effective RC-101 vaginal microbicide product, we assessed safety in ex vivo macaque and human models and efficacy using in vitro and ex vivo models. A polyvinyl-alcohol vaginal film containing RC-101 (100 μg/film) was developed. Formulation assessment was conducted by evaluating disintegration, drug content, mechanical properties, and stability. Efficacy was evaluated by in vitro peripheral blood mononuclear cells (PBMC) assay and ex vivo human ectocervical tissue explant model. Ex vivo safety studies were conducted by exposing RC-101 to an excised monkey reproductive tract and excised human ectocervical tissue. RC-101 100 μg films were shown to be safe to human and monkey tissue and effective against HIV-1 in vitro and ex vivo in human ectocervical tissue. The 90% inhibitory concentration (IC90) for RC-101 films at 2,000 μg (IC90=57.5 μM) using an ex vivo model was 10-fold higher than the IC90 observed using an in vitro model (IC90=5.0 μM). RC-101 films were stable for 1 month at 25°C, with in vitro bioactivity maintained for up to 6 months. RC-101 was developed in a quick-dissolve film formulation that was shown to be safe in an ex vivo model and effective in in vitro and ex vivo models. RC-101 film formulations were shown to maintain bioactivity for a period of 6 months. Findings from the present study contribute to the development of a safe and effective topical microbicide product.

Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012).

PubMed

Yan, Long; Wang, Hong; Zhang, Xuan; Li, Ming-Yue; He, Juan

2017-01-01

Influence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model. A time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970-2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE). Firstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004-0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009-0.037) displayed the highest prediction accuracy. The ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity.

Modeling monthly meteorological and agronomic frost days, based on minimum air temperature, in Center-Southern Brazil

NASA Astrophysics Data System (ADS)

Alvares, Clayton Alcarde; Sentelhas, Paulo César; Stape, José Luiz

2017-09-01

Although Brazil is predominantly a tropical country, frosts are observed with relative high frequency in the Center-Southern states of the country, affecting mainly agriculture, forestry, and human activities. Therefore, information about the frost climatology is of high importance for planning of these activities. Based on that, the aims of the present study were to develop monthly meteorological (F MET) and agronomic (F AGR) frost day models, based on minimum shelter air temperature (T MN), in order to characterize the temporal and spatial frost days variability in Center-Southern Brazil. Daily minimum air temperature data from 244 weather stations distributed across the study area were used, being 195 for developing the models and 49 for validating them. Multivariate regression models were obtained to estimate the monthly T MN, once the frost day models were based on this variable. All T MN regression models were statistically significant (p < 0.001), presenting adjusted R 2 between 0.69 and 0.90. Center-Southern Brazil is mainly hit by frosts from mid-fall (April) to mid-spring (October). The period from November to March is considered as frost-free, being very rare a frost day within that period. Monthly F MET and F AGR presented significant sigmoidal relationships with T MN (p < 0.0001), with adjusted R 2 above of 0.82. The residuals of the frost day models were random, which means that the sigmoidal models performed quite well for interpreting the frost day variability throughout the study area. The highlands of Santa Catarina, Rio Grande do Sul, São Paulo, and Minas Gerais had in average more than 25 and 13 frosts per year, respectively, for F MET and F AGR. The F MET and F AGR maps developed in this study for Center-Southern Brazil is a useful tool for farmers, foresters, and researchers, since they contribute to reduce frost spatial and temporal uncertainty, helping in planning project for strategic purposes. Furthermore, the monthly F MET and F AGR maps for this Brazilian region are the first zoning of these variables for the country.

Epicatechin as a Therapeutic Strategy to Mitigate the Development of Cardiac Remodeling and Fibrosis

DTIC Science & Technology

2017-09-01

Currently, no drugs target HFpEF and the development of animal models can assist in therapy evaluation. We developed a female rat model of aging...allocated into an aging group, aging + ovariectomy and aging + ovariectomy + 10% fructose in drinking water. At 22 months of age, animals were...epicatechin (Epi) will ameliorate adverse tissue remodeling and cardiac fibrosis in female animal models developing diastolic dysfunction as seen in women

Regression models of monthly water-level change in and near the Closed Basin Division of the San Luis Valley, south-central Colorado

USGS Publications Warehouse

Watts, Kenneth R.

1995-01-01

The Bureau of Reclamation is developing a water-resource project, the Closed Basin Division, in the San Luis Valley of south-central Colorado that is designed to salvage unconfined ground water that currently is discharged as evapotranspiration. The water table in and near the 130,000-acre Closed Basin Division area will be lowered by an annual withdrawal of as much as 100,000 acre-feet of ground water from the unconfined aquifer. The legislation authorizing the project limits resulting drawdown of the water table in preexisting irrigation and domestic wells outside the Closed Basin Division to a maximum of 2 feet. Water levels in the closed basin in the northern part of the San Luis Valley historically have fluctuated more than 2 feet in response to water-use practices and variation of climatically controlled recharge and discharge. Declines of water levels in nearby wells that are caused by withdrawals in the Closed Basin Division can be quantified if water-level fluctuations that result from other water-use practices and climatic variations can be estimated. This study was done to evaluate water-level change at selected observation wells in and near the Closed Basin Division. Regression models of monthly water-level change were developed to predict monthly water-level change in 46 selected observation wells. Predictions of monthly water-level change are based on one or more of the following: elapsed time, cosine and sine functions with an annual period, streamflow depletion of the Rio Grande, electrical use for agricultural purposes, runoff into the closed basin, precipitation, and mean air temperature. Regression models for five of the wells include only an intercept term and either an elapsed-time term or terms determined by the cosine and sine functions. Regression models for the other 41 wells include 1 to 4 of the 5 other variables, which can vary from month to month and from year to year. Serial correlation of the residuals was detected in 24 of the regression models. These models also include an autoregressive term to account for serial correlation in the residuals. The adjusted coefficient of determination (Ra2) for the 46 regression models range from 0.08 to 0.89, and the standard errors of estimate range from 0.034 to 2.483 feet. The regression models of monthly water- level change can be used to evaluate whether post-1985 monthly water-level change values at the selected observation wells are within the 95-percent confidence limits of predicted monthly water-level change.

A modified acceleration-based monthly gravity field solution from GRACE data

NASA Astrophysics Data System (ADS)

Chen, Qiujie; Shen, Yunzhong; Chen, Wu; Zhang, Xingfu; Hsu, Houze; Ju, Xiaolei

2015-08-01

This paper describes an alternative acceleration approach for determining GRACE monthly gravity field models. The main differences compared to the traditional acceleration approach can be summarized as: (1) The position errors of GRACE orbits in the functional model are taken into account; (2) The range ambiguity is eliminated via the difference of the range measurements and (3) The mean acceleration equation is formed based on Cowell integration. Using this developed approach, a new time-series of GRACE monthly solution spanning the period January 2003 to December 2010, called Tongji_Acc RL01, has been derived. The annual signals from the Tongji_Acc RL01 time-series agree well with those from the GLDAS model. The performance of Tongji_Acc RL01 shows that this new model is comparable with the RL05 models released by CSR and JPL as well as with the RL05a model released by GFZ.

Maternal communicative behaviours and interaction quality as predictors of language development: findings from a community-based study of slow-to-talk toddlers.

PubMed

Conway, Laura J; Levickis, Penny A; Smith, Jodie; Mensah, Fiona; Wake, Melissa; Reilly, Sheena

2018-03-01

Identifying risk and protective factors for language development informs interventions for children with developmental language disorder (DLD). Maternal responsive and intrusive communicative behaviours are associated with language development. Mother-child interaction quality may influence how children use these behaviours in language learning. To identify (1) communicative behaviours and interaction quality associated with language outcomes; (2) whether the association between a maternal intrusive behaviour (directive) and child language scores changed alongside a maternal responsive behaviour (expansion); and (3) whether interaction quality modified these associations. Language skills were assessed at 24, 36 and 48 months in 197 community-recruited children who were slow to talk at 18 months. Mothers and 24-month-olds were video-recorded playing at home. Maternal praise, missed opportunities, and successful and unsuccessful directives (i.e., whether followed by the child) were coded during a 10-min segment. Interaction quality was rated using a seven-point fluency and connectedness (FC) scale, during a 5-min segment. Linear regressions examined associations between these behaviours/rating and language scores. Interaction analysis and simple slopes explored effect modification by FC. There was no evidence that missed opportunities or praise were associated with language scores. Higher rates of successful directives in the unadjusted model and unsuccessful directives in the adjusted model were associated with lower 24-month-old receptive language scores (e.g., unsuccessful directives effect size (ES) = -0.41). The association between unsuccessful directives and receptive language was weaker when adjusting for co-occurring expansions (ES = -0.34). Both types of directives were associated with poorer receptive and expressive language scores in adjusted models at 36 and 48 months (e.g., unsuccessful directive and 48-month receptive language, ES = -0.66). FC was positively associated with 24-, 36- and 48-month language scores in adjusted models (e.g., receptive language at 24 months, ES = 0.21, at 48 months, ES = 0.18). Interaction analysis showed the negative association between successful directives and 24-month receptive language existed primarily in poorly connected dyads with low FC levels. These findings illustrate the effects of the combined interaction between different maternal communicative behaviours and features of the interaction itself on child language development, and the need to consider both in research and practice. Whilst more intrusive directives were associated with poorer language scores, this association attenuated when adjusting for co-occurring responsive expansions, and the association was strongest for children in lower quality interactions. This work may inform clinical practice by helping clinicians target the most appropriate communicative behaviours for specific mother-child dyads. © 2017 Royal College of Speech and Language Therapists.

Promoting Sustained Breastfeeding of Infants at Risk for Asthma: Explaining the “Active Ingredients” of an Effective Program Using Intervention Mapping

PubMed Central

Mesters, Ilse; Gijsbers, Barbara; Bartholomew, L. Kay

2018-01-01

Infants whose parents and/or siblings have a history of asthma or allergy may profit from receiving exclusive breastfeeding during the first 6 months of life. This is expected to diminish the chance of developing childhood asthma and/or atopic disease. Ongoing breastfeeding for 6 months seems challenging for many women. An educational program was developed using Intervention Mapping as a logic model to guide development and was found successful in improving breastfeeding rates at 6 months postpartum, improving knowledge and beliefs about breastfeeding for 6 months, after exposure to the program compared to controls. Intervention elements included an evidence- and theory-based booklet addressed during pre- and postnatal home visits by trained assistants. This paper elucidates the inner workings of the program by systematically describing and illustrating the steps for intervention development. PMID:29616209

Promoting Sustained Breastfeeding of Infants at Risk for Asthma: Explaining the "Active Ingredients" of an Effective Program Using Intervention Mapping.

PubMed

Mesters, Ilse; Gijsbers, Barbara; Bartholomew, L Kay

2018-01-01

Infants whose parents and/or siblings have a history of asthma or allergy may profit from receiving exclusive breastfeeding during the first 6 months of life. This is expected to diminish the chance of developing childhood asthma and/or atopic disease. Ongoing breastfeeding for 6 months seems challenging for many women. An educational program was developed using Intervention Mapping as a logic model to guide development and was found successful in improving breastfeeding rates at 6 months postpartum, improving knowledge and beliefs about breastfeeding for 6 months, after exposure to the program compared to controls. Intervention elements included an evidence- and theory-based booklet addressed during pre- and postnatal home visits by trained assistants. This paper elucidates the inner workings of the program by systematically describing and illustrating the steps for intervention development.

Development of survival skills in captive-raised Siberian polecats (Mustela eversmanni) II: predator avoidance

USGS Publications Warehouse

Miller, Brian; Biggins, Dean; Wemmer, Chris; Powell, Roger; Calvo, Lorena; Hanebury, Lou; Wharton, Tracy

1990-01-01

We exposed naive Siberain polecats (Mustela eversmanni) (aged 2, 3, and 4 months) to a swooping stuffed great horned owl (Buho virginianus) and a stuffed badger (Taxidae taxus) mounted on a remote control toy automobile frame. The first introduction to each was harmless, the second was accompanied by a mild aversive stimulus, the third (1 day after attack) was harmless, and the fourth (30 days after attack) was harmless. Alert behavior increased after a single attack by either predator model. Escape responses of naive polecats did not differ between ages when exposed to the badger, but 4 month old polecats reduced their escape times after a single badger attack. When exposed to the swooping owl, naive 4 month old polecats redponded more quickly than the other two age groups, and 3 and 4 month old polecats reduced escape times after a single owl attack. This indicates an innate escape response to the owl model at 4 months of age, and a short-tert ability to remember a single mild aversive encounter with the badger and owl models at 3 or 4 months of age.

Perfluoroalkyl substances measured in breast milk and child neuropsychological development in a Norwegian birth cohort study.

PubMed

Forns, J; Iszatt, N; White, R A; Mandal, S; Sabaredzovic, A; Lamoree, M; Thomsen, C; Haug, L S; Stigum, H; Eggesbø, M

2015-10-01

Perfluoroalkyl substances (PFASs) are chemicals with potential neurotoxic effects although the current evidence is still limited. This study investigated the association between perinatal exposure to perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) and neuropsychological development assessed at 6, 12 and 24 months. We measured PFOS and PFOA in breast milk samples collected one month after delivery by mothers of children participating in the HUMIS study (Norway). Cognitive and psychomotor development was measured at 6 and at 24 months using the Ages and Stages Questionnaire (ASQ-II). Behavioral development was assessed using the infant-toddler symptom checklist (ITSC) at 12 and at 24 months. Weighted logistic regression and weighted negative binomial regression models were applied to analyze the associations between PFASs and ASQ-II and ITSC, respectively. The median concentration of PFOS was 110 ng/L, while the median for PFOA was 40 ng/L. We did not detect an increased risk of having an abnormal score in ASQ-II at 6 months or 24 months. Moreover, no consistent increase in behavioral problems assessed at 12 and 24 months by ITSC questionnaire was detected. We observed no association between perinatal PFOS and PFOA exposure and early neuropsychological development. Further longitudinal studies are needed to confirm the effects of these compounds on neuropsychological development in older children. Copyright © 2015. Published by Elsevier Ltd.

Estrogen contributes to the onset, persistence, and malignant progression of cervical cancer in a human papillomavirus-transgenic mouse model

PubMed Central

Brake, Tiffany; Lambert, Paul F.

2005-01-01

Cervical cancer is a leading cause of death by cancer among women worldwide. High-risk human papillomaviruses (HPVs) are the major etiological agents for cervical cancer, but other factors likely contribute to cervical cancer, because these cancers commonly arise decades after initial exposure to HPV. Estrogen is thought to be one such cofactor; however, its temporal requirements in human cervical cancer are not known. Here we evaluate the temporal requirements of estrogen in cervical carcinogenesis in a mouse model for HPV-associated cervical cancer. Tumors arising in HPV16 transgenic mice treated with estrogen for 9 months were greatly increased in their size compared with tumors developing after 6 months of estrogen treatment. HPV16 transgenic mice treated 6 months with estrogen followed by 3 months without exogenous estrogen had significantly fewer tumors and the tumors were smaller and less aggressive than those arising in mice treated the full 9 months. Importantly, cervical cancers that arose in the mice treated the first 6 of 9 months with estrogen must have regressed, based upon the reduced incidence of cancers in these mice compared with those treated for 6 months with estrogen, then immediately analyzed. We conclude that estrogen plays a critical role not only in the genesis of cervical cancer but also in its persistence and continued development in this mouse model. These findings raise the clinically relevant possibility that, if human cervical cancer has a similar dependence on estrogen for continued tumor growth, then antiestrogen therapy may be effective in the treatment of cervical cancer. PMID:15699322

Agrometeorological models for forecasting the qualitative attributes of "Valência" oranges

NASA Astrophysics Data System (ADS)

Moreto, Victor Brunini; Rolim, Glauco de Souza; Zacarin, Bruno Gustavo; Vanin, Ana Paula; de Souza, Leone Maia; Latado, Rodrigo Rocha

2017-11-01

Forecasting is the act of predicting unknown future events using available data. Estimating, in contrast, uses data to simulate an actual condition. Brazil is the world's largest producer of oranges, and the state of São Paulo is the largest producer in Brazil. The "Valência" orange is among the most common cultivars in the state. We analyzed the influence of monthly meteorological variables during the growth cycle of Valência oranges grafted onto "Rangpur" lime rootstocks (VACR) for São Paulo, and developed monthly agrometeorological models for forecasting the qualitative attributes of VACR in mature orchard. For fruits per box for all months, the best accuracy was of 0.84 % and the minimum forecast range of 4 months. For the relation between °brix and juice acidity (RATIO) the best accuracy was of 0.69 % and the minimum forecast range of 5 months. Minimum, mean and maximum air temperatures, and relative evapotranspiration were the most important variables in the models.

Developing a hydrological model in the absence of field data

NASA Astrophysics Data System (ADS)

Sproles, E. A.; Orrego Nelson, C.; Kerr, T.; Lopez Aspe, D.

2014-12-01

We present two runoff models that use remotely-sensed snow cover products from the Moderate Resolution Imaging Spectrometer (MODIS) as the first order hydrologic input. These simplistic models are the first step in developing an operational model for the Elqui River watershed located in northern Central Chile (30°S). In this semi-arid region, snow and glacier melt are the dominant hydrologic inputs where annual precipitation is limited to three or four winter events. Unfortunately winter access to the Andean Cordillera where snow accumulates is limited. While a monitoring network to measure snow where it accumulates in the upper elevations is under development, management decisions regarding water resources cannot wait. The two models we present differ in structure. The first applies a Monte Carlo approach to determine relationships between lagged changes in monthly snow cover frequency and monthly discharge. The second is a modified degree-day melt model, utilizing the MODIS snow cover product to determine where and when snow melt occurs. These models are not watershed specific and are applicable in other regions where snow dominates hydrologic inputs, but measurements are minimal.

Turbulence and transition modeling for high-speed flows

NASA Technical Reports Server (NTRS)

Wilcox, David C.

1993-01-01

Research conducted during the past three and a half years aimed at developing and testing a turbulence/transition model applicable to high-speed turbulent flows is summarized. The first two years of the project focused on fully turbulent flows, while emphasis shifted to boundary-layer development in the transition region during the final year and a half. A brief summary of research accomplished during the first three years is included and publications that describe research results in greater detail are cited. Research conducted during the final six months of the period of performance is summarized. The primary results of the last six months of the project are elimination of the k-omega model's sensitivity to the freestream value of omega and development of a method for triggering transition at a specified location, independent of the freestream turbulence level.

Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper.

PubMed

Kim, Ji-Hoon; Kang, Wee-Soo; Yun, Sung-Chul

2014-06-01

A population model of bacterial spot caused by Xanthomonas campestris pv. vesicatoria on hot pepper was developed to predict the primary disease infection date. The model estimated the pathogen population on the surface and within the leaf of the host based on the wetness period and temperature. For successful infection, at least 5,000 cells/ml of the bacterial population were required. Also, wind and rain were necessary according to regression analyses of the monitored data. Bacterial spot on the model is initiated when the pathogen population exceeds 10(15) cells/g within the leaf. The developed model was validated using 94 assessed samples from 2000 to 2007 obtained from monitored fields. Based on the validation study, the predicted initial infection dates varied based on the year rather than the location. Differences in initial infection dates between the model predictions and the monitored data in the field were minimal. For example, predicted infection dates for 7 locations were within the same month as the actual infection dates, 11 locations were within 1 month of the actual infection, and only 3 locations were more than 2 months apart from the actual infection. The predicted infection dates were mapped from 2009 to 2012; 2011 was the most severe year. Although the model was not sensitive enough to predict disease severity of less than 0.1% in the field, our model predicted bacterial spot severity of 1% or more. Therefore, this model can be applied in the field to determine when bacterial spot control is required.

Development of a Model to Predict the Primary Infection Date of Bacterial Spot (Xanthomonas campestris pv. vesicatoria) on Hot Pepper

PubMed Central

Kim, Ji-Hoon; Kang, Wee-Soo; Yun, Sung-Chul

2014-01-01

A population model of bacterial spot caused by Xanthomonas campestris pv. vesicatoria on hot pepper was developed to predict the primary disease infection date. The model estimated the pathogen population on the surface and within the leaf of the host based on the wetness period and temperature. For successful infection, at least 5,000 cells/ml of the bacterial population were required. Also, wind and rain were necessary according to regression analyses of the monitored data. Bacterial spot on the model is initiated when the pathogen population exceeds 1015 cells/g within the leaf. The developed model was validated using 94 assessed samples from 2000 to 2007 obtained from monitored fields. Based on the validation study, the predicted initial infection dates varied based on the year rather than the location. Differences in initial infection dates between the model predictions and the monitored data in the field were minimal. For example, predicted infection dates for 7 locations were within the same month as the actual infection dates, 11 locations were within 1 month of the actual infection, and only 3 locations were more than 2 months apart from the actual infection. The predicted infection dates were mapped from 2009 to 2012; 2011 was the most severe year. Although the model was not sensitive enough to predict disease severity of less than 0.1% in the field, our model predicted bacterial spot severity of 1% or more. Therefore, this model can be applied in the field to determine when bacterial spot control is required. PMID:25288995

Regionalized rainfall-runoff model to estimate low flow indices

NASA Astrophysics Data System (ADS)

Garcia, Florine; Folton, Nathalie; Oudin, Ludovic

2016-04-01

Estimating low flow indices is of paramount importance to manage water resources and risk assessments. These indices are derived from river discharges which are measured at gauged stations. However, the lack of observations at ungauged sites bring the necessity of developing methods to estimate these low flow indices from observed discharges in neighboring catchments and from catchment characteristics. Different estimation methods exist. Regression or geostatistical methods performed on the low flow indices are the most common types of methods. Another less common method consists in regionalizing rainfall-runoff model parameters, from catchment characteristics or by spatial proximity, to estimate low flow indices from simulated hydrographs. Irstea developed GR2M-LoiEau, a conceptual monthly rainfall-runoff model, combined with a regionalized model of snow storage and melt. GR2M-LoiEau relies on only two parameters, which are regionalized and mapped throughout France. This model allows to cartography monthly reference low flow indices. The inputs data come from SAFRAN, the distributed mesoscale atmospheric analysis system, which provides daily solid and liquid precipitation and temperature data from everywhere in the French territory. To exploit fully these data and to estimate daily low flow indices, a new version of GR-LoiEau has been developed at a daily time step. The aim of this work is to develop and regionalize a GR-LoiEau model that can provide any daily, monthly or annual estimations of low flow indices, yet keeping only a few parameters, which is a major advantage to regionalize them. This work includes two parts. On the one hand, a daily conceptual rainfall-runoff model is developed with only three parameters in order to simulate daily and monthly low flow indices, mean annual runoff and seasonality. On the other hand, different regionalization methods, based on spatial proximity and similarity, are tested to estimate the model parameters and to simulate low flow indices in ungauged sites. The analysis is carried out on 691 French catchments that are representative of various hydro-meteorological behaviors. The results are validated with a cross-validation procedure and are compared with the ones obtained with GR4J, a conceptual rainfall-runoff model, which already provides daily estimations, but involves four parameters that cannot easily be regionalized.

Predicting hospital stay, mortality and readmission in people admitted for hypoglycaemia: prognostic models derivation and validation.

PubMed

Zaccardi, Francesco; Webb, David R; Davies, Melanie J; Dhalwani, Nafeesa N; Gray, Laura J; Chatterjee, Sudesna; Housley, Gemma; Shaw, Dominick; Hatton, James W; Khunti, Kamlesh

2017-06-01

Hospital admissions for hypoglycaemia represent a significant burden on individuals with diabetes and have a substantial economic impact on healthcare systems. To date, no prognostic models have been developed to predict outcomes following admission for hypoglycaemia. We aimed to develop and validate prediction models to estimate risk of inpatient death, 24 h discharge and one month readmission in people admitted to hospital for hypoglycaemia. We used the Hospital Episode Statistics database, which includes data on all hospital admission to National Health Service hospital trusts in England, to extract admissions for hypoglycaemia between 2010 and 2014. We developed, internally and temporally validated, and compared two prognostic risk models for each outcome. The first model included age, sex, ethnicity, region, social deprivation and Charlson score ('base' model). In the second model, we added to the 'base' model the 20 most common medical conditions and applied a stepwise backward selection of variables ('disease' model). We used C-index and calibration plots to assess model performance and developed a calculator to estimate probabilities of outcomes according to individual characteristics. In derivation samples, 296 out of 11,136 admissions resulted in inpatient death, 1789/33,825 in one month readmission and 8396/33,803 in 24 h discharge. Corresponding values for validation samples were: 296/10,976, 1207/22,112 and 5363/22,107. The two models had similar discrimination. In derivation samples, C-indices for the base and disease models, respectively, were: 0.77 (95% CI 0.75, 0.80) and 0.78 (0.75, 0.80) for death, 0.57 (0.56, 0.59) and 0.57 (0.56, 0.58) for one month readmission, and 0.68 (0.67, 0.69) and 0.69 (0.68, 0.69) for 24 h discharge. Corresponding values in validation samples were: 0.74 (0.71, 0.76) and 0.74 (0.72, 0.77), 0.55 (0.54, 0.57) and 0.55 (0.53, 0.56), and 0.66 (0.65, 0.67) and 0.67 (0.66, 0.68). In both derivation and validation samples, calibration plots showed good agreement for the three outcomes. We developed a calculator of probabilities for inpatient death and 24 h discharge given the low performance of one month readmission models. This simple and pragmatic tool to predict in-hospital death and 24 h discharge has the potential to reduce mortality and improve discharge in people admitted for hypoglycaemia.

Statistical prediction of seasonal discharge in Central Asia for water resources management: development of a generic (pre-)operational modeling tool

NASA Astrophysics Data System (ADS)

Apel, Heiko; Baimaganbetov, Azamat; Kalashnikova, Olga; Gavrilenko, Nadejda; Abdykerimova, Zharkinay; Agalhanova, Marina; Gerlitz, Lars; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Gafurov, Abror

2017-04-01

The semi-arid regions of Central Asia crucially depend on the water resources supplied by the mountainous areas of the Tien-Shan and Pamirs. During the summer months the snow and glacier melt dominated river discharge originating in the mountains provides the main water resource available for agricultural production, but also for storage in reservoirs for energy generation during the winter months. Thus a reliable seasonal forecast of the water resources is crucial for a sustainable management and planning of water resources. In fact, seasonal forecasts are mandatory tasks of all national hydro-meteorological services in the region. In order to support the operational seasonal forecast procedures of hydromet services, this study aims at the development of a generic tool for deriving statistical forecast models of seasonal river discharge. The generic model is kept as simple as possible in order to be driven by available hydrological and meteorological data, and be applicable for all catchments with their often limited data availability in the region. As snowmelt dominates summer runoff, the main meteorological predictors for the forecast models are monthly values of winter precipitation and temperature as recorded by climatological stations in the catchments. These data sets are accompanied by snow cover predictors derived from the operational ModSnow tool, which provides cloud free snow cover data for the selected catchments based on MODIS satellite images. In addition to the meteorological data antecedent streamflow is used as a predictor variable. This basic predictor set was further extended by multi-monthly means of the individual predictors, as well as composites of the predictors. Forecast models are derived based on these predictors as linear combinations of up to 3 or 4 predictors. A user selectable number of best models according to pre-defined performance criteria is extracted automatically by the developed model fitting algorithm, which includes a test for robustness by a leave-one-out cross validation. Based on the cross validation the predictive uncertainty was quantified for every prediction model. According to the official procedures of the hydromet services forecasts of the mean seasonal discharge of the period April to September are derived every month starting from January until June. The application of the model for several catchments in Central Asia - ranging from small to the largest rivers - for the period 2000-2015 provided skillful forecasts for most catchments already in January. The skill of the prediction increased every month, with R2 values often in the range 0.8 - 0.9 in April just before the prediction period. The forecasts further improve in the following months, most likely due to the integration of spring precipitation, which is not included in the predictors before May, or spring discharge, which contains indicative information for the overall seasonal discharge. In summary, the proposed generic automatic forecast model development tool provides robust predictions for seasonal water availability in Central Asia, which will be tested against the official forecasts in the upcoming years, with the vision of eventual operational implementation.

Short Term Single Station GNSS TEC Prediction Using Radial Basis Function Neural Network

NASA Astrophysics Data System (ADS)

Muslim, Buldan; Husin, Asnawi; Efendy, Joni

2018-04-01

TEC prediction models for 24 hours ahead have been developed from JOG2 GPS TEC data during 2016. Eleven month of TEC data were used as a training model of the radial basis function neural network (RBFNN) and 1 month of last data (December 2016) is used for the RBFNN model testing. The RBFNN inputs are the previous 24 hour TEC data and the minimum of Dst index during the previous 24 hours. Outputs of the model are 24 ahead TEC prediction. Comparison of model prediction show that the RBFNN model is able to predict the next 24 hours TEC is more accurate than the TEC GIM model.

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.

Methods for estimating monthly mean concentrations of selected water-quality constituents for stream sites in the Red River of the North basin, North Dakota and Minnesota

USGS Publications Warehouse

Guenthner, R.S.

1991-01-01

Future development of the Garrison Diversion Unit may divert water from the Missouri River into the Sheyenne River and the Red River of the North for municipal and industrial use. The U.S. Bureau of Reclamation's Canals, Rivers, and Reservoirs Salinity Accounting Procedures model can be used to predict the effect various operating plans could have on water quality in the Sheyenne River and the Red River of the North. The model uses, as Input, monthly means of streamflow and selected water-quality constituents for a 54-year period at 28 nodes on the Sheyenne River and the Red River of the North. This report provides methods for estimating monthly mean concentrations of selected water-quality constituents that can be used for input to and calibration of the salinity model.Mater-quality data for 32 gaging stations can be used to define selected water-quality characteristics at the 28 model nodes. Materquality data were retrieved from the U.S. Geological Survey's National Mater Data Storage and Retrieval System data base and statistical summaries were prepared. The frequency of water-quality data collection at the gaging stations is inadequate to define monthly mean concentrations of the individual water-quality constituents for all months for the 54-year period; therefore, methods for estimating monthly mean concentrations were developed. Relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and streamflow were developed as the primary method to estimate monthly mean concentrations. Relations between specific conductance and streamflow and relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and specific conductance were developed so that a cascaded-regression relation could be developed as a second method of estimating monthly mean concentrations and, thus, utilize a large specific-conductance data base. Information about the quantity and the quality of ground water discharging to the Sheyenne River is needed for model input for reaches of the river where ground water accounts for a substantial part of streamflow during periods of low flow. Ground-water discharge was identified for two reaches of the Sheyenne River. Ground-water discharge to the Sheyenne River in the vicinity of Warwick, N.Dak., was about 14.8 cubic feet per second and the estimated dissolved-solids concentration was about 441 milligrams per liter during October 15 and 16, 1986. Ground-water discharge to the Sheyenne River in a reach between Lisbon and Kindred, N.Dak., ranged from an average of 25.3 cubic feet per second during September 13 to November 19, 1963, to about 45.0 cubic feet per second during October 21 and 22, 1986. Dissolved-solids concentration was estimated at about 442 milligrams per liter during October 21 and 22, 1986.

Modelling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, M.; Rey, A.; Freibauer, A.; Tenhunen, J.; Valentini, R.; Soil Respiration Synthesis Team

2003-04-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, inter-annual and spatial variability of soil respiration as affected by water availability, temperature and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g. leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical non-linear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and inter-site variability of soil respiration with a mean absolute error of 0.82 µmol m-2 s-1. The parameterised model exhibits the following principal properties: 1) At a relative amount of upper-layer soil water of 16% of field capacity half-maximal soil respiration rates are reached. 2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. 3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly time-scale we employed the approach by Raich et al. (2002, Global Change Biol. 8, 800-812) that used monthly precipitation and air temperature to globally predict soil respiration (T&P-model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the inter-site variability, regardless whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly time scale we developed a simple T&P&LAI-model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time-step model and explained 50 % of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index.

Determinants of early child development in rural Tanzania.

PubMed

Ribe, Ingeborg G; Svensen, Erling; Lyngmo, Britt A; Mduma, Estomih; Hinderaker, Sven G

2018-01-01

It has been estimated that more than 200 million children under the age of five do not reach their full potential in cognitive development. Much of what we know about brain development is based on research from high-income countries. There is limited evidence on the determinants of early child development in low-income countries, especially rural sub-Saharan Africa. The present study aimed to identify the determinants of cognitive development in children living in villages surrounding Haydom, a rural area in north-central Tanzania. This cohort study is part of the MAL-ED (The Interactions of Malnutrition & Enteric Infections: Consequences for Child Health and Development) multi-country consortium studying risk factors for ill health and poor development in children. Descriptive analysis and linear regression analyses were performed. Associations between nutritional status, socio-economic status, and home environment at 6 months of age and cognitive outcomes at 15 months of age were studied. The third edition of the Bayley Scales for Infant and Toddler Development was used to assess cognitive, language and motor development. There were 262 children enrolled into the study, and this present analysis included the 137 children with data for 15-month Bayley scores. Univariate regression analysis, weight-for-age and weight-for-length z-scores at 6 months were significantly associated with 15-month Bayley gross motor score, but not with other 15-month Bayley scores. Length-for-age z-scores at 6 months were not significantly associated with 15-month Bayley scores. The socio-economic status, measured by a set of assets and monthly income was significantly associated with 15-month Bayley cognitive score, but not with language, motor, nor total 15-month Bayley scores. Other socio-economic variables were not significantly associated with 15-month Bayley scores. No significant associations were found between the home environment and 15-month Bayley scores. In multivariate regression analyses we found higher Bayley scores for girls and higher Bayley scores in families with more assets. Adjusted R-squared of this model was 8%. We conclude that poverty is associated with a slower cognitive development in children and malnutrition is associated with slower gross motor development. This information should encourage authorities and other stakeholders to invest in improved welfare and nutrition programmes for children from early infancy.

Drought Prediction Site Specific and Regional up to Three Years in Advance

NASA Astrophysics Data System (ADS)

Suhler, G.; O'Brien, D. P.

2002-12-01

Dynamic Predictables has developed proprietary software that analyzes and predicts future climatic behavior based on past data. The programs employ both a regional thermodynamic model together with a unique predictive algorithm to achieve a high degree of prediction accuracy up to 36 months. The thermodynamic model was developed initially to explain the results of a study on global circulation models done at SUNY-Stony Brook by S. Hameed, R.G. Currie, and H. LaGrone (Int. Jour. Climatology, 15, pp.852-871, 1995). The authors pointed out that on a time scale of 2-70 months the spectrum of sea level pressure is dominated by the harmonics and subharmonics of the seasonal cycle and their combination tones. These oscillations are fundamental to an understanding of climatic variations on a sub-regional to continental basis. The oscillatory nature of these variations allows them to be used as broad based climate predictors. In addition, they can be subtracted from the data to yield residuals. The residuals are then analyzed to determine components that are predictable. The program then combines both the thermodynamic model results (the primary predictive model) with those from the residual data (the secondary model) to yield an estimate of the future behavior of the climatic variable. Spatial resolution is site specific or aggregated regional based upon appropriate length (45 years or more monthly data) and reasonable quality weather observation records. Most climate analysis has been based on monthly time-step data, but time scales on the order of days can be used. Oregon Climate Division 1 (Coastal) precipitation provides an example relating DynaPred's method to nature's observed elements in the early 2000s. The prediction's leading dynamic factors are the strong seasonal in the primary model combined with high secondary model contributions from planet Earth's Chandler Wobble (near 15 months) and what has been called the Quasi-Triennial Oscillation (QTO, near 36 months) in equatorial regions. Examples of regional aggregate and site-specific predictions previously made blind forward and publicly available (AASC Annual Meetings 1998-2002) will be shown. Certain climate dynamics features relevant to extrema prediction and specifically drought prediction will then be discussed. Time steps presented will be monthly. Climate variables examined are mean temperature and accumulated precipitation. NINO3 SST, interior continental and marine/continental transition area examples will be shown. http://www.dynamicpredictables.com

Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

NASA Astrophysics Data System (ADS)

Yunus, R. M.; Hasan, M. M.; Zubairi, Y. Z.

2017-09-01

In this study, the Tweedie distribution was used to fit the monthly rainfall data from 24 monitoring stations of Peninsula Malaysia for the period from January, 2008 to April, 2015. The aim of the study is to determine whether the distributions within the Tweedie family fit well the monthly Malaysian rainfall data. Within the Tweedie family, the gamma distribution is generally used for fitting the rainfall totals, however the Poisson-gamma distribution is more useful to describe two important features of rainfall pattern, which are the occurrences (dry months) and the amount (wet months). First, the appropriate distribution of the monthly rainfall was identified within the Tweedie family for each station. Then, the Tweedie Generalised Linear Model (GLM) with no explanatory variable was used to model the monthly rainfall data. Graphical representation was used to assess model appropriateness. The QQ plots of quantile residuals show that the Tweedie models fit the monthly rainfall data better for majority of the stations in the west coast and mid land than those in the east coast of Peninsula. This significant finding suggests that the best fitted distribution depends on the geographical location of the monitoring station. In this paper, a simple model is developed for generating synthetic rainfall data for use in various areas, including agriculture and irrigation. We have showed that the data that were simulated using the Tweedie distribution have fairly similar frequency histogram to that of the actual data. Both the mean number of rainfall events and mean amount of rain for a month were estimated simultaneously for the case that the Poisson gamma distribution fits the data reasonably well. Thus, this work complements previous studies that fit the rainfall amount and the occurrence of rainfall events separately, each to a different distribution.

PTSD after childbirth: A predictive ethological model for symptom development.

PubMed

Haagen, Joris F G; Moerbeek, Mirjam; Olde, Eelco; van der Hart, Onno; Kleber, Rolf J

2015-10-01

Childbirth can be a traumatic experience occasionally leading to posttraumatic stress disorder (PTSD). This study aimed to assess childbirth-related PTSD risk-factors using an etiological model inspired by the transactional model of stress and coping. 348 out of 505 (70%) Dutch women completed questionnaires during pregnancy, one week postpartum, and three months postpartum. A further 284 (56%) also completed questionnaires ten months postpartum. The model was tested using path analysis. Antenatal depressive symptoms (β=.15, p<.05), state anxiety (β=.17, p<.01), and perinatal psychoform (β=.17, p<.01) and somatoform (β=.17, p<.01) dissociation were identified as PTSD symptom risk factors three months postpartum. Antenatal depressive symptoms (β=.31, p<.001) and perinatal somatoform dissociation (β=.14, p<.05) predicted symptoms ten months postpartum. Almost a third of our sample was lost at three months postpartum, and 44% at ten months. The sample size was relatively small. The present study did not control for prior PTSD. The PTSD A criterion was not considered an exclusion criteria for model testing, and the fit index of the ten months model was just below suggested cut-off values. Screening for high risk pregnant women should focus on antenatal depression, anxiety and dissociative tendencies. Hospital staff and midwives are advised to be vigilant for perinatal dissociation after intense negative emotions. To help regulate perinatal negative emotional responses, hospital staff and midwifes are recommended to provide information about birth procedures and be attentive to women's birth-related needs. Copyright © 2015 Elsevier B.V. All rights reserved.

Longitudinal analysis of latent classes of psychopathology and patterns of class migration in survivors of severe injury.

PubMed

Forbes, David; Nickerson, Angela; Alkemade, Nathan; Bryant, Richard A; Creamer, Mark; Silove, Derrick; McFarlane, Alexander C; Van Hooff, Miranda; Fletcher, Susan L; O'Donnell, Meaghan

2015-09-01

Little research to date has explored the typologies of psychopathology following trauma, beyond development of particular diagnoses such as posttraumatic stress disorder (PTSD). The objective of this study was to determine the longitudinal patterns of these typologies, especially the movement of persons across clusters of psychopathology. In this 6-year longitudinal study, 1,167 hospitalized severe injury patients who were recruited between April 2004-February 2006 were analyzed, with repeated measures at baseline, 3 months, 12 months, and 72 months after injury. All patients met the DSM-IV criterion A1 for PTSD. Structured clinical interviews were used to assess psychiatric disorders at each follow-up point. Latent class analysis and latent transition analysis were applied to assess clusters of individuals determined by psychopathology. The Mini International Neuropsychiatric Interview (MINI) and Clinician-Administered PTSD Scale (CAPS) were employed to complete diagnoses. Four latent classes were identified at each time point: (1) Alcohol/Depression class (3 months, 2.1%; 12 months, 1.3%; and 72 months, 1.1%), (2) Alcohol class (3 months, 3.3%; 12 months, 3.7%; and 72 months, 5.4%), (3) PTSD/Depression class (3 months, 10.3%; 12 months, 11.5%; and 72 months, 6.4%), and (4) No Disorder class (3 months, 84.2%; 12 months, 83.5%; and 72 months, 87.1%). Latent transition analyses conducted across the 2 transition points (12 months and 72 months) found consistently high levels of stability in the No Disorder class (90.9%, 93.0%, respectively) but lower and reducing levels of consistency in the PTSD/Depression class (81.3%, 46.6%), the Alcohol/Depression class (59.7%, 21.5%), and the Alcohol class (61.0%, 36.5%), demonstrating high levels of between-class migration. Despite the array of psychiatric disorders that may develop following severe injury, a 4-class model best described the data with excellent classification certainty. The high levels of migration across classes indicate a complex pattern of psychopathology expression over time. The findings have considerable implications for tailoring multifocused interventions to class type, as well as flexible stepped care models, and for the potential development and delivery of transdiagnostic interventions targeting underlying mechanisms. © Copyright 2015 Physicians Postgraduate Press, Inc.

Evaluation of wind induced currents modeling along the Southern Caspian Sea

NASA Astrophysics Data System (ADS)

Bohluly, Asghar; Esfahani, Fariba Sadat; Montazeri Namin, Masoud; Chegini, Fatemeh

2018-02-01

To improve our understanding of the Caspian Sea hydrodynamics, its circulation is simulated with special focus on wind-driven currents of its southern basin. The hydrodynamic models are forced with a newly developed fine resolution wind field to increase the accuracy of current modeling. A 2D shallow water equation model and a 3D baroclinic model are applied separately to examine the performance of each model for specific applications in the Caspian Sea. The model results are validated against recent field measurements including AWAC and temperature observations in the southern continental shelf region. Results show that the 2D model is able to well predict the depth-averaged current speed in storm conditions in narrow area of southern coasts. This finding suggests physical oceanographers apply 2D modeling as a more affordable method for extreme current speed analysis at the continental shelf region. On the other hand the 3D model demonstrates a better performance in reproducing monthly mean circulation and hence is preferable for surface circulation of Caspian Sea. Monthly sea surface circulation fields of the southern basin reveal a dipole cyclonic-anticyclonic pattern, a dominant eastward current along the southern coasts which intensifies from May to November and a dominant southward current along the eastern coasts in all months except February when the flow is northward. Monthly mean wind fields exhibit two main patterns including a north-south pattern occurring at warm months and collision of two wind fronts especially in the cold months. This collision occurs on a narrow region at the southern continental shelf regions. Due to wind field complexities, it leads to a major source of uncertainty in predicting the wind-driven currents. However, this source of uncertainty is significantly alleviated by applying a fine resolution wind field.

Estimating direct, diffuse, and global solar radiation for various cities in Iran by two methods and their comparison with the measured data

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

Ashjaee, M.; Roomina, M.R.; Ghafouri-Azar, R.

1993-05-01

Two computational methods for calculating hourly, daily, and monthly average values of direct, diffuse, and global solar radiation on horizontal collectors have been presented in this article for location with different latitude, altitude, and atmospheric conditions in Iran. These methods were developed using two different independent sets of measured data from the Iranian Meteorological Organization (IMO) for two cities in Iran (Tehran and Isfahan) during 14 years of measurement for Tehran and 4 years of measurement for Isfahan. Comparison of calculated monthly average global solar radiation, using the two models for Tehran and Isfahan with measured data from the IMO,more » has indicated a good agreement between them. Then these developed methods were extended to another location (city of Bandar-Abbas), where measured data are not available. But the work of Daneshyar predicts its monthly global radiation. The maximum discrepancy of 7% between the developed models and the work of Daneshyar was observed.« less

The potential of composite cognitive scores for tracking progression in Huntington's disease.

PubMed

Jones, Rebecca; Stout, Julie C; Labuschagne, Izelle; Say, Miranda; Justo, Damian; Coleman, Allison; Dumas, Eve M; Hart, Ellen; Owen, Gail; Durr, Alexandra; Leavitt, Blair R; Roos, Raymund; O'Regan, Alison; Langbehn, Doug; Tabrizi, Sarah J; Frost, Chris

2014-01-01

Composite scores derived from joint statistical modelling of individual risk factors are widely used to identify individuals who are at increased risk of developing disease or of faster disease progression. We investigated the ability of composite measures developed using statistical models to differentiate progressive cognitive deterioration in Huntington's disease (HD) from natural decline in healthy controls. Using longitudinal data from TRACK-HD, the optimal combinations of quantitative cognitive measures to differentiate premanifest and early stage HD individuals respectively from controls was determined using logistic regression. Composite scores were calculated from the parameters of each statistical model. Linear regression models were used to calculate effect sizes (ES) quantifying the difference in longitudinal change over 24 months between premanifest and early stage HD groups respectively and controls. ES for the composites were compared with ES for individual cognitive outcomes and other measures used in HD research. The 0.632 bootstrap was used to eliminate biases which result from developing and testing models in the same sample. In early HD, the composite score from the HD change prediction model produced an ES for difference in rate of 24-month change relative to controls of 1.14 (95% CI: 0.90 to 1.39), larger than the ES for any individual cognitive outcome and UHDRS Total Motor Score and Total Functional Capacity. In addition, this composite gave a statistically significant difference in rate of change in premanifest HD compared to controls over 24-months (ES: 0.24; 95% CI: 0.04 to 0.44), even though none of the individual cognitive outcomes produced statistically significant ES over this period. Composite scores developed using appropriate statistical modelling techniques have the potential to materially reduce required sample sizes for randomised controlled trials.

The U.S. Geological Survey Monthly Water Balance Model Futures Portal

USGS Publications Warehouse

Bock, Andrew R.; Hay, Lauren E.; Markstrom, Steven L.; Emmerich, Christopher; Talbert, Marian

2017-05-03

The U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) is a user-friendly interface that summarizes monthly historical and simulated future conditions for seven hydrologic and meteorological variables (actual evapotranspiration, potential evapotranspiration, precipitation, runoff, snow water equivalent, atmospheric temperature, and streamflow) at locations across the conterminous United States (CONUS).The estimates of these hydrologic and meteorological variables were derived using a Monthly Water Balance Model (MWBM), a modular system that simulates monthly estimates of components of the hydrologic cycle using monthly precipitation and atmospheric temperature inputs. Precipitation and atmospheric temperature from 222 climate datasets spanning historical conditions (1952 through 2005) and simulated future conditions (2020 through 2099) were summarized for hydrographic features and used to drive the MWBM for the CONUS. The MWBM input and output variables were organized into an open-access database. An Open Geospatial Consortium, Inc., Web Feature Service allows the querying and identification of hydrographic features across the CONUS. To connect the Web Feature Service to the open-access database, a user interface—the Monthly Water Balance Model Futures Portal—was developed to allow the dynamic generation of summary files and plots  based on plot type, geographic location, specific climate datasets, period of record, MWBM variable, and other options. Both the plots and the data files are made available to the user for download 

Statistical prediction of September Arctic Sea Ice minimum based on stable teleconnections with global climate and oceanic patterns

NASA Astrophysics Data System (ADS)

Ionita, M.; Grosfeld, K.; Scholz, P.; Lohmann, G.

2016-12-01

Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad information interest exists on sea ice, its coverage, variability and long term change. Knowledge on sea ice requires high quality data on ice extent, thickness and its dynamics. However, its predictability depends on various climate parameters and conditions. In order to provide insights into the potential development of a monthly/seasonal signal, we developed a robust statistical model based on ocean heat content, sea surface temperature and atmospheric variables to calculate an estimate of the September minimum sea ice extent for every year. Although previous statistical attempts at monthly/seasonal forecasts of September sea ice minimum show a relatively reduced skill, here it is shown that more than 97% (r = 0.98) of the September sea ice extent can predicted three months in advance by using previous months conditions via a multiple linear regression model based on global sea surface temperature (SST), mean sea level pressure (SLP), air temperature at 850hPa (TT850), surface winds and sea ice extent persistence. The statistical model is based on the identification of regions with stable teleconnections between the predictors (climatological parameters) and the predictand (here sea ice extent). The results based on our statistical model contribute to the sea ice prediction network for the sea ice outlook report (https://www.arcus.org/sipn) and could provide a tool for identifying relevant regions and climate parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.

September Arctic Sea Ice minimum prediction - a new skillful statistical approach

NASA Astrophysics Data System (ADS)

Ionita-Scholz, Monica; Grosfeld, Klaus; Scholz, Patrick; Treffeisen, Renate; Lohmann, Gerrit

2017-04-01

Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea ice, its coverage, variability and long term change. Knowledge on sea ice requires high quality data on ice extent, thickness and its dynamics. However, its predictability is complex and it depends on various climate and oceanic parameters and conditions. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we developed a robust statistical model based on ocean heat content, sea surface temperature and different atmospheric variables to calculate an estimate of the September Sea ice extent (SSIE) on monthly time scale. Although previous statistical attempts at monthly/seasonal forecasts of SSIE show a relatively reduced skill, we show here that more than 92% (r = 0.96) of the September sea ice extent can be predicted at the end of May by using previous months' climate and oceanic conditions. The skill of the model increases with a decrease in the time lag used for the forecast. At the end of August, our predictions are even able to explain 99% of the SSIE. Our statistical model captures both the general trend as well as the interannual variability of the SSIE. Moreover, it is able to properly forecast the years with extreme high/low SSIE (e.g. 1996/ 2007, 2012, 2013). Besides its forecast skill for SSIE, the model could provide a valuable tool for identifying relevant regions and climate parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.

The effects of a flexible visual acuity-driven ranibizumab treatment regimen in age-related macular degeneration: outcomes of a drug and disease model.

PubMed

Holz, Frank G; Korobelnik, Jean-François; Lanzetta, Paolo; Mitchell, Paul; Schmidt-Erfurth, Ursula; Wolf, Sebastian; Markabi, Sabri; Schmidli, Heinz; Weichselberger, Andreas

2010-01-01

Differences in treatment responses to ranibizumab injections observed within trials involving monthly (MARINA and ANCHOR studies) and quarterly (PIER study) treatment suggest that an individualized treatment regimen may be effective in neovascular age-related macular degeneration. In the present study, a drug and disease model was used to evaluate the impact of an individualized, flexible treatment regimen on disease progression. For visual acuity (VA), a model was developed on the 12-month data from ANCHOR, MARINA, and PIER. Data from untreated patients were used to model patient-specific disease progression in terms of VA loss. Data from treated patients from the period after the three initial injections were used to model the effect of predicted ranibizumab vitreous concentration on VA loss. The model was checked by comparing simulations of VA outcomes after monthly and quarterly injections during this period with trial data. A flexible VA-guided regimen (after the three initial injections) in which treatment is initiated by loss of >5 letters from best previously observed VA scores was simulated. Simulated monthly and quarterly VA-guided regimens showed good agreement with trial data. Simulation of VA-driven individualized treatment suggests that this regimen, on average, sustains the initial gains in VA seen in clinical trials at month 3. The model predicted that, on average, to maintain initial VA gains, an estimated 5.1 ranibizumab injections are needed during the 9 months after the three initial monthly injections, which amounts to a total of 8.1 injections during the first year. A flexible, individualized VA-guided regimen after the three initial injections may sustain vision improvement with ranibizumab and could improve cost-effectiveness and convenience and reduce drug administration-associated risks.

A Standardized Rat Model of Volumetric Muscle Loss Injury for the Development of Tissue Engineering Therapies

PubMed Central

Wu, Xiaowu; Corona, Benjamin T.; Chen, Xiaoyu

2012-01-01

Abstract Soft tissue injuries involving volumetric muscle loss (VML) are defined as the traumatic or surgical loss of skeletal muscle with resultant functional impairment and represent a challenging clinical problem for both military and civilian medicine. In response, a variety of tissue engineering and regenerative medicine treatments are under preclinical development. A wide variety of animal models are being used, all with critical limitations. The objective of this study was to develop a model of VML that was reproducible and technically uncomplicated to provide a standardized platform for the development of tissue engineering and regenerative medicine solutions to VML repair. A rat model of VML involving excision of ∼20% of the muscle's mass from the superficial portion of the middle third of the tibialis anterior (TA) muscle was developed and was functionally characterized. The contralateral TA muscle served as the uninjured control. Additionally, uninjured age-matched control rats were also tested to determine the effect of VML on the contralateral limb. TA muscles were assessed at 2 and 4 months postinjury. VML muscles weighed 22.7% and 19.5% less than contralateral muscles at 2 and 4 months postinjury, respectively. These differences were accompanied by a reduction in peak isometric tetanic force (Po) of 28.4% and 32.5% at 2 and 4 months. Importantly, Po corrected for differences in body weight and muscle wet weights were similar between contralateral and age-matched control muscles, indicating that VML did not have a significant impact on the contralateral limb. Lastly, repair of the injury with a biological scaffold resulted in rapid vascularization and integration with the wound. The technical simplicity, reliability, and clinical relevance of the VML model developed in this study make it ideal as a standard model for the development of tissue engineering solutions for VML. PMID:23515319

Testing efficacy of monthly forecast application in agrometeorology: Winter wheat phenology dynamic

NASA Astrophysics Data System (ADS)

Lalic, B.; Jankovic, D.; Dekic, Lj; Eitzinger, J.; Firanj Sremac, A.

2017-02-01

Use of monthly weather forecast as input meteorological data for agrometeorological forecasting, crop modelling and plant protection can foster promising applications in agricultural production. Operational use of monthly or seasonal weather forecast can help farmers to optimize field operations (fertilizing, irrigation) and protection measures against plant diseases and pests by taking full advantage of monthly forecast information in predicting plant development, pest and disease risks and yield potentials few weeks in advance. It can help producers to obtain stable or higher yield with the same inputs and to minimise losses caused by weather. In Central and South-Eastern Europe ongoing climate change lead to shifts of crops phenology dynamics (i.e. in Serbia 4-8 weeks earlier in 2016 than in previous years) and brings this subject in the front of agronomy science and practice. Objective of this study is to test efficacy of monthly forecast in predicting phenology dynamics of different winter wheat varieties, using phenological model developed by Forecasting and Warning Service of Serbia in plant protection. For that purpose, historical monthly forecast for four months (March 1, 2005 - June 30, 2005) was assimilated from ECMWF MARS archive for 50 ensemble members and control run. Impact of different agroecological conditions is tested by using observed and forecasted data for two locations - Rimski Sancevi (Serbia) and Groß-Enzersdorf (Austria).

T-R Cycle Characterization and Imaging: Advanced Diagnostic Methodology for Petroleum Reservoir and Trap Detection and Delineation

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

Ernest A. Mancini; William C. Parcell; Bruce S. Hart

The principal research effort for Year 2 of the project is on stratigraphic model assessment and development. The research focus for the first six (6) months of Year 2 is on T-R cycle model development. The emphasis for the remainder of the year is on assessing the depositional model and developing and testing a sequence stratigraphy model. The development and testing of the sequence stratigraphy model has been accomplished through integrated outcrop, well log and seismic studies of Mesozoic strata in the Gulf of Mexico, North Atlantic and Rocky Mountain areas.

Estimation of monthly water yields and flows for 1951-2012 for the United States portion of the Great Lakes Basin with AFINCH

USGS Publications Warehouse

Luukkonen, Carol L.; Holtschlag, David J.; Reeves, Howard W.; Hoard, Christopher J.; Fuller, Lori M.

2015-01-01

Monthly water yields from 105,829 catchments and corresponding flows in 107,691 stream segments were estimated for water years 1951–2012 in the Great Lakes Basin in the United States. Both sets of estimates were computed by using the Analysis of Flows In Networks of CHannels (AFINCH) application within the NHDPlus geospatial data framework. AFINCH provides an environment to develop constrained regression models to integrate monthly streamflow and water-use data with monthly climatic data and fixed basin characteristics data available within NHDPlus or supplied by the user. For this study, the U.S. Great Lakes Basin was partitioned into seven study areas by grouping selected hydrologic subregions and adjoining cataloguing units. This report documents the regression models and data used to estimate monthly water yields and flows in each study area. Estimates of monthly water yields and flows are presented in a Web-based mapper application. Monthly flow time series for individual stream segments can be retrieved from the Web application and used to approximate monthly flow-duration characteristics and to identify possible trends.

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-01-01

Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p < 0.01) in the Everglades of Florida over the years 1996-2001. The modeled monthly soil moisture for Illinois of the US agrees well (R2 = 0.79, p < 0.01) with the observed over the years 1984-2001. The modeled monthly stream flow for most 12 major rivers in the US is consistent R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficients >0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

Physical Aggression and Expressive Vocabulary in 19-Month-Old Twins.

ERIC Educational Resources Information Center

Dionne, Ginette; Tremblay, Richard; Boivin, Michel; Laplante, David; Perusse, Daniel

2003-01-01

Used a genetic design to investigate association between physical aggression and language development in 19-month-old twins. Found a modest but significant correlation between aggression and expressive vocabulary. Substantial heritability was found for physical aggression. Quantitative genetic modeling suggested that the correlation could not be…

Simulating the Role of Visual Selective Attention during the Development of Perceptual Completion

ERIC Educational Resources Information Center

Schlesinger, Matthew; Amso, Dima; Johnson, Scott P.

2012-01-01

We recently proposed a multi-channel, image-filtering model for simulating the development of visual selective attention in young infants (Schlesinger, Amso & Johnson, 2007). The model not only captures the performance of 3-month-olds on a visual search task, but also implicates two cortical regions that may play a role in the development of…

Development of Regional Power Sector Coal Fuel Costs (Prices) for the Short-Term Energy Outlook (STEO) Model

EIA Publications

2017-01-01

The U.S. Energy Information Administration's Short-Term Energy Outlook (STEO) produces monthly projections of energy supply, demand, trade, and prices over a 13-24 month period. Every January, the forecast horizon is extended through December of the following year. The STEO model is an integrated system of econometric regression equations and identities that link data on the various components of the U.S. energy industry together in order to develop consistent forecasts. The regression equations are estimated and the STEO model is solved using the EViews 9.5 econometric software package from IHS Global Inc. The model consists of various modules specific to each energy resource. All modules provide projections for the United States, and some modules provide more detailed forecasts for different regions of the country.

A review and update of the Virginia Department of Transportation's cash flow forecasting model : interim report.

DOT National Transportation Integrated Search

1995-01-01

The Virginia Department of Transportation uses a cash flow forecasting model to predict operations expenditures by month. Components of this general forecasting model estimate line items in the VDOT budget. The cash flow model was developed in the ea...

Comparison of artificial intelligence techniques for prediction of soil temperatures in Turkey

NASA Astrophysics Data System (ADS)

Citakoglu, Hatice

2017-10-01

Soil temperature is a meteorological data directly affecting the formation and development of plants of all kinds. Soil temperatures are usually estimated with various models including the artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models. Soil temperatures along with other climate data are recorded by the Turkish State Meteorological Service (MGM) at specific locations all over Turkey. Soil temperatures are commonly measured at 5-, 10-, 20-, 50-, and 100-cm depths below the soil surface. In this study, the soil temperature data in monthly units measured at 261 stations in Turkey having records of at least 20 years were used to develop relevant models. Different input combinations were tested in the ANN and ANFIS models to estimate soil temperatures, and the best combination of significant explanatory variables turns out to be monthly minimum and maximum air temperatures, calendar month number, depth of soil, and monthly precipitation. Next, three standard error terms (mean absolute error (MAE, °C), root mean squared error (RMSE, °C), and determination coefficient ( R 2 )) were employed to check the reliability of the test data results obtained through the ANN, ANFIS, and MLR models. ANFIS (RMSE 1.99; MAE 1.09; R 2 0.98) is found to outperform both ANN and MLR (RMSE 5.80, 8.89; MAE 1.89, 2.36; R 2 0.93, 0.91) in estimating soil temperature in Turkey.

Evaluation of work stress, turnover intention, work experience, and satisfaction with preceptors of new graduate nurses using a 10-minute preceptor model.

PubMed

Hu, Yi-Chun; Chen, Su-Ru; Chen, I-Hui; Shen, Hsi-Che; Lin, Yen-Kuang; Chang, Wen-Yin

2015-06-01

Preparing new graduate nurses (NGNs) to achieve standards of nursing competence is challenging; therefore, this study developed and evaluated the effects of a 10-minute preceptor (10MP) model for assisting NGNs in their professional development and increasing their retention in hospitals. A repeated-measures design study, with an intervention and a two-group comparison, was conducted. A total of 107 NGNs participated in the study. At day 7, work stress and work experience were moderately high for the NGNs in both the 10MP and traditional preceptor model (TPM) groups. The preceptorship program showed significant differences between groups (p = 0.001) regarding work stress at months 2 and 3 and work experience at months 1, 2, and 3. The 10MP group reported lower turnover intention and higher satisfaction with the preceptors than the TPM group. The 10MP model is effective at improving training outcomes and facilitating the professional development of NGNs. Copyright 2015, SLACK Incorporated.

Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study.

PubMed

Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng

2015-09-22

The increasing rate of health care expenditures in the United States has placed a significant burden on the nation's economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. In the HealthInfoNet, Maine's health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient's next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree-based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes.

Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study

PubMed Central

Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank

2015-01-01

Background The increasing rate of health care expenditures in the United States has placed a significant burden on the nation’s economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. Objective This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. Methods In the HealthInfoNet, Maine’s health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient’s next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree–based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Results Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. Conclusions The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes. PMID:26395541

Children's negative emotions and ego-resiliency: longitudinal relations with social competence.

PubMed

Taylor, Zoe E; Eisenberg, Nancy; VanSchyndel, Sarah K; Eggum-Wilkens, Natalie D; Spinrad, Tracy L

2014-04-01

We examined the relations of negative emotions in toddlerhood to the development of ego-resiliency and social competence across early childhood. Specifically, we addressed whether fear and anger/frustration in 30-month-old children (N = 213) was associated with the development of ego-resiliency across 4 time points (42 to 84 months), and, in turn, whether ego-resiliency predicted social competence at 84 months. Child anger/frustration negatively predicted the intercept of ego-resiliency at 42 months (controlling for prior ego-resiliency at 18 months) as well as the slope. Fear did not significantly predict either the intercept or slope of ego-resiliency in the structural model, although it was positively correlated with anger/frustration and was negatively related to ego-resiliency in zero-order correlations. The slope of ego-resiliency was positively related to children's social competence at 84 months; however, the intercept of ego-resiliency (set at 42 months) was not a significant predictor of later social competence. Furthermore, the slope of ego-resiliency mediated the relations between anger/frustration and children's later social competence. The results suggest that individual differences in anger/frustration might contribute to the development of ego-resiliency, which, in turn, is associated with children's social competence.

Statistical Prediction of Sea Ice Concentration over Arctic

NASA Astrophysics Data System (ADS)

Kim, Jongho; Jeong, Jee-Hoon; Kim, Baek-Min

2017-04-01

In this study, a statistical method that predict sea ice concentration (SIC) over the Arctic is developed. We first calculate the Season-reliant Empirical Orthogonal Functions (S-EOFs) of monthly Arctic SIC from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, which contain the seasonal cycles (12 months long) of dominant SIC anomaly patterns. Then, the current SIC state index is determined by projecting observed SIC anomalies for latest 12 months to the S-EOFs. Assuming the current SIC anomalies follow the spatio-temporal evolution in the S-EOFs, we project the future (upto 12 months) SIC anomalies by multiplying the SI and the corresponding S-EOF and then taking summation. The predictive skill is assessed by hindcast experiments initialized at all the months for 1980-2010. When comparing predictive skill of SIC predicted by statistical model and NCEP CFS v2, the statistical model shows a higher skill in predicting sea ice concentration and extent.

@AACAnatomy twitter account goes live: A sustainable social media model for professional societies.

PubMed

Benjamin, Hannah K; Royer, Danielle F

2018-05-01

Social media, with its capabilities of fast, global information sharing, provides a useful medium for professional development, connecting and collaborating with peers, and outreach. The goals of this study were to describe a new, sustainable model for Twitter use by professional societies, and analyze its impact on @AACAnatomy, the Twitter account of the American Association of Clinical Anatomists. Under supervision of an Association committee member, an anatomy graduate student developed a protocol for publishing daily tweets for @AACAnatomy. Five tweet categories were used: Research, Announcements, Replies, Engagement, and Community. Analytics from the 6-month pilot phase were used to assess the impact of the new model. @AACAnatomy had a steady average growth of 33 new followers per month, with less than 10% likely representing Association members. Research tweets, based on Clinical Anatomy articles with an abstract link, were the most shared, averaging 5,451 impressions, 31 link clicks, and nine #ClinAnat hashtag clicks per month. However, tweets from non-Research categories accounted for the highest impression and engagement metrics in four out of six months. For all tweet categories, monthly averages show consistent interaction of followers with the account. Daily tweet publication resulted in a 103% follower increase. An active Twitter account successfully facilitated regular engagement with @AACAnatomy followers and the promotion of clinical anatomy topics within a broad community. This Twitter model has the potential for implementation by other societies as a sustainable medium for outreach, networking, collaboration, and member engagement. Clin. Anat. 31:566-575, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Development of growth equations from longitudinal studies of body weight and height in the full term and preterm neonate: From birth to four years postnatal age.

PubMed

Troutman, John A; Sullivan, Mary C; Carr, Gregory J; Fisher, Jeffrey

2018-03-14

Physiologically based pharmacokinetic (PBPK) models are developed from compound-independent information to describe important anatomical and physiological characteristics of an individual or population of interest. Modeling pediatric populations is challenging because of the rapid changes that occur during growth, particularly in the first few weeks and months after birth. Neonates who are born premature pose several unique challenges in PBPK model development. To provide appropriate descriptions for body weight (BW) and height (Ht) for age and appropriate incremental gains in PBPK models of the developing preterm and full term neonate, anthropometric measurements collected longitudinally from 1,063 preterm and 158 full term neonates were combined with 2,872 cross-sectional measurements obtained from the NHANES 2007-2010 survey. Age-specific polynomial growth equations for BW and Ht were created for male and female neonates with corresponding gestational birth ages of 25, 28, 31, 34, and 40 weeks. Model-predicted weights at birth were within 20% of published fetal/neonatal reference standards. In comparison to full term neonates, postnatal gains in BW and Ht were slower in preterm subgroups, particularly in those born at earlier gestational ages. Catch up growth for BW in neonates born at 25, 28, 31, and 34 weeks gestational age was complete by 13, 8, 6, and 2 months of life (males) and by 10, 6, 5, and 2 months of life (females), respectively. The polynomial growth equations reported in this paper represent extrauterine growth in full term and preterm neonates and differ from the intrauterine growth standards that were developed for the healthy unborn fetus. © 2018 The Authors. Birth Defects Research Published by Wiley Periodicals, Inc.

Integrated healthy workplace model: An experience from North Indian industry

PubMed Central

Thakur, Jarnail Singh; Bains, Puneet; Kar, Sitanshu Sekhar; Wadhwa, Sanjay; Moirangthem, Prabha; Kumar, Rajesh; Wadwalker, Sanjay; Sharma, Yashpal

2012-01-01

Background: Keeping in view of rapid industrialization and growing Indian economy, there has been a substantial increase in the workforce in India. Currently there is no organized workplace model for promoting health of industrial workers in India. Objective: To develop and implement a healthy workplace model in three industrial settings of North India. Materials and Methods: An operations research was conducted for 12 months in purposively selected three industries of Chandigarh. In phase I, a multi-stakeholder workshop was conducted to finalize the components and tools for the healthy workplace model. NCD risk factors were assessed in 947 employees in these three industries. In phase II, the healthy workplace model was implemented on pilot basis for a period of 12 months in these three industries to finalize the model. Findings: Healthy workplace committee with involvement of representatives of management, labor union and research organization was formed in three industries. Various tools like comprehensive and rapid healthy workplace assessment forms, NCD work-lite format for risk factors surveillance and monitoring and evaluation format were developed. The prevalence of tobacco use, ever alcoholics was found to be 17.8% and 47%, respectively. Around one-third (28%) of employees complained of back pain in the past 12 months. Healthy workplace model with focus on three key components (physical environment, psychosocial work environment, and promoting healthy habits) was developed, implemented on pilot basis, and finalized based on experience in participating industries. A stepwise approach for model with a core, expanded, and optional components were also suggested. An accreditation system is also required for promoting healthy workplace program. Conclusion: Integrated healthy workplace model is feasible, could be implemented in industrial setting in northern India and needs to be pilot tested in other parts of the country. PMID:23776318

Climate variation and incidence of Ross river virus in Cairns, Australia: a time-series analysis.

PubMed Central

Tong, S; Hu, W

2001-01-01

In this study we assessed the impact of climate variability on the Ross River virus (RRv) transmission and validated an epidemic-forecasting model in Cairns, Australia. Data on the RRv cases recorded between 1985 and 1996 were obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. The cross-correlation function (CCF) showed that maximum temperature in the current month and rainfall and relative humidity at a lag of 2 months were positively and significantly associated with the monthly incidence of RRv, whereas relative humidity at a lag of 5 months was inversely associated with the RRv transmission. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996. The results show that the relative humidity at a lag of 5 months (p < 0.001) and the rainfall at a lag of 2 months (p < 0.05) appeared to play significant roles in the transmission of RRv disease in Cairns. Furthermore, the regressive forecast curves were consistent with the pattern of actual values. PMID:11748035

Trajectories of Infants' Biobehavioral Development: Timing and Rate of A-Not-B Performance Gains and EEG Maturation

ERIC Educational Resources Information Center

MacNeill, Leigha A.; Ram, Nilam; Bell, Martha Ann; Fox, Nathan A.; Pérez-Edgar, Koraly

2018-01-01

This study examined how timing (i.e., relative maturity) and rate (i.e., how quickly infants attain proficiency) of A-not-B performance were related to changes in brain activity from age 6 to 12 months. A-not-B performance and resting EEG (electroencephalography) were measured monthly from age 6 to 12 months in 28 infants and were modeled using…

The option value of innovative treatments for non-small cell lung cancer and renal cell carcinoma.

PubMed

Thornton Snider, Julia; Batt, Katharine; Wu, Yanyu; Tebeka, Mahlet Gizaw; Seabury, Seth

2017-10-01

To develop a model of the option value a therapy provides by enabling patients to live to see subsequent innovations and to apply the model to the case of nivolumab in renal cell carcinoma (RCC) and non-small cell lung cancer (NSCLC). A model of the option value of nivolumab in RCC and NSCLC was developed and estimated. Data from the Surveillance, Epidemiology, and End Results (SEER) cancer registry and published clinical trial results were used to estimate survival curves for metastatic cancer patients with RCC, squamous NSCLC, or nonsquamous NSCLC. To estimate the conventional value of nivolumab, survival with the pre-nivolumab standard of care was compared with survival with nivolumab assuming no future innovation. To estimate the option value of nivolumab, long-term survival trends in RCC and squamous and nonsquamous NSCLC were measured in SEER to forecast mortality improvements that nivolumab patients may live to see. Compared with the previous standard of care, nivolumab extended life expectancy by 6.3 months in RCC, 7.5 months in squamous NSCLC, and 4.5 months in nonsquamous NSCLC, according to conventional methods. Accounting for expected future mortality trends, nivolumab patients are likely to gain an additional 1.2 months in RCC, 0.4 months in squamous NSCLC, and 0.5 months in nonsquamous NSCLC. These option values correspond to 18%, 5%, and 10% of the conventional value of nivolumab, respectively. Option value is important when valuing therapies like nivolumab that extend life in a rapidly evolving area of care.

Histological analysis and identification of spermatogenesis-related genes in 2-, 6-, and 12-month-old sheep testes

NASA Astrophysics Data System (ADS)

Bai, Man; Sun, Limin; Zhao, Jia; Xiang, Lujie; Cheng, Xiaoyin; Li, Jiarong; Jia, Chao; Jiang, Huaizhi

2017-10-01

Testis development and spermatogenesis are vital factors that influence male animal fertility. In order to identify spermatogenesis-related genes and further provide a theory basis for finding biomarkers related to male sheep fertility, 2-, 6-, and 12-month-old Small Tail Han Sheep testes were selected to investigate the dynamic changes of sheep testis development. Hematoxylin-eosin routine staining and RNA-Seq technique were used to perform histological and transcriptome analysis for these testes. The results showed that 630, 102, and 322 differentially expressed genes (DEGs) were identified in 2- vs 6-month-old, 6- vs 12-month-old, and 2- vs 12-month-old testes, respectively. GO and KEGG analysis showed the following: DEGs in 2- vs 6-month-old testes were mainly related to the GO terms of sexual maturation and the pathways of multiple metabolism and biosynthesis; in 6- vs 12-month-old testes, most of the GO terms that DEGs involved in were related to metabolism and translation processes; the most significantly enriched pathway is the ribosome pathway. The union of DEGs in 2- vs 6-month-old, 6- vs 12-month-old, and 2- vs 12-month-old testes was categorized into eight profiles by series cluster. Subsequently, the eight profiles were classified into four model profiles and four co-expression networks were constructed based on the DEGs in these model profiles. Finally, 29 key regulatory genes related to spermatogenesis were identified in the four co-expression networks. The expression of 13 DEGs (CA3, APOH, MYOC, CATSPER4, SYT6, SERPINA10, DAZL, ADIPOR2, RAB13, CEP41, SPAG4, ODF1, and FRG1) was validated by RT-PCR.

Time series analysis of cholera in Matlab, Bangladesh, during 1988-2001.

PubMed

Ali, Mohammad; Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-03-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001 were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab.

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

USGS Publications Warehouse

Kittel, T.G.F.; Rosenbloom, N.A.; Royle, J. Andrew; Daly, Christopher; Gibson, W.P.; Fisher, H.H.; Thornton, P.; Yates, D.N.; Aulenbach, S.; Kaufman, C.; McKeown, R.; Bachelet, D.; Schimel, D.S.; Neilson, R.; Lenihan, J.; Drapek, R.; Ojima, D.S.; Parton, W.J.; Melillo, J.M.; Kicklighter, D.W.; Tian, H.; McGuire, A.D.; Sykes, M.T.; Smith, B.; Cowling, S.; Hickler, T.; Prentice, I.C.; Running, S.; Hibbard, K.A.; Post, W.M.; King, A.W.; Smith, T.; Rizzo, B.; Woodward, F.I.

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895-1993 on a 0.5?? latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers. ?? Inter-Research 2004.

Using event-related potentials to study perinatal nutrition and brain development in infants of diabetic mothers.

PubMed

deRegnier, Raye-Ann; Long, Jeffrey D; Georgieff, Michael K; Nelson, Charles A

2007-01-01

Proper prenatal and postnatal nutrition is essential for optimal brain development and function. The early use of event-related potentials enables neuroscientists to study the development of cognitive function from birth and to evaluate the role of specific nutrients in development. Perinatal iron deficiency occurs in severely affected infants of diabetic mothers. In animal models, severe perinatal iron deficiency targets the explicit memory system of the brain. Cross-sectional ERP studies have shown that infants of diabetic mothers have impairments in recognition memory from birth through 8 months of age. The purpose of this study was to evaluate longitudinal development of recognition memory using ERPs in infants of diabetic mothers compared with control infants. Infants of diabetic mothers were divided into high and low risk status based upon their birth weights and iron status and compared with healthy control infants. Infants were tested in the newborn period for auditory recognition memory, at 6 months for visual recognition memory and at 8 months for cross modal memory. ERPs were evaluated for developmental changes in the slow waves that are thought to reflect memory and the Nc component that is thought to reflect attention. The results of the study showed differences in development between the IDMs and control infants in the development of the slow waves over the left anterior temporal leads and age-related patterns of development in the NC component. These results are consistent with animal models showing that perinatal iron deficiency affects the development of the memory networks of the brain. This study highlights the value of using ERPs to translate basic science information obtained from animal models to the development of the human infant.

Using Event-Related Potentials to Study Perinatal Nutrition and Brain Development in Infants of Diabetic Mothers

PubMed Central

deRegnier, Raye-Ann; Long, Jeffrey D.; Georgieff, Michael K.; Nelson, Charles A.

2009-01-01

Proper prenatal and postnatal nutrition is essential for optimal brain development and function. The early use of event-related potentials enables neuroscientists to study the development of cognitive function from birth and to evaluate the role of specific nutrients in development. Perinatal iron deficiency occurs in severely affected infants of diabetic mothers. In animal models, severe perinatal iron deficiency targets the explicit memory system of the brain. Cross-sectional ERP studies have shown that infants of diabetic mothers have impairments in recognition memory from birth through 8 months of age. The purpose of this study was to evaluate longitudinal development of recognition memory using ERPs in infants of diabetic mothers compared with control infants. Infants of diabetic mothers were divided into high and low risk status based upon their birthweights and iron status and compared with healthy control infants. Infants were tested in the newborn period for auditory recognition memory, at 6 months for visual recognition memory and at 8 months for cross modal memory. ERPs were evaluated for developmental changes in the slow waves that are thought to reflect memory and the Nc component that is thought to reflect attention. The results of the study showed differences in development between the IDMs and control infants in the development of the slow waves over the left anterior temporal leads and age-related patterns of development in the NC component. These results are consistent with animal models showing that perinatal iron deficiency affects the development of the memory networks of the brain. This study highlights the value of using ERPs to translate basic science information obtained from animal models to the development of the human infant. PMID:17559331

Adaptive Planning: Understanding Organizational Workload to Capability/ Capacity through Modeling and Simulation

NASA Technical Reports Server (NTRS)

Hase, Chris

2010-01-01

In August 2003, the Secretary of Defense (SECDEF) established the Adaptive Planning (AP) initiative [1] with an objective of reducing the time necessary to develop and revise Combatant Commander (COCOM) contingency plans and increase SECDEF plan visibility. In addition to reducing the traditional plan development timeline from twenty-four months to less than twelve months (with a goal of six months)[2], AP increased plan visibility to Department of Defense (DoD) leadership through In-Progress Reviews (IPRs). The IPR process, as well as the increased number of campaign and contingency plans COCOMs had to develop, increased the workload while the number of planners remained fixed. Several efforts from collaborative planning tools to streamlined processes were initiated to compensate for the increased workload enabling COCOMS to better meet shorter planning timelines. This paper examines the Joint Strategic Capabilities Plan (JSCP) directed contingency planning and staffing requirements assigned to a combatant commander staff through the lens of modeling and simulation. The dynamics of developing a COCOM plan are captured with an ExtendSim [3] simulation. The resulting analysis provides a quantifiable means by which to measure a combatant commander staffs workload associated with development and staffing JSCP [4] directed contingency plans with COCOM capability/capacity. Modeling and simulation bring significant opportunities in measuring the sensitivity of key variables in the assessment of workload to capability/capacity analysis. Gaining an understanding of the relationship between plan complexity, number of plans, planning processes, and number of planners with time required for plan development provides valuable information to DoD leadership. Through modeling and simulation AP leadership can gain greater insight in making key decisions on knowing where to best allocate scarce resources in an effort to meet DoD planning objectives.

Forecasting the incidence of tuberculosis in China using the seasonal auto-regressive integrated moving average (SARIMA) model.

PubMed

Mao, Qiang; Zhang, Kai; Yan, Wu; Cheng, Chaonan

2018-05-02

The aims of this study were to develop a forecasting model for the incidence of tuberculosis (TB) and analyze the seasonality of infections in China; and to provide a useful tool for formulating intervention programs and allocating medical resources. Data for the monthly incidence of TB from January 2004 to December 2015 were obtained from the National Scientific Data Sharing Platform for Population and Health (China). The Box-Jenkins method was applied to fit a seasonal auto-regressive integrated moving average (SARIMA) model to forecast the incidence of TB over the subsequent six months. During the study period of 144 months, 12,321,559 TB cases were reported in China, with an average monthly incidence of 6.4426 per 100,000 of the population. The monthly incidence of TB showed a clear 12-month cycle, and a seasonality with two peaks occurring in January and March and a trough in December. The best-fit model was SARIMA (1,0,0)(0,1,1) 12 , which demonstrated adequate information extraction (white noise test, p>0.05). Based on the analysis, the incidence of TB from January to June 2016 were 6.6335, 4.7208, 5.8193, 5.5474, 5.2202 and 4.9156 per 100,000 of the population, respectively. According to the seasonal pattern of TB incidence in China, the SARIMA model was proposed as a useful tool for monitoring epidemics. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Recent progress in tidal modeling

NASA Technical Reports Server (NTRS)

Vial, F.; Forbes, J. M.

1989-01-01

Recent contributions to tidal theory during the last five years are reviewed. Specific areas where recent progress has occurred include: the action of mean wind and dissipation on tides, interactions of other waves with tides, the use of TGCM in tidal studies. Furthermore, attention is put on the nonlinear interaction between semidiurnal and diurnal tides. Finally, more realistic thermal excitation and background wind and temperature models have been developed in the past few years. This has led to new month-to-month numerical simulations of the semidiurnal tide. Some results using these models are presented and compared with ATMAP tidal climatologies.

The NASA Marshall Space Flight Center Earth Global Reference Atmospheric Model-2010 Version

NASA Technical Reports Server (NTRS)

Leslie, F. W.; Justus, C. G.

2011-01-01

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA Marshall Space Flight Center Global Reference Atmospheric Model was developed in response to the need for a design reference atmosphere that provides complete global geographical variability and complete altitude coverage (surface to orbital altitudes), as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. In addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations.

Development and Evaluation of a Pilot Nurse Case Management Model to Address Multidrug-Resistant Tuberculosis (MDR-TB) and HIV in South Africa

PubMed Central

Farley, Jason E.; Kelly, Ana M.; Reiser, Katrina; Brown, Maria; Kub, Joan; Davis, Jeane G.; Walshe, Louise; Van der Walt, Martie

2014-01-01

Setting Multidrug-resistant tuberculosis (MDR-TB) unit in KwaZulu-Natal, South Africa. Objective To develop and evaluate a nurse case management model and intervention using the tenets of the Chronic Care Model to manage treatment for MDR-TB patients with a high prevalence of human immunodeficiency virus (HIV) co-infection. Design A quasi-experimental pilot programme utilizing a nurse case manager to manage care for 40 hospitalized MDR-TB patients, 70% HIV co-infected, during the intensive phase of MDR-TB treatment. Patients were followed for six months to compare proximal outcomes identified in the model between the pre- and post-intervention period. Results The greatest percent differences between baseline and six-month MDR-TB proximal outcomes were seen in the following three areas: baseline symptom evaluation on treatment initiation (95% improvement), baseline and monthly laboratory evaluations completed per guidelines (75% improvement), and adverse drug reactions acted upon by medical and/or nursing intervention (75% improvement). Conclusion Improvements were identified in guideline-based treatment and monitoring of adverse drug reactions following implementation of the nurse case management intervention. Further study is required to determine if the intervention introduced in this model will ultimately result in improvements in final MDR-TB treatment outcomes. PMID:25405988

Modeling temporal and large-scale spatial variability of soil respiration from soil water availability, temperature and vegetation productivity indices

NASA Astrophysics Data System (ADS)

Reichstein, Markus; Rey, Ana; Freibauer, Annette; Tenhunen, John; Valentini, Riccardo; Banza, Joao; Casals, Pere; Cheng, Yufu; Grünzweig, Jose M.; Irvine, James; Joffre, Richard; Law, Beverly E.; Loustau, Denis; Miglietta, Franco; Oechel, Walter; Ourcival, Jean-Marc; Pereira, Joao S.; Peressotti, Alessandro; Ponti, Francesca; Qi, Ye; Rambal, Serge; Rayment, Mark; Romanya, Joan; Rossi, Federica; Tedeschi, Vanessa; Tirone, Giampiero; Xu, Ming; Yakir, Dan

2003-12-01

Field-chamber measurements of soil respiration from 17 different forest and shrubland sites in Europe and North America were summarized and analyzed with the goal to develop a model describing seasonal, interannual and spatial variability of soil respiration as affected by water availability, temperature, and site properties. The analysis was performed at a daily and at a monthly time step. With the daily time step, the relative soil water content in the upper soil layer expressed as a fraction of field capacity was a good predictor of soil respiration at all sites. Among the site variables tested, those related to site productivity (e.g., leaf area index) correlated significantly with soil respiration, while carbon pool variables like standing biomass or the litter and soil carbon stocks did not show a clear relationship with soil respiration. Furthermore, it was evidenced that the effect of precipitation on soil respiration stretched beyond its direct effect via soil moisture. A general statistical nonlinear regression model was developed to describe soil respiration as dependent on soil temperature, soil water content, and site-specific maximum leaf area index. The model explained nearly two thirds of the temporal and intersite variability of soil respiration with a mean absolute error of 0.82 μmol m-2 s-1. The parameterized model exhibits the following principal properties: (1) At a relative amount of upper-layer soil water of 16% of field capacity, half-maximal soil respiration rates are reached. (2) The apparent temperature sensitivity of soil respiration measured as Q10 varies between 1 and 5 depending on soil temperature and water content. (3) Soil respiration under reference moisture and temperature conditions is linearly related to maximum site leaf area index. At a monthly timescale, we employed the approach by [2002] that used monthly precipitation and air temperature to globally predict soil respiration (T&P model). While this model was able to explain some of the month-to-month variability of soil respiration, it failed to capture the intersite variability, regardless of whether the original or a new optimized model parameterization was used. In both cases, the residuals were strongly related to maximum site leaf area index. Thus, for a monthly timescale, we developed a simple T&P&LAI model that includes leaf area index as an additional predictor of soil respiration. This extended but still simple model performed nearly as well as the more detailed time step model and explained 50% of the overall and 65% of the site-to-site variability. Consequently, better estimates of globally distributed soil respiration should be obtained with the new model driven by satellite estimates of leaf area index. Before application at the continental or global scale, this approach should be further tested in boreal, cold-temperate, and tropical biomes as well as for non-woody vegetation.

A Model Program for Teenage Youth: First Year Evaluation of Knowledge Development.

ERIC Educational Resources Information Center

Pooley, Richard C.

Progress in the second 6 months of a program development model for learning disabled (LD) and emotionally disturbed (ED) adolescents is reported. The program is designed to teach ED and LD children necessary work skills so that they can become productive members of society. Three methods are under investigation: (1) use of audio/visual resources…

The influence of mothers' and fathers' sensitivity in the first year of life on children's cognitive outcomes at 18 and 36 months.

PubMed

Malmberg, L-E; Lewis, S; West, A; Murray, E; Sylva, K; Stein, A

2016-01-01

There has been increasing interest in the relative effects of mothers' and fathers' interactions with their infants on later development. However to date there has been little work on children's cognitive outcomes. We examined the relative influence of fathers' and mothers' sensitivity during interactions with their children at the end of the child's first year (10-12 months, n = 97), on child general cognitive development at 18 months and language at 36 months. Both parents' sensitivity was associated with cognitive and language outcomes in univariate analyses. Mothers' sensitivity, however, appeared to be associated with family socio-demographic factors to a greater extent that fathers' sensitivity. Using path modelling the effect of paternal sensitivity on general cognitive development at 18 months and language at 36 months was significantly greater than the effect of maternal sensitivity, when controlling for socio-demographic background. In relation to language at 36 months, there was some evidence that sensitivity of one parent buffered the effect of lower sensitivity of the other parent. These findings suggest that parental sensitivity can play an important role in children's cognitive and language development, and that higher sensitivity of one parent can compensate for the lower sensitivity of the other parent. Replication of these findings, however, is required in larger samples. © 2015 John Wiley & Sons Ltd.

An educational intervention to improve hand hygiene compliance in Vietnam.

PubMed

Phan, Hang Thi; Tran, Hang Thi Thuy; Tran, Hanh Thi My; Dinh, Anh Pham Phuong; Ngo, Ha Thanh; Theorell-Haglow, Jenny; Gordon, Christopher J

2018-03-07

Hand hygiene compliance is the basis of infection control programs. In developing countries models to improve hand hygiene compliance to reduce healthcare acquired infections are required. The aim of this study was to determine hand hygiene compliance following an educational program in an obstetric and gynecological hospital in Vietnam. Health care workers from neonatal intensive care, delivery suite and a surgical ward from Hung Vuong Hospital, Ho Chi Minh City, Vietnam undertook a 4-h educational program targeting hand hygiene. Compliance was monitored monthly for six months following the intervention. Hand hygiene knowledge was assessed at baseline and after six months of the study. There were 7124 opportunities over 370 hand hygiene recording sessions with 1531 opportunities at baseline and 1620 at 6 months following the intervention. Hand hygiene compliance increased significantly from baseline across all sites (43.6% [95% Confidence interval CI: 41.1-46.1] to 63% [95% CI: 60.6-65.3]; p < 0.0001). Health care worker hand hygiene compliance increased significantly after intervention (p < 0.0001). There were significant improvements in knowledge scores from baseline to 2 months post educational intervention with mean difference standard deviations (SD): 1.5 (2.5); p < 0.001). A simple educational model was implemented in a Vietnamese hospital that revealed good hand hygiene compliance for an extended period of time. Hand hygiene knowledge increased during the intervention. This hand hygiene model could be used in developing countries were resources are limited.

High resolution reconstruction of monthly precipitation of Iberian Peninsula using circulation weather types

NASA Astrophysics Data System (ADS)

Cortesi, N.; Trigo, R.; Gonzalez-Hidalgo, J. C.; Ramos, A. M.

2012-06-01

Precipitation over the Iberian Peninsula (IP) is highly variable and shows large spatial contrasts between wet mountainous regions, to the north, and dry regions in the inland plains and southern areas. In this work, a high-density monthly precipitation dataset for the IP was coupled with a set of 26 atmospheric circulation weather types (Trigo and DaCamara, 2000) to reconstruct Iberian monthly precipitation from October to May with a very high resolution of 3030 precipitation series (overall mean density one station each 200 km2). A stepwise linear regression model with forward selection was used to develop monthly reconstructed precipitation series calibrated and validated over 1948-2003 period. Validation was conducted by means of a leave-one-out cross-validation over the calibration period. The results show a good model performance for selected months, with a mean coefficient of variation (CV) around 0.6 for validation period, being particularly robust over the western and central sectors of IP, while the predicted values in the Mediterranean and northern coastal areas are less acute. We show for three long stations (Lisbon, Madrid and Valencia) the comparison between model and original data as an example to how these models can be used in order to obtain monthly precipitation fields since the 1850s over most of IP for this very high density network.

Evaluation of drought using SPEI drought class transitions and log-linear models for different agro-ecological regions of India

NASA Astrophysics Data System (ADS)

Alam, N. M.; Sharma, G. C.; Moreira, Elsa; Jana, C.; Mishra, P. K.; Sharma, N. K.; Mandal, D.

2017-08-01

Markov chain and 3-dimensional log-linear models were attempted to model drought class transitions derived from the newly developed drought index the Standardized Precipitation Evapotranspiration Index (SPEI) at a 12 month time scale for six major drought prone areas of India. Log-linear modelling approach has been used to investigate differences relative to drought class transitions using SPEI-12 time series derived form 48 yeas monthly rainfall and temperature data. In this study, the probabilities of drought class transition, the mean residence time, the 1, 2 or 3 months ahead prediction of average transition time between drought classes and the drought severity class have been derived. Seasonality of precipitation has been derived for non-homogeneous Markov chains which could be used to explain the effect of the potential retreat of drought. Quasi-association and Quasi-symmetry log-linear models have been fitted to the drought class transitions derived from SPEI-12 time series. The estimates of odds along with their confidence intervals were obtained to explain the progression of drought and estimation of drought class transition probabilities. For initial months as the drought severity increases the calculated odds shows lower value and the odds decreases for the succeeding months. This indicates that the ratio of expected frequencies of occurrence of transition from drought class to the non-drought class decreases as compared to transition to any drought class when the drought severity of the present class increases. From 3-dimensional log-linear model it is clear that during the last 24 years the drought probability has increased for almost all the six regions. The findings from the present study will immensely help to assess the impact of drought on the gross primary production and to develop future contingent planning in similar regions worldwide.

Source apportionment of PM2.5 organic carbon in the San Joaquin Valley using monthly and daily observations and meteorological clustering.

PubMed

Skiles, Matthew J; Lai, Alexandra M; Olson, Michael R; Schauer, James J; de Foy, Benjamin

2018-06-01

Two hundred sixty-three fine particulate matter (PM 2.5 ) samples collected on 3-day intervals over a 14-month period at two sites in the San Joaquin Valley (SJV) were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC), and organic molecular markers. A unique source profile library was applied to a chemical mass balance (CMB) source apportionment model to develop monthly and seasonally averaged source apportionment results. Five major OC sources were identified: mobile sources, biomass burning, meat smoke, vegetative detritus, and secondary organic carbon (SOC), as inferred from OC not apportioned by CMB. The SOC factor was the largest source contributor at Fresno and Bakersfield, contributing 44% and 51% of PM mass, respectively. Biomass burning was the only source with a statistically different average mass contribution (95% CI) between the two sites. Wintertime peaks of biomass burning, meat smoke, and total OC were observed at both sites, with SOC peaking during the summer months. Exceptionally strong seasonal variation in apportioned meat smoke mass could potentially be explained by oxidation of cholesterol between source and receptor and trends in wind transport outlined in a Residence Time Analysis (RTA). Fast moving nighttime winds prevalent during warmer months caused local emissions to be replaced by air mass transported from the San Francisco Bay Area, consisting of mostly diluted, oxidized concentrations of molecular markers. Good agreement was observed between SOC derived from the CMB model and from non-biomass burning WSOC mass, suggesting the CMB model is sufficiently accurate to assist in policy development. In general, uncertainty in monthly mass values derived from daily CMB apportionments were lower than that of CMB results produced with monthly marker composites, further validating daily sampling methodologies. Strong seasonal trends were observed for biomass and meat smoke OC apportionment, and monthly mass averages had lowest uncertainty when derived from daily CMB apportionments. Copyright © 2018 Elsevier Ltd. All rights reserved.

Functional Deficits Precede Structural Lesions in Mice With High-Fat Diet–Induced Diabetic Retinopathy

PubMed Central

Rajagopal, Rithwick; Bligard, Gregory W.; Zhang, Sheng; Yin, Li; Lukasiewicz, Peter

2016-01-01

Obesity predisposes to human type 2 diabetes, the most common cause of diabetic retinopathy. To determine if high-fat diet–induced diabetes in mice can model retinal disease, we weaned mice to chow or a high-fat diet and tested the hypothesis that diet-induced metabolic disease promotes retinopathy. Compared with controls, mice fed a diet providing 42% of energy as fat developed obesity-related glucose intolerance by 6 months. There was no evidence of microvascular disease until 12 months, when trypsin digests and dye leakage assays showed high fat–fed mice had greater atrophic capillaries, pericyte ghosts, and permeability than controls. However, electroretinographic dysfunction began at 6 months in high fat–fed mice, manifested by increased latencies and reduced amplitudes of oscillatory potentials compared with controls. These electroretinographic abnormalities were correlated with glucose intolerance. Unexpectedly, retinas from high fat–fed mice manifested striking induction of stress kinase and neural inflammasome activation at 3 months, before the development of systemic glucose intolerance, electroretinographic defects, or microvascular disease. These results suggest that retinal disease in the diabetic milieu may progress through inflammatory and neuroretinal stages long before the development of vascular lesions representing the classic hallmark of diabetic retinopathy, establishing a model for assessing novel interventions to treat eye disease. PMID:26740595

Beginning to Talk Like an Adult: Increases in Speech-like Utterances in Young Cochlear Implant Recipients and Toddlers with Normal Hearing

PubMed Central

Ertmer, David J.; Jung, Jongmin; Kloiber, Diana True

2013-01-01

Background Speech-like utterances containing rapidly combined consonants and vowels eventually dominate the prelinguistic and early word productions of toddlers who are developing typically (TD). It seems reasonable to expect a similar phenomenon in young cochlear implants (CI) recipients. This study sought to determine the number of months of robust hearing experience needed to achieve a majority of speech-like utterances in both of these groups. Methods Speech samples were recorded at 3-month intervals during the first 2 years of CI experience, and between 6- and 24 months of age in TD children. Speech-like utterances were operationally defined as those belonging to the Basic Canonical Syllables (BCS) or Advanced Forms (AF) levels of the Consolidated Stark Assessment of Early Vocal Development-Revised. Results On average, the CI group achieved a majority of speech- like utterances after 12 months, and the TD group after 18 months of robust hearing experience. The CI group produced greater percentages of speech-like utterances at each interval until 24-months, when both groups approximated 80%. Conclusion Auditory deprivation did not limit progress in vocal development as young CI recipients showed more-rapid-than-typical speech development during the first 2 years of device use. Implications for the Infraphonological model of speech development are considered. PMID:23813203

A hybrid spatiotemporal drought forecasting model for operational use

NASA Astrophysics Data System (ADS)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis

PubMed Central

Botai, Joel O.; Rautenbach, Hannes; Ncongwane, Katlego P.; Botai, Christina M.

2017-01-01

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease’s transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998–2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables’ and malaria cases’ time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature (R2 = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention. PMID:29117114

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

PubMed

Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

2017-11-08

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention.

Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America

NASA Astrophysics Data System (ADS)

Soares dos Santos, T.; Mendes, D.; Rodrigues Torres, R.

2016-01-01

Several studies have been devoted to dynamic and statistical downscaling for analysis of both climate variability and climate change. This paper introduces an application of artificial neural networks (ANNs) and multiple linear regression (MLR) by principal components to estimate rainfall in South America. This method is proposed for downscaling monthly precipitation time series over South America for three regions: the Amazon; northeastern Brazil; and the La Plata Basin, which is one of the regions of the planet that will be most affected by the climate change projected for the end of the 21st century. The downscaling models were developed and validated using CMIP5 model output and observed monthly precipitation. We used general circulation model (GCM) experiments for the 20th century (RCP historical; 1970-1999) and two scenarios (RCP 2.6 and 8.5; 2070-2100). The model test results indicate that the ANNs significantly outperform the MLR downscaling of monthly precipitation variability.

Modeling and simulation of maintenance treatment in first-line non-small cell lung cancer with external validation.

PubMed

Han, Kelong; Claret, Laurent; Sandler, Alan; Das, Asha; Jin, Jin; Bruno, Rene

2016-07-13

Maintenance treatment (MTx) in responders following first-line treatment has been investigated and practiced for many cancers. Modeling and simulation may support interpretation of interim data and development decisions. We aimed to develop a modeling framework to simulate overall survival (OS) for MTx in NSCLC using tumor growth inhibition (TGI) data. TGI metrics were estimated using longitudinal tumor size data from two Phase III first-line NSCLC studies evaluating bevacizumab and erlotinib as MTx in 1632 patients. Baseline prognostic factors and TGI metric estimates were assessed in multivariate parametric models to predict OS. The OS model was externally validated by simulating a third independent NSCLC study (n = 253) based on interim TGI data (up to progression-free survival database lock). The third study evaluated pemetrexed + bevacizumab vs. bevacizumab alone as MTx. Time-to-tumor-growth (TTG) was the best TGI metric to predict OS. TTG, baseline tumor size, ECOG score, Asian ethnicity, age, and gender were significant covariates in the final OS model. The OS model was qualified by simulating OS distributions and hazard ratios (HR) in the two studies used for model-building. Simulations of the third independent study based on interim TGI data showed that pemetrexed + bevacizumab MTx was unlikely to significantly prolong OS vs. bevacizumab alone given the current sample size (predicted HR: 0.81; 95 % prediction interval: 0.59-1.09). Predicted median OS was 17.3 months and 14.7 months in both arms, respectively. These simulations are consistent with the results of the final OS analysis published 2 years later (observed HR: 0.87; 95 % confidence interval: 0.63-1.21). Final observed median OS was 17.1 months and 13.2 months in both arms, respectively, consistent with our predictions. A robust TGI-OS model was developed for MTx in NSCLC. TTG captures treatment effect. The model successfully predicted the OS outcomes of an independent study based on interim TGI data and thus may facilitate trial simulation and interpretation of interim data. The model was built based on erlotinib data and externally validated using pemetrexed data, suggesting that TGI-OS models may be treatment-independent. The results supported the use of longitudinal tumor size and TTG as endpoints in early clinical oncology studies.

Using statistical and artificial neural network models to forecast potentiometric levels at a deep well in South Texas

NASA Astrophysics Data System (ADS)

Uddameri, V.

2007-01-01

Reliable forecasts of monthly and quarterly fluctuations in groundwater levels are necessary for short- and medium-term planning and management of aquifers to ensure proper service of seasonal demands within a region. Development of physically based transient mathematical models at this time scale poses considerable challenges due to lack of suitable data and other uncertainties. Artificial neural networks (ANN) possess flexible mathematical structures and are capable of mapping highly nonlinear relationships. Feed-forward neural network models were constructed and trained using the back-percolation algorithm to forecast monthly and quarterly time-series water levels at a well that taps into the deeper Evangeline formation of the Gulf Coast aquifer in Victoria, TX. Unlike unconfined formations, no causal relationships exist between water levels and hydro-meteorological variables measured near the vicinity of the well. As such, an endogenous forecasting model using dummy variables to capture short-term seasonal fluctuations and longer-term (decadal) trends was constructed. The root mean square error, mean absolute deviation and correlation coefficient ( R) were noted to be 1.40, 0.33 and 0.77 m, respectively, for an evaluation dataset of quarterly measurements and 1.17, 0.46, and 0.88 m for an evaluative monthly dataset not used to train or test the model. These statistics were better for the ANN model than those developed using statistical regression techniques.

Learning-based deformable image registration for infant MR images in the first year of life.

PubMed

Hu, Shunbo; Wei, Lifang; Gao, Yaozong; Guo, Yanrong; Wu, Guorong; Shen, Dinggang

2017-01-01

Many brain development studies have been devoted to investigate dynamic structural and functional changes in the first year of life. To quantitatively measure brain development in such a dynamic period, accurate image registration for different infant subjects with possible large age gap is of high demand. Although many state-of-the-art image registration methods have been proposed for young and elderly brain images, very few registration methods work for infant brain images acquired in the first year of life, because of (a) large anatomical changes due to fast brain development and (b) dynamic appearance changes due to white-matter myelination. To address these two difficulties, we propose a learning-based registration method to not only align the anatomical structures but also alleviate the appearance differences between two arbitrary infant MR images (with large age gap) by leveraging the regression forest to predict both the initial displacement vector and appearance changes. Specifically, in the training stage, two regression models are trained separately, with (a) one model learning the relationship between local image appearance (of one development phase) and its displacement toward the template (of another development phase) and (b) another model learning the local appearance changes between the two brain development phases. Then, in the testing stage, to register a new infant image to the template, we first predict both its voxel-wise displacement and appearance changes by the two learned regression models. Since such initializations can alleviate significant appearance and shape differences between new infant image and the template, it is easy to just use a conventional registration method to refine the remaining registration. We apply our proposed registration method to align 24 infant subjects at five different time points (i.e., 2-week-old, 3-month-old, 6-month-old, 9-month-old, and 12-month-old), and achieve more accurate and robust registration results, compared to the state-of-the-art registration methods. The proposed learning-based registration method addresses the challenging task of registering infant brain images and achieves higher registration accuracy compared with other counterpart registration methods. © 2016 American Association of Physicists in Medicine.

Association between breast milk intake at 9-10 months of age and growth and development among Malawian young children.

PubMed

Kumwenda, Chiza; Hemsworth, Jaimie; Phuka, John; Ashorn, Ulla; Arimond, Mary; Maleta, Kenneth; Prado, Elizabeth L; Haskell, Marjorie J; Dewey, Kathryn G; Ashorn, Per

2018-07-01

World Health Organization recommends exclusive breastfeeding for infants for the first 6 months of life, followed by introduction of nutritious complementary foods alongside breastfeeding. Breast milk remains a significant source of nourishment in the second half of infancy and beyond; however, it is not clear whether more breast milk is always better. The present study was designed to determine the association between amount of breast milk intake at 9-10 months of age and infant growth and development by 12-18 months of age. The study was nested in a randomized controlled trial conducted in Malawi. Regression analysis was used to determine associations between breast milk intake and growth and development. Mean (SD) breast milk intake at 9-10 months of age was 752 (244) g/day. Mean (SD) length-for-age z-score at 12 months and change in length-for-age z-score between 12 and 18 months were -1.69 (1.0) and -0.17 (0.6), respectively. At 18 months, mean (SD) expressive vocabulary score was 32 (24) words and median (interquartile range) skills successfully performed for fine, gross, and overall motor skills were 21 (19-22), 18 (16-19), and 38 (26-40), respectively. Breast milk intake (g/day) was not associated with either growth or development. Proportion of total energy intake from breast milk was negatively associated with fine motor (β = -0.18, p = .015) but not other developmental scores in models adjusted for potential confounders. Among Malawian infants, neither breast milk intake nor percent of total energy intake from breast milk at 9-10 months was positively associated with subsequent growth between 12 and 18 months, or development at 18 months. © 2018 John Wiley & Sons Ltd.

Emotional availability at bedtime, infant temperament, and infant sleep development from 1 to 6 months

PubMed Central

Jian, Ni; Teti, Douglas M.

2016-01-01

Infant sleep consolidates rapidly during the first half year of life in the context of a dynamic, bidirectional exchange between infant characteristics and the caregiving environment. The current study examined relations among mothers’ emotional availability (EA) at bedtime, infant temperament, and objectively assessed infant sleep development from 1 to 6 months, and in particular focused on whether infant temperament moderated linkages between EA at bedtime and infant sleep development. The sample consisted of seventy-two mother-infant dyads, and measures included actigraphy-assessed infant sleep at 1 and 6 months, observed maternal EA coded from bedtime videos at 3 and 6 months, and maternal reports of infant temperament at 3 and 6 months. Analysis showed significant positive effects of maternal EA at bedtime on developmental changes in infant sleep minutes. Additionally, infant temperamental surgency moderated the influence of EA at bedtime on the increase in infant sleep minutes. In other words, highly surgent infants increased their sleep time more than other infants if their mothers were emotionally available at bedtime. Results were discussed in terms of the transactional model of infant sleep development. PMID:27692276

The development of prosocial behaviors in young children: a prospective population-based cohort study.

PubMed

Baillargeon, Raymond H; Morisset, Alexandre; Keenan, Kate; Normand, Claude L; Jeyaganth, Suganthiny; Boivin, Michel; Tremblay, Richard E

2011-01-01

Researchers know relatively little about the normative development of children's behaviors aimed at alleviating distress or discomfort in others. In this article, the authors aim to describe the continuity and discontinuity in the degree to which young children in the general population are reported to exhibit specific prosocial behaviors. Data came from the Québec Longitudinal Study of Child Development. Consistent with Hay's model of prosocial development, the results show that there were about as many children who stopped exhibiting prosocial behaviors between 29 and 41 months of age as there were children who started doing so during this period. Further, gender differences (girls > boys) in prosocial behaviors are either emerging or at least increasing in magnitude, with girls being more likely to start and boys being more likely to stop exhibiting these behaviors between 29 and 41 months of age. Consistent with the early-onset hypothesis, children who exhibit prosocial behaviors at 17 months of age are less likely to stop exhibiting the same behaviors between 29 and 41 months of age. Otherwise, if they did not exhibit prosocial behaviors at 29 months of age, they are also more likely to start doing so in the following year.

Creating a Common Data Model for Comparative Effectiveness with the Observational Medical Outcomes Partnership.

PubMed

FitzHenry, F; Resnic, F S; Robbins, S L; Denton, J; Nookala, L; Meeker, D; Ohno-Machado, L; Matheny, M E

2015-01-01

Adoption of a common data model across health systems is a key infrastructure requirement to allow large scale distributed comparative effectiveness analyses. There are a growing number of common data models (CDM), such as Mini-Sentinel, and the Observational Medical Outcomes Partnership (OMOP) CDMs. In this case study, we describe the challenges and opportunities of a study specific use of the OMOP CDM by two health systems and describe three comparative effectiveness use cases developed from the CDM. The project transformed two health system databases (using crosswalks provided) into the OMOP CDM. Cohorts were developed from the transformed CDMs for three comparative effectiveness use case examples. Administrative/billing, demographic, order history, medication, and laboratory were included in the CDM transformation and cohort development rules. Record counts per person month are presented for the eligible cohorts, highlighting differences between the civilian and federal datasets, e.g. the federal data set had more outpatient visits per person month (6.44 vs. 2.05 per person month). The count of medications per person month reflected the fact that one system's medications were extracted from orders while the other system had pharmacy fills and medication administration records. The federal system also had a higher prevalence of the conditions in all three use cases. Both systems required manual coding of some types of data to convert to the CDM. The data transformation to the CDM was time consuming and resources required were substantial, beyond requirements for collecting native source data. The need to manually code subsets of data limited the conversion. However, once the native data was converted to the CDM, both systems were then able to use the same queries to identify cohorts. Thus, the CDM minimized the effort to develop cohorts and analyze the results across the sites.

Alteration of infant attention and activity by polychlorinated biphenyls: unravelling critical windows of susceptibility using physiologically based pharmacokinetic modeling.

PubMed

Verner, M-A; Plusquellec, P; Muckle, G; Ayotte, P; Dewailly, E; Jacobson, S W; Jacobson, J L; Charbonneau, M; Haddad, S

2010-09-01

Pre- and postnatal exposure to polychlorinated biphenyls (PCBs) can impair behavioural function in animal models at doses within the range at which humans are commonly exposed. Yet, epidemiologic studies conducted in the US and Europe are inconsistent with regard to the developmental effects of lactational exposure to these chemicals. This inconsistency may be due to limitations in the current methodological approaches for assessing postnatal exposure to PCBs. Our study used a physiologically based pharmacokinetic (PBPK) model to simulate blood PCB levels during specific pre- and postnatal periods and to evaluate the relation of those levels to infant behaviour. A previously validated PBPK model was used to simulate infant blood PCB-153 levels at delivery and on a month-by-month basis during the first year of life for Inuit infants enrolled in a longitudinal birth cohort. Infant behaviour was assessed using the Behaviour Rating Scales (BRS) of the Bayley Scales of Infant Development (BSID-II) at 11 months of age and video coding of inattention and activity measured during the administration of the mental development subscale of the BSID-II. The estimated pre- and postnatal PCB exposure measures predicted significant increases in inattention and activity at 11 months. Whereas inattention was related to prenatal exposure, activity level, measured by non-elicited activity, was best predicted by postnatal exposure, with the strongest association obtained for simulated PCB levels during the 4th month of life. These findings are consistent with previous reports indicating PCB-induced behavioural alteration in attention and activity level. Simulated infant toxicokinetic profiles for the first year of life revealed windows of susceptibility during which PCBs may impair infant attention and activity. Copyright © 2010 Elsevier Inc. All rights reserved.

Possible determinants and spatial patterns of anaemia among young children in Nigeria: a Bayesian semi-parametric modelling.

PubMed

Gayawan, Ezra; Arogundade, Ekundayo D; Adebayo, Samson B

2014-03-01

Anaemia is a global public health problem affecting both developing and developed countries with major consequences for human health and socioeconomic development. This paper examines the possible relationship between Hb concentration and severity of anaemia with individual and household characteristics of children aged 6-59 months in Nigeria; and explores possible geographical variations of these outcome variables. Data on Hb concentration and severity of anaemia in children aged 6-59 months that participated in the 2010 Nigeria Malaria Indicator Survey were analysed. A semi-parametric model using a hierarchical Bayesian approach was adopted to examine the putative relationship of covariates of different types and possible spatial variation. Gaussian, binary and ordinal outcome variables were considered in modelling. Spatial analyses reveal a distinct North-South divide in Hb concentration of the children analysed and that states in Northern Nigeria possess a higher risk of anaemia. Other important risk factors include the household wealth index, sex of the child, whether or not the child had fever or malaria in the 2 weeks preceding the survey, and children under 24 months of age. There is a need for state level implementation of specific programmes that target vulnerable children as this can help in reversing the existing patterns.

The Vicious Cycle of Family Atmosphere, Interpersonal Self-concepts, and Paranoia in Schizophrenia—A Longitudinal Study

PubMed Central

Hesse, Klaus; Kriston, Levente; Mehl, Stephanie; Wittorf, Andreas; Wiedemann, Wolfgang; Wölwer, Wolfgang; Klingberg, Stefan

2015-01-01

Recent cognitive models of paranoid delusions highlight the role of self-concepts in the development and maintenance of paranoia. Evidence is growing that especially interpersonal self-concepts are relevant in the genesis of paranoia. In addition, negative interpersonal life-experiences are supposed to influence the course of paranoia. As dysfunctional family atmosphere corresponds with multiple distressing dyadic experiences, it could be a risk factor for the development and maintenance of paranoia. A total of 160 patients with a diagnosis of schizophrenia were assessed twice within 12 months. Standardized questionnaires and symptom rating scales were used to measure interpersonal self-concepts, perceived family atmosphere, and paranoia. Data were analyzed using longitudinal cross-lagged structural equation models. Perceived negative family atmosphere was associated with the development of more pronounced negative interpersonal self-concepts 12 months later. Moreover, paranoia was related to negative family atmosphere after 12 months as well. As tests revealed that reversed associations were not able to explain the data, we found evidence for a vicious cycle between paranoia, family atmosphere, and interpersonal self-concepts as suggested by theoretical/cognitive model of paranoid delusions. Results suggest that broader interventions for patients and their caretakers that aim at improving family atmosphere might also be able to improve negative self-concepts and paranoia. PMID:25925392

Time series analysis of monthly pulpwood use in the Northeast

Treesearch

James T. Bones

1980-01-01

Time series analysis was used to develop a model that depicts pulpwood use in the Northeast. The model is useful in forecasting future pulpwood requirements (short term) or monitoring pulpwood-use activity in relation to past use patterns. The model predicted a downturn in use during 1980.

Deficits in working memory and motor performance in the APP/PS1ki mouse model for Alzheimer's disease.

PubMed

Wirths, Oliver; Breyhan, Henning; Schäfer, Stephanie; Roth, Christian; Bayer, Thomas A

2008-06-01

The APP/PS1ki mouse model for Alzheimer's disease (AD) exhibits robust brain and spinal cord axonal degeneration and hippocampal CA1 neuron loss starting at 6 months of age. It expresses human mutant APP751 with the Swedish and London mutations together with two FAD-linked knocked-in mutations (PS1 M233T and PS1 L235P) in the murine PS1 gene. The present report covers a phenotypical analysis of this model using either behavioral tests for working memory and motor performance, as well as an analysis of weight development and body shape. At the age of 6 months, a dramatic, age-dependent change in all of these properties and characteristics was observed, accompanied by a significantly reduced ability to perform working memory and motor tasks. The APP/PS1ki mice were smaller and showed development of a thoracolumbar kyphosis, together with an incremental loss of body weight. While 2-month-old APP/PS1ki mice were inconspicuous in all of these tasks and properties, there is a massive age-related impairment in all tested behavioral paradigms. We have previously reported robust axonal degeneration in brain and spinal cord, as well as abundant hippocampal CA1 neuron loss starting at 6 months of age in the APP/PS1ki mouse model, which coincides with the onset of motor and memory deficits described in the present report.

Moderate Traumatic Brain Injury: Clinical Characteristics and a Prognostic Model of 12-Month Outcome.

PubMed

Einarsen, Cathrine Elisabeth; van der Naalt, Joukje; Jacobs, Bram; Follestad, Turid; Moen, Kent Gøran; Vik, Anne; Håberg, Asta Kristine; Skandsen, Toril

2018-06-01

Patients with moderate traumatic brain injury (TBI) often are studied together with patients with severe TBI, even though the expected outcome of the former is better. Therefore, we aimed to describe patient characteristics and 12-month outcomes, and to develop a prognostic model based on admission data, specifically for patients with moderate TBI. Patients with Glasgow Coma Scale scores of 9-13 and age ≥16 years were prospectively enrolled in 2 level I trauma centers in Europe. Glasgow Outcome Scale Extended (GOSE) score was assessed at 12 months. A prognostic model predicting moderate disability or worse (GOSE score ≤6), as opposed to a good recovery, was fitted by penalized regression. Model performance was evaluated by area under the curve of the receiver operating characteristics curves. Of the 395 enrolled patients, 81% had intracranial lesions on head computed tomography, and 71% were admitted to an intensive care unit. At 12 months, 44% were moderately disabled or worse (GOSE score ≤6), whereas 8% were severely disabled and 6% died (GOSE score ≤4). Older age, lower Glasgow Coma Scale score, no day-of-injury alcohol intoxication, presence of a subdural hematoma, occurrence of hypoxia and/or hypotension, and preinjury disability were significant predictors of GOSE score ≤6 (area under the curve = 0.80). Patients with moderate TBI exhibit characteristics of significant brain injury. Although few patients died or experienced severe disability, 44% did not experience good recovery, indicating that follow-up is needed. The model is a first step in development of prognostic models for moderate TBI that are valid across centers. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Children’s Negative Emotions and Ego-Resiliency: Longitudinal Relations With Social Competence

PubMed Central

Taylor, Zoe E.; Eisenberg, Nancy; VanSchyndel, Sarah K.; Eggum-Wilkens, Natalie D.; Spinrad, Tracy L.

2015-01-01

We examined the relations of negative emotions in toddlerhood to the development of ego-resiliency and social competence across early childhood. Specifically, we addressed whether fear and anger/frustration in 30-month-old children (N = 213) was associated with the development of ego-resiliency across 4 time points (42 to 84 months), and, in turn, whether ego-resiliency predicted social competence at 84 months. Child anger/frustration negatively predicted the intercept of ego-resiliency at 42 months (controlling for prior ego-resiliency at 18 months) as well as the slope. Fear did not significantly predict either the intercept or slope of ego-resiliency in the structural model, although it was positively correlated with anger/frustration and was negatively related to ego-resiliency in zero-order correlations. The slope of ego-resiliency was positively related to children’s social competence at 84 months; however, the intercept of ego-resiliency (set at 42 months) was not a significant predictor of later social competence. Furthermore, the slope of ego-resiliency mediated the relations between anger/frustration and children’s later social competence. The results suggest that individual differences in anger/frustration might contribute to the development of ego-resiliency, which, in turn, is associated with children’s social competence. PMID:24364850

Development and validation of PediaTrac™: A web-based tool to track developing infants.

PubMed

Lajiness-O'Neill, Renée; Brooks, Judith; Lukomski, Angela; Schilling, Stephen; Huth-Bocks, Alissa; Warschausky, Seth; Flores, Ana-Mercedes; Swick, Casey; Nyman, Tristin; Andersen, Tiffany; Morris, Natalie; Schmitt, Thomas A; Bell-Smith, Jennifer; Moir, Barbara; Hodges, Elise K; Lyddy, James E

2018-02-01

PediaTrac™, a 363-item web-based tool to track infant development, administered in modules of ∼40-items per sampling period, newborn (NB), 2--, 4--, 6--, 9-- and 12--months was validated. Caregivers answered demographic, medical, and environmental questions, and questions covering the sensorimotor, feeding/eating, sleep, speech/language, cognition, social-emotional, and attachment domains. Expert Panel Reviews and Cognitive Interviews (CI) were conducted to validate the item bank. Classical Test Theory (CTT) and Item Response Theory (IRT) methods were employed to examine the dimensionality and psychometric properties of PediaTrac with pooled longitudinal and cross-sectional cohorts (N = 132). Intraclass correlation coefficients (ICC) for the Expert Panel Review revealed moderate agreement at 6 -months and good reliability at other sampling periods. ICC estimates for CI revealed moderate reliability regarding clarity of the items at NB and 4 months, good reliability at 2--, 9-- and 12--months and excellent reliability at 6 -months. CTT revealed good coefficient alpha estimates (α ≥ 0.77 for five of the six ages) for the Social-Emotional/Communication, Attachment (α ≥ 0.89 for all ages), and Sensorimotor (α ≥ 0.75 at 6-months) domains, revealing the need for better targeting of sensorimotor items. IRT modeling revealed good reliability (r = 0.85-0.95) for three distinct domains (Feeding/Eating, Social-Emotional/Communication and Attachment) and four subdomains (Feeding Breast/Formula, Feeding Solid Food, Social-Emotional Information Processing, Communication/Cognition). Convergent and discriminant construct validity were demonstrated between our IRT-modeled domains and constructs derived from existing developmental, behavioral and caregiver measures. Our Attachment domain was significantly correlated with existing measures at the NB and 2-month periods, while the Social-Emotional/Communication domain was highly correlated with similar constructs at the 6-, 9- and 12-month periods. PediaTrac has potential for producing novel and effective estimates of infant development via the Sensorimotor, Feeding/Eating, Social-Emotional/Communication and Attachment domains. Copyright © 2018 Elsevier Inc. All rights reserved.

Long-term prediction of fish growth under varying ambient temperature using a multiscale dynamic model

PubMed Central

2009-01-01

Background Feed composition has a large impact on the growth of animals, particularly marine fish. We have developed a quantitative dynamic model that can predict the growth and body composition of marine fish for a given feed composition over a timespan of several months. The model takes into consideration the effects of environmental factors, particularly temperature, on growth, and it incorporates detailed kinetics describing the main metabolic processes (protein, lipid, and central metabolism) known to play major roles in growth and body composition. Results For validation, we compared our model's predictions with the results of several experimental studies. We showed that the model gives reliable predictions of growth, nutrient utilization (including amino acid retention), and body composition over a timespan of several months, longer than most of the previously developed predictive models. Conclusion We demonstrate that, despite the difficulties involved, multiscale models in biology can yield reasonable and useful results. The model predictions are reliable over several timescales and in the presence of strong temperature fluctuations, which are crucial factors for modeling marine organism growth. The model provides important improvements over existing models. PMID:19903354

The RenTg mice: a powerful tool to study renin-dependent chronic kidney disease.

PubMed

Huby, Anne-Cecile; Kavvadas, Panagiotis; Alfieri, Carlo; Abed, Ahmed; Toubas, Julie; Rastaldi, Maria-Pia; Dussaule, Jean-Claude; Chatziantoniou, Christos; Chadjichristos, Christos E

2012-01-01

Several studies have shown that activation of the renin-angiotensin system may lead to hypertension, a major risk factor for the development of chronic kidney disease (CKD). The existing hypertension-induced CDK mouse models are quite fast and consequently away from the human pathology. Thus, there is an urgent need for a mouse model that can be used to delineate the pathogenic process leading to progressive renal disease. The objective of this study was dual: to investigate whether mice overexpressing renin could mimic the kinetics and the physiopathological characteristics of hypertension-induced renal disease and to identify cellular and/or molecular events characterizing the different steps of the progression of CKD. We used a novel transgenic strain, the RenTg mice harboring a genetically clamped renin transgene. At 3 months, heterozygous mice are hypertensive and slightly albuminuric. The expression of adhesion markers such as vascular cell adhesion molecule-1 and platelet endothelial cell adhesion molecule-1 are increased in the renal vasculature indicating initiation of endothelial dysfunction. At 5 months, perivascular and periglomerular infiltrations of macrophages are observed. These early renal vascular events are followed at 8 months by leukocyte invasion, decreased expression of nephrin, increased expression of KIM-1, a typical protein of tubular cell stress, and of several pro-fibrotic agents of the TGFβ family. At 12 months, mice display characteristic structural alterations of hypertensive renal disease such as glomerular ischemia, glomerulo- and nephroangio-sclerosis, mesangial expansion and tubular dilation. The RenTg strain develops CKD progressively. In this model, endothelial dysfunction is an early event preceding the structural and fibrotic alterations which ultimately lead to the development of CKD. This model can provide new insights into the mechanisms of chronic renal failure and help to identify new targets for arresting and/or reversing the development of the disease.

Comparison of simulation modeling and satellite techniques for monitoring ecological processes

NASA Technical Reports Server (NTRS)

Box, Elgene O.

1988-01-01

In 1985 improvements were made in the world climatic data base for modeling and predictive mapping; in individual process models and the overall carbon-balance models; and in the interface software for mapping the simulation results. Statistical analysis of the data base was begun. In 1986 mapping was shifted to NASA-Goddard. The initial approach involving pattern comparisons was modified to a more statistical approach. A major accomplishment was the expansion and improvement of a global data base of measurements of biomass and primary production, to complement the simulation data. The main accomplishments during 1987 included: production of a master tape with all environmental and satellite data and model results for the 1600 sites; development of a complete mapping system used for the initial color maps comparing annual and monthly patterns of Normalized Difference Vegetation Index (NDVI), actual evapotranspiration, net primary productivity, gross primary productivity, and net ecosystem production; collection of more biosphere measurements for eventual improvement of the biological models; and development of some initial monthly models for primary productivity, based on satellite data.

Modeling the seasonal circulation in Massachusetts Bay

USGS Publications Warehouse

Signell, Richard P.; Jenter, Harry L.; Blumberg, Alan F.; ,

1994-01-01

An 18 month simulation of circulation was conducted in Massachusetts Bay, a roughly 35 m deep, 100??50 km embayment on the northeastern shelf of the United States. Using a variant of the Blumberg-Mellor (1987) model, it was found that a continuous 18 month run was only possible if the velocity field was Shapiro filtered to remove two grid length energy that developed along the open boundary due to mismatch in locally generated and climatologically forced water properties. The seasonal development of temperature and salinity stratification was well-represented by the model once ??-coordinate errors were reduced by subtracting domain averaged vertical profiles of temperature, salinity and density before horizontal differencing was performed. Comparison of modeled and observed subtidal currents at fixed locations revealed that the model performance varies strongly with season and distance from the open boundaries. The model performs best during unstratified conditions, and in the interior of the bay. The model performs poorest during stratified conditions and in the regions where the bay is driven predominantly by remote fluctuations from the Gulf of Maine.

Prostate and mammary adenocarcinoma in transgenic mice carrying a rat C3(1) simian virus 40 large tumor antigen fusion gene.

PubMed Central

Maroulakou, I G; Anver, M; Garrett, L; Green, J E

1994-01-01

A transgenic mouse model for prostate and mammary cancer has been developed in mice containing a recombinant gene expressing the simian virus 40 early-region transforming sequences under the regulatory control of the rat prostatic steroid binding protein [C3(1)] gene. Male transgenic mice develop prostatic hyperplasia in early life that progresses to adenoma or adenocarcinoma in most animals surviving to longer than 7 months of age. Prostate cancer metastases to lung have been observed. Female animals from the same founder lines generally develop mammary hyperplasia by 3 months of age with subsequent development of mammary adenocarcinoma by 6 months of age in 100% of the animals. The development of tumors correlates with the expression of the transgene as determined by Northern blot and immunohistochemical analyses. The results of these experiments demonstrate that the C3(1) regulatory region used in these experiments is useful for targeting expression to the prostate and mammary gland. To our knowledge, this experimental system is the first reported transgenic mouse model for prostate cancer. These transgenic animals offer the opportunity to study hormone response elements in vivo and the multistage progression from normal tissue to carcinoma in the prostate and mammary glands. Images PMID:7972041

Outcomes of Embedded Care Management in a Family Medicine Residency Patient-Centered Medical Home.

PubMed

Newman, Robert J; Bikowski, Richard; Nakayama, Kristy; Cunningham, Tina; Acker, Pam; Bradshaw, Dana

2017-01-01

Much attention is devoted nationally to preventing hospital readmissions and emergency department (ED) use, given the high cost of this care. There is a growing body of evidence from the Patient Centered Primary Care Collaborative that a patient-centered medical home (PCMH) model successfully lowers these costs. Our study evaluates a specific intervention in a family medicine residency PCMH to decrease readmissions and ED utilization using an embedded care manager. The Department of Family and Community Medicine at Eastern Virginia Medical School in Norfolk, VA, hired an RN care manager in May of 2013 with a well-defined job description focused on decreasing hospital readmissions and ED usage. Our primary outcomes for the study were number of monthly hospital admissions and readmissions over 23 months and monthly ED visits over 20 months. Readmission rates averaged 22.2% per month in the first year of the intervention and 18.3% in the second year, a statistically significant 3.9% decrease. ED visits averaged 176 per month in the first year and 146 per month in the second year, a statistically significant 17% reduction. Our study adds to the evidence that a PCMH model of care with an embedded RN care manager can favorably lower readmission rates and ED utilization in a family medicine residency practice. Developing a viable business model to support this important work remains a challenge.

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

Yamankaradeniz, R.; Horuz, I.

In this study, the characteristics of solar assisted heat pump are investigated theoretically and experimentally for clear days during the seven months of the winter season in Istanbul/Turkey. A theoretical model was developed and a computer program was written on this basis. The characteristics such as: daily average collector efficiency and solar radiation, monthly average heat transfer at the condenser, monthly average cooling capacity, the mean COP and the mean COP for total system were examined. The theoretical results were found to be in good agreement with the experimental values.

Application of thermochemical modeling to aircraft interior polymeric materials

DOT National Transportation Integrated Search

1982-06-01

This report summarizes the results from a twelve-month study of the feasibility of applying certain basic concepts in the thermochemical modeling to aircraft cabin fire safety. The concepts developed earlier on a NASA-sponsored program were applied t...

The Progressive BSSG Rat Model of Parkinson's: Recapitulating Multiple Key Features of the Human Disease

PubMed Central

Van Kampen, Jackalina M.; Baranowski, David C.; Robertson, Harold A.; Shaw, Christopher A.; Kay, Denis G.

2015-01-01

The development of effective neuroprotective therapies for Parkinson's disease (PD) has been severely hindered by the notable lack of an appropriate animal model for preclinical screening. Indeed, most models currently available are either acute in nature or fail to recapitulate all characteristic features of the disease. Here, we present a novel progressive model of PD, with behavioural and cellular features that closely approximate those observed in patients. Chronic exposure to dietary phytosterol glucosides has been found to be neurotoxic. When fed to rats, β-sitosterol β-d-glucoside (BSSG) triggers the progressive development of parkinsonism, with clinical signs and histopathology beginning to appear following cessation of exposure to the neurotoxic insult and continuing to develop over several months. Here, we characterize the progressive nature of this model, its non-motor features, the anatomical spread of synucleinopathy, and response to levodopa administration. In Sprague Dawley rats, chronic BSSG feeding for 4 months triggered the progressive development of a parkinsonian phenotype and pathological events that evolved slowly over time, with neuronal loss beginning only after toxin exposure was terminated. At approximately 3 months following initiation of BSSG exposure, animals displayed the early emergence of an olfactory deficit, in the absence of significant dopaminergic nigral cell loss or locomotor deficits. Locomotor deficits developed gradually over time, initially appearing as locomotor asymmetry and developing into akinesia/bradykinesia, which was reversed by levodopa treatment. Late-stage cognitive impairment was observed in the form of spatial working memory deficits, as assessed by the radial arm maze. In addition to the progressive loss of TH+ cells in the substantia nigra, the appearance of proteinase K-resistant intracellular α-synuclein aggregates was also observed to develop progressively, appearing first in the olfactory bulb, then the striatum, the substantia nigra and, finally, hippocampal and cortical regions. The slowly progressive nature of this model, together with its construct, face and predictive validity, make it ideal for the screening of potential neuroprotective therapies for the treatment of PD. PMID:26439489

Cumulative Risk Disparities in Children's Neurocognitive Functioning: A Developmental Cascade Model

ERIC Educational Resources Information Center

Wade, Mark; Browne, Dillon T.; Plamondon, Andre; Daniel, Ella; Jenkins, Jennifer M.

2016-01-01

The current longitudinal study examined the role of cumulative social risk on children's theory of mind (ToM) and executive functioning (EF) across early development. Further, we also tested a cascade model of development in which children's social cognition at 18 months was hypothesized to predict ToM and EF at age 4.5 through intermediary…

Gradual Phenotype Development in Huntington Disease Transgenic Minipig Model at 24 Months of Age.

PubMed

Vidinská, Daniela; Vochozková, Petra; Šmatlíková, Petra; Ardan, Taras; Klíma, Jiří; Juhás, Štefan; Juhásová, Jana; Bohuslavová, Božena; Baxa, Monika; Valeková, Ivona; Motlík, Jan; Ellederová, Zdenka

2018-06-05

Huntington disease (HD) is an incurable neurodegenerative disease caused by the expansion of a polyglutamine sequence in a gene encoding the huntingtin (Htt) protein, which is expressed in almost all cells of the body. In addition to small animal models, new therapeutic approaches (including gene therapy) require large animal models as their large brains are a more realistic model for translational research. In this study, we describe phenotype development in transgenic minipigs (TgHD) expressing the N-terminal part of mutated human Htt at the age of 24 months. TgHD and wild-type littermates were compared. Western blot analysis and subcellular fractionation of different tissues was used to determine the fragmentation of Htt. Immunohistochemistry and optical analysis of coronal sections measuring aggregates, Htt expression, neuroinflammation, and myelination was applied. Furthermore, the expression of Golgi protein acyl-CoA binding domain containing 3 (ACBD3) was analyzed. We found age-correlated Htt fragmentation in the brain. Among various tissues studied, the testes displayed the highest fragmentation, with Htt fragments detectable even in cell nuclei. Also, Golgi protein ACBD3 was upregulated in testes, which is in agreement with previously reported testicular degeneration in TgHD minipigs. Nevertheless, the TgHD-specific mutated Htt fragments were also present in the cytoplasm of striatum and cortex cells. Moreover, microglial cells were activated and myelination was slightly decreased, suggesting the development of a premanifest stage of neurodegeneration in TgHD minipigs. The gradual development of a neurodegenerative phenotype, ac-companied with testicular degeneration, is observed in 24- month-old TgHD minipigs. © 2018 S. Karger AG, Basel.

Dynamic Models of Learning That Characterize Parent-Child Exchanges Predict Vocabulary Growth

ERIC Educational Resources Information Center

Ober, David R.; Beekman, John A.

2016-01-01

Cumulative vocabulary models for infants and toddlers were developed from models of learning that predict trajectories associated with low, average, and high vocabulary growth rates (14 to 46 months). It was hypothesized that models derived from rates of learning mirror the type of exchanges provided to infants and toddlers by parents and…

The Bridges SOI Model School Program at Palo Verde School, Palo Verde, Arizona.

ERIC Educational Resources Information Center

Stock, William A.; DiSalvo, Pamela M.

The Bridges SOI Model School Program is an educational service based upon the SOI (Structure of Intellect) Model School curriculum. For the middle seven months of the academic year, all students in the program complete brief daily exercises that develop specific cognitive skills delineated in the SOI model. Additionally, intensive individual…

Cognitive Mediation of Rape's Mental Health Impact: Constructive Replication of a Cross-Sectional Model in Longitudinal Data

ERIC Educational Resources Information Center

Koss, Mary P.; Figueredo, Aurelio Jose

2004-01-01

The constructive replication of a prespecified, cognitively mediated model of rape's impact on psychosocial health is reported using longitudinal data (see Koss, Figueredo, & Prince, 2002, for a summary of model development). Rape survivors (n= 59) were assessed four times, 3 to 24 months postrape. Structural equations modeling of baseline data…

77 FR 76311 - Self-Regulatory Organizations; Fixed Income Clearing Corporation; Notice of Filing of Advance...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-27

... the Advance Notice FICC is proposing to replace the prepayment model component (``Prepayment Model... calculations. The cash flow of a TBA CUSIP is the sum of all discounted future monthly cash flows. The future... prepayment model developed by the Office of Thrift Supervision (``OTS''); this particular model is no longer...

Developmental Changes in Early Comprehension and Production of Drawings: Evidence From Two Socioeconomic Backgrounds.

PubMed

Salsa, Analía M; Vivaldi, Romina

2017-01-01

Two studies examined young children's comprehension and production of representational drawings across and within 2 socioeconomic strata (SES). Participants were 130 middle-SES (MSES) and low-SES (LSES) Argentine children, from 30 to 60 months old, given a task with 2 phases, production and comprehension. The production phase assessed free drawing and drawings from simple 3-dimensional objects (model drawing); the comprehension phase assessed children's understanding of an adult's line drawings of the objects. MSES children solved the comprehension phase of the task within the studied age range; representational production emerged first in model drawing (42 months) and later in free drawing (48 months). The same developmental pathway was observed in LSES children but with a clear asynchrony in the age of onset of comprehension and production: Children understood the symbolic nature of drawings at 42 months old and the first representational drawings were found at 60 months old. These results provide empirical evidence that support the crucial influence of social experiences by organizing and constraining graphic development.

Impact of meteorological changes on the incidence of scarlet fever in Hefei City, China

NASA Astrophysics Data System (ADS)

Duan, Yu; Huang, Xiao-lei; Wang, Yu-jie; Zhang, Jun-qing; Zhang, Qi; Dang, Yue-wen; Wang, Jing

2016-10-01

Studies on scarlet fever with meteorological factors included were few. We aimed to illustrate meteorological factors' effects on monthly incidence of scarlet fever. Cases of scarlet fever were collected from the report of legal infectious disease in Hefei City from 1985 to 2006; the meteorological data were obtained from the weather bureau of Hefei City. Monthly incidence and corresponding meteorological data in these 22 years were used to develop the model. The model of auto regressive integrated moving average with covariates was used in statistical analyses. There was a highest peak from March to June and a small peak from November to January. The incidence of scarlet fever ranges from 0 to 0.71502 (per 105 population). SARIMAX (1,0,0)(1,0,0)12 model was fitted with monthly incidence and meteorological data optimally. It was shown that relative humidity ( β = -0.002, p = 0.020), mean temperature ( β = 0.006, p = 0.004), and 1 month lag minimum temperature ( β = -0.007, p < 0.001) had effect on the incidence of scarlet fever in Hefei. Besides, the incidence in a previous month (AR( β) = 0.469, p < 0.001) and in 12 months before (SAR( β) = 0.255, p < 0.001) was positively associated with the incidence. This study shows that scarlet fever incidence was negatively associated with monthly minimum temperature and relative humidity while was positively associated with mean temperature in Hefei City, China. Besides, the ARIMA model could be useful not only for prediction but also for the analysis of multiple correlations.

Monthly streamflow forecasting with auto-regressive integrated moving average

NASA Astrophysics Data System (ADS)

Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

2017-09-01

Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

Soil and climate modelling to explain soil differences in MIS5e and MIS13 on the Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Finke, P. A.; Yu, Y.; Yin, Q.; Bernardini, N. J.

2016-12-01

Objective Proxy records indicate that MIS5 (about 120 ka ago) was warmer than MIS13 (about 500 ka ago). Nevertheless, MIS13-soils in the Chinese loess plateau (105 -115°E and 30-40°N) are stronger developed than MIS5-soils. This has been attributed to a stronger East Asian summer monsoon. Other differences are interglacial lengths and loess deposition rates. We aimed to find explanations for soil development differences by using a soil formation model (SoilGen) with climatic inputs obtained from an earth system model (LOVECLIM). Material and Methods The LOVECLIM model is driven by time-varying insolation and greenhouse gas concentrations and was run to give monthly values for temperature, precipitation and evaporation as well the dominant vegetation type. Model results for were corrected for systematic differences between present-day observation data and simulation. Reconstructions were made for both interglacials of the amount of inblown loess, and the mineralogy and grain size distribution of the initial loess as well as the dust. These data were fed into the SoilGen model, which was used to calculate various soil parameters with depth and over time. Results Simulations show a stronger developed MIS13 soil, in terms of weathering (loss of anorthite), and redistribution of calcite, gypsum and clay. This corresponds to observed paleosoils. MIS13-soils are more leached. As simulated temperatures and annual precipitation between MIS5 and MIS13 did not vary strongly, the greater length of MIS13 seemed the main explanation for the stronger leaching and weathering. Closer analysis however showed a larger number of months in MIS13 with a precipitation surplus, even when only considering the first 22 ka. Only in such months significant leaching can occur. Conclusion Using simulation models it was demonstrated that the stronger soil expression in MIS13 than in MIS5 is likely caused by more months with a precipitation surplus, in combination with a longer duration of MIS13.

Experiments of reconstructing discrete atmospheric dynamic models from data (I)

NASA Astrophysics Data System (ADS)

Lin, Zhenshan; Zhu, Yanyu; Deng, Ziwang

1995-03-01

In this paper, we give some experimental results of our study in reconstructing discrete atmospheric dynamic models from data. After a great deal of numerical experiments, we found that the logistic map, x n + 1 = 1- μx {2/n}, could be used in monthly mean temperature prediction when it was approaching the chaotic region, and its predictive results were in reverse states to the practical data. This means that the nonlinear developing behavior of the monthly mean temperature system is bifurcating back into the critical chaotic states from the chaotic ones.

Development of injury in a rat model of chronic renal allograft rejection: effect of dietary protein restriction.

PubMed

Bombas, A; Stein-Oakley, A N; Baxter, K; Thomson, N M; Jablonski, P

1999-01-01

Non-allogeneic factors such as increased nephron "workload" may contribute to chronic renal allograft rejection. Reducing dietary protein from 20% to 8% was tested in a model of chronic rejection: Dark Agouti kidney to Albino Surgery recipient, "tolerised" by previous donor blood transfusions. Survival, weight gain, serum creatinine concentration and creatinine clearance were similar for both groups at all times. Urinary protein was significantly (P < 0.05) lower in the low-protein (LP) group 1 month after transplantation. After 3 and 6 months, both groups demonstrated mild chronic rejection. After 6 months, tubular atrophy was significantly (P < 0.05) less in the LP group and interstitial fibrosis was marginally reduced. Glomerular hypertrophy, glomerular sclerosis, tubular dilatation, leucocyte infiltration, adhesion molecule expression and TGF-beta1 mRNA expression were similarly increased in both groups. Thus, reducing dietary protein to 8% lowered urinary protein, but did not significantly affect the development of chronic rejection in renal allografts beyond affording a degree of protection from tubulointerstitial damage.

Longitudinal in vivo muscle function analysis of the DMSXL mouse model of myotonic dystrophy type 1.

PubMed

Decostre, Valérie; Vignaud, Alban; Matot, Béatrice; Huguet, Aline; Ledoux, Isabelle; Bertil, Emilie; Gjata, Bernard; Carlier, Pierre G; Gourdon, Geneviève; Hogrel, Jean-Yves

2013-12-01

Myotonic dystrophy is the most common adult muscle dystrophy. In view of emerging therapies, which use animal models as a proof of principle, the development of reliable outcome measures for in vivo longitudinal study of mouse skeletal muscle function is becoming crucial. To satisfy this need, we have developed a device to measure ankle dorsi- and plantarflexion torque in rodents. We present an in vivo 8-month longitudinal study of the contractile properties of the skeletal muscles of the DMSXL mouse model of myotonic dystrophy type 1. Between 4 and 12 months of age, we observed a reduction in muscle strength in the ankle dorsi- and plantarflexors of DMSXL compared to control mice although the strength per muscle cross-section was normal. Mild steady myotonia but no abnormal muscle fatigue was also observed in the DMSXL mice. Magnetic resonance imaging and histological analysis performed at the end of the study showed respectively reduced muscle cross-section area and smaller muscle fibre diameter in DMSXL mice. In conclusion, our study demonstrates the feasibility of carrying out longitudinal in vivo studies of muscle function over several months in a mouse model of myotonic dystrophy confirming the feasibility of this method to test preclinical therapeutics. Copyright © 2013 Elsevier B.V. All rights reserved.

Time series analysis of malaria in Afghanistan: using ARIMA models to predict future trends in incidence.

PubMed

Anwar, Mohammad Y; Lewnard, Joseph A; Parikh, Sunil; Pitzer, Virginia E

2016-11-22

Malaria remains endemic in Afghanistan. National control and prevention strategies would be greatly enhanced through a better ability to forecast future trends in disease incidence. It is, therefore, of interest to develop a predictive tool for malaria patterns based on the current passive and affordable surveillance system in this resource-limited region. This study employs data from Ministry of Public Health monthly reports from January 2005 to September 2015. Malaria incidence in Afghanistan was forecasted using autoregressive integrated moving average (ARIMA) models in order to build a predictive tool for malaria surveillance. Environmental and climate data were incorporated to assess whether they improve predictive power of models. Two models were identified, each appropriate for different time horizons. For near-term forecasts, malaria incidence can be predicted based on the number of cases in the four previous months and 12 months prior (Model 1); for longer-term prediction, malaria incidence can be predicted using the rates 1 and 12 months prior (Model 2). Next, climate and environmental variables were incorporated to assess whether the predictive power of proposed models could be improved. Enhanced vegetation index was found to have increased the predictive accuracy of longer-term forecasts. Results indicate ARIMA models can be applied to forecast malaria patterns in Afghanistan, complementing current surveillance systems. The models provide a means to better understand malaria dynamics in a resource-limited context with minimal data input, yielding forecasts that can be used for public health planning at the national level.

Scaffolding, Analysis and Materials: Contributing Factors in an Unexpected Finding of Advanced Infant/Toddler Pretend Play?

ERIC Educational Resources Information Center

Morrissey, Anne-Marie

2014-01-01

As part of a longitudinal study, infant/toddler pretend play development and maternal play modelling were investigated in dyadic context. A total of 21 children were videotaped in monthly play sessions with their mothers, from age 8 to 17 months. Child and mother pretend play frequencies and levels were measured using Brown's Pretend Play…

The Development of the Classroom Social Climate during the First Months of the School Year

ERIC Educational Resources Information Center

Mainhard, M. Tim; Brekelmans, Mieke; den Brok, Perry; Wubbels, Theo

2011-01-01

In this study the mean stability of classroom social climates during the first months of the school year and the deviation of individual classrooms (N = 48) and students (N = 1208) from this general trend were investigated by taping students' interpersonal perceptions of their teachers. Multilevel growth modeling was used to identify the average…

Retention and clearance of inhaled ceramic fibres in rat lungs and development of a dissolution model.

PubMed Central

Yamato, H; Hori, H; Tanaka, I; Higashi, T; Morimoto, Y; Kido, M

1994-01-01

Male Wistar rats were exposed to aluminium silicate ceramic fibres by inhalation to study pulmonary deposition, clearance, and dissolution of the fibres. Rats were killed at one day, one month, three months, and six months after the termination of exposure. After exposure, fibres greater than 50 microns in length were seen with a scanning electron microscope in the alveolar region of the lung. Fibres were recovered from the lungs with a low temperature ashing technique and their number, diameter, and length were measured by scanning electron microscopy. The number of fibres remaining in the lungs declined exponentially with time after exposure and their silicon content also fell. The geometric median diameter of fibres decreased linearly with time. By six months after exposure, the surface of fibres recovered from the lungs had an eroded appearance. The results suggest that ceramic fibres are physically cleared from the lung and that they show signs of dissolution. Finally, the results were used to develop a theoretical model of fibre dissolution that gives a satisfactory fit to the experimental data. Images Figure 1 Figure 2 Figure 5 PMID:8199672

Developing Leaders for the 21st Century

ERIC Educational Resources Information Center

Phillips, John L.

2005-01-01

This article describes the Leadership Development for the 21st Century: Linking Research, Academics and Extension program that began in June 2005. This 12-month program, designed to explore different models of leadership, develop peer networks, and enhance skills and knowledge in leadership competencies, is specifically for land grand educators…

Self-assessment of Rheumatoid Arthritis Disease Activity Using a Smartphone Application. Development and 3-month Feasibility Study.

PubMed

Nishiguchi, S; Ito, H; Yamada, M; Yoshitomi, H; Furu, M; Ito, T; Shinohara, A; Ura, T; Okamoto, K; Aoyama, T; Tsuboyama, Tadao

2016-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Methodologies, Models and Algorithms for Patients Rehabilitation". Rheumatoid arthritis (RA) is a progressive inflammatory disease that causes damage to multiple joints, decline in functional status, and premature mortality. Thus, effective and frequent objective assessments are necessary. Then, we developed a self-assessment system for RA patients based on a smartphone application. The purpose of this study was to investigate the feasibility of a self-assessment system for RA patients using a smartphone application. We measured daily disease activity in nine RA patients who used the smartphone application for a period of three months. A disease activity score (DAS28) predictive model was used and feedback comments relating to disease activity were shown to patients via the smartphone application each day. To assess participants' RA disease activity, the DAS28 based on the C-reactive protein level was measured by a rheumatologist during monthly clinical visits. The disease activity measured by the application correlated well with the patients' actual disease activity during the 3-month period, as assessed by clinical examination. Furthermore, most participants gave favourable responses to a questionnaire administered at the end of the 3-month period containing questions relating to the ease of use and usefulness of the system. The results of this feasibility study indicated that the DAS28 predictive model can longitudinally predict DAS28 and may be an acceptable and useful tool for assessment of RA disease activity for both patients and healthcare providers.

Modeling erosion under future climates with the WEPP model

Treesearch

Timothy Bayley; William Elliot; Mark A. Nearing; D. Phillp Guertin; Thomas Johnson; David Goodrich; Dennis Flanagan

2010-01-01

The Water Erosion Prediction Project Climate Assessment Tool (WEPPCAT) was developed to be an easy-to-use, web-based erosion model that allows users to adjust climate inputs for user-specified climate scenarios. WEPPCAT allows the user to modify monthly mean climate parameters, including maximum and minimum temperatures, number of wet days, precipitation, and...

Potential impact of a maternal vaccine for RSV: A mathematical modelling study.

PubMed

Hogan, Alexandra B; Campbell, Patricia T; Blyth, Christopher C; Lim, Faye J; Fathima, Parveen; Davis, Stephanie; Moore, Hannah C; Glass, Kathryn

2017-10-27

Respiratory syncytial virus (RSV) is a major cause of respiratory morbidity and one of the main causes of hospitalisation in young children. While there is currently no licensed vaccine for RSV, a vaccine candidate for pregnant women is undergoing phase 3 trials. We developed a compartmental age-structured model for RSV transmission, validated using linked laboratory-confirmed RSV hospitalisation records for metropolitan Western Australia. We adapted the model to incorporate a maternal RSV vaccine, and estimated the expected reduction in RSV hospitalisations arising from such a program. The introduction of a vaccine was estimated to reduce RSV hospitalisations in Western Australia by 6-37% for 0-2month old children, and 30-46% for 3-5month old children, for a range of vaccine effectiveness levels. Our model shows that, provided a vaccine is demonstrated to extend protection against RSV disease beyond the first three months of life, a policy using a maternal RSV vaccine could be effective in reducing RSV hospitalisations in children up to six months of age, meeting the objective of a maternal vaccine in delaying an infant's first RSV infection to an age at which severe disease is less likely. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of Terrestrial Conditions and Dynamics

NASA Technical Reports Server (NTRS)

Goward, S. N.

1985-01-01

An ecological model is developed to estimate annual net primary productivity of vegetation in twelve major North American biomes. Three models are adapted and combined, each addressing a different factor known to govern primary productivity, i.e., photosynthesis, respiration, and moisture availability. Measures of intercepted photosynthetically active radiation (1PAR) for input to the photosynthesis model are derived from spectral vegetation index data. Normalized Difference Vegetation Index (NDVI) data are produced from NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) observations for April 1982 through March 1983. NDVI values are sampled from within the biomes at locations for which climatological data are available. Monthly estimates of Net Primary Productivity (NPP) for each sample location are generated and summed over the twelve month period. These monthly estimates are averaged to produce a single annual estimated NPP value for each biomes. Comparison of estimated NPP values with figures reported in the literature produces a correlation coefficient of 85.

Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America

NASA Astrophysics Data System (ADS)

dos Santos, T. S.; Mendes, D.; Torres, R. R.

2015-08-01

Several studies have been devoted to dynamic and statistical downscaling for analysis of both climate variability and climate change. This paper introduces an application of artificial neural networks (ANN) and multiple linear regression (MLR) by principal components to estimate rainfall in South America. This method is proposed for downscaling monthly precipitation time series over South America for three regions: the Amazon, Northeastern Brazil and the La Plata Basin, which is one of the regions of the planet that will be most affected by the climate change projected for the end of the 21st century. The downscaling models were developed and validated using CMIP5 model out- put and observed monthly precipitation. We used GCMs experiments for the 20th century (RCP Historical; 1970-1999) and two scenarios (RCP 2.6 and 8.5; 2070-2100). The model test results indicate that the ANN significantly outperforms the MLR downscaling of monthly precipitation variability.

Reduction of spatial distribution of risk factors for transportation of contaminants released by coal mining activities.

PubMed

Karan, Shivesh Kishore; Samadder, Sukha Ranjan

2016-09-15

It is reported that water-energy nexus composes two of the biggest development and human health challenges. In the present study we presented a Risk Potential Index (RPI) model which encapsulates Source, Vector (Transport), and Target risks for forecasting surface water contamination. The main aim of the model is to identify critical surface water risk zones for an open cast mining environment, taking Jharia Coalfield, India as the study area. The model also helps in feasible sampling design. Based on spatial analysis various risk zones were successfully delineated. Monthly RPI distribution revealed that the risk of surface water contamination was highest during the monsoon months. Surface water samples were analysed to validate the model. A GIS based alternative management option was proposed to reduce surface water contamination risk and observed 96% and 86% decrease in the spatial distribution of very high risk areas for the months June and July respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Time Series Analysis of Cholera in Matlab, Bangladesh, during 1988-2001

PubMed Central

Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-01-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab. PMID:23617200

Differential Susceptibility and the Early Development of Aggression: Interactive Effects of Respiratory Sinus Arrhythmia and Environmental Quality

PubMed Central

Eisenberg, Nancy; Sulik, Michael J.; Spinrad, Tracy L.; Edwards, Alison; Eggum, Natalie D.; Liew, Jeffrey; Sallquist, Julie; Popp, Tierney K.; Smith, Cynthia L.; Hart, Daniel

2012-01-01

The purpose of the current study was to predict the development of aggressive behavior from young children’s respiratory sinus arrhythmia (RSA) and environmental quality. In a longitudinal sample of 213 children, baseline RSA, RSA suppression in response to a film of crying babies, and a composite measure of environmental quality (incorporating socioeconomic status and marital adjustment) were measured, and parent-reported aggression was assessed from 18 to 54 months of age. Predictions based on biological sensitivity-to-context/differential susceptibility and diathesis-stress models, as well as potential moderation by child sex, were examined. The interaction of baseline RSA with environmental quality predicted the development (slope) and 54-month intercept of mothers’ reports of aggression. For girls only, the interaction between baseline RSA and environmental quality predicted the 18-month intercept of fathers’ reports. In general, significant negative relations between RSA and aggression were found primarily at high levels of environmental quality. In addition, we found a significant Sex × RSA interaction predicting the slope and 54-month intercept of fathers’ reports of aggression, such that RSA was negatively related to aggression for boys but not for girls. Contrary to predictions, no significant main effects or interactions were found for RSA suppression. The results provide mixed but not full support for differential susceptibility theory and provide little support for the diathesis-stress model. PMID:22182294

BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER’S DISEASE*

PubMed Central

Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G

2015-01-01

The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer’s disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer’s Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM. PMID:26900412

Seasonal variation of polycyclic aromatic hydrocarbons (PAHs) emissions in China.

PubMed

Zhang, Yanxu; Tao, Shu

2008-12-01

A regression model based on the provincial energy consumption data was developed to calculate the monthly proportions of residential energy consumption compared to the total year volume. This model was also validated by comparing with some survey and statistical data. With this model, a PAHs emission inventory with seasonal variation was developed. The seasonal variations of different sources in different regions of China and the spatial distribution of the major sources in different seasons were also achieved. The PAHs emissions were larger in the winter than in the summer, with a difference of about 1.3-folds between the months with the largest and the smallest emissions. Residential solid fuel combustion dominated the pattern of seasonal variation with the winter-time emissions as much as 1.6 times as that in the summer, while the emissions from wild fires and open fire straw burning was mainly concentrated during the spring and summer.

FY 1993 report on aluminum-nitrate testing at the ETF

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

Goodman, M.D.D.; Wise, M.D.

1993-09-30

This report summarizes the progress of the Aluminum Nitrate Nonhydrate (ANN) testing program at the F/H-Area Effluent Treatment Facility (ETF) for Fiscal Year 1993. Three tests were conducted in the months of February, April, and September. The tests yielded data that validated earlier conclusions that the addition of ANN to non-routine feed has a positive effect on the performance of ETF`s submicron filtration unit. Performance was observed to increase from 30--309%, depending on the season. The data also supports SRTC`s earlier conclusion that an optimal aluminum concentration exists in the range of 30--40 ppm, and concentrations above this range beginmore » to retard filtration performance. A rudimentary mathematical model that would predict Stage 1 flux was also developed during FY93. The model allowed for a more concise comparison of filter test runs, as well as increase the efficiency of the testing program by allowing shorter test runs to be conducted. It is postulated that the model can be further optimized to include aluminum concentration and time of year as independent variables that determine Stage 1 flux. Such a model should unequivocally prove the merits of pretreating ETF`s wastewater with aluminum nitrate. To proceed with the development of the model, further testing is proposed with stringent control of the aluminum concentration in the feed. In order to account for seasonal effects, one test should be conducted each month for Fiscal Year 1994. High Level Waste Engineering requests permission to conduct these test runs according to the following schedule: conduct tests in even numbered months beginning with October with routine influent as it is collected from normal process sewer influents and conduct tests in odd numbered months beginning with November with non-routine feed from H-Retention Basin.« less

Statistical modelling of software reliability

NASA Technical Reports Server (NTRS)

Miller, Douglas R.

1991-01-01

During the six-month period from 1 April 1991 to 30 September 1991 the following research papers in statistical modeling of software reliability appeared: (1) A Nonparametric Software Reliability Growth Model; (2) On the Use and the Performance of Software Reliability Growth Models; (3) Research and Development Issues in Software Reliability Engineering; (4) Special Issues on Software; and (5) Software Reliability and Safety.

Increased Accuracy in Statistical Seasonal Hurricane Forecasting

NASA Astrophysics Data System (ADS)

Nateghi, R.; Quiring, S. M.; Guikema, S. D.

2012-12-01

Hurricanes are among the costliest and most destructive natural hazards in the U.S. Accurate hurricane forecasts are crucial to optimal preparedness and mitigation decisions in the U.S. where 50 percent of the population lives within 50 miles of the coast. We developed a flexible statistical approach to forecast annual number of hurricanes in the Atlantic region during the hurricane season. Our model is based on the method of Random Forest and captures the complex relationship between hurricane activity and climatic conditions through careful variable selection, model testing and validation. We used the National Hurricane Center's Best Track hurricane data from 1949-2011 and sixty-one candidate climate descriptors to develop our model. The model includes information prior to the hurricane season, i.e., from the last three months of the previous year (Oct. through Dec.) and the first five months of the current year (January through May). Our forecast errors are substantially lower than other leading forecasts such as that of the National Oceanic and Atmospheric Administration (NOAA).

Model analysis of effects on water levels at Indiana Dunes National Lakeshore caused by construction dewatering

USGS Publications Warehouse

Marie, James R.

1976-01-01

The computer models were developed to investigate possible hydrologic effects within the Indiana Dunes National Lakeshore caused by planned dewatering at the adjacent Bailly Nuclear Generator construction site. The model analysis indicated that the planned dewatering would cause a drawdown of about 4 ft under the westernmost pond of the Lakeshore and that this drawdown would cause the pond to go almost dry--less than 0.5 ft of water remaining in about 1 percent of the pond--under average conditions during the 18-month dewatering period. When water levels are below average, as during late July and early August 1974, the pond would go dry in about 5.5 months. However, the pond may not have to go completely dry to damage the ecosystem. If the National Park Service 's independent study determines the minimum pond level at which ecosystem damage would be minimized, the models developed in this study could be used to predict the hydrologic conditions necessary to maintain that level. 

GRAM-86 - FOUR DIMENSIONAL GLOBAL REFERENCE ATMOSPHERE MODEL

NASA Technical Reports Server (NTRS)

Johnson, D.

1994-01-01

The Four-D Global Reference Atmosphere program was developed from an empirical atmospheric model which generates values for pressure, density, temperature, and winds from surface level to orbital altitudes. This program can be used to generate altitude profiles of atmospheric parameters along any simulated trajectory through the atmosphere. The program was developed for design applications in the Space Shuttle program, such as the simulation of external tank re-entry trajectories. Other potential applications would be global circulation and diffusion studies, and generating profiles for comparison with other atmospheric measurement techniques, such as satellite measured temperature profiles and infrasonic measurement of wind profiles. The program is an amalgamation of two empirical atmospheric models for the low (25km) and the high (90km) atmosphere, with a newly developed latitude-longitude dependent model for the middle atmosphere. The high atmospheric region above 115km is simulated entirely by the Jacchia (1970) model. The Jacchia program sections are in separate subroutines so that other thermosphericexospheric models could easily be adapted if required for special applications. The atmospheric region between 30km and 90km is simulated by a latitude-longitude dependent empirical model modification of the latitude dependent empirical model of Groves (1971). Between 90km and 115km a smooth transition between the modified Groves values and the Jacchia values is accomplished by a fairing technique. Below 25km the atmospheric parameters are computed by the 4-D worldwide atmospheric model of Spiegler and Fowler (1972). This data set is not included. Between 25km and 30km an interpolation scheme is used between the 4-D results and the modified Groves values. The output parameters consist of components for: (1) latitude, longitude, and altitude dependent monthly and annual means, (2) quasi-biennial oscillations (QBO), and (3) random perturbations to partially simulate the variability due to synoptic, diurnal, planetary wave, and gravity wave variations. Quasi-biennial and random variation perturbations are computed from parameters determined by various empirical studies and are added to the monthly mean values. The UNIVAC version of GRAM is written in UNIVAC FORTRAN and has been implemented on a UNIVAC 1110 under control of EXEC 8 with a central memory requirement of approximately 30K of 36 bit words. The GRAM program was developed in 1976 and GRAM-86 was released in 1986. The monthly data files were last updated in 1986. The DEC VAX version of GRAM is written in FORTRAN 77 and has been implemented on a DEC VAX 11/780 under control of VMS 4.X with a central memory requirement of approximately 100K of 8 bit bytes. The GRAM program was originally developed in 1976 and later converted to the VAX in 1986 (GRAM-86). The monthly data files were last updated in 1986.

Predicting summer residential electricity demand across the U.S.A using climate information

NASA Astrophysics Data System (ADS)

Sun, X.; Wang, S.; Lall, U.

2017-12-01

We developed a Bayesian Hierarchical model to predict monthly residential per capita electricity consumption at the state level across the USA using climate information. The summer period was selected since cooling requirements may be directly associated with electricity use, while for winter a mix of energy sources may be used to meet heating needs. Historical monthly electricity consumption data from 1990 to 2013 were used to build a predictive model with a set of corresponding climate and non-climate covariates. A clustering analysis was performed first to identify groups of states that had similar temporal patterns for the cooling degree days of each state. Then, a partial pooling model was applied to each cluster to assess the sensitivity of monthly per capita residential electricity demand to each predictor (including cooling-degree-days, gross domestic product (GDP) per capita, per capita electricity demand of previous month and previous year, and the residential electricity price). The sensitivity of residential electricity to cooling-degree-days has an identifiable geographic distribution with higher values in northeastern United States.

A method for estimating cost savings for population health management programs.

PubMed

Murphy, Shannon M E; McGready, John; Griswold, Michael E; Sylvia, Martha L

2013-04-01

To develop a quasi-experimental method for estimating Population Health Management (PHM) program savings that mitigates common sources of confounding, supports regular updates for continued program monitoring, and estimates model precision. Administrative, program, and claims records from January 2005 through June 2009. Data are aggregated by member and month. Study participants include chronically ill adult commercial health plan members. The intervention group consists of members currently enrolled in PHM, stratified by intensity level. Comparison groups include (1) members never enrolled, and (2) PHM participants not currently enrolled. Mixed model smoothing is employed to regress monthly medical costs on time (in months), a history of PHM enrollment, and monthly program enrollment by intensity level. Comparison group trends are used to estimate expected costs for intervention members. Savings are realized when PHM participants' costs are lower than expected. This method mitigates many of the limitations faced using traditional pre-post models for estimating PHM savings in an observational setting, supports replication for ongoing monitoring, and performs basic statistical inference. This method provides payers with a confident basis for making investment decisions. © Health Research and Educational Trust.

Intercomparison of Downscaling Methods on Hydrological Impact for Earth System Model of NE United States

NASA Astrophysics Data System (ADS)

Yang, P.; Fekete, B. M.; Rosenzweig, B.; Lengyel, F.; Vorosmarty, C. J.

2012-12-01

Atmospheric dynamics are essential inputs to Regional-scale Earth System Models (RESMs). Variables including surface air temperature, total precipitation, solar radiation, wind speed and humidity must be downscaled from coarse-resolution, global General Circulation Models (GCMs) to the high temporal and spatial resolution required for regional modeling. However, this downscaling procedure can be challenging due to the need to correct for bias from the GCM and to capture the spatiotemporal heterogeneity of the regional dynamics. In this study, the results obtained using several downscaling techniques and observational datasets were compared for a RESM of the Northeast Corridor of the United States. Previous efforts have enhanced GCM model outputs through bias correction using novel techniques. For example, the Climate Impact Research at Potsdam Institute developed a series of bias-corrected GCMs towards the next generation climate change scenarios (Schiermeier, 2012; Moss et al., 2010). Techniques to better represent the heterogeneity of climate variables have also been improved using statistical approaches (Maurer, 2008; Abatzoglou, 2011). For this study, four downscaling approaches to transform bias-corrected HADGEM2-ES Model output (daily at .5 x .5 degree) to the 3'*3'(longitude*latitude) daily and monthly resolution required for the Northeast RESM were compared: 1) Bilinear Interpolation, 2) Daily bias-corrected spatial downscaling (D-BCSD) with Gridded Meteorological Datasets (developed by Abazoglou 2011), 3) Monthly bias-corrected spatial disaggregation (M-BCSD) with CRU(Climate Research Unit) and 4) Dynamic Downscaling based on Weather Research and Forecast (WRF) model. Spatio-temporal analysis of the variability in precipitation was conducted over the study domain. Validation of the variables of different downscaling methods against observational datasets was carried out for assessment of the downscaled climate model outputs. The effects of using the different approaches to downscale atmospheric variables (specifically air temperature and precipitation) for use as inputs to the Water Balance Model (WBMPlus, Vorosmarty et al., 1998;Wisser et al., 2008) for simulation of daily discharge and monthly stream flow in the Northeast US for a 100-year period in the 21st century were also assessed. Statistical techniques especially monthly bias-corrected spatial disaggregation (M-BCSD) showed potential advantage among other methods for the daily discharge and monthly stream flow simulation. However, Dynamic Downscaling will provide important complements to the statistical approaches tested.

Perinatal stroke and the risk of developing childhood epilepsy

PubMed Central

Golomb, Meredith R.; Garg, Bhuwan P.; Carvalho, Karen S.; Johnson, Cynthia S.; Williams, Linda S.

2008-01-01

Objectives To describe the prevalence of epilepsy after 6 months-of-age in children with perinatal stroke and examine whether perinatal data predict epilepsy onset and resolution. Study design A retrospective review of 64 children with perinatal stroke. In children with at least 6 months of follow-up data, Kaplan-Meier curves, univariate log-rank tests, and Cox proportional hazards models were used to examine predictors of time to development of seizures, and time to resolution of seizures in children with epilepsy. The association of risk factors with the presence of epilepsy at any time after 6 months-of-age was examined using Fisher’s exact test. Results Forty-one of the 61 children with at least 6 months of follow-up data (67%) had epilepsy between 6 months-of-age and last follow-up, but in 13 of 41 seizures eventually resolved and anticonvulsants were discontinued. Infarct on prenatal ultrasound (p=0.0065) and family history of epilepsy (p=0.0093) were significantly associated with time to development of seizures after 6 months-of-age in the univariate analysis. No assessed variables were associated with time to resolution of epilepsy or with the presence of epilepsy after 6 months-of-age. Conclusions Childhood epilepsy is frequent after perinatal stroke. Evidence of infarction on prenatal ultrasound and a family history of epilepsy predict earlier onset of active seizures. PMID:17889079

Proposal for a New Predictive Model of Short-Term Mortality After Living Donor Liver Transplantation due to Acute Liver Failure.

PubMed

Chung, Hyun Sik; Lee, Yu Jung; Jo, Yun Sung

2017-02-21

BACKGROUND Acute liver failure (ALF) is known to be a rapidly progressive and fatal disease. Various models which could help to estimate the post-transplant outcome for ALF have been developed; however, none of them have been proved to be the definitive predictive model of accuracy. We suggest a new predictive model, and investigated which model has the highest predictive accuracy for the short-term outcome in patients who underwent living donor liver transplantation (LDLT) due to ALF. MATERIAL AND METHODS Data from a total 88 patients were collected retrospectively. King's College Hospital criteria (KCH), Child-Turcotte-Pugh (CTP) classification, and model for end-stage liver disease (MELD) score were calculated. Univariate analysis was performed, and then multivariate statistical adjustment for preoperative variables of ALF prognosis was performed. A new predictive model was developed, called the MELD conjugated serum phosphorus model (MELD-p). The individual diagnostic accuracy and cut-off value of models in predicting 3-month post-transplant mortality were evaluated using the area under the receiver operating characteristic curve (AUC). The difference in AUC between MELD-p and the other models was analyzed. The diagnostic improvement in MELD-p was assessed using the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS The MELD-p and MELD scores had high predictive accuracy (AUC >0.9). KCH and serum phosphorus had an acceptable predictive ability (AUC >0.7). The CTP classification failed to show discriminative accuracy in predicting 3-month post-transplant mortality. The difference in AUC between MELD-p and the other models had statistically significant associations with CTP and KCH. The cut-off value of MELD-p was 3.98 for predicting 3-month post-transplant mortality. The NRI was 9.9% and the IDI was 2.9%. CONCLUSIONS MELD-p score can predict 3-month post-transplant mortality better than other scoring systems after LDLT due to ALF. The recommended cut-off value of MELD-p is 3.98.

High Spatial Resolution Forecasting of Long-Term Monthly Precipitation and Mean Temperature Trends in Data Scarce Regions

NASA Astrophysics Data System (ADS)

Mosier, T. M.; Hill, D. F.; Sharp, K. V.

2013-12-01

High spatial resolution time-series data are critical for many hydrological and earth science studies. Multiple groups have developed historical and forecast datasets of high-resolution monthly time-series for regions of the world such as the United States (e.g. PRISM for hindcast data and MACA for long-term forecasts); however, analogous datasets have not been available for most data scarce regions. The current work fills this data need by producing and freely distributing hindcast and forecast time-series datasets of monthly precipitation and mean temperature for all global land surfaces, gridded at a 30 arc-second resolution. The hindcast data are constructed through a Delta downscaling method, using as inputs 0.5 degree monthly time-series and 30 arc-second climatology global weather datasets developed by Willmott & Matsuura and WorldClim, respectively. The forecast data are formulated using a similar downscaling method, but with an additional step to remove bias from the climate variable's probability distribution over each region of interest. The downscaling package is designed to be compatible with a number of general circulation models (GCM) (e.g. with GCMs developed for the IPCC AR4 report and CMIP5), and is presently implemented using time-series data from the NCAR CESM1 model in conjunction with 30 arc-second future decadal climatologies distributed by the Consultative Group on International Agricultural Research. The resulting downscaled datasets are 30 arc-second time-series forecasts of monthly precipitation and mean temperature available for all global land areas. As an example of these data, historical and forecast 30 arc-second monthly time-series from 1950 through 2070 are created and analyzed for the region encompassing Pakistan. For this case study, forecast datasets corresponding to the future representative concentration pathways 45 and 85 scenarios developed by the IPCC are presented and compared. This exercise highlights a range of potential meteorological trends for the Pakistan region and more broadly serves to demonstrate the utility of the presented 30 arc-second monthly precipitation and mean temperature datasets for use in data scarce regions.

Geostatistical interpolation of individual average monthly temperature supported by MODIS MOD11C3 product

NASA Astrophysics Data System (ADS)

Perčec Tadić, M.

2010-09-01

The increased availability of satellite products of high spatial and temporal resolution together with developing user support, encourages the climatologists to use this data in research and practice. Since climatologists are mainly interested in monthly or even annual averages or aggregates, this high temporal resolution and hence, large amount of data, can be challenging for the less experienced users. Even if the attempt is made to aggregate e. g. the 15' (temporal) MODIS LST (land surface temperature) to daily temperature average, the development of the algorithm is not straight forward and should be done by the experts. Recent development of many temporary aggregated products on daily, several days or even monthly scale substantially decrease the amount of satellite data that needs to be processed and rise the possibility for development of various climatological applications. Here the attempt is presented in incorporating the MODIS satellite MOD11C3 product (Wan, 2009), that is monthly CMG (climate modelling 0.05 degree latitude/longitude grids) LST, as predictor in geostatistical interpolation of climatological data in Croatia. While in previous applications, e. g. in Climate Atlas of Croatia (Zaninović et al. 2008), the static predictors as digital elevation model, distance to the sea, latitude and longitude were used for the interpolation of monthly, seasonal and annual 30-years averages (reference climatology), here the monthly MOD11C3 is used to support the interpolation of the individual monthly average in the regression kriging framework. We believe that this can be a valuable show case of incorporating the remote sensed data for climatological application, especially in the areas that are under-sampled by conventional observations. Zaninović K, Gajić-Čapka M, Perčec Tadić M et al (2008) Klimatski atlas Hrvatske / Climate atlas of Croatia 1961-1990, 1971-2000. Meteorological and Hydrological Service of Croatia, Zagreb, pp 200. Wan Z, 2009: Collection-5 MODIS Land Surface Temperature Products Users' Guide, ICESS, University of California, Santa Barbara, pp 30.

Long-term characterization of the diet-induced obese and diet-resistant rat model: a polygenetic rat model mimicking the human obesity syndrome.

PubMed

Madsen, Andreas Nygaard; Hansen, Gitte; Paulsen, Sarah Juel; Lykkegaard, Kirsten; Tang-Christensen, Mads; Hansen, Harald S; Levin, Barry E; Larsen, Philip Just; Knudsen, Lotte Bjerre; Fosgerau, Keld; Vrang, Niels

2010-09-01

The availability of useful animal models reflecting the human obesity syndrome is crucial in the search for novel compounds for the pharmacological treatment of obesity. In the current study, we have performed an extensive characterization of the obesity syndrome in a polygenetic animal model, namely the selectively bred diet-induced obese (DIO) and diet-resistant (DR) rat strains. We show that they constitute useful models of the human obesity syndrome. DIO and DR rats were fed either a high-energy (HE) or a standard chow (Chow) diet from weaning to 9 months of age. Metabolic characterization including blood biochemistry and glucose homeostasis was examined at 2, 3, 6, and 9 months of age. Furthermore, in 6-month-old HE-fed DIO rats, the anti-obesity effects of liraglutide and sibutramine were examined in a 28-day study. Only HE-fed DIO rats developed visceral obesity, hyperleptinemia, hyperinsulinemia, and dyslipidemia, and showed a worsening of glucose tolerance over time. In line with the hyperlipidemic profile, a severe hepatic fat infiltration was observed in DIO rats at 6 months of age. The effects of liraglutide and sibutramine were tested in 6-month-old DIO rats. Both compounds effectively reduced food intake and body weight in DIO rats. Liraglutide furthermore improved glucose tolerance when compared with sibutramine. Our data highlights the usefulness of a polygenetic animal model for screening of compounds affecting food intake, body weight, and glucose homeostasis. Furthermore, the results underscore the effectiveness of GLP-1 mimetics both as anti-diabetes and anti-obesity agents.

The pathophysiology underlying repetitive mild traumatic brain injury in a novel mouse model of chronic traumatic encephalopathy.

PubMed

Petraglia, Anthony L; Plog, Benjamin A; Dayawansa, Samantha; Dashnaw, Matthew L; Czerniecka, Katarzyna; Walker, Corey T; Chen, Michael; Hyrien, Ollivier; Iliff, Jeffrey J; Deane, Rashid; Huang, Jason H; Nedergaard, Maiken

2014-01-01

An animal model of chronic traumatic encephalopathy (CTE) is essential for further understanding the pathophysiological link between repetitive head injury and the development of chronic neurodegenerative disease. We previously described a model of repetitive mild traumatic brain injury (mTBI) in mice that encapsulates the neurobehavioral spectrum characteristic of patients with CTE. We aimed to study the pathophysiological mechanisms underlying this animal model. Our previously described model allows for controlled, closed head impacts to unanesthetized mice. Briefly, 12-week-old mice were divided into three groups: Control, single, and repetitive mTBI. Repetitive mTBI mice received six concussive impacts daily, for 7 days. Mice were then subsequently sacrificed for macro- and micro-histopathologic analysis at 7 days, 1 month, and 6 months after the last TBI received. Brain sections were immunostained for glial fibrillary acidic protein (GFAP) for astrocytes, CD68 for activated microglia, and AT8 for phosphorylated tau protein. Brains from single and repetitive mTBI mice lacked macroscopic tissue damage at all time-points. Single mTBI resulted in an acute rea ctive astrocytosis at 7 days and increased phospho-tau immunoreactivity that was present acutely and at 1 month, but was not persistent at 6 months. Repetitive mTBI resulted in a more marked neuroinflammatory response, with persistent and widespread astrogliosis and microglial activation, as well as significantly elevated phospho-tau immunoreactivity to 6-months. The neuropathological findings in this new model of repetitive mTBI resemble some of the histopathological hallmarks of CTE, including increased astrogliosis, microglial activation, and hyperphosphorylated tau protein accumulation.

Predictive Skill of Meteorological Drought Based on Multi-Model Ensemble Forecasts: A Real-Time Assessment

NASA Astrophysics Data System (ADS)

Chen, L. C.; Mo, K. C.; Zhang, Q.; Huang, J.

2014-12-01

Drought prediction from monthly to seasonal time scales is of critical importance to disaster mitigation, agricultural planning, and multi-purpose reservoir management. Starting in December 2012, NOAA Climate Prediction Center (CPC) has been providing operational Standardized Precipitation Index (SPI) Outlooks using the North American Multi-Model Ensemble (NMME) forecasts, to support CPC's monthly drought outlooks and briefing activities. The current NMME system consists of six model forecasts from U.S. and Canada modeling centers, including the CFSv2, CM2.1, GEOS-5, CCSM3.0, CanCM3, and CanCM4 models. In this study, we conduct an assessment of the predictive skill of meteorological drought using real-time NMME forecasts for the period from May 2012 to May 2014. The ensemble SPI forecasts are the equally weighted mean of the six model forecasts. Two performance measures, the anomaly correlation coefficient and root-mean-square errors against the observations, are used to evaluate forecast skill.Similar to the assessment based on NMME retrospective forecasts, predictive skill of monthly-mean precipitation (P) forecasts is generally low after the second month and errors vary among models. Although P forecast skill is not large, SPI predictive skill is high and the differences among models are small. The skill mainly comes from the P observations appended to the model forecasts. This factor also contributes to the similarity of SPI prediction among the six models. Still, NMME SPI ensemble forecasts have higher skill than those based on individual models or persistence, and the 6-month SPI forecasts are skillful out to four months. The three major drought events occurred during the 2012-2014 period, the 2012 Central Great Plains drought, the 2013 Upper Midwest flash drought, and 2013-2014 California drought, are used as examples to illustrate the system's strength and limitations. For precipitation-driven drought events, such as the 2012 Central Great Plains drought, NMME SPI forecasts perform well in predicting drought severity and spatial patterns. For fast-developing drought events, such as the 2013 Upper Midwest flash drought, the system failed to capture the onset of the drought.

Birth month affects lifetime disease risk: a phenome-wide method

PubMed Central

Boland, Mary Regina; Shahn, Zachary; Madigan, David; Hripcsak, George; Tatonetti, Nicholas P

2015-01-01

Objective An individual’s birth month has a significant impact on the diseases they develop during their lifetime. Previous studies reveal relationships between birth month and several diseases including atherothrombosis, asthma, attention deficit hyperactivity disorder, and myopia, leaving most diseases completely unexplored. This retrospective population study systematically explores the relationship between seasonal affects at birth and lifetime disease risk for 1688 conditions. Methods We developed a hypothesis-free method that minimizes publication and disease selection biases by systematically investigating disease-birth month patterns across all conditions. Our dataset includes 1 749 400 individuals with records at New York-Presbyterian/Columbia University Medical Center born between 1900 and 2000 inclusive. We modeled associations between birth month and 1688 diseases using logistic regression. Significance was tested using a chi-squared test with multiplicity correction. Results We found 55 diseases that were significantly dependent on birth month. Of these 19 were previously reported in the literature (P < .001), 20 were for conditions with close relationships to those reported, and 16 were previously unreported. We found distinct incidence patterns across disease categories. Conclusions Lifetime disease risk is affected by birth month. Seasonally dependent early developmental mechanisms may play a role in increasing lifetime risk of disease. PMID:26041386

Regression to the mean and changes in risk behavior following study enrollment in a cohort of U.S. women at risk for HIV.

PubMed

Hughes, James P; Haley, Danielle F; Frew, Paula M; Golin, Carol E; Adimora, Adaora A; Kuo, Irene; Justman, Jessica; Soto-Torres, Lydia; Wang, Jing; Hodder, Sally

2015-06-01

Reductions in risk behaviors are common following enrollment in human immunodeficiency virus (HIV) prevention studies. We develop methods to quantify the proportion of change in risk behaviors that can be attributed to regression to the mean versus study participation and other factors. A novel model that incorporates both regression to the mean and study participation effects is developed for binary measures. The model is used to estimate the proportion of change in the prevalence of "unprotected sex in the past 6 months" that can be attributed to study participation versus regression to the mean in a longitudinal cohort of women at risk for HIV infection who were recruited from ten U.S. communities with high rates of HIV and poverty. HIV risk behaviors were evaluated using audio computer-assisted self-interviews at baseline and every 6 months for up to 12 months. The prevalence of "unprotected sex in the past 6 months" declined from 96% at baseline to 77% at 12 months. However, this change could be almost completely explained by regression to the mean. Analyses that examine changes over time in cohorts selected for high- or low- risk behaviors should account for regression to the mean effects. Copyright © 2015 Elsevier Inc. All rights reserved.

A new approach to flow simulation using hybrid models

NASA Astrophysics Data System (ADS)

Solgi, Abazar; Zarei, Heidar; Nourani, Vahid; Bahmani, Ramin

2017-11-01

The necessity of flow prediction in rivers, for proper management of water resource, and the need for determining the inflow to the dam reservoir, designing efficient flood warning systems and so forth, have always led water researchers to think about models with high-speed response and low error. In the recent years, the development of Artificial Neural Networks and Wavelet theory and using the combination of models help researchers to estimate the river flow better and better. In this study, daily and monthly scales were used for simulating the flow of Gamasiyab River, Nahavand, Iran. The first simulation was done using two types of ANN and ANFIS models. Then, using wavelet theory and decomposing input signals of the used parameters, sub-signals were obtained and were fed into the ANN and ANFIS to obtain hybrid models of WANN and WANFIS. In this study, in addition to the parameters of precipitation and flow, parameters of temperature and evaporation were used to analyze their effects on the simulation. The results showed that using wavelet transform improved the performance of the models in both monthly and daily scale. However, it had a better effect on the monthly scale and the WANFIS was the best model.

Prediction of Scar Size in Rats Six Months after Burns Based on Early Post-injury Polarization-Sensitive Optical Frequency Domain Imaging

PubMed Central

Kravez, Eli; Villiger, Martin; Bouma, Brett; Yarmush, Martin; Yakhini, Zohar; Golberg, Alexander

2017-01-01

Hypertrophic scars remain a major clinical problem in the rehabilitation of burn survivors and lead to physical, aesthetic, functional, psychological, and social stresses. Prediction of healing outcome and scar formation is critical for deciding on the best treatment plan. Both subjective and objective scales have been devised to assess scar severity. Whereas scales of the first type preclude cross-comparison between observers, those of the second type are based on imaging modalities that either lack the ability to image individual layers of the scar or only provide very limited fields of view. To overcome these deficiencies, this work aimed at developing a predictive model of scar formation based on polarization sensitive optical frequency domain imaging (PS-OFDI), which offers comprehensive subsurface imaging. We report on a linear regression model that predicts the size of a scar 6 months after third-degree burn injuries in rats based on early post-injury PS-OFDI and measurements of scar area. When predicting the scar area at month 6 based on the homogeneity and the degree of polarization (DOP), which are signatures derived from the PS-OFDI signal, together with the scar area measured at months 2 and 3, we achieved predictions with a Pearson coefficient of 0.57 (p < 10−4) and a Spearman coefficient of 0.66 (p < 10−5), which were significant in comparison to prediction models trained on randomly shuffled data. As the model in this study was developed on the rat burn model, the methodology can be used in larger studies that are more relevant to humans; however, the actual model inferred herein is not translatable. Nevertheless, our analysis and modeling methodology can be extended to perform larger wound healing studies in different contexts. This study opens new possibilities for quantitative and objective assessment of scar severity that could help to determine the optimal course of therapy. PMID:29249978

Relations between early family risk, children’s behavioral regulation, and academic achievement

PubMed Central

Sektnan, Michaella; McClelland, Megan M.; Acock, Alan; Morrison, Frederick J.

2010-01-01

This study examined relations among early family risk, children’s behavioral regulation at 54 months and kindergarten, and academic achievement in first grade using data on 1,298 children from the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development. Family risk was indexed by ethnic minority status, low maternal education, low average family income from 1 – 54 months, and high maternal depressive symptoms from 1 - 54 months. Results of structural equation modeling indicated that minority status, low maternal education, and low family income had significant negative effects on reading, math, and vocabulary achievement in first grade. Modest indirect effects were also found from ethnicity, maternal education, and maternal depressive symptoms, through 54-month and kindergarten behavioral regulation to first-grade achievement. Discussion focuses on the importance of behavioral regulation for school success especially for children facing early risk. PMID:20953343

Monthly communication skill coaching for healthcare staff.

PubMed

Rowan, Katherine E

2008-06-01

To promote monthly interpersonal skill communication role-play and coaching for front-office staff. For 15 min a month, during staff meetings, healthcare staff such as receptionists and medical assistants should participate in communication skill coaching. Participants should discuss a recurring communication challenge (e.g., patients irritated by repeated requests for health histories), role-play options for communication, and receive feedback. Interpersonal communication skills such as acknowledging the concerns of others are acquired slowly. Repeated practice and supportive feedback increase the likelihood that these skills will be valued and mastered. Research shows communication skills develop when they are modeled and role-played frequently and are less likely to develop with occasional interventions. Health care professionals should devote time to role-playing interaction with patients for brief intervals at least monthly. Staff should give one another feedback on the best options for managing challenging communication situations.

Analysis of the relationship between the monthly temperatures and weather types in Iberian Peninsula

NASA Astrophysics Data System (ADS)

Peña Angulo, Dhais; Trigo, Ricardo; Nicola, Cortesi; José Carlos, González-Hidalgo

2016-04-01

In this study, the relationship between the atmospheric circulation and weather types and the monthly average maximum and minimum temperatures in the Iberian Peninsula is modeled (period 1950-2010). The temperature data used were obtained from a high spatial resolution (10km x 10km) dataset (MOTEDAS dataset, Gonzalez-Hidalgo et al., 2015a). In addition, a dataset of Portuguese temperatures was used (obtained from the Portuguese Institute of Sea and Atmosphere). The weather type classification used was the one developed by Jenkinson and Collison, which was adapted for the Iberian Peninsula by Trigo and DaCamara (2000), using Sea Level Pressure data from NCAR/NCEP Reanalysis dataset (period 1951-2010). The analysis of the behaviour of monthly temperatures based on the weather types was carried out using a stepwise regression procedure of type forward to estimate temperatures in each cell of the considered grid, for each month, and for both maximum and minimum monthly average temperatures. The model selects the weather types that best estimate the temperatures. From the validation model it was obtained the error distribution in the time (months) and space (Iberian Peninsula). The results show that best estimations are obtained for minimum temperatures, during the winter months and in coastal areas. González-Hidalgo J.C., Peña-Angulo D., Brunetti M., Cortesi, C. (2015a): MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951-2010). International Journal of Climatology 31, 715-731. DOI: 10.1002/joc.4298

GIS/RS-based Integrated Eco-hydrologic Modeling in the East River Basin, South China

NASA Astrophysics Data System (ADS)

Wang, Kai

Land use/cover change (LUCC) has significantly altered the hydrologic system in the East River (Dongjiang) Basin. Quantitative modeling of hydrologic impacts of LUCC is of great importance for water supply, drought monitoring and integrated water resources management. An integrated eco-hydrologic modeling system of Distributed Monthly Water Balance Model (DMWBM), Surface Energy Balance System (SEBS) was developed with aid of GIS/RS to quantify LUCC, to conduct physically-based ET (evapotranspiration) mapping and to predict hydrologic impacts of LUCC. To begin with, in order to evaluate LUCC, understand implications of LUCC and provide boundary condition for the integrated eco-hydrologic modeling, firstly the long-term vegetation dynamics was investigated based on Normalized Difference Vegetation Index (NDVI) data, and then LUCC was analyzed with post-classification methods and finally LUCC prediction was conducted based on Markov chain model. The results demonstrate that the vegetation activities decreased significantly in summer over the years. Moreover, there were significant changes in land use/cover over the past two decades. Particularly there was a sharp increase of urban and built-up area and a significant decrease of grassland and cropland. All these indicate that human activities are intensive in the East River Basin and provide valuable information for constructing scenarios for studying hydrologic impacts of LUCC. The physically-remote-sensing-based Surface Energy Balance System (SEBS) was employed to estimate areal actual ET for a large area rather than traditional point measurements . The SEBS was enhanced for application in complex vegetated area. Then the inter-comparison with complimentary ET model and distributed monthly water balance model was made to validate the enhanced SEBS (ESEBS). The application and test of ESEBS show that it has a good accuracy both monthly and annually and can be effectively applied in the East River Basin. The results of ET mapping based on ESEBS demonstrate that actual ET in the East River Basin decreases significantly in the last two decades, which is probably caused by decrease of sunshine duration. In order to effectively simulate hydrologic impact of LUCC, an integrated model of ESEBS and distributed monthly water balance model has been developed in this study. The model is capable of considering basin terrain and the spatial distribution of precipitation and soil moisture. Particularly, the model is unique in accounting for spatial and temporal variations of vegetation cover and ET, which provides a powerful tool for studying the hydrologic impacts of LUCC. The model was applied to simulate the monthly runoff for the period of 1980-1994 for model calibration and for the period of 1995-2000 for validation. The calibration and validation results show that the newly integrated model is suitable for simulating monthly runoff and studying hydrologic impacts ofLUCC in the East River Basin. Finally, the newly integrated model was firstly applied to analyze the relationship of land use and hydrologic regimes based on the land use maps in 1980 and 2000. Then the newly integrated model was applied to simulate the potential impacts of land use change on hydrologic regimes in the East River Basin under a series of hypothetical scenarios. The results show that ET has a positive relationship with Leaf Area Index (LAI) while runoff has a negative relationship with LAI in the same climatic zone, which can be elaborated by surface energy balance and water balance equation. Specifically, on an annual basis, ET of forest scenarios is larger than that of grassland or cropland scenarios. On the contrary, runoff of forest scenarios is less than that of grassland or cropland scenarios. On a monthly basis, for most of the scenarios, particularly the grassland and cropland scenarios, the most significant changes occurred in the rainy season. The results indicate that deforestation would cause increase of runoff and decrease of ET on an annual basis in the East River Basin. On a monthly basis, deforestation would cause significant decrease of ET and increase of runoff in the rainy season in the East River Basin. These results are not definitive statements as to what will happen to runoff, ET and soil moisture regimes in the East River Basin, but rather offer an insight into the plausible changes in basin hydrology due to land use change. The integrated model developed in this study and these results have significant implications for integrated water resources management and sustainable development in the East River Basin.

Metabolomic profiling of urinary changes in mice with monosodium glutamate-induced obesity.

PubMed

Pelantová, Helena; Bártová, Simona; Anýž, Jiří; Holubová, Martina; Železná, Blanka; Maletínská, Lenka; Novák, Daniel; Lacinová, Zdena; Šulc, Miroslav; Haluzík, Martin; Kuzma, Marek

2016-01-01

Obesity with related complications represents a widespread health problem. The etiopathogenesis of obesity is often studied using numerous rodent models. The mouse model of monosodium glutamate (MSG)-induced obesity was exploited as a model of obesity combined with insulin resistance. The aim of this work was to characterize the metabolic status of MSG mice by NMR-based metabolomics in combination with relevant biochemical and hormonal parameters. NMR analysis of urine at 2, 6, and 9 months revealed altered metabolism of nicotinamide and polyamines, attenuated excretion of major urinary proteins, increased levels of phenylacetylglycine and allantoin, and decreased concentrations of methylamine in urine of MSG-treated mice. Altered levels of creatine, citrate, succinate, and acetate were observed at 2 months of age and approached the values of control mice with aging. The development of obesity and insulin resistance in 6-month-old MSG mice was also accompanied by decreased mRNA expressions of adiponectin, lipogenetic and lipolytic enzymes and peroxisome proliferator-activated receptor-gamma in fat while mRNA expressions of lipogenetic enzymes in the liver were enhanced. At the age of 9 months, biochemical parameters of MSG mice were normalized to the values of the controls. This fact pointed to a limited predictive value of biochemical data up to age of 6 months as NMR metabolomics confirmed altered urine metabolic composition even at 9 months.

Hybrid Stochastic Forecasting Model for Management of Large Open Water Reservoir with Storage Function

NASA Astrophysics Data System (ADS)

Kozel, Tomas; Stary, Milos

2017-12-01

The main advantage of stochastic forecasting is fan of possible value whose deterministic method of forecasting could not give us. Future development of random process is described better by stochastic then deterministic forecasting. Discharge in measurement profile could be categorized as random process. Content of article is construction and application of forecasting model for managed large open water reservoir with supply function. Model is based on neural networks (NS) and zone models, which forecasting values of average monthly flow from inputs values of average monthly flow, learned neural network and random numbers. Part of data was sorted to one moving zone. The zone is created around last measurement average monthly flow. Matrix of correlation was assembled only from data belonging to zone. The model was compiled for forecast of 1 to 12 month with using backward month flows (NS inputs) from 2 to 11 months for model construction. Data was got ridded of asymmetry with help of Box-Cox rule (Box, Cox, 1964), value r was found by optimization. In next step were data transform to standard normal distribution. The data were with monthly step and forecast is not recurring. 90 years long real flow series was used for compile of the model. First 75 years were used for calibration of model (matrix input-output relationship), last 15 years were used only for validation. Outputs of model were compared with real flow series. For comparison between real flow series (100% successfully of forecast) and forecasts, was used application to management of artificially made reservoir. Course of water reservoir management using Genetic algorithm (GE) + real flow series was compared with Fuzzy model (Fuzzy) + forecast made by Moving zone model. During evaluation process was founding the best size of zone. Results show that the highest number of input did not give the best results and ideal size of zone is in interval from 25 to 35, when course of management was almost same for all numbers from interval. Resulted course of management was compared with course, which was obtained from using GE + real flow series. Comparing results showed that fuzzy model with forecasted values has been able to manage main malfunction and artificially disorders made by model were founded essential, after values of water volume during management were evaluated. Forecasting model in combination with fuzzy model provide very good results in management of water reservoir with storage function and can be recommended for this purpose.

Novel Lean Type 2 Diabetic Rat Model Using Gestational Low Protein Programming

PubMed Central

BLESSON, Chellakkan S.; SCHUTT, Amy K.; BALAKRISHNAN, Meena P.; PAUTLER, Robia G.; PEDERSEN, Steen E.; SARKAR, Poonam; GONZALES, Daniel; ZHU, Gang; MARINI, Juan C.; CHACKO, Shaji K.; YALLAMPALLI, Uma; YALLAMPALLI, Chandra

2016-01-01

Background Type 2 diabetes in lean individuals is not well studied and up to 26% of diabetes occurs in these individuals. Although the cause is not well understood, it has been primarily attributed to nutritional issues during early development. Objective Our objective was to develop a lean type 2 diabetes model using gestational low protein programming. Study Design Pregnant rats were fed control (20% protein) or isocaloric low protein (6%) diet from gestational day 4 until delivery. Standard diet was given to dams after delivery and to pups after weaning. Glucose tolerance test was done at 2, 4 and 6 months of age. Magnetic resonance imaging of body fat for the females was done at 4 months. Rats were sacrificed at 4 months and 8 months of age and their peri-gonadal, peri-renal, inguinal and brown fat were weighed and expressed relative to their body weight. Euglycemic-hyperinsulinemic clamp was done around 6 months of age. Results Male and female offspring exposed to a low protein diet during gestation developed glucose intolerance and insulin resistance. Further, glucose intolerance progressed with increasing age and occurred earlier and was more severe in females when compared to males. Euglycemic hyperinsulinemic clamp showed whole body insulin resistance in both sexes, with females demonstrating increased insulin resistance compared to males. Low protein females showed a 4.5-fold increase in insulin resistance while males showed a 2.5-fold increase when compared to their respective controls. Data from magnetic resonance imaging on female offspring showed no difference in the subcutaneous, inguinal and visceral fat content. We were able to validate this observation by sacrificing the rats at 4 and 8 months and measuring total body fat content. This showed no differences in body fat content between control and LP offspring in both males and females. Additionally, diabetic rats had a similar body mass index to that of the controls. Conclusion LP gestational programming produces a progressively worsening type 2 diabetes model in rats with a lean phenotype without obesity. PMID:26874300

Progressive proliferative and dysplastic typhlocolitis in aging syrian hamsters naturally infected with Helicobacter spp.: a spontaneous model of inflammatory bowel disease.

PubMed

Nambiar, P R; Kirchain, S M; Courmier, K; Xu, S; Taylor, N S; Theve, E J; Patterson, M M; Fox, J G

2006-01-01

Helicobacter spp. have been implicated in a variety of gastrointestinal tract diseases, including peptic ulcer disease, gastric cancer, and inflammatory bowel disease (IBD), in humans and animals. Although most models of IBD are experimentally induced, spontaneous or natural models of IBD are rare. Herein, we describe a long-term study of chronic, progressive lesions that develop in the distal portion of the large bowel of unmanipulated Syrian hamsters naturally infected with Helicobacter spp. Twenty-four Syrian hamsters of three age groups (group A, 1 month [n = 4], group B, 7-12 months [n = 12], group C, 18-24 months [n = 12]), underwent complete postmortem examination. Results of microbial isolation and polymerase chain reaction and restriction fragment length polymorphism analyses confirmed the presence of Helicobacter spp. infection in the distal portion of the large bowel of all animals. Additionally, confounding pathogens, such as Clostridium difficile, Lawsonia intracellularis, and Giardia spp. that can cause proliferative enteritis, were absent in the hamsters of this study. Histopathologic scores for inflammation (P < 0.01), hyperplasia (P < 0.01), and dysplasia (P < 0.05) were significantly higher in the ileocecocolic (ICC) junction of animals in group C, relative to group A. Dysplastic lesions of various grades were detected in 5 of 11 hamsters in group C. Interestingly, the segment of the bowel that is usually colonized by Helicobacter spp. in hamsters had the most severe lesions. One hamster of group C developed a malignant fibrous histiocytoma, whereas another hamster developed a round cell sarcoma originating from the ICC junction. Thus, lesions in the distal portion of the large bowel of aging hamsters naturally colonized with Helicobacter spp. warrants developing the hamster as an animal model of IBD and potentially IBD-related cancer.

The Family Life Project: an epidemiological and developmental study of young children living in poor rural communities.

PubMed

Vernon-Feagans, Lynne; Cox, Martha

2013-10-01

About 20% of children in the United States have been reported to live in rural communities, with child poverty rates higher and geographic isolation from resources greater than in urban communities. There have been surprisingly few studies of children living in rural communities, especially poor rural communities. The Family Life Project helped fill this gap by using an epidemiological design to recruit and study a representative sample of every baby born to a mother who resided in one of six poor rural counties over a 1-year period, oversampling for poverty and African American. 1,292 children were followed from birth to 36 months of age. This monograph described these children and used a cumulative risk model to examine the relation between social risk and children's executive functioning, language development, and behavioral competence at 36 months. Using both the Family Process Model of development and the Family Investment Model of development, observed parenting was examined over time in relation to child functioning at 36 months. Different aspects of observed parenting were examined as mediators/moderators of risk in predicting child outcomes. Results suggested that cumulative risk was important in predicting all three major domains of child outcomes and that positive and negative parenting and maternal language complexity were mediators of these relations. Maternal positive parenting was found to be a buffer for the most risky families in predicting behavioral competence. In a final model using both family process and investment measures, there was evidence of mediation but with little evidence of the specificity of parenting for particular outcomes. Discussion focused on the importance of cumulative risk and parenting in understanding child competence in rural poverty and the implications for possible intervention strategies that might be effective in maximizing the early development of these children.

Impact of meteorological changes on the incidence of scarlet fever in Hefei City, China.

PubMed

Duan, Yu; Huang, Xiao-Lei; Wang, Yu-Jie; Zhang, Jun-Qing; Zhang, Qi; Dang, Yue-Wen; Wang, Jing

2016-10-01

Studies on scarlet fever with meteorological factors included were few. We aimed to illustrate meteorological factors' effects on monthly incidence of scarlet fever. Cases of scarlet fever were collected from the report of legal infectious disease in Hefei City from 1985 to 2006; the meteorological data were obtained from the weather bureau of Hefei City. Monthly incidence and corresponding meteorological data in these 22 years were used to develop the model. The model of auto regressive integrated moving average with covariates was used in statistical analyses. There was a highest peak from March to June and a small peak from November to January. The incidence of scarlet fever ranges from 0 to 0.71502 (per 10 5 population). SARIMAX (1,0,0)(1,0,0) 12 model was fitted with monthly incidence and meteorological data optimally. It was shown that relative humidity (β = -0.002, p = 0.020), mean temperature (β = 0.006, p = 0.004), and 1 month lag minimum temperature (β = -0.007, p < 0.001) had effect on the incidence of scarlet fever in Hefei. Besides, the incidence in a previous month (AR(β) = 0.469, p < 0.001) and in 12 months before (SAR(β) = 0.255, p < 0.001) was positively associated with the incidence. This study shows that scarlet fever incidence was negatively associated with monthly minimum temperature and relative humidity while was positively associated with mean temperature in Hefei City, China. Besides, the ARIMA model could be useful not only for prediction but also for the analysis of multiple correlations.

Data Mining of Web-Based Documents on Social Networking Sites That Included Suicide-Related Words Among Korean Adolescents.

PubMed

Song, Juyoung; Song, Tae Min; Seo, Dong-Chul; Jin, Jae Hyun

2016-12-01

To investigate online search activity of suicide-related words in South Korean adolescents through data mining of social media Web sites as the suicide rate in South Korea is one of the highest in the world. Out of more than 2.35 billion posts for 2 years from January 1, 2011 to December 31, 2012 on 163 social media Web sites in South Korea, 99,693 suicide-related documents were retrieved by Crawler and analyzed using text mining and opinion mining. These data were further combined with monthly employment rate, monthly rental prices index, monthly youth suicide rate, and monthly number of reported bully victims to fit multilevel models as well as structural equation models. The link from grade pressure to suicide risk showed the largest standardized path coefficient (beta = .357, p < .001) in structural models and a significant random effect (p < .01) in multilevel models. Depression was a partial mediator between suicide risk and grade pressure, low body image, victims of bullying, and concerns about disease. The largest total effect was observed in the grade pressure to depression to suicide risk. The multilevel models indicate about 27% of the variance in the daily suicide-related word search activity is explained by month-to-month variations. A lower employment rate, a higher rental prices index, and more bullying were associated with an increased suicide-related word search activity. Academic pressure appears to be the biggest contributor to Korean adolescents' suicide risk. Real-time suicide-related word search activity monitoring and response system needs to be developed. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Mouth opening in patients irradiated for head and neck cancer: a prospective repeated measures study.

PubMed

Kamstra, J I; Dijkstra, P U; van Leeuwen, M; Roodenburg, J L N; Langendijk, J A

2015-05-01

Aims of this prospective cohort study were (1) to analyze the course of mouth opening up to 48months post-radiotherapy (RT), (2) to assess risk factors predicting decrease in mouth opening, and (3) to develop a multivariable prediction model for change in mouth opening in a large sample of patients irradiated for head and neck cancer. Mouth opening was measured prior to RT (baseline) and at 6, 12, 18, 24, 36, and 48months post-RT. The primary outcome variable was mouth opening. Potential risk factors were entered into a linear mixed model analysis (manual backward-stepwise elimination) to create a multivariable prediction model. The interaction terms between time and risk factors that were significantly related to mouth opening were explored. The study population consisted of 641 patients: 70.4% male, mean age at baseline 62.3years (sd 12.5). Primary tumors were predominantly located in the oro- and nasopharynx (25.3%) and oral cavity (20.6%). Mean mouth opening at baseline was 38.7mm (sd 10.8). Six months post-RT, mean mouth opening was smallest, 36.7mm (sd 10.0). In the linear mixed model analysis, mouth opening was statistically predicted by the location of the tumor, natural logarithm of time post-RT in months (Ln (months)), gender, baseline mouth opening, and baseline age. All main effects interacted with Ln (months). The mean mouth opening decreased slightly over time. Mouth opening was predicted by tumor location, time, gender, baseline mouth opening, and age. The model can be used to predict mouth opening. Copyright © 2015 Elsevier Ltd. All rights reserved.

UWR/MSAA demonstration of coordinated human-services transportation models - phase II : phased implementation.

DOT National Transportation Integrated Search

2012-12-01

This report presents the results of a 16-month project for system development and design of a model for a Travel Management Coordination Center (TMCC) using ITS capabilities. The system was designed as a tool to facilitate the exchange of knowledge a...

Using Multivariate Regression Model with Least Absolute Shrinkage and Selection Operator (LASSO) to Predict the Incidence of Xerostomia after Intensity-Modulated Radiotherapy for Head and Neck Cancer

PubMed Central

Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Wu, Jia-Ming; Wang, Hung-Yu; Horng, Mong-Fong; Chang, Chun-Ming; Lan, Jen-Hong; Huang, Ya-Yu; Fang, Fu-Min; Leung, Stephen Wan

2014-01-01

Purpose The aim of this study was to develop a multivariate logistic regression model with least absolute shrinkage and selection operator (LASSO) to make valid predictions about the incidence of moderate-to-severe patient-rated xerostomia among head and neck cancer (HNC) patients treated with IMRT. Methods and Materials Quality of life questionnaire datasets from 206 patients with HNC were analyzed. The European Organization for Research and Treatment of Cancer QLQ-H&N35 and QLQ-C30 questionnaires were used as the endpoint evaluation. The primary endpoint (grade 3+ xerostomia) was defined as moderate-to-severe xerostomia at 3 (XER3m) and 12 months (XER12m) after the completion of IMRT. Normal tissue complication probability (NTCP) models were developed. The optimal and suboptimal numbers of prognostic factors for a multivariate logistic regression model were determined using the LASSO with bootstrapping technique. Statistical analysis was performed using the scaled Brier score, Nagelkerke R2, chi-squared test, Omnibus, Hosmer-Lemeshow test, and the AUC. Results Eight prognostic factors were selected by LASSO for the 3-month time point: Dmean-c, Dmean-i, age, financial status, T stage, AJCC stage, smoking, and education. Nine prognostic factors were selected for the 12-month time point: Dmean-i, education, Dmean-c, smoking, T stage, baseline xerostomia, alcohol abuse, family history, and node classification. In the selection of the suboptimal number of prognostic factors by LASSO, three suboptimal prognostic factors were fine-tuned by Hosmer-Lemeshow test and AUC, i.e., Dmean-c, Dmean-i, and age for the 3-month time point. Five suboptimal prognostic factors were also selected for the 12-month time point, i.e., Dmean-i, education, Dmean-c, smoking, and T stage. The overall performance for both time points of the NTCP model in terms of scaled Brier score, Omnibus, and Nagelkerke R2 was satisfactory and corresponded well with the expected values. Conclusions Multivariate NTCP models with LASSO can be used to predict patient-rated xerostomia after IMRT. PMID:24586971

Using multivariate regression model with least absolute shrinkage and selection operator (LASSO) to predict the incidence of Xerostomia after intensity-modulated radiotherapy for head and neck cancer.

PubMed

Lee, Tsair-Fwu; Chao, Pei-Ju; Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Wu, Jia-Ming; Wang, Hung-Yu; Horng, Mong-Fong; Chang, Chun-Ming; Lan, Jen-Hong; Huang, Ya-Yu; Fang, Fu-Min; Leung, Stephen Wan

2014-01-01

The aim of this study was to develop a multivariate logistic regression model with least absolute shrinkage and selection operator (LASSO) to make valid predictions about the incidence of moderate-to-severe patient-rated xerostomia among head and neck cancer (HNC) patients treated with IMRT. Quality of life questionnaire datasets from 206 patients with HNC were analyzed. The European Organization for Research and Treatment of Cancer QLQ-H&N35 and QLQ-C30 questionnaires were used as the endpoint evaluation. The primary endpoint (grade 3(+) xerostomia) was defined as moderate-to-severe xerostomia at 3 (XER3m) and 12 months (XER12m) after the completion of IMRT. Normal tissue complication probability (NTCP) models were developed. The optimal and suboptimal numbers of prognostic factors for a multivariate logistic regression model were determined using the LASSO with bootstrapping technique. Statistical analysis was performed using the scaled Brier score, Nagelkerke R(2), chi-squared test, Omnibus, Hosmer-Lemeshow test, and the AUC. Eight prognostic factors were selected by LASSO for the 3-month time point: Dmean-c, Dmean-i, age, financial status, T stage, AJCC stage, smoking, and education. Nine prognostic factors were selected for the 12-month time point: Dmean-i, education, Dmean-c, smoking, T stage, baseline xerostomia, alcohol abuse, family history, and node classification. In the selection of the suboptimal number of prognostic factors by LASSO, three suboptimal prognostic factors were fine-tuned by Hosmer-Lemeshow test and AUC, i.e., Dmean-c, Dmean-i, and age for the 3-month time point. Five suboptimal prognostic factors were also selected for the 12-month time point, i.e., Dmean-i, education, Dmean-c, smoking, and T stage. The overall performance for both time points of the NTCP model in terms of scaled Brier score, Omnibus, and Nagelkerke R(2) was satisfactory and corresponded well with the expected values. Multivariate NTCP models with LASSO can be used to predict patient-rated xerostomia after IMRT.

Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region

NASA Astrophysics Data System (ADS)

Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Mohd, Nuruol Syuhadaa; Deo, Ravinesh C.; El-Shafie, Ahmed

2017-10-01

Existing forecast models applied for reservoir inflow forecasting encounter several drawbacks, due to the difficulty of the underlying mathematical procedures being to cope with and to mimic the naturalization and stochasticity of the inflow data patterns. In this study, appropriate adjustments to the conventional coactive neuro-fuzzy inference system (CANFIS) method are proposed to improve the mathematical procedure, thus enabling a better detection of the high nonlinearity patterns found in the reservoir inflow training data. This modification includes the updating of the back propagation algorithm, leading to a consequent update of the membership rules and the induction of the centre-weighted set rather than the global weighted set used in feature extraction. The modification also aids in constructing an integrated model that is able to not only detect the nonlinearity in the training data but also the wide range of features within the training data records used to simulate the forecasting model. To demonstrate the model's efficacy, the proposed CANFIS method has been applied to forecast monthly inflow data at Aswan High Dam (AHD), located in southern Egypt. Comparative analyses of the forecasting skill of the modified CANFIS and the conventional ANFIS model are carried out with statistical score indicators to assess the reliability of the developed method. The statistical metrics support the better performance of the developed CANFIS model, which significantly outperforms the ANFIS model to attain a low relative error value (23%), mean absolute error (1.4 BCM month-1), root mean square error (1.14 BCM month-1), and a relative large coefficient of determination (0.94). The present study ascertains the better utility of the modified CANFIS model in respect to the traditional ANFIS model applied in reservoir inflow forecasting for a semi-arid region.

A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

NASA Astrophysics Data System (ADS)

Wang, Wen-Chuan; Chau, Kwok-Wing; Cheng, Chun-Tian; Qiu, Lin

2009-08-01

SummaryDeveloping a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation ( R), Nash-Sutcliffe efficiency coefficient ( E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.

Rapid Crop Cover Mapping for the Conterminous United States.

PubMed

Dahal, Devendra; Wylie, Bruce; Howard, Danny

2018-06-05

Timely crop cover maps with sufficient resolution are important components to various environmental planning and research applications. Through the modification and use of a previously developed crop classification model (CCM), which was originally developed to generate historical annual crop cover maps, we hypothesized that such crop cover maps could be generated rapidly during the growing season. Through a process of incrementally removing weekly and monthly independent variables from the CCM and implementing a 'two model mapping' approach, we found it viable to generate conterminous United States-wide rapid crop cover maps at a resolution of 250 m for the current year by the month of September. In this approach, we divided the CCM model into one 'crop type model' to handle the classification of nine specific crops and a second, binary model to classify the presence or absence of 'other' crops. Under the two model mapping approach, the training errors were 0.8% and 1.5% for the crop type and binary model, respectively, while test errors were 5.5% and 6.4%, respectively. With spatial mapping accuracies for annual maps reaching upwards of 70%, this approach demonstrated a strong potential for generating rapid crop cover maps by the 1 st of September.

[Early prediction of the neurological result at 12 months in newborns at neurological risk].

PubMed

Herbón, F; Garibotti, G; Moguilevsky, J

2015-08-01

The aim of this study was to evaluate the Amiel-Tison neurological examination (AT) and cranial ultrasound at term for predicting the neurological result at 12 months in newborns with neurological risk. The study included 89 newborns with high risk of neurological damage, who were discharged from the Neonatal Intensive Care of the Hospital Zonal Bariloche, Argentina. The assessment consisted of a neurological examination and cranial ultrasound at term, and neurological examination and evaluation of development at 12 months. The sensitivity, specificity, positive and negative predictor value was calculated. The relationship between perinatal factors and neurodevelopment at 12 month of age was also calculated using logistic regression models. Seventy children completed the follow-up. At 12 months of age, 14% had an abnormal neurological examination, and 17% abnormal development. The neurological examination and the cranial ultrasound at term had low sensitivity to predict abnormal neurodevelopment. At 12 months, 93% of newborns with normal AT showed normal neurological results, and 86% normal development. Among newborns with normal cranial ultrasound the percentages were 90 and 81%, respectively. Among children with three or more perinatal risk factors, the frequency of abnormalities in the neurological response was 5.4 times higher than among those with fewer risk factors, and abnormal development was 3.5 times more frequent. The neurological examination and cranial ultrasound at term had low sensitivity but high negative predictive value for the neurodevelopment at 12 months. Three or more perinatal risk factors were associated with neurodevelopment abnormalities at 12 months of age. Copyright © 2014 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

Development of fine motor skills is associated with expressive language outcomes in infants at high and low risk for autism spectrum disorder.

PubMed

Choi, Boin; Leech, Kathryn A; Tager-Flusberg, Helen; Nelson, Charles A

2018-04-12

A growing body of research suggests that fine motor abilities are associated with skills in a variety of domains in both typical and atypical development. In this study, we investigated developmental trajectories of fine motor skills between 6 and 24 months in relation to expressive language outcomes at 36 months in infants at high and low familial risk for autism spectrum disorder (ASD). Participants included 71 high-risk infants without ASD diagnoses, 30 high-risk infants later diagnosed with ASD, and 69 low-risk infants without ASD diagnoses. As part of a prospective, longitudinal study, fine motor skills were assessed at 6, 12, 18, and 24 months of age and expressive language outcomes at 36 months using the Mullen Scales of Early Learning. Diagnosis of ASD was determined at the infant's last visit to the lab (18, 24, or 36 months) using the Autism Diagnostic Observation Schedule. Hierarchical linear modeling revealed that high-risk infants who later developed ASD showed significantly slower growth in fine motor skills between 6 and 24 months, compared to their typically developing peers. In contrast to group differences in growth from age 6 months, cross-sectional group differences emerged only in the second year of life. Also, fine motor skills at 6 months predicted expressive language outcomes at 3 years of age. These results highlight the importance of utilizing longitudinal approaches in measuring early fine motor skills to reveal subtle group differences in infancy between ASD high-risk and low-risk infant populations and to predict their subsequent language outcomes.

Model-based prediction of nephropathia epidemica outbreaks based on climatological and vegetation data and bank vole population dynamics.

PubMed

Haredasht, S Amirpour; Taylor, C J; Maes, P; Verstraeten, W W; Clement, J; Barrios, M; Lagrou, K; Van Ranst, M; Coppin, P; Berckmans, D; Aerts, J-M

2013-11-01

Wildlife-originated zoonotic diseases in general are a major contributor to emerging infectious diseases. Hantaviruses more specifically cause thousands of human disease cases annually worldwide, while understanding and predicting human hantavirus epidemics pose numerous unsolved challenges. Nephropathia epidemica (NE) is a human infection caused by Puumala virus, which is naturally carried and shed by bank voles (Myodes glareolus). The objective of this study was to develop a method that allows model-based predicting 3 months ahead of the occurrence of NE epidemics. Two data sets were utilized to develop and test the models. These data sets were concerned with NE cases in Finland and Belgium. In this study, we selected the most relevant inputs from all the available data for use in a dynamic linear regression (DLR) model. The number of NE cases in Finland were modelled using data from 1996 to 2008. The NE cases were predicted based on the time series data of average monthly air temperature (°C) and bank voles' trapping index using a DLR model. The bank voles' trapping index data were interpolated using a related dynamic harmonic regression model (DHR). Here, the DLR and DHR models used time-varying parameters. Both the DHR and DLR models were based on a unified state-space estimation framework. For the Belgium case, no time series of the bank voles' population dynamics were available. Several studies, however, have suggested that the population of bank voles is related to the variation in seed production of beech and oak trees in Northern Europe. Therefore, the NE occurrence pattern in Belgium was predicted based on a DLR model by using remotely sensed phenology parameters of broad-leaved forests, together with the oak and beech seed categories and average monthly air temperature (°C) using data from 2001 to 2009. Our results suggest that even without any knowledge about hantavirus dynamics in the host population, the time variation in NE outbreaks in Finland could be predicted 3 months ahead with a 34% mean relative prediction error (MRPE). This took into account solely the population dynamics of the carrier species (bank voles). The time series analysis also revealed that climate change, as represented by the vegetation index, changes in forest phenology derived from satellite images and directly measured air temperature, may affect the mechanics of NE transmission. NE outbreaks in Belgium were predicted 3 months ahead with a 40% MRPE, based only on the climatological and vegetation data, in this case, without any knowledge of the bank vole's population dynamics. In this research, we demonstrated that NE outbreaks can be predicted using climate and vegetation data or the bank vole's population dynamics, by using dynamic data-based models with time-varying parameters. Such a predictive modelling approach might be used as a step towards the development of new tools for the prevention of future NE outbreaks. © 2012 Blackwell Verlag GmbH.

High beta and second stability region transport and stability analysis: Technical progress report

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

Hughes, M.H.; Phillips, M.W.

1995-03-01

This report summarizes MHD equilibrium and stability studies carried out at Northrop Grumman`s Advanced Technology and Development Center during the 12 month period starting March 1, 1994. Progress is reported in both ideal and resistive MHD modeling of TFTR plasmas. The development of codes to calculate the significant effects of highly anisotropic pressure distributions is discussed along with results from this model.

Navy Mobile Apps Acquisition: Doing It in Weeks, Not Months or Years

DTIC Science & Technology

2016-04-30

êÉ~íáåÖ=póåÉêÖó=Ñçê=fåÑçêãÉÇ=`Ü~åÖÉ= - 162 - Panel 6. Considerations in Software Modeling and Design Wednesday, May 4, 2016 1:45 p.m. – 3:15 p.m...investigation is considering implementations that leverage Government Furnished Equipment (GFE) and “Bring Your Own Device” (BYOD) models . ^Åèìáëáíáçå...Engineering Technical Reviews (SETR) events. However, that document generally guides development through a waterfall approach that requires months and even

Application of the Nelson model to four timelag fuel classes using Oklahoma field observations: Model evaluation and comparison with national Fire Danger Rating System algorithms

Treesearch

J. D. Carlson; Larry S. Bradshaw; Ralph M. Nelson; Randall R Bensch; Rafal Jabrzemski

2007-01-01

The application of a next-generation dead-fuel moisture model, the 'Nelson model', to four timelag fuel classes using an extensive 21-month dataset of dead-fuel moisture observations is described. Developed by Ralph Nelson in the 1990s, the Nelson model is a dead-fuel moisture model designed to take advantage of frequent automated weather observations....

Delirium as a Predictor of Physical and Cognitive Function in Individuals Aged 80 and Older After Transcatheter Aortic Valve Implantation or Surgical Aortic Valve Replacement.

PubMed

Eide, Leslie S P; Ranhoff, Anette H; Fridlund, Bengt; Haaverstad, Rune; Hufthammer, Karl Ove; Kuiper, Karel K J; Nordrehaug, Jan E; Norekvål, Tone M

2016-06-01

To determine how development of delirium after surgical aortic valve replacement (SAVR) or transcatheter aortic valve implantation (TAVI) could predict activity of daily living (ADL) and instrumental ADLs (IADL) disability, cognitive function, and self-reported health in individuals aged 80 and older. Prospective cohort study. Tertiary university hospital. Individuals aged 80 and older undergoing elective SAVR or TAVI (N = 136). Delirium was assessed for 5 days using the Confusion Assessment Method. The Barthel Index, Nottingham Extended ADL Scale, and SF-12 were used to determine ADL and IADL ability and self-reported health at baseline and 1- and 6-month follow-up. Cognition was assessed using the Mini-Mental State Examination at baseline and 6-month follow-up. Participants had lower IADL scores 1 month after SAVR than at baseline (baseline 58, 1 month: delirium 42, no delirium 50, P ≤ .02), but scores had returned to baseline levels at 6 months. The Medical Outcomes Study 12-item Short-Form Health Survey (SF-12) Physical Component Summary (PCS) score was higher at 6-month follow-up (48) than at baseline (39), especially in participants who did not develop delirium (P < .001). No differences in other outcomes were found. Regression models suggest that delirium may help predict IADL disability 1 month after baseline (P ≤ .07) but does not predict large differences in ADL disability, cognitive function, or SF-12-scores. Individuals who underwent TAVI and developed delirium had lower ADL (baseline 19, 1-month 16, P < .001) and IADL (baseline 49, 1-month 40, P = .003) scores at 1-month follow-up. SF-12 PCS score (baseline 30) increased from baseline to 1- (35, P = .04) and 6- (35, P = .02) month follow-up in individuals who underwent TAVI and did not develop delirium. Delirium after TAVI predicted greater ADL and IADL disability at 1-month but not at 6-month follow-up. Individuals who develop delirium after SAVR and TAVI have poorer short-term IADL function but do not seem to have long-term reductions in physical, mental, or self-reported health. © 2016 The Authors. The Journal of the American Geriatrics Society published by Wiley Periodicals, Inc. on behalf of The American Geriatrics Society.

Novel biomarker-based model for the prediction of sorafenib response and overall survival in advanced hepatocellular carcinoma: a prospective cohort study.

PubMed

Kim, Hwi Young; Lee, Dong Hyeon; Lee, Jeong-Hoon; Cho, Young Youn; Cho, Eun Ju; Yu, Su Jong; Kim, Yoon Jun; Yoon, Jung-Hwan

2018-03-20

Prediction of the outcome of sorafenib therapy using biomarkers is an unmet clinical need in patients with advanced hepatocellular carcinoma (HCC). The aim was to develop and validate a biomarker-based model for predicting sorafenib response and overall survival (OS). This prospective cohort study included 124 consecutive HCC patients (44 with disease control, 80 with progression) with Child-Pugh class A liver function, who received sorafenib. Potential serum biomarkers (namely, hepatocyte growth factor [HGF], fibroblast growth factor [FGF], vascular endothelial growth factor receptor-1, CD117, and angiopoietin-2) were tested. After identifying independent predictors of tumor response, a risk scoring system for predicting OS was developed and 3-fold internal validation was conducted. A risk scoring system was developed with six covariates: etiology, platelet count, Barcelona Clinic Liver Cancer stage, protein induced by vitamin K absence-II, HGF, and FGF. When patients were stratified into low-risk (score ≤ 5), intermediate-risk (score 6), and high-risk (score ≥ 7) groups, the model provided good discriminant functions on tumor response (concordance [c]-index, 0.884) and 12-month survival (area under the curve [AUC], 0.825). The median OS was 19.0, 11.2, and 6.1 months in the low-, intermediate-, and high-risk group, respectively (P < 0.001). In internal validation, the model maintained good discriminant functions on tumor response (c-index, 0.825) and 12-month survival (AUC, 0.803), and good calibration functions (all P > 0.05 between expected and observed values). This new model including serum FGF and HGF showed good performance in predicting the response to sorafenib and survival in patients with advanced HCC.

Does Caregiver Behavior Mediate the Relationship Between Cultural Individualism and Infant Pain at 12 Months of Age?

PubMed

O'Neill, Monica C; Pillai Riddell, Rebecca; Garfield, Hartley; Greenberg, Saul

2016-12-01

This study aimed to understand the relationship between caregiver culture and infant pain expression at the 12-month immunization and discern if a mechanism subsuming this relationship was the quality of caregiver behaviors (emotional availability). Infants (N = 393) with immunization data at 12 months of age were examined. On the basis of the Development of Infant Acute Pain Responding model, a mediation model was developed to examine how caregiver behaviors mediate the relationship between caregiver heritage culture and infant pain. Culture was operationalized by an objectively derived quantification of caregivers' self-reported heritage culture's individualism. Two mediation models were estimated, examining infant pain expression at 1 and 2 minutes post-needle. Caregivers who self-reported heritage cultures that were more highly individualistic tended to show greater emotional availability, which in turn predicted decreased infant pain expression at 1 and 2 minutes post-needle. The present findings further our understanding of one mechanism by which caregiver culture affects infant acute pain expression. Adding to the literature examining direct relationships between culture and infant immunization pain, this article proposes the quality of caregiver behaviors as a mechanism by which culture affects infant acute pain expression at 12 months of age. Results support the proposed mechanism and inform our understanding of the role of caregiver culture in the infant pain context. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

SUSCEPTIBILITY OF A GULF OF MEXICO ESTUARY TO HYPOXIA: AN ANALYSIS USING BOX MODELS

EPA Science Inventory

The extent of hypoxia and the physical factors affecting development and maintenance of hypoxia were examined for Pensacola Bay, Florida (USA) by conducting monthly water quality surveys for 3 years and by constructing salt-and-water balance box models using the resulting data. W...

WBVTE Talent Pool/Job Bank Model. Five Month Report.

ERIC Educational Resources Information Center

Davis, Ellen Rulseh

This report summarizes steps in the evolution and implementation of a computerized talent pool/job bank model developed primarily to assist women and minorities in the identification of and placement in leadership positions in vocational administration. Included in the report are chapters on recruiting participants for the talent pool, encouraging…

Development of exploration of spatial-relational object properties in the second and third years of life.

PubMed

Oudgenoeg-Paz, Ora; Boom, Jan; Volman, M Chiel J M; Leseman, Paul P M

2016-06-01

Within a perception-action framework, exploration is seen as a driving force in young children's development. Through exploration, children become skilled in perceiving the affordances in their environment and acting on them. Using a perception-action framework, the current study examined the development of children's exploration of the spatial-relational properties of objects such as the possibility of containing or stacking. A total of 61 children, belonging to two age cohorts, were followed from 9 to 24 months and from 20 to 36 months of age, respectively. Exploration of a standard set of objects was observed in five home visits in each cohort conducted every 4 months. A cohort-sequential augmented growth model for categorical data, incorporating assumptions of item response theory, was constructed that fitted the data well, showing that the development of exploration of spatial-relational object properties follows an overlapping waves pattern. This is in line with Siegler's model (Emerging Minds, 1996), which suggested that skill development can be seen as ebbing and flowing of alternative (simple and advanced) behaviors. Although the probability of observing the more complex forms of exploration increased with age, the simpler forms did not disappear altogether but only became less probable. Findings support a perception-action view on development. Individual differences in observed exploration and their relations with other variables, as well as future directions for research, are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Language Development in the First Year of Life: What Deaf Children Might Be Missing Before Cochlear Implantation.

PubMed

Levine, Dani; Strother-Garcia, Kristina; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathy

2016-02-01

Language development is a multifaceted, dynamic process involving the discovery of complex patterns, and the refinement of native language competencies in the context of communicative interactions. This process is already advanced by the end of the first year of life for hearing children, but prelingually deaf children who initially lack a language model may miss critical experiences during this early window. The purpose of this review is twofold. First, we examine the published literature on language development during the first 12 months in typically developing children. Second, we use this literature to inform our understanding of the language outcomes of prelingually deaf children who receive cochlear implants (CIs), and therefore language input, either before or after the first year. During the first 12 months, typically developing infants exhibit advances in speech segmentation, word learning, syntax acquisition, and communication, both verbal and nonverbal. Infants and their caregivers coconstruct a communication foundation during this time, supporting continued language growth. The language outcomes of hearing children are robustly predicted by their experiences and acquired competencies during the first year; yet these predictive links are absent among prelingually deaf infants lacking a language model (i.e., those without exposure to sign). For deaf infants who receive a CI, implantation timing is crucial. Children receiving CIs before 12 months frequently catch up with their typically developing peers, whereas those receiving CIs later do not. Explanations for the language difficulties of late-implanted children are discussed.

A model for the development of mothers' perceived vulnerability of preterm infants.

PubMed

Horwitz, Sarah McCue; Storfer-Isser, Amy; Kerker, Bonnie D; Lilo, Emily; Leibovitz, Ann; St John, Nick; Shaw, Richard J

2015-06-01

Some mothers of preterm infants continue to view them as vulnerable after their health has improved. These exaggerated perceptions of vulnerability lead to poor parent-child interactions and, subsequently, to adverse child outcomes. However, there is no theoretical model to explain why these exaggerated perceptions develop in only some mother-child dyads. Data for this study come from a randomized trial of an intervention to reduce distress in mothers of preterm infants. A total of 105 mothers older than 18 years of infants aged 25-34 weeks, weighing >600 g and with clinically significant anxiety, depression, or trauma symptoms, were recruited and randomized. Women were assessed at baseline, after intervention, and at 6 months after birth. The outcome for these analyses was perceptions of infant vulnerability as measured by the Vulnerable Baby Scale (VBS) at 6 months after birth. A theoretical model developed from the extant literature was tested using the MacArthur Mediator-Moderator Approach. A dysfunctional coping style, high depression, anxiety, or trauma symptoms in response to the preterm birth, and low social support were related to 6-month VBS scores. Maternal response to trauma was directly related to VBS, and an important precursor of maternal response to trauma was a dysfunctional coping style. This model suggests that maternal responses to trauma are critical in the formation of exaggerated perceptions of vulnerability as are dysfunctional coping styles and low social support. Women with these characteristics should be targeted for intervention to prevent poor parenting practices that result from exaggerated perceptions of vulnerability.

Potential for malaria seasonal forecasting in Africa

NASA Astrophysics Data System (ADS)

Tompkins, Adrian; Di Giuseppe, Francesca; Colon-Gonzalez, Felipe; Namanya, Didas; Friday, Agabe

2014-05-01

As monthly and seasonal dynamical prediction systems have improved their skill in the tropics over recent years, there is now the potential to use these forecasts to drive dynamical malaria modelling systems to provide early warnings in epidemic and meso-endemic regions. We outline a new pilot operational system that has been developed at ECMWF and ICTP. It uses a precipitation bias correction methodology to seamlessly join the monthly ensemble prediction system (EPS) and seasonal (system 4) forecast systems of ECMWF together. The resulting temperature and rainfall forecasts for Africa are then used to drive the recently developed ICTP malaria model known as VECTRI. The resulting coupled system of ECMWF climate forecasts and VECTRI thus produces predictions of malaria prevalence rates and transmission intensity across Africa. The forecasts are filtered to highlight the regions and months in which the system has particular value due to high year to year variability. In addition to epidemic areas, these also include meso and hyper-endemic regions which undergo considerable variability in the onset months. We demonstrate the limits of the forecast skill as a function of lead-time, showing that for many areas the dynamical system can add one to two months additional warning time to a system based on environmental monitoring. We then evaluate the past forecasts against district level case data in Uganda and show that when interventions can be discounted, the system can show significant skill at predicting interannual variability in transmission intensity up to 3 or 4 months ahead at the district scale. The prospects for a operational implementation will be briefly discussed.

The Relationship Between Grammatical Development and Disfluencies in Preschool Children Who Stutter and Those Who Recover

PubMed Central

Van Horne, Amanda Owen; Zebrowski, Patricia

2017-01-01

Purpose The dual diathesis stressor model indicates that a mismatch between a child's endogenous linguistic abilities and exogenous linguistic contexts is one factor that contributes to stuttering behavior. In the present study, we used a developmental framework to investigate if reducing the gap between endogenous and exogenous linguistics factors would result in less disfluency for typical children, children who recover from stuttering (CWS-R), and children who persist. Method Children between 28 and 43 months of age participated in this study: 8 typical children, 5 CWS-R, and 8 children who persist. The children were followed for 18 months with language samples collected every 6 months. The Index of Productive Syntax (Scarborough, 1990) served as a measure of endogenous grammatical ability. Length and complexity of active declarative sentences served as a measure of exogenous linguistic demand. A hierarchical linear model analysis was conducted using a mixed-model approach. Results The results partially corroborate the dual diathesis stressor model. Disfluencies significantly decreased in CWS-R as grammatical abilities (not age) increased. Language development may serve as a protective factor or catalyst for recovery for CWS-R. As grammatical ability grew and the gap between linguistic ability and demand decreased; however, none of the three groups was more likely to produce disfluencies in longer and more complex utterances. PMID:27936278

Using an Adoption Design to Separate Genetic, Prenatal, and Temperament Influences on Toddler Executive Function

PubMed Central

Leve, Leslie D.; DeGarmo, David S.; Bridgett, David J.; Neiderhiser, Jenae M.; Shaw, Daniel S.; Harold, Gordon T.; Natsuaki, Misaki N.; Reiss, David

2012-01-01

Poor executive functioning has been implicated in children’s concurrent and future behavioral difficulties, making work aimed at understanding processes related to the development of early executive function (EF) critical for models of developmental psychopathology. Deficits in EF have been associated with adverse prenatal experiences, genetic influences, and temperament characteristics. However, our ability to disentangle the predictive and independent effects of these influences has been limited by a dearth of genetically-informed research designs that also consider prenatal influences. The present study examined EF and language development in a sample of 361 toddlers who were adopted at birth and reared in non-relative adoptive families. Predictors included genetic influences (as inherited from birth mothers), prenatal risk, and growth in child negative emotionality. Structural equation modeling indicated that the effect of prenatal risk on toddler effortful attention at age 27 months became nonsignificant once genetic influences were considered in the model. In addition, genetic influences had unique effects on toddler effortful attention. Latent growth modeling indicated that increases in toddler negative emotionality from 9 to 27 months were associated with poorer delay of gratification and poorer language development. Similar results were obtained in models incorporating birth father data. Mechanisms of intergenerational transmission of EF deficits are discussed. PMID:22799580

Using an adoption design to separate genetic, prenatal, and temperament influences on toddler executive function.

PubMed

Leve, Leslie D; DeGarmo, David S; Bridgett, David J; Neiderhiser, Jenae M; Shaw, Daniel S; Harold, Gordon T; Natsuaki, Misaki N; Reiss, David

2013-06-01

Poor executive functioning has been implicated in children's concurrent and future behavioral difficulties, making work aimed at understanding processes related to the development of early executive function (EF) critical for models of developmental psychopathology. Deficits in EF have been associated with adverse prenatal experiences, genetic influences, and temperament characteristics. However, our ability to disentangle the predictive and independent effects of these influences has been limited by a dearth of genetically informed research designs that also consider prenatal influences. The present study examined EF and language development in a sample of 361 toddlers who were adopted at birth and reared in nonrelative adoptive families. Predictors included genetic influences (as inherited from birth mothers), prenatal risk, and growth in child negative emotionality. Structural equation modeling indicated that the effect of prenatal risk on toddler effortful attention at age 27 months became nonsignificant once genetic influences were considered in the model. In addition, genetic influences had unique effects on toddler effortful attention. Latent growth modeling indicated that increases in toddler negative emotionality from 9 to 27 months were associated with poorer delay of gratification and poorer language development. Similar results were obtained in models incorporating birth father data. Mechanisms of intergenerational transmission of EF deficits are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved

Statistical models for sediment/detritus and dissolved absorption coefficients in coastal waters of the northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Green, Rebecca E.; Gould, Richard W., Jr.; Ko, Dong S.

2008-06-01

We developed statistically-based, optical models to estimate tripton (sediment/detrital) and colored dissolved organic matter (CDOM) absorption coefficients ( a sd, a g) from physical hydrographic and atmospheric properties. The models were developed for northern Gulf of Mexico shelf waters using multi-year satellite and physical data. First, empirical algorithms for satellite-derived a sd and a g were developed, based on comparison with a large data set of cruise measurements from northern Gulf shelf waters; these algorithms were then applied to a time series of ocean color (SeaWiFS) satellite imagery for 2002-2005. Unique seasonal timing was observed in satellite-derived optical properties, with a sd peaking most often in fall/winter on the shelf, in contrast to summertime peaks observed in a g. Next, the satellite-derived values were coupled with the physical data to form multiple regression models. A suite of physical forcing variables were tested for inclusion in the models: discharge from the Mississippi River and Mobile Bay, Alabama; gridded fields for winds, precipitation, solar radiation, sea surface temperature and height (SST, SSH); and modeled surface salinity and currents (Navy Coastal Ocean Model, NCOM). For satellite-derived a sd and a g time series (2002-2004), correlation and stepwise regression analyses revealed the most important physical forcing variables. Over our region of interest, the best predictors of tripton absorption were wind speed, river discharge, and SST, whereas dissolved absorption was best predicted by east-west wind speed, river discharge, and river discharge lagged by 1 month. These results suggest the importance of vertical mixing (as a function of winds and thermal stratification) in controlling a sd distribution patterns over large regions of the shelf, in comparison to advection as the most important control on a g. The multiple linear regression models for estimating a sd and a g were applied on a pixel-by-pixel basis and results were compared to monthly SeaWiFS composite imagery. The models performed well in resolving seasonal and interannual optical variability in model development years (2002-2004) (mean error of 32% for a sd and 29% for a g) and in predicting shelfwide optical patterns in a year independent of model development (2005; mean error of 41% for a sd and 46% for a g). The models provide insight into the dominant processes controlling optical distributions in this region, and they can be used to predict the optical fields from the physical properties at monthly timescales.

Successful Treatment of Passive Fecal Incontinence in an Animal Model Using Engineered Biosphincters: A 3‐Month Follow‐Up Study

PubMed Central

Bohl, Jaime L.; Zakhem, Elie

2017-01-01

Abstract Fecal incontinence (FI) is the involuntary passage of fecal material. Current treatments have limited successful outcomes. The objective of this study was to develop a large animal model of passive FI and to demonstrate sustained restoration of fecal continence using anorectal manometry in this model after implantation of engineered autologous internal anal sphincter (IAS) biosphincters. Twenty female rabbits were used in this study. The animals were divided into three groups: (a) Non‐treated group: Rabbits underwent IAS injury by hemi‐sphincterectomy without treatment. (b) Treated group: Rabbits underwent IAS injury by hemi‐sphincterectomy followed by implantation of autologous biosphincters. (c) Sham group: Rabbits underwent IAS injury by hemi‐sphincterectomy followed by re‐accessing the surgical site followed by immediate closure without implantation of biosphincters. Anorectal manometry was used to measure resting anal pressure and recto‐anal inhibitory reflex (RAIR) at baseline, 1 month post‐sphincterectomy, up to 3 months after implantation and post‐sham. Following sphincterectomy, all rabbits had decreased basal tone and loss of RAIR, indicative of FI. Anal hygiene was also lost in the rabbits. Decreases in basal tone and RAIR were sustained more than 3 months in the non‐treated group. Autologous biosphincters were successfully implanted into eight donor rabbits in the treated group. Basal tone and RAIR were restored at 3 months following biosphincter implantation and were significantly higher compared with rabbits in the non‐treated and sham groups. Histologically, smooth muscle reconstruction and continuity was restored in the treated group compared with the non‐treated group. Results in this study provided promising outcomes for treatment of FI. Results demonstrated the feasibility of developing and validating a large animal model of passive FI. This study also showed the efficacy of the engineered biosphincters to restore fecal continence as demonstrated by manometry. Stem Cells Translational Medicine 2017;6:1795–1802 PMID:28678378

Wise Investment? Modeling Industry Profitability and Risk of Targeted Chemotherapy for Incurable Solid Cancers

PubMed Central

Conter, Henry J.; Chu, Quincy S.C.

2012-01-01

Purpose: Pharmaceutical development involves substantial financial risk. This risk, rising development costs, and the promotion of continued research and development have been cited as major drivers in the progressive increase in drug prices. Currently, cost-effective analyses are being used to determine the value of treatment. However, cost-effective analyses practically function as a threshold for value and do not directly address the rationale for drug prices. We set out to create a functional model for industry price decisions and clarify the minimum acceptable profitability of new drugs. Methods: Assuming that industry should only invest in profitable ventures, we employed a linear cost-volume-profit breakeven analysis to equate initial capital investment and risk and post–drug-approval profits, where drug development represents the bulk of investment. A Markov decision analysis model was also used to define the relationships between investment events risk. A systematic literature search was performed to determine event probabilities, clinical trial costs, and total expenses as inputs into the model. Disease-specific inputs, current market size across regions, and lengths of treatment for cancer types were also included. Results: With development of single novel chemotherapies costing from $802 to $1,042 million (2002 US dollars), pharmaceutical profits should range from $4.3 to $5.2 billion, with an expected rate of return on investment of 11% annually. However, diversification across cancer types for chemotherapy can reduce the minimum required profit to less than $3 billion. For optimal diversification, industry should study four tumor types per drug; however, nonprofit organizations could tolerate eight parallel development tracks to minimize the risk of development failure. Assuming that pharmaceutical companies hold exclusive rights for drug sales for only 5 years after market approval, the minimum required profit per drug per month per patient ranges from $294 for end-stage lung cancer to $3,231 for end-stage renal cell carcinoma. Conclusion: Pharmaceutical development in oncology is costly, with substantial risk, but is also highly profitable. Minimum acceptable profits per drug per month of treatment per patient vary with prevalence of disease, but they should be less than $5,000 per month of treatment in the developed world. Minimum acceptable profits may be lower for treatments with additional efficacy in the earlier stages of a tumor type. However, this type of event could not be statistically modeled. PMID:29447097

Application of the Precipitation-Runoff Modeling System (PRMS) in the Apalachicola-Chattahoochee-Flint River Basin in the southeastern United States

USGS Publications Warehouse

LaFontaine, Jacob H.; Hay, Lauren E.; Viger, Roland J.; Markstrom, Steve L.; Regan, R. Steve; Elliott, Caroline M.; Jones, John W.

2013-01-01

A hydrologic model of the Apalachicola–Chattahoochee–Flint River Basin (ACFB) has been developed as part of a U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center effort to provide integrated science that helps resource managers understand the effect of climate change on a range of ecosystem responses. The hydrologic model was developed as part of the Southeast Regional Assessment Project using the Precipitation Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, and land use on basin hydrology. The ACFB PRMS model simulates streamflow throughout the approximately 50,700 square-kilometer basin on a daily time step for the period 1950–99 using gridded climate forcings of air temperature and precipitation, and parameters derived from spatial data layers of altitude, land cover, soils, surficial geology, depression storage (small water bodies), and data from 56 USGS streamgages. Measured streamflow data from 35 of the 56 USGS streamgages were used to calibrate and evaluate simulated basin streamflow; the remaining gage locations were used for model delineation only. The model matched measured daily streamflow at 31 of the 35 calibration gages with Nash-Sutcliffe Model Efficiency Index (NS) greater than 0.6. Streamflow data for some calibration gages were augmented for regulation and water use effects to represent more natural flow volumes. Time-static parameters describing land cover limited the ability of the simulation to match historical runoff in the more developed subbasins. Overall, the PRMS simulation of the ACFB provides a good representation of basin hydrology on annual and monthly time steps. Calibration subbasins were analyzed by separating the 35 subbasins into five classes based on physiography, land use, and stream type (tributary or mainstem). The lowest NS values were rarely below 0.6, whereas the median NS for all five classes was within 0.74 to 0.96 for annual mean streamflow, 0.89 to 0.98 for mean monthly streamflow, and 0.82 to 0.98 for monthly mean streamflow. The median bias for all five classes was within –4.3 to 0.8 percent for annual mean streamflow, –6.3 to 0.5 percent for mean monthly streamflow, and –9.3 to 1.3 percent for monthly mean streamflow. The NS results combined with the percent bias results indicated a good to very good streamflow volume simulation for all subbasins. This simulation of the ACFB provides a foundation for future modeling and interpretive studies. Streamflow and other components of the hydrologic cycle simulated by PRMS can be used to inform other types of simulations; water-temperature, hydrodynamic, and ecosystem-dynamics simulations are three examples. In addition, possible future hydrologic conditions could be studied using this model in combination with land cover projections and downscaled general circulation model results.

A hybrid least squares support vector machines and GMDH approach for river flow forecasting

NASA Astrophysics Data System (ADS)

Samsudin, R.; Saad, P.; Shabri, A.

2010-06-01

This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

Comparison of CEAS and Williams-type models for spring wheat yields in North Dakota and Minnesota

NASA Technical Reports Server (NTRS)

Barnett, T. L. (Principal Investigator)

1982-01-01

The CEAS and Williams-type yield models are both based on multiple regression analysis of historical time series data at CRD level. The CEAS model develops a separate relation for each CRD; the Williams-type model pools CRD data to regional level (groups of similar CRDs). Basic variables considered in the analyses are USDA yield, monthly mean temperature, monthly precipitation, and variables derived from these. The Williams-type model also used soil texture and topographic information. Technological trend is represented in both by piecewise linear functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test of each model (1970-1979) demonstrate that the models are very similar in performance in all respects. Both models are about equally objective, adequate, timely, simple, and inexpensive. Both consider scientific knowledge on a broad scale but not in detail. Neither provides a good current measure of modeled yield reliability. The CEAS model is considered very slightly preferable for AgRISTARS applications.

Two levels ARIMAX and regression models for forecasting time series data with calendar variation effects

NASA Astrophysics Data System (ADS)

Suhartono, Lee, Muhammad Hisyam; Prastyo, Dedy Dwi

2015-12-01

The aim of this research is to develop a calendar variation model for forecasting retail sales data with the Eid ul-Fitr effect. The proposed model is based on two methods, namely two levels ARIMAX and regression methods. Two levels ARIMAX and regression models are built by using ARIMAX for the first level and regression for the second level. Monthly men's jeans and women's trousers sales in a retail company for the period January 2002 to September 2009 are used as case study. In general, two levels of calendar variation model yields two models, namely the first model to reconstruct the sales pattern that already occurred, and the second model to forecast the effect of increasing sales due to Eid ul-Fitr that affected sales at the same and the previous months. The results show that the proposed two level calendar variation model based on ARIMAX and regression methods yields better forecast compared to the seasonal ARIMA model and Neural Networks.

Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels

EIA Publications

2003-01-01

This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using Organization for Economic Cooperation and Development (OECD) petroleum inventory levels.

Bimanual Behaviours in Children Aged 8-18 Months: A Literature Review to Select Toys that Elicit the Use of Two Hands

ERIC Educational Resources Information Center

Greaves, Susan; Imms, Christine; Krumlinde-Sundholm, Lena; Dodd, Karen; Eliasson, Ann-Christin

2012-01-01

Toys that provoke the use of both hands are required to develop a test of bimanual performance in children 8-18 months with unilateral cerebral palsy (Mini-AHA). To choose the toys, a conceptual model based on perception-action theory and object use was used to guide a literature review. Evidence was sought for three critical relationships…

An appraisal of drug development timelines in the Era of precision oncology

PubMed Central

Jardim, Denis Leonardo; Schwaederle, Maria; Hong, David S.; Kurzrock, Razelle

2016-01-01

The effects of incorporating a biomarker-based (personalized or precision) selection strategy on drug development timelines for new oncology drugs merit investigation. Here we accessed documents from the Food and Drug Administration (FDA) database for anticancer agents approved between 09/1998 and 07/2014 to compare drugs developed with and without a personalized strategy. Sixty-three drugs were included (28 [44%] personalized and 35 [56%] non-personalized). No differences in access to FDA-expedited programs were observed between personalized and non-personalized drugs. A personalized approach for drug development was associated with faster clinical development (Investigational New Drug [IND] to New Drug Application [NDA] submission; median = 58.8 months [95% CI 53.8–81.8] vs. 93.5 months [95% CI 73.9–112.9], P =.001), but a similar approval time (NDA submission to approval; median=6.0 months [95% CI 5.5–8.4] vs. 6.1 months [95% CI 5.9–8.3], P = .756) compared to a non-personalized strategy. In the multivariate model, class of drug stratified by personalized status (targeted personalized vs. targeted non-personalized vs. cytotoxic) was the only independent factor associated with faster total time of clinical drug development (clinical plus approval phase, median = 64.6 vs 87.1 vs. 112.7 months [cytotoxic], P = .038). Response rates (RR) in early trials were positively correlated with RR in registration trials (r = 0.63, P = <.001), and inversely associated with total time of drug development (r = −0.29, P = .049). In conclusion, targeted agents were developed faster than cytotoxic agents. Shorter times to approval were associated, in multivariate analysis, with a biomarker-based clinical development strategy. PMID:27419632

Modeling and predicting intertidal variations of the salinity field in the Bay/Delta

USGS Publications Warehouse

Knowles, Noah; Uncles, Reginald J.

1995-01-01

One approach to simulating daily to monthly variability in the bay is the development of intertidal model using tidally-averaged equations and a time step on the order of the day.  An intertidal numerical model of the bay's physics, capable of portraying seasonal and inter-annual variability, would have several uses.  Observations are limited in time and space, so simulation could help fill the gaps.  Also, the ability to simulate multi-year episodes (eg, an extended drought) could provide insight into the response of the ecosystem to such events.  Finally, such a model could be used in a forecast mode wherein predicted delta flow is used as model input, and predicted salinity distribution is output with estimates days and months in advance.  This note briefly introduces such a tidally-averaged model (Uncles and Peterson, in press) and a corresponding predictive scheme for baywide forecasting.

Development of a Rabbit Model of Radiation-Induced Sciatic Nerve Injury: In Vivo Evaluation Using T2 Relaxation Time Measurements.

PubMed

Wan, Qi; Zeng, Qian; Li, Xinchun; Sun, Chongpeng; Zhou, Jiaxuan; Zou, Qiao; Deng, Yingshi; Niu, Daoli

2015-01-01

To develop a rabbit model of radiation-induced sciatic nerve injury (RISNI), using computed tomography (CT)-guided stereotactic radiosurgery, and assess the value of T2 measurements of injured nerves. Twenty New Zealand rabbits were randomly divided into A (n = 5) and B (n = 15) groups. Group A rabbits underwent CT and magnetic resonance scan and were then killed for comparison of images and anatomy of sciatic nerves. One side of the sciatic nerve of group B rabbits received irradiation doses of 35, 50, or 70 Gy (n = 5 per group). Magnetic resonance imaging and functional assessments were performed before irradiation and 1, 2, 3, and 4 months thereafter. The thigh section of the sciatic nerve outside the pelvis could be observed by CT and magnetic resonance imaging. T2 values of the irradiated nerve of the 35-Gy group increased gradually, peaking at 4 months; T2 values of the 50-Gy group increased faster, peaking at 3 months. Significant differences between the 35-Gy and control groups were found at 3 and 4 months, and between the 50-Gy and control groups at 2, 3, and 4 months. Functional scores of the 50-Gy group declined progressively, whereas the 35-Gy group scores reached a low point at 3 months posttreatment and then recovered. Functional scores of the irradiated limbs demonstrated a negative correlation with T2 values (r = -0.591 and -0.595, P < 0.05). Electron microscopy revealed progressive deformation and degeneration of the irradiated nerve in the 35- and 50-Gy groups, which were more severe in the 50-Gy group. A rabbit RISNI model can be produced using the midthigh segment of the sciatic nerve and single-fraction doses of 35 and 50 Gy. Although T2 values are useful for monitoring RISNI, they may not be sensitive enough to evaluate its severity.

Functional Deficits Precede Structural Lesions in Mice With High-Fat Diet-Induced Diabetic Retinopathy.

PubMed

Rajagopal, Rithwick; Bligard, Gregory W; Zhang, Sheng; Yin, Li; Lukasiewicz, Peter; Semenkovich, Clay F

2016-04-01

Obesity predisposes to human type 2 diabetes, the most common cause of diabetic retinopathy. To determine if high-fat diet-induced diabetes in mice can model retinal disease, we weaned mice to chow or a high-fat diet and tested the hypothesis that diet-induced metabolic disease promotes retinopathy. Compared with controls, mice fed a diet providing 42% of energy as fat developed obesity-related glucose intolerance by 6 months. There was no evidence of microvascular disease until 12 months, when trypsin digests and dye leakage assays showed high fat-fed mice had greater atrophic capillaries, pericyte ghosts, and permeability than controls. However, electroretinographic dysfunction began at 6 months in high fat-fed mice, manifested by increased latencies and reduced amplitudes of oscillatory potentials compared with controls. These electroretinographic abnormalities were correlated with glucose intolerance. Unexpectedly, retinas from high fat-fed mice manifested striking induction of stress kinase and neural inflammasome activation at 3 months, before the development of systemic glucose intolerance, electroretinographic defects, or microvascular disease. These results suggest that retinal disease in the diabetic milieu may progress through inflammatory and neuroretinal stages long before the development of vascular lesions representing the classic hallmark of diabetic retinopathy, establishing a model for assessing novel interventions to treat eye disease. © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Modeling physical and chemical climate of the northeastern United States for a geographic information system

Treesearch

Scott V. Ollinger; John D. Aber; Anthony C. Federer; Gary M. Lovett; Jennifer M. Ellis

1995-01-01

A model of physical and chemical climate was developed for New York and New England that can be used in a GIs for integration with ecosystem models. The variables included are monthly average maximum and minimum daily temperatures, precipitation, humidity, and solar radiation, as well as annual atmospheric deposition of sulfur and nitrogen. Equations generated from...

Testing Alternative Hypotheses Regarding the Association Between Behavioral Inhibition and Language Development in Toddlerhood

PubMed Central

Watts, Ashley K. Smith; Patel, Deepika; Corley, Robin P.; Friedman, Naomi P.; Hewitt, John K.; Robinson, JoAnn L.; Rhee, Soo H.

2014-01-01

Studies have reported an inverse association between language development and behavioral inhibition or shyness across childhood, but the direction of this association is unclear. The present study tested alternative hypotheses regarding this association in a large sample of toddlers. Data on behavioral inhibition and expressive and receptive language abilities were collected from 816 twins at ages 14, 20, and 24 months. Growth and regression models were fit to the data to assess the longitudinal associations between behavioral inhibition and language development from 14 to 24 months. Overall, there were significant associations between behavioral inhibition and expressive language, and minimal associations with receptive language, indicating that the association is better explained by reticence to respond rather than deficient language development. PMID:24499266

Comparison of two statistical methods for probability prediction of monthly precipitation during summer over Huaihe River Basin in China, and applications in runoff prediction based on hydrological model

NASA Astrophysics Data System (ADS)

Liu, L.; Du, L.; Liao, Y.

2017-12-01

Based on the ensemble hindcast dataset of CSM1.1m by NCC, CMA, Bayesian merging models and a two-step statistical model are developed and employed to predict monthly grid/station precipitation in the Huaihe River China during summer at the lead-time of 1 to 3 months. The hindcast datasets span a period of 1991 to 2014. The skill of the two models is evaluated using area under the ROC curve (AUC) in a leave-one-out cross-validation framework, and is compared to the skill of CSM1.1m. CSM1.1m has highest skill for summer precipitation from April while lowest from May, and has highest skill for precipitation in June but lowest for precipitation in July. Compared with raw outputs of climate models, some schemes of the two approaches have higher skill for the prediction from March and May, but almost schemes have lower skill for prediction from April. Compared to two-step approach, one sampling scheme of Bayesian merging approach has higher skill for the prediction from March, but has lower skill from May. The results suggest that there is potential to apply the two statistical models for monthly precipitation forecast in summer from March and from May over Huaihe River basin, but is potential to apply CSM1.1m forecast from April. Finally, the summer runoff during 1991 to 2014 is simulated based on one hydrological model using the climate hindcast of CSM1.1m and the two statistical models.

Research and development program for the development of advanced time-temperature dependent constitutive relationships. Volume 2: Programming manual

NASA Technical Reports Server (NTRS)

Cassenti, B. N.

1983-01-01

The results of a 10-month research and development program for nonlinear structural modeling with advanced time-temperature constitutive relationships are presented. The implementation of the theory in the MARC nonlinear finite element code is discussed, and instructions for the computational application of the theory are provided.

Breast cancer in older women: quality of life and psychosocial adjustment in the 15 months after diagnosis.

PubMed

Ganz, Patricia A; Guadagnoli, Edward; Landrum, Mary Beth; Lash, Timothy L; Rakowski, William; Silliman, Rebecca A

2003-11-01

We examined the health-related quality of life (QOL) of a cohort of older women with breast cancer after their diagnosis. Six hundred ninety-one women aged 65 years and older were interviewed approximately 3 months after breast cancer surgery and two additional times in the following year using standardized QOL measures. Demographic factors, breast cancer treatments, and comorbid conditions were used to model ratings of health-related QOL over time. Self-perceived health and psychosocial adjustment at 15 months after surgery were modeled. Physical and mental health scores declined significantly in the follow-up year, independent of age. However, a cancer-specific psychosocial instrument showed significant improvement in scores. Better 3-month physical and mental health scores, as well as better emotional social support, predicted more favorable self-perceived health 15 months after surgery. Psychosocial adjustment at 15 months was significantly predicted by better mental health, emotional social support, and better self-rated interaction with health care providers assessed at 3 months. Contrary to reports from younger women with breast cancer, we observed significant declines in the physical and mental health of older women in the 15 months after breast cancer surgery, whereas scores on a cancer-specific psychosocial QOL measure improved over time, consistent with patterns in younger women. Predictive models indicate that older women with impaired physical functioning, mental health, and emotional social support after surgery have poorer self-perceived health and psychosocial adjustment 1 year later. Interventions to address the physical and emotional needs of older women with breast cancer should be developed and evaluated to determine their impact on subsequent health-related QOL.

Seasonal predictions of precipitation in the Aksu-Tarim River basin for improved water resources management

NASA Astrophysics Data System (ADS)

Hartmann, Heike; Snow, Julie A.; Su, Buda; Jiang, Tong

2016-12-01

Since the 1950s, the population in the arid to hyperarid Tarim River basin has grown rapidly concurrent with an expansion of irrigated agriculture. This threatens the Tarim River basin's natural ecosystems and causes water shortages, even though increased discharges in the headwaters have been observed more recently. These increases have mainly been attributed to receding glaciers and are projected to cease when the glaciers are unable to provide sufficient amounts of meltwater. Under these circumstances water management will face a serious challenge in adapting its strategies to changes in river discharge, which to a greater extent will depend on changes in precipitation. In this paper, we aim to develop accurate seasonal predictions of precipitation to improve water resources management. Possible predictors of precipitation for the Tarim River basin were either downloaded directly or calculated using NCEP/NCAR Reanalysis 1 and NOAA Extended Reconstructed Sea Surface Temperature (SST) V3b data in monthly resolution. To evaluate the significance of the predictors, they were then correlated with the monthly precipitation dataset GPCCv6 extracted for the Tarim River basin for the period 1961 to 2010. Prior to the Spearman rank correlation analyses, the precipitation data were averaged over the subbasins of the Tarim River. The strongest correlations were mainly detected with lead times of four and five months. Finally, an artificial neural network model, namely a multilayer perceptron (MLP), and a multiple linear regression (LR) model were developed each in two different configurations for the Aksu River subbasin, predicting precipitation five months in advance. Overall, the MLP using all predictors shows the best performance. The performance of both models drops only slightly when restricting the model input to the SST of the Black Sea and the Siberian High Intensity (SHI) pointing towards their importance as predictors.

Striatal Synaptic Dysfunction and Hippocampal Plasticity Deficits in the Hu97/18 Mouse Model of Huntington Disease

PubMed Central

Kolodziejczyk, Karolina; Parsons, Matthew P.; Southwell, Amber L.; Hayden, Michael R.; Raymond, Lynn A.

2014-01-01

Huntington disease (HD) is a fatal neurodegenerative disorder caused by a CAG repeat expansion in the gene (HTT) encoding the huntingtin protein (HTT). This mutation leads to multiple cellular and synaptic alterations that are mimicked in many current HD animal models. However, the most commonly used, well-characterized HD models do not accurately reproduce the genetics of human disease. Recently, a new ‘humanized’ mouse model, termed Hu97/18, has been developed that genetically recapitulates human HD, including two human HTT alleles, no mouse Hdh alleles and heterozygosity of the HD mutation. Previously, behavioral and neuropathological testing in Hu97/18 mice revealed many features of HD, yet no electrophysiological measures were employed to investigate possible synaptic alterations. Here, we describe electrophysiological changes in the striatum and hippocampus of the Hu97/18 mice. At 9 months of age, a stage when cognitive deficits are fully developed and motor dysfunction is also evident, Hu97/18 striatal spiny projection neurons (SPNs) exhibited small changes in membrane properties and lower amplitude and frequency of spontaneous excitatory postsynaptic currents (sEPSCs); however, release probability from presynaptic terminals was unaltered. Strikingly, these mice also exhibited a profound deficiency in long-term potentiation (LTP) at CA3-to-CA1 synapses. In contrast, at 6 months of age we found only subtle alterations in SPN synaptic transmission, while 3-month old animals did not display any electrophysiologically detectable changes in the striatum and CA1 LTP was intact. Together, these data reveal robust, progressive deficits in synaptic function and plasticity in Hu97/18 mice, consistent with previously reported behavioral abnormalities, and suggest an optimal age (9 months) for future electrophysiological assessment in preclinical studies of HD. PMID:24728353

Application of satellite precipitation data to analyse and model arbovirus activity in the tropics

PubMed Central

2011-01-01

Background Murray Valley encephalitis virus (MVEV) is a mosquito-borne Flavivirus (Flaviviridae: Flavivirus) which is closely related to Japanese encephalitis virus, West Nile virus and St. Louis encephalitis virus. MVEV is enzootic in northern Australia and Papua New Guinea and epizootic in other parts of Australia. Activity of MVEV in Western Australia (WA) is monitored by detection of seroconversions in flocks of sentinel chickens at selected sample sites throughout WA. Rainfall is a major environmental factor influencing MVEV activity. Utilising data on rainfall and seroconversions, statistical relationships between MVEV occurrence and rainfall can be determined. These relationships can be used to predict MVEV activity which, in turn, provides the general public with important information about disease transmission risk. Since ground measurements of rainfall are sparse and irregularly distributed, especially in north WA where rainfall is spatially and temporally highly variable, alternative data sources such as remote sensing (RS) data represent an attractive alternative to ground measurements. However, a number of competing alternatives are available and careful evaluation is essential to determine the most appropriate product for a given problem. Results The Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 product was chosen from a range of RS rainfall products to develop rainfall-based predictor variables and build logistic regression models for the prediction of MVEV activity in the Kimberley and Pilbara regions of WA. Two models employing monthly time-lagged rainfall variables showed the strongest discriminatory ability of 0.74 and 0.80 as measured by the Receiver Operating Characteristics area under the curve (ROC AUC). Conclusions TMPA data provide a state-of-the-art data source for the development of rainfall-based predictive models for Flavivirus activity in tropical WA. Compared to ground measurements these data have the advantage of being collected spatially regularly, irrespective of remoteness. We found that increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Pilbara at a time-lag of two months. Increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Kimberley at a lag of three months. PMID:21255449

Benzene patterns in different urban environments and a prediction model for benzene rates based on NOx values

NASA Astrophysics Data System (ADS)

Paz, Shlomit; Goldstein, Pavel; Kordova-Biezuner, Levana; Adler, Lea

2017-04-01

Exposure to benzene has been associated with multiple severe impacts on health. This notwithstanding, at most monitoring stations, benzene is not monitored on a regular basis. The aims of the study were to compare benzene rates in different urban environments (region with heavy traffic and industrial region), to analyse the relationship between benzene and meteorological parameters in a Mediterranean climate type, to estimate the linkages between benzene and NOx and to suggest a prediction model for benzene rates based on NOx levels in order contribute to a better estimation of benzene. Data were used from two different monitoring stations, located on the eastern Mediterranean coast: 1) a traffic monitoring station in Tel Aviv, Israel (TLV) located in an urban region with heavy traffic; 2) a general air quality monitoring station in Haifa Bay (HIB), located in Israel's main industrial region. At each station, hourly, daily, monthly, seasonal, and annual data of benzene, NOx, mean temperature, relative humidity, inversion level, and temperature gradient were analysed over three years: 2008, 2009, and 2010. A prediction model for benzene rates based on NOx levels (which are monitored regularly) was developed to contribute to a better estimation of benzene. The severity of benzene pollution was found to be considerably higher at the traffic monitoring station (TLV) than at the general air quality station (HIB), despite the location of the latter in an industrial area. Hourly, daily, monthly, seasonal, and annual patterns have been shown to coincide with anthropogenic activities (traffic), the day of the week, and atmospheric conditions. A strong correlation between NOx and benzene allowed the development of a prediction model for benzene rates, based on NOx, the day of the week, and the month. The model succeeded in predicting the benzene values throughout the year (except for September). The severity of benzene pollution was found to be considerably higher at the traffic station (TLV) than at the general air quality station (HIB), despite being located in an industrial area. Hourly, daily, seasonal, and annual patterns of benzene rates have been shown to coincide with anthropogenic activities (traffic), day of the week, and atmospheric conditions. A prediction model for benzene rates was developed, based on NOx, the day of the week, and the month. The model suggested in this study might be useful for identifying potential risk of benzene in other urban environments.

Building the Workforce of the Future

ERIC Educational Resources Information Center

González-Rivera, Christian

2016-01-01

"Building the Workforce of the Future" is an in-depth, independent report on the first eighteen months of Career Pathways, New York City's sweeping new strategy for workforce development. In November 2014, Mayor de Blasio launched a sweeping new approach to workforce development in New York City. Unlike the previous model, which…

Association between feeding difficulties and language delay in preterm infants using Bayley Scales of Infant Development-Third Edition.

PubMed

Adams-Chapman, Ira; Bann, Carla M; Vaucher, Yvonne E; Stoll, Barbara J

2013-09-01

To evaluate the relationship between abnormal feeding patterns and language performance on the Bayley Scales of Infant Development-Third Edition at 18-22 months adjusted age among a cohort of extremely premature infants. This is a descriptive analysis of 1477 preterm infants born ≤ 26 weeks gestation or enrolled in a clinical trial between January 1, 2006 and March 18, 2008 at a National Institute of Child Health and Human Development Neonatal Research Network center who completed the 18-month neurodevelopmental follow-up assessment. At 18-22 months adjusted age, a comprehensive neurodevelopmental evaluation was performed by certified examiners including the Receptive and Expressive Language Subscales of the Bayley Scales of Infant Development-Third Edition and a standardized adjusted age feeding behaviors and nutritional intake. Data were analyzed using bivariate and multilevel linear and logistic regression modeling. Abnormal feeding behaviors were reported in 193 (13%) of these infants at 18-22 months adjusted age. Abnormal feeding patterns, days of mechanical ventilation, hearing impairment, and Gross Motor Functional Classification System level ≥ 2 each independently predicted lower composite language scores. At 18 months adjusted age, premature infants with a history of feeding difficulties are more likely to have language delay. Neuromotor impairment and days of mechanical ventilation are both important risk factors associated with these outcomes. Copyright © 2013 Mosby, Inc. All rights reserved.

Feasibility of dynamic risk prediction for hepatocellular carcinoma development in patients with chronic hepatitis B.

PubMed

Jeon, Mi Young; Lee, Hye Won; Kim, Seung Up; Kim, Beom Kyung; Park, Jun Yong; Kim, Do Young; Han, Kwang-Hyub; Ahn, Sang Hoon

2018-04-01

Several risk prediction models for hepatocellular carcinoma (HCC) development are available. We explored whether the use of risk prediction models can dynamically predict HCC development at different time points in chronic hepatitis B (CHB) patients. Between 2006 and 2014, 1397 CHB patients were recruited. All patients underwent serial transient elastography at intervals of >6 months. The median age of this study population (931 males and 466 females) was 49.0 years. The median CU-HCC, REACH-B, LSM-HCC and mREACH-B score at enrolment were 4.0, 9.0, 10.0 and 8.0 respectively. During the follow-up period (median, 68.0 months), 87 (6.2%) patients developed HCC. All risk prediction models were successful in predicting HCC development at both the first liver stiffness (LS) measurement (hazard ratio [HR] = 1.067-1.467 in the subgroup without antiviral therapy [AVT] and 1.096-1.458 in the subgroup with AVT) and second LS measurement (HR = 1.125-1.448 in the subgroup without AVT and 1.087-1.249 in the subgroup with AVT). In contrast, neither the absolute nor percentage change in the scores from the risk prediction models predicted HCC development (all P > .05). The mREACH-B score performed similarly or significantly better than did the other scores (AUROCs at 5 years, 0.694-0.862 vs 0.537-0.875). Dynamic prediction of HCC development at different time points was achieved using four risk prediction models, but not using the changes in the absolute and percentage values between two time points. The mREACH-B score was the most appropriate prediction model of HCC development among four prediction models. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Simulation of groundwater level variations using wavelet combined with neural network, linear regression and support vector machine

NASA Astrophysics Data System (ADS)

Ebrahimi, Hadi; Rajaee, Taher

2017-01-01

Simulation of groundwater level (GWL) fluctuations is an important task in management of groundwater resources. In this study, the effect of wavelet analysis on the training of the artificial neural network (ANN), multi linear regression (MLR) and support vector regression (SVR) approaches was investigated, and the ANN, MLR and SVR along with the wavelet-ANN (WNN), wavelet-MLR (WLR) and wavelet-SVR (WSVR) models were compared in simulating one-month-ahead of GWL. The only variable used to develop the models was the monthly GWL data recorded over a period of 11 years from two wells in the Qom plain, Iran. The results showed that decomposing GWL time series into several sub-time series, extremely improved the training of the models. For both wells 1 and 2, the Meyer and Db5 wavelets produced better results compared to the other wavelets; which indicated wavelet types had similar behavior in similar case studies. The optimal number of delays was 6 months, which seems to be due to natural phenomena. The best WNN model, using Meyer mother wavelet with two decomposition levels, simulated one-month-ahead with RMSE values being equal to 0.069 m and 0.154 m for wells 1 and 2, respectively. The RMSE values for the WLR model were 0.058 m and 0.111 m, and for WSVR model were 0.136 m and 0.060 m for wells 1 and 2, respectively.

Forecasting paediatric malaria admissions on the Kenya Coast using rainfall.

PubMed

Karuri, Stella Wanjugu; Snow, Robert W

2016-01-01

Malaria is a vector-borne disease which, despite recent scaled-up efforts to achieve control in Africa, continues to pose a major threat to child survival. The disease is caused by the protozoan parasite Plasmodium and requires mosquitoes and humans for transmission. Rainfall is a major factor in seasonal and secular patterns of malaria transmission along the East African coast. The goal of the study was to develop a model to reliably forecast incidences of paediatric malaria admissions to Kilifi District Hospital (KDH). In this article, we apply several statistical models to look at the temporal association between monthly paediatric malaria hospital admissions, rainfall, and Indian Ocean sea surface temperatures. Trend and seasonally adjusted, marginal and multivariate, time-series models for hospital admissions were applied to a unique data set to examine the role of climate, seasonality, and long-term anomalies in predicting malaria hospital admission rates and whether these might become more or less predictable with increasing vector control. The proportion of paediatric admissions to KDH that have malaria as a cause of admission can be forecast by a model which depends on the proportion of malaria admissions in the previous 2 months. This model is improved by incorporating either the previous month's Indian Ocean Dipole information or the previous 2 months' rainfall. Surveillance data can help build time-series prediction models which can be used to anticipate seasonal variations in clinical burdens of malaria in stable transmission areas and aid the timing of malaria vector control.

A syngeneic glioma model to assess the impact of neural progenitor target cell age on tumor malignancy

PubMed Central

Mikheev, Andrei M; Stoll, Elizabeth A; Mikheeva, Svetlana A; Maxwell, John-Patrick; Jankowski, Pawel P; Ray, Sutapa; Uo, Takuma; Morrison, Richard S; Horner, Philip J; Rostomily, Robert C

2010-01-01

Summary Human glioma incidence, malignancy and treatment resistance are directly proportional to patient age. Cell intrinsic factors are reported to contribute to human age-dependent glioma malignancy but suitable animal models to examine the role of aging are lacking. Here we developed an orthotopic syngeneic glioma model to test the hypothesis that the age of neural progenitor cells (NPCs), presumed cells of glioma origin, influences glioma malignancy. Gliomas generated from transformed donor 3-, 12-, and 18-month-old NPCs in same-aged adult hosts all formed highly invasive glial tumors that phenocopied the human disease. Survival analysis indicated increased malignancy of gliomas generated from older 12- and 18-month-old transformed NPCs compared with their 3-month counterparts (median survival of 38.5 and 42.5 vs. 77 days, respectively). This study showed for the first time that age of target cells at the time of transformation can affect malignancy and demonstrated the feasibility of a syngeneic model using transformed NPCs for future examination of the relative impacts of age-related cell intrinsic and cell-extrinsic factors in glioma malignancy. PMID:19489742

The developmental course of salivary alpha-amylase and cortisol from 12 to 36 months: Relations with early poverty and later behavior problems.

PubMed

Hill-Soderlund, Ashley L; Holochwost, Steven J; Willoughby, Michael T; Granger, Douglas A; Gariépy, Jean-Louis; Mills-Koonce, W Roger; Cox, Martha J

2015-02-01

This study examined the development of baseline autonomic nervous system (ANS) and hypothalamic-pituitary-adrenal (HPA) physiological activity from 12 to 36 months as well as antecedents (poverty) and consequents (behavior problems) of individual differences in physiological development. Children (N=179; 50% poor; 56% African American; 52% male) provided saliva samples at 12, 18, 24, 30, and 36 months of age. Latent growth curve models indicated that nonlinear change was evident for both sAA and cortisol, with sAA increasing and cortisol decreasing with age. Children residing in poor households exhibited lower initial levels of sAA, but not cortisol. African-American children showed slightly smaller decreases in cortisol over time. Initial levels of sAA predicted higher levels of internalizing behaviors at 36 months and both initial levels of and total change in sAA predicted higher levels of externalizing behaviors at 36 months. There was no evidence that sAA or cortisol mediated the relationship between poverty and later behavior problems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Putaminal dopamine depletion in de novo Parkinson's disease predicts future development of wearing-off.

PubMed

Chung, Su Jin; Lee, Yoonju; Oh, Jungsu S; Kim, Jae Seung; Lee, Phil Hyu; Sohn, Young H

2018-05-10

The present study aimed to investigate whether the level of presynaptic dopamine neuronal loss predicts future development of wearing-off in de novo Parkinson's disease. This retrospective cohort study included a total of 342 non-demented patients with de novo Parkinson's disease who underwent dopamine transporter positron emission tomography scans at their initial evaluation and received dopaminergic medications for 24 months or longer. Onset of wearing-off was determined based on patients' medical records at their outpatient clinic visits every 3-6 months. Predictive power of dopamine transporter activity in striatal subregions and other clinical factors for the development of wearing-off was evaluated by Cox proportional hazard models. During a median follow-up period of 50.2 ± 18.9 months, 69 patients (20.2%) developed wearing-off. Patients with wearing-off exhibited less dopamine transporter activity in the putamen, particularly the anterior and posterior putamens, compared to those without wearing-off. Multivariate Cox proportional hazard models revealed that dopamine transporter activities of the anterior (hazard ratio 0.556; p = 0.008) and whole putamens (hazard ratio 0.504; p = 0.025) were significant predictors of development of wearing-off. In addition, younger age at onset of Parkinson's disease, lower body weight, and a motor phenotype of postural instability/gait disturbance were also significant predictors for development of wearing-off. The present results provide in vivo evidence to support the hypothesis that presynaptic dopamine neuronal loss, particularly in the anterior putamen, leads to development of wearing-off in Parkinson's disease. Copyright © 2018. Published by Elsevier Ltd.

Birth month affects lifetime disease risk: a phenome-wide method.

PubMed

Boland, Mary Regina; Shahn, Zachary; Madigan, David; Hripcsak, George; Tatonetti, Nicholas P

2015-09-01

An individual's birth month has a significant impact on the diseases they develop during their lifetime. Previous studies reveal relationships between birth month and several diseases including atherothrombosis, asthma, attention deficit hyperactivity disorder, and myopia, leaving most diseases completely unexplored. This retrospective population study systematically explores the relationship between seasonal affects at birth and lifetime disease risk for 1688 conditions. We developed a hypothesis-free method that minimizes publication and disease selection biases by systematically investigating disease-birth month patterns across all conditions. Our dataset includes 1 749 400 individuals with records at New York-Presbyterian/Columbia University Medical Center born between 1900 and 2000 inclusive. We modeled associations between birth month and 1688 diseases using logistic regression. Significance was tested using a chi-squared test with multiplicity correction. We found 55 diseases that were significantly dependent on birth month. Of these 19 were previously reported in the literature (P < .001), 20 were for conditions with close relationships to those reported, and 16 were previously unreported. We found distinct incidence patterns across disease categories. Lifetime disease risk is affected by birth month. Seasonally dependent early developmental mechanisms may play a role in increasing lifetime risk of disease. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Reducing absenteeism in hospital cleaning staff: pilot of a theory based intervention.

PubMed

Michie, S; Wren, B; Williams, S

2004-04-01

To develop, pilot, and evaluate a workplace intervention to reduce sickness absence, based on a demand-control-support model of job strain. Changes in the working arrangements of hospital cleaning staff were introduced with the aim of increasing their control over work and the support received at work. The study design was quasi-experimental, with 221 cleaning staff in the intervention group and 91 catering staff in the control group. The dependent variable was the difference in percentage monthly sickness absence between the 12 months preceding and following the intervention. Differences in sickness absence between staff groups for each month after the intervention were compared with differences between staff groups for the equivalent month one year prior to it. There was a significant reduction in the difference in sickness absence rates between the intervention and control group of 2.3% in the six months after the intervention, compared to the six months before. The difference was not maintained at 12 months. These results suggest that a workplace intervention aimed at increasing control and support at work has a small effect on reducing sickness absence among hospital cleaning staff in the short term. Future research should seek to replicate this effect in larger, experimental studies, analyse postulated mediators of such theory based interventions, and develop interventions that maintain improvement.

Development of a Precipitation-Runoff Model to Simulate Unregulated Streamflow in the Salmon Creek Basin, Okanogan County, Washington

USGS Publications Warehouse

van Heeswijk, Marijke

2006-01-01

Surface water has been diverted from the Salmon Creek Basin for irrigation purposes since the early 1900s, when the Bureau of Reclamation built the Okanogan Project. Spring snowmelt runoff is stored in two reservoirs, Conconully Reservoir and Salmon Lake Reservoir, and gradually released during the growing season. As a result of the out-of-basin streamflow diversions, the lower 4.3 miles of Salmon Creek typically has been a dry creek bed for almost 100 years, except during the spring snowmelt season during years of high runoff. To continue meeting the water needs of irrigators but also leave water in lower Salmon Creek for fish passage and to help restore the natural ecosystem, changes are being considered in how the Okanogan Project is operated. This report documents development of a precipitation-runoff model for the Salmon Creek Basin that can be used to simulate daily unregulated streamflows. The precipitation-runoff model is a component of a Decision Support System (DSS) that includes a water-operations model the Bureau of Reclamation plans to develop to study the water resources of the Salmon Creek Basin. The DSS will be similar to the DSS that the Bureau of Reclamation and the U.S. Geological Survey developed previously for the Yakima River Basin in central southern Washington. The precipitation-runoff model was calibrated for water years 1950-89 and tested for water years 1990-96. The model was used to simulate daily streamflows that were aggregated on a monthly basis and calibrated against historical monthly streamflows for Salmon Creek at Conconully Dam. Additional calibration data were provided by the snowpack water-equivalent record for a SNOTEL station in the basin. Model input time series of daily precipitation and minimum and maximum air temperatures were based on data from climate stations in the study area. Historical records of unregulated streamflow for Salmon Creek at Conconully Dam do not exist for water years 1950-96. Instead, estimates of historical monthly mean unregulated streamflow based on reservoir outflows and storage changes were used as a surrogate for the missing data and to calibrate and test the model. The estimated unregulated streamflows were corrected for evaporative losses from Conconully Reservoir (about 1 ft3/s) and ground-water losses from the basin (about 2 ft3/s). The total of the corrections was about 9 percent of the mean uncorrected streamflow of 32.2 ft3/s (23,300 acre-ft/yr) for water years 1949-96. For the calibration period, the basinwide mean annual evapotranspiration was simulated to be 19.1 inches, or about 83 percent of the mean annual precipitation of 23.1 inches. Model calibration and testing indicated that the daily streamflows simulated using the precipitation-runoff model should be used only to analyze historical and forecasted annual mean and April-July mean streamflows for Salmon Creek at Conconully Dam. Because of the paucity of model input data and uncertainty in the estimated unregulated streamflows, the model is not adequately calibrated and tested to estimate monthly mean streamflows for individual months, such as during low-flow periods, or for shorter periods such as during peak flows. No data were available to test the accuracy of simulated streamflows for lower Salmon Creek. As a result, simulated streamflows for lower Salmon Creek should be used with caution. For the calibration period (water years 1950-89), both the simulated mean annual streamflow and the simulated mean April-July streamflow compared well with the estimated uncorrected unregulated streamflow (UUS) and corrected unregulated streamflow (CUS). The simulated mean annual streamflow exceeded UUS by 5.9 percent and was less than CUS by 2.7 percent. Similarly, the simulated mean April-July streamflow exceeded UUS by 1.8 percent and was less than CUS by 3.1 percent. However, streamflow was significantly undersimulated during the low-flow, baseflow-dominated months of November through F

Research and development program for non-linear structural modeling with advanced time-temperature dependent constitutive relationships

NASA Technical Reports Server (NTRS)

Walker, K. P.

1981-01-01

Results of a 20-month research and development program for nonlinear structural modeling with advanced time-temperature constitutive relationships are reported. The program included: (1) the evaluation of a number of viscoplastic constitutive models in the published literature; (2) incorporation of three of the most appropriate constitutive models into the MARC nonlinear finite element program; (3) calibration of the three constitutive models against experimental data using Hastelloy-X material; and (4) application of the most appropriate constitutive model to a three dimensional finite element analysis of a cylindrical combustor liner louver test specimen to establish the capability of the viscoplastic model to predict component structural response.

The Vicious Cycle of Family Atmosphere, Interpersonal Self-concepts, and Paranoia in Schizophrenia-A Longitudinal Study.

PubMed

Hesse, Klaus; Kriston, Levente; Mehl, Stephanie; Wittorf, Andreas; Wiedemann, Wolfgang; Wölwer, Wolfgang; Klingberg, Stefan

2015-11-01

Recent cognitive models of paranoid delusions highlight the role of self-concepts in the development and maintenance of paranoia. Evidence is growing that especially interpersonal self-concepts are relevant in the genesis of paranoia. In addition, negative interpersonal life-experiences are supposed to influence the course of paranoia. As dysfunctional family atmosphere corresponds with multiple distressing dyadic experiences, it could be a risk factor for the development and maintenance of paranoia. A total of 160 patients with a diagnosis of schizophrenia were assessed twice within 12 months. Standardized questionnaires and symptom rating scales were used to measure interpersonal self-concepts, perceived family atmosphere, and paranoia. Data were analyzed using longitudinal cross-lagged structural equation models. Perceived negative family atmosphere was associated with the development of more pronounced negative interpersonal self-concepts 12 months later. Moreover, paranoia was related to negative family atmosphere after 12 months as well. As tests revealed that reversed associations were not able to explain the data, we found evidence for a vicious cycle between paranoia, family atmosphere, and interpersonal self-concepts as suggested by theoretical/cognitive model of paranoid delusions. Results suggest that broader interventions for patients and their caretakers that aim at improving family atmosphere might also be able to improve negative self-concepts and paranoia. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Development of Hepatocellular Carcinoma in a Murine Model of Nonalcoholic Steatohepatitis Induced by Use of a High-Fat/Fructose Diet and Sedentary Lifestyle

PubMed Central

Dowman, Joanna K.; Hopkins, Laurence J.; Reynolds, Gary M.; Nikolaou, Nikolaos; Armstrong, Matthew J.; Shaw, Jean C.; Houlihan, Diarmaid D.; Lalor, Patricia F.; Tomlinson, Jeremy W.; Hübscher, Stefan G.; Newsome, Philip N.

2014-01-01

Obesity is increasingly prevalent, strongly associated with nonalcoholic liver disease, and a risk factor for numerous cancers. Here, we describe the liver-related consequences of long-term diet-induced obesity. Mice were exposed to an extended obesity model comprising a diet high in trans-fats and fructose corn syrup concurrent with a sedentary lifestyle. Livers were assessed histologically using the nonalcoholic fatty liver disease (NAFLD) activity score (Kleiner system). Mice in the American Lifestyle-Induced Obesity Syndrome (ALIOS) model developed features of early nonalcoholic steatohepatitis at 6 months (mean NAFLD activity score = 2.4) and features of more advanced nonalcoholic steatohepatitis at 12 months, including liver inflammation and bridging fibrosis (mean NAFLD activity score = 5.0). Hepatic expression of lipid metabolism and insulin signaling genes were increased in ALIOS mice compared with normal chow-fed mice. Progressive activation of the mouse hepatic stem cell niche in response to ALIOS correlated with steatosis, fibrosis, and inflammation. Hepatocellular neoplasms were observed in 6 of 10 ALIOS mice after 12 months. Tumors displayed cytological atypia, absence of biliary epithelia, loss of reticulin, alteration of normal perivenular glutamine synthetase staining (absent or diffuse), and variable α-fetoprotein expression. Notably, perivascular tumor cells expressed hepatic stem cell markers. These studies indicate an adipogenic lifestyle alone is sufficient for the development of nonalcoholic steatohepatitis, hepatic stem cell activation, and hepatocarcinogenesis in wild-type mice. PMID:24650559

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

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

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

DOE PAGES

Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

2018-02-09

Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

Language, cognitive flexibility, and explicit false belief understanding: longitudinal analysis in typical development and specific language impairment.

PubMed

Farrant, Brad M; Maybery, Murray T; Fletcher, Janet

2012-01-01

The hypothesis that language plays a role in theory-of-mind (ToM) development is supported by a number of lines of evidence (e.g., H. Lohmann & M. Tomasello, 2003). The current study sought to further investigate the relations between maternal language input, memory for false sentential complements, cognitive flexibility, and the development of explicit false belief understanding in 91 English-speaking typically developing children (M age = 61.3 months) and 30 children with specific language impairment (M age = 63.0 months). Concurrent and longitudinal findings converge in supporting a model in which maternal language input predicts the child's memory for false complements, which predicts cognitive flexibility, which in turn predicts explicit false belief understanding. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.

Climate variables as predictors for seasonal forecast of dengue occurrence in Chennai, Tamil Nadu

NASA Astrophysics Data System (ADS)

Subash Kumar, D. D.; Andimuthu, R.

2013-12-01

Background Dengue is a recently emerging vector borne diseases in Chennai. As per the WHO report in 2011 dengue is one of eight climate sensitive disease of this century. Objective Therefore an attempt has been made to explore the influence of climate parameters on dengue occurrence and use for forecasting. Methodology Time series analysis has been applied to predict the number of dengue cases in Chennai, a metropolitan city which is the capital of Tamil Nadu, India. Cross correlation of the climate variables with dengue cases revealed that the most influential parameters were monthly relative humidity, minimum temperature at 4 months lag and rainfall at one month lag (Table 1). However due to intercorrelation of relative humidity and rainfall was high and therefore for predictive purpose the rainfall at one month lag was used for the model development. Autoregressive Integrated Moving Average (ARIMA) models have been applied to forecast the occurrence of dengue. Results and Discussion The best fit model was ARIMA (1,0,1). It was seen that the monthly minimum temperature at four months lag (β= 3.612, p = 0.02) and rainfall at one month lag (β= 0.032, p = 0.017) were associated with dengue occurrence and they had a very significant effect. Mean Relative Humidity had a directly significant positive correlation at 99% confidence level, but the lagged effect was not prominent. The model predicted dengue cases showed significantly high correlation of 0.814(Figure 1) with the observed cases. The RMSE of the model was 18.564 and MAE was 12.114. The model is limited by the scarcity of the dataset. Inclusion of socioeconomic conditions and population offset are further needed to be incorporated for effective results. Conclusion Thus it could be claimed that the change in climatic parameters is definitely influential in increasing the number of dengue occurrence in Chennai. The climate variables therefore can be used for seasonal forecasting of dengue with rise in minimum temperature and rainfall at a city level. Table 1. Cross correlation of climate variables with dengue cases in Chennai ** p<0.01,*p<0.05

Early Learning in Psychomotor Training of Down's Syndrome.

ERIC Educational Resources Information Center

Sanz Aparicio, Maria Teresa; Menendez Balana, Javier

2003-01-01

Compared effectiveness of modeling from a clinician to that of written instructions to train parents to use a motor stimulation program with their infants with Down syndrome. Obtained motor development quotients prior to the program and at 6, 12, 18, and 24 months. Found that infants of parents trained by modeling obtained higher motor…

The Transition from Preschool to First Grade: A Transactional Model of Development

ERIC Educational Resources Information Center

Goble, Priscilla; Eggum-Wilkens, Natalie D.; Bryce, Crystal I.; Foster, Stacie A.; Hanish, Laura D.; Martin, Carol Lynn; Fabes, Richard A.

2017-01-01

Transactional relations between children's positive social interaction skills, school engagement, and academic achievement were examined using a longitudinal panel model across the transition from preschool to first grade. Participants were Head Start children (N = 241; 49% girls, M age = 53 months, range 45-60); 78% were Mexican/Mexican-American;…

Business Management Coaching: Focusing on Entrepreneur's Current Position and Aims

ERIC Educational Resources Information Center

Cheah, Kheng T.

2012-01-01

One-to-one business coaching over 6 months was provided to nine clients in Hawaii to help them acquire business transition skills. The STARS model was used to determine the individual business situation and to explore suitable leadership strategies to move forward. Systematically, each client developed a business model, business strategies, a…

Social-Emotional Development, School Readiness, Teacher-Child Interactions, and Classroom Environment

ERIC Educational Resources Information Center

Heller, Sherryl Scott; Rice, Janet; Boothe, Allison; Sidell, Margo; Vaughn, Krystal; Keyes, Angela; Nagle, Geoffrey

2012-01-01

This article investigates the effectiveness of a statewide 6-month early childhood mental health consultation (ECMHC) model on teachers' emotional support of children and classroom organization. We provide a brief historical and theoretical background of the field of ECMHC, present the logic model for our ECMHC intervention, and discuss the…

Utilization of UARS Data in Validation of Photochemical and Dynamical Mechanism in Stratospheric Models

NASA Technical Reports Server (NTRS)

Rodriquez, Jose M.; Hu, Wenjie; Ko, Malcolm K. W.

1995-01-01

We proposed model-data intercomparison studies for UARS data. In the past three months, we have been working on constructing analysis tools to diagnose the UARS data. The 'Trajectory mapping' technique, which was developed by Morris (1994), is adaptable to generate synoptic maps of trace gas data from asynoptic observations. An in-house trajectory model (kinematic methods following Merrill et al., 1986 and Pickering et al., 1994) has been developed in AER under contract with NASA/ACMAP and the trajectory mapping tool has been applied to analyze UARS measurement.

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Rouse, W. B.; Hammer, J. M.; Mitchell, C. M.; Morris, N. M.; Lewis, C. M.; Yoon, W. C.

1985-01-01

Progress was made in the three following areas. In the rule-based modeling area, two papers related to identification and significane testing of rule-based models were presented. In the area of operator aiding, research focused on aiding operators in novel failure situations; a discrete control modeling approach to aiding PLANT operators was developed; and a set of guidelines were developed for implementing automation. In the area of flight simulator hardware and software, the hardware will be completed within two months and initial simulation software will then be integrated and tested.

Longitudinal Evaluation of Fatty Acid Metabolism in Normal and Spontaneously Hypertensive Rat Hearts with Dynamic MicroSPECT Imaging

DOE PAGES

Reutter, Bryan W.; Huesman, Ronald H.; Brennan, Kathleen M.; ...

2011-01-01

The goal of this project is to develop radionuclide molecular imaging technologies using a clinical pinhole SPECT/CT scanner to quantify changes in cardiac metabolism using the spontaneously hypertensive rat (SHR) as a model of hypertensive-related pathophysiology. This paper quantitatively compares fatty acid metabolism in hearts of SHR and Wistar-Kyoto normal rats as a function of age and thereby tracks physiological changes associated with the onset and progression of heart failure in the SHR model. The fatty acid analog, 123 I-labeled BMIPP, was used in longitudinal metabolic pinhole SPECT imaging studies performed every seven months for 21 months. The uniqueness ofmore » this project is the development of techniques for estimating the blood input function from projection data acquired by a slowly rotating camera that is imaging fast circulation and the quantification of the kinetics of 123 I-BMIPP by fitting compartmental models to the blood and tissue time-activity curves.« less

Advantages of a multi-state approach in surgical research: how intermediate events and risk factor profile affect the prognosis of a patient with locally advanced rectal cancer.

PubMed

Manzini, G; Ettrich, T J; Kremer, M; Kornmann, M; Henne-Bruns, D; Eikema, D A; Schlattmann, P; de Wreede, L C

2018-02-13

Standard survival analysis fails to give insight into what happens to a patient after a first outcome event (like first relapse of a disease). Multi-state models are a useful tool for analyzing survival data when different treatments and results (intermediate events) can occur. Aim of this study was to implement a multi-state model on data of patients with rectal cancer to illustrate the advantages of multi-state analysis in comparison to standard survival analysis. We re-analyzed data from the RCT FOGT-2 study by using a multi-state model. Based on the results we defined a high and low risk reference patient. Using dynamic prediction, we estimated how the survival probability changes as more information about the clinical history of the patient becomes available. A patient with stage UICC IIIc (vs UICC II) has a higher risk to develop distant metastasis (DM) or both DM and local recurrence (LR) if he/she discontinues chemotherapy within 6 months or between 6 and 12 months, as well as after the completion of 12 months CTx with HR 3.55 (p = 0.026), 5.33 (p = 0.001) and 3.37 (p < 0.001), respectively. He/she also has a higher risk to die after the development of DM (HR 1.72, p = 0.023). Anterior resection vs. abdominoperineal amputation means 63% risk reduction to develop DM or both DM and LR (HR 0.37, p = 0.003) after discontinuation of chemotherapy between 6 and 12 months. After development of LR, a woman has a 4.62 times higher risk to die (p = 0.006). A high risk reference patient has an estimated 43% 5-year survival probability at start of CTx, whereas for a low risk patient this is 79%. After the development of DM 1 year later, the high risk patient has an estimated 5-year survival probability of 11% and the low risk patient one of 21%. Multi-state models help to gain additional insight into the complex events after start of treatment. Dynamic prediction shows how survival probabilities change by progression of the clinical history.

An enhanced archive facilitating climate impacts analysis

USGS Publications Warehouse

Maurer, E.P.; Brekke, L.; Pruitt, T.; Thrasher, B.; Long, J.; Duffy, P.; Dettinger, M.; Cayan, D.; Arnold, J.

2014-01-01

We describe the expansion of a publicly available archive of downscaled climate and hydrology projections for the United States. Those studying or planning to adapt to future climate impacts demand downscaled climate model output for local or regional use. The archive we describe attempts to fulfill this need by providing data in several formats, selectable to meet user needs. Our archive has served as a resource for climate impacts modelers, water managers, educators, and others. Over 1,400 individuals have transferred more than 50 TB of data from the archive. In response to user demands, the archive has expanded from monthly downscaled data to include daily data to facilitate investigations of phenomena sensitive to daily to monthly temperature and precipitation, including extremes in these quantities. New developments include downscaled output from the new Coupled Model Intercomparison Project phase 5 (CMIP5) climate model simulations at both the monthly and daily time scales, as well as simulations of surface hydrologi- cal variables. The web interface allows the extraction of individual projections or ensemble statistics for user-defined regions, promoting the rapid assessment of model consensus and uncertainty for future projections of precipitation, temperature, and hydrology. The archive is accessible online (http://gdo-dcp.ucllnl.org/downscaled_ cmip_projections).

Optimizing Surface Winds using QuikSCAT Measurements in the Mediterranean Sea During 2000-2006

DTIC Science & Technology

2009-02-28

Temperature and salinity from the 1/4° Generalized Digital Envi- ronmental Model ( GDEM ) monthly climatology developed at the Naval Oceanographic...monthly GDEM climatology was also used for relaxation of the sea-surface salinity (SSS) to keep the surface salinity balance on track. The net heat...salinity from the GDEM clima- tology are used to initialize themodel. There is a relaxation tomonthly mean SSS fromGDEM. The referencemixed-layer

Imitation from 12 to 24 months in autism and typical development: A longitudinal Rasch analysis

PubMed Central

Young, Gregory S.; Rogers, Sally J.; Hutman, Ted; Rozga, Agata; Sigman, Marian; Ozonoff, Sally

2013-01-01

The development of imitation during the second year of life plays an important role in domains of socio-cognitive development such as language and social learning. Deficits in imitation ability in persons with autism spectrum disorder (ASD) have also been repeatedly documented from toddlerhood into adulthood, raising the possibility that early disruptions in imitation contribute to the onset of ASD and the deficits in language and social interaction that define the disorder. This study prospectively examined the development of imitation between 12 and 24 months of age in 154 infants at familial risk for ASD and 78 typically developing infants who were all later assessed at 36 months for ASD or other developmental delays. The study established a developmental measure of imitation ability, and examined group differences over time, using an analytic Rasch measurement model. Results revealed a unidimensional latent construct of imitation and verified a reliable sequence of imitation skills that was invariant over time for all outcome groups. Results also showed that all groups displayed similar significant linear increases in imitation ability between 12 and 24 months and that these increases were related to individual growth in both expressive language and ratings of social engagement, but not fine motor development. The group of children who developed ASD by age 3 years exhibited delayed imitation development compared to the low-risk typical outcome group across all time-points, but were indistinguishable from other high-risk infants who showed other cognitive delays not related to ASD. PMID:21910524

Risk stratification for death and all-cause hospitalization in heart failure clinic outpatients.

PubMed

Hummel, Scott L; Ghalib, Hussam H; Ratz, David; Koelling, Todd M

2013-11-01

Most heart failure (HF) risk stratification models were developed for inpatient use, and available outpatient models use a complex set of variables. We hypothesized that routinely collected clinical data could predict the 6-month risk of death and all-cause medical hospitalization in HF clinic outpatients. Using a quality improvement database and multivariable Cox modeling, we derived the Heart Failure Patient Severity Index (HFPSI) in the University of Michigan HF clinic (UM cohort, n = 1,536; 314 reached primary outcome). We externally validated the HFPSI in the Ann Arbor Veterans' Affairs HF clinic (VA cohort, n = 445; 106 outcomes) and explored "real-time" HFPSI use (VA-RT cohort, n = 486; 141 outcomes) by tracking VA patients for 6 months from their most recently calculated HFPSI, rather than using an arbitrary start date for the cohort. The HFPSI model included blood urea nitrogen, B-type natriuretic peptide, New York Heart Association class, diabetes status, history of atrial fibrillation/flutter, and all-cause hospitalization within the prior 1 and 2 to 6 months. The concordance c statistics in the UM/VA/VA-RT cohorts were 0.71/0.68/0.74. Kaplan-Meier curves and log-rank testing demonstrated excellent risk stratification, particularly between a large, low-risk group (40% of patients, 6-month event rates in the UM/VA/VA-RT cohorts 8%/12%/12%) and a small, high-risk group (10% of patients, 6-month event rates in the UM/VA/VA-RT cohorts 57%/58%/79%). The HFPSI uses readily available data to predict the 6-month risk of death and/or all-cause medical hospitalization in HF clinic outpatients and could potentially help allocate specialized HF resources within health systems. © 2013.

A predictive risk model for medical intractability in epilepsy.

PubMed

Huang, Lisu; Li, Shi; He, Dake; Bao, Weiqun; Li, Ling

2014-08-01

This study aimed to investigate early predictors (6 months after diagnosis) of medical intractability in epilepsy. All children <12 years of age having two or more unprovoked seizures 24 h apart at Xinhua Hospital between 1992 and 2006 were included. Medical intractability was defined as failure, due to lack of seizure control, of more than 2 antiepileptic drugs at maximum tolerated doses, with an average of more than 1 seizure per month for 24 months and no more than 3 consecutive months of seizure freedom during this interval. Univariate and multivariate logistic regression models were performed to determine the risk factors for developing medical intractability. Receiver operating characteristic curve was applied to fit the best compounded predictive model. A total of 649 patients were identified, out of which 119 (18%) met the study definition of intractable epilepsy at 2 years after diagnosis, and the rate of intractable epilepsy in patients with idiopathic syndromes was 12%. Multivariate logistic regression analysis revealed that neurodevelopmental delay, symptomatic etiology, partial seizures, and more than 10 seizures before diagnosis were significant and independent risk factors for intractable epilepsy. The best model to predict medical intractability in epilepsy comprised neurological physical abnormality, age at onset of epilepsy under 1 year, more than 10 seizures before diagnosis, and partial epilepsy, and the area under receiver operating characteristic curve was 0.7797. This model also fitted best in patients with idiopathic syndromes. A predictive model of medically intractable epilepsy composed of only four characteristics is established. This model is comparatively accurate and simple to apply clinically. Copyright © 2014 Elsevier Inc. All rights reserved.

Ecological covariates based predictive model of malaria risk in the state of Chhattisgarh, India.

PubMed

Kumar, Rajesh; Dash, Chinmaya; Rani, Khushbu

2017-09-01

Malaria being an endemic disease in the state of Chhattisgarh and ecologically dependent mosquito-borne disease, the study is intended to identify the ecological covariates of malaria risk in districts of the state and to build a suitable predictive model based on those predictors which could assist developing a weather based early warning system. This secondary data based analysis used one month lagged district level malaria positive cases as response variable and ecological covariates as independent variables which were tested with fixed effect panelled negative binomial regression models. Interactions among the covariates were explored using two way factorial interaction in the model. Although malaria risk in the state possesses perennial characteristics, higher parasitic incidence was observed during the rainy and winter seasons. The univariate analysis indicated that the malaria incidence risk was statistically significant associated with rainfall, maximum humidity, minimum temperature, wind speed, and forest cover ( p  < 0.05). The efficient predictive model include the forest cover [IRR-1.033 (1.024-1.042)], maximum humidity [IRR-1.016 (1.013-1.018)], and two-way factorial interactions between district specific averaged monthly minimum temperature and monthly minimum temperature, monthly minimum temperature was statistically significant [IRR-1.44 (1.231-1.695)] whereas the interaction term has a protective effect [IRR-0.982 (0.974-0.990)] against malaria infections. Forest cover, maximum humidity, minimum temperature and wind speed emerged as potential covariates to be used in predictive models for modelling the malaria risk in the state which could be efficiently used for early warning systems in the state.

Assessment of Areal Recharge to the Spokane Valley-Rathdrum Prairie Aquifer, Spokane County, Washington, and Bonner and Kootenai Counties, Idaho

USGS Publications Warehouse

Bartolino, James R.

2007-01-01

A numerical flow model of the Spokane Valley-Rathdrum Prairie aquifer currently (2007) being developed requires the input of values for areally-distributed recharge, a parameter that is often the most uncertain component of water budgets and ground-water flow models because it is virtually impossible to measure over large areas. Data from six active weather stations in and near the study area were used in four recharge-calculation techniques or approaches; the Langbein method, in which recharge is estimated on the basis of empirical data from other basins; a method developed by the U.S. Department of Agriculture (USDA), in which crop consumptive use and effective precipitation are first calculated and then subtracted from actual precipitation to yield an estimate of recharge; an approach developed as part of the Eastern Snake Plain Aquifer Model (ESPAM) Enhancement Project in which recharge is calculated on the basis of precipitation-recharge relations from other basins; and an approach in which reference evapotranspiration is calculated by the Food and Agriculture Organization (FAO) Penman-Monteith equation, crop consumptive use is determined (using a single or dual coefficient approach), and recharge is calculated. Annual recharge calculated by the Langbein method for the six weather stations was 4 percent of annual mean precipitation, yielding the lowest values of the methods discussed in this report, however, the Langbein method can be only applied to annual time periods. Mean monthly recharge calculated by the USDA method ranged from 53 to 73 percent of mean monthly precipitation. Mean annual recharge ranged from 64 to 69 percent of mean annual precipitation. Separate mean monthly recharge calculations were made with the ESPAM method using initial input parameters to represent thin-soil, thick-soil, and lava-rock conditions. The lava-rock parameters yielded the highest recharge values and the thick-soil parameters the lowest. For thin-soil parameters, calculated monthly recharge ranged from 10 to 29 percent of mean monthly precipitation and annual recharge ranged from 16 to 23 percent of mean annual precipitation. For thick-soil parameters, calculated monthly recharge ranged from 1 to 5 percent of mean monthly precipitation and mean annual recharge ranged from 2 to 4 percent of mean annual precipitation. For lava-rock parameters, calculated mean monthly recharge ranged from 37 to 57 percent of mean monthly precipitation and mean annual recharge ranged from 45 to 52 percent of mean annual precipitation. Single-coefficient (crop coefficient) FAO Penman-Monteith mean monthly recharge values were calculated for Spokane Weather Service Office (WSO) Airport, the only station for which the necessary meteorological data were available. Grass-referenced values of mean monthly recharge ranged from 0 to 81 percent of mean monthly precipitation and mean annual recharge was 21 percent of mean annual precipitation; alfalfa-referenced values of mean monthly recharge ranged from 0 to 85 percent of mean monthly precipitation and mean annual recharge was 24 percent of mean annual precipitation. Single-coefficient FAO Penman-Monteith calculations yielded a mean monthly recharge of zero during the eight warmest and driest months of the year (March-October). In order to refine the mean monthly recharge estimates, dual-coefficient (basal crop and soil evaporation coefficients) FAO Penman-Monteith dual-crop evapotranspiration and deep-percolation calculations were applied to daily values from the Spokane WSO Airport for January 1990 through December 2005. The resultant monthly totals display a temporal variability that is absent from the mean monthly values and demonstrate that the daily amount and timing of precipitation dramatically affect calculated recharge. The dual-coefficient FAO Penman-Monteith calculations were made for the remaining five stations using wind-speed values for Spokane WSO Airport and other assumptions regarding

SENSITIVITY OF THE REGIONAL WATER BALANCE IN THE COLUMBIA RIVER BASIN TO CLIMATE VARIABILITY: APPLICATION OF A SPATIALLY DISTRIBUTED WATER BALANCE MODEL

EPA Science Inventory

A one-dimensional water balance model was developed and used to simulate water balance for the Columbia River Basin. he model was run over a 10 km X 10 km grid for the United State's portion of the basin. he regional water balance was calculated using a monthly time-step for a re...

Functional connectivity in the developing brain: A longitudinal study from 4 to 9 months of age

PubMed Central

Damaraju, E.; Caprihan, A.; Lowe, J.R.; Allen, E.A.; Calhoun, V.D.; Phillips, J.P.

2013-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9 months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9 months. However at 9 months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. PMID:23994454

Testing Reciprocal Links Between Trouble Getting to Sleep and Internalizing Behavior Problems, and Bedtime Resistance and Externalizing Behavior Problems in Toddlers.

PubMed

Conway, Anne; Miller, Alison L; Modrek, Anahid

2017-08-01

Sleep problems are associated with problematic adjustment in toddlers, but less is known regarding the direction of association between specific sleep problems and adjustment. To address this gap, we used data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (N = 1001) to examine reciprocal associations between sleep problems and behavior problems from 24- to 36-months. Results from cross-lagged path models suggested specificity of associations between type of sleep problem and behavior problem. Specifically, there were reciprocal associations between trouble getting to sleep and internalizing problems, and unidirectional links between externalizing problems and bedtime resistance from 24- to 36-months. Internalizing and externalizing problems at 24 months, however, predicted increases in bedtime resistance from 24- to 36-months for boys, but not girls. Findings highlight specific relations between sleep problems and internalizing and externalizing problems during toddlerhood, and the importance of examining sex differences.

Functional connectivity in the developing brain: a longitudinal study from 4 to 9months of age.

PubMed

Damaraju, E; Caprihan, A; Lowe, J R; Allen, E A; Calhoun, V D; Phillips, J P

2014-01-01

We characterize the development of intrinsic connectivity networks (ICNs) from 4 to 9months of age with resting state magnetic resonance imaging performed on sleeping infants without sedative medication. Data is analyzed with independent component analysis (ICA). Using both low (30 components) and high (100 components) ICA model order decompositions, we find that the functional network connectivity (FNC) map is largely similar at both 4 and 9months. However at 9months the connectivity strength decreases within local networks and increases between more distant networks. The connectivity within the default-mode network, which contains both local and more distant nodes, also increases in strength with age. The low frequency power spectrum increases with age only in the posterior cingulate cortex and posterior default mode network. These findings are consistent with a general developmental pattern of increasing longer distance functional connectivity over the first year of life and raise questions regarding the developmental importance of the posterior cingulate at this age. © 2013.

Faculty development to enhance humanistic teaching and role modeling: a collaborative study at eight institutions.

PubMed

Branch, William T; Chou, Calvin L; Farber, Neil J; Hatem, David; Keenan, Craig; Makoul, Gregory; Quinn, Mariah; Salazar, William; Sillman, Jane; Stuber, Margaret; Wilkerson, LuAnn; Mathew, George; Fost, Michael

2014-09-01

There is increased emphasis on practicing humanism in medicine but explicit methods for faculty development in humanism are rare. We sought to demonstrate improved faculty teaching and role modeling of humanistic and professional values by participants in a multi-institutional faculty development program as rated by their learners in clinical settings compared to contemporaneous controls. Blinded learners in clinical settings rated their clinical teachers, either participants or controls, on the previously validated 10-item Humanistic Teaching Practices Effectiveness (HTPE) questionnaire. Groups of 7-9 participants at 8 academic medical centers completed an 18-month faculty development program. Participating faculty were chosen by program facilitators at each institution on the basis of being promising teachers, willing to participate in the longitudinal faculty development program. Our 18-month curriculum combined experiential learning of teaching skills with critical reflection using appreciative inquiry narratives about their experiences as teachers and other reflective discussions. The main outcome was the aggregate score of the ten items on the questionnaire at all institutions. The aggregate score favored participants over controls (P = 0.019) independently of gender, experience on faculty, specialty area, and/or overall teaching skills. Longitudinal, intensive faculty development that employs experiential learning and critical reflection likely enhances humanistic teaching and role modeling. Almost all participants completed the program. Results are generalizable to other schools.

New insights for the hydrology of the Rhine based on the new generation climate models

NASA Astrophysics Data System (ADS)

Bouaziz, Laurène; Sperna Weiland, Frederiek; Beersma, Jules; Buiteveld, Hendrik

2014-05-01

Decision makers base their choices of adaptation strategies on climate change projections and their associated hydrological consequences. New insights of climate change gained under the new generation of climate models belonging to the IPCC 5th assessment report may influence (the planning of) adaption measures and/or future expectations. In this study, hydrological impacts of climate change as projected under the new generation of climate models for the Rhine were assessed. Hereto we downscaled 31 General Circulation Models (GCMs), which were developed as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5), using an advanced Delta Change Method for the Rhine basin. Changes in mean monthly, maximum and minimum flows at Lobith were derived with the semi-distributed hydrological model HBV of the Rhine. The projected changes were compared to changes that were previously obtained in the trans-boundary project Rheinblick using eight CMIP3 GCMs and Regional Climate Models (RCMs) for emission scenario A1B. All eight selected CMIP3 models (scenario A1B) predicted for 2071-2100 a decrease in mean monthly flows between June and October. Similar decreases were found for some of the 31 CMIP5 models for Representative Concentration Pathways (RCPs) 4.5, 6.0 and 8.5. However, under each RCP, there were also models that projected an increase in mean flows between June and October and on average the decrease was smaller than for the eight CMIP3 models. For 2071-2100, also the mean annual minimum 7-days discharge decreased less in the CMIP5 model simulations than was projected in CMIP3. When assessing the response of mean monthly flows of the CMIP5 simulation with the CSIRO-Mk3-6-0 and HadGEM2-ES models with respect to initial conditions and RCPs, it was found that natural variability plays a dominant role in the near future (2021-2050), while changes in mean monthly flows are dominated by the radiative forcing in the far future (2071-2100). According to RCP 8.5 model simulations, the change in mean monthly flow from May to November may be half the change in mean monthly flow projected by RCP 4.5. From January to March, RCP 8.5 simulations projected higher changes in mean monthly flows than RCP 4.5 simulations. These new insights based on the CMIP5 simulations imply that for the Rhine, the mean and low flow extremes might not decrease as much in summer as was expected under CMIP3. Stresses on water availability during summer are therefore also less than expected from CMIP3.

Improved ensemble-mean forecasting of ENSO events by a zero-mean stochastic error model of an intermediate coupled model

NASA Astrophysics Data System (ADS)

Zheng, Fei; Zhu, Jiang

2017-04-01

How to design a reliable ensemble prediction strategy with considering the major uncertainties of a forecasting system is a crucial issue for performing an ensemble forecast. In this study, a new stochastic perturbation technique is developed to improve the prediction skills of El Niño-Southern Oscillation (ENSO) through using an intermediate coupled model. We first estimate and analyze the model uncertainties from the ensemble Kalman filter analysis results through assimilating the observed sea surface temperatures. Then, based on the pre-analyzed properties of model errors, we develop a zero-mean stochastic model-error model to characterize the model uncertainties mainly induced by the missed physical processes of the original model (e.g., stochastic atmospheric forcing, extra-tropical effects, Indian Ocean Dipole). Finally, we perturb each member of an ensemble forecast at each step by the developed stochastic model-error model during the 12-month forecasting process, and add the zero-mean perturbations into the physical fields to mimic the presence of missing processes and high-frequency stochastic noises. The impacts of stochastic model-error perturbations on ENSO deterministic predictions are examined by performing two sets of 21-yr hindcast experiments, which are initialized from the same initial conditions and differentiated by whether they consider the stochastic perturbations. The comparison results show that the stochastic perturbations have a significant effect on improving the ensemble-mean prediction skills during the entire 12-month forecasting process. This improvement occurs mainly because the nonlinear terms in the model can form a positive ensemble-mean from a series of zero-mean perturbations, which reduces the forecasting biases and then corrects the forecast through this nonlinear heating mechanism.

Systems modeling and analysis for Saudi Arabian electric power requirements

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

Al-Mohawes, N.A.

This thesis addresses the long-range generation planning problem in Saudi Arabia up to the year 2000. The first part presents various models for electric energy consumption in the residential and industrial sectors. These models can be used by the decision makers for the purposes of policy analysis, evaluation, and forecasting. Forecasts of energy in each sector are obtained from two different models for each sector. These models are based on two forecasting techniques: (1) Hybrid econometric/time series model. The idea of adaptive smoothing was utilized to produce forecasts under several scenarios. (2) Box-Jenkins time series technique. Box-Jenkins models and forecastsmore » are developed for the monthly number of electric consumers and the monthly energy consumption per consumer. The results obtained indicate that high energy consumption is expected during the coming two decades which necessitate serious energy assessment and optimization. Optimization of a mix of energy sources was considered using the group multiattribute utility (MAU) function. The results of MAU for three classes of decision makers (managerial, technical, and consumers) are developed through personal interactions. The computer package WASP was also used to develop a tentative optimum plan. According to this plan, four heavy-water nuclear power plants (800 MW) and four light-water nuclear power plants (1200 MW) have to be introduced by the year 2000 in addition to sixteen oil-fired power plants (400 MW) and nine gas turbines (100 MW).« less

Plumes and Blooms: Observations, Analysis and Modeling for SIMBIOS

NASA Technical Reports Server (NTRS)

Maritorena, S.; Siegel, D. A.; Nelson, N. B.

2004-01-01

The goal of the Plumes and Blooms (PnB) project is to develop, validate and apply to imagery state-of-the-art ocean color algorithms for quantifying sediment plumes and phytoplankton blooms for the Case II environment of the Santa Barbara Channel. We conduct monthly to twice-monthly transect observations across the Santa Barbara Channel to develop an algorithm development and product validation data set. A primary goal is the use the PnB field data set to objectively tune semi-analytical models of ocean color for this site and apply them using available satellite imagery (SeaWiFS and MODIS). However, the comparison between PnB field observations and satellite estimates of primary products has been disappointing. We find that field estimates of water-leaving radiance correspond poorly to satellite estimates for both SeaWiFS and MODIS local area coverage imagery. We believe this is due to poor atmospheric correction due to complex mixtures of aerosol types found in these near-coastal regions.

Estimated SAGE II ozone mixing ratios in early 1993 and comparisons with Stratospheric Photochemistry, Aerosols and Dynamic Expedition measurements

NASA Technical Reports Server (NTRS)

Yue, G. K.; Veiga, R. E.; Poole, L. R.; Zawodny, J. M.; Proffitt, M. H.

1994-01-01

An empirical time-series model for estimating ozone mixing ratios based on Stratospheric Aerosols and Gas Experiment II (SAGE II) monthly mean ozone data for the period October 1984 through June 1991 has been developed. The modeling results for ozone mixing ratios in the 10- to 30- km region in early months of 1993 are presented. In situ ozone profiles obtained by a dual-beam UV-absorption ozone photometer during the Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE) campaign, May 1-14, 1993, are compared with the model results. With the exception of two profiles at altitudes below 16 km, ozone mixing ratios derived by the model and measured by the ozone photometer are in relatively good agreement within their individual uncertainties. The identified discrepancies in the two profiles are discussed.

Evaluating the impacts of agricultural land management practices on water resources: A probabilistic hydrologic modeling approach.

PubMed

Prada, A F; Chu, M L; Guzman, J A; Moriasi, D N

2017-05-15

Evaluating the effectiveness of agricultural land management practices in minimizing environmental impacts using models is challenged by the presence of inherent uncertainties during the model development stage. One issue faced during the model development stage is the uncertainty involved in model parameterization. Using a single optimized set of parameters (one snapshot) to represent baseline conditions of the system limits the applicability and robustness of the model to properly represent future or alternative scenarios. The objective of this study was to develop a framework that facilitates model parameter selection while evaluating uncertainty to assess the impacts of land management practices at the watershed scale. The model framework was applied to the Lake Creek watershed located in southwestern Oklahoma, USA. A two-step probabilistic approach was implemented to parameterize the Agricultural Policy/Environmental eXtender (APEX) model using global uncertainty and sensitivity analysis to estimate the full spectrum of total monthly water yield (WYLD) and total monthly Nitrogen loads (N) in the watershed under different land management practices. Twenty-seven models were found to represent the baseline scenario in which uncertainty of up to 29% and 400% in WYLD and N, respectively, is plausible. Changing the land cover to pasture manifested the highest decrease in N to up to 30% for a full pasture coverage while changing to full winter wheat cover can increase the N up to 11%. The methodology developed in this study was able to quantify the full spectrum of system responses, the uncertainty associated with them, and the most important parameters that drive their variability. Results from this study can be used to develop strategic decisions on the risks and tradeoffs associated with different management alternatives that aim to increase productivity while also minimizing their environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development and Validation of a Risk Model for Prediction of Hazardous Alcohol Consumption in General Practice Attendees: The PredictAL Study

PubMed Central

King, Michael; Marston, Louise; Švab, Igor; Maaroos, Heidi-Ingrid; Geerlings, Mirjam I.; Xavier, Miguel; Benjamin, Vicente; Torres-Gonzalez, Francisco; Bellon-Saameno, Juan Angel; Rotar, Danica; Aluoja, Anu; Saldivia, Sandra; Correa, Bernardo; Nazareth, Irwin

2011-01-01

Background Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. Results 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse. PMID:21853028

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study.

PubMed

King, Michael; Marston, Louise; Švab, Igor; Maaroos, Heidi-Ingrid; Geerlings, Mirjam I; Xavier, Miguel; Benjamin, Vicente; Torres-Gonzalez, Francisco; Bellon-Saameno, Juan Angel; Rotar, Danica; Aluoja, Anu; Saldivia, Sandra; Correa, Bernardo; Nazareth, Irwin

2011-01-01

Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

A single-station empirical model for TEC over the Antarctic Peninsula using GPS-TEC data

NASA Astrophysics Data System (ADS)

Feng, Jiandi; Wang, Zhengtao; Jiang, Weiping; Zhao, Zhenzhen; Zhang, Bingbing

2017-02-01

Compared with regional or global total electron content (TEC) empirical models, single-station TEC empirical models may exhibit higher accuracy in describing TEC spatial and temporal variations for a single station. In this paper, a new single-station empirical total electron content (TEC) model, called SSM-month, for the O'Higgins Station in the Antarctic Peninsula is proposed by using Global Positioning System (GPS)-TEC data from 01 January 2004 to 30 June 2015. The diurnal variation of TEC in the O'Higgins Station may have changing features in different months, sometimes even in opposite forms, because of ionospheric phenomena, such as the Mid-latitude Summer Nighttime Anomaly (MSNA). To avoid the influence of different diurnal variations, the concept of monthly modeling is proposed in this study. The SSM-month model, which is established by month (including 12 submodels that correspond to the 12 months), can effectively describe the diurnal variation of TEC in different months. Each submodel of the SSM-month model exhibits good agreement with GPS-TEC input data. Overall, the SSM-month model fits the input data with a bias of 0.03 TECU (total electron content unit, 1 TECU = 1016 el m-2) and a standard deviation of 2.78 TECU. This model, which benefits from the modeling method, can effectively describe the MSNA phenomenon without implementing any modeling correction. TEC data derived from Center for Orbit Determination in Europe global ionosphere maps (CODE GIMs), International Reference Ionosphere 2012 (IRI2012), and NeQuick are compared with the SSM-month model in the years of 2001 and 2015-2016. Result shows that the SSM-month model exhibits good consistency with CODE GIMs, which is better than that of IRI2012 and NeQuick, in the O'Higgins Station on the test days.

Upscaling key ecosystem functions across the conterminous United States by a water‐centric ecosystem model

Treesearch

Ge Sun; Peter Caldwell; Asko Noormets; Steven G. McNulty; Erika Cohen; al. et.

2011-01-01

We developed a water‐centric monthly scale simulation model (WaSSI‐C) by integrating empirical water and carbon flux measurements from the FLUXNET network and an existing water supply and demand accounting model (WaSSI). The WaSSI‐C model was evaluated with basin‐scale evapotranspiration (ET), gross ecosystem productivity (GEP), and net ecosystem exchange (NEE)...

The refined biomimetic NeuroDigm GEL™ model of neuropathic pain in a mature rat

PubMed Central

Hannaman, Mary R.; Fitts, Douglas A.; Doss, Rose M.; Weinstein, David E.; Bryant, Joseph L.

2017-01-01

Background: Many humans suffering with chronic neuropathic pain have no objective evidence of an etiological lesion or disease. Frequently their persistent pain occurs after the healing of a soft tissue injury. Based on clinical observations over time, our hypothesis was that after an injury in mammals the process of tissue repair could cause chronic neural pain. Our objectives were to create the delayed onset of neuropathic pain in rats with minimal nerve trauma using a physiologic hydrogel, and characterize the rats’ responses to known analgesics and a targeted biologic. Methods: In mature male Sprague Dawley rats (age 9.5 months) a percutaneous implant of tissue-derived hydrogel was placed in the musculofascial tunnel of the distal tibial nerve. Subcutaneous morphine (3 mg/kg), celecoxib (10 mg/kg), gabapentin (25 mg/kg) and duloxetine (10 mg/kg) were each screened in the model three times each over 5 months after pain behaviors developed. Sham and control groups were used in all screenings. A pilot study followed in which recombinant human erythropoietin (200 units) was injected by the GEL™ neural procedure site. Results: The GEL group gradually developed mechanical hypersensitivity lasting months. Morphine, initially effective, had less analgesia over time. Celecoxib produced no analgesia, while gabapentin and duloxetine at low doses demonstrated profound analgesia at all times tested. The injected erythropoietin markedly decreased bilateral pain behavior that had been present for over 4 months, p ≤ 0.001. Histology of the GEL group tibial nerve revealed a site of focal neural remodeling, with neural regeneration, as found in nerve biopsies of patients with neuropathic pain. Conclusion: The refined NeuroDigm GEL™ model induces a neural response resulting in robust neuropathic pain behavior. The analgesic responses in this model reflect known responses of humans with neuropathic pain. The targeted recombinant human erythropoietin at the ectopic neural lesion appears to alleviate the persistent pain behavior in the GEL™ model rodents. PMID:28620451

Athena in 2013 and Beyond

NASA Technical Reports Server (NTRS)

Chamberlain, Robert G.; Duquette, William H.

2013-01-01

TRISA, the U.S. Army TRADOC G2 Intelligence Support Activity, received Athena 1 in 2009. They first used Athena 3 to support studies in 2011. This paper describes Athena 4, which they started using in October 2012. A final section discusses issues that are being considered for incorporation into Athena 5 and later. Athena's objective is to help skilled intelligence analysts anticipate the likely consequences of complex courses of action that use our country's entire power base, not just our military capabilities, for operations in troubled regions of the world. Measures of effectiveness emphasize who is in control and the effects of our actions on the attitudes and well-being of civilians. The planning horizon encompasses not weeks or months, but years. Athena is a scalable, laptop-based simulation with weekly resolution. Up to three months of simulated time can pass between game turns that require user interaction. Athena's geographic scope is nominally a country, but can be a region within a county. Geographic resolution is "neighborhoods", which are defined by the user and may be actual neighborhoods, provinces, or anything in between. Models encompass phenomena whose effects are expected to be relevant over a medium-term planning horizon-three months to three years. The scope and intrinsic complexity of the problem dictate a spiral development process. That is, the model is used during development and lessons learned are used to improve the model. Even more important is that while every version must consider the "big picture" at some level of detail, development priority is given to those issues that are most relevant to currently anticipated studies. For example, models of the delivery and effectiveness of information operations messaging were among the additions in Athena 4.

Athena in 2013 and Beyond

NASA Technical Reports Server (NTRS)

Chamberlain, Robert G.; Duquette, William H.

2013-01-01

TRISA, the U.S. Army TRADOC G2 Intelligence Support Activity, received Athena 1 in 2009. They first used Athena 3 to support studies in 2011. This paper describes Athena 4, which they started using in October 2012. A final section discusses issues that are being considered for incorporation into Athena 5 and later. Athena's objective is to help skilled intelligence analysts anticipate the likely consequences of complex courses of action that use our country's entire power base, not just our military capabilities, for operations in troubled regions of the world. Measures of effectiveness emphasize who is in control and the effects of our actions on the attitudes and well being of civilians. The planning horizon encompasses not weeks or months, but years.Athena is a scalable, laptop-based simulation with weekly resolution. Up to three months of simulated time can pass between game turns that require user interaction. Athena's geographic scope is nominally a country, but can be a region within a county. Geographic resolution is "neighborhoods", which are defined by the user and may be actual neighborhoods, provinces, or anything in between. Models encompass phenomena whose effects are expected to be relevant over a medium-term planning horizon--three months to three years.The scope and intrinsic complexity of the problem dictate a spiral development process. That is, the model is used during development and lessons learned are used to improve the model. Even more important is that while every version must consider the "big picture" at some level of detail, development priority is given to those issues that are most relevant to currently anticipated studies. For example, models of the delivery and effectiveness of information operations messaging were among the additions in Athena 4.

Biocompatibility of poly(ethylene glycol) and poly(acrylic acid) interpenetrating network hydrogel by intrastromal implantation in rabbit cornea

PubMed Central

Zheng, Luo Luo; Vanchinathan, Vijay; Dalal, Roopa; Noolandi, Jaan; Waters, Dale J.; Hartmann, Laura; Cochran, Jennifer R.; Frank, Curtis W.; Yu, Charles Q.; Ta, Christopher N.

2015-01-01

We evaluated the biocompatibility of a poly(ethylene glycol) and poly(acrylic acid) (PEG/PAA) interpenetrating network hydrogel designed for artificial cornea in a rabbit model. PEG/PAA hydrogel measuring 6 mm in diameter was implanted in the corneal stroma of twelve rabbits. Stromal flaps were created with a microkeratome. Randomly, six rabbits were assigned to bear the implant for 2 months, two rabbits for 6 months, two rabbits for 9 months, one rabbit for 12 months, and one rabbit for 16 months. Rabbits were evaluated monthly. After the assigned period, eyes were enucleated, and corneas were processed for histology and immunohistochemistry. There were clear corneas in three of six rabbits that had implantation of hydrogel for 2 months. In the six rabbits with implant for 6 months or longer, the corneas remained clear in four. There was a high rate of epithelial defect and corneal thinning in these six rabbits. One planned 9-month rabbit developed extrusion of implant at 4 months. The cornea remained clear in the 16-month rabbit but histology revealed epithelial in-growth. Intrastromal implantation of PEG/PAA resulted in a high rate of long-term complications. PMID:25778285

Influence of backup bearings and support structure dynamics on the behavior of rotors with active supports

NASA Technical Reports Server (NTRS)

Flowers, George T.

1994-01-01

Substantial progress has been made toward the goals of this research effort in the past six months. A simplified rotor model with a flexible shaft and backup bearings has been developed. The model is based upon the work of Ishii and Kirk. Parameter studies of the behavior of this model are currently being conducted. A simple rotor model which includes a flexible disk and bearings with clearance has been developed and the dynamics of the model investigated. The study consists of simulation work coupled with experimental verification. The work is documented in the attached paper. A rotor model based upon the T-501 engine has been developed which includes backup bearing effects. The dynamics of this model are currently being studied with the objective of verifying the conclusions obtained from the simpler models. Parallel simulation runs are being conducted using an ANSYS based finite element model of the T-501.

Adjusting Wavelet-based Multiresolution Analysis Boundary Conditions for Robust Long-term Streamflow Forecasting Model

NASA Astrophysics Data System (ADS)

Maslova, I.; Ticlavilca, A. M.; McKee, M.

2012-12-01

There has been an increased interest in wavelet-based streamflow forecasting models in recent years. Often overlooked in this approach are the circularity assumptions of the wavelet transform. We propose a novel technique for minimizing the wavelet decomposition boundary condition effect to produce long-term, up to 12 months ahead, forecasts of streamflow. A simulation study is performed to evaluate the effects of different wavelet boundary rules using synthetic and real streamflow data. A hybrid wavelet-multivariate relevance vector machine model is developed for forecasting the streamflow in real-time for Yellowstone River, Uinta Basin, Utah, USA. The inputs of the model utilize only the past monthly streamflow records. They are decomposed into components formulated in terms of wavelet multiresolution analysis. It is shown that the model model accuracy can be increased by using the wavelet boundary rule introduced in this study. This long-term streamflow modeling and forecasting methodology would enable better decision-making and managing water availability risk.

Measuring Teachers' Learning from a Problem-Based Learning Approach to Professional Development in Science Education

ERIC Educational Resources Information Center

Weizman, Ayelet; Covitt, Beth A.; Koehler, Matthew J.; Lundeberg, Mary A.; Oslund, Joy A.; Low, Mark R.; Eberhardt, Janet; Urban-Lurain, Mark

2008-01-01

In this study we measured changes in science teachers' conceptual science understanding (content knowledge) and pedagogical content knowledge (PCK) while participating in a problem-based learning (PBL) model of professional development. Teachers participated in a two-week long workshop followed by nine monthly meetings during one academic year…

External validation of a six simple variable model of stroke outcome and verification in hyper-acute stroke.

PubMed

Reid, J M; Gubitz, G J; Dai, D; Reidy, Y; Christian, C; Counsell, C; Dennis, M; Phillips, S J

2007-12-01

We aimed to validate a previously described six simple variable (SSV) model that was developed from acute and sub-acute stroke patients in our population that included hyper-acute stroke patients. A Stroke Outcome Study enrolled patients from 2001 to 2002. Functional status was assessed at 6 months using the modified Rankin Scale (mRS). SSV model performance was tested in our cohort. 538 acute ischaemic (87%) and haemorrhagic stroke patients were enrolled, 51% of whom presented to hospital within 6 h of symptom recognition. At 6 months post-stroke, 42% of patients had a good outcome (mRS < or = 2). Stroke patients presenting within 6 h of symptom recognition were significantly older with higher stroke severity. In our Stroke Outcome Study dataset, the SSV model had an area under the curve of 0.792 for 6 month outcomes and performed well for hyper-acute or post-acute stroke, age < or > or = 75 years, haemorrhagic or ischaemic stroke, men or women, moderate and severe stroke, but poorly for mild stroke. This study confirms the external validity of the SSV model in our hospital stroke population. This model can therefore be utilised for stratification in acute and hyper-acute stroke trials.

Can we use Earth Observations to improve monthly water level forecasts?

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2017-12-01

Dynamical-statistical hydrologic forecasting approaches benefit from different strengths in comparison with traditional hydrologic forecasting systems: they are computationally efficient, can integrate and `learn' from a broad selection of input data (e.g., General Circulation Model (GCM) forecasts, Earth Observation time series, teleconnection patterns), and can take advantage of recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques). Recent efforts to develop a dynamical-statistical ensemble approach for forecasting seasonal streamflow using both GCM forecasts and changing land cover have shown promising results over the U.S. Midwest. Here, we use climate forecasts from several GCMs of the North American Multi Model Ensemble (NMME) alongside 15-minute stage time series from the National River Flow Archive (NRFA) and land cover classes extracted from the European Space Agency's Climate Change Initiative 300 m annual Global Land Cover time series. With these data, we conduct systematic long-range probabilistic forecasting of monthly water levels in UK catchments over timescales ranging from one to twelve months ahead. We evaluate the improvement in model fit and model forecasting skill that comes from using land cover classes as predictors in the models. This work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards from space using data science techniques.

Using GRACE and climate model simulations to predict mass loss of Alaskan glaciers through 2100

DOE PAGES

Wahr, John; Burgess, Evan; Swenson, Sean

2016-05-30

Glaciers in Alaska are currently losing mass at a rate of ~–50 Gt a –1, one of the largest ice loss rates of any regional collection of mountain glaciers on Earth. Existing projections of Alaska's future sea-level contributions tend to be divergent and are not tied directly to regional observations. Here we develop a simple, regional observation-based projection of Alaska's future sea-level contribution. We compute a time series of recent Alaska glacier mass variability using monthly GRACE gravity fields from August 2002 through December 2014. We also construct a three-parameter model of Alaska glacier mass variability based on monthly ERA-Interimmore » snowfall and temperature fields. When these three model parameters are fitted to the GRACE time series, the model explains 94% of the variance of the GRACE data. Using these parameter values, we then apply the model to simulated fields of monthly temperature and snowfall from the Community Earth System Model, to obtain predictions of mass variations through 2100. Here, we conclude that mass loss rates may increase between –80 and –110 Gt a –1by 2100, with a total sea-level rise contribution of 19 ± 4 mm during the 21st century.« less

Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate

DOE PAGES

Li, Wenliang; Zhou, Yuyu; Cetin, Kristen S.; ...

2018-03-24

Urban buildings account for up to 75% of total energy use in the United States (U.S.). Understanding urban building energy use is important for developing feasible options to mitigate energy use and greenhouse gas emissions. In this study, an improved bottom-up building energy use model, named City Building Energy Use Model (CityBEUM), was developed to estimate building energy use for all buildings in Polk County, Iowa. First, 28 commercial and 6 residential building prototypes were designed by combing Assessor's parcel data and building footprint data. Then, the EnergyPlus in the CityBEUM was calibrated for all building prototypes using the U.S.more » Energy Information Administration's survey data, monthly utility meter data, and actual weather data. Finally, spatial and temporal variations of building energy use in the study area were estimated using the CityBEUM. Results indicate that the spatial variation of building energy use in the study area can be captured using the CityBEUM. With the monthly-calibrated model, the temporal pattern of urban building energy use can be well represented. The comparison of building energy use using the Typical Meteorological Year and actual weather data demonstrates the importance of using actual weather data in building energy modeling for an improved temporal representation.« less

Developing a landscape of urban building energy use with improved spatiotemporal representations in a cool-humid climate

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

Li, Wenliang; Zhou, Yuyu; Cetin, Kristen S.

Urban buildings account for up to 75% of total energy use in the United States (U.S.). Understanding urban building energy use is important for developing feasible options to mitigate energy use and greenhouse gas emissions. In this study, an improved bottom-up building energy use model, named City Building Energy Use Model (CityBEUM), was developed to estimate building energy use for all buildings in Polk County, Iowa. First, 28 commercial and 6 residential building prototypes were designed by combing Assessor's parcel data and building footprint data. Then, the EnergyPlus in the CityBEUM was calibrated for all building prototypes using the U.S.more » Energy Information Administration's survey data, monthly utility meter data, and actual weather data. Finally, spatial and temporal variations of building energy use in the study area were estimated using the CityBEUM. Results indicate that the spatial variation of building energy use in the study area can be captured using the CityBEUM. With the monthly-calibrated model, the temporal pattern of urban building energy use can be well represented. The comparison of building energy use using the Typical Meteorological Year and actual weather data demonstrates the importance of using actual weather data in building energy modeling for an improved temporal representation.« less

Radiotherapy induced dermatitis is a strong predictor for late fibrosis in head and neck cancer. The development of a predictive model for late fibrosis.

PubMed

Nevens, Daan; Duprez, Fréderic; Daisne, Jean Francois; Laenen, Annouschka; De Neve, Wilfried; Nuyts, Sandra

2017-02-01

To determine if the severity of radiodermatitis at the end of radio(chemo)therapy (R(C)T) for head and neck cancer (HNC) is a predictive factor for late fibrosis of the neck and to find a model to predict neck fibrosis grade⩾2 (fibrosis RTOG 2-4 ) at 6months following R(C)T for HNC. 161 patients were prospectively included. We correlated radiodermatitis at the end of RCT, age, sex, T/N stage, tumor site, concomitant chemotherapy, upfront neck dissection, neo-adjuvant chemotherapy, accelerated RT, smoking, alcohol consumption, HPV status and the dose prescribed to the elective neck with fibrosis RTOG 2-4 6months after the end of treatment. Radiodermatitis at the end of R(C)T ⩾grade 3 proved to be associated with the incidence of fibrosis RTOG 2-4 at 6months (p<0.01). Furthermore, upfront neck dissection (p<0.01), increasing N stage (p<0.01) and tumor site (p=0.02) are significantly associated in univariate analysis with fibrosis RTOG 2-4 at 6months of follow-up. Upfront neck dissection and radiodermatitis grade⩾3 at the end of R(C)T were identified by our multivariate model. Additionally, increasing N stage was selected as an independent predictor variable. The AUC for this model was 0.92. A model for the prediction of fibrosis RTOG 2-4 following R(C)T for head and neck cancer is presented with an AUC of 0.92. Interestingly, radiodermatitis grade⩾3 at the end of R(C)T is associated with RTOG 2-4 fibrosis at 6months. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Migration timing and parenting practices: Contributions to social development in preschoolers with foreign-born and native-born mothers

PubMed Central

Glick, Jennifer E.; Hanish, Laura D.; Yabiku, Scott T.; Bradley, Robert H.

2012-01-01

Little is known about how key aspects of parental migration or child-rearing history affect social development across children from immigrant families. Relying on data on approximately 6,400 children from the Early Childhood Longitudinal Study – Birth Cohort, analyses assessed the role of mothers’ age at migration on children’s social development in the United States (sociability and problem behaviors). Consistent with models of divergent adaptation and assimilation, the relationship between age at arrival and children’s social development is not linear. Parenting practices, observed when children were approximately 24 months of age, partially mediated the relation between mothers’ age at arrival and children’s social development reported at approximate age 48 months, particularly in the case of mothers who arrived as adults. PMID:22966921

A short-term ionospheric forecasting empirical regional model (IFERM) to predict the critical frequency of the F2 layer during moderate, disturbed, and very disturbed geomagnetic conditions over the European area

NASA Astrophysics Data System (ADS)

Pietrella, M.

2012-02-01

A short-term ionospheric forecasting empirical regional model (IFERM) has been developed to predict the state of the critical frequency of the F2 layer (foF2) under different geomagnetic conditions. IFERM is based on 13 short term ionospheric forecasting empirical local models (IFELM) developed to predict foF2 at 13 ionospheric observatories scattered around the European area. The forecasting procedures were developed by taking into account, hourly measurements of foF2, hourly quiet-time reference values of foF2 (foF2QT), and the hourly time-weighted accumulation series derived from the geomagnetic planetary index ap, (ap(τ)), for each observatory. Under the assumption that the ionospheric disturbance index ln(foF2/foF2QT) is correlated to the integrated geomagnetic disturbance index ap(τ), a set of statistically significant regression coefficients were established for each observatory, over 12 months, over 24 h, and under 3 different ranges of geomagnetic activity. This data was then used as input to compute short-term ionospheric forecasting of foF2 at the 13 local stations under consideration. The empirical storm-time ionospheric correction model (STORM) was used to predict foF2 in two different ways: scaling both the hourly median prediction provided by IRI (STORM_foF2MED,IRI model), and the foF2QT values (STORM_foF2QT model) from each local station. The comparison between the performance of STORM_foF2MED,IRI, STORM_foF2QT, IFELM, and the foF2QT values, was made on the basis of root mean square deviation (r.m.s.) for a large number of periods characterized by moderate, disturbed, and very disturbed geomagnetic activity. The results showed that the 13 IFELM perform much better than STORM_foF2,sub>MED,IRI and STORM_foF2QT especially in the eastern part of the European area during the summer months (May, June, July, and August) and equinoctial months (March, April, September, and October) under disturbed and very disturbed geomagnetic conditions, respectively. The performance of IFELM is also very good in the western and central part of the Europe during the summer months under disturbed geomagnetic conditions. STORM_foF2MED,IRI performs particularly well in central Europe during the equinoctial months under moderate geomagnetic conditions and during the summer months under very disturbed geomagnetic conditions. The forecasting maps generated by IFERM on the basis of the results provided by the 13 IFELM, show very large areas located at middle-high and high latitudes where the foF2 predictions quite faithfully match the foF2 measurements, and consequently IFERM can be used for generating short-term forecasting maps of foF2 (up to 3 h ahead) over the European area.

Description and initial evaluation of an educational and psychosocial support model for adults with congenitally malformed hearts.

PubMed

Rönning, Helén; Nielsen, Niels Erik; Swahn, Eva; Strömberg, Anna

2011-05-01

Various programmes for adults with congenitally malformed hearts have been developed, but detailed descriptions of content, rationale and goals are often missing. The aim of this study was to describe and make an initial evaluation of a follow-up model for adults with congenitally malformed hearts, focusing on education and psychosocial support by a multidisciplinary team (EPS). The model is described in steps and evaluated with regards to perceptions of knowledge, anxiety and satisfaction. The EPS model included a policlinic visit to the physician/nurse (medical consultation, computer-based and individual education face-to-face as well as psychosocial support) and a 1-month telephone follow-up. Fifty-five adults (mean age 34, 29 women) with the nine most common forms of congenitally malformed hearts participated in the EPS model as well as the 3-months follow-up. Knowledge about congenital heart malformation had increased in 40% of the participants at the 3-months follow-up. This study describes and evaluates a model that combines a multidisciplinary approach and computer-based education for follow-up of adults with congenitally malformed hearts. The EPS model was found to increase self-estimated knowledge, but further evaluations need to be conducted to prove patient-centred outcomes over time. The model is now ready to be implemented in adults with congenitally malformed hearts. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

NMME Monthly / Seasonal Forecasts for NASA SERVIR Applications Science

NASA Astrophysics Data System (ADS)

Robertson, F. R.; Roberts, J. B.

2014-12-01

This work details use of the North American Multi-Model Ensemble (NMME) experimental forecasts as drivers for Decision Support Systems (DSSs) in the NASA / USAID initiative, SERVIR (a Spanish acronym meaning "to serve"). SERVIR integrates satellite observations, ground-based data and forecast models to monitor and forecast environmental changes and to improve response to natural disasters. Through the use of DSSs whose "front ends" are physically based models, the SERVIR activity provides a natural testbed to determine the extent to which NMME monthly to seasonal projections enable scientists, educators, project managers and policy implementers in developing countries to better use probabilistic outlooks of seasonal hydrologic anomalies in assessing agricultural / food security impacts, water availability, and risk to societal infrastructure. The multi-model NMME framework provides a "best practices" approach to probabilistic forecasting. The NMME forecasts are generated at resolution more coarse than that required to support DSS models; downscaling in both space and time is necessary. The methodology adopted here applied model output statistics where we use NMME ensemble monthly projections of sea-surface temperature (SST) and precipitation from 30 years of hindcasts with observations of precipitation and temperature for target regions. Since raw model forecasts are well-known to have structural biases, a cross-validated multivariate regression methodology (CCA) is used to link the model projected states as predictors to the predictands of the target region. The target regions include a number of basins in East and South Africa as well as the Ganges / Baramaputra / Meghna basin complex. The MOS approach used address spatial downscaling. Temporal disaggregation of monthly seasonal forecasts is achieved through use of a tercile bootstrapping approach. We interpret the results of these studies, the levels of skill by several metrics, and key uncertainties.

NMME Monthly / Seasonal Forecasts for NASA SERVIR Applications Science

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Roberts, Jason B.

2014-01-01

This work details use of the North American Multi-Model Ensemble (NMME) experimental forecasts as drivers for Decision Support Systems (DSSs) in the NASA / USAID initiative, SERVIR (a Spanish acronym meaning "to serve"). SERVIR integrates satellite observations, ground-based data and forecast models to monitor and forecast environmental changes and to improve response to natural disasters. Through the use of DSSs whose "front ends" are physically based models, the SERVIR activity provides a natural testbed to determine the extent to which NMME monthly to seasonal projections enable scientists, educators, project managers and policy implementers in developing countries to better use probabilistic outlooks of seasonal hydrologic anomalies in assessing agricultural / food security impacts, water availability, and risk to societal infrastructure. The multi-model NMME framework provides a "best practices" approach to probabilistic forecasting. The NMME forecasts are generated at resolution more coarse than that required to support DSS models; downscaling in both space and time is necessary. The methodology adopted here applied model output statistics where we use NMME ensemble monthly projections of sea-surface temperature (SST) and precipitation from 30 years of hindcasts with observations of precipitation and temperature for target regions. Since raw model forecasts are well-known to have structural biases, a cross-validated multivariate regression methodology (CCA) is used to link the model projected states as predictors to the predictands of the target region. The target regions include a number of basins in East and South Africa as well as the Ganges / Baramaputra / Meghna basin complex. The MOS approach used address spatial downscaling. Temporal disaggregation of monthly seasonal forecasts is achieved through use of a tercile bootstrapping approach. We interpret the results of these studies, the levels of skill by several metrics, and key uncertainties.

A national-scale seasonal hydrological forecast system: development and evaluation over Britain

NASA Astrophysics Data System (ADS)

Bell, Victoria A.; Davies, Helen N.; Kay, Alison L.; Brookshaw, Anca; Scaife, Adam A.

2017-09-01

Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better) rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (hindcasts) from the GloSea5 model (1996 to 2009) are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean) rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region). Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 %) in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows), whereas for the 3-month ahead lead time, GloSea5 forecasts account for ˜ 70 % of the forecast skill (mostly in areas of high rainfall to the north and west) and only 30 % of the skill arises from hydrological memory (typically groundwater-dominated areas). Given the high spatial heterogeneity in typical patterns of UK rainfall and evaporation, future development of skilful spatially distributed seasonal forecasts could lead to substantial improvements in seasonal flow forecast capability, potentially benefitting practitioners interested in predicting hydrological extremes, not only in the UK but also across Europe.

The emergency first aid responder system model: using community members to assist life-threatening emergencies in violent, developing areas of need.

PubMed

Sun, Jared H; Wallis, Lee A

2012-08-01

As many as 90% of all trauma-related deaths occur in developing nations, and this is expected to get worse with modernisation. The current method of creating an emergency care system by modelling after that of a Western nation is too resource-heavy for most developing countries to handle. A cheaper, more community-based model is needed to establish new emergency care systems and to support them to full maturity. A needs assessment was undertaken in Manenberg, a township in Cape Town with high violence and injury rates. Community leaders and successfully established local services were consulted for the design of a first responder care delivery model. The resultant community-based emergency first aid responder (EFAR) system was implemented, and EFARs were tracked over time to determine skill retention and usage. The EFAR system model and training curriculum. Basic EFARs are spread throughout the community with the option of becoming stationed advanced EFARs. All EFARs are overseen by a local organisation and a professional body, and are integrated with the local ambulance response if one exists. On competency examinations, all EFARs tested averaged 28.2% before training, 77.8% after training, 71.3% 4 months after training and 71.0% 6 months after training. EFARs reported using virtually every skill taught them, and further review showed that they had done so adequately. The EFAR system is a low-cost, versatile model that can be used in a developing region both to lay the foundation for an emergency care system or support a new one to maturity.

Stochastic Generation of Monthly Rainfall Data

NASA Astrophysics Data System (ADS)

Srikanthan, R.

2009-03-01

Monthly rainfall data is generally needed in the simulation of water resources systems, and in the estimation of water yield from large catchments. Monthly streamflow data generation models are usually applied to generate monthly rainfall data, but this presents problems for most regions, which have significant months of no rainfall. In an earlier study, Srikanthan et al. (J. Hydrol. Eng., ASCE 11(3) (2006) 222-229) recommended the modified method of fragments to disaggregate the annual rainfall data generated by a first-order autoregressive model. The main drawback of this approach is the occurrence of similar patterns when only a short length of historic data is available. Porter and Pink (Hydrol. Water Res. Symp. (1991) 187-191) used synthetic fragments from a Thomas-Fiering monthly model to overcome this drawback. As an alternative, a new two-part monthly model is nested in an annual model to generate monthly rainfall data which preserves both the monthly and annual characteristics. This nested model was applied to generate rainfall data from seven rainfall stations located in eastern and southern parts of Australia, and the results showed that the model performed satisfactorily.

Cognitive Delay and Behavior Problems Prior to School Age

PubMed Central

Palta, Mari; Kotelchuck, Milton; Poehlmann, Julie; Witt, Whitney P.

2014-01-01

OBJECTIVE: To investigate the relationship between cognitive delay (CD) and behavior problems between ages 9 months and 5 years, while adjusting for covariates related to CD. METHODS: Data were from 4 waves of the Early Childhood Longitudinal Study, Birth Cohort (n = 8000). Children were classified as typically developing (TD) or as having resolved, newly developed, or persistent CD between 9 and 24 months, based on scores from the Bayley Short Form-Research Edition below or above the 10th percentile. Child behavior was measured by using the Infant/Toddler Symptom Checklist (ages 9 and 24 months) and the Preschool and Kindergarten Behavior Scales (ages 4 and 5 years); children in the top 10th percentile were considered to have a behavior problem. Hierarchical linear modeling estimated the effect of CD status on children’s behavioral trajectories, adjusted for confounders. RESULTS: CD resolved for 80.3% of children between 9 and 24 months. Behavior problems at 24 months were detected in 19.3%, 21.8%, and 35.5% of children with resolved, newly developed, and persistent CD, respectively, versus 13.0% of TD children. Behavior problems increased among children with CD over time, and more so among children with persistent CD. By age 5, children with persistent CD had behavior scores moderately (0.59 SD) higher than TD children. CONCLUSIONS: Behavior problems among children with CD are slightly higher at 9 months, clearly evident by 24 months, and increase as children move toward school age. Efforts to promote the earliest identification, evaluation, and service referral may be necessary to improve outcomes for these children. PMID:25113290

Monthly sediment discharge changes and estimates in a typical karst catchment of southwest China

NASA Astrophysics Data System (ADS)

Li, Zhenwei; Xu, Xianli; Xu, Chaohao; Liu, Meixian; Wang, Kelin; Yi, Ruzhou

2017-12-01

As one of the largest karst regions in the world, southwest China is experiencing severe soil erosion due to its special geological conditions, inappropriate land use, and lower soil loss tolerance. Knowledge and accurate estimations of changes in sediment discharge rates is important for finding potential measures to effectively control sediment delivery. This study investigated temporal variation in monthly sediment discharge (SD), and developed sediment rating curves and state-space model to estimate SD. Monthly water discharge, SD, precipitation, potential evapotranspiration, and normalized differential vegetation index during 2003-2015 collected from a typical karst catchment of Yujiang River were analyzed in present study. A Mann-Kendal test and Morlet wavelet analysis were employed to detect the changes in SD. Results indicated that a decreasing trend was observed in sediment discharge at monthly and annual scale. The water and sediment discharge both had a significant 1-year period, implying that water discharge has substantial influence on SD. The best state-space model using water discharge was a simple but effective model, accounting for 99% of the variation in SD. The sediment rating curves, however, represented only 78% of the variation in SD. This study provides an insight into the possibility of accurate estimation of SD only using water discharge with state-space model approach. State-space model is recommended as an effective approach for quantifying the temporal relationships between SD and its driving factors in karst regions of southwest China.

Development of a multihospital pharmacy quality assurance program.

PubMed

Hoffmann, R P; Ravin, R; Colaluca, D M; Gifford, R; Grimes, D; Grzegorczyk, R; Keown, F; Kuhr, F; McKay, R; Peyser, J; Ryan, R; Zalewski, C

1980-07-01

Seven community hospitals have worked cooperatively for 18 months to develop an initial hospital pharmacy quality assurance program. Auditing criteria were developed for nine service areas corresponding to the model program developed by the American Society of Hospital Pharmacists. Current plans are to implement and modify this program as required at each participating hospital. Follow-up programs will also be essential to a functional, ongoing program, and these will be developed in the future.

Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam

USGS Publications Warehouse

Rosa, Sarah N.; Hay, Lauren E.

2017-12-01

In 2014, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense’s Strategic Environmental Research and Development Program, initiated a project to evaluate the potential impacts of projected climate-change on Department of Defense installations that rely on Guam’s water resources. A major task of that project was to develop a watershed model of southern Guam and a water-balance model for the Fena Valley Reservoir. The southern Guam watershed model provides a physically based tool to estimate surface-water availability in southern Guam. The U.S. Geological Survey’s Precipitation Runoff Modeling System, PRMS-IV, was used to construct the watershed model. The PRMS-IV code simulates different parts of the hydrologic cycle based on a set of user-defined modules. The southern Guam watershed model was constructed by updating a watershed model for the Fena Valley watersheds, and expanding the modeled area to include all of southern Guam. The Fena Valley watershed model was combined with a previously developed, but recently updated and recalibrated Fena Valley Reservoir water-balance model.Two important surface-water resources for the U.S. Navy and the citizens of Guam were modeled in this study; the extended model now includes the Ugum River watershed and improves upon the previous model of the Fena Valley watersheds. Surface water from the Ugum River watershed is diverted and treated for drinking water, and the Fena Valley watersheds feed the largest surface-water reservoir on Guam. The southern Guam watershed model performed “very good,” according to the criteria of Moriasi and others (2007), in the Ugum River watershed above Talofofo Falls with monthly Nash-Sutcliffe efficiency statistic values of 0.97 for the calibration period and 0.93 for the verification period (a value of 1.0 represents perfect model fit). In the Fena Valley watershed, monthly simulated streamflow volumes from the watershed model compared reasonably well with the measured values for the gaging stations on the Almagosa, Maulap, and Imong Rivers—tributaries to the Fena Valley Reservoir—with Nash-Sutcliffe efficiency values of 0.87 or higher. The southern Guam watershed model simulated the total volume of the critical dry season (January to May) streamflow for the entire simulation period within –0.54 percent at the Almagosa River, within 6.39 percent at the Maulap River, and within 6.06 percent at the Imong River.The recalibrated water-balance model of the Fena Valley Reservoir generally simulated monthly reservoir storage volume with reasonable accuracy. For the calibration and verification periods, errors in end-of-month reservoir-storage volume ranged from 6.04 percent (284.6 acre-feet or 92.7 million gallons) to –5.70 percent (–240.8 acre-feet or –78.5 million gallons). Monthly simulation bias ranged from –0.48 percent for the calibration period to 0.87 percent for the verification period; relative error ranged from –0.60 to 0.88 percent for the calibration and verification periods, respectively. The small bias indicated that the model did not consistently overestimate or underestimate reservoir storage volume.In the entirety of southern Guam, the watershed model has a “satisfactory” to “very good” rating when simulating monthly mean streamflow for all but one of the gaged watersheds during the verification period. The southern Guam watershed model uses a more sophisticated climate-distribution scheme than the older model to make use of the sparse climate data, as well as includes updated land-cover parameters and the capability to simulate closed depression areas.The new Fena Valley Reservoir water-balance model is useful as an updated tool to forecast short-term changes in the surface-water resources of Guam. Furthermore, the now spatially complete southern Guam watershed model can be used to evaluate changes in streamflow and recharge owing to climate or land-cover changes. These are substantial improvements to the previous models of the Fena Valley watershed and Reservoir. Datasets associated with this report are available as a U.S. Geological Survey data release (Rosa and Hay, 2017; DOI:10.5066/F7HH6HV4).

A new monthly gravity field model based on GRACE observations computed by the modified dynamic approach

NASA Astrophysics Data System (ADS)

Zhou, H.; Luo, Z.; Li, Q.; Zhong, B.

2016-12-01

The monthly gravity field model can be used to compute the information about the mass variation within the system Earth, i.e., the relationship between mass variation in the oceans, land hydrology, and ice sheets. For more than ten years, GRACE has provided valuable information for recovering monthly gravity field model. In this study, a new time series of GRACE monthly solution, which is truncated to degree and order 60, is computed by the modified dynamic approach. Compared with the traditional dynamic approach, the major difference of our modified approach is the way to process the nuisance parameters. This type of parameters is mainly used to absorb low-frequency errors in KBRR data. One way is to remove the nuisance parameters before estimating the geo-potential coefficients, called Pure Predetermined Strategy (PPS). The other way is to determine the nuisance parameters and geo-potential coefficients simultaneously, called Pure Simultaneous Strategy (PSS). It is convenient to detect the gross error by PPS, while there is also obvious signal loss compared with the solutions derived from PSS. After comparing the difference of practical calculation formulas between PPS and PSS, we create the Filter Predetermine Strategy (FPS), which can combine the advantages of PPS and PSS efficiently. With FPS, a new monthly gravity field model entitled HUST-Grace2016s is developed. The comparisons of geoid degree powers and mass change signals in the Amazon basin, the Greenland and the Antarctic demonstrate that our model is comparable with the other published models, e.g., the CSR RL05, JPL RL05 and GFZ RL05 models. Acknowledgements: This work is supported by China Postdoctoral Science Foundation (Grant No.2016M592337), the National Natural Science Foundation of China (Grant Nos. 41131067, 41504014), the Open Research Fund Program of the State Key Laboratory of Geodesy and Earth's Dynamics (Grant No. SKLGED2015-1-3-E).

Development of a precipitation-runoff model to simulate unregulated streamflow in the South Fork Flathead River Basin, Montana

USGS Publications Warehouse

Chase, K.J.

2011-01-01

This report documents the development of a precipitation-runoff model for the South Fork Flathead River Basin, Mont. The Precipitation-Runoff Modeling System model, developed in cooperation with the Bureau of Reclamation, can be used to simulate daily mean unregulated streamflow upstream and downstream from Hungry Horse Reservoir for water-resources planning. Two input files are required to run the model. The time-series data file contains daily precipitation data and daily minimum and maximum air-temperature data from climate stations in and near the South Fork Flathead River Basin. The parameter file contains values of parameters that describe the basin topography, the flow network, the distribution of the precipitation and temperature data, and the hydrologic characteristics of the basin soils and vegetation. A primary-parameter file was created for simulating streamflow during the study period (water years 1967-2005). The model was calibrated for water years 1991-2005 using the primary-parameter file. This calibration was further refined using snow-covered area data for water years 2001-05. The model then was tested for water years 1967-90. Calibration targets included mean monthly and daily mean unregulated streamflow upstream from Hungry Horse Reservoir, mean monthly unregulated streamflow downstream from Hungry Horse Reservoir, basin mean monthly solar radiation and potential evapotranspiration, and daily snapshots of basin snow-covered area. Simulated streamflow generally was in better agreement with observed streamflow at the upstream gage than at the downstream gage. Upstream from the reservoir, simulated mean annual streamflow was within 0.0 percent of observed mean annual streamflow for the calibration period and was about 2 percent higher than observed mean annual streamflow for the test period. Simulated mean April-July streamflow upstream from the reservoir was about 1 percent lower than observed streamflow for the calibration period and about 4 percent higher than observed for the test period. Downstream from the reservoir, simulated mean annual streamflow was 17 percent lower than observed streamflow for the calibration period and 12 percent lower than observed streamflow for the test period. Simulated mean April-July streamflow downstream from the reservoir was 13 percent lower than observed streamflow for the calibration period and 6 percent lower than observed streamflow for the test period. Calibrating to solar radiation, potential evapotranspiration, and snow-covered area improved the model representation of evapotranspiration, snow accumulation, and snowmelt processes. Simulated basin mean monthly solar radiation values for both the calibration and test periods were within 9 percent of observed values except during the month of December (28 percent different). Simulated basin potential evapotranspiration values for both the calibration and test periods were within 10 percent of observed values except during the months of January (100 percent different) and February (13 percent different). The larger percent errors in simulated potential evaporation occurred in the winter months when observed potential evapotranspiration values were very small; in January the observed value was 0.000 inches and in February the observed value was 0.009 inches. Simulated start of melting of the snowpack occurred at about the same time as observed start of melting. The simulated snowpack accumulated to 90-100 percent snow-covered area 1 to 3 months earlier than observed snowpack. This overestimated snowpack during the winter corresponded to underestimated streamflow during the same period. In addition to the primary-parameter file, four other parameter files were created: for a "recent" period (1991-2005), a historical period (1967-90), a "wet" period (1989-97), and a "dry" period (1998-2005). For each data file of projected precipitation and air temperature, a single parameter file can be used to simulate a s

Adapting and Implementing a Community Program to Improve Retention in Care among Patients with HIV in Southern Haiti: "Group of 6".

PubMed

Naslund, John A; Dionne-Odom, Jodie; Junior Destiné, Cléonas; Jogerst, Kristen M; Renold Sénécharles, Redouin; Jean Louis, Michelande; Desir, Jasmin; Néptune Ledan, Yvette; Beauséjour, Jude Ronald; Charles, Roland; Werbel, Alice; Talbot, Elizabeth A; Joseph, Patrice; Pape, Jean William; Wright, Peter F

2014-01-01

Objective. In Mozambique, a patient-led Community ART Group model developed by Médecins Sans Frontières improved retention in care and adherence to antiretroviral therapy (ART) among persons with HIV. We describe the adaptation and implementation of this model within the HIV clinic located in the largest public hospital in Haiti's Southern Department. Methods. Our adapted model was named Group of 6. Hospital staff enabled stable patients with HIV receiving ART to form community groups with 4-6 members to facilitate monthly ART distribution, track progress and adherence, and provide support. Implementation outcomes included recruitment success, participant retention, group completion of monthly monitoring forms, and satisfaction surveys. Results. Over one year, 80 patients from nine communities enrolled into 15 groups. Six participants left to receive HIV care elsewhere, two moved away, and one died of a non-HIV condition. Group members successfully completed monthly ART distribution and returned 85.6% of the monthly monitoring forms. Members reported that Group of 6 made their HIV management easier and hospital staff reported that it reduced their workload. Conclusions. We report successful adaptation and implementation of a validated community HIV-care model in Southern Haiti. Group of 6 can reduce barriers to ART adherence, and will be integrated as a routine care option.

Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China

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

Zhang, Xuejun; Tang, Qiuhong; Liu, Xingcai

Real-time monitoring and predicting drought development with several months in advance is of critical importance for drought risk adaptation and mitigation. In this paper, we present a drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity (VIC) hydrologic model over Southwest China (SW). The satellite precipitation data are used to force VIC model for near real-time estimate of land surface hydrologic conditions. As initialized with satellite-aided monitoring, the climate model-based forecast (CFSv2_VIC) and ensemble streamflow prediction (ESP)-based forecast (ESP_VIC) are both performed and evaluated through their ability in reproducing the evolution of the 2009/2010 severe drought overmore » SW. The results show that the satellite-aided monitoring is able to provide reasonable estimate of forecast initial conditions (ICs) in a real-time manner. Both of CFSv2_VIC and ESP_VIC exhibit comparable performance against the observation-based estimates for the first month, whereas the predictive skill largely drops beyond 1-month. Compared to ESP_VIC, CFSv2_VIC shows better performance as indicated by the smaller ensemble range. This study highlights the value of this operational framework in generating near real-time ICs and giving a reliable prediction with 1-month ahead, which has great implications for drought risk assessment, preparation and relief.« less

Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

PubMed

Abbasi, Maryam; El Hanandeh, Ali

2016-10-01

Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Developing Multi-model Ensemble for Precipitation and Temperature Seasonal Forecasts: Implications for Karkheh River Basin in Iran

NASA Astrophysics Data System (ADS)

Najafi, Husain; Massah Bavani, Ali Reza; Wanders, Niko; Wood, Eric; Irannejad, Parviz; Robertson, Andrew

2017-04-01

Water resource managers can utilize reliable seasonal forecasts for allocating water between different users within a water year. In the west of Iran where a decline of renewable water resources has been observed, basin-wide water management has been the subject of many inter-provincial conflicts in recent years. The problem is exacerbated when the environmental water requirements is not provided leaving the Hoor-al-Azim marshland in the downstream dry. It has been argued that information on total seasonal rainfall can support the Iranian Ministry of Energy within the water year. This study explores the skill of the North America Multi Model Ensemble for Karkheh River Basin in the of west Iran. NMME seasonal precipitation and temperature forecasts from eight models are evaluated against PERSIANN-CDR and Climate Research Unit (CRU) datasets. Analysis suggests that anomaly correlation for both precipitation and temperature is greater than 0.4 for all individual models. Lead time-dependent seasonal forecasts are improved when a multi-model ensemble is developed for the river basin using stepwise linear regression model. MME R-squared exceeds 0.6 for temperature for almost all initializations suggesting high skill of NMME in Karkheh river basin. The skill of MME for rainfall forecasts is high for 1-month lead time for October, February, March and October initializations. However, for months when the amount of rainfall accounts for a significant proportion of total annual rainfall, the skill of NMME is limited a month in advance. It is proposed that operational regional water companies incorporate NMME seasonal forecasts into water resource planning and management, especially during growing seasons that are essential for agricultural risk management.

Risking it for Love: Romantic Relationships and Early Pubertal Development Confer Risk for later Disruptive Behavior Disorders in African-American Girls Receiving Psychiatric Care

PubMed Central

Rodriguez, Erin M.; Nichols, Sara; Emerson, Erin; Donenberg, Geri R.

2014-01-01

Disruptive behavior problems (DBP) represent a growing concern for young women (e.g., Snyder & Sickmund, 2006), but gender-specific investigations have been traditionally underrepresented in this area. The purpose of this study is to examine the associations among gender-relevant risk factors for DBP among 217 African American girls in psychiatric care. African American girls, 12–16 years old (M=14.6; SD=1.2), and their primary female caregivers (N=254) were recruited from outpatient mental health clinics and reported on girls’ DBP, heterosexual dating experiences (romantic and sexual), peer relationships, pubertal development, and self-silencing at baseline, 6-, and 12-months. Structural Equation Modeling examined evidence for full versus mediated (via self-silencing) models and the structural relationships (direct and indirect) among key study variables. Results suggest that the full model was a significantly better fit than the mediated model as indicated by a Chi-squared difference test (p < .01). In the full model, direct effects of greater romantic dating experiences and lower quality peer relationships at baseline predicted DBP at 12-months. Sexual dating experiences were more strongly linked with DBP at 12-months for early maturing compared to average or later maturing girls. Indirect effects analyses suggested that girls’ suppression of relational needs, assessed through a measure of self-silencing, explained the association between peer relationships and DBP. Findings highlight the importance of the relational context for girls’ DBP, with treatment implications supporting relationship-based models of care, early intervention, and skill building around negotiating needs with peers and partners. PMID:24748499

Assessment of Ground-Water Resources in the Seacoast Region of New Hampshire

USGS Publications Warehouse

Mack, Thomas J.

2009-01-01

Numerical ground-water-flow models were developed for a 160-square-mile area of coastal New Hampshire to provide insight into the recharge, discharge, and availability of ground water. Population growth and increasing water use prompted concern for the sustainability of the region's ground-water resources. Previously, the regional hydraulic characteristics of the fractured bedrock aquifer in the Seacoast region of New Hampshire were not well known. In the current study, the ground-water-flow system was assessed by using two different models developed and calibrated under steady-state seasonal low-flow and transient monthly conditions to ground-water heads and base-flow discharges. The models were, (1) a steady-state model representing current (2003-04) seasonal low-flow conditions used to simulate current and future projected water use during low-flow conditions; and (2) a transient model representing current average and estimated future monthly conditions over a 2-year period used to simulate current and future projected climate-change conditions. The analysis by the ground-water-flow models indicates that the Seacoast aquifer system is a transient flow system with seasonal variations in ground-water flow. A pseudosteady- state condition exists in the fall when the steady-state model was calibrated. The average annual recharge during the period analyzed, 2000-04, was approximately 51 percent of the annual precipitation. The average net monthly recharge rate between 2003 and 2004 varied from 5.5 inches per month in March, to zero in July, and to about 0.3 inches per month in August and September. Recharge normally increases to about 2 inches per month in late fall and early winter (November through December) and declines to about 1.5 inches per month in late winter (January and February). About 50 percent of the annual recharge coincides with snowmelt in the spring (March and April), and 20 percent occurs in the late fall and early winter (November through February). Net recharge, calculated as infiltration of precipitation minus evapotranspiration, can be negative during summer months (particularly July). Regional bulk hydraulic conductivities of the bedrock aquifer were estimated to be about 0.1 to 1.0 feet per day. Estimated hydraulic conductivities in model areas representing the Rye Complex and the Kittery Formation were higher (0.5 to 1 foot per day) than in areas representing the Eliot Formation, the Exeter Diorite, and the Newburyport Complex, which have estimated hydraulic conductivities of 0.1 to 0.2 foot per day. A northeast-southwest regional anisotropy of about 5:1 was estimated in some areas of the model; this pattern is parallel to the regional structural trend and predominant fracture orientation. In areas of the model with more observation data, the upper and lower 95-percent confidence intervals for the estimated bedrock hydraulic conductivity were about half an order of magnitude above and below the parameter, respectively, and the estimated confidence intervals for estimated specific storage were within an order of magnitude of the parameter. In areas of the model with few data points, or few stresses, confidence intervals were several orders of magnitude. Estimated model parameters and their confidence intervals are a function of the conceptual model design, observation data, and the weights placed on the data. The amount of recharge that enters the bedrock aquifer at a specific point depends on (1) the location of the point in the flow field; (2) the hydraulic conductivity of the bedrock (or the connectivity of fractures); and (3) the stresses within the bedrock aquifer. In addition, ground water stored in unconsolidated overburden sediments, including till and other fine-grained sediments, may constitute a large percentage of the water available from storage to the bedrock aquifer. Recharge into the bedrock aquifer at a point can range from zero to nearly all the recharge at the surface dependin

Quantitative prediction of oral cancer risk in patients with oral leukoplakia.

PubMed

Liu, Yao; Li, Yicheng; Fu, Yue; Liu, Tong; Liu, Xiaoyong; Zhang, Xinyan; Fu, Jie; Guan, Xiaobing; Chen, Tong; Chen, Xiaoxin; Sun, Zheng

2017-07-11

Exfoliative cytology has been widely used for early diagnosis of oral squamous cell carcinoma. We have developed an oral cancer risk index using DNA index value to quantitatively assess cancer risk in patients with oral leukoplakia, but with limited success. In order to improve the performance of the risk index, we collected exfoliative cytology, histopathology, and clinical follow-up data from two independent cohorts of normal, leukoplakia and cancer subjects (training set and validation set). Peaks were defined on the basis of first derivatives with positives, and modern machine learning techniques were utilized to build statistical prediction models on the reconstructed data. Random forest was found to be the best model with high sensitivity (100%) and specificity (99.2%). Using the Peaks-Random Forest model, we constructed an index (OCRI2) as a quantitative measurement of cancer risk. Among 11 leukoplakia patients with an OCRI2 over 0.5, 4 (36.4%) developed cancer during follow-up (23 ± 20 months), whereas 3 (5.3%) of 57 leukoplakia patients with an OCRI2 less than 0.5 developed cancer (32 ± 31 months). OCRI2 is better than other methods in predicting oral squamous cell carcinoma during follow-up. In conclusion, we have developed an exfoliative cytology-based method for quantitative prediction of cancer risk in patients with oral leukoplakia.

The Digital Astronaut Project Bone Remodeling Model

NASA Technical Reports Server (NTRS)

Pennline, James A.; Mulugeta, Lealem; Lewandowski, Beth E.; Thompson, William K.; Sibonga, Jean D.

2014-01-01

Under the conditions of microgravity, astronauts lose bone mass at a rate of 1% to 2% a month, particularly in the lower extremities such as the proximal femur: (1) The most commonly used countermeasure against bone loss has been prescribed exercise, (2) However, current exercise countermeasures do not completely eliminate bone loss in long duration, 4 to 6 months, spaceflight, (3,4) leaving the astronaut susceptible to early onset osteoporosis and a greater risk of fracture later in their lives. The introduction of the Advanced Resistive Exercise Device, coupled with improved nutrition, has further minimized the 4 to 6 month bone loss. But further work is needed to implement optimal exercise prescriptions, and (5) In this light, NASA's Digital Astronaut Project (DAP) is working with NASA physiologists to implement well-validated computational models that can help understand the mechanisms of bone demineralization in microgravity, and enhance exercise countermeasure development.

Simulation of water-quality data at selected stream sites in the Missouri River Basin, Montana

USGS Publications Warehouse

Knapton, J.R.; Jacobson, M.A.

1980-01-01

Modification of sampling programs at some water-quality stations in the Missouri River basin in Montana has eliminated the means by which solute loads have been directly obtained in past years. To compensate for this loss, water-quality and streamflow data were statistically analyzed and solute loads were simulated using computer techniques.Functional relationships existing between specific conductance and solute concentration for monthly samples were used to develop linear regression models. The models were then used to simulate daily solute concentrations using daily specific conductance as the independent variable. Once simulated, the solute concentrations, in milligrams per liter, were transformed into daily solute loads, in tons, using mean daily streamflow records.Computer output was formatted into tables listing simulated mean monthly solute concentrations, in milligrams per liter, and the monthly and annual solute loads, in tons, for water years 1975-78.

Writing Became a Chore Like the Laundry: The Realities of Using Journals To Encourage a Reflective Approach to Practice.

ERIC Educational Resources Information Center

Lewison, Mitzi

This action research study investigated a model of professional development designed to encourage elementary language arts teachers to adopt a more reflective approach to literacy instruction. The model consisted of monthly negotiated-topic study group sessions, theoretically-based reading, and dialogue journal writing. This paper focuses on the…

Automating Partial Period Bond Valuation with Excel's Day Counting Functions

ERIC Educational Resources Information Center

Vicknair, David; Spruell, James

2009-01-01

An Excel model for calculating the actual price of bonds under a 30 day/month, 360 day/year day counting assumption by nesting the DAYS360 function within the PV function is developed. When programmed into an Excel spreadsheet, the model can accommodate annual and semiannual payment bonds sold on or between interest dates using six fundamental…

A Rat Excised Larynx Model of Vocal Fold Scar

ERIC Educational Resources Information Center

Welham, Nathan V.; Montequin, Douglas W.; Tateya, Ichiro; Tateya, Tomoko; Choi, Seong Hee; Bless, Diane M.

2009-01-01

Purpose: To develop and evaluate a rat excised larynx model for the measurement of acoustic, aerodynamic, and vocal fold vibratory changes resulting from vocal fold scar. Method: Twenty-four 4-month-old male Sprague-Dawley rats were assigned to 1 of 4 experimental groups: chronic vocal fold scar, chronic vocal fold scar treated with 100-ng basic…

The development of aggression in 18 to 48 month old children of alcoholic parents.

PubMed

Edwards, Ellen P; Eiden, Rina D; Colder, Craig; Leonard, Kenneth E

2006-06-01

This study examined the development of aggressive and oppositional behavior among alcoholic and nonalcoholic families using latent growth modeling. The sample consisted of 226 families assessed at 18, 24, 36, and 48 months of child age. Results indicated that children in families with nonalcoholic parents had the lowest levels of aggressive behavior at all time points compared to children with one or more alcoholic parents. Children in families with two alcoholic parents did not exhibit normative decreases in aggressive behavior from 3 to 4 years of age compared to nonalcoholic families. However, this association was no longer significant once a cumulative family risk score was added to the model. Children in families with high cumulative risk scores, reflective of high parental depression, antisocial behavior, negative affect during play, difficult child temperament, marital conflict, fathers' education, and hours spent in child care, had higher levels of aggression at 18 months than children in low risk families. These associations were moderated by child gender. Boys had higher levels of aggressive behavior at all ages than girls, regardless of group status. Cumulative risk was predictive of higher levels of initial aggressive behavior in both girls and boys. However, boys with two alcoholic parents had significantly less of a decline in aggression from 36 to 48 months compared to boys in the nonalcoholic group.

Positive effect of human milk feeding during NICU hospitalization on 24 month neurodevelopment of very low birth weight infants: an Italian cohort study.

PubMed

Gibertoni, Dino; Corvaglia, Luigi; Vandini, Silvia; Rucci, Paola; Savini, Silvia; Alessandroni, Rosina; Sansavini, Alessandra; Fantini, Maria Pia; Faldella, Giacomo

2015-01-01

The aim of this study was to determine the effect of human milk feeding during NICU hospitalization on neurodevelopment at 24 months of corrected age in very low birth weight infants. A cohort of 316 very low birth weight newborns (weight ≤ 1500 g) was prospectively enrolled in a follow-up program on admission to the Neonatal Intensive Care Unit of S. Orsola Hospital, Bologna, Italy, from January 2005 to June 2011. Neurodevelopment was evaluated at 24 months corrected age using the Griffiths Mental Development Scale. The effect of human milk nutrition on neurodevelopment was first investigated using a multiple linear regression model, to adjust for the effects of gestational age, small for gestational age, complications at birth and during hospitalization, growth restriction at discharge and socio-economic status. Path analysis was then used to refine the multiple regression model, taking into account the relationships among predictors and their temporal sequence. Human milk feeding during NICU hospitalization and higher socio-economic status were associated with better neurodevelopment at 24 months in both models. In the path analysis model intraventricular hemorrhage-periventricular leukomalacia and growth restriction at discharge proved to be directly and independently associated with poorer neurodevelopment. Gestational age and growth restriction at birth had indirect significant effects on neurodevelopment, which were mediated by complications that occurred at birth and during hospitalization, growth restriction at discharge and type of feeding. In conclusion, our findings suggest that mother's human milk feeding during hospitalization can be encouraged because it may improve neurodevelopment at 24 months corrected age.

INEL BNCT Research Program, March/April 1992

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

Venhuizen, J.R.

1992-09-01

This report presents summaries for two months of current research for the Idaho National Engineering Laboratory (INEL) Boron Neutron Capture Therapy (BNCT) Program. Information is presented on development and murino screening experiments of low-density lipoprotein, carboranyl alanine, and liposome boron containing compounds. Pituitary tumor call culture studies are described. Drug stability, pharmacology and toxicity evaluation of borocaptate sodium (BSH) and boronopheoylalanine (BPA) are described. Treatment protocol development via the large animal (canine) model studies and physiological response evaluation in rats are discussed. Supporting technology development and technical support activities for boron drug biochemistry and purity, analytical and measurement dosimetry, andmore » noninvasive boron quantification activities are included for the current time period. Current publications for the two months are listed.« less

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets

NASA Astrophysics Data System (ADS)

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Spinoni, Jonathan; Alewell, Christine; Borrelli, Pasquale

2017-05-01

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha-1 h-1 yr-1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Towards estimates of future rainfall erosivity in Europe based on REDES and WorldClim datasets.

PubMed

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Spinoni, Jonathan; Alewell, Christine; Borrelli, Pasquale

2017-05-01

The policy requests to develop trends in soil erosion changes can be responded developing modelling scenarios of the two most dynamic factors in soil erosion, i.e. rainfall erosivity and land cover change. The recently developed Rainfall Erosivity Database at European Scale (REDES) and a statistical approach used to spatially interpolate rainfall erosivity data have the potential to become useful knowledge to predict future rainfall erosivity based on climate scenarios. The use of a thorough statistical modelling approach (Gaussian Process Regression), with the selection of the most appropriate covariates (monthly precipitation, temperature datasets and bioclimatic layers), allowed to predict the rainfall erosivity based on climate change scenarios. The mean rainfall erosivity for the European Union and Switzerland is projected to be 857 MJ mm ha -1  h -1  yr -1 till 2050 showing a relative increase of 18% compared to baseline data (2010). The changes are heterogeneous in the European continent depending on the future projections of most erosive months (hot period: April-September). The output results report a pan-European projection of future rainfall erosivity taking into account the uncertainties of the climatic models.

Dynamics of the job search process: developing and testing a mediated moderation model.

PubMed

Sun, Shuhua; Song, Zhaoli; Lim, Vivien K G

2013-09-01

Taking a self-regulatory perspective, we develop a mediated moderation model explaining how within-person changes in job search efficacy and chronic regulatory focus interactively affect the number of job interview offers and whether job search effort mediates the cross-level interactive effects. A sample of 184 graduating college students provided monthly reports of their job search activities over a period of 8 months. Findings supported the hypothesized relationships. Specifically, at the within-person level, job search efficacy was positively related with the number of interview offers for job seekers with strong prevention focus and negatively related with the number of interview offers for job seekers with strong promotion focus. Results show that job search effort mediated the moderated relationships. Findings enhance understandings of the complex self-regulatory processes underlying job search. PsycINFO Database Record (c) 2013 APA, all rights reserved

Boys' and girls' weight status and math performance from kindergarten entry through fifth grade: a mediated analysis.

PubMed

Gable, Sara; Krull, Jennifer L; Chang, Yiting

2012-01-01

This study tests a mediated model of boys' and girls' weight status and math performance with 6,250 children from the Early Childhood Longitudinal Study. Five data points spanning kindergarten entry (mean age=68.46 months) through fifth grade (mean age=134.60 months) were analyzed. Three weight status groups were identified: persistent obesity, later onset obesity, and never obese. Multilevel models tested relations between weight status and math performance, weight status and interpersonal skills and internalizing behaviors, and interpersonal skills and internalizing behaviors and math performance. Interpersonal skills mediated the association between weight status and math performance for girls, and internalizing behaviors mediated the association between weight status and math performance for both sexes, with effects varying by group and time. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Optical fiber sensors and signal processing for intelligent structure monitoring

NASA Technical Reports Server (NTRS)

Rogowski, Robert; Claus, R. O.; Lindner, D. K.; Thomas, Daniel; Cox, Dave

1988-01-01

The analytic and experimental performance of optical fiber sensors for the control of vibration of large aerospace and other structures are investigated. In particular, model domain optical fiber sensor systems, are being studied due to their apparent potential as distributed, low mass sensors of vibration over appropriate ranges of both low frequency and low amplitude displacements. Progress during the past three months is outlined. Progress since September is divided into work in the areas of experimental hardware development, analytical analysis, control design and sensor development. During the next six months, tests of a prototype closed-loop control system for a beam are planned which will demonstrate the solution of several optical fiber instrumentation device problems, the performance of the control system theory which incorporates the model of the modal domain sensor, and the potential for distributed control which this sensor approach offers.

Improvement and extension of a radar forest backscattering model

NASA Technical Reports Server (NTRS)

Simonett, David S.; Wang, Yong

1988-01-01

Research to-date has focused on modeling development and programming based on model components proposed during the past several months and research progress made by the Simonett team. The model components and programs (in C language under UNIX) finished to date are summarized. These model components may help explain the contributions of various vegetation structural components to the attenuation and backscattering of vegetated surfaces to extract useful data concerning forest stands and their underlying surfaces for both the seawater-on and seawater-off.

Processing and Monthly Summaries of Downscaled Climate Data for Knoxville, Tennessee and Surrounding Region

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

Sylvester, Linda; Omitaomu, Olufemi A.; Parish, Esther S.

2016-09-01

Oak Ridge National Laboratory (ORNL) and the City of Knoxville, Tennessee have partnered to work on a Laboratory Directed Research and Development (LDRD) project towards investigating climate change, mitigation, and adaptation measures in mid-sized cities. ORNL has statistically and dynamically downscaled ten Global Climate Models (GCMs) to both 1 km and 4 km resolutions. The processing and summary of those ten gridded datasets for use in a web-based tool is described. The summaries of each model are shown individually to assist in determining the similarities and differences between the model scenarios. The variables of minimum and maximum daily temperature andmore » total monthly precipitation are summarized for the area of Knoxville, Tennessee for the periods of 1980-2005 and 2025-2050.« less

Placental pathology predicts infantile physical development during first 18 months in Japanese population: Hamamatsu birth cohort for mothers and children (HBC Study)

PubMed Central

Yaguchi, Chizuko; Tsuchiya, Kenji J.; Furuta-Isomura, Naomi; Horikoshi, Yoshimasa; Matsumoto, Masako; Jeenat, Ferdous U.; Keiko, Muramatsu-Kato; Kohmura-Kobatashi, Yukiko; Tamura, Naoaki; Sugihara, Kazuhiro; Kanayama, Naohiro

2018-01-01

The present study aimed to investigate the relationship between placental pathological findings and physiological development during the neonate and infantile periods. Study participants were 258 infants from singleton pregnancies enrolled in the Hamamatsu Birth Cohort for Mothers and Children (HBC Study) whose placentas were stored in our pathological division. They were followed up from birth to 18 months of age. Physiological development (body weight and the ponderal index [PI]) was assessed at 0, 1, 4, 6, 10, 14, and 18 months. Placental blocks were prepared by random sampling and eleven pathological findings were assessed, as follows: ‘Accelerated villous maturation’, ‘Decidual vasculopathy’, ‘Thrombosis or Intramural fibrin deposition’, ‘Avascular villi’, ‘Delayed villous maturation’, ‘Maternal inflammatory response’, ‘Fetal inflammatory response’, ‘Villitis of unknown etiology (VUE)’, ‘Deciduitis’, ‘Maternal vascular malperfusion’, and ‘Fetal vascular malperfusion’. Mixed model analysis with the use of the xtmixed command by the generic statistical software, Stata version 13.1., identified ‘Accelerated villous maturation’ and ‘Maternal vascular malperfusion’ as significant predictors of a lower body weight and ‘Deciduitis’ as a significant predictor of a small PI, throughout the first 18 months of life. In conclusion, the present study is the first to demonstrate that some pathological findings of the placenta are associated with changes in infantile physical development during the initial 18 months of life in the Japanese population. PMID:29634735

Spline models of contemporary, 2030, 2060, and 2090 climates for Mexico and their use in understanding climate-change impacts on the vegetation

Treesearch

Cuauhtemoc Saenz-Romero; Gerald E. Rehfeldt; Nicholas L. Crookston; Pierre Duval; Remi St-Amant; Jean Beaulieu; Bryce A. Richardson

2010-01-01

Spatial climate models were developed for Mexico and its periphery (southern USA, Cuba, Belize and Guatemala) for monthly normals (1961-1990) of average, maximum and minimum temperature and precipitation using thin plate smoothing splines of ANUSPLIN software on ca. 3,800 observations. The fit of the model was generally good: the signal was considerably less than one-...

Implications of newborn amygdala connectivity for fear and cognitive development at 6-months-of-age

PubMed Central

Graham, Alice M.; Buss, Claudia; Rasmussen, Jerod M.; Rudolph, Marc D.; Demeter, Damion V.; Gilmore, John H.; Styner, Martin; Entringer, Sonja; Wadhwa, Pathik D.; Fair, Damien A.

2015-01-01

The first year of life is an important period for emergence of fear in humans. While animal models have revealed developmental changes in amygdala circuitry accompanying emerging fear, human neural systems involved in early fear development remain poorly understood. To increase understanding of the neural foundations of human fear, it is important to consider parallel cognitive development, which may modulate associations between typical development of early fear and subsequent risk for fear-related psychopathology. We, therefore, examined amygdala functional connectivity with rs-fcMRI in 48 neonates (M=3.65 weeks, SD=1.72), and measured fear and cognitive development at 6-months-of-age. Stronger, positive neonatal amygdala connectivity to several regions, including bilateral anterior insula and ventral striatum, was prospectively associated with higher fear at 6-months. Stronger amygdala connectivity to ventral anterior cingulate/anterior medial prefrontal cortex predicted a specific phenotype of higher fear combined with more advanced cognitive development. Overall, findings demonstrate unique profiles of neonatal amygdala functional connectivity related to emerging fear and cognitive development, which may have implications for normative and pathological fear in later years. Consideration of infant fear in the context of cognitive development will likely contribute to a more nuanced understanding of fear, its neural bases, and its implications for future mental health. PMID:26499255

Breastfeeding and motor development: A longitudinal cohort study.

PubMed

Grace, Tegan; Oddy, Wendy; Bulsara, Max; Hands, Beth

2017-01-01

While there is a large body of work supporting the importance of early feeding practices on cognitive, immunity, behavioural and mental outcomes, few longitudinal studies have focused on motor development. The relationship between duration of breast feeding and motor development outcomes at 10, 14, and 17years were examined. Data were obtained from the Western Australian Pregnancy (Raine) Study. There were 2868 live births recorded and children were examined for motor proficiency at 10 (M=10.54, SD=2.27), 14 (M=14.02, SD=2.33) and 17 (M=16.99, SD=2.97) years using the McCarron Assessment of Neuromuscular Development (MAND). Using linear mixed models, adjusted for covariates known to affect motor development, the influence of predominant breast feeding for <6months and ⩾6months on motor development outcomes was examined. Breast feeding for ⩾6months was positively associated with improved motor development outcomes at 10, 14 and 17yearsof age (p=0.019, β 1.38) when adjusted for child's sex, maternal age, alcohol intake, family income, hypertensive status, gestational stress and mode of delivery. Early life feeding practices have an influence on motor development outcomes into late childhood and adolescence independent of sociodemographic factors. Copyright © 2016 Elsevier B.V. All rights reserved.

Rapid crop cover mapping for the conterminous United States

USGS Publications Warehouse

Dahal, Devendra; Wylie, Bruce K.; Howard, Daniel

2018-01-01

Timely crop cover maps with sufficient resolution are important components to various environmental planning and research applications. Through the modification and use of a previously developed crop classification model (CCM), which was originally developed to generate historical annual crop cover maps, we hypothesized that such crop cover maps could be generated rapidly during the growing season. Through a process of incrementally removing weekly and monthly independent variables from the CCM and implementing a ‘two model mapping’ approach, we found it viable to generate conterminous United States-wide rapid crop cover maps at a resolution of 250 m for the current year by the month of September. In this approach, we divided the CCM model into one ‘crop type model’ to handle the classification of nine specific crops and a second, binary model to classify the presence or absence of ‘other’ crops. Under the two model mapping approach, the training errors were 0.8% and 1.5% for the crop type and binary model, respectively, while test errors were 5.5% and 6.4%, respectively. With spatial mapping accuracies for annual maps reaching upwards of 70%, this approach demonstrated a strong potential for generating rapid crop cover maps by the 1st of September.

A predictive model to allocate frequent service users of community-based mental health services to different packages of care.

PubMed

Grigoletti, Laura; Amaddeo, Francesco; Grassi, Aldrigo; Boldrini, Massimo; Chiappelli, Marco; Percudani, Mauro; Catapano, Francesco; Fiorillo, Andrea; Perris, Francesco; Bacigalupi, Maurizio; Albanese, Paolo; Simonetti, Simona; De Agostini, Paola; Tansella, Michele

2010-01-01

To develop predictive models to allocate patients into frequent and low service users groups within the Italian Community-based Mental Health Services (CMHSs). To allocate frequent users to different packages of care, identifying the costs of these packages. Socio-demographic and clinical data and GAF scores at baseline were collected for 1250 users attending five CMHSs. All psychiatric contacts made by these patients during six months were recorded. A logistic regression identified frequent service users predictive variables. Multinomial logistic regression identified variables able to predict the most appropriate package of care. A cost function was utilised to estimate costs. Frequent service users were 49%, using nearly 90% of all contacts. The model classified correctly 80% of users in the frequent and low users groups. Three packages of care were identified: Basic Community Treatment (4,133 Euro per six months); Intensive Community Treatment (6,180 Euro) and Rehabilitative Community Treatment (11,984 Euro) for 83%, 6% and 11% of frequent service users respectively. The model was found to be accurate for 85% of users. It is possible to develop predictive models to identify frequent service users and to assign them to pre-defined packages of care, and to use these models to inform the funding of psychiatric care.

A Standardized Rat Model of Volumetric Muscle Loss Injury for the Development of Tissue Engineering Therapies

DTIC Science & Technology

2012-12-01

isometric tetanic force (Po) of 28.4% and 32.5% at 2 and 4 months. Importantly, Po corrected for differences in body weight and muscle wet weights were...development, we removed progres- sively larger amounts of muscle tissue followed by a mea- surement of maximal isometric force (Po). The final model, and...indicated by increased collagen deposition (Fig. 2). The scarred area and the area immediately adjacent to it contained disorganized muscle fibers

Spatiotemporal drought forecasting using nonlinear models

NASA Astrophysics Data System (ADS)

Vasiliades, Lampros; Loukas, Athanasios

2010-05-01

Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with increase in lead time. Finally, the developed nonlinear models could be used in an early warning system for risk and decision analyses at the study area.

Why are Anxiety and Depressive Symptoms Comorbid in Youth? A Multi-Wave, Longitudinal Examination of Competing Etiological Models

PubMed Central

Cohen, Joseph R.; Young, Jami, F.; Gibb, Brandon E.; Hankin, Benjamin L.; Abela, John R. Z.

2014-01-01

Background The present study sought to clarify the development of comorbid emotional distress by comparing different explanations for how youth develop anxiety and depressive symptoms. Specifically, we introduced the diathesis-anxiety approach (whether cognitive vulnerabilities interact with anxiety symptoms), and compared it to a causal model (anxiety symptoms predicting depressive symptoms), and a correlated liabilities model (whether cognitive vulnerabilities interacted with stressors to predict both anxiety and depressive symptoms) to examine which model best explained the relation between depressive and anxiety symptoms in youth. Methods 678 3rd (n=208), 6th (n=245), and 9th (n=225) grade girls (n=380) and boys (n=298) completed self-report measures at baseline assessing cognitive vulnerabilities (rumination and self-criticism), stressors, depressive and anxiety symptoms. Every 3 months over the next 18 months, youth completed follow-up measures of symptoms and stressors. Results While limited support was found for a causal (p > .10) or correlated-liability model (p > .05) for comorbidity, findings did support a diathesis-anxiety approach for both self-criticism (t(2494) = 3.36, p < .001) and rumination (t(2505) = 2.40, p < .05). Limitations The present study’s findings are based on self-report measure and makes inferences concerning comorbidity with a community sample. Conclusions These results may help clarify past research concerning comorbidity by introducing a diathesis-anxiety approach as a viable model to understand which youth are most at-risk for developing comorbid emotional distress. PMID:24751303

Multivariable model development and internal validation for prostate cancer specific survival and overall survival after whole-gland salvage Iodine-125 prostate brachytherapy.

PubMed

Peters, Max; van der Voort van Zyp, Jochem R N; Moerland, Marinus A; Hoekstra, Carel J; van de Pol, Sandrine; Westendorp, Hendrik; Maenhout, Metha; Kattevilder, Rob; Verkooijen, Helena M; van Rossum, Peter S N; Ahmed, Hashim U; Shah, Taimur T; Emberton, Mark; van Vulpen, Marco

2016-04-01

Whole-gland salvage Iodine-125-brachytherapy is a potentially curative treatment strategy for localised prostate cancer (PCa) recurrences after radiotherapy. Prognostic factors influencing PCa-specific and overall survival (PCaSS & OS) are not known. The objective of this study was to develop a multivariable, internally validated prognostic model for survival after whole-gland salvage I-125-brachytherapy. Whole-gland salvage I-125-brachytherapy patients treated in the Netherlands from 1993-2010 were included. Eligible patients had a transrectal ultrasound-guided biopsy-confirmed localised recurrence after biochemical failure (clinical judgement, ASTRO or Phoenix-definition). Recurrences were assessed clinically and with CT and/or MRI. Metastases were excluded using CT/MRI and technetium-99m scintigraphy. Multivariable Cox-regression was used to assess the predictive value of clinical characteristics in relation to PCa-specific and overall mortality. PCa-specific mortality was defined as patients dying with distant metastases present. Missing data were handled using multiple imputation (20 imputed sets). Internal validation was performed and the C-statistic calculated. Calibration plots were created to visually assess the goodness-of-fit of the final model. Optimism-corrected survival proportions were calculated. All analyses were performed according to the TRIPOD statement. Median total follow-up was 78months (range 5-139). A total of 62 patients were treated, of which 28 (45%) died from PCa after mean (±SD) 82 (±36) months. Overall, 36 patients (58%) patients died after mean 84 (±40) months. PSA doubling time (PSADT) remained a predictive factor for both types of mortality (PCa-specific and overall): corrected hazard ratio's (HR's) 0.92 (95% CI: 0.86-0.98, p=0.02) and 0.94 (95% CI: 0.90-0.99, p=0.01), respectively (C-statistics 0.71 and 0.69, respectively). Calibration was accurate up to 96month follow-up. Over 80% of patients can survive 8years if PSADT>24months (PCaSS) and >33months (OS). Only approximately 50% survival is achieved with a PSADT of 12months. A PSADT of respectively >24months and >33months can result in >80% probability of PCa- specific and overall survival 8years after whole-gland salvage I-125-brachytherapy. Survival should be weighed against toxicity from a salvage procedure. Larger series and external validation are necessary. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Application of a Systems Engineering Approach to Support Space Reactor Development

NASA Astrophysics Data System (ADS)

Wold, Scott

2005-02-01

In 1992, approximately 25 Russian and 12 U.S. engineers and technicians were involved in the transport, assembly, inspection, and testing of over 90 tons of Russian equipment associated with the Thermionic System Evaluation Test (TSET) Facility. The entire Russian Baikal Test Stand, consisting of a 5.79 m tall vacuum chamber and related support equipment, was reassembled and tested at the TSET facility in less than four months. In November 1992, the first non-nuclear operational test of a complete thermionic power reactor system in the U.S. was accomplished three months ahead of schedule and under budget. A major factor in this accomplishment was the application of a disciplined top-down systems engineering approach and application of a spiral development model to achieve the desired objectives of the TOPAZ International Program (TIP). Systems Engineering is a structured discipline that helps programs and projects conceive, develop, integrate, test and deliver products and services that meet customer requirements within cost and schedule. This paper discusses the impact of Systems Engineering and a spiral development model on the success of the TOPAZ International Program and how the application of a similar approach could help ensure the success of future space reactor development projects.

Simultaneous characterization of metabolic, cardiac, vascular and renal phenotypes of lean and obese SHHF rats.

PubMed

Youcef, Gina; Olivier, Arnaud; L'Huillier, Clément P J; Labat, Carlos; Fay, Renaud; Tabcheh, Lina; Toupance, Simon; Rodriguez-Guéant, Rosa-Maria; Bergerot, Damien; Jaisser, Frédéric; Lacolley, Patrick; Zannad, Faiez; Laurent Vallar; Pizard, Anne

2014-01-01

Individuals with metabolic syndrome (MetS) are prone to develop heart failure (HF). However, the deleterious effects of MetS on the continuum of events leading to cardiac remodeling and subsequently to HF are not fully understood. This study characterized simultaneously MetS and cardiac, vascular and renal phenotypes in aging Spontaneously Hypertensive Heart Failure lean (SHHF(+/?) regrouping (+/+) and (+/cp) rats) and obese (SHHF(cp/cp), "cp" defective mutant allele of the leptin receptor gene) rats. We aimed to refine the milestones and their onset during the progression from MetS to HF in this experimental model. We found that SHHF(cp/cp )but not SHHF(+/?) rats developed dyslipidemia, as early as 1.5 months of age. This early alteration in the lipidic profile was detectable concomitantly to impaired renal function (polyuria, proteinuria but no glycosuria) and reduced carotid distensibility as compared to SHHF(+/?) rats. By 3 months of age SHHFcp/cp animals developed severe obesity associated with dislipidemia and hypertension defining the onset of MetS. From 6 months of age, SHHF(+/?) rats developed concentric left ventricular hypertrophy (LVH) while SHHF(cp/cp) rats developed eccentric LVH apparent from progressive dilation of the LV dimensions. By 14 months of age only SHHF(cp/cp) rats showed significantly higher central systolic blood pressure and a reduced ejection fraction resulting in systolic dysfunction as compared to SHHF(+/?). In summary, the metabolic and hemodynamic mechanisms participating in the faster decline of cardiac functions in SHHF(cp/cp) rats are established long before their physiological consequences are detectable. Our results suggest that the molecular mechanisms triggered within the first three months after birth of SHHF(cp/cp) rats should be targeted preferentially by therapeutic interventions in order to mitigate the later HF development.

Simultaneous Characterization of Metabolic, Cardiac, Vascular and Renal Phenotypes of Lean and Obese SHHF Rats

PubMed Central

Youcef, Gina; Olivier, Arnaud; L'Huillier, Clément P. J.; Labat, Carlos; Fay, Renaud; Tabcheh, Lina; Toupance, Simon; Rodriguez-Guéant, Rosa-Maria; Bergerot, Damien; Jaisser, Frédéric; Lacolley, Patrick; Zannad, Faiez; Laurent Vallar; Pizard, Anne

2014-01-01

Individuals with metabolic syndrome (MetS) are prone to develop heart failure (HF). However, the deleterious effects of MetS on the continuum of events leading to cardiac remodeling and subsequently to HF are not fully understood. This study characterized simultaneously MetS and cardiac, vascular and renal phenotypes in aging Spontaneously Hypertensive Heart Failure lean (SHHF+/? regrouping +/+ and +/cp rats) and obese (SHHFcp/cp, “cp” defective mutant allele of the leptin receptor gene) rats. We aimed to refine the milestones and their onset during the progression from MetS to HF in this experimental model. We found that SHHFcp/cp but not SHHF+/? rats developed dyslipidemia, as early as 1.5 months of age. This early alteration in the lipidic profile was detectable concomitantly to impaired renal function (polyuria, proteinuria but no glycosuria) and reduced carotid distensibility as compared to SHHF+/? rats. By 3 months of age SHHFcp/cp animals developed severe obesity associated with dislipidemia and hypertension defining the onset of MetS. From 6 months of age, SHHF+/? rats developed concentric left ventricular hypertrophy (LVH) while SHHFcp/cp rats developed eccentric LVH apparent from progressive dilation of the LV dimensions. By 14 months of age only SHHFcp/cp rats showed significantly higher central systolic blood pressure and a reduced ejection fraction resulting in systolic dysfunction as compared to SHHF+/?. In summary, the metabolic and hemodynamic mechanisms participating in the faster decline of cardiac functions in SHHFcp/cp rats are established long before their physiological consequences are detectable. Our results suggest that the molecular mechanisms triggered within the first three months after birth of SHHFcp/cp rats should be targeted preferentially by therapeutic interventions in order to mitigate the later HF development. PMID:24831821

Prevalence of low back symptoms and its consequences in relation to occupational group.

PubMed

Widanarko, Baiduri; Legg, Stephen; Stevenson, Mark; Devereux, Jason; Jones, Geoff

2013-05-01

The purpose of this study was to examine: (1) the prevalence of low back symptoms (LBS) and its consequences (reduced activities and absenteeism); (2) the association between occupational group and LBS; and (3) the association between LBS and its consequences. A self-administered questionnaire was used to determine the prevalence of LBS in 1,294 Indonesian coal mining workers. A Cox proportional hazards model was developed to quantify the 12-monthly hazard of LBS. Logistic regression models were developed to identify risk factors for reduced activity and absenteeism from the workplace. The 12-month period prevalence for LBS, reduced activities, and absenteeism were 75%, 16%, and 13%, respectively. The 12-monthly hazard of LBS for blue-collar workers was 1.85 (95% CI: 1.06-3.25) times that of white-collar workers. LBS and smoking increased the risk of reduced activity and absenteeism. Indonesian coal mining workers have a high prevalence of LBS. The findings imply that efforts to reduce LBS and in the workplace should focus on blue-collar workers. For smokers who report reduced activities and/or absenteeism, there should be a focus on rehabilitation and/or return-to-work programs. Copyright © 2012 Wiley Periodicals, Inc.

Metabolic and oxidative stress markers in Wistar rats after 2 months on a high-fat diet.

PubMed

Auberval, Nathalie; Dal, Stéphanie; Bietiger, William; Pinget, Michel; Jeandidier, Nathalie; Maillard-Pedracini, Elisa; Schini-Kerth, Valérie; Sigrist, Séverine

2014-01-01

Metabolic syndrome is associated with an increased risk of cardiovascular and hepatic complications. Oxidative stress in metabolic tissues has emerged as a universal feature of metabolic syndrome and its co-morbidities. We aimed to develop a rapidly and easily induced model of metabolic syndrome in rats to evaluate its impact on plasma and tissue oxidative stress. Metabolic syndrome was induced in rats using a high-fat diet (HFD), and these rats were compared to rats fed a normal diet (ND) for 2 months. Metabolic control was determined by measuring body weight, blood glucose, triglycerides, lipid peroxidation and protein carbonylation in plasma. Insulinemia was evaluated through the measure of C-peptide. Histological analysis was performed on the pancreas, liver and blood vessels. After 2 months, the HFD induced an increase in body weight, insulin and triglycerides. Liver steatosis was also observed in the HFD group, which was associated with an increase in glycogen storage. In the pancreas, the HFD induced islet hyperplasia. Tissue oxidative stress was also increased in the liver, pancreas and blood vessels, but plasma oxidative stress remained unchanged. This paper reports the development of a fast and easy model of rat metabolic syndrome associated with tissue oxidative stress. This model may be a good tool for the biological validation of drugs or antioxidants to limit or prevent the complications of metabolic syndrome.

Development of hepatocellular carcinoma in a murine model of nonalcoholic steatohepatitis induced by use of a high-fat/fructose diet and sedentary lifestyle.

PubMed

Dowman, Joanna K; Hopkins, Laurence J; Reynolds, Gary M; Nikolaou, Nikolaos; Armstrong, Matthew J; Shaw, Jean C; Houlihan, Diarmaid D; Lalor, Patricia F; Tomlinson, Jeremy W; Hübscher, Stefan G; Newsome, Philip N

2014-05-01

Obesity is increasingly prevalent, strongly associated with nonalcoholic liver disease, and a risk factor for numerous cancers. Here, we describe the liver-related consequences of long-term diet-induced obesity. Mice were exposed to an extended obesity model comprising a diet high in trans-fats and fructose corn syrup concurrent with a sedentary lifestyle. Livers were assessed histologically using the nonalcoholic fatty liver disease (NAFLD) activity score (Kleiner system). Mice in the American Lifestyle-Induced Obesity Syndrome (ALIOS) model developed features of early nonalcoholic steatohepatitis at 6 months (mean NAFLD activity score = 2.4) and features of more advanced nonalcoholic steatohepatitis at 12 months, including liver inflammation and bridging fibrosis (mean NAFLD activity score = 5.0). Hepatic expression of lipid metabolism and insulin signaling genes were increased in ALIOS mice compared with normal chow-fed mice. Progressive activation of the mouse hepatic stem cell niche in response to ALIOS correlated with steatosis, fibrosis, and inflammation. Hepatocellular neoplasms were observed in 6 of 10 ALIOS mice after 12 months. Tumors displayed cytological atypia, absence of biliary epithelia, loss of reticulin, alteration of normal perivenular glutamine synthetase staining (absent or diffuse), and variable α-fetoprotein expression. Notably, perivascular tumor cells expressed hepatic stem cell markers. These studies indicate an adipogenic lifestyle alone is sufficient for the development of nonalcoholic steatohepatitis, hepatic stem cell activation, and hepatocarcinogenesis in wild-type mice. Copyright © 2014 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Temporal patterns and forecast of dengue infection in Northeastern Thailand.

PubMed

Silawan, Tassanee; Singhasivanon, Pratap; Kaewkungwal, Jaranit; Nimmanitya, Suchitra; Suwonkerd, Wanapa

2008-01-01

This study aimed to determine temporal patterns and develop a forecasting model for dengue incidence in northeastern Thailand. Reported cases were obtained from the Thailand national surveillance system. The temporal patterns were displayed by plotting monthly rates, the seasonal-trend decomposition procedure based on loess (STL) was performed using R 2.2.1 software, and the trend was assessed using Poisson regression. The forecasting model for dengue incidence was performed in R 2.2.1 and Intercooled Stata 9.2 using the seasonal Autoregressive Integrated Moving Average (ARIMA) model. The model was evaluated by comparing predicted versus actual rates of dengue for 1996 to 2005 and used to forecast monthly rates during January to December 2006. The results reveal that epidemics occurred every two years, with approximately three years per epidemic, and that the next epidemic will take place in 2006 to 2008. It was found that if a month increased, the rate ratio for dengue infection decreased by a factor 0.9919 for overall region and 0.9776 to 0.9984 for individual provinces. The amplitude of the peak, which was evident in June or July, was 11.32 to 88.08 times greater than the rest of the year. The seasonal ARIMA (2, 1, 0) (0, 1, 1)12 model was model with the best fit for regionwide data of total dengue incidence whereas the models with the best fit varied by province. The forecasted regional monthly rates during January to December 2006 should range from 0.27 to 17.89 per 100,000 population. The peak for 2006 should be much higher than the peak for 2005. The highest peaks in 2006 should be in Loei, Buri Ram, Surin, Nakhon Phanom, and Ubon Ratchathani Provinces.

A spurious warming trend in the NMME equatorial Pacific SST hindcasts

NASA Astrophysics Data System (ADS)

Shin, Chul-Su; Huang, Bohua

2017-06-01

Using seasonal hindcasts of six different models participating in the North American Multimodel Ensemble project, the trend of the predicted sea surface temperature (SST) in the tropical Pacific for 1982-2014 at each lead month and its temporal evolution with respect to the lead month are investigated for all individual models. Since the coupled models are initialized with the observed ocean, atmosphere, land states from observation-based reanalysis, some of them using their own data assimilation process, one would expect that the observed SST trend is reasonably well captured in their seasonal predictions. However, although the observed SST features a weak-cooling trend for the 33-year period with La Niña-like spatial pattern in the tropical central-eastern Pacific all year round, it is demonstrated that all models having a time-dependent realistic concentration of greenhouse gases (GHG) display a warming trend in the equatorial Pacific that amplifies as the lead-time increases. In addition, these models' behaviors are nearly independent of the starting month of the hindcasts although the growth rates of the trend vary with the lead month. This key characteristic of the forecasted SST trend in the equatorial Pacific is also identified in the NCAR CCSM3 hindcasts that have the GHG concentration for a fixed year. This suggests that a global warming forcing may not play a significant role in generating the spurious warming trend of the coupled models' SST hindcasts in the tropical Pacific. This model SST trend in the tropical central-eastern Pacific, which is opposite to the observed one, causes a developing El Niño-like warming bias in the forecasted SST with its peak in boreal winter. Its implications for seasonal prediction are discussed.

Animal reservoir, natural and socioeconomic variations and the transmission of hemorrhagic fever with renal syndrome in Chenzhou, China, 2006-2010.

PubMed

Xiao, Hong; Tian, Huai-Yu; Gao, Li-Dong; Liu, Hai-Ning; Duan, Liang-Song; Basta, Nicole; Cazelles, Bernard; Li, Xiu-Jun; Lin, Xiao-Ling; Wu, Hong-Wei; Chen, Bi-Yun; Yang, Hui-Suo; Xu, Bing; Grenfell, Bryan

2014-01-01

China has the highest incidence of hemorrhagic fever with renal syndrome (HFRS) worldwide. Reported cases account for 90% of the total number of global cases. By 2010, approximately 1.4 million HFRS cases had been reported in China. This study aimed to explore the effect of the rodent reservoir, and natural and socioeconomic variables, on the transmission pattern of HFRS. Data on monthly HFRS cases were collected from 2006 to 2010. Dynamic rodent monitoring data, normalized difference vegetation index (NDVI) data, climate data, and socioeconomic data were also obtained. Principal component analysis was performed, and the time-lag relationships between the extracted principal components and HFRS cases were analyzed. Polynomial distributed lag (PDL) models were used to fit and forecast HFRS transmission. Four principal components were extracted. Component 1 (F1) represented rodent density, the NDVI, and monthly average temperature. Component 2 (F2) represented monthly average rainfall and monthly average relative humidity. Component 3 (F3) represented rodent density and monthly average relative humidity. The last component (F4) represented gross domestic product and the urbanization rate. F2, F3, and F4 were significantly correlated, with the monthly HFRS incidence with lags of 4 months (r = -0.289, P<0.05), 5 months (r = -0.523, P<0.001), and 0 months (r = -0.376, P<0.01), respectively. F1 was correlated with the monthly HFRS incidence, with a lag of 4 months (r = 0.179, P = 0.192). Multivariate PDL modeling revealed that the four principal components were significantly associated with the transmission of HFRS. The monthly trend in HFRS cases was significantly associated with the local rodent reservoir, climatic factors, the NDVI, and socioeconomic conditions present during the previous months. The findings of this study may facilitate the development of early warning systems for the control and prevention of HFRS and similar diseases.

Development of the Hand Assessment for Infants: evidence of internal scale validity.

PubMed

Krumlinde-Sundholm, Lena; Ek, Linda; Sicola, Elisa; Sjöstrand, Lena; Guzzetta, Andrea; Sgandurra, Giuseppina; Cioni, Giovanni; Eliasson, Ann-Christin

2017-12-01

The aim of this study was to develop a descriptive and evaluative assessment of upper limb function for infants aged 3 to 12 months and to investigate its internal scale validity for use with infants at risk of unilateral cerebral palsy. The concepts of the test items and scoring criteria were developed. Internal scale validity and aspects of reliability were investigated on the basis of 156 assessments of infants at 3 to 12 months corrected age (mean 7.2mo, SD 2.5) with signs of asymmetric hand use. Rasch measurement model analysis and non-parametric statistics were used. The new test, the Hand Assessment for Infants (HAI), consists of 12 unimanual and five bimanual items, each scored on a 3-point rating scale. It demonstrated a unidimensional construct and good fit to the Rasch model requirements. The excellent person reliability enabled person separation to six significant ability strata. The HAI produced an interval-level measure of bilateral hand use as well as unimanual scores of each hand, allowing a quantification of possible asymmetry expressed as an asymmetry index. The HAI can be considered a valid assessment tool for measuring bilateral hand use and quantifying side difference between hands among infants at risk of developing unilateral cerebral palsy. The Hand Assessment for Infants (HAI) measures the use of both hands and quantifies a possible asymmetry of hand use. HAI is valid for infants at 3 to 12 months corrected age at risk of unilateral cerebral palsy. © 2017 Mac Keith Press.

Simple View of Reading in Down's syndrome: the role of listening comprehension and reading skills.

PubMed

Roch, Maja; Levorato, M Chiara

2009-01-01

According to the 'Simple View of Reading' (Hoover and Gough 1990), individual differences in reading comprehension are accounted for by decoding skills and listening comprehension, each of which makes a unique and specific contribution. The current research was aimed at testing the Simple View of Reading in individuals with Down's syndrome and comparing their profiles with typically developing first graders. Listening comprehension and the ability to read both words and non-words was compared in two groups with the same level of reading comprehension: 23 individuals with Down's syndrome aged between 11 years 3 months and 18 years 2 months and 23 first-grade typically developing children aged between 6 years 2 months and 7 years 4 months. The results indicate that at the same level of reading comprehension, individuals with Down's syndrome have less developed listening comprehension and more advanced word recognition than typically developing first graders. A comparison of the profiles of the two groups revealed that reading comprehension level was predicted by listening comprehension in both groups of participants and by word-reading skills only in typically developing children. The Simple View of Reading model is confirmed for individuals with Down's syndrome, although they do not show the reading profile of typically developing first graders; rather, they show an atypical profile similar to that of 'poor comprehenders' (Cain and Oakhill 2006). The crucial role of listening comprehension in Down's syndrome is also discussed with reference to the educational implications.

Risk factors and algorithms for chlamydial and gonococcal cervical infections in women attending family planning clinics in Thailand.

PubMed

Rugpao, Sungwal; Rungruengthanakit, Kittipong; Werawatanakul, Yuthapong; Sinchai, Wanida; Ruengkris, Tosaporn; Lamlertkittikul, Surachai; Pinjareon, Sutham; Koonlertkit, Sompong; Limtrakul, Aram; Sriplienchan, Somchai; Wongthanee, Antika; Sirirojn, Bangorn; Morrison, Charles S; Celentano, David D

2010-02-01

To identify risk factors associated with and evaluate algorithms for predicting Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) cervical infections in women attending family planning clinics in Thailand. Eligible women were recruited from family planning clinics from all regions in Thailand. The women were followed at 3-month intervals for 15-24 months. At each visit, the women were interviewed for interval sexually transmitted infection (STI) history in the past 3 months, recent sexual behavior, and contraceptive use. Pelvic examinations were performed and endocervical specimens were collected to test for CT and NG using polymerase chain reaction. Factors associated with incident CT/NG cervical infections in multivariate analyses included region of country other than the north, age

Trend analysis of salt load and evaluation of the frequency of water-quality measurements for the Gunnison, the Colorado, and the Dolores rivers in Colorado and Utah

USGS Publications Warehouse

Kircher, J.E.; Dinicola, Richard S.; Middelburg, R.F.

1984-01-01

Monthly values were computed for water-quality constituents at four streamflow gaging stations in the Upper Colorado River basin for the determination of trends. Seasonal regression and seasonal Kendall trend analysis techniques were applied to two monthly data sets at each station site for four different time periods. A recently developed method for determining optimal water-discharge data-collection frequency was also applied to the monthly water-quality data. Trend analysis results varied with each monthly load computational method, period of record, and trend detection model used. No conclusions could be reached regarding which computational method was best to use in trend analysis. Time-period selection for analysis was found to be important with regard to intended use of the results. Seasonal Kendall procedures were found to be applicable to most data sets. Seasonal regression models were more difficult to apply and were sometimes of questionable validity; however, those results were more informative than seasonal Kendall results. The best model to use depends upon the characteristics of the data and the amount of trend information needed. The measurement-frequency optimization method had potential for application to water-quality data, but refinements are needed. (USGS)

Forecast of Frost Days Based on Monthly Temperatures

NASA Astrophysics Data System (ADS)

Castellanos, M. T.; Tarquis, A. M.; Morató, M. C.; Saa-Requejo, A.

2009-04-01

Although frost can cause considerable crop damage and mitigation practices against forecasted frost exist, frost forecasting technologies have not changed for many years. The paper reports a new method to forecast the monthly number of frost days (FD) for several meteorological stations at Community of Madrid (Spain) based on successive application of two models. The first one is a stochastic model, autoregressive integrated moving average (ARIMA), that forecasts monthly minimum absolute temperature (tmin) and monthly average of minimum temperature (tminav) following Box-Jenkins methodology. The second model relates these monthly temperatures to minimum daily temperature distribution during one month. Three ARIMA models were identified for the time series analyzed with a stational period correspondent to one year. They present the same stational behavior (moving average differenced model) and different non-stational part: autoregressive model (Model 1), moving average differenced model (Model 2) and autoregressive and moving average model (Model 3). At the same time, the results point out that minimum daily temperature (tdmin), for the meteorological stations studied, followed a normal distribution each month with a very similar standard deviation through years. This standard deviation obtained for each station and each month could be used as a risk index for cold months. The application of Model 1 to predict minimum monthly temperatures showed the best FD forecast. This procedure provides a tool for crop managers and crop insurance companies to asses the risk of frost frequency and intensity, so that they can take steps to mitigate against frost damage and estimated the damage that frost would cost. This research was supported by Comunidad de Madrid Research Project 076/92. The cooperation of the Spanish National Meteorological Institute and the Spanish Ministerio de Agricultura, Pesca y Alimentation (MAPA) is gratefully acknowledged.

Estimating sediment yield in the southern Appalachians using WCS-SED

Treesearch

Paul Bolstad; Andrew Jenks; Mark Riedel; James M. Vose

2006-01-01

We measured and modeled sediment yield over two months on five watersheds in the southern Appalachian Mountains of North Carolina. These watersheds contained first and second-order streams and are primarily forested, but span the development gradient common in this region, with up to 10 percent in suburban and transitional development and up to 27% low-intensity...

A Study of Chinese Engineering Students' Communication Strategies in a Mobile-Assisted Professional Development Course

ERIC Educational Resources Information Center

Cheng, Li

2016-01-01

The development of students' professional skills is an important issue in higher education in China. This research reports a 3-month study investigating engineering students' communication strategies (CSs) while they were interacting to do a 12-week mobile-assisted learning project, i.e., "Organizing and Attending a Model International…

Trajectories of Maternal Depressive Symptoms, Maternal Sensitivity, and Children's Functioning at School Entry

ERIC Educational Resources Information Center

Campbell, Susan B.; Matestic, Patricia; von Stauffenberg, Camilla; Mohan, Roli; Kirchner, Thomas

2007-01-01

Using data from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development, the authors modeled trajectories of maternal depressive symptoms from infant age 1 month to 7 years. The authors identified 6 trajectories of maternal depressive symptoms: high-chronic, moderate-increasing, high-decreasing,…

Optimising seasonal streamflow forecast lead time for operational decision making in Australia

NASA Astrophysics Data System (ADS)

Schepen, Andrew; Zhao, Tongtiegang; Wang, Q. J.; Zhou, Senlin; Feikema, Paul

2016-10-01

Statistical seasonal forecasts of 3-month streamflow totals are released in Australia by the Bureau of Meteorology and updated on a monthly basis. The forecasts are often released in the second week of the forecast period, due to the onerous forecast production process. The current service relies on models built using data for complete calendar months, meaning the forecast production process cannot begin until the first day of the forecast period. Somehow, the bureau needs to transition to a service that provides forecasts before the beginning of the forecast period; timelier forecast release will become critical as sub-seasonal (monthly) forecasts are developed. Increasing the forecast lead time to one month ahead is not considered a viable option for Australian catchments that typically lack any predictability associated with snowmelt. The bureau's forecasts are built around Bayesian joint probability models that have antecedent streamflow, rainfall and climate indices as predictors. In this study, we adapt the modelling approach so that forecasts have any number of days of lead time. Daily streamflow and sea surface temperatures are used to develop predictors based on 28-day sliding windows. Forecasts are produced for 23 forecast locations with 0-14- and 21-day lead time. The forecasts are assessed in terms of continuous ranked probability score (CRPS) skill score and reliability metrics. CRPS skill scores, on average, reduce monotonically with increase in days of lead time, although both positive and negative differences are observed. Considering only skilful forecast locations, CRPS skill scores at 7-day lead time are reduced on average by 4 percentage points, with differences largely contained within +5 to -15 percentage points. A flexible forecasting system that allows for any number of days of lead time could benefit Australian seasonal streamflow forecast users by allowing more time for forecasts to be disseminated, comprehended and made use of prior to the commencement of a forecast season. The system would allow for forecasts to be updated if necessary.

Estimated monthly streamflows for selected locations on the Kabul and Logar Rivers, Aynak copper, cobalt, and chromium area of interest, Afghanistan, 1951-2010

USGS Publications Warehouse

Vining, Kevin C.; Vecchia, Aldo V.

2014-01-01

The U.S. Geological Survey, in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, used the stochastic monthly water-balance model and existing climate data to estimate monthly streamflows for 1951–2010 for selected streamgaging stations located within the Aynak copper, cobalt, and chromium area of interest in Afghanistan. The model used physically based, nondeterministic methods to estimate the monthly volumetric water-balance components of a watershed. A comparison of estimated and recorded monthly streamflows for the streamgaging stations Kabul River at Maidan and Kabul River at Tangi-Saidan indicated that the stochastic water-balance model was able to provide satisfactory estimates of monthly streamflows for high-flow months and low-flow months even though withdrawals for irrigation likely occurred. A comparison of estimated and recorded monthly streamflows for the streamgaging stations Logar River at Shekhabad and Logar River at Sangi-Naweshta also indicated that the stochastic water-balance model was able to provide reasonable estimates of monthly streamflows for the high-flow months; however, for the upstream streamgaging station, the model overestimated monthly streamflows during periods when summer irrigation withdrawals likely occurred. Results from the stochastic water-balance model indicate that the model should be able to produce satisfactory estimates of monthly streamflows for locations along the Kabul and Logar Rivers. This information could be used by Afghanistan authorities to make decisions about surface-water resources for the Aynak copper, cobalt, and chromium area of interest.

Using short-term evidence to predict six-month outcomes in clinical trials of signs and symptoms in rheumatoid arthritis.

PubMed

Nixon, Richard M; Bansback, Nick; Stevens, John W; Brennan, Alan; Madan, Jason

2009-01-01

A model is presented to generate a distribution for the probability of an ACR response at six months for a new treatment for rheumatoid arthritis given evidence from a one- or three-month clinical trial. The model is based on published evidence from 11 randomized controlled trials on existing treatments. A hierarchical logistic regression model is used to find the relationship between the proportion of patients achieving ACR20 and ACR50 at one and three months and the proportion at six months. The model is assessed by Bayesian predictive P-values that demonstrate that the model fits the data well. The model can be used to predict the number of patients with an ACR response for proposed six-month clinical trials given data from clinical trials of one or three months duration. Copyright 2008 John Wiley & Sons, Ltd.

A new evidence-based model for weight management in primary care: the Counterweight Programme.

PubMed

Laws, Rachel

2004-06-01

Obesity has become a global epidemic, and a major preventable cause of morbidity and mortality. Management strategies and treatment protocols are however poorly developed and evaluated. The aim of the Counterweight Programme is to develop an evidence-based model for the management of obesity in primary care. The Counterweight Programme is based on the theoretical model of Evidence-Based Quality Assessment aimed at improving the management of obese adults (18-75 years) in primary care. The model consists of four phases: (1) practice audit and needs assessment, (2) practice support and training, (3) practice nurse-led patient intervention, and (4) evaluation. Patient intervention consisted of screening and treatment pathways incorporating evidence-based approaches, including patient-centred goal setting, prescribed eating plans, a group programme, physical activity and behavioural approaches, anti-obesity medication and weight maintenance strategies. Weight Management Advisers who are specialist obesity dietitians facilitated programme implementation. Eighty practices were recruited of which 18 practices were randomized to act as controls and receive deferred intervention 2 years after the initial audit. By February 2004, 58 of the 62 (93.5%) intervention practices had been trained to run the intervention programme, 47 (75.8%) practices were active in implementing the model and 1256 patients had been recruited (74% female, 26% male, mean age 50.6 years, SD 14). At baseline, 75% of patients had at one or more co-morbidity, and the mean body mass index (BMI) was 36.9 kg/m(2) (SD 5.4). Of the 1256 patients recruited, 91% received one of the core lifestyle interventions in the first 12 months. For all patients followed up at 12 months, 34% achieved a clinical meaningful weight loss of 5% or more. A total of 51% of patients were classed as compliant in that they attended the required level of appointments in 3, 6, and 12 months. For fully compliant patients, weight loss improved with 43% achieving a weight loss of 5% or more at 12 months. The Counterweight Programme is an evidence-based weight management model which is feasible to implement in primary care.

Child patterns of growth delay and cognitive development in a Bolivian mining city.

PubMed

Ruiz-Castell, María; Carsin, Anne-Elie; Barbieri, Flavia-Laura; Paco, Pamela; Gardon, Jacques; Sunyer, Jordi

2013-01-01

This study aims to (1) follow up and characterize infant growth patterns during the first year of life in Bolivia, and (2) determine whether there exists an association between weight gain and cognitive development in children living near contaminated mining industries. Data on 175 children participating to the ToxBol (Toxicity in Bolivia) birth cohort were analyzed. Rapid-growth during the first 6 months was defined as a change in weight z-score > 0.67 while slow-growth was defined as a weight z-score change of < -0.67. Neurodevelopment was evaluated using the Bayley Scales of Infant Development at 10.5-12.5 months of age. Mixed models were used to examine the association between cognitive development and weight gain. Rapid growers weighed less at birth (P < 0.01). However, they revealed a higher body mass index at 12 months of age (0.70 ± 0.73, P < 0.01). After adjustment for confounding, rapid growth was not associated with cognitive development (coef = 0.49, 95% confidence interval = -4.10, 5.08). In this Bolivian cohort, children born smaller were more likely to grow/develop faster and attain greater weight and length. Their cognitive development was not affected by their growth patterns. Copyright © 2012 Wiley Periodicals, Inc.

High resolution statistical downscaling of the EUROSIP seasonal prediction. Application for southeastern Romania

NASA Astrophysics Data System (ADS)

Busuioc, Aristita; Dumitrescu, Alexandru; Dumitrache, Rodica; Iriza, Amalia

2017-04-01

Seasonal climate forecasts in Europe are currently issued at the European Centre for Medium-Range Weather Forecasts (ECMWF) in the form of multi-model ensemble predictions available within the "EUROSIP" system. Different statistical techniques to calibrate, downscale and combine the EUROSIP direct model output are used to optimize the quality of the final probabilistic forecasts. In this study, a statistical downscaling model (SDM) based on canonical correlation analysis (CCA) is used to downscale the EUROSIP seasonal forecast at a spatial resolution of 1km x 1km over the Movila farm placed in southeastern Romania. This application is achieved in the framework of the H2020 MOSES project (http://www.moses-project.eu). The combination between monthly standardized values of three climate variables (maximum/minimum temperatures-Tmax/Tmin, total precipitation-Prec) is used as predictand while combinations of various large-scale predictors are tested in terms of their availability as outputs in the seasonal EUROSIP probabilistic forecasting (sea level pressure, temperature at 850 hPa and geopotential height at 500 hPa). The predictors are taken from the ECMWF system considering 15 members of the ensemble, for which the hindcasts since 1991 until present are available. The model was calibrated over the period 1991-2014 and predictions for summers 2015 and 2016 were achieved. The calibration was made for the ensemble average as well as for each ensemble member. The model was developed for each lead time: one month anticipation for June, two months anticipation for July and three months anticipation for August. The main conclusions from these preliminary results are: best predictions (in terms of the anomaly sign) for Tmax (July-2 months anticipation, August-3 months anticipation) for both years (2015, 2016); for Tmin - good predictions only for August (3 months anticipation ) for both years; for precipitation, good predictions for July (2 months anticipation) in 2015 and August (3 months anticipation) in 2016; failed prediction for June (1-month anticipation) for all parameters. To see if the results obtained for 2015 and 2016 summers are in agreement with the general ECMWF model performance in forecast of the three predictors used in the CCA SDM calibration, the mean bias and root mean square errors (RMSE) calculated over the entire period in each grid point, for each ensemble member and ensemble average were computed. The obtained results are confirmed, showing highest ECMWF performance in forecasting of the three predictors for 3 months anticipation (August) and lowest performance for one month anticipation (June). The added value of the CCA SDM in forecasting local Tmax/Tmin and total precipitation was compared to the ECMWF performance using nearest grid point method. Comparisons were performed for the 1991-2014 period, taking into account the forecast made in May for July. An important improvement was found for the CCA SDM predictions in terms of the RMSE value (computed against observations) for Tmax/Tmin and less for precipitation. The tests are in progress for the other summer months (June, July).

A simple prognostic model for overall survival in metastatic renal cell carcinoma.

PubMed

Assi, Hazem I; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis.

A simple prognostic model for overall survival in metastatic renal cell carcinoma

PubMed Central

Assi, Hazem I.; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

Introduction: The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. Methods: We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. Results: There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. Conclusions: In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis. PMID:27217858

Forecasting monthly inflow discharge of the Iffezheim reservoir using data-driven models

NASA Astrophysics Data System (ADS)

Zhang, Qing; Aljoumani, Basem; Hillebrand, Gudrun; Hoffmann, Thomas; Hinkelmann, Reinhard

2017-04-01

River stream flow is an essential element in hydrology study fields, especially for reservoir management, since it defines input into reservoirs. Forecasting this stream flow plays an important role in short or long-term planning and management in the reservoir, e.g. optimized reservoir and hydroelectric operation or agricultural irrigation. Highly accurate flow forecasting can significantly reduce economic losses and is always pursued by reservoir operators. Therefore, hydrologic time series forecasting has received tremendous attention of researchers. Many models have been proposed to improve the hydrological forecasting. Due to the fact that most natural phenomena occurring in environmental systems appear to behave in random or probabilistic ways, different cases may need a different methods to forecast the inflow and even a unique treatment to improve the forecast accuracy. The purpose of this study is to determine an appropriate model for forecasting monthly inflow to the Iffezheim reservoir in Germany, which is the last of the barrages in the Upper Rhine. Monthly time series of discharges, measured from 1946 to 2001 at the Plittersdorf station, which is located 6 km downstream of the Iffezheim reservoir, were applied. The accuracies of the used stochastic models - Fiering model and Auto-Regressive Integrated Moving Average models (ARIMA) are compared with Artificial Intelligence (AI) models - single Artificial Neural Network (ANN) and Wavelet ANN models (WANN). The Fiering model is a linear stochastic model and used for generating synthetic monthly data. The basic idea in modeling time series using ARIMA is to identify a simple model with as few model parameters as possible in order to provide a good statistical fit to the data. To identify and fit the ARIMA models, four phase approaches were used: identification, parameter estimation, diagnostic checking, and forecasting. An automatic selection criterion, such as the Akaike information criterion, is utilized to enhance this flexible approach to set up the model. As distinct from both stochastic models, the ANN and its related conjunction methods Wavelet-ANN (WANN) models are effective to handle non-linear systems and have been developed with antecedent flows as inputs to forecast up to 12-months lead-time for the Iffezheim reservoir. In the ANN and WANN models, the Feed Forward Back Propagation method (FFBP) is applied. The sigmoid activity and linear functions were used with several different neurons for the hidden layers and for the output layer, respectively. To compare the accuracy of the different models and identify the most suitable model for reliable forecasting, four quantitative standard statistical performance evaluation measures, the root mean square error (RMSE), the mean bias error (MAE) and the determination correlation coefficient (DC), are employed. The results reveal that the ARIMA (2, 1, 2) performs better than Fiering, ANN and WANN models. Further, the WANN model is found to be slightly better than the ANN model for forecasting monthly inflow of the Iffezheim reservoir. As a result, by using the ARIMA model, the predicted and observed values agree reasonably well.

A Bayesian approach for estimating under-reported dengue incidence with a focus on non-linear associations between climate and dengue in Dhaka, Bangladesh.

PubMed

Sharmin, Sifat; Glass, Kathryn; Viennet, Elvina; Harley, David

2018-04-01

Determining the relation between climate and dengue incidence is challenging due to under-reporting of disease and consequent biased incidence estimates. Non-linear associations between climate and incidence compound this. Here, we introduce a modelling framework to estimate dengue incidence from passive surveillance data while incorporating non-linear climate effects. We estimated the true number of cases per month using a Bayesian generalised linear model, developed in stages to adjust for under-reporting. A semi-parametric thin-plate spline approach was used to quantify non-linear climate effects. The approach was applied to data collected from the national dengue surveillance system of Bangladesh. The model estimated that only 2.8% (95% credible interval 2.7-2.8) of all cases in the capital Dhaka were reported through passive case reporting. The optimal mean monthly temperature for dengue transmission is 29℃ and average monthly rainfall above 15 mm decreases transmission. Our approach provides an estimate of true incidence and an understanding of the effects of temperature and rainfall on dengue transmission in Dhaka, Bangladesh.

Treating the untreated: applying a community-based, culturally sensitive psychiatric intervention to confined and physically restrained mentally ill individuals in Bali, Indonesia.

PubMed

Suryani, Luh Ketut; Lesmana, Cokorda Bagus Jaya; Tiliopoulos, Niko

2011-11-01

This study identified, mapped and treated the clinical features of mentally ill people, who had been isolated and restrained by family and community members as a result of a functional failure of the traditional medical, hospital-based mental health model currently practiced in Indonesia. A 10-month epidemiological population survey was carried out in Karangasem regency of Bali, Indonesia. A total of 404,591 individuals were clinically interviewed, of which 895 individuals with mental health problems were identified, with 23 satisfying criteria of physical restraint and confinement. Of the latter, twenty were males; age range was 19-69 years, all diagnosed by the researchers with schizophrenia-spectrum disorder (ICD-10 diagnostic criteria). Duration of restraint ranged from 3 months to 30 years (mean = 8.1 years, SD = 8.3 years). Through the application of a holistic intervention model, all patients exhibited a remarkable recovery within 19 months of treatment. We conclude that the development of a community-based, culturally sensitive and respectful mental health model can serve as an optimum promoter of positive mental health outcomes.

Forecasting the probability of future groundwater levels declining below specified low thresholds in the conterminous U.S.

USGS Publications Warehouse

Dudley, Robert W.; Hodgkins, Glenn A.; Dickinson, Jesse

2017-01-01

We present a logistic regression approach for forecasting the probability of future groundwater levels declining or maintaining below specific groundwater-level thresholds. We tested our approach on 102 groundwater wells in different climatic regions and aquifers of the United States that are part of the U.S. Geological Survey Groundwater Climate Response Network. We evaluated the importance of current groundwater levels, precipitation, streamflow, seasonal variability, Palmer Drought Severity Index, and atmosphere/ocean indices for developing the logistic regression equations. Several diagnostics of model fit were used to evaluate the regression equations, including testing of autocorrelation of residuals, goodness-of-fit metrics, and bootstrap validation testing. The probabilistic predictions were most successful at wells with high persistence (low month-to-month variability) in their groundwater records and at wells where the groundwater level remained below the defined low threshold for sustained periods (generally three months or longer). The model fit was weakest at wells with strong seasonal variability in levels and with shorter duration low-threshold events. We identified challenges in deriving probabilistic-forecasting models and possible approaches for addressing those challenges.

Development of a New Class of Drugs to Inhibit All Forms of Androgen Receptor in Castration Resistant Prostate Cancers

DTIC Science & Technology

2015-10-01

inhibitor, chromatin, x-ray crystallography , pre-clinical 3. ACCOMPLISHMENTS a. Major goals of the project as outlined in the approved Statement of...modeling of derivatives of our current lead VPC-14228 (months 1-30) 3.2. Synthesis of derivatives of our lead compounds (months 6-30). 3.3.Experimental...Activities for Vancouver Prostate Centre Site (Rennie, PI) In the first reporting period, the major activities consisted of a) design and synthesis of

Water balance models in one-month-ahead streamflow forecasting

USGS Publications Warehouse

Alley, William M.

1985-01-01

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

Limiting parental feedback disrupts vocal development in marmoset monkeys

PubMed Central

Gultekin, Yasemin B.; Hage, Steffen R.

2017-01-01

Vocalizations of human infants undergo dramatic changes across the first year by becoming increasingly mature and speech-like. Human vocal development is partially dependent on learning by imitation through social feedback between infants and caregivers. Recent studies revealed similar developmental processes being influenced by parental feedback in marmoset monkeys for apparently innate vocalizations. Marmosets produce infant-specific vocalizations that disappear after the first postnatal months. However, it is yet unclear whether parental feedback is an obligate requirement for proper vocal development. Using quantitative measures to compare call parameters and vocal sequence structure we show that, in contrast to normally raised marmosets, marmosets that were separated from parents after the third postnatal month still produced infant-specific vocal behaviour at subadult stages. These findings suggest a significant role of social feedback on primate vocal development until the subadult stages and further show that marmoset monkeys are a compelling model system for early human vocal development. PMID:28090084

Validation of High Frequency (HF) Propagation Prediction Models in the Arctic region

NASA Astrophysics Data System (ADS)

Athieno, R.; Jayachandran, P. T.

2014-12-01

Despite the emergence of modern techniques for long distance communication, Ionospheric communication in the high frequency (HF) band (3-30 MHz) remains significant to both civilian and military users. However, the efficient use of the ever-varying ionosphere as a propagation medium is dependent on the reliability of ionospheric and HF propagation prediction models. Most available models are empirical implying that data collection has to be sufficiently large to provide good intended results. The models we present were developed with little data from the high latitudes which necessitates their validation. This paper presents the validation of three long term High Frequency (HF) propagation prediction models over a path within the Arctic region. Measurements of the Maximum Usable Frequency for a 3000 km range (MUF (3000) F2) for Resolute, Canada (74.75° N, 265.00° E), are obtained from hand-scaled ionograms generated by the Canadian Advanced Digital Ionosonde (CADI). The observations have been compared with predictions obtained from the Ionospheric Communication Enhanced Profile Analysis Program (ICEPAC), Voice of America Coverage Analysis Program (VOACAP) and International Telecommunication Union Recommendation 533 (ITU-REC533) for 2009, 2011, 2012 and 2013. A statistical analysis shows that the monthly predictions seem to reproduce the general features of the observations throughout the year though it is more evident in the winter and equinox months. Both predictions and observations show a diurnal and seasonal variation. The analysed models did not show large differences in their performances. However, there are noticeable differences across seasons for the entire period analysed: REC533 gives a better performance in winter months while VOACAP has a better performance for both equinox and summer months. VOACAP gives a better performance in the daily predictions compared to ICEPAC though, in general, the monthly predictions seem to agree more with the observations compared to the daily predictions.

Predicting hydrological response to forest changes by simple statistical models: the selection of the best indicator of forest changes with a hydrological perspective

NASA Astrophysics Data System (ADS)

Ning, D.; Zhang, M.; Ren, S.; Hou, Y.; Yu, L.; Meng, Z.

2017-01-01

Forest plays an important role in hydrological cycle, and forest changes will inevitably affect runoff across multiple spatial scales. The selection of a suitable indicator for forest changes is essential for predicting forest-related hydrological response. This study used the Meijiang River, one of the headwaters of the Poyang Lake as an example to identify the best indicator of forest changes for predicting forest change-induced hydrological responses. Correlation analysis was conducted first to detect the relationships between monthly runoff and its predictive variables including antecedent monthly precipitation and indicators for forest changes (forest coverage, vegetation indices including EVI, NDVI, and NDWI), and by use of the identified predictive variables that were most correlated with monthly runoff, multiple linear regression models were then developed. The model with best performance identified in this study included two independent variables -antecedent monthly precipitation and NDWI. It indicates that NDWI is the best indicator of forest change in hydrological prediction while forest coverage, the most commonly used indicator of forest change is insignificantly related to monthly runoff. This highlights the use of vegetation index such as NDWI to indicate forest changes in hydrological studies. This study will provide us with an efficient way to quantify the hydrological impact of large-scale forest changes in the Meijiang River watershed, which is crucial for downstream water resource management and ecological protection in the Poyang Lake basin.

34 CFR 366.63 - What evidence must a center present to demonstrate that it is in minimum compliance with the...

Code of Federal Regulations, 2013 CFR

2013-07-01

... employees who are on unpaid family or maternity leave during this six-month period. (2) Self-help and self... relationships and peer role models. The center shall provide evidence in its most recent annual performance report that it promotes the development of peer relationships and peer role models among individuals with...

34 CFR 366.63 - What evidence must a center present to demonstrate that it is in minimum compliance with the...

Code of Federal Regulations, 2012 CFR

2012-07-01

... employees who are on unpaid family or maternity leave during this six-month period. (2) Self-help and self... relationships and peer role models. The center shall provide evidence in its most recent annual performance report that it promotes the development of peer relationships and peer role models among individuals with...

34 CFR 366.63 - What evidence must a center present to demonstrate that it is in minimum compliance with the...

Code of Federal Regulations, 2014 CFR

2014-07-01

... employees who are on unpaid family or maternity leave during this six-month period. (2) Self-help and self... relationships and peer role models. The center shall provide evidence in its most recent annual performance report that it promotes the development of peer relationships and peer role models among individuals with...

Natural and molecular history of prolactinoma: insights from a Prlr-/- mouse model.

PubMed

Bernard, Valérie; Villa, Chiara; Auguste, Aurélie; Lamothe, Sophie; Guillou, Anne; Martin, Agnès; Caburet, Sandrine; Young, Jacques; Veitia, Reiner A; Binart, Nadine

2018-01-19

Lactotroph adenoma, also called prolactinoma, is the most common pituitary tumor but little is known about its pathogenesis. Mouse models of prolactinoma can be useful to better understand molecular mechanisms involved in abnormal lactotroph cell proliferation and secretion. We have previously developed a prolactin receptor deficient ( Prlr -/- ) mouse, which develops prolactinoma. The present study aims to explore the natural history of prolactinoma formation in Prlr -/- mice, using hormonal, radiological, histological and molecular analyses to uncover mechanisms involved in lactotroph adenoma development. Prlr -/- females develop large secreting prolactinomas from 12 months of age, with a penetrance of 100%, mimicking human aggressive densely granulated macroprolactinoma, which is a highly secreting subtype. Mean blood PRL measurements reach 14 902 ng/mL at 24 months in Prlr -/- females while PRL levels were below 15 ng/mL in control mice ( p < 0.01). By comparing pituitary microarray data of Prlr -/- mice and an estrogen-induced prolactinoma model in ACI rats, we pinpointed 218 concordantly differentially expressed (DE) genes involved in cell cycle, mitosis, cell adhesion molecules, dopaminergic synapse and estrogen signaling. Pathway/gene-set enrichment analyses suggest that the transcriptomic dysregulation in both models of prolactinoma might be mediated by a limited set of transcription factors (i.e., STAT5, STAT3, AhR, ESR1, BRD4, CEBPD, YAP, FOXO1) and kinases (i.e., JAK2, AKT1, BRAF, BMPR1A, CDK8, HUNK, ALK, FGFR1, ILK). Our experimental results and their bioinformatic analysis provide insights into early genomic changes in murine models of the most frequent human pituitary tumor.

Identification of age-dependent motor and neuropsychological behavioural abnormalities in a mouse model of Mucopolysaccharidosis Type II

PubMed Central

Gleitz, Hélène F. E.; O’Leary, Claire; Holley, Rebecca J.

2017-01-01

Severe mucopolysaccharidosis type II (MPS II) is a progressive lysosomal storage disease caused by mutations in the IDS gene, leading to a deficiency in the iduronate-2-sulfatase enzyme that is involved in heparan sulphate and dermatan sulphate catabolism. In constitutive form, MPS II is a multi-system disease characterised by progressive neurocognitive decline, severe skeletal abnormalities and hepatosplenomegaly. Although enzyme replacement therapy has been approved for treatment of peripheral organs, no therapy effectively treats the cognitive symptoms of the disease and novel therapies are in development to remediate this. Therapeutic efficacy and subsequent validation can be assessed using a variety of outcome measures that are translatable to clinical practice, such as behavioural measures. We sought to consolidate current knowledge of the cognitive, skeletal and motor abnormalities present in the MPS II mouse model by performing time course behavioural examinations of working memory, anxiety, activity levels, sociability and coordination and balance, up to 8 months of age. Cognitive decline associated with alterations in spatial working memory is detectable at 8 months of age in MPS II mice using spontaneous alternation, together with an altered response to novel environments and anxiolytic behaviour in the open-field. Coordination and balance on the accelerating rotarod were also significantly worse at 8 months, and may be associated with skeletal changes seen in MPS II mice. We demonstrate that the progressive nature of MPS II disease is also seen in the mouse model, and that cognitive and motor differences are detectable at 8 months of age using spontaneous alternation, the accelerating rotarod and the open-field tests. This study establishes neurological, motor and skeletal measures for use in pre-clinical studies to develop therapeutic approaches in MPS II. PMID:28207863

Association between month of birth and melanoma risk: fact or fiction?

PubMed

Fiessler, Cornelia; Pfahlberg, Annette B; Keller, Andrea K; Radespiel-Tröger, Martin; Uter, Wolfgang; Gefeller, Olaf

2017-04-01

Evidence on the effect of ultraviolet radiation (UVR) exposure in infancy on melanoma risk in later life is scarce. Three recent studies suggest that people born in spring carry a higher melanoma risk. Our study aimed at verifying whether such a seasonal pattern of melanoma risk actually exists. Data from the population-based Cancer Registry Bavaria (CRB) on the birth months of 28 374 incident melanoma cases between 2002 and 2012 were analysed and compared with data from the Bavarian State Office for Statistics and Data Processing on the birth month distribution in the Bavarian population. Crude and adjusted analyses using negative binomial regression models were performed in the total study group and supplemented by several subgroup analyses. In the crude analysis, the birth months March-May were over-represented among melanoma cases. Negative binomial regression models adjusted only for sex and birth year revealed a seasonal association between melanoma risk and birth month with 13-21% higher relative incidence rates for March, April and May compared with the reference December. However, after additionally adjusting for the birth month distribution of the Bavarian population, these risk estimates decreased markedly and no association with the birth month was observed any more. Similar results emerged in all subgroup analyses. Our large registry-based study provides no evidence that people born in spring carry a higher risk for developing melanoma in later life and thus lends no support to the hypothesis of higher UVR susceptibility during the first months of life. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

Forecasting incidence of dengue in Rajasthan, using time series analyses.

PubMed

Bhatnagar, Sunil; Lal, Vivek; Gupta, Shiv D; Gupta, Om P

2012-01-01

To develop a prediction model for dengue fever/dengue haemorrhagic fever (DF/DHF) using time series data over the past decade in Rajasthan and to forecast monthly DF/DHF incidence for 2011. Seasonal autoregressive integrated moving average (SARIMA) model was used for statistical modeling. During January 2001 to December 2010, the reported DF/DHF cases showed a cyclical pattern with seasonal variation. SARIMA (0,0,1) (0,1,1) 12 model had the lowest normalized Bayesian information criteria (BIC) of 9.426 and mean absolute percentage error (MAPE) of 263.361 and appeared to be the best model. The proportion of variance explained by the model was 54.3%. Adequacy of the model was established through Ljung-Box test (Q statistic 4.910 and P-value 0.996), which showed no significant correlation between residuals at different lag times. The forecast for the year 2011 showed a seasonal peak in the month of October with an estimated 546 cases. Application of SARIMA model may be useful for forecast of cases and impending outbreaks of DF/DHF and other infectious diseases, which exhibit seasonal pattern.

River flow simulation using a multilayer perceptron-firefly algorithm model

NASA Astrophysics Data System (ADS)

Darbandi, Sabereh; Pourhosseini, Fatemeh Akhoni

2018-06-01

River flow estimation using records of past time series is importance in water resources engineering and management and is required in hydrologic studies. In the past two decades, the approaches based on the artificial neural networks (ANN) were developed. River flow modeling is a non-linear process and highly affected by the inputs to the modeling. In this study, the best input combination of the models was identified using the Gamma test then MLP-ANN and hybrid multilayer perceptron (MLP-FFA) is used to forecast monthly river flow for a set of time intervals using observed data. The measurements from three gauge at Ajichay watershed, East Azerbaijani, were used to train and test the models approach for the period from January 2004 to July 2016. Calibration and validation were performed within the same period for MLP-ANN and MLP-FFA models after the preparation of the required data. Statistics, the root mean square error and determination coefficient, are used to verify outputs from MLP-ANN to MLP-FFA models. The results show that MLP-FFA model is satisfactory for monthly river flow simulation in study area.

Infant Characteristics and Parental Engagement at the Transition to Parenthood

PubMed Central

Schoppe-Sullivan, Sarah J.; Kamp Dush, Claire M.

2015-01-01

Positive engagement activities support children's adaptive development and new parents are encouraged to be highly engaged with infants. Yet, fathers' engagement is widely understudied and maternal engagement quantity is frequently overlooked. Our study contributes to growing knowledge on associations between infant temperament and parental engagement by testing transactional and moderation models in a recent sample of first-time parents when infants were 3, 6, and 9 months old. Stringent longitudinal, reciprocal structural equation models partially confirmed an engagement "benefit". Mothers' engagement marginally contributed to their children's gains in effortful control from 3 to 6 months regardless of child gender. Further, mothers' engagement reduced infant negative affect from 6 to 9 months regardless of child gender. Mothers' ratings of infant negative affect were gendered; mothers' ratings of infant negative affect increases more from 3 to 6 months for boys. Fathers' engagement was contextually sensitive; child gender moderated the link between negative affect and engagement from 6 to 9 months, such that fathers became more engaged with boys whom they rated higher on negative affect; there was no effect for daughters. Finally, we found that effortful control moderated associations between negative affect and maternal engagement; mothers' engagement increases from 3 to 6 months were greater for children initially rated lower in effortful control. Implications for future research and parenting education and support services are discussed. PMID:25459796

Behavioral and Socioemotional Outcomes Through Age 5 Years of the Legacy for Children Public Health Approach to Improving Developmental Outcomes Among Children Born Into Poverty

PubMed Central

Perou, Ruth; Visser, Susanna N.; Scott, Keith G.; Beckwith, Leila; Howard, Judy; Smith, D. Camille; Danielson, Melissa L.

2013-01-01

Objectives. We evaluated Legacy for Children, a public health strategy to improve child health and development among low-income families. Methods. Mothers were recruited prenatally or at the birth of a child to participate in Legacy parenting groups for 3 to 5 years. A set of 2 randomized trials in Miami, Florida, and Los Angeles, California, between 2001 and 2009 assessed 574 mother-child pairs when the children were 6, 12, 24, 36, 48, and 60 months old. Intent-to-treat analyses from 12 to 60 months compared groups on child behavioral and socioemotional outcomes. Results. Children of mothers in the intervention group were at lower risk for behavioral concerns at 24 months and socioemotional problems at 48 months in Miami, and lower risk for hyperactive behavior at 60 months in Los Angeles. Longitudinal analyses indicated that children of intervention mothers in Miami were at lower risk for behavior problems from 24 to 60 months of age. Conclusions. Randomized controlled trials documented effectiveness of the Legacy model over time while allowing for implementation adaptations by 2 different sites. Broadly disseminable, parent-focused prevention models such as Legacy have potential for public health impact. These investments in prevention might reduce the need for later intervention strategies. PMID:23597356

Modeling Parenting Programs as an Interim Service for Families Waiting for Children's Mental Health Treatment.

PubMed

Cunningham, Charles E; Rimas, Heather; Chen, Yvonne; Deal, Ken; McGrath, Patrick; Lingley-Pottie, Patricia; Reid, Graham J; Lipman, Ellen; Corkum, Penny

2015-01-01

Using a discrete choice conjoint experiment, we explored the design of parenting programs as an interim strategy for families waiting for children's mental health treatment. Latent class analysis yielded 4 segments with different design preferences. Simulations predicted the Fast-Paced Personal Contact segment, 22.1% of the sample, would prefer weekly therapist-led parenting groups. The Moderate-Paced Personal Contact segment (24.7%) preferred twice-monthly therapist-led parenting groups with twice-monthly lessons. The Moderate-Paced E-Contact segment (36.3%), preferred weekly to twice-monthly contacts, e-mail networking, and a program combining therapist-led sessions with the support of a computerized telephone e-coach. The Slow-Paced E-Contact segment (16.9%) preferred an approach combining monthly therapist-led sessions, e-coaching, and e-mail networking with other parents. Simulations predicted 45.3% of parents would utilize an option combining 5 therapist coaching calls with 5 e-coaching calls, a model that could reduce costs and extend the availability of interim services. Although 41.0% preferred weekly pacing, 58% were predicted to choose an interim parenting service conducted at a twice-monthly to monthly pace. The results of this study suggest that developing interim services reflecting parental preferences requires a choice of formats that includes parenting groups, telephone-coached distance programs, and e-coaching options conducted at a flexible pace.

Experiments in monthly mean simulation of the atmosphere with a coarse-mesh general circulation model

NASA Technical Reports Server (NTRS)

Lutz, R. J.; Spar, J.

1978-01-01

The Hansen atmospheric model was used to compute five monthly forecasts (October 1976 through February 1977). The comparison is based on an energetics analysis, meridional and vertical profiles, error statistics, and prognostic and observed mean maps. The monthly mean model simulations suffer from several defects. There is, in general, no skill in the simulation of the monthly mean sea-level pressure field, and only marginal skill is indicated for the 850 mb temperatures and 500 mb heights. The coarse-mesh model appears to generate a less satisfactory monthly mean simulation than the finer mesh GISS model.

Peak Weight and Height Velocity to Age 36 Months and Asthma Development: The Norwegian Mother and Child Cohort Study

PubMed Central

Magnus, Maria C.; Stigum, Hein; Håberg, Siri E.; Nafstad, Per; London, Stephanie J.; Nystad, Wenche

2015-01-01

Background The immediate postnatal period is the period of the fastest growth in the entire life span and a critical period for lung development. Therefore, it is interesting to examine the association between growth during this period and childhood respiratory disorders. Methods We examined the association of peak weight and height velocity to age 36 months with maternal report of current asthma at 36 months (n = 50,311), recurrent lower respiratory tract infections (LRTIs) by 36 months (n = 47,905) and current asthma at 7 years (n = 24,827) in the Norwegian Mother and Child Cohort Study. Peak weight and height velocity was calculated using the Reed1 model through multilevel mixed-effects linear regression. Multivariable log-binomial regression was used to calculate adjusted relative risks (adj.RR) and 95% confidence intervals (CI). We also conducted a sibling pair analysis using conditional logistic regression. Results Peak weight velocity was positively associated with current asthma at 36 months [adj.RR 1.22 (95%CI: 1.18, 1.26) per standard deviation (SD) increase], recurrent LRTIs by 36 months [adj.RR 1.14 (1.10, 1.19) per SD increase] and current asthma at 7 years [adj.RR 1.13 (95%CI: 1.07, 1.19) per SD increase]. Peak height velocity was not associated with any of the respiratory disorders. The positive association of peak weight velocity and asthma at 36 months remained in the sibling pair analysis. Conclusions Higher peak weight velocity, achieved during the immediate postnatal period, increased the risk of respiratory disorders. This might be explained by an influence on neonatal lung development, shared genetic/epigenetic mechanisms and/or environmental factors. PMID:25635872

Treatment carryover impacts on effectiveness of intraocular pressure lowering agents, estimated by a discrete event simulation model.

PubMed

Denis, P; Le Pen, C; Umuhire, D; Berdeaux, G

2008-01-01

To compare the effectiveness of two treatment sequences, latanoprost-latanoprost timolol fixed combination (L-LT) versus travoprost-travoprost timolol fixed combination (T-TT), in the treatment of open-angle glaucoma (OAG) or ocular hypertension (OHT). A discrete event simulation (DES) model was constructed. Patients with either OAG or OHT were treated first-line with a prostaglandin, either latanoprost or travoprost. In case of treatment failure, patients were switched to the specific prostaglandin-timolol sequence LT or TT. Failure was defined as intraocular pressure higher than or equal to 18 mmHg at two visits. Time to failure was estimated from two randomized clinical trials. Log-rank tests were computed. Linear functions after log-log transformation were used to model time to failure. The time horizon of the model was 60 months. Outcomes included treatment failure and disease progression. Sensitivity analyses were performed. Latanoprost treatment resulted in more treatment failures than travoprost (p<0.01), and LT more than TT (p<0.01). At 60 months, the probability of starting a third treatment line was 39.2% with L-LT versus 29.9% with T-TT. On average, L-LT patients developed 0.55 new visual field defects versus 0.48 for T-TT patients. The probability of no disease progression at 60 months was 61.4% with L-LT and 65.5% with T-TT. Based on randomized clinical trial results and using a DES model, the T-TT sequence was more effective at avoiding starting a third line treatment than the L-LT sequence. T-TT treated patients developed less glaucoma progression.

A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China.

PubMed

Xu, Lilai; Gao, Peiqing; Cui, Shenghui; Liu, Chun

2013-06-01

Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 - 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 - 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term. Copyright © 2013 Elsevier Ltd. All rights reserved.

Modelling human skull growth: a validated computational model

PubMed Central

Marghoub, Arsalan; Johnson, David; Khonsari, Roman H.; Fagan, Michael J.; Moazen, Mehran

2017-01-01

During the first year of life, the brain grows rapidly and the neurocranium increases to about 65% of its adult size. Our understanding of the relationship between the biomechanical forces, especially from the growing brain, the craniofacial soft tissue structures and the individual bone plates of the skull vault is still limited. This basic knowledge could help in the future planning of craniofacial surgical operations. The aim of this study was to develop a validated computational model of skull growth, based on the finite-element (FE) method, to help understand the biomechanics of skull growth. To do this, a two-step validation study was carried out. First, an in vitro physical three-dimensional printed model and an in silico FE model were created from the same micro-CT scan of an infant skull and loaded with forces from the growing brain from zero to two months of age. The results from the in vitro model validated the FE model before it was further developed to expand from 0 to 12 months of age. This second FE model was compared directly with in vivo clinical CT scans of infants without craniofacial conditions (n = 56). The various models were compared in terms of predicted skull width, length and circumference, while the overall shape was quantified using three-dimensional distance plots. Statistical analysis yielded no significant differences between the male skull models. All size measurements from the FE model versus the in vitro physical model were within 5%, with one exception showing a 7.6% difference. The FE model and in vivo data also correlated well, with the largest percentage difference in size being 8.3%. Overall, the FE model results matched well with both the in vitro and in vivo data. With further development and model refinement, this modelling method could be used to assist in preoperative planning of craniofacial surgery procedures and could help to reduce reoperation rates. PMID:28566514

Modelling human skull growth: a validated computational model.

PubMed

Libby, Joseph; Marghoub, Arsalan; Johnson, David; Khonsari, Roman H; Fagan, Michael J; Moazen, Mehran

2017-05-01

During the first year of life, the brain grows rapidly and the neurocranium increases to about 65% of its adult size. Our understanding of the relationship between the biomechanical forces, especially from the growing brain, the craniofacial soft tissue structures and the individual bone plates of the skull vault is still limited. This basic knowledge could help in the future planning of craniofacial surgical operations. The aim of this study was to develop a validated computational model of skull growth, based on the finite-element (FE) method, to help understand the biomechanics of skull growth. To do this, a two-step validation study was carried out. First, an in vitro physical three-dimensional printed model and an in silico FE model were created from the same micro-CT scan of an infant skull and loaded with forces from the growing brain from zero to two months of age. The results from the in vitro model validated the FE model before it was further developed to expand from 0 to 12 months of age. This second FE model was compared directly with in vivo clinical CT scans of infants without craniofacial conditions ( n = 56). The various models were compared in terms of predicted skull width, length and circumference, while the overall shape was quantified using three-dimensional distance plots. Statistical analysis yielded no significant differences between the male skull models. All size measurements from the FE model versus the in vitro physical model were within 5%, with one exception showing a 7.6% difference. The FE model and in vivo data also correlated well, with the largest percentage difference in size being 8.3%. Overall, the FE model results matched well with both the in vitro and in vivo data. With further development and model refinement, this modelling method could be used to assist in preoperative planning of craniofacial surgery procedures and could help to reduce reoperation rates. © 2017 The Author(s).

Effect of glatiramer acetate three-times weekly on the evolution of new, active multiple sclerosis lesions into T1-hypointense "black holes": a post hoc magnetic resonance imaging analysis.

PubMed

Zivadinov, Robert; Dwyer, Michael; Barkay, Hadas; Steinerman, Joshua R; Knappertz, Volker; Khan, Omar

2015-03-01

Conversion of active lesions to black holes has been associated with disability progression in subjects with relapsing-remitting multiple sclerosis (RRMS) and represents a complementary approach to evaluating clinical efficacy. The objective of this study was to assess the conversion of new active magnetic resonance imaging (MRI) lesions, identified 6 months after initiating treatment with glatiramer acetate 40 mg/mL three-times weekly (GA40) or placebo, to T1-hypointense black holes in subjects with RRMS. Subjects received GA40 (n = 943) or placebo (n = 461) for 12 months. MRI was obtained at baseline and Months 6 and 12. New lesions were defined as either gadolinium-enhancing T1 or new T2 lesions at Month 6 that were not present at baseline. The adjusted mean numbers of new active lesions at Month 6 converting to black holes at Month 12 were analyzed using a negative binomial model; adjusted proportions of new active lesions at Month 6 converting to black holes at Month 12 were analyzed using a logistic regression model. Of 1,292 subjects with complete MRI data, 433 (50.3 %) GA-treated and 247 (57.2 %) placebo-treated subjects developed new lesions at Month 6. Compared with placebo, GA40 significantly reduced the mean number (0.31 versus 0.45; P = .0258) and proportion (15.8 versus 19.6 %; P = .006) of new lesions converting to black holes. GA significantly reduced conversion of new active lesions to black holes, highlighting the ability of GA40 to prevent tissue damage in RRMS.

Box Model of a Series of Salt Ponds, as Applied to the Alviso Salt Pond Complex, South San Francisco Bay, California

USGS Publications Warehouse

Lionberger, Megan A.; Schoellhamer, David H.; Shellenbarger, Gregory; Orlando, James L.; Ganju, Neil K.

2007-01-01

This report documents the development and application of a box model to simulate water level, salinity, and temperature of the Alviso Salt Pond Complex in South San Francisco Bay. These ponds were purchased for restoration in 2003 and currently are managed by the U.S. Fish and Wildlife Service to maintain existing wildlife habitat and prevent a build up of salt during the development of a long-term restoration plan. The model was developed for the purpose of aiding pond managers during the current interim management period to achieve these goals. A previously developed box model of a salt pond, SPOOM, which calculates daily pond volume and salinity, was reconfigured to simulate multiple connected ponds and a temperature subroutine was added. The updated model simulates rainfall, evaporation, water flowing between the ponds and the adjacent tidal slough network, and water flowing from one pond to the next by gravity and pumps. Theoretical and measured relations between discharge and corresponding differences in water level are used to simulate most flows between ponds and between ponds and sloughs. The principle of conservation of mass is used to calculate daily pond volume and salinity. The model configuration includes management actions specified in the Interim Stewardship Plan for the ponds. The temperature subroutine calculates hourly net heat transfer to or from a pond resulting in a rise or drop in pond temperature and daily average, minimum, and maximum pond temperatures are recorded. Simulated temperature was compared with hourly measured data from pond 3 of the Napa?Sonoma Salt Pond Complex and monthly measured data from pond A14 of the Alviso Salt-Pond Complex. Comparison showed good agreement of measured and simulated pond temperature on the daily and monthly time scales.

Statistical downscaling of general-circulation-model- simulated average monthly air temperature to the beginning of flowering of the dandelion (Taraxacum officinale) in Slovenia

NASA Astrophysics Data System (ADS)

Bergant, Klemen; Kajfež-Bogataj, Lučka; Črepinšek, Zalika

2002-02-01

Phenological observations are a valuable source of information for investigating the relationship between climate variation and plant development. Potential climate change in the future will shift the occurrence of phenological phases. Information about future climate conditions is needed in order to estimate this shift. General circulation models (GCM) provide the best information about future climate change. They are able to simulate reliably the most important mean features on a large scale, but they fail on a regional scale because of their low spatial resolution. A common approach to bridging the scale gap is statistical downscaling, which was used to relate the beginning of flowering of Taraxacum officinale in Slovenia with the monthly mean near-surface air temperature for January, February and March in Central Europe. Statistical models were developed and tested with NCAR/NCEP Reanalysis predictor data and EARS predictand data for the period 1960-1999. Prior to developing statistical models, empirical orthogonal function (EOF) analysis was employed on the predictor data. Multiple linear regression was used to relate the beginning of flowering with expansion coefficients of the first three EOF for the Janauary, Febrauary and March air temperatures, and a strong correlation was found between them. Developed statistical models were employed on the results of two GCM (HadCM3 and ECHAM4/OPYC3) to estimate the potential shifts in the beginning of flowering for the periods 1990-2019 and 2020-2049 in comparison with the period 1960-1989. The HadCM3 model predicts, on average, 4 days earlier occurrence and ECHAM4/OPYC3 5 days earlier occurrence of flowering in the period 1990-2019. The analogous results for the period 2020-2049 are a 10- and 11-day earlier occurrence.

Framework for the mapping of the monthly average daily solar radiation using an advanced case-based reasoning and a geostatistical technique.

PubMed

Lee, Minhyun; Koo, Choongwan; Hong, Taehoon; Park, Hyo Seon

2014-04-15

For the effective photovoltaic (PV) system, it is necessary to accurately determine the monthly average daily solar radiation (MADSR) and to develop an accurate MADSR map, which can simplify the decision-making process for selecting the suitable location of the PV system installation. Therefore, this study aimed to develop a framework for the mapping of the MADSR using an advanced case-based reasoning (CBR) and a geostatistical technique. The proposed framework consists of the following procedures: (i) the geographic scope for the mapping of the MADSR is set, and the measured MADSR and meteorological data in the geographic scope are collected; (ii) using the collected data, the advanced CBR model is developed; (iii) using the advanced CBR model, the MADSR at unmeasured locations is estimated; and (iv) by applying the measured and estimated MADSR data to the geographic information system, the MADSR map is developed. A practical validation was conducted by applying the proposed framework to South Korea. It was determined that the MADSR map developed through the proposed framework has been improved in terms of accuracy. The developed MADSR map can be used for estimating the MADSR at unmeasured locations and for determining the optimal location for the PV system installation.

Improving the performance of streamflow forecasting model using data-preprocessing technique in Dungun River Basin

NASA Astrophysics Data System (ADS)

Khai Tiu, Ervin Shan; Huang, Yuk Feng; Ling, Lloyd

2018-03-01

An accurate streamflow forecasting model is important for the development of flood mitigation plan as to ensure sustainable development for a river basin. This study adopted Variational Mode Decomposition (VMD) data-preprocessing technique to process and denoise the rainfall data before putting into the Support Vector Machine (SVM) streamflow forecasting model in order to improve the performance of the selected model. Rainfall data and river water level data for the period of 1996-2016 were used for this purpose. Homogeneity tests (Standard Normal Homogeneity Test, the Buishand Range Test, the Pettitt Test and the Von Neumann Ratio Test) and normality tests (Shapiro-Wilk Test, Anderson-Darling Test, Lilliefors Test and Jarque-Bera Test) had been carried out on the rainfall series. Homogenous and non-normally distributed data were found in all the stations, respectively. From the recorded rainfall data, it was observed that Dungun River Basin possessed higher monthly rainfall from November to February, which was during the Northeast Monsoon. Thus, the monthly and seasonal rainfall series of this monsoon would be the main focus for this research as floods usually happen during the Northeast Monsoon period. The predicted water levels from SVM model were assessed with the observed water level using non-parametric statistical tests (Biased Method, Kendall's Tau B Test and Spearman's Rho Test).

Impact of a comprehensive population health management program on health care costs.

PubMed

Grossmeier, Jessica; Seaverson, Erin L D; Mangen, David J; Wright, Steven; Dalal, Karl; Phalen, Chris; Gold, Daniel B

2013-06-01

Assess the influence of participation in a population health management (PHM) program on health care costs. A quasi-experimental study relied on logistic and ordinary least squares regression models to compare the costs of program participants with those of nonparticipants, while controlling for differences in health care costs and utilization, demographics, and health status. Propensity score models were developed and analyses were weighted by inverse propensity scores to control for selection bias. Study models yielded an estimated savings of $60.65 per wellness participant per month and $214.66 per disease management participant per month. Program savings were combined to yield an integrated return-on-investment of $3 in savings for every dollar invested. A PHM program yielded a positive return on investment after 2 years of wellness program and 1 year of integrated disease management program launch.

Calcar bone graft

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

Bargar, W.L.; Paul, H.A.; Merritt, K.

1986-01-01

A canine model was developed to investigate the use of an autogeneic iliac bone graft to treat the calcar deficiency commonly found at the time of revision surgery for femoral component loosening. Five large male mixed-breed dogs had bilateral total hip arthroplasty staged at three-month intervals, and were sacrificed at six months. Prior to cementing the femoral component, an experimental calcar defect was made, and a bicortical iliac bone graft was fashioned to fill the defect. Serial roentgenograms showed the grafts had united with no resorption. Technetium-99 bone scans showed more uptake at three months than at six months inmore » the graft region. Disulfine blue injection indicated all grafts were perfused at both three and six months. Thin section histology, fluorochromes, and microradiographs confirmed graft viability in all dogs. Semiquantitative grading of the fluorochromes indicated new bone deposition in 20%-50% of each graft at three months and 50%-80% at six months. Although the calcar bone graft was uniformly successful in this canine study, the clinical application of this technique should be evaluated by long-term results in humans.« less

Developmental processes across the first two years of parenthood: Stability and change in adult attachment style.

PubMed

Stern, Jessica A; Fraley, R Chris; Jones, Jason D; Gross, Jacquelyn T; Shaver, Phillip R; Cassidy, Jude

2018-05-01

The first months after becoming a new parent are a unique and important period in human development. Despite substantial research on the many social and biological changes that occur during the first months of parenthood, little is known about changes in mothers' attachment. The present study examines developmental stability and change in first-time mothers' attachment style across the first 2 years of motherhood. At Time 1, 162 economically stressed primiparous mothers (Mage = 23.98 years, SD = 5.18) completed measures of attachment anxiety and avoidance at five time points: when their children were 0, 6, 12, 18, and 24 months of age. Converging results of stability functions and latent growth curve models suggest that attachment styles were generally stable during the first 2 years of motherhood, even in this economically stressed sample. Furthermore, model comparisons revealed that a prototype model better characterized the developmental dynamics of mothers' attachment style than did a revisionist model, consistent with previous studies of adults and adolescents. This suggests that a relatively enduring prototype underlies mothers' attachment style and anchors the extent to which mothers experience attachment-related changes following the birth of their first child. Within this overall picture of continuity, however, some mothers did show change over time, and specific factors emerged as moderators of attachment stability, including maternal depressive symptoms and overall psychological distress, as well as sensitive care from their own mothers. Findings shed light on patterns of continuity and change in new parents' development. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Maternal warmth and toddler development: support for transactional models in disadvantaged families.

PubMed

Girard, Lisa-Christine; Doyle, Orla; Tremblay, Richard E

2017-04-01

Studies support cognitive and social domains of development as entwined in childhood, however, there is a paucity of investigation into the nature of the mother-child relationship within an interdependence framework. Furthermore, the focus on these processes within families from impoverished communities using frequent assessments in early childhood has been limited. Our objectives were to identify (1) the directional associations between toddler's communication ability and social competence, (2) to establish whether the association between toddler's communication ability and social competence is mediated by maternal warmth, and (3) to establish support for transactional models between toddlers' outcomes and maternal warmth in disadvantaged communities in Ireland. Participants included 173 toddlers and their families enrolled in a prenatally commencing prevention programme. Toddler's communication and social competence were assessed at 12, 18, 24 and 36 months and maternal warmth at 6 and 24 months. Cross-lagged models were estimated examining multiple paths of associations simultaneously. Direct and indirect paths of maternal warmth were also examined. Bi-directional associations were found between communication ability and social competence from 12 to 24 months but not thereafter. Maternal warmth did not significantly mediate these associations, however, support of a transactional model was found with social competence. The results support early positive associations between better communication ability and social competence in the first 2 years, however, they suggest that these associations are no longer present by the third year. The role of maternal warmth in fostering social competencies is important for toddlers and equally important is toddler's level of social competence in eliciting increased maternal warmth.

Houston, We Have a Problem Solving Model for Training

NASA Technical Reports Server (NTRS)

Schmidt, Lacey; Slack, Kelley; Keeton, Kathryn; Barshi, Immanuel; Martin, Lynne; Mauro, Robert; O'Keefe, William; Baldwin, Evelyn; Huning, Therese

2011-01-01

In late 2006, the Mission Operations Directorate (MOD) at NASA began looking at ways to make training more efficient for the flight controllers who support the International Space Station. The average certification times for flight controllers spanned from 18 months to three years and the MOD, responsible for technical training, was eager to develop creative solutions that would reduce the time to 12 months. Additionally, previously trained flight controllers sometimes participated in more than 50 very costly, eight-hour integrated simulations before becoming certified. New trainees needed to gain proficiency with far fewer lessons and training simulations than their predecessors. This poster presentation reviews the approach and the process that is currently in development to accomplish this goal.

Mouse Models for Assessing the Protective Efficacy of Lactobacillus gasseri SBT2055 against Helicobacter suis Infection Associated with the Development of Gastric Mucosa-Associated Lymphoid Tissue Lymphoma.

PubMed

Matsui, Hidenori; Takahashi, Tetsufumi; Øverby, Anders; Murayama, Somay Yamagata; Yoshida, Haruno; Yamamoto, Yuji; Nishiyama, Keita; Seto, Yasuyuki; Takahashi, Takashi; Mukai, Takao; Nakamura, Masahiko

2015-08-01

Helicobacter suis strain TKY infection has been strongly associated with the development of gastric mucosa-associated lymphoid tissue (MALT) lymphoma in a C57BL/6J mouse model. 1. C57BL/6J mice were intragastrically administered Lactobacillus strains once daily with 10(8)-10(9) colony-forming units (CFU), starting 2 days before intragastric infection with H. suis TKY (approximately 1 × 10(4) copies of 16S rRNA genes) or H. pylori Sydney strain 1 (SS1; 3 × 10(8) CFU) and continuing for 14 days after infection. 2. C57BL/6J mice were given powdered feed mixed with lyophilized L. gasseri SBT2055 (LG2055) cells (5 × 10(8) CFU/g), starting 2 weeks before intragastric infection with H. suis TKY and continuing 12 months after infection. 1. Among the 5 Lactobacillus strains that we examined, only LG2055 exhibited significantly preventive efficacy against both H. suis TKY and H. pylori SS1 at day 15 after infection. 2. Dietary supplementation with LG2055 protected mice from the formation of round protrusive lesions in the gastric fundus 12 months after infection with H. suis TKY, whereas such lesions had developed in the gastric fundus of nonsupplemented mice 12 months after infection. In addition, the formation of lymphoid follicles in gastric mucus layers was suppressed by dietary LG2055 at 3 months after infection. LG2055 administration is effective for suppressing the progression of gastric MALT lymphoma by reducing H. suis colonization. © 2015 John Wiley & Sons Ltd.

Deformation analysis of rotary combustion engine housings

NASA Technical Reports Server (NTRS)

Vilmann, Carl

1991-01-01

This analysis of the deformation of rotary combustion engine housings targeted the following objectives: (1) the development and verification of a finite element model of the trochoid housing, (2) the prediction of the stress and deformation fields present within the trochoid housing during operating conditions, and (3) the development of a specialized preprocessor which would shorten the time necessary for mesh generation of a trochoid housing's FEM model from roughly one month to approximately two man hours. Executable finite element models were developed for both the Mazda and the Outboard Marine Corporation trochoid housings. It was also demonstrated that a preprocessor which would hasten the generation of finite element models of a rotary engine was possible to develop. The above objectives are treated in detail in the attached appendices. The first deals with finite element modeling of a Wankel engine center housing, and the second with the development of a preprocessor that generates finite element models of rotary combustion engine center housings. A computer program, designed to generate finite element models of user defined rotary combustion engine center housing geometries, is also included.

Willingness-to-accept reductions in HIV risks: conditional economic incentives in Mexico.

PubMed

Galárraga, Omar; Sosa-Rubí, Sandra G; Infante, César; Gertler, Paul J; Bertozzi, Stefano M

2014-01-01

The objective of this study was to measure willingness-to-accept (WTA) reductions in risks for HIV and other sexually transmitted infections (STI) using conditional economic incentives (CEI) among men who have sex with men (MSM), including male sex workers (MSW) in Mexico City. A survey experiment was conducted with 1,745 MSM and MSW (18-25 years of age) who received incentive offers to decide first whether to accept monthly prevention talks and STI testing; and then a second set of offers to accept to stay free of STIs (verified by quarterly biological testing). The survey used random-starting-point and iterative offers. WTA was estimated with a maximum likelihood double-bounded dichotomous choice model. The average acceptance probabilities were: 73.9 % for the monthly model, and 80.4 % for the quarterly model. The incentive-elasticity of participation in the monthly model was 0.222, and 0.515 in the quarterly model. For a combination program with monthly prevention talks, and staying free of curable STI, the implied WTA was USD$ 288 per person per year, but it was lower for MSW: USD$ 156 per person per year. Thus, some of the populations at highest risk of HIV infection (MSM and MSW) seem well disposed to participate in a CEI program for HIV and STI prevention in Mexico. The average WTA estimate is within the range of feasible allocations for prevention in the local context. Given the potential impact, Mexico, a leader in conditional cash transfers for human development and poverty reduction, could extend that successful model to targeted HIV/STI prevention.

Modeling of phosphorus loads in sugarcane in a low-relief landscape using ontology-based simulation.

PubMed

Kwon, Ho-Young; Grunwald, Sabine; Beck, Howard W; Jung, Yunchul; Daroub, Samira H; Lang, Timothy A; Morgan, Kelly T

2010-01-01

Water flow and P dynamics in a low-relief landscape manipulated by extensive canal and ditch drainage systems were modeled utilizing an ontology-based simulation model. In the model, soil water flux and processes between three soil inorganic P pools (labile, active, and stable) and organic P are represented as database objects. And user-defined relationships among objects are used to automatically generate computer code (Java) for running the simulation of discharge and P loads. Our objectives were to develop ontology-based descriptions of soil P dynamics within sugarcane- (Saccharum officinarum L.) grown farm basins of the Everglades Agricultural Area (EAA) and to calibrate and validate such processes with water quality monitoring data collected at one farm basin (1244 ha). In the calibration phase (water year [WY] 99-00), observed discharge totaled 11,114 m3 ha(-1) and dissolved P 0.23 kg P ha(-1); and in the validation phase (WY 02-03), discharge was 10,397 m3 ha(-1) and dissolved P 0.11 kg P ha(-). During WY 99-00 the root mean square error (RMSE) for monthly discharge was 188 m3 ha(-1) and for monthly dissolved P 0.0077 kg P ha(-1); whereas during WY 02-03 the RMSE for monthly discharge was 195 m3 ha(-1) and monthly dissolved P 0.0022 kg P ha(-1). These results were confirmed by Nash-Sutcliffe Coefficient of 0.69 (calibration) and 0.81 (validation) comparing measured and simulated P loads. The good model performance suggests that our model has promise to simulate P dynamics, which may be useful as a management tool to reduce P loads in other similar low-relief areas.

Willingness-to-accept reductions in HIV risks: conditional economic incentives in Mexico

PubMed Central

Galárraga, Omar; Sosa-Rubí, Sandra G.; Infante, César; Gertler, Paul J.; Bertozzi, Stefano M.

2014-01-01

The objective of this study was to measure willingness-to-accept (WTA) reductions in risks for HIV and other sexually transmitted infections (STI) using conditional economic incentives (CEI) among men who have sex with men (MSM), including male sex workers (MSW) in Mexico City. A survey experiment was conducted with 1,745 MSM and MSW (18-25 years of age) who received incentive offers to decide first whether to accept monthly prevention talks and STI testing; and then a second set of offers to accept to stay free of STIs (verified by quarterly biological testing). The survey used random-starting-point and iterative offers. WTA was estimated with a maximum likelihood double-bounded dichotomous choice model. The average acceptance probabilities were: 73.9% for the monthly model, and 80.4% for the quarterly model. The incentive-elasticity of participation in the monthly model was 0.222, and it was 0.515 in the quarterly model. For a combination program with monthly prevention talks, and staying free of curable STI, the implied WTA was USD$288 per person per year, but it was lower for MSW: USD$156 per person per year. Thus, some of the populations at highest risk of HIV infection (MSM & MSW) seem well disposed to participate in a CEI program for HIV and STI prevention in Mexico. The average willingness-to-accept estimate is within the range of feasible allocations for prevention in the local context. Given the potential impact, Mexico, a leader in conditional cash transfers for human development and poverty reduction, could extend that successful model for targeted HIV/STI prevention. PMID:23377757

Long-term medical costs and life expectancy of acute myeloid leukemia: a probabilistic decision model.

PubMed

Wang, Han-I; Aas, Eline; Howell, Debra; Roman, Eve; Patmore, Russell; Jack, Andrew; Smith, Alexandra

2014-03-01

Acute myeloid leukemia (AML) can be diagnosed at any age and treatment, which can be given with supportive and/or curative intent, is considered expensive compared with that for other cancers. Despite this, no long-term predictive models have been developed for AML, mainly because of the complexities associated with this disease. The objective of the current study was to develop a model (based on a UK cohort) to predict cost and life expectancy at a population level. The model developed in this study combined a decision tree with several Markov models to reflect the complexity of the prognostic factors and treatments of AML. The model was simulated with a cycle length of 1 month for a time period of 5 years and further simulated until age 100 years or death. Results were compared for two age groups and five different initial treatment intents and responses. Transition probabilities, life expectancies, and costs were derived from a UK population-based specialist registry-the Haematological Malignancy Research Network (www.hmrn.org). Overall, expected 5-year medical costs and life expectancy ranged from £8,170 to £81,636 and 3.03 to 34.74 months, respectively. The economic and health outcomes varied with initial treatment intent, age at diagnosis, trial participation, and study time horizon. The model was validated by using face, internal, and external validation methods. The results show that the model captured more than 90% of the empirical costs, and it demonstrated good fit with the empirical overall survival. Costs and life expectancy of AML varied with patient characteristics and initial treatment intent. The robust AML model developed in this study could be used to evaluate new diagnostic tools/treatments, as well as enable policy makers to make informed decisions. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

The timing of maternal depressive symptoms and mothers' parenting practices with young children: implications for pediatric practice.

PubMed

McLearn, Kathryn Taaffe; Minkovitz, Cynthia S; Strobino, Donna M; Marks, Elisabeth; Hou, William

2006-07-01

The prevalence of maternal depressive symptoms and its associated consequences on parental behaviors, child health, and development are well documented. Researchers have called for additional work to investigate the effects of the timing of maternal depressive symptoms at various stages in the development of the young child on the emergence of developmentally appropriate parenting practices. For clinicians, data are limited about when or how often to screen for maternal depressive symptoms or how to target anticipatory guidance to address parental needs. We sought to determine whether concurrent maternal depressive symptoms have a greater effect than earlier depressive symptoms on the emergence of maternal parenting practices at 30 to 33 months in 3 important domains of child safety, development, and discipline. Secondary analyses from the Healthy Steps National Evaluation were conducted for this study. Data sources included a self-administered enrollment questionnaire and computer-assisted telephone interviews with the mother when the Healthy Steps children were 2 to 4 and 30 to 33 months of age. The 30- to 33-month interview provided information about 4 safety practices (ie, always uses car seat, has electric outlet covers, has safety latches on cabinets, and lowered temperature on the water heater), 6 child development practices (ie, talks daily to child while working, plays daily with child, reads daily to child, limits child television and video watching to <2 hours a day, follows > or = 3 daily routines, and being more nurturing), and 3 discipline practices (ie, uses more reasoning, uses more harsh punishment, and ever slapped child on the face or spanked the child with an object). The parenting practices were selected based on evidence of their importance for child health and development, near complete data, and sample variability. The discipline practices were constructed from the Parental Response to Misbehavior Scale. Maternal depressive symptoms were assessed using a 14-item modified version of the Center for Epidemiologic Studies-Depression Scale. Multiple logistic regression models estimated the effect of depressive symptoms on parenting practices, adjusted for baseline demographic characteristics, Healthy Steps participation, and site. No significant interactions were found when testing analytic models with dummy variables for depressive symptoms at 2 to 4 months only, 30 to 33 months only, and at both times; reported models do not include interaction terms. We report main effects of depressive symptoms at 2 to 4 and 30 to 33 months when both are included in the model. Of 5565 families, 3412 mothers (61%) completed 2- to 4- and 30- to 33-month interviews and provided Center for Epidemiologic Studies-Depression Scale data at both times. Mothers with depressive symptoms at 2 to 4 months had reduced odds of using car seats, lowering the water heater temperature, and playing with the child at 30 to 33 months. Mothers with concurrent depressive symptoms had reduced odds of using electric outlet covers, using safety latches, talking with the child, limiting television or video watching, following daily routines, and being more nurturing. Mothers with concurrent depressive symptoms had increased odds of using harsh punishment and of slapping the child on the face or spanking with an object. The study findings suggest that concurrent maternal depressive symptoms have stronger relations than earlier depressive symptoms, with mothers not initiating recommended age-appropriate safety and child development practices and also using harsh discipline practices for toddlers. Our findings, however, also suggest that for parenting practices that are likely to be established early in the life of the child, it may be reasonable that mothers with early depressive symptoms may continue to affect use of those practices by mothers. The results of our study underscore the importance of clinicians screening for maternal depressive symptoms during the toddler period, as well as the early postpartum period, because these symptoms can appear later independent of earlier screening results. Providing periodic depressive symptom screening of the mothers of young patients has the potential to improve clinician capacity to provide timely and tailored anticipatory guidance about important parenting practices, as well as to make appropriate referrals.

A computationally efficient modelling of laminar separation bubbles

NASA Technical Reports Server (NTRS)

Dini, Paolo; Maughmer, Mark D.

1989-01-01

The goal is to accurately predict the characteristics of the laminar separation bubble and its effects on airfoil performance. Toward this end, a computational model of the separation bubble was developed and incorporated into the Eppler and Somers airfoil design and analysis program. Thus far, the focus of the research was limited to the development of a model which can accurately predict situations in which the interaction between the bubble and the inviscid velocity distribution is weak, the so-called short bubble. A summary of the research performed in the past nine months is presented. The bubble model in its present form is then described. Lastly, the performance of this model in predicting bubble characteristics is shown for a few cases.

A multi-state model examining patterns of transitioning among states of engagement in care in HIV-positive individuals initiating combination antiretroviral therapy

PubMed Central

Gillis, Jennifer; Loutfy, Mona; Bayoumi, Ahmed M; Antoniou, Tony; Burchell, Ann N; Walmsley, Sharon; Cooper, Curtis; Klein, Marina B.; Machouf, Nima; Montaner, Julio SG; Rourke, Sean B.; Tsoukas, Christos; Hogg, Robert; Raboud, Janet

2016-01-01

Background Common measures of engagement in care fail to acknowledge that infrequent follow-up may occur either intentionally among patients with sustained virologic suppression or unintentionally among patients with poor clinical outcomes. Methods Five states of HIV care were defined within the Canadian Observational Cohort (CANOC) Collaboration following combination antiretroviral therapy (cART) initiation: (1) guidelines HIV care (suppressed viral load (VL) and CD4 >200 cells/mm3, no gaps in cART >3 months, no gaps in CD4 or VL measurement >6 months), (2) successful care with decreased frequency of follow-up (as above except no gaps in CD4 or VL measurement >12 months), (3) suboptimal care (unsuppressed VL, CD4<200 cells/mm3 on 2 consecutive visits, ≥1 gap in cART >3 months, or ≥1 gap in CD4 or VL measurement >12 months), (4) loss to follow-up (no contact for 18 months), and (5) death. Multi-state models were used to determine factors associated with transitioning among states. Results 7810 participants were included. Younger age, female gender, Indigenous ethnicity and people who have injected drugs (PWID) were associated with increased likelihoods of transitioning from guidelines to suboptimal care and decreased likelihoods of transitioning from suboptimal to guidelines care. One-fifth of individuals in successful, decreased follow-up after cART initiation (mean sojourn time 0.72 years) were in suboptimal care in subsequent years. Conclusions Using routinely collected data, we have developed a flexible framework that characterizes patient transitions among states of HIV clinical care. We have demonstrated that multi-state models provide a useful approach to supplement ‘cascade of care’ work. PMID:27851713

Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes: Lessons From the COMPANION Trial.

PubMed

Kalscheur, Matthew M; Kipp, Ryan T; Tattersall, Matthew C; Mei, Chaoqun; Buhr, Kevin A; DeMets, David L; Field, Michael E; Eckhardt, Lee L; Page, C David

2018-01-01

Cardiac resynchronization therapy (CRT) reduces morbidity and mortality in heart failure patients with reduced left ventricular function and intraventricular conduction delay. However, individual outcomes vary significantly. This study sought to use a machine learning algorithm to develop a model to predict outcomes after CRT. Models were developed with machine learning algorithms to predict all-cause mortality or heart failure hospitalization at 12 months post-CRT in the COMPANION trial (Comparison of Medical Therapy, Pacing, and Defibrillation in Heart Failure). The best performing model was developed with the random forest algorithm. The ability of this model to predict all-cause mortality or heart failure hospitalization and all-cause mortality alone was compared with discrimination obtained using a combination of bundle branch block morphology and QRS duration. In the 595 patients with CRT-defibrillator in the COMPANION trial, 105 deaths occurred (median follow-up, 15.7 months). The survival difference across subgroups differentiated by bundle branch block morphology and QRS duration did not reach significance ( P =0.08). The random forest model produced quartiles of patients with an 8-fold difference in survival between those with the highest and lowest predicted probability for events (hazard ratio, 7.96; P <0.0001). The model also discriminated the risk of the composite end point of all-cause mortality or heart failure hospitalization better than subgroups based on bundle branch block morphology and QRS duration. In the COMPANION trial, a machine learning algorithm produced a model that predicted clinical outcomes after CRT. Applied before device implant, this model may better differentiate outcomes over current clinical discriminators and improve shared decision-making with patients. © 2018 American Heart Association, Inc.

Efficacy of a Systematic Process for Developing Function-Based Treatment for Young Children with Disabilities

ERIC Educational Resources Information Center

Aldosari, Mubarak S.

2016-01-01

This study conducted an in-depth analysis of the efficacy of the Decision Model in the development of function-based treatments for disruptive behaviors in four toddlers with disabilities aged from 26 to 34 months in inclusive toddler classrooms. The research was conducted in three parts. In Part 1, a functional behavioral assessment was conducted…

Design of a Model Management Information System (MIS) for California's Regional Occupational Centers and Programs. Final Report.

ERIC Educational Resources Information Center

Dick, James C.; And Others

The management information system (MIS) development project for California's Regional Occupational Centers and Programs (ROC/Ps) was conducted in 3 phases over a 12-month period. Phase I involved a literature review and field study to match MIS design features and development strategy with existing conditions in ROC/Ps. A decision support system…

The Development of Referential Communication and Autism Symptomatology in High-Risk Infants

PubMed Central

Ibañez, Lisa V.; Grantz, Caroline J.; Messinger, Daniel S.

2013-01-01

Non-verbal referential communication is impaired in children with Autism Spectrum Disorders (ASD). However, the development of difficulties with referential communication in the younger siblings of children with ASD (High-Risk Siblings)—and the degree to which early referential communication predicts later autism symptomatology—is not clear. We modeled the early developmental trajectories of three types of referential communication: responding to joint attention (RJA), initiating joint attention (IJA), and initiating behavioral requests (IBR) across 8, 10, 12, 15, and18 months of age in High-Risk Siblings (n = 40) and the infant siblings of children without ASD (Low-Risk Siblings; n = 21). Hierarchical Linear Modeling indicated that High-Risk Siblings exhibited lower levels of baseline RJA and IJA and a lower rate of linear change in IBR than Low-Risk Siblings. When the 10 High-Risk Siblings who received an ASD diagnosis were excluded from analyses, group differences in the development of referential communication remained significant only for RJA. Baseline levels of IJA were associated with later ASD symptomatology among High-Risk Siblings, suggesting that individual differences in referential communication development at 8 months may index early manifestations of ASD. PMID:24403864

Effect of year-to-year variability of leaf area index on variable infiltration capacity model performance and simulation of streamflow during drought

NASA Astrophysics Data System (ADS)

Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

2014-09-01

This study assessed the effect of using observed monthly leaf area index (LAI) on hydrologic model performance and the simulation of streamflow during drought using the variable infiltration capacity (VIC) hydrological model in the Goulburn-Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) observed monthly LAI dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash-Sutcliffe efficiency, the logarithm transformed flow Nash-Sutcliffe efficiency and the percentage bias. Finally, the percentage deviation of the simulated monthly streamflow using the observed monthly LAI from simulated streamflow using long-term mean monthly LAI was computed. The VIC model predicted monthly streamflow in the selected sub-catchments with model efficiencies ranging from 61.5 to 95.9% during calibration (1982-1997) and 59 to 92.4% during validation (1998-2012). Our results suggest systematic improvements from 4 to 25% in the Nash-Sutcliffe efficiency in pasture dominated catchments when the VIC model was calibrated with the observed monthly LAI instead of the long-term mean monthly LAI. There was limited systematic improvement in tree dominated catchments. The results also suggest that the model overestimation or underestimation of streamflow during wet and dry periods can be reduced to some extent by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

Maternal Consumption of Hesperidin and Naringin Flavanones Exerts Transient Effects to Tibia Bone Structure in Female CD-1 Offspring

PubMed Central

Sacco, Sandra M.; Saint, Caitlin; LeBlanc, Paul J.; Ward, Wendy E.

2017-01-01

Hesperidin (HSP) and naringin (NAR), flavanones rich in citrus fruits, support skeletal integrity in adult and aging rodent models. This study determined whether maternal consumption of HSP and NAR favorably programs bone development, resulting in higher bone mineral density (BMD) and greater structure and biomechanical strength (i.e., peak load) in female offspring. Female CD-1 mice were fed a control diet or a HSP + NAR diet five weeks before pregnancy and throughout pregnancy and lactation. At weaning, female offspring were fed a control diet until six months of age. The structure and BMD of the proximal tibia were measured longitudinally using in vivo micro-computed tomography at 2, 4, and 6 months of age. The trabecular bone structure at two and four months and the trabecular BMD at four months were compromised at the proximal tibia in mice exposed to HSP and NAR compared to the control diet (p < 0.001). At six months of age, these differences in trabecular structure and BMD at the proximal tibia had disappeared. At 6 months of age, the tibia midpoint peak load, BMD, structure, and the peak load of lumbar vertebrae and femurs were similar (p > 0.05) between the HSP + NAR and control groups. In conclusion, maternal consumption of HSP and NAR does not enhance bone development in female CD-1 offspring. PMID:28282882

Building a Better Model: A Personalized Breast Cancer Risk Model Incorporating Breast Density to Stratify Risk and Improve Application of Resources

DTIC Science & Technology

2015-12-01

conducted a second round of focus groups in early 2013, designed as group self-administered pre- tests followed by a group debriefing. The first...procedures for team communication and coordination (month 1) Completed. A listserve was developed for the group early on . Bi-weekly conference calls were... group has developed an automated 2D method. Figure 7 shows the automated 2D (area) results on the same dataset presented in Task 4 (figures 1 and 2). The

Building a Better Model: A Personalized Breast Cancer Risk Model Incorporating Breast Density to Stratify Risk and Improve Application of Resources

DTIC Science & Technology

2015-12-01

designed as group self-administered pre- tests followed by a group debriefing. The first group was conducted in Charlottesville, Virginia, and the second...coordination (month 1) Completed. A listserve was developed for the group early on . Bi-weekly conference calls were held on Tuesdays at noon. An agenda...Yaffe’s group has developed an automated 2D method. Figure 7 shows the automated 2D (area) results on the same dataset presented in Task 4 (figures 1

Gene Therapy for the Treatment of Neurological Disorders: Central Nervous System Neoplasms

PubMed Central

Kamran, Neha; Candolfi, Marianela; Baker, Gregory J.; Ayala, Mariela Moreno; Dzaman, Marta; Lowenstein, Pedro R.; Castro, Maria G.

2015-01-01

Summary Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults with a median survival of 16.2 to 21.2 months post diagnosis [1]. Because of its location, complete surgical resection is impossible; additionally because GBM is also resistant to chemotherapeutic and radiotherapy approaches, development of novel therapies is urgently needed. In this chapter we describe the development of preclinical animal models and a conditionally cytotoxic and immune-stimulatory gene therapy strategy that successfully causes tumor regression in several rodent GBM models. PMID:26611605

Mathematics teacher professional development in and through internet use: reflections on an ethnographic study

NASA Astrophysics Data System (ADS)

Patahuddin, Sitti Maesuri

2013-12-01

This paper is a reflection on a model for mathematics teacher professional development with respect to technology. The model was informed by three interrelated concepts: (1) a theory of teacher professional development from analysis of the field, (2) the zone theory of teacher professional learning, and (3) ethnography as a method. The model was applied in a study that focused on the uses of the Internet for primary mathematics teacher professional development, particularly to exploit the potential of the Internet for professional learning and to use it in professional work. This is illustrated through selected critical events over an eight-month ethnographic intervention in a primary mathematics classroom in Australia. Though the model is theoretically grounded, it opens up questions about the power, potential, and challenges as well as its feasibility, with respect to not only the teacher but also the ethnographer.

Spatial and seasonal dynamics of surface soil carbon in the Luquillo Experimental Forest, Puerto Rico.

Treesearch

Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley

2002-01-01

We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0–30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...

Use of the Box and Jenkins time series technique in traffic forecasting

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

Nihan, N.L.; Holmesland, K.O.

The use of recently developed time series techniques for short-term traffic volume forecasting is examined. A data set containing monthly volumes on a freeway segment for 1968-76 is used to fit a time series model. The resultant model is used to forecast volumes for 1977. The forecast volumes are then compared with actual volumes in 1977. Time series techniques can be used to develop highly accurate and inexpensive short-term forecasts. The feasibility of using these models to evaluate the effects of policy changes or other outside impacts is considered. (1 diagram, 1 map, 14 references,2 tables)

Impacts of Participatory Modeling on Climate Change-related Water Management Impacts in Sonora, Mexico

NASA Astrophysics Data System (ADS)

Halvorsen, K. E.; Kossak, D. J.; Mayer, A. S.; Vivoni, E. R.; Robles-Morua, A.; Gamez Molina, V.; Dana, K.; Mirchi, A.

2013-12-01

Climate change-related impacts on water resources are expected to be particularly severe in the arid developing world. As a result, we conducted a series of participatory modeling workshops on hydrologic and water resources systems modeling in the face of climate change in Sonora, Mexico. Pre-surveys were administered to participants on Day 1 of a series of four workshops spaced out over three months in 2013. Post-surveys repeated many pre-survey questions and included questions assessing the quality of the workshops and models. We report on significant changes in participant perceptions of water resource models and problems and their assessment of the workshops. These findings will be of great value to future participatory modeling efforts, particularly within the developing world.

Impact of predictive model-directed end-of-life counseling for Medicare beneficiaries.

PubMed

Hamlet, Karen S; Hobgood, Adam; Hamar, Guy Brent; Dobbs, Angela C; Rula, Elizabeth Y; Pope, James E

2010-05-01

To validate a predictive model for identifying Medicare beneficiaries who need end-of-life care planning and to determine the impact on cost and hospice care of a telephonic counseling program utilizing this predictive model in 2 Medicare Health Support (MHS) pilots. Secondary analysis of data from 2 MHS pilot programs that used a randomized controlled design. A predictive model was developed using intervention group data (N = 43,497) to identify individuals at greatest risk of death. Model output guided delivery of a telephonic intervention designed to support educated end-of-life decisions and improve end-of-life provisions. Control group participants received usual care. As a primary outcome, Medicare costs in the last 6 months of life were compared between intervention group decedents (n = 3112) and control group decedents (n = 1630). Hospice admission rates and duration of hospice care were compared as secondary measures. The predictive model was highly accurate, and more than 80% of intervention group decedents were contacted during the 12 months before death. Average Medicare costs were $1913 lower for intervention group decedents compared with control group decedents in the last 6 months of life (P = .05), for a total savings of $5.95 million. There were no significant changes in hospice admissions or mean duration of hospice care. Telephonic end-of-life counseling provided as an ancillary Medicare service, guided by a predictive model, can reach a majority of individuals needing support and can reduce costs by facilitating voluntary election of less intensive care.

Mathematical Modeling for Scrub Typhus and Its Implications for Disease Control.

PubMed

Min, Kyung Duk; Cho, Sung Il

2018-03-19

The incidence rate of scrub typhus has been increasing in the Republic of Korea. Previous studies have suggested that this trend may have resulted from the effects of climate change on the transmission dynamics among vectors and hosts, but a clear explanation of the process is still lacking. In this study, we applied mathematical models to explore the potential factors that influence the epidemiology of tsutsugamushi disease. We developed mathematical models of ordinary differential equations including human, rodent and mite groups. Two models, including simple and complex models, were developed, and all parameters employed in the models were adopted from previous articles that represent epidemiological situations in the Republic of Korea. The simulation results showed that the force of infection at the equilibrium state under the simple model was 0.236 (per 100,000 person-months), and that in the complex model was 26.796 (per 100,000 person-months). Sensitivity analyses indicated that the most influential parameters were rodent and mite populations and contact rate between them for the simple model, and trans-ovarian transmission for the complex model. In both models, contact rate between humans and mites is more influential than morality rate of rodent and mite group. The results indicate that the effect of controlling either rodents or mites could be limited, and reducing the contact rate between humans and mites is more practical and effective strategy. However, the current level of control would be insufficient relative to the growing mite population. © 2018 The Korean Academy of Medical Sciences.

Association between prenatal exposure to poliovirus infection and adult schizophrenia.

PubMed

Suvisaari, J; Haukka, J; Tanskanen, A; Hovi, T; Lönnqvist, J

1999-07-01

The authors' goal was to determine whether there is an association between prenatal exposure to poliovirus infection and later development of schizophrenia. All Finnish patients born between 1951 and 1969 with discharge diagnoses of schizophrenia (N = 13,559) were identified from the Finnish Hospital Discharge Register. Information on the monthly number of cases of paralytic poliomyelitis was obtained for each province in Finland. The authors analyzed the incidence of births of individuals who later developed schizophrenia by using a Poisson regression model with year and place of birth, age, sex, season of birth, and smoothed incidence of poliomyelitis in different gestational periods as explanatory variables. An association between the incidence of poliomyelitis and the incidence of births 5 months later of individuals who later developed schizophrenia was observed. Without controlling for seasonality, the effect was significant throughout the second trimester. Second-trimester exposure to poliovirus infection may increase the risk for the later development of schizophrenia.

The broader autism phenotype in infancy: when does it emerge?

PubMed

Ozonoff, Sally; Young, Gregory S; Belding, Ashleigh; Hill, Monique; Hill, Alesha; Hutman, Ted; Johnson, Scott; Miller, Meghan; Rogers, Sally J; Schwichtenberg, A J; Steinfeld, Marybeth; Iosif, Ana-Maria

2014-04-01

This study had 3 goals, which were to examine the following: the frequency of atypical development, consistent with the broader autism phenotype, in high-risk infant siblings of children with autism spectrum disorder (ASD); the age at which atypical development is first evident; and which developmental domains are affected. A prospective longitudinal design was used to compare 294 high-risk infants and 116 low-risk infants. Participants were tested at 6, 12, 18, 24, and 36 months of age. At the final visit, outcome was classified as ASD, Typical Development (TD), or Non-TD (defined as elevated Autism Diagnostic Observation Schedule [ADOS] score, low Mullen Scale scores, or both). Of the high-risk group, 28% were classified as Non-TD at 36 months of age. Growth curve models demonstrated that the Non-TD group could not be distinguished from the other groups at 6 months of age, but differed significantly from the Low-Risk TD group by 12 months on multiple measures. The Non-TD group demonstrated atypical development in cognitive, motor, language, and social domains, with differences particularly prominent in the social-communication domain. These results demonstrate that features of atypical development, consistent with the broader autism phenotype, are detectable by the first birthday and affect development in multiple domains. This highlights the necessity for close developmental surveillance of infant siblings of children with ASD, along with implementation of appropriate interventions as needed. Copyright © 2014 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Memory and representation in young children with Down syndrome: Exploring deferred imitation and object permanence.

PubMed

Rast, Mechthild; Meltzoff, Andrew N

1995-01-01

Deferred imitation and object permanence (OP) were tested in 48 young children with Down syndrome (DS), ranging from 20 to 43 months of age. Deferred imitation and high-level OP (invisible displacements) have long been held to be synchronous developments during sensory-motor "Stage 6" (18-24 months of age in unimpaired children). The results of the current study demonstrate deferred imitation in young children with DS, showing they can learn novel behaviors from observation and retain multiple models in memory. This is the first demonstration of deferred imitation in young children with DS. The average OP level passed in this sample was A-not-B, a task passed at 8-12 months of age in normally developing infants. Analyses showed that individual children who failed high-level OP (invisible displacements) could still perform deferred imitation. This indicates that deferred imitation and OP invisible displacements are not synchronous developments in children with DS. This asynchrony is compatible with new data from unimpaired children suggesting that deferred imitation and high-level OP entail separate and distinctive kinds of memory and representation.

Newcomer nurses' organisational socialisation and turnover intention during the first 2 years of employment.

PubMed

Tomietto, Marco; Rappagliosi, Cristina M; Sartori, Riccardo; Battistelli, Adalgisa

2015-10-01

The aim of this study was to determine which organisational socialisation contents affect turnover intention in newcomer nurses within their first 2 years of employment. Strategies to decrease turnover are a priority for improving organisational stability, reducing costs and enhancing effective nursing care. A cross-sectional design was employed, and standardised scales were used. The sample was divided into three groups: 0-6, 7-12 and 13-24 months of employment. Regression analyses were performed. A total of 156 Italian nurses participated in this study. In the 0-6 months group (model 1), the main factors that decreased turnover intention were competence acquisition (β = -0.42, P < 0.01) and comprehension of organisational rules (β = -0.38, P < 0.01). In the 7-12 months group (model 2), workgroup integration was relevant (β = -0.33, P = 0.02) and in the second year (model 3), the main factor was opportunities for professional development (β = -0.30, P = 0.05). Newcomer nurses were sensitive to different organisational socialisation contents over time. This result supports planning different on-boarding strategies to enhance organisational socialisation success and to improve nurse retention. Useful strategies to improve retention include enhancing task mastery and workgroup integration at the ward level and a professional development plan at the organisational level. © 2014 John Wiley & Sons Ltd.

Creation of a Prognostic Index for Spine Metastasis to Stratify Survival in Patients Treated With Spinal Stereotactic Radiosurgery: Secondary Analysis of Mature Prospective Trials

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

Tang, Chad; Hess, Kenneth; Bishop, Andrew J.

Purpose: There exists uncertainty in the prognosis of patients following spinal metastasis treatment. We sought to create a scoring system that stratifies patients based on overall survival. Methods and Materials: Patients enrolled in 2 prospective trials investigating stereotactic spine radiation surgery (SSRS) for spinal metastasis with ≥3-year follow-up were analyzed. A multivariate Cox regression model was used to create a survival model. Pretreatment variables included were race, sex, age, performance status, tumor histology, extent of vertebrae involvement, previous therapy at the SSRS site, disease burden, and timing of diagnosis and metastasis. Four survival groups were generated based on the model-derivedmore » survival score. Results: Median follow-up in the 206 patients included in this analysis was 70 months (range: 37-133 months). Seven variables were selected: female sex (hazard ratio [HR] = 0.7, P=.02), Karnofsky performance score (HR = 0.8 per 10-point increase above 60, P=.007), previous surgery at the SSRS site (HR = 0.7, P=.02), previous radiation at the SSRS site (HR = 1.8, P=.001), the SSRS site as the only site of metastatic disease (HR = 0.5, P=.01), number of organ systems involved outside of bone (HR = 1.4 per involved system, P<.001), and >5 year interval from initial diagnosis to detection of spine metastasis (HR = 0.5, P<.001). The median survival among all patients was 25.5 months and was significantly different among survival groups (in group 1 [excellent prognosis], median survival was not reached; group 2 reached 32.4 months; group 3 reached 22.2 months; and group 4 [poor prognosis] reached 9.1 months; P<.001). Pretreatment symptom burden was significantly higher in the patient group with poor survival than in the group with excellent survival (all metrics, P<.05). Conclusions: We developed the prognostic index for spinal metastases (PRISM) model, a new model that identified patient subgroups with poor and excellent prognoses.« less

Assessment of an ensemble seasonal streamflow forecasting system for Australia

NASA Astrophysics Data System (ADS)

Bennett, James C.; Wang, Quan J.; Robertson, David E.; Schepen, Andrew; Li, Ming; Michael, Kelvin

2017-11-01

Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean-land-atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall-runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( < 4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall-runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall-runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does not remedy poor reliability in very dry catchments. Overall, FoGSS is an attractive alternative to historical inflow sequences in all but the driest catchments. We discuss ways in which forecast reliability in very dry catchments could be improved in future work.

Hospitalization and development of dependence in activities of daily living in a cohort of disabled older women: the Women's Health and Aging Study I.

PubMed

Boyd, Cynthia M; Xue, Qian-Li; Guralnik, Jack M; Fried, Linda P

2005-07-01

Changes in self-reported function in older adults are known to occur in the 2 weeks prior to, during, and in the first few months after hospitalization. The long-term outcome of hospitalization on functional status in disabled older adults is not known. The objective of this study was to determine whether hospitalization predicts long-term Activities of Daily Living (ADL) dependence in previously ADL independent, although disabled, older women. The Women's Health and Aging Study I is a population-based, prospective cohort study of disabled, community-dwelling women > or =65 years old. We evaluated participants who were independent in ADLs at baseline and excluded women with incident stroke, lower extremity joint surgery, amputation, or hip fracture. We examined the association between self-reported incident hospitalization at three consecutive 6-month intervals and incident dependence in at least one ADL at 18 months (n = 595). Of 595 women evaluated, 32% had at least one hospitalization. Women who were hospitalized were more likely to become dependent in ADLs than were women who were not hospitalized (17% vs 8%, p =.001). In a multivariate model, hospitalization was independently predictive of development of ADL dependence that persisted at 18 months after baseline (odds ratio [OR], 3.2; 95% confidence interval [CI], 1.7-5.8), adjusting for age, race, education, baseline walking speed, difficulty with ADLs, self-reported health status, depressive symptoms, cognitive status, and presence of congestive heart failure, diabetes, or pulmonary disease. Increasing numbers of 6-month intervals with hospitalizations were independently predictive of higher risk in an adjusted model: one (OR, 2.3; 95% CI, 1.1-4.6), two (OR, 5.8; 95% CI, 2.4-14.4), and three (OR, 12.5; 95% CI, 2.7-57.6). These results suggest that hospitalization has an independent and dose-response effect on loss of ADL independence in disabled older women over an 18-month period.

On the Origins of Disorganized Attachment and Internal Working Models: Paper II. An Empirical Microanalysis of 4-Month Mother-Infant Interaction

PubMed Central

Beebe, Beatrice; Lachmann, Frank; Markese, Sara; Buck, Karen A.; Bahrick, Lorraine E.; Chen, Henian; Cohen, Patricia; Andrews, Howard; Feldstein, Stanley; Jaffe, Joseph

2012-01-01

A microanalysis of 4-month mother-infant face-to-face communication predicted 12-month infant disorganized (vs. secure) attachment outcomes in an urban community sample. We documented a dyadic systems view of the roles of both partners, the roles of both self- and interactive contingency, and the importance of attention, orientation and touch, and as well as facial and vocal affect, in the co-construction of attachment disorganization. The analysis of different communication modalities identified striking intrapersonal and interpersonal intermodal discordance or conflict, in the context of intensely distressed infants, as the central feature of future disorganized dyads at 4 months. Lowered maternal contingent coordination, and failures of maternal affective correspondence, constituted maternal emotional withdrawal from distressed infants. This maternal withdrawal compromises infant interactive agency and emotional coherence. We characterize of the nature of emerging internal working models of future disorganized infants as follows: Future disorganized infants represent states of not being sensed and known by their mothers, particularly in moments of distress; they represent confusion about both their own and their mothers’ basic emotional organization, and about their mothers’ response to their distress. This internal working model sets a trajectory in development which may disturb the fundamental integration of the person. The remarkable specificity of our findings has the potential to lead to more finely-focused clinical interventions. PMID:23066334

Drought forecasting in Luanhe River basin involving climatic indices

NASA Astrophysics Data System (ADS)

Ren, Weinan; Wang, Yixuan; Li, Jianzhu; Feng, Ping; Smith, Ronald J.

2017-11-01

Drought is regarded as one of the most severe natural disasters globally. This is especially the case in Tianjin City, Northern China, where drought can affect economic development and people's livelihoods. Drought forecasting, the basis of drought management, is an important mitigation strategy. In this paper, we evolve a probabilistic forecasting model, which forecasts transition probabilities from a current Standardized Precipitation Index (SPI) value to a future SPI class, based on conditional distribution of multivariate normal distribution to involve two large-scale climatic indices at the same time, and apply the forecasting model to 26 rain gauges in the Luanhe River basin in North China. The establishment of the model and the derivation of the SPI are based on the hypothesis of aggregated monthly precipitation that is normally distributed. Pearson correlation and Shapiro-Wilk normality tests are used to select appropriate SPI time scale and large-scale climatic indices. Findings indicated that longer-term aggregated monthly precipitation, in general, was more likely to be considered normally distributed and forecasting models should be applied to each gauge, respectively, rather than to the whole basin. Taking Liying Gauge as an example, we illustrate the impact of the SPI time scale and lead time on transition probabilities. Then, the controlled climatic indices of every gauge are selected by Pearson correlation test and the multivariate normality of SPI, corresponding climatic indices for current month and SPI 1, 2, and 3 months later are demonstrated using Shapiro-Wilk normality test. Subsequently, we illustrate the impact of large-scale oceanic-atmospheric circulation patterns on transition probabilities. Finally, we use a score method to evaluate and compare the performance of the three forecasting models and compare them with two traditional models which forecast transition probabilities from a current to a future SPI class. The results show that the three proposed models outperform the two traditional models and involving large-scale climatic indices can improve the forecasting accuracy.

Developing teachers' models for assessing students' competence in mathematical modelling through lesson study

NASA Astrophysics Data System (ADS)

Aydogan Yenmez, Arzu; Erbas, Ayhan Kursat; Cakiroglu, Erdinc; Alacaci, Cengiz; Cetinkaya, Bulent

2017-08-01

Applications and modelling have gained a prominent role in mathematics education reform documents and curricula. Thus, there is a growing need for studies focusing on the effective use of mathematical modelling in classrooms. Assessment is an integral part of using modelling activities in classrooms, since it allows teachers to identify and manage problems that arise in various stages of the modelling process. However, teachers' difficulties in assessing student modelling work are a challenge to be considered when implementing modelling in the classroom. Thus, the purpose of this study was to investigate how teachers' knowledge on generating assessment criteria for assessing student competence in mathematical modelling evolved through a professional development programme, which is based on a lesson study approach and modelling perspective. The data was collected with four teachers from two public high schools over a five-month period. The professional development programme included a cyclical process, with each cycle consisting of an introductory meeting, the implementation of a model-eliciting activity with students, and a follow-up meeting. The results showed that the professional development programme contributed to teachers' knowledge for generating assessment criteria on the products, and the observable actions that affect the modelling cycle.