Development of reference equations for spirometry in Japanese children aged 6-18 years.

PubMed

Takase, Masato; Sakata, Hiroshi; Shikada, Masahiro; Tatara, Katsuyoshi; Fukushima, Takayoshi; Miyakawa, Tomoo

2013-01-01

Spirometry is the most widely used pulmonary function test and the measured values of spirometric parameters need to be evaluated using reference values predicted for the corresponding race, sex, age, and height. However, none of the existing reference equations for Japanese children covers the entire age range of 6-18 years. The Japanese Society of Pediatric Pulmonology had organized a working group in 2006, in order to develop a new set of national standard reference equations for commonly used spirometric parameters that are applicable through the age range of 6-18 years. Quality assured spirometric data were collected through 2006-2008, from 14 institutions in Japan. We applied multiple regression analysis, using age in years (A), square of age (A(2)), height in meters (H), square of height (H(2)), and the product of age and height (AH) as explanatory variables to predict forced vital capacity (FVC), forced expiratory volume in 1 sec (FEV(1)), peak expiratory flow (PEF), forced expiratory flow between 25% and 75% of the FVC (FEF(25-75%)), instantaneous forced expiratory flow when 50% (FEF(50%)) or 75% (FEF(75%)) of the FVC have been expired. Finally, 1,296 tests (674 boys, 622 girls) formed the reference data set. Distributions of the percent predicted values did not differ by ages, confirming excellent fit of the prediction equations throughout the entire age range from 6 to 18 years. Cut-off values (around 5 percentile points) for the parameters were also determined. We recommend the use of this new set of prediction equations together with suggested cut-off values, for assessment of spirometry in Japanese children and adolescents. Copyright © 2012 Wiley Periodicals, Inc.

Accuracy of Predicted Genomic Breeding Values in Purebred and Crossbred Pigs.

PubMed

Hidalgo, André M; Bastiaansen, John W M; Lopes, Marcos S; Harlizius, Barbara; Groenen, Martien A M; de Koning, Dirk-Jan

2015-05-26

Genomic selection has been widely implemented in dairy cattle breeding when the aim is to improve performance of purebred animals. In pigs, however, the final product is a crossbred animal. This may affect the efficiency of methods that are currently implemented for dairy cattle. Therefore, the objective of this study was to determine the accuracy of predicted breeding values in crossbred pigs using purebred genomic and phenotypic data. A second objective was to compare the predictive ability of SNPs when training is done in either single or multiple populations for four traits: age at first insemination (AFI); total number of piglets born (TNB); litter birth weight (LBW); and litter variation (LVR). We performed marker-based and pedigree-based predictions. Within-population predictions for the four traits ranged from 0.21 to 0.72. Multi-population prediction yielded accuracies ranging from 0.18 to 0.67. Predictions across purebred populations as well as predicting genetic merit of crossbreds from their purebred parental lines for AFI performed poorly (not significantly different from zero). In contrast, accuracies of across-population predictions and accuracies of purebred to crossbred predictions for LBW and LVR ranged from 0.08 to 0.31 and 0.11 to 0.31, respectively. Accuracy for TNB was zero for across-population prediction, whereas for purebred to crossbred prediction it ranged from 0.08 to 0.22. In general, marker-based outperformed pedigree-based prediction across populations and traits. However, in some cases pedigree-based prediction performed similarly or outperformed marker-based prediction. There was predictive ability when purebred populations were used to predict crossbred genetic merit using an additive model in the populations studied. AFI was the only exception, indicating that predictive ability depends largely on the genetic correlation between PB and CB performance, which was 0.31 for AFI. Multi-population prediction was no better than within-population prediction for the purebred validation set. Accuracy of prediction was very trait-dependent. Copyright © 2015 Hidalgo et al.

Sensitivity of the Speech Intelligibility Index to the Assumed Dynamic Range

ERIC Educational Resources Information Center

Jin, In-Ki; Kates, James M.; Arehart, Kathryn H.

2017-01-01

Purpose: This study aims to evaluate the sensitivity of the speech intelligibility index (SII) to the assumed speech dynamic range (DR) in different languages and with different types of stimuli. Method: Intelligibility prediction uses the absolute transfer function (ATF) to map the SII value to the predicted intelligibility for a given stimuli.…

International normalized ratio stability in warfarin-experienced patients with nonvalvular atrial fibrillation.

PubMed

Nelson, Winnie W; Desai, Sunita; Damaraju, Chandrasekharrao V; Lu, Lang; Fields, Larry E; Wildgoose, Peter; Schein, Jeffery R

2015-06-01

Maintaining stable levels of anticoagulation using warfarin therapy is challenging. Few studies have examined the stability of the international normalized ratio (INR) in patients with nonvalvular atrial fibrillation (NVAF) who have had ≥6 months' exposure to warfarin anticoagulation for stroke prevention. Our objective was to describe INR control in NVAF patients who had been receiving warfarin for at least 6 months. Using retrospective patient data from the CoagClinic™ database, we analyzed data from NVAF patients treated with warfarin to assess the quality of INR control and possible predictors of poor INR control. Time within, above, and below the recommended INR range (2.0-3.0) was calculated for patients who had received warfarin for ≥6 months and had three or more INR values. The analysis also assessed INR patterns and resource utilization of patients with an INR >4.0. Logistic regression models were used to determine factors associated with poor INR control. Patients (n = 9433) had an average of 1.6 measurements per 30 days. Mean follow-up time was 544 days. Approximately 39% of INR values were out of range, with 23% of INR values being <2.0 and 16% being >3.0. Mean percent time with INR in therapeutic range was 67%; INR <2.0 was 19% and INR >3.0 was 14%. Patients with more than one reading of INR >4.0 (~39%) required an average of one more visit and took 3 weeks to return to an in-range INR. Male sex and age >75 years were predictive of better INR control, whereas a history of heart failure or diabetes were predictive of out-of-range INR values. However, patient characteristics did not predict the likelihood of INR >4.0. Out-of-range INR values remain frequent in patients with NVAF treated with warfarin. Exposure to high INR values was common, resulting in increased resource utilization.

Multivariate linear regression analysis to identify general factors for quantitative predictions of implant stability quotient values

PubMed Central

Huang, Hairong; Xu, Zanzan; Shao, Xianhong; Wismeijer, Daniel; Sun, Ping; Wang, Jingxiao

2017-01-01

Objectives This study identified potential general influencing factors for a mathematical prediction of implant stability quotient (ISQ) values in clinical practice. Methods We collected the ISQ values of 557 implants from 2 different brands (SICace and Osstem) placed by 2 surgeons in 336 patients. Surgeon 1 placed 329 SICace implants, and surgeon 2 placed 113 SICace implants and 115 Osstem implants. ISQ measurements were taken at T1 (immediately after implant placement) and T2 (before dental restoration). A multivariate linear regression model was used to analyze the influence of the following 11 candidate factors for stability prediction: sex, age, maxillary/mandibular location, bone type, immediate/delayed implantation, bone grafting, insertion torque, I-stage or II-stage healing pattern, implant diameter, implant length and T1-T2 time interval. Results The need for bone grafting as a predictor significantly influenced ISQ values in all three groups at T1 (weight coefficients ranging from -4 to -5). In contrast, implant diameter consistently influenced the ISQ values in all three groups at T2 (weight coefficients ranging from 3.4 to 4.2). Other factors, such as sex, age, I/II-stage implantation and bone type, did not significantly influence ISQ values at T2, and implant length did not significantly influence ISQ values at T1 or T2. Conclusions These findings provide a rational basis for mathematical models to quantitatively predict the ISQ values of implants in clinical practice. PMID:29084260

Model for estimating enteric methane emissions from United States dairy and feedlot cattle.

PubMed

Kebreab, E; Johnson, K A; Archibeque, S L; Pape, D; Wirth, T

2008-10-01

Methane production from enteric fermentation in cattle is one of the major sources of anthropogenic greenhouse gas emission in the United States and worldwide. National estimates of methane emissions rely on mathematical models such as the one recommended by the Intergovernmental Panel for Climate Change (IPCC). Models used for prediction of methane emissions from cattle range from empirical to mechanistic with varying input requirements. Two empirical and 2 mechanistic models (COWPOLL and MOLLY) were evaluated for their prediction ability using individual cattle measurements. Model selection was based on mean square prediction error (MSPE), concordance correlation coefficient, and residuals vs. predicted values analyses. In dairy cattle, COWPOLL had the lowest root MSPE and greatest accuracy and precision of predicting methane emissions (correlation coefficient estimate = 0.75). The model simulated differences in diet more accurately than the other models, and the residuals vs. predicted value analysis showed no mean bias (P = 0.71). In feedlot cattle, MOLLY had the lowest root MSPE with almost all errors from random sources (correlation coefficient estimate = 0.69). The IPCC model also had good agreement with observed values, and no significant mean (P = 0.74) or linear bias (P = 0.11) was detected when residuals were plotted against predicted values. A fixed methane conversion factor (Ym) might be an easier alternative to diet-dependent variable Ym. Based on the results, the 2 mechanistic models were used to simulate methane emissions from representative US diets and were compared with the IPCC model. The average Ym in dairy cows was 5.63% of GE (range 3.78 to 7.43%) compared with 6.5% +/- 1% recommended by IPCC. In feedlot cattle, the average Ym was 3.88% (range 3.36 to 4.56%) compared with 3% +/- 1% recommended by IPCC. Based on our simulations, using IPCC values can result in an overestimate of about 12.5% and underestimate of emissions by about 9.8% for dairy and feedlot cattle, respectively. In addition to providing improved estimates of emissions based on diets, mechanistic models can be used to assess mitigation options such as changing source of carbohydrate or addition of fat to decrease methane, which is not possible with empirical models. We recommend national inventories use diet-specific Ym values predicted by mechanistic models to estimate methane emissions from cattle.

Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves.

PubMed

Lee, Wen-Chung; Wu, Yun-Chun

2016-01-01

The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities.Based on decision theory, the authors propose an alternative index, the "average deviation about the probability threshold" (ADAPT).An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model.Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models.

Laharz_py: GIS tools for automated mapping of lahar inundation hazard zones

USGS Publications Warehouse

Schilling, Steve P.

2014-01-01

Laharz_py is written in the Python programming language as a suite of tools for use in ArcMap Geographic Information System (GIS). Primarily, Laharz_py is a computational model that uses statistical descriptions of areas inundated by past mass-flow events to forecast areas likely to be inundated by hypothetical future events. The forecasts use physically motivated and statistically calibrated power-law equations that each has a form A = cV2/3, relating mass-flow volume (V) to planimetric or cross-sectional areas (A) inundated by an average flow as it descends a given drainage. Calibration of the equations utilizes logarithmic transformation and linear regression to determine the best-fit values of c. The software uses values of V, an algorithm for idenitifying mass-flow source locations, and digital elevation models of topography to portray forecast hazard zones for lahars, debris flows, or rock avalanches on maps. Laharz_py offers two methods to construct areas of potential inundation for lahars: (1) Selection of a range of plausible V values results in a set of nested hazard zones showing areas likely to be inundated by a range of hypothetical flows; and (2) The user selects a single volume and a confidence interval for the prediction. In either case, Laharz_py calculates the mean expected A and B value from each user-selected value of V. However, for the second case, a single value of V yields two additional results representing the upper and lower values of the confidence interval of prediction. Calculation of these two bounding predictions require the statistically calibrated prediction equations, a user-specified level of confidence, and t-distribution statistics to calculate the standard error of regression, standard error of the mean, and standard error of prediction. The portrayal of results from these two methods on maps compares the range of inundation areas due to prediction uncertainties with uncertainties in selection of V values. The Open-File Report document contains an explanation of how to install and use the software. The Laharz_py software includes an example data set for Mount Rainier, Washington. The second part of the documentation describes how to use all of the Laharz_py tools in an example dataset at Mount Rainier, Washington.

The utility of rapid antigen detection testing for the diagnosis of streptococcal pharyngitis in low-resource settings.

PubMed

Rimoin, Anne W; Walker, Christa L Fischer; Hamza, Hala S; Elminawi, Nevine; Ghafar, Hadeer Abdel; Vince, Adriana; da Cunha, Antonia L A; Qazi, Shamim; Gardovska, Dace; Steinhoff, Mark C

2010-12-01

To evaluate the utility of rapid antigen detection testing (RADT) for the diagnosis of group A streptococcal (GAS) pharyngitis in pediatric outpatient clinics in four countries with varied socio-economic and geographic profiles. We prospectively evaluated the utility of a commercial RADT in children aged 2-12 years presenting with symptoms of pharyngitis to urban outpatient clinics in Brazil, Croatia, Egypt, and Latvia between August 2001 and December 2005. We compared the performance of the RADT to culture using diagnostic and agreement statistics, including sensitivity, specificity, and positive and negative predictive values. The Centor scores for GAS diagnosis were used to assess the potential effect of spectrum bias on RADT results. Two thousand four hundred and seventy-two children were enrolled at four sites. The prevalence of GAS by throat culture varied by country (range 24.5-39.4%) and by RADT (range 23.9-41.8%). Compared to culture, RADT sensitivity ranged from 72.4% to 91.8% and specificity ranged from 85.7% to 96.4%. The positive predictive value ranged from 67.9% to 88.6% and negative predictive value ranged from 88.1% to 95.7%. In limited-resource regions where microbiological diagnosis is not feasible or practical, RADTs should be considered an option that can be performed in a clinic and provide timely results. Copyright © 2010 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Design with limited anthropometric data: A method of interpreting sums of percentiles in anthropometric design.

PubMed

Albin, Thomas J

2017-07-01

Occasionally practitioners must work with single dimensions defined as combinations (sums or differences) of percentile values, but lack information (e.g. variances) to estimate the accommodation achieved. This paper describes methods to predict accommodation proportions for such combinations of percentile values, e.g. two 90th percentile values. Kreifeldt and Nah z-score multipliers were used to estimate the proportions accommodated by combinations of percentile values of 2-15 variables; two simplified versions required less information about variance and/or correlation. The estimates were compared to actual observed proportions; for combinations of 2-15 percentile values the average absolute differences ranged between 0.5 and 1.5 percentage points. The multipliers were also used to estimate adjusted percentile values, that, when combined, estimate a desired proportion of the combined measurements. For combinations of two and three adjusted variables, the average absolute difference between predicted and observed proportions ranged between 0.5 and 3.0 percentage points. Copyright © 2017 Elsevier Ltd. All rights reserved.

Experimental and predicted cavitation performance of an 80.6 deg helical inducer in high temperature water

NASA Technical Reports Server (NTRS)

Kovich, G.

1972-01-01

The cavitating performance of a stainless steel 80.6 degree flat-plate helical inducer was investigated in water over a range of liquid temperatures and flow coefficients. A semi-empirical prediction method was used to compare predicted values of required net positive suction head in water with experimental values obtained in water. Good agreement was obtained between predicted and experimental data in water. The required net positive suction head in water decreased with increasing temperature and increased with flow coefficient, similar to that observed for a like inducer in liquid hydrogen.

Adjustment of regional regression equations for urban storm-runoff quality using at-site data

USGS Publications Warehouse

Barks, C.S.

1996-01-01

Regional regression equations have been developed to estimate urban storm-runoff loads and mean concentrations using a national data base. Four statistical methods using at-site data to adjust the regional equation predictions were developed to provide better local estimates. The four adjustment procedures are a single-factor adjustment, a regression of the observed data against the predicted values, a regression of the observed values against the predicted values and additional local independent variables, and a weighted combination of a local regression with the regional prediction. Data collected at five representative storm-runoff sites during 22 storms in Little Rock, Arkansas, were used to verify, and, when appropriate, adjust the regional regression equation predictions. Comparison of observed values of stormrunoff loads and mean concentrations to the predicted values from the regional regression equations for nine constituents (chemical oxygen demand, suspended solids, total nitrogen as N, total ammonia plus organic nitrogen as N, total phosphorus as P, dissolved phosphorus as P, total recoverable copper, total recoverable lead, and total recoverable zinc) showed large prediction errors ranging from 63 percent to more than several thousand percent. Prediction errors for 6 of the 18 regional regression equations were less than 100 percent and could be considered reasonable for water-quality prediction equations. The regression adjustment procedure was used to adjust five of the regional equation predictions to improve the predictive accuracy. For seven of the regional equations the observed and the predicted values are not significantly correlated. Thus neither the unadjusted regional equations nor any of the adjustments were appropriate. The mean of the observed values was used as a simple estimator when the regional equation predictions and adjusted predictions were not appropriate.

Predicting the digestible energy of corn determined with growing swine from nutrient composition and cross-species measurements.

PubMed

Smith, B; Hassen, A; Hinds, M; Rice, D; Jones, D; Sauber, T; Iiams, C; Sevenich, D; Allen, R; Owens, F; McNaughton, J; Parsons, C

2015-03-01

The DE values of corn grain for pigs will differ among corn sources. More accurate prediction of DE may improve diet formulation and reduce diet cost. Corn grain sources ( = 83) were assayed with growing swine (20 kg) in DE experiments with total collection of feces, with 3-wk-old broiler chick in nitrogen-corrected apparent ME (AME) trials and with cecectomized adult roosters in nitrogen-corrected true ME (TME) studies. Additional AME data for the corn grain source set was generated based on an existing near-infrared transmittance prediction model (near-infrared transmittance-predicted AME [NIT-AME]). Corn source nutrient composition was determined by wet chemistry methods. These data were then used to 1) test the accuracy of predicting swine DE of individual corn sources based on available literature equations and nutrient composition and 2) develop models for predicting DE of sources from nutrient composition and the cross-species information gathered above (AME, NIT-AME, and TME). The overall measured DE, AME, NIT-AME, and TME values were 4,105 ± 11, 4,006 ± 10, 4,004 ± 10, and 4,086 ± 12 kcal/kg DM, respectively. Prediction models were developed using 80% of the corn grain sources; the remaining 20% was reserved for validation of the developed prediction equation. Literature equations based on nutrient composition proved imprecise for predicting corn DE; the root mean square error of prediction ranged from 105 to 331 kcal/kg, an equivalent of 2.6 to 8.8% error. Yet among the corn composition traits, 4-variable models developed in the current study provided adequate prediction of DE (model ranging from 0.76 to 0.79 and root mean square error [RMSE] of 50 kcal/kg). When prediction equations were tested using the validation set, these models had a 1 to 1.2% error of prediction. Simple linear equations from AME, NIT-AME, or TME provided an accurate prediction of DE for individual sources ( ranged from 0.65 to 0.73 and RMSE ranged from 50 to 61 kcal/kg). Percentage error of prediction based on the validation data set was greater (1.4%) for the TME model than for the NIT-AME or AME models (1 and 1.2%, respectively), indicating that swine DE values could be accurately predicted by using AME or NIT-AME. In conclusion, regression equations developed from broiler measurements or from analyzed nutrient composition proved adequate to reliably predict the DE of commercially available corn hybrids for growing pigs.

Development of a predictive model for lead, cadmium and fluorine soil-water partition coefficients using sparse multiple linear regression analysis.

PubMed

Nakamura, Kengo; Yasutaka, Tetsuo; Kuwatani, Tatsu; Komai, Takeshi

2017-11-01

In this study, we applied sparse multiple linear regression (SMLR) analysis to clarify the relationships between soil properties and adsorption characteristics for a range of soils across Japan and identify easily-obtained physical and chemical soil properties that could be used to predict K and n values of cadmium, lead and fluorine. A model was first constructed that can easily predict the K and n values from nine soil parameters (pH, cation exchange capacity, specific surface area, total carbon, soil organic matter from loss on ignition and water holding capacity, the ratio of sand, silt and clay). The K and n values of cadmium, lead and fluorine of 17 soil samples were used to verify the SMLR models by the root mean square error values obtained from 512 combinations of soil parameters. The SMLR analysis indicated that fluorine adsorption to soil may be associated with organic matter, whereas cadmium or lead adsorption to soil is more likely to be influenced by soil pH, IL. We found that an accurate K value can be predicted from more than three soil parameters for most soils. Approximately 65% of the predicted values were between 33 and 300% of their measured values for the K value; 76% of the predicted values were within ±30% of their measured values for the n value. Our findings suggest that adsorption properties of lead, cadmium and fluorine to soil can be predicted from the soil physical and chemical properties using the presented models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting Forearm Physical Exposures During Computer Work Using Self-Reports, Software-Recorded Computer Usage Patterns, and Anthropometric and Workstation Measurements.

PubMed

Huysmans, Maaike A; Eijckelhof, Belinda H W; Garza, Jennifer L Bruno; Coenen, Pieter; Blatter, Birgitte M; Johnson, Peter W; van Dieën, Jaap H; van der Beek, Allard J; Dennerlein, Jack T

2017-12-15

Alternative techniques to assess physical exposures, such as prediction models, could facilitate more efficient epidemiological assessments in future large cohort studies examining physical exposures in relation to work-related musculoskeletal symptoms. The aim of this study was to evaluate two types of models that predict arm-wrist-hand physical exposures (i.e. muscle activity, wrist postures and kinematics, and keyboard and mouse forces) during computer use, which only differed with respect to the candidate predicting variables; (i) a full set of predicting variables, including self-reported factors, software-recorded computer usage patterns, and worksite measurements of anthropometrics and workstation set-up (full models); and (ii) a practical set of predicting variables, only including the self-reported factors and software-recorded computer usage patterns, that are relatively easy to assess (practical models). Prediction models were build using data from a field study among 117 office workers who were symptom-free at the time of measurement. Arm-wrist-hand physical exposures were measured for approximately two hours while workers performed their own computer work. Each worker's anthropometry and workstation set-up were measured by an experimenter, computer usage patterns were recorded using software and self-reported factors (including individual factors, job characteristics, computer work behaviours, psychosocial factors, workstation set-up characteristics, and leisure-time activities) were collected by an online questionnaire. We determined the predictive quality of the models in terms of R2 and root mean squared (RMS) values and exposure classification agreement to low-, medium-, and high-exposure categories (in the practical model only). The full models had R2 values that ranged from 0.16 to 0.80, whereas for the practical models values ranged from 0.05 to 0.43. Interquartile ranges were not that different for the two models, indicating that only for some physical exposures the full models performed better. Relative RMS errors ranged between 5% and 19% for the full models, and between 10% and 19% for the practical model. When the predicted physical exposures were classified into low, medium, and high, classification agreement ranged from 26% to 71%. The full prediction models, based on self-reported factors, software-recorded computer usage patterns, and additional measurements of anthropometrics and workstation set-up, show a better predictive quality as compared to the practical models based on self-reported factors and recorded computer usage patterns only. However, predictive quality varied largely across different arm-wrist-hand exposure parameters. Future exploration of the relation between predicted physical exposure and symptoms is therefore only recommended for physical exposures that can be reasonably well predicted. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Accurate prediction of acute fish toxicity of fragrance chemicals with the RTgill-W1 cell assay.

PubMed

Natsch, Andreas; Laue, Heike; Haupt, Tina; von Niederhäusern, Valentin; Sanders, Gordon

2018-03-01

Testing for acute fish toxicity is an integral part of the environmental safety assessment of chemicals. A true replacement of primary fish tissue was recently proposed using cell viability in a fish gill cell line (RTgill-W1) as a means of predicting acute toxicity, showing good predictivity on 35 chemicals. To promote regulatory acceptance, the predictivity and applicability domain of novel tests need to be carefully evaluated on chemicals with existing high-quality in vivo data. We applied the RTgill-W1 cell assay to 38 fragrance chemicals with a wide range of both physicochemical properties and median lethal concentration (LC50) values and representing a diverse range of chemistries. A strong correlation (R 2  = 0.90-0.94) between the logarithmic in vivo LC50 values, based on fish mortality, and the logarithmic in vitro median effect concentration (EC50) values based on cell viability was observed. A leave-one-out analysis illustrates a median under-/overprediction from in vitro EC50 values to in vivo LC50 values by a factor of 1.5. This assay offers a simple, accurate, and reliable alternative to in vivo acute fish toxicity testing for chemicals, presumably acting mainly by a narcotic mode of action. Furthermore, the present study provides validation of the predictivity of the RTgill-W1 assay on a completely independent set of chemicals that had not been previously tested and indicates that fragrance chemicals are clearly within the applicability domain. Environ Toxicol Chem 2018;37:931-941. © 2017 SETAC. © 2017 SETAC.

Comparing diagnostic accuracy of bedside ultrasound and radiography for bone fracture screening in multiple trauma patients at the ED.

PubMed

Bolandparvaz, Shahram; Moharamzadeh, Payman; Jamali, Kazem; Pouraghaei, Mahboob; Fadaie, Maryam; Sefidbakht, Sepideh; Shahsavari, Kavous

2013-11-01

Long bone fractures are currently diagnosed using radiography, but radiography has some disadvantages (radiation and being time consuming). The present study compared the diagnostic accuracy of bedside ultrasound and radiography in multiple trauma patients at the emergency department (ED). The study assessed 80 injured patients with multiple trauma from February 2011 to July 2012. The patients were older than 18 years and triaged to the cardiopulmonary resuscitation ward of the ED. Bedside ultrasound and radiography were conducted for them. The findings were separately and blindly assessed by 2 radiologists. Sensitivity, specificity, the positive and negative predictive value, and κ coefficient were measured to assess the accuracy and validity of ultrasound as compared with radiography. The sensitivity of ultrasound for diagnosis of limb bone fractures was not high enough and ranged between 55% and 75% depending on the fracture site. The specificity of this diagnostic method had an acceptable range of 62% to 84%. Ultrasound negative prediction value was higher than other indices under study and ranged between 73% and 83%, but its positive prediction value varied between 33.3% and 71%. The κ coefficient for diagnosis of long bone fractures of upper limb (κ = 0.58) and upper limb joints (κ = 0.47) and long bones of lower limb (κ = 0.52) was within the medium range. However, the value for diagnosing fractures of lower limb joints (κ = 0.47) was relatively low. Bedside ultrasound is not a reliable method for diagnosing fractures of upper and lower limb bones compared with radiography. © 2013 Elsevier Inc. All rights reserved.

Predicting species richness and distribution ranges of centipedes at the northern edge of Europe

NASA Astrophysics Data System (ADS)

Georgopoulou, Elisavet; Djursvoll, Per; Simaiakis, Stylianos M.

2016-07-01

In recent decades, interest in understanding species distributions and exploring processes that shape species diversity has increased, leading to the development of advanced methods for the exploitation of occurrence data for analytical and ecological purposes. Here, with the use of georeferenced centipede data, we explore the importance and contribution of bioclimatic variables and land cover, and predict distribution ranges and potential hotspots in Norway. We used a maximum entropy analysis (Maxent) to model species' distributions, aiming at exploring centres of distribution, latitudinal spans and northern range boundaries of centipedes in Norway. The performance of all Maxent models was better than random with average test area under the curve (AUC) values above 0.893 and True Skill Statistic (TSS) values above 0.593. Our results showed a highly significant latitudinal gradient of increased species richness in southern grid-cells. Mean temperatures of warmest and coldest quarters explained much of the potential distribution of species. Predictive modelling analyses revealed that south-eastern Norway and the Atlantic coast in the west (inclusive of the major fjord system of Sognefjord), are local biodiversity hotspots with regard to high predictive species co-occurrence. We conclude that our predicted northward shifts of centipedes' distributions in Norway are likely a result of post-glacial recolonization patterns, species' ecological requirements and dispersal abilities.

SU-D-207B-03: A PET-CT Radiomics Comparison to Predict Distant Metastasis in Lung Adenocarcinoma

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

Coroller, T; Yip, S; Lee, S

2016-06-15

Purpose: Early prediction of distant metastasis may provide crucial information for adaptive therapy, subsequently improving patient survival. Radiomic features that extracted from PET and CT images have been used for assessing tumor phenotype and predicting clinical outcomes. This study investigates the values of radiomic features in predicting distant metastasis (DM) in non-small cell lung cancer (NSCLC). Methods: A total of 108 patients with stage II–III lung adenocarcinoma were included in this retrospective study. Twenty radiomic features were selected (10 from CT and 10 from PET). Conventional features (metabolic tumor volume, SUV, volume and diameter) were included for comparison. Concordance indexmore » (CI) was used to evaluate features prognostic value. Noether test was used to compute p-value to consider CI significance from random (CI = 0.5) and were adjusted for multiple testing using false rate discovery (FDR). Results: A total of 70 patients had DM (64.8%) with a median time to event of 8.8 months. The median delivered dose was 60 Gy (range 33–68 Gy). None of the conventional features from PET (CI ranged from 0.51 to 0.56) or CT (CI ranged from 0.57 to 0.58) were significant from random. Five radiomics features were significantly prognostic from random for DM (p-values < 0.05). Four were extracted from CT (CI = 0.61 to 0.63, p-value <0.01) and one from PET which was also the most prognostic (CI = 0.64, p-value <0.001). Conclusion: This study demonstrated significant association between radiomic features and DM for patients with locally advanced lung adenocarcinoma. Moreover, conventional (clinically utilized) metrics were not significantly associated with DM. Radiomics can potentially help classify patients at higher risk of DM, allowing clinicians to individualize treatment, such as intensification of chemotherapy) to reduce the risk of DM and improve survival. R.M. has consulting interests with Amgen.« less

How Massive Can Stars Be?

ERIC Educational Resources Information Center

Pinochet, Jorge; Van Sint Jan, Michael

2017-01-01

Theoretical assessment of the upper limit of a star's mass is a difficult problem which lies at the frontier of astrophysical research. In this article we develop a simple and plausible argument to estimate this value. The value at which we arrive is ~228 solar masses; well within the range of predicted accepted theoretical values. Towards the end…

Bona-fide method for the determination of short range order and transport properties in a ferro-aluminosilicate slag

PubMed Central

Karalis, Konstantinos T.; Dellis, Dimitrios; Antipas, Georgios S. E.; Xenidis, Anthimos

2016-01-01

The thermodynamics, structural and transport properties (density, melting point, heat capacity, thermal expansion coefficient, viscosity and electrical conductivity) of a ferro-aluminosilicate slag have been studied in the solid and liquid state (1273–2273 K) using molecular dynamics. The simulations were based on a Buckingham-type potential, which was extended here, to account for the presence of Cr and Cu. The potential was optimized by fitting pair distribution function partials to values determined by Reverse Monte Carlo modelling of X-ray and neutron diffraction experiments. The resulting short range order features and ring statistics were in tight agreement with experimental data and created consensus for the accurate prediction of transport properties. Accordingly, calculations yielded rational values both for the average heat capacity, equal to 1668.58 J/(kg·K), and for the viscosity, in the range of 4.09–87.64 cP. The potential was consistent in predicting accurate values for mass density (i.e. 2961.50 kg/m3 vs. an experimental value of 2940 kg/m3) and for electrical conductivity (5.3–233 S/m within a temperature range of 1273.15–2273.15 K). PMID:27455915

Note: Calibration of EBT3 radiochromic film for measuring solar ultraviolet radiation

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

Chun, S. L.; Yu, P. K. N., E-mail: peter.yu@cityu.edu.hk; State Key Laboratory in Marine Pollution, City University of Hong Kong, Kowloon Tong

Solar (UVA + UVB) exposure was assessed using the Gafchromic EBT3 film. The coloration change was represented by the net reflective optical density (Net ROD). Through calibrations against a UV-tube lamp, operational relationships were obtained between Net ROD and the (UVA + UVB) exposures (in J cm⁻²p or J m⁻²). The useful range was from ~0.2 to ~30 J cm⁻². The uniformity of UV irradiation was crucial for an accurate calibration. For solar exposures ranging from 2 to 11 J cm⁻², the predicted Net ROD agreed with the recorded values within 9%, while the predicted exposures agreed with the recordedmore » values within 15%.« less

Predicting the solubility and lability of Zn, Cd, and Pb in soils from a minespoil-contaminated catchment by stable isotopic exchange

NASA Astrophysics Data System (ADS)

Marzouk, E. R.; Chenery, S. R.; Young, S. D.

2013-12-01

The Rookhope catchment of Weardale, England, has a diverse legacy of contaminated soils due to extensive lead mining activity over four centuries. We measured the isotopically exchangeable content of Pb, Cd and Zn (E-values) in a large representative subset of the catchment soils (n = 246) using stable isotope dilution. All three metals displayed a wide range of %E-values (c. 1-100%) but relative lability followed the sequence Cd > Pb > Zn. A refinement of the stable isotope dilution approach also enabled detection of non-reactive metal contained within suspended sub-micron (<0.22 μm) colloidal particles (SCP-metal). For most soils, the presence of non-labile SCP-metal caused only minor over-estimation of E-values (<2%) but the effect was greater for soils with particularly large humus or carbonate contents. Approximately 80%, 53% and 66% of the variability in Zn, Cd and Pb %E-values (respectively) could be explained by pH, loss on ignition and total metal content. E-values were affected by the presence of ore minerals at high metal contents leading to an inconsistent trend in the relationship between %E-value and soil metal concentration. Metal solubility, in the soil suspensions used to measure E-values, was predicted using the WHAM geochemical speciation model (versions VI and VII). The use of total and isotopically exchangeable metal as alternative input variables was compared; the latter provided significantly better predictions of solubility, especially in the case of Zn. Lead solubility was less well predicted by either version of WHAM, with over-prediction at low pH and under-prediction at high soil pH values. Quantify the isotopically exchangeable fractions of Zn, Cd and Pb (E-values), and assess their local and regional variability, using multi-element stable isotope dilution, in a diverse range of soil ecosystems within the catchment of an old Pb/Zn mining area. Assess the controlling influences of soil properties on metal lability and develop predictive algorithms for metal lability in the contaminated catchment based on simple soil properties (such as pH, organic matter (LOI), and total metal content). Examine the incidence of non-isotopically-exchangeable metal held within suspended colloidal particles (SCP-metal) in filtered soil solutions (<0.22 μm) by comparing E-values from isotopic abundance in solutions equilibrated with soil and in a resin phase equilibrated with the separated solution. Assess the ability of a geochemical speciation model, WHAM(VII), to predict metal solubility using isotopically exchangeable metal as an input variable.

The physics behind Van der Burgh's empirical equation, providing a new predictive equation for salinity intrusion in estuaries

NASA Astrophysics Data System (ADS)

Zhang, Zhilin; Savenije, Hubert H. G.

2017-07-01

The practical value of the surprisingly simple Van der Burgh equation in predicting saline water intrusion in alluvial estuaries is well documented, but the physical foundation of the equation is still weak. In this paper we provide a connection between the empirical equation and the theoretical literature, leading to a theoretical range of Van der Burgh's coefficient of 1/2 < K < 2/3 for density-driven mixing which falls within the feasible range of 0 < K < 1. In addition, we developed a one-dimensional predictive equation for the dispersion of salinity as a function of local hydraulic parameters that can vary along the estuary axis, including mixing due to tide-driven residual circulation. This type of mixing is relevant in the wider part of alluvial estuaries where preferential ebb and flood channels appear. Subsequently, this dispersion equation is combined with the salt balance equation to obtain a new predictive analytical equation for the longitudinal salinity distribution. Finally, the new equation was tested and applied to a large database of observations in alluvial estuaries, whereby the calibrated K values appeared to correspond well to the theoretical range.

Conformal Regression for Quantitative Structure-Activity Relationship Modeling-Quantifying Prediction Uncertainty.

PubMed

Svensson, Fredrik; Aniceto, Natalia; Norinder, Ulf; Cortes-Ciriano, Isidro; Spjuth, Ola; Carlsson, Lars; Bender, Andreas

2018-05-29

Making predictions with an associated confidence is highly desirable as it facilitates decision making and resource prioritization. Conformal regression is a machine learning framework that allows the user to define the required confidence and delivers predictions that are guaranteed to be correct to the selected extent. In this study, we apply conformal regression to model molecular properties and bioactivity values and investigate different ways to scale the resultant prediction intervals to create as efficient (i.e., narrow) regressors as possible. Different algorithms to estimate the prediction uncertainty were used to normalize the prediction ranges, and the different approaches were evaluated on 29 publicly available data sets. Our results show that the most efficient conformal regressors are obtained when using the natural exponential of the ensemble standard deviation from the underlying random forest to scale the prediction intervals, but other approaches were almost as efficient. This approach afforded an average prediction range of 1.65 pIC50 units at the 80% confidence level when applied to bioactivity modeling. The choice of nonconformity function has a pronounced impact on the average prediction range with a difference of close to one log unit in bioactivity between the tightest and widest prediction range. Overall, conformal regression is a robust approach to generate bioactivity predictions with associated confidence.

The use of atmospheric measurements to constrain model predictions of ozone change from chlorine perturbations

NASA Technical Reports Server (NTRS)

Douglass, Anne R.; Stolarski, Richard S.

1987-01-01

Atmospheric photochemistry models have been used to predict the sensitivity of the ozone layer to various perturbations. These same models also predict concentrations of chemical species in the present day atmosphere which can be compared to observations. Model results for both present day values and sensitivity to perturbation depend upon input data for reaction rates, photodissociation rates, and boundary conditions. A method of combining the results of a Monte Carlo uncertainty analysis with the existing set of present atmospheric species measurements is developed. The method is used to examine the range of values for the sensitivity of ozone to chlorine perturbations that is possible within the currently accepted ranges for input data. It is found that model runs which predict ozone column losses much greater than 10 percent as a result of present fluorocarbon fluxes produce concentrations and column amounts in the present atmosphere which are inconsistent with the measurements for ClO, HCl, NO, NO2, and HNO3.

Combining first-principles and data modeling for the accurate prediction of the refractive index of organic polymers

NASA Astrophysics Data System (ADS)

Afzal, Mohammad Atif Faiz; Cheng, Chong; Hachmann, Johannes

2018-06-01

Organic materials with a high index of refraction (RI) are attracting considerable interest due to their potential application in optic and optoelectronic devices. However, most of these applications require an RI value of 1.7 or larger, while typical carbon-based polymers only exhibit values in the range of 1.3-1.5. This paper introduces an efficient computational protocol for the accurate prediction of RI values in polymers to facilitate in silico studies that can guide the discovery and design of next-generation high-RI materials. Our protocol is based on the Lorentz-Lorenz equation and is parametrized by the polarizability and number density values of a given candidate compound. In the proposed scheme, we compute the former using first-principles electronic structure theory and the latter using an approximation based on van der Waals volumes. The critical parameter in the number density approximation is the packing fraction of the bulk polymer, for which we have devised a machine learning model. We demonstrate the performance of the proposed RI protocol by testing its predictions against the experimentally known RI values of 112 optical polymers. Our approach to combine first-principles and data modeling emerges as both a successful and a highly economical path to determining the RI values for a wide range of organic polymers.

Enhancing the 'real world' prediction of cardiovascular events and major bleeding with the CHA2DS2-VASc and HAS-BLED scores using multiple biomarkers.

PubMed

Roldán, Vanessa; Rivera-Caravaca, José Miguel; Shantsila, Alena; García-Fernández, Amaya; Esteve-Pastor, María Asunción; Vilchez, Juan Antonio; Romera, Marta; Valdés, Mariano; Vicente, Vicente; Marín, Francisco; Lip, Gregory Y H

2018-02-01

Atrial fibrillation (AF)-European guidelines suggest the use of biomarkers to stratify patients for stroke and bleeding risks. We investigated if a multibiomarker strategy improved the predictive performance of CHA 2 DS 2 -VASc and HAS-BLED in anticoagulated AF patients. We included consecutive patients stabilized for six months on vitamin K antagonists (INRs 2.0-3.0). High sensitivity troponin T, NT-proBNP, interleukin-6, von Willebrand factor concentrations and glomerular filtration rate (eGFR; using MDRD-4 formula) were quantified at baseline. Time in therapeutic range (TTR) was recorded at six months after inclusion. Patients were follow-up during a median of 2375 (IQR 1564-2887) days and all adverse events were recorded. In 1361 patients, adding four blood biomarkers, TTR and MDRD-eGFR, the predictive value of CHA 2 DS 2 -VASc increased significantly by c-index (0.63 vs. 0.65; p = .030) and IDI (0.85%; p < .001), but not by NRI (-2.82%; p < .001). The predictive value of HAS-BLED increased up to 1.34% by IDI (p < .001). Nevertheless, the overall predictive value remains modest (c-indexes approximately 0.65) and decision curve analyses found lower net benefit compared with the originals scores. Addition of biomarkers enhanced the predictive value of CHA 2 DS 2 -VASc and HAS-BLED, although the overall improvement was modest and the added predictive advantage over original scores was marginal. Key Messages Recent atrial fibrillation (AF)-European guidelines for the first time suggest the use of biomarkers to stratify patients for stroke and bleeding risks, but their usefulness in real world for risk stratification is still questionable. In this cohort study involving 1361 AF patients optimally anticoagulated with vitamin K antagonists, adding high sensitivity troponin T, N-terminal pro-B-type natriuretic peptide, interleukin 6, von Willebrand factor, glomerular filtration rate (by the MDRD-4 formula) and time in therapeutic range, increased the predictive value of CHA 2 DS 2 -VASc for cardiovascular events, but not the predictive value of HAS-BLED for major bleeding. Reclassification analyses did not show improvement adding multiple biomarkers. Despite the improvement observed, the added predictive advantage is marginal and the clinical usefulness and net benefit over current clinical scores is lower.

Impact of fitting dominance and additive effects on accuracy of genomic prediction of breeding values in layers.

PubMed

Heidaritabar, M; Wolc, A; Arango, J; Zeng, J; Settar, P; Fulton, J E; O'Sullivan, N P; Bastiaansen, J W M; Fernando, R L; Garrick, D J; Dekkers, J C M

2016-10-01

Most genomic prediction studies fit only additive effects in models to estimate genomic breeding values (GEBV). However, if dominance genetic effects are an important source of variation for complex traits, accounting for them may improve the accuracy of GEBV. We investigated the effect of fitting dominance and additive effects on the accuracy of GEBV for eight egg production and quality traits in a purebred line of brown layers using pedigree or genomic information (42K single-nucleotide polymorphism (SNP) panel). Phenotypes were corrected for the effect of hatch date. Additive and dominance genetic variances were estimated using genomic-based [genomic best linear unbiased prediction (GBLUP)-REML and BayesC] and pedigree-based (PBLUP-REML) methods. Breeding values were predicted using a model that included both additive and dominance effects and a model that included only additive effects. The reference population consisted of approximately 1800 animals hatched between 2004 and 2009, while approximately 300 young animals hatched in 2010 were used for validation. Accuracy of prediction was computed as the correlation between phenotypes and estimated breeding values of the validation animals divided by the square root of the estimate of heritability in the whole population. The proportion of dominance variance to total phenotypic variance ranged from 0.03 to 0.22 with PBLUP-REML across traits, from 0 to 0.03 with GBLUP-REML and from 0.01 to 0.05 with BayesC. Accuracies of GEBV ranged from 0.28 to 0.60 across traits. Inclusion of dominance effects did not improve the accuracy of GEBV, and differences in their accuracies between genomic-based methods were small (0.01-0.05), with GBLUP-REML yielding higher prediction accuracies than BayesC for egg production, egg colour and yolk weight, while BayesC yielded higher accuracies than GBLUP-REML for the other traits. In conclusion, fitting dominance effects did not impact accuracy of genomic prediction of breeding values in this population. © 2016 Blackwell Verlag GmbH.

Calculation of skin-friction coefficients for low Reynolds number turbulent boundary layer flows. M.S. Thesis - California Univ. at Davis

NASA Technical Reports Server (NTRS)

Barr, P. K.

1980-01-01

An analysis is presented of the reliability of various generally accepted empirical expressions for the prediction of the skin-friction coefficient C/sub f/ of turbulent boundary layers at low Reynolds numbers in zero-pressure-gradient flows on a smooth flat plate. The skin-friction coefficients predicted from these expressions were compared to the skin-friction coefficients of experimental profiles that were determined from a graphical method formulated from the law of the wall. These expressions are found to predict values that are consistently different than those obtained from the graphical method over the range 600 Re/sub theta 2000. A curve-fitted empirical relationship was developed from the present data and yields a better estimated value of C/sub f/ in this range. The data, covering the range 200 Re/sub theta 7000, provide insight into the nature of transitional flows. They show that fully developed turbulent boundary layers occur at Reynolds numbers Re/sub theta/ down to 425. Below this level there appears to be a well-ordered evolutionary process from the laminar to the turbulent profiles. These profiles clearly display the development of the turbulent core region and the shrinking of the laminar sublayer with increasing values of Re/sub theta/.

On Geomagnetism and Paleomagnetism

NASA Technical Reports Server (NTRS)

Voorhies, Coerte V.

1998-01-01

A statistical description of Earth's broad scale, core-source magnetic field has been developed and tested. The description features an expected, or mean, spatial magnetic power spectrum that is neither "flat" nor "while" at any depth, but is akin to spectra advanced by Stevenson and McLeod. This multipole spectrum describes the magnetic energy range; it is not steep enough for Gubbins' magnetic dissipation range. Natural variations of core multipole powers about their mean values are to be expected over geologic time and are described via trial probability distribution functions that neither require nor prohibit magnetic isotropy. The description is thus applicable to core-source dipole and low degree non-dipole fields despite axial dipole anisotropy. The description is combined with main field models of modem satellite and surface geomagnetic measurements to make testable predictions of: (1) the radius of Earth's core, (2) mean paleomagnetic field intensity, and (3) the mean rates and durations of both dipole power excursions and durable axial dipole reversals. The predicted core radius is 0.7% above the 3480 km seismologic value. The predicted root mean square paleointensity (35.6 mu T) and mean Virtual Axial Dipole Moment (about 6.2 lx 1022 Am(exp 2)) are within the range of various mean paleointensity estimates. The predicted mean rate of dipole power excursions, as defined by an absolute dipole moment <20% of the 1980 value, is 9.04/Myr and 14% less than obtained by analysis of a 4 Myr paleointensity record. The predicted mean rate of durable axial dipole reversals (2.26/Myr) is 2.3% more than established by the polarity time-scale for the past 84 Myr. The predicted mean duration of axial dipole reversals (5533 yr) is indistinguishable from an observational value. The accuracy of these predictions demonstrates the power and utility of the description, which is thought to merit further development and testing. It is suggested that strong stable stratification of Earth's uppermost outer core leads to a geologically long interval of no dipole reversals and a very nearly axisymmetric field outside the core. Statistical descriptions of other planetary magnetic fields are outlined.

NASA-Langley Research Center's participation in a round-robin comparison between some current crack-propagation prediction methods

NASA Technical Reports Server (NTRS)

Hudson, C. M.; Lewis, P. E.

1979-01-01

A round-robin study was conducted which evaluated and compared different methods currently in practice for predicting crack growth in surface-cracked specimens. This report describes the prediction methods used by the Fracture Mechanics Engineering Section, at NASA-Langley Research Center, and presents a comparison between predicted crack growth and crack growth observed in laboratory experiments. For tests at higher stress levels, the correlation between predicted and experimentally determined crack growth was generally quite good. For tests at lower stress levels, the predicted number of cycles to reach a given crack length was consistently higher than the experimentally determined number of cycles. This consistent overestimation of the number of cycles could have resulted from a lack of definition of crack-growth data at low values of the stress intensity range. Generally, the predicted critical flaw sizes were smaller than the experimentally determined critical flaw sizes. This underestimation probably resulted from using plane-strain fracture toughness values to predict failure rather than the more appropriate values based on maximum load.

Fast and simultaneous prediction of animal feed nutritive values using near infrared reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Samadi; Wajizah, S.; Munawar, A. A.

2018-02-01

Feed plays an important factor in animal production. The purpose of this study is to apply NIRS method in determining feed values. NIRS spectra data were acquired for feed samples in wavelength range of 1000 - 2500 nm with 32 scans and 0.2 nm wavelength. Spectral data were corrected by de-trending (DT) and standard normal variate (SNV) methods. Prediction of in vitro dry matter digestibility (IVDMD) and in vitro organic matter digestibility (IVOMD) were established as model by using principal component regression (PCR) and validated using leave one out cross validation (LOOCV). Prediction performance was quantified using coefficient correlation (r) and residual predictive deviation (RPD) index. The results showed that IVDMD and IVOMD can be predicted by using SNV spectra data with r and RPD index: 0.93 and 2.78 for IVDMD ; 0.90 and 2.35 for IVOMD respectively. In conclusion, NIRS technique appears feasible to predict animal feed nutritive values.

Evaluation of decision rules for identifying low bone density in postmenopausal African-American women.

PubMed Central

Wallace, Lorraine Silver; Ballard, Joyce E.; Holiday, David; Turner, Lori W.; Keenum, Amy J.; Pearman, Cynthia M.

2004-01-01

OBJECTIVE: While African-American women tend to have greater bone mineral density (BMD) than caucasian women, they are still at risk of developing osteoporosis later in life. Clinical decision rules (i.e., algorithms) have been developed to assist clinicians identify women at greatest risk of low BMD. However, such tools have only been validated in caucasian and Asian populations. Accordingly, the objective of this study was to compare the performance of five clinical decision rules in identifying postmenopausal African-American women at greatest risk for low femoral BMD. METHODOLOGY: One hundred-seventy-four (n=174) postmenopausal African-American women completed a valid and reliable oral questionnaire to assess lifestyle characteristics, and completed height and weight measures. BMD at the femoral neck was measured via dual energy x-ray absorptiometry (DXA). We calculated sensitivity, specificity, positive predictive value, and negative predictive value for identifying African-American women with low BMD (T-Score < or = -2.0 SD) using five clinical decision rules: Age, Body Size, No Estrogen (ABONE), Osteoporosis Risk Assessment Instrument (ORAI), Osteoporosis Self-Assessment Tool (OST), Simple Calculated Osteoporosis Risk Estimation (SCORE), and body weight less than 70 kg. RESULTS: Approximately 30% of African-American women had low BMD, half of whom had osteoporosis (BMD T-Score < or = -2.5 SD). Sensitivity for identifying women with a low BMD (T-Score < or = -2.0 SD) ranged from 65.57-83.61%, while specificity ranged from 53.85-78.85%. Positive predictive values ranged from 80.95-87.91%, while negative predictive values ranged from 48.44-58.33%. CONCLUSION: Our data suggest that the clinical decision rules analyzed in this study have some usefulness for identifying postmenopausal African-American women with low BMD. However, there is a need to establish cut-points for these clinical decision rules in a larger, more diverse sample of African-American women. PMID:15040510

A prospective study of a quantitative PCR ELISA assay for the diagnosis of CMV pneumonia in lung and heart-transplant recipients.

PubMed

Barber, L; Egan, J J; Lomax, J; Haider, Y; Yonan, N; Woodcock, A A; Turner, A J; Fox, A J

2000-08-01

Qualitative polymerase chain reaction (PCR) for the identification of cytomegalovirus (CMV) infection has a low predictive value for the identification of CMV pneumonia. This study prospectively evaluated the application of a quantitative PCR Enzyme-Linked Immuno-Sorbent Assay (ELISA) assay in 9 lung- and 18 heart-transplant recipients who did not receive ganciclovir prophylaxis. DNA was collected from peripheral blood polymorphonuclear leucocytes (PMNL) posttransplantation. Oligonucleotide primers for the glycoprotein B gene (149 bp) were used in a PCR ELISA assay using an internal standard for quantitation. CMV disease was defined as histological evidence of end organ damage. The median level CMV genome equivalents in patients with CMV disease was 2665/2 x 10(5) PMNL (range 1,200 to 61,606) compared to 100 x 10(5) PMNL (range 20 to 855) with infection but no CMV disease (p = 0.036). All patients with CMV disease had genome equivalents levels of >1200/2 x 10(5) PMNL. A cut-off level of 1,200 PMNL had a positive predictive value for CMV disease of 100% and a negative predictive value of 100%. The first detection of levels of CMV genome equivalents above a level of 1200/2 x 10(5) PMNL was at a median of 58 days (range 47 to 147) posttransplant. Quantitative PCR assays for the diagnosis of CMV infection may predict patients at risk of CMV disease and thereby direct preemptive treatment to high-risk patients.

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation.

PubMed

Saatchi, Mahdi; McClure, Mathew C; McKay, Stephanie D; Rolf, Megan M; Kim, JaeWoo; Decker, Jared E; Taxis, Tasia M; Chapple, Richard H; Ramey, Holly R; Northcutt, Sally L; Bauck, Stewart; Woodward, Brent; Dekkers, Jack C M; Fernando, Rohan L; Schnabel, Robert D; Garrick, Dorian J; Taylor, Jeremy F

2011-11-28

Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

PubMed Central

2011-01-01

Background Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Methods Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Results Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. Conclusions These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy. PMID:22122853

Distance M-Me: A novel parameter having significant potential as a predictor of mandibular growth.

PubMed

Jain, Parul; Kaul, Rahul; Mukhopadhyay, Santanu; Saha, Subrata; Sarkar, Subir

2017-01-01

The purpose of the present study was to investigate the relationship of the measured distance between two mandibular points (distance M-Me) to chronological age and to find out whether the absolute values of distance M-Me could be classified age-wise into a unique range, which could be directly read for predicting the stage of mandibular growth. The study sample consists of lateral cephalometric records of 65 patients (34 females and 31 males; age range: 6-21 years). Chronological age was calculated in decimal years. Lateral cephalograms were assessed by two independent examiners. Points M and Me were located on the lateral cephalograms, and linear distance between them was measured. Pearson product-moment correlation coefficients showed a high correlation between chronological age and distance M-Me (0.746 for females and 0.869 for males, p < 0.01). When the values of distance M-Me were compared with chronological age, it was possible to make four age groups (for females and males separately), where each group showed a unique range of value for distance M-Me. The values increased with increasing age. Increase in value of distance M-Me with age, showing reduced individual variation, depicts a well-conserved linear dimension. Values of distance M-Me can be directly read for predicting the stage of mandibular growth and can be used as a valuable adjunct or substitute to chronological age.

Genetic relationships between carcass cut weights predicted from video image analysis and other performance traits in cattle.

PubMed

Pabiou, T; Fikse, W F; Amer, P R; Cromie, A R; Näsholm, A; Berry, D P

2012-09-01

The objective of this study was to quantify the genetic associations between a range of carcass-related traits including wholesale cut weights predicted from video image analysis (VIA) technology, and a range of pre-slaughter performance traits in commercial Irish cattle. Predicted carcass cut weights comprised of cut weights based on retail value: lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC) and very high value cuts (VHVC), as well as total meat, fat and bone weights. Four main sources of data were used in the genetic analyses: price data of live animals collected from livestock auctions, live-weight data and linear type collected from both commercial and pedigree farms as well as from livestock auctions and weanling quality recorded on-farm. Heritability of carcass cut weights ranged from 0.21 to 0.39. Genetic correlations between the cut traits and the other performance traits were estimated using a series of bivariate sire linear mixed models where carcass cut weights were phenotypically adjusted to a constant carcass weight. Strongest positive genetic correlations were obtained between predicted carcass cut weights and carcass value (min r g(MVC) = 0.35; max r(g(VHVC)) = 0.69), and animal price at both weaning (min r(g(MVC)) = 0.37; max r(g(VHVC)) = 0.66) and post weaning (min r(g(MVC)) = 0.50; max r(g(VHVC)) = 0.67). Moderate genetic correlations were obtained between carcass cut weights and calf price (min r g(HVC) = 0.34; max r g(LVC) = 0.45), weanling quality (min r(g(MVC)) = 0.12; max r (g(VHVC)) = 0.49), linear scores for muscularity at both weaning (hindquarter development: min r(g(MVC)) = -0.06; max r(g(VHVC)) = 0.46), post weaning (hindquarter development: min r(g(MVC)) = 0.23; max r(g(VHVC)) = 0.44). The genetic correlations between total meat weight were consistent with those observed with the predicted wholesale cut weights. Total fat and total bone weights were generally negatively correlated with carcass value, auction prices and weanling quality. Total bone weight was, however, positively correlated with skeletal scores at weaning and post weaning. These results indicate that some traits collected early in life are moderate-to-strongly correlated with carcass cut weights predicted from VIA technology. This information can be used to improve the accuracy of selection for carcass cut weights in national genetic evaluations.

Limited Sampling Strategy for the Prediction of Area Under the Curve (AUC) of Statins: Reliability of a Single Time Point for AUC Prediction for Pravastatin and Simvastatin.

PubMed

Srinivas, N R

2016-02-01

Statins are widely prescribed medicines and are also available in fixed dose combinations with other drugs to treat several chronic ailments. Given the safety issues associated with statins it may be important to assess feasibility of a single time concentration strategy for prediction of exposure (area under the curve; AUC). The peak concentration (Cmax) was used to establish relationship with AUC separately for pravastatin and simvastatin using published pharmacokinetic data. The regression equations generated for statins were used to predict the AUC values from various literature references. The fold difference of the observed divided by predicted values along with correlation coefficient (r) were used to judge the feasibility of the single time point approach. Both pravastatin and simvastatin showed excellent correlation of Cmax vs. AUC values with r value ≥ 0.9638 (p<0.001). The fold difference was within 0.5-fold to 2-fold for 220 out of 227 AUC predictions and >81% of the predicted values were in a narrower range of >0.75-fold but <1.5-fold difference. Predicted vs. observed AUC values showed excellent correlation for pravastatin (r=0.9708, n=115; p<0.001) and simvastatin (r=0.9810; n=117; p<0.001) suggesting the utility of Cmax for AUC predictions. On the basis of the present work, it is feasible to develop a single concentration time point strategy that coincides with Cmax occurrence for both pravastatin and simvastatin from a therapeutic drug monitoring perspective. © Georg Thieme Verlag KG Stuttgart · New York.

Radiation-MHD simulations for the development of a spark discharge channel.

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

Niederhaus, John Henry; Jorgenson, Roy E.; Warne, Larry K.

The growth of a cylindrical s park discharge channel in water and Lexan is studied using a series of one - dimensional simulations with the finite - element radiation - magnetohydrodynamics code ALEGRA. Computed solutions are analyzed in order to characterize the rate of growth and dynamics of the spark c hannels during the rising - current phase of the drive pulse. The current ramp rate is varied between 0.2 and 3.0 kA/ns, and values of the mechanical coupling coefficient K p are extracted for each case. The simulations predict spark channel expansion veloc ities primarily in the range ofmore » 2000 to 3500 m/s, channel pressures primarily in the range 10 - 40 GPa, and K p values primarily between 1.1 and 1.4. When Lexan is preheated, slightly larger expansion velocities and smaller K p values are predicted , but the o verall behavior is unchanged.« less

Determination of octanol-air partition coefficients and supercooled liquid vapor pressures of PAHs as a function of temperature: Application to gas-particle partitioning in an urban atmosphere

NASA Astrophysics Data System (ADS)

Odabasi, Mustafa; Cetin, Eylem; Sofuoglu, Aysun

Octanol-air partition coefficients ( KOA) for 14 polycyclic aromatic hydrocarbons (PAHs) were determined as a function of temperature using the gas chromatographic retention time method. log KOA values at 25° ranged over six orders of magnitude, between 6.34 (acenaphthylene) and 12.59 (dibenz[ a,h]anthracene). The determined KOA values were within factor of 0.7 (dibenz[ a,h]anthracene) to 15.1 (benz[ a]anthracene) of values calculated as the ratio of octanol-water partition coefficient to dimensionless Henry's law constant. Supercooled liquid vapor pressures ( PL) of 13 PAHs were also determined using the gas chromatographic retention time technique. Activity coefficients in octanol calculated using KOA and PL ranged between 3.2 and 6.2 indicating near-ideal solution behavior. Atmospheric concentrations measured in this study in Izmir, Turkey were used to investigate the partitioning of PAHs between particle and gas-phases. Experimental gas-particle partition coefficients ( Kp) were compared to the predictions of KOA absorption and KSA (soot-air partition coefficient) models. Octanol-based absorptive partitioning model predicted lower partition coefficients especially for relatively volatile PAHs. Ratios of measured/modeled partition coefficients ranged between 1.1 and 15.5 (4.5±6.0, average±SD) for KOA model. KSA model predictions were relatively better and measured to modeled ratios ranged between 0.6 and 5.6 (2.3±2.7, average±SD).

Diagnostic Inaccuracy of Smart Phone Applications for Melanoma Detection

PubMed Central

Wolf, Joel; Moreau, Jacqui; Akilov, Oleg; Patton, Timothy; English, Joseph C; Ho, Jon; Ferris, Laura Korb

2013-01-01

Objective To measure the performance of smart phone applications which evaluate photographs of skin lesions and provide the user feedback as to their likelihood of malignancy. Design Case-control diagnostic accuracy study Setting Academic dermatology department Participants Digital clinical images of pigmented cutaneous lesions (60 melanoma cases and 128 benign lesion controls), all with histologic diagnosis rendered by a board-certified dermatopathologist, obtained prior to biopsy in patients undergoing lesion removal as part of routine care. Main Outcome Measures Sensitivity, specificity, and positive and negative predictive values of four smart phone applications designed to aid non-clinician users in determining if their skin lesion is benign or malignant. Results Sensitivity of the four tested applications ranged from 6.8% to 98.1%. Specificity ranged from 30.4% to 93.7%. Positive predictive value ranged from 33.3% to 42.1%, and negative predictive value ranged from 65.4% to 97.0%. The highest sensitivity for melanoma diagnosis was observed for an application that sends the image directly to a board-certified dermatologist for analysis and the lowest sensitivity was observed for applications that use automated algorithms to analyze images. Conclusions The performance of smart phone applications in assessing melanoma risk is highly variable, and 3 out of 4 smart phone applications incorrectly classified 30% or more of melanomas as unconcerning. Reliance on these applications, which are not subject to regulatory oversight, in lieu of medical consultation, has the potential to delay the diagnosis of melanoma and to harm users. PMID:23325302

Genetic evaluation of lactation persistency for five breeds of dairy cattle.

PubMed

Cole, J B; Null, D J

2009-05-01

Cows with high lactation persistency tend to produce less milk than expected at the beginning of lactation and more than expected at the end. Best prediction of lactation persistency is calculated as a function of trait-specific standard lactation curves and linear regressions of test-day deviations on days in milk. Because regression coefficients are deviations from a tipping point selected to make yield and lactation persistency phenotypically uncorrelated it should be possible to use 305-d actual yield and lactation persistency to predict yield for lactations with later endpoints. The objectives of this study were to calculate (co)variance components and breeding values for best predictions of lactation persistency of milk (PM), fat (PF), protein (PP), and somatic cell score (PSCS) in breeds other than Holstein, and to demonstrate the calculation of prediction equations for 400-d actual milk yield. Data included lactations from Ayrshire, Brown Swiss, Guernsey (GU), Jersey (JE), and Milking Shorthorn (MS) cows calving since 1997. The number of sires evaluated ranged from 86 (MS) to 3,192 (JE), and mean sire estimated breeding value for PM ranged from 0.001 (Ayrshire) to 0.10 (Brown Swiss); mean estimated breeding value for PSCS ranged from -0.01 (MS) to -0.043 (JE). Heritabilities were generally highest for PM (0.09 to 0.15) and lowest for PSCS (0.03 to 0.06), with PF and PP having intermediate values (0.07 to 0.13). Repeatabilities varied considerably between breeds, ranging from 0.08 (PSCS in GU, JE, and MS) to 0.28 (PM in GU). Genetic correlations of PM, PF, and PP with PSCS were moderate and favorable (negative), indicating that increasing lactation persistency of yield traits is associated with decreases in lactation persistency of SCS, as expected. Genetic correlations among yield and lactation persistency were low to moderate and ranged from -0.55 (PP in GU) to 0.40 (PP in MS). Prediction equations for 400-d milk yield were calculated for each breed by regression of both 305-d yield and 305-d yield and lactation persistency on 400-d yield. Goodness-of-fit was very good for both models, but the addition of lactation persistency to the model significantly improved fit in all cases. Routine genetic evaluations for lactation persistency, as well as the development of prediction equations for several lactation end-points, may provide producers with tools to better manage their herds.

Accuracy of stroke volume variation in predicting fluid responsiveness: a systematic review and meta-analysis.

PubMed

Zhang, Zhongheng; Lu, Baolong; Sheng, Xiaoyan; Jin, Ni

2011-12-01

Stroke volume variation (SVV) appears to be a good predictor of fluid responsiveness in critically ill patients. However, a wide range of its predictive values has been reported in recent years. We therefore undertook a systematic review and meta-analysis of clinical trials that investigated the diagnostic value of SVV in predicting fluid responsiveness. Clinical investigations were identified from several sources, including MEDLINE, EMBASE, WANFANG, and CENTRAL. Original articles investigating the diagnostic value of SVV in predicting fluid responsiveness were considered to be eligible. Participants included critically ill patients in the intensive care unit (ICU) or operating room (OR) who require hemodynamic monitoring. A total of 568 patients from 23 studies were included in our final analysis. Baseline SVV was correlated to fluid responsiveness with a pooled correlation coefficient of 0.718. Across all settings, we found a diagnostic odds ratio of 18.4 for SVV to predict fluid responsiveness at a sensitivity of 0.81 and specificity of 0.80. The SVV was of diagnostic value for fluid responsiveness in OR or ICU patients monitored with the PiCCO or the FloTrac/Vigileo system, and in patients ventilated with tidal volume greater than 8 ml/kg. SVV is of diagnostic value in predicting fluid responsiveness in various settings.

Predictive value of cognition for different domains of outcome in recent-onset schizophrenia.

PubMed

Holthausen, Esther A E; Wiersma, Durk; Cahn, Wiepke; Kahn, René S; Dingemans, Peter M; Schene, Aart H; van den Bosch, Robert J

2007-01-15

The aim of this study was to see whether and how cognition predicts outcome in recent-onset schizophrenia in a large range of domains such as course of illness, self-care, interpersonal functioning, vocational functioning and need for care. At inclusion, 115 recent-onset patients were tested on a cognitive battery and 103 patients participated in the follow-up 2 years after inclusion. Differences in outcome between cognitively normal and cognitively impaired patients were also analysed. Cognitive measures at inclusion did not predict number of relapses, activities of daily living and interpersonal functioning. Time in psychosis or in full remission, as well as need for care, were partly predicted by specific cognitive measures. Although statistically significant, the predictive value of cognition with regard to clinical outcome was limited. There was a significant difference between patients with and without cognitive deficits in competitive employment status and vocational functioning. The predictive value of cognition for different social outcome domains varies. It seems that cognition most strongly predicts work performance, where having a cognitive deficit, regardless of the nature of the deficit, acts as a rate-limiting factor.

Comparison of Urine Albumin-to-Creatinine Ratio (ACR) Between ACR Strip Test and Quantitative Test in Prediabetes and Diabetes

PubMed Central

Cho, Seon; Kim, Suyoung; Cho, Han-Ik

2017-01-01

Background Albuminuria is generally known as a sensitive marker of renal and cardiovascular dysfunction. It can be used to help predict the occurrence of nephropathy and cardiovascular disorders in diabetes. Individuals with prediabetes have a tendency to develop macrovascular and microvascular pathology, resulting in an increased risk of retinopathy, cardiovascular diseases, and chronic renal diseases. We evaluated the clinical value of a strip test for measuring the urinary albumin-to-creatinine ratio (ACR) in prediabetes and diabetes. Methods Spot urine samples were obtained from 226 prediabetic and 275 diabetic subjects during regular health checkups. Urinary ACR was measured by using strip and laboratory quantitative tests. Results The positive rates of albuminuria measured by using the ACR strip test were 15.5% (microalbuminuria, 14.6%; macroalbuminuria, 0.9%) and 30.5% (microalbuminuria, 25.1%; macroalbuminuria, 5.5%) in prediabetes and diabetes, respectively. In the prediabetic population, the sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the ACR strip method were 92.0%, 94.0%, 65.7%, 99.0%, and 93.8%, respectively; the corresponding values in the diabetic population were 80.0%, 91.6%, 81.0%, 91.1%, and 88.0%, respectively. The median [interquartile range] ACR values in the strip tests for measurement ranges of <30, 30-300, and >300 mg/g were 9.4 [6.3-15.4], 46.9 [26.5-87.7], and 368.8 [296.2-575.2] mg/g, respectively, using the laboratory method. Conclusions The ACR strip test showed high sensitivity, specificity, and negative predictive value, suggesting that the test can be used to screen for albuminuria in cases of prediabetes and diabetes. PMID:27834062

The prognostic value of panoramic radiography of inferior alveolar nerve damage after mandibular third molar removal: retrospective study of 400 cases.

PubMed

Szalma, József; Lempel, Edina; Jeges, Sára; Szabó, Gyula; Olasz, Lajos

2010-02-01

The aim of the study was to estimate the accuracy of panoramic radiographic signs predicting inferior alveolar nerve (IAN) paresthesia after lower third molar removal. In a case-control study the sample was composed of 41 cases with postoperative IAN paresthesia and 359 control cases without it. The collected data included "classic" specific signs indicating a close spatial relationship between third molar root and inferior alveolar canal (IAC), root curvatures, and the extent of IAC-root tip overlap. Bivariate and multivariate logistic regression analyses were completed to estimate the association between radiographic findings and IAN paresthesia. The multivariate logistic analysis identified 3 signs significantly associated with IAN paresthesia (P < .001): interruption of the superior cortex of the canal wall, diversion of the canal, and darkening of the root. The sensitivities and specificities ranged from 14.6% to 68.3% and from 85.5% to 96.9%, respectively. The positive predictive values, calculated to factor a 1.1% prevalence of paresthesia, ranged from 3.6% to 10.9%, whereas the negative predictive values >99%. Panoramic radiography is an inadequate screening method for predicting IAN paresthesia after mandibular third molar removal. Copyright (c) 2010 Mosby, Inc. All rights reserved.

AERMOD performance evaluation for three coal-fired electrical generating units in Southwest Indiana.

PubMed

Frost, Kali D

2014-03-01

An evaluation of the steady-state dispersion model AERMOD was conducted to determine its accuracy at predicting hourly ground-level concentrations of sulfur dioxide (SO2) by comparing model-predicted concentrations to a full year of monitored SO2 data. The two study sites are comprised of three coal-fired electrical generating units (EGUs) located in southwest Indiana. The sites are characterized by tall, buoyant stacks,flat terrain, multiple SO2 monitors, and relatively isolated locations. AERMOD v12060 and AERMOD v12345 with BETA options were evaluated at each study site. For the six monitor-receptor pairs evaluated, AERMOD showed generally good agreement with monitor values for the hourly 99th percentile SO2 design value, with design value ratios that ranged from 0.92 to 1.99. AERMOD was within acceptable performance limits for the Robust Highest Concentration (RHC) statistic (RHC ratios ranged from 0.54 to 1.71) at all six monitors. Analysis of the top 5% of hourly concentrations at the six monitor-receptor sites, paired in time and space, indicated poor model performance in the upper concentration range. The amount of hourly model predicted data that was within a factor of 2 of observations at these higher concentrations ranged from 14 to 43% over the six sites. Analysis of subsets of data showed consistent overprediction during low wind speed and unstable meteorological conditions, and underprediction during stable, low wind conditions. Hourly paired comparisons represent a stringent measure of model performance; however given the potential for application of hourly model predictions to the SO2 NAAQS design value, this may be appropriate. At these two sites, AERMOD v12345 BETA options do not improve model performance. A regulatory evaluation of AERMOD utilizing quantile-quantile (Q-Q) plots, the RHC statistic, and 99th percentile design value concentrations indicates that model performance is acceptable according to widely accepted regulatory performance limits. However, a scientific evaluation examining hourly paired monitor and model values at concentrations of interest indicates overprediction and underprediction bias that is outside of acceptable model performance measures. Overprediction of 1-hr SO2 concentrations by AERMOD presents major ramifications for state and local permitting authorities when establishing emission limits.

Enthalpy measurement of coal-derived liquids. Combined quarterly technical progress reports, April-June 1979 and July-September 1979. [Effect of association

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

Kidnay, A.J.; Yesavage, V.F.

1979-01-01

Enthalpy measurements on a coal-derived naphtha and middle distillate, both produced by the SRC-II process, were made using flow calorimetry. The accuracy of the measurements, as reported by Omid, was within +- 1% of the measured enthalpy differences, ..delta..H. Experimental data for the naphtha were obtained over a pressure range of 100-300 psia and temperatures from 148/sup 0/ to 456/sup 0/F. The middle distillate enthalpy measurements were made in the pressure and temperature ranges of 130 to 1000 psia, and 157/sup 0/ to 675/sup 0/F, respectively. The methods of prediction of enthalpy developed for petroleum fractions were unsatisfactory when appliedmore » to the above data. A negative bias was observed in the predicted enthalpy values for several of the coal-liquids. Based on these results, it was theorized that the high experimental enthalpy values for coal-liquids were due to an energy of association attributed, primarily, to hydrogen-bonding effects. The petroleum-fraction enthalpy correlations were then tested on the experimental data for pure compounds, both associating and non-associating. The predicted values compared very well with the experimental results for non-associating model compounds. However, for associating model compounds the predicted enthalpy values were considerably lower than their experimental data. This served to confirm the basic premise that the high experimental enthalpy values, for model compounds and coal liquids, were a direct consequence of an energy of association attributed, primarily, to hydrogen-bonding effects.« less

Rate of value change in Pennsylvania timber stands

Treesearch

Owen W. Herrick

1984-01-01

Data from remeasured Pennsylvania forest inventory plots revealed that during a 13-year period the compound rate of value change in uncut hardwood forest stands averaged 4.7 percent, and ranged from -5.5 to 18.8 percent. No well-defined means for predicting a stand's rate of value change could be identified, However, some measures of initial stand condition can be...

Determination of the saturated film conductivity to improve the EMFX model in describing the soil hydraulic properties over the entire moisture range

NASA Astrophysics Data System (ADS)

Wang, Yunquan; Ma, Jinzhu; Guan, Huade; Zhu, Gaofeng

2017-06-01

Difficulty in measuring hydraulic conductivity, particularly under dry conditions, calls for methods of predicting the conductivity from easily obtained soil properties. As a complement to the recently published EMFX model, a method based on two specific suction conditions is proposed to estimate saturated film conductivity from the soil water retention curve. This method reduces one fitting parameter in the previous EMFX model, making it possible to predict the hydraulic conductivity from the soil water retention curve over the complete moisture range. Model performance is evaluated with published data of soils in a broad texture range from sand to clay. The testing results indicate that 1) the modified EMFX model (namely the EMFX-K model), incorporating both capillary and adsorption forces, provides good agreement with the conductivity data over the entire moisture range; 2) a value of 0.5 for the tortuosity factor in the EMFX-K model as that in the Mualem's model gives comparable estimation of the relative conductivity associated with the capillary force; and 3) a value of -1.0 × 10-20 J for the Hamaker constant, rather than the commonly used value of -6.0 × 10-20 J, appears to be more appropriate to represent solely the effect of the van der Waals forces and to predict the film conductivity. In comparison with the commonly used van Genuchten-Mualem model, the EMFX-K model significantly improves the prediction of hydraulic conductivity under dry conditions. The sensitivity analysis result suggests that the uncertainty in the film thickness estimation is important in explaining the model underestimation of hydraulic conductivity for the soils with fine texture, in addition to the uncertainties from the measurements and the model structure. High quality data that cover the complete moisture range for a variety of soil textures are required to further test the method.

Unchained Melody: Revisiting the Estimation of SF-6D Values

PubMed Central

Craig, Benjamin M.

2015-01-01

Purpose In the original SF-6D valuation study, the analytical design inherited conventions that detrimentally affected its ability to predict values on a quality-adjusted life year (QALY) scale. Our objective is to estimate UK values for SF-6D states using the original data and multi-attribute utility (MAU) regression after addressing its limitations and to compare the revised SF-6D and EQ-5D value predictions. Methods Using the unaltered data (611 respondents, 3503 SG responses), the parameters of the original MAU model were re-estimated under 3 alternative error specifications, known as the instant, episodic, and angular random utility models. Value predictions on a QALY scale were compared to EQ-5D3L predictions using the 1996 Health Survey for England. Results Contrary to the original results, the revised SF-6D value predictions range below 0 QALYs (i.e., worse than death) and agree largely with EQ-5D predictions after adjusting for scale. Although a QALY is defined as a year in optimal health, the SF-6D sets a higher standard for optimal health than the EQ-5D-3L; therefore, it has larger units on a QALY scale by construction (20.9% more). Conclusions Much of the debate in health valuation has focused on differences between preference elicitation tasks, sampling, and instruments. After correcting errant econometric practices and adjusting for differences in QALY scale between the EQ-5D and SF-6D values, the revised predictions demonstrate convergent validity, making them more suitable for UK economic evaluations compared to original estimates. PMID:26359242

The Aristotle score predicts mortality after surgery of patent ductus arteriosus in preterm infants.

PubMed

Chang, Yun Hee; Lee, Jae Young; Kim, Jeong Eun; Kim, Ji-yong; Youn, YoungAh; Lee, Eun-Jung; Moon, Sena; Lee, Ju Young; Sung, In Kyung

2013-09-01

Outcomes after surgical ligation of patent ductus arteriosus (PDA) in preterm infants are often complicated by prematurity associated comorbidities. The Aristotle comprehensive complexity score (ACCS) has been proposed as a useful tool for complexity adjustment in the analysis of outcome after congenital heart surgery. The aims of this study were to define preoperative risk factors for mortality and to demonstrate the usefulness of ACCS to predict mortality after surgical ligation of PDA in the preterm. Included were 49 preterm babies (≤35 weeks of gestation) who had surgical ligation of PDA between May 2009 and July 2012. Median gestational age was 27.6 weeks (range, 23 to 35 weeks) and median birth weight was 1,040 g (range, 520 to 2,280 g). Median age at operation was 15 days (range, 4 to 44 days) and median weight was 1,120 g (range, 400 to 2,880 g). Initial oral ibuprofen was ineffective in 24 patients and contraindicated in 25. All surgical ligations were done at bedside in the neonatal intensive care unit. Preoperative clinical and laboratory profiles were reviewed and ACCS was derived. Eight of 49 patients (16.3%) died at a median of 14 days (range, 2 to 73 days) after PDA ligation. Patients who had contraindications for oral ibuprofen (odds ratio [OR] 8.94; p=0.049), coagulopathy (OR 12.13; p=0.025), renal dysfunction (OR 28.88; p=0.003), intraventricular hemorrhage greater than grade II or seizure (OR 34.00; p=0.002), and ACCS points (OR 29.594; p<0.05) were significantly associated with an increased risk for mortality. Among the risk factors, ACCS showed the largest area under curve (0.991) by receiver-operating characteristic curve analysis. Optimal cutoff value of ACCS for mortality were 15 or greater, with sensitivity of 87.5%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 97.6%. The ACCS, especially for procedure-independent complexity factors, is a useful tool to predict mortality after ligation of PDA in preterm infants. Copyright © 2013 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Influence of Temperature, Relative Humidity, and Soil Properties on the Soil-Air Partitioning of Semivolatile Pesticides: Laboratory Measurements and Predictive Models.

PubMed

Davie-Martin, Cleo L; Hageman, Kimberly J; Chin, Yu-Ping; Rougé, Valentin; Fujita, Yuki

2015-09-01

Soil-air partition coefficient (Ksoil-air) values are often employed to investigate the fate of organic contaminants in soils; however, these values have not been measured for many compounds of interest, including semivolatile current-use pesticides. Moreover, predictive equations for estimating Ksoil-air values for pesticides (other than the organochlorine pesticides) have not been robustly developed, due to a lack of measured data. In this work, a solid-phase fugacity meter was used to measure the Ksoil-air values of 22 semivolatile current- and historic-use pesticides and their degradation products. Ksoil-air values were determined for two soils (semiarid and volcanic) under a range of environmentally relevant temperature (10-30 °C) and relative humidity (30-100%) conditions, such that 943 Ksoil-air measurements were made. Measured values were used to derive a predictive equation for pesticide Ksoil-air values based on temperature, relative humidity, soil organic carbon content, and pesticide-specific octanol-air partition coefficients. Pesticide volatilization losses from soil, calculated with the newly derived Ksoil-air predictive equation and a previously described pesticide volatilization model, were compared to previous results and showed that the choice of Ksoil-air predictive equation mainly affected the more-volatile pesticides and that the way in which relative humidity was accounted for was the most critical difference.

Clinical value of CT-based preoperative software assisted lung lobe volumetry for predicting postoperative pulmonary function after lung surgery

NASA Astrophysics Data System (ADS)

Wormanns, Dag; Beyer, Florian; Hoffknecht, Petra; Dicken, Volker; Kuhnigk, Jan-Martin; Lange, Tobias; Thomas, Michael; Heindel, Walter

2005-04-01

This study was aimed to evaluate a morphology-based approach for prediction of postoperative forced expiratory volume in one second (FEV1) after lung resection from preoperative CT scans. Fifteen Patients with surgically treated (lobectomy or pneumonectomy) bronchogenic carcinoma were enrolled in the study. A preoperative chest CT and pulmonary function tests before and after surgery were performed. CT scans were analyzed by prototype software: automated segmentation and volumetry of lung lobes was performed with minimal user interaction. Determined volumes of different lung lobes were used to predict postoperative FEV1 as percentage of the preoperative values. Predicted FEV1 values were compared to the observed postoperative values as standard of reference. Patients underwent lobectomy in twelve cases (6 upper lobes; 1 middle lobe; 5 lower lobes; 6 right side; 6 left side) and pneumonectomy in three cases. Automated calculation of predicted postoperative lung function was successful in all cases. Predicted FEV1 ranged from 54% to 95% (mean 75% +/- 11%) of the preoperative values. Two cases with obviously erroneous LFT were excluded from analysis. Mean error of predicted FEV1 was 20 +/- 160 ml, indicating absence of systematic error; mean absolute error was 7.4 +/- 3.3% respective 137 +/- 77 ml/s. The 200 ml reproducibility criterion for FEV1 was met in 11 of 13 cases (85%). In conclusion, software-assisted prediction of postoperative lung function yielded a clinically acceptable agreement with the observed postoperative values. This method might add useful information for evaluation of functional operability of patients with lung cancer.

Two-question depression-screeners - the solution to all problems?

PubMed

Albani, Cornelia; Bailer, Harald; Blaser, Gerd; Brähler, Elmar; Geyer, Michael; Grulke, Norbert

2006-04-01

Depression constitutes a considerable issue in medicine and it is anticipated that the amount of people suffering from affective disorders will increase significantly. It would be useful to have a simple, fast screening procedure which would help detect depression. In four recently published articles a two-question depression-screener is recommended. Sensitivity, specificity, likelihood ratios, negative and positive predictive values were compared. For four different clinical samples and one sample that was representative of the German population the prevalence for depression ranged from 6.9 % to 18.1 %. Sensitivity and specificity reached values from 72.6 % to 96.6 % and from 56.9 % to 90.0 % respectively. All negative predictive values were high (< 97 %) opposed to positive predictive values (17.8 % to 38.5 %). Overall, it seems that the two-question screenings are well suited for the exclusion of a major depression. It is possible that regular screening could further lower the percentage of undiagnosed cases.

Predictions of CD4 lymphocytes’ count in HIV patients from complete blood count

PubMed Central

2013-01-01

Background HIV diagnosis, prognostic and treatment requires T CD4 lymphocytes’ number from flow cytometry, an expensive technique often not available to people in developing countries. The aim of this work is to apply a previous developed methodology that predicts T CD4 lymphocytes’ value based on total white blood cell (WBC) count and lymphocytes count applying sets theory, from information taken from the Complete Blood Count (CBC). Methods Sets theory was used to classify into groups named A, B, C and D the number of leucocytes/mm3, lymphocytes/mm3, and CD4/μL3 subpopulation per flow cytometry of 800 HIV diagnosed patients. Union between sets A and C, and B and D were assessed, and intersection between both unions was described in order to establish the belonging percentage to these sets. Results were classified into eight ranges taken by 1000 leucocytes/mm3, calculating the belonging percentage of each range with respect to the whole sample. Results Intersection (A ∪ C) ∩ (B ∪ D) showed an effectiveness in the prediction of 81.44% for the range between 4000 and 4999 leukocytes, 91.89% for the range between 3000 and 3999, and 100% for the range below 3000. Conclusions Usefulness and clinical applicability of a methodology based on sets theory were confirmed to predict the T CD4 lymphocytes’ value, beginning with WBC and lymphocytes’ count from CBC. This methodology is new, objective, and has lower costs than the flow cytometry which is currently considered as Gold Standard. PMID:24034560

Comparison of three-view thoracic radiography and computed tomography for detection of pulmonary nodules in dogs with neoplasia.

PubMed

Armbrust, Laura J; Biller, David S; Bamford, Aubrey; Chun, Ruthanne; Garrett, Laura D; Sanderson, Michael W

2012-05-01

To compare the detection of pulmonary nodules by use of 3-view thoracic radiography and CT in dogs with confirmed neoplasia. Prospective case series. 33 dogs of various breeds. 3 interpreters independently evaluated 3-view thoracic radiography images. The location and size of pulmonary nodules were recorded. Computed tomographic scans of the thorax were obtained and evaluated by a single interpreter. The location, size, margin, internal architecture, and density of pulmonary nodules were recorded. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for thoracic radiography (with CT as the gold standard). 21 of 33 (64%) dogs had pulmonary nodules or masses detected on CT. Of the dogs that had positive CT findings, 17 of 21 (81%) had pulmonary nodules or masses detected on radiographs by at least 1 interpreter. Sensitivity of radiography ranged from 71% to 95%, and specificity ranged from 67% to 92%. Radiography had a positive predictive value of 83% to 94% and a negative predictive value of 65% to 89%. The 4 dogs that were negative for nodules on thoracic radiography but positive on CT were all large-breed to giant-breed dogs with osteosarcoma. CT was more sensitive than radiography for detection of pulmonary nodules. This was particularly evident in large-breed to giant-breed dogs. Thoracic CT is recommended in large-breed to giant-breed dogs with osteosarcoma if the detection of pulmonary nodules will change treatment.

Can acceleromyography detect low levels of residual paralysis? A probability approach to detect a mechanomyographic train-of-four ratio of 0.9.

PubMed

Capron, Florent; Alla, Francois; Hottier, Claire; Meistelman, Claude; Fuchs-Buder, Thomas

2004-05-01

The incidence of residual paralysis, i.e., a mechanomyographic train-of-four (TOF) ratio (T4/T1) less than 0.9, remains frequent. Routine acceleromyography has been proposed to detect residual paralysis in clinical practice. Although acceleromyographic data are easy to obtain, they differ from mechanomyographic data, with which they are not interchangeable. The current study aimed to determine (1) the acceleromyographic TOF ratio that detects residual paralysis with a 95% probability, and (2) the impact of calibration and normalization on this predictive acceleromyographic value. In 60 patients, recovery from neuromuscular block was assessed simultaneously with mechanomyography and acceleromyography. To obtain calibrated acceleromyographic TOF ratios in group A, the implemented calibration modus 2 was activated in the TOF-Watch S; to obtain uncalibrated acceleromyographic TOF ratios in group B, the current was manually set at 50 mA (n = 30 for each). In addition, data in group B were normalized (i.e., dividing the final TOF ratio by the baseline value). The agreement between mechanomyography and acceleromyography was assessed by calculating the intraclass correlation coefficient. Negative predictive values were calculated for detecting residual paralysis from acceleromyographic TOFs of 0.9, 0.95, and 1.0. : For a mechanomyographic TOF of 0.9 or greater, the corresponding acceleromyographic TOF was 0.95 (range, 0.86-1.0), and the negative predictive values for acceleromyographic TOFs of 0.9, 0.95, and 1.0 were 37% (95% CI, 20-56%), 70% (95% CI, 51-85%), and 97% (95% CI, 83-100%), respectively. Group B: Without normalization, an acceleromyographic TOF of 0.97 (range, 0.68-1.18) corresponded to a mechanomyographic TOF of 0.9 or greater, with negative predictive values for acceleromyographic TOFs of 0.9, 0.95, and 1.0 being 40% (95% CI, 23-59%), 60% (95% CI, 41-77%), and 77% (95% CI, 58-90%), respectively. After normalization, an acceleromyographic TOF of 0.89 (range, 0.63-1.06) corresponded to a mechanomyographic TOF of 0.9 or greater, and the negative predictive values of acceleromyographic TOFs of 0.9, 0.95, and 1.0 were 89% (95% CI, 70-98%), 92% (95% CI, 75-99%), and 96% (95% CI, 80-100%), respectively. To exclude residual paralysis reliably when using acceleromyography, TOF recovery to 1.0 is mandatory.

Prediction of octanol-air partition coefficients for polychlorinated biphenyls (PCBs) using 3D-QSAR models.

PubMed

Chen, Ying; Cai, Xiaoyu; Jiang, Long; Li, Yu

2016-02-01

Based on the experimental data of octanol-air partition coefficients (KOA) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using logKOA values as the dependent variable with the Sybyl software to predict the KOA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient (q(2)) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825-0.969 (>0.5), the correlation coefficient (r(2)) obtained was in the range of 0.957-1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070-0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the logKOA. The correlation analysis of the relationship between the number of Cl atoms and the average logKOA values of PCBs indicated that logKOA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher logKOA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, logKOA decreased when substituents possessed electropositive groups at the 2-, 3-, 3'-, 5- and 6- positions, which could reduce the PCB migration ability. These results are expected to be beneficial in predicting logKOA values of PCB homologues and derivatives and in providing a theoretical foundation for further elucidation of the global migration behaviour of PCBs. Copyright © 2015 Elsevier Inc. All rights reserved.

A Comparative Study on Johnson Cook, Modified Zerilli-Armstrong and Arrhenius-Type Constitutive Models to Predict High-Temperature Flow Behavior of Ti-6Al-4V Alloy in α + β Phase

NASA Astrophysics Data System (ADS)

Cai, Jun; Wang, Kuaishe; Han, Yingying

2016-03-01

True stress and true strain values obtained from isothermal compression tests over a wide temperature range from 1,073 to 1,323 K and a strain rate range from 0.001 to 1 s-1 were employed to establish the constitutive equations based on Johnson Cook, modified Zerilli-Armstrong (ZA) and strain-compensated Arrhenius-type models, respectively, to predict the high-temperature flow behavior of Ti-6Al-4V alloy in α + β phase. Furthermore, a comparative study has been made on the capability of the three models to represent the elevated temperature flow behavior of Ti-6Al-4V alloy. Suitability of the three models was evaluated by comparing both the correlation coefficient R and the average absolute relative error (AARE). The results showed that the Johnson Cook model is inadequate to provide good description of flow behavior of Ti-6Al-4V alloy in α + β phase domain, while the predicted values of modified ZA model and the strain-compensated Arrhenius-type model could agree well with the experimental values except under some deformation conditions. Meanwhile, the modified ZA model could track the deformation behavior more accurately than other model throughout the entire temperature and strain rate range.

Analysis on Experimental Investigation and Mathematical Modeling of Incompressible Flow Through Ceramic Foam Filters

NASA Astrophysics Data System (ADS)

Akbarnejad, Shahin; Jonsson, Lage Tord Ingemar; Kennedy, Mark William; Aune, Ragnhild Elizabeth; Jönsson, Pӓr Göran

2016-08-01

This paper presents experimental results of pressure drop measurements on 30, 50, and 80 pores per inch (PPI) commercial alumina ceramic foam filters (CFF) and compares the obtained pressure drop profiles to numerically modeled values. In addition, it is aimed at investigating the adequacy of the mathematical correlations used in the analytical and the computational fluid dynamics (CFD) simulations. It is shown that the widely used correlations for predicting pressure drop in porous media continuously under-predict the experimentally obtained pressure drop profiles. For analytical predictions, the negative deviations from the experimentally obtained pressure drop using the unmodified Ergun and Dietrich equations could be as high as 95 and 74 pct, respectively. For the CFD predictions, the deviation to experimental results is in the range of 84.3 to 88.5 pct depending on filter PPI. Better results can be achieved by applying the Forchheimer second-order drag term instead of the Brinkman-Forchheimer drag term. Thus, the final deviation of the CFD model estimates lie in the range of 0.3 to 5.5 pct compared to the measured values.

Prediction of coal grindability from exploration data

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

Gomez, M.; Hazen, K.

1970-08-01

A general prediction model for the Hardgrove grindability index was constructed from 735 coal samples using the proximate analysis, heating value, and sulfur content. The coals used to develop the general model ranged in volatile matter from 12.8 to 49.2 percent, dry basis, and had grindability indexes ranging from 35 to 121. A restricted model applicable to bituminous coals having grindabilities in the 40 to 110 range was developed from the proximate analysis and the petrographic composition of the coal. The prediction of coal grindability within a single seam was also investigated. The results reported support the belief that mechanicalmore » properties of the coal are related to both chemical and petrographic factors of the coal. The mechanical properties coal may be forecast in advance of mining, because the variables used as input to the prediction models can be measured from drill core samples collected during exploration.« less

Accuracy of genomic prediction using deregressed breeding values estimated from purebred and crossbred offspring phenotypes in pigs.

PubMed

Hidalgo, A M; Bastiaansen, J W M; Lopes, M S; Veroneze, R; Groenen, M A M; de Koning, D-J

2015-07-01

Genomic selection is applied to dairy cattle breeding to improve the genetic progress of purebred (PB) animals, whereas in pigs and poultry the target is a crossbred (CB) animal for which a different strategy appears to be needed. The source of information used to estimate the breeding values, i.e., using phenotypes of CB or PB animals, may affect the accuracy of prediction. The objective of our study was to assess the direct genomic value (DGV) accuracy of CB and PB pigs using different sources of phenotypic information. Data used were from 3 populations: 2,078 Dutch Landrace-based, 2,301 Large White-based, and 497 crossbreds from an F1 cross between the 2 lines. Two female reproduction traits were analyzed: gestation length (GLE) and total number of piglets born (TNB). Phenotypes used in the analyses originated from offspring of genotyped individuals. Phenotypes collected on CB and PB animals were analyzed as separate traits using a single-trait model. Breeding values were estimated separately for each trait in a pedigree BLUP analysis and subsequently deregressed. Deregressed EBV for each trait originating from different sources (CB or PB offspring) were used to study the accuracy of genomic prediction. Accuracy of prediction was computed as the correlation between DGV and the DEBV of the validation population. Accuracy of prediction within PB populations ranged from 0.43 to 0.62 across GLE and TNB. Accuracies to predict genetic merit of CB animals with one PB population in the training set ranged from 0.12 to 0.28, with the exception of using the CB offspring phenotype of the Dutch Landrace that resulted in an accuracy estimate around 0 for both traits. Accuracies to predict genetic merit of CB animals with both parental PB populations in the training set ranged from 0.17 to 0.30. We conclude that prediction within population and trait had good predictive ability regardless of the trait being the PB or CB performance, whereas using PB population(s) to predict genetic merit of CB animals had zero to moderate predictive ability. We observed that the DGV accuracy of CB animals when training on PB data was greater than or equal to training on CB data. However, when results are corrected for the different levels of reliabilities in the PB and CB training data, we showed that training on CB data does outperform PB data for the prediction of CB genetic merit, indicating that more CB animals should be phenotyped to increase the reliability and, consequently, accuracy of DGV for CB genetic merit.

How useful are ARFI elastography cut-off values proposed by meta-analysis for predicting the significant fibrosis and compensated liver cirrhosis?

PubMed

Bota, Simona; Sporea, Ioan; Sirli, Roxana; Popescu, Alina; Gradinaru-Tascau, Oana

2015-06-01

To evaluate how often do we "miss" chronic hepatitis C patients with at least significant fibrosis (F>/=2) and those with compensated cirrhosis, by using Acoustic Radiation Force Impulse (ARFI) elastography cut-off values proposed by meta-analysis. Our study included 132 patients with chronic hepatitis C, evaluated by means of ARFI and liver biopsy (LB), in the same session. Reliable measurements were defined as: median value of 10 liver stiffness (LS) measurements with a success rate>/=60% and an interquartile range interval<30%. For predicting F>/=2 and F=4 we used the LS cut-offs proposed in the last published meta-analysis: 1.35 m/s and 1.87 m/s, respectively. Reliable LS measurements by means of ARFI were obtained in 117 patients (87.9%). In our study, 58 patients (49.6%) had LS values <1.35 m/s; from these 75.8% had F>/=2 in LB. From the 59 patients (50.4%) with LS values>/=1.35 m/s, only 6.8% had F0 or F1 in LB. Also, in our study, 88 patients (75.3%) had LS values <1.87 m/s; from these only 2.2 % had F4 in LB. From the 29 patients (24.7%) with LS values>/=1.87 m/s, 41.3% had F4 in LB. Both for prediction of at least significant fibrosis and liver cirrhosis, higher aminotransferases levels were associated with wrongly classified patients, in univariate and multivariate analysis. ARFI elastography had a very good positive predictive value (93.2%) for predicting the presence of significant fibrosis and excellent negative predictive value (97.8%) for excluding the presence of compensated liver cirrhosis.

Heat Transfer to 36.75 and 45 degree Swept Blunt Leading Edges in Free Flight at Mach Numbers from 1.70 to 2.99 and From 2.50 to 4.05

NASA Technical Reports Server (NTRS)

ONeal, Robert L.

1960-01-01

A flight investigation has been conducted to study the heat transfer to swept-wing leading edges. A rocket-powered model was used for the investigation and provided data for Mach number ranges of 1.78 to 2.99 and 2.50 to 4.05 with corresponding free-stream Reynolds number per foot ranges of 13.32 x 10(exp 6) to 19.90 x 10(exp 6) and 2.85 x 10(exp 6) to 4.55 x 10(exp 6). The leading edges employed were cylindrically blunted wedges ', three of which were swept 450 with leading-edge diameters of 1/4, 1/2, and 3/4 inch and one swept 36-750 with a leading-edge diameter of 1/2 inch. In the high Reynolds number range, measured values of heat transfer were found to be much higher than those predicted by laminar theory and at the larger values of leading-edge diameter were approaching the values predicted by turbulent theory. For the low Reynolds number range a comparison between measured and theoretical heat transfer showed that increasing the leading-edge diameter resulted in turbulent flow on the cylindrical portion of the leading edge.

Diagnostic value of C-reactive protein to rule out infectious complications after major abdominal surgery: a systematic review and meta-analysis.

PubMed

Gans, Sarah L; Atema, Jasper J; van Dieren, Susan; Groot Koerkamp, Bas; Boermeester, Marja A

2015-07-01

Infectious complications occur frequently after major abdominal surgery and have a major influence on patient outcome and hospital costs. A marker that can rule out postoperative infectious complications (PICs) could aid patient selection for safe and early hospital discharge. C-reactive protein (CRP) is a widely available, fast, and cheap marker that might be of value in detecting PIC. Present meta-analysis evaluates the diagnostic value of CRP to rule out PIC following major abdominal surgery, aiding patient selection for early discharge. A systematic literature search of Medline, PubMed, and Cochrane was performed identifying all prospective studies evaluating the diagnostic value of CRP after abdominal surgery. Meta-analysis was performed according to the PRISMA statement. Twenty-two studies were included for qualitative analysis of which 16 studies were eligible for meta-analysis, representing 2215 patients. Most studies analyzed the value of CRP in colorectal surgery (eight studies). The pooled negative predictive value (NPV) improved each day after surgery up to 90% at postoperative day (POD) 3 for a pooled CRP cutoff of 159 mg/L (range 92-200). Maximum predictive values for PICs were reached on POD 5 for a pooled CRP cutoff of 114 mg/L (range 48-150): a pooled sensitivity of 86% (95% confidence interval (CI) 79-91%), specificity of 86% (95% CI 75-92%), and a positive predictive value of 64% (95% CI 49-77%). The pooled sensitivity and specificity were significantly higher on POD 5 than on other PODs (p < 0.001). Infectious complications after major abdominal surgery are very unlikely in patients with a CRP below 159 mg/L on POD 3. This can aid patient selection for safe and early hospital discharge and prevent overuse of imaging.

Real-ear-to-coupler difference predictions as a function of age for two coupling procedures.

PubMed

Bagatto, Marlene P; Scollie, Susan D; Seewald, Richard C; Moodie, K Shane; Hoover, Brenda M

2002-09-01

The predicted real-ear-to-coupler difference (RECD) values currently used in pediatric hearing instrument prescription methods are based on 12-month age range categories and were derived from measures using standard acoustic immittance probe tips. Consequently, the purpose of this study was to develop normative RECD predicted values for foam/acoustic immittance tips and custom earmolds across the age continuum. To this end, RECD data were collected on 392 infants and children (141 with acoustic immittance tips, 251 with earmolds) to develop normative regression equations for use in deriving continuous age predictions of RECDs for foam/acoustic immittance tips and earmolds. Owing to the substantial between-subject variability observed in the data, the predictive equations of RECDs by age (in months) resulted in only gross estimates of RECD values (i.e., within +/- 4.4 dB for 95% of acoustic immittance tip measures; within +/- 5.4 dB in 95% of measures with custom earmolds) across frequency. Thus, it is concluded that the estimates derived from this study should not be used to replace the more precise individual RECD measurements. Relative to previously available normative RECD values for infants and young children, however, the estimates derived through this study provide somewhat more accurate predicted values for use under those circumstances for which individual RECD measurements cannot be made.

Quantifying confidence in density functional theory predictions of magnetic ground states

NASA Astrophysics Data System (ADS)

Houchins, Gregory; Viswanathan, Venkatasubramanian

2017-10-01

Density functional theory (DFT) simulations, at the generalized gradient approximation (GGA) level, are being routinely used for material discovery based on high-throughput descriptor-based searches. The success of descriptor-based material design relies on eliminating bad candidates and keeping good candidates for further investigation. While DFT has been widely successfully for the former, oftentimes good candidates are lost due to the uncertainty associated with the DFT-predicted material properties. Uncertainty associated with DFT predictions has gained prominence and has led to the development of exchange correlation functionals that have built-in error estimation capability. In this work, we demonstrate the use of built-in error estimation capabilities within the BEEF-vdW exchange correlation functional for quantifying the uncertainty associated with the magnetic ground state of solids. We demonstrate this approach by calculating the uncertainty estimate for the energy difference between the different magnetic states of solids and compare them against a range of GGA exchange correlation functionals as is done in many first-principles calculations of materials. We show that this estimate reasonably bounds the range of values obtained with the different GGA functionals. The estimate is determined as a postprocessing step and thus provides a computationally robust and systematic approach to estimating uncertainty associated with predictions of magnetic ground states. We define a confidence value (c-value) that incorporates all calculated magnetic states in order to quantify the concurrence of the prediction at the GGA level and argue that predictions of magnetic ground states from GGA level DFT is incomplete without an accompanying c-value. We demonstrate the utility of this method using a case study of Li-ion and Na-ion cathode materials and the c-value metric correctly identifies that GGA-level DFT will have low predictability for NaFePO4F . Further, there needs to be a systematic test of a collection of plausible magnetic states, especially in identifying antiferromagnetic (AFM) ground states. We believe that our approach of estimating uncertainty can be readily incorporated into all high-throughput computational material discovery efforts and this will lead to a dramatic increase in the likelihood of finding good candidate materials.

A new method to estimate average hourly global solar radiation on the horizontal surface

NASA Astrophysics Data System (ADS)

Pandey, Pramod K.; Soupir, Michelle L.

2012-10-01

A new model, Global Solar Radiation on Horizontal Surface (GSRHS), was developed to estimate the average hourly global solar radiation on the horizontal surfaces (Gh). The GSRHS model uses the transmission function (Tf,ij), which was developed to control hourly global solar radiation, for predicting solar radiation. The inputs of the model were: hour of day, day (Julian) of year, optimized parameter values, solar constant (H0), latitude, and longitude of the location of interest. The parameter values used in the model were optimized at a location (Albuquerque, NM), and these values were applied into the model for predicting average hourly global solar radiations at four different locations (Austin, TX; El Paso, TX; Desert Rock, NV; Seattle, WA) of the United States. The model performance was assessed using correlation coefficient (r), Mean Absolute Bias Error (MABE), Root Mean Square Error (RMSE), and coefficient of determinations (R2). The sensitivities of parameter to prediction were estimated. Results show that the model performed very well. The correlation coefficients (r) range from 0.96 to 0.99, while coefficients of determination (R2) range from 0.92 to 0.98. For daily and monthly prediction, error percentages (i.e. MABE and RMSE) were less than 20%. The approach we proposed here can be potentially useful for predicting average hourly global solar radiation on the horizontal surface for different locations, with the use of readily available data (i.e. latitude and longitude of the location) as inputs.

Parametric response mapping cut-off values that predict survival of hepatocellular carcinoma patients after TACE.

PubMed

Nörthen, Aventinus; Asendorf, Thomas; Shin, Hoen-Oh; Hinrichs, Jan B; Werncke, Thomas; Vogel, Arndt; Kirstein, Martha M; Wacker, Frank K; Rodt, Thomas

2018-04-21

Parametric response mapping (PRM) is a novel image-analysis technique applicable to assess tumor viability and predict intrahepatic recurrence of hepatocellular carcinoma (HCC) patients treated with transarterial chemoembolization (TACE). However, to date, the prognostic value of PRM for prediction of overall survival in HCC patients undergoing TACE is unclear. The objective of this explorative, single-center study was to identify cut-off values for voxel-specific PRM parameters that predict the post TACE overall survival in HCC patients. PRM was applied to biphasic CT data obtained at baseline and following 3 TACE treatments of 20 patients with HCC tumors ≥ 2 cm. The individual portal venous phases were registered to the arterial phases followed by segmentation of the largest lesion, i.e., the region of interest (ROI). Segmented voxels with their respective arterial and portal venous phase density values were displayed as a scatter plot. Voxel-specific PRM parameters were calculated and compared to patients' survival at 1, 2, and 3 years post treatment to identify the maximal predictive parameters. The hypervascularized tissue portion of the ROI was found to represent an independent predictor of the post TACE overall survival. For this parameter, cut-off values of 3650, 2057, and 2057 voxels, respectively, were determined to be optimal to predict overall survival at 1, 2, and 3 years after TACE. Using these cut points, patients were correctly classified as having died with a sensitivity of 80, 92, and 86% and as still being alive with a specificity of 60, 75, and 83%, respectively. The prognostic accuracy measured by area under the curve (AUC) values ranged from 0.73 to 0.87. PRM may have prognostic value to predict post TACE overall survival in HCC patients.

Fetal nasal bone hypoplasia in the second trimester: Comparison of diagnostic methods for predicting trisomy 21 (Down syndrome).

PubMed

Has, Recep; Akel, Esra Gilbaz; Kalelioglu, Ibrahim H; Dural, Ozlem; Yasa, Cenk; Esmer, Aytül Corbacioglu; Yuksel, Atıl; Yildirim, Alkan; Ibrahimoglu, Lemi; Ermis, Hayri

2016-02-01

The aim of this prospective observational study was to identify the best method for use in diagnosing fetal nasal bone (NB) hypoplasia in the second trimester as a means of predicting trisomy 21 (Down syndrome). The NB length (NBL), NBL percentiles, and NBL multiple-of-median (MoM) values and the biparietal diameter-to-NBL ratios were calculated and compared in an attempt to identify the best predictive method and most appropriate cutoff value. Predictive values for several cutoff points were calculated. Receiver operating characteristic curves at a fixed 5% false-positive rate were used to compare the four methods. NBL measurements were obtained from 2,211 (95.6%) of a total of 2,314 fetuses. Data from 1,689 of those 2,211 fetuses were used to obtain reference ranges, derive a linear regression equation, and calculate NBL percentiles and MoM values. Using a fixed 5% false-positive rate, we found 25.5% sensitivity for NBL (95% confidence interval [CI], 15-39.1) and 23.5% sensitivity for NBL percentiles (95% CI, 13.4-37), NBL MoM values (95% CI, 13.4-37), and biparietal diameter-to-NBL ratios (95% CI, 13.4-37). Our study demonstrated that all four methods can be used in the second trimester for diagnosing fetal NB hypoplasia as a means of predicting trisomy 21 because their predictive values are similar at a fixed 5% false-positive rate. For simplicity of use, we recommend using 3 mm as the NBL cutoff value. © 2015 Wiley Periodicals, Inc.

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

PubMed

Meng, Jie; Zhu, Lijing; Zhu, Li; Xie, Li; Wang, Huanhuan; Liu, Song; Yan, Jing; Liu, Baorui; Guan, Yue; He, Jian; Ge, Yun; Zhou, Zhengyang; Yang, Xiaofeng

2017-11-03

To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT). 36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm 2 ) were performed before CCRT (pre-CCRT) and at the end of 2nd week of CCRT (mid-CCRT). ADC histogram and texture features were derived from the whole volume of cervical cancers. With a mean follow-up of 25 months (range, 11 ∼ 43), 10/36 (27.8%) patients ended with recurrence. Pre-CCRT 75th, 90th, correlation, autocorrelation and mid-CCRT ADC mean , 10th, 25th, 50th, 75th, 90th, autocorrelation can effectively differentiate the recurrence from nonrecurrence group with area under the curve ranging from 0.742 to 0.850 (P values range, 0.001 ∼ 0.038). Pre- and mid-treatment whole-lesion ADC histogram and texture analysis hold great potential in predicting tumor recurrence of advanced cervical cancer treated with CCRT.

Bayesian model aggregation for ensemble-based estimates of protein pKa values

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

Gosink, Luke J.; Hogan, Emilie A.; Pulsipher, Trenton C.

2014-03-01

This paper investigates an ensemble-based technique called Bayesian Model Averaging (BMA) to improve the performance of protein amino acid pmore » $$K_a$$ predictions. Structure-based p$$K_a$$ calculations play an important role in the mechanistic interpretation of protein structure and are also used to determine a wide range of protein properties. A diverse set of methods currently exist for p$$K_a$$ prediction, ranging from empirical statistical models to {\\it ab initio} quantum mechanical approaches. However, each of these methods are based on a set of assumptions that have inherent bias and sensitivities that can effect a model's accuracy and generalizability for p$$K_a$$ prediction in complicated biomolecular systems. We use BMA to combine eleven diverse prediction methods that each estimate pKa values of amino acids in staphylococcal nuclease. These methods are based on work conducted for the pKa Cooperative and the pKa measurements are based on experimental work conducted by the Garc{\\'i}a-Moreno lab. Our study demonstrates that the aggregated estimate obtained from BMA outperforms all individual prediction methods in our cross-validation study with improvements from 40-70\\% over other method classes. This work illustrates a new possible mechanism for improving the accuracy of p$$K_a$$ prediction and lays the foundation for future work on aggregate models that balance computational cost with prediction accuracy.« less

[Effect of vitamin D deficiency on hypocalcaemia after total thyroidectomy due to benign goitre].

PubMed

Díez, Manuel; Vera, Cristina; Ratia, Tomás; Diego, Lucía; Mendoza, Fernando; Guillamot, Paloma; San Román, Rosario; Mugüerza, José M; Rodríguez, Angel; Medina, Carlos; Gómez, Beatriz; Granell, Javier

2013-04-01

The purpose of this study was to analyse the relationship between preoperative serum levels of vitamin D and postoperative hypocalcaemia after total thyroidectomy. A prospective observational study was conducted on 113 patients treated by total thyroidectomy due to benign disease. Preoperative vitamin D serum levels and postoperative albumin-corrected calcium and parathormone (PTH) levels were determined. Sensitivity, specificity, positive predictive value and negative predictive value of vitamin D and PTH levels, respectively, in the diagnosis of postoperative hypocalcaemia were calculated. Hypocalcaemia was diagnosed in 44 (38.9%) patients. Vitamin D levels were significantly higher in the group of patients with normal postoperative calcium (median: 25.4pg/mL; range: 4-60), compared to those who developed hypocalcaemia (median: 16.4pg/mL; range: 6.3-46.9) (P=.001). Postoperative hypocalcaemia was more frequent in patients with vitamin D < 30ng/mL (39/78) (50%), than among those with normal levels (5/35) (14.2%) (P=.001). Sensitivity, specificity, positive predictive value and negative predictive value were 88% and 68%, 43% and 82%, 50% and 71%, and 85% and 80% for vitamin D and PTH, respectively. Vitamin D and PTH showed independent prognostic values on the risk of hypocalcaemia. The OR associated with vitamin D < 30ng/mL was 4.25 (95% CI: 1.31-13.78) (P=.016), and the OR of PTH<13pg/mL was 15.4 (95% CI: 4.83-49.1) (P<.001). Vitamin D deficiency is a risk factor of hypocalcaemia after total thyroidectomy for benign goitre. The vitamin D level provides independent prognostic information, which is complementary to that given by PTH. Copyright © 2012 AEC. Published by Elsevier Espana. All rights reserved.

Prediction of whole-genome risk for selection and management of hyperketonemia in Holstein dairy cattle.

PubMed

Weigel, K A; Pralle, R S; Adams, H; Cho, K; Do, C; White, H M

2017-06-01

Hyperketonemia (HYK), a common early postpartum health disorder characterized by elevated blood concentrations of β-hydroxybutyrate (BHB), affects millions of dairy cows worldwide and leads to significant economic losses and animal welfare concerns. In this study, blood concentrations of BHB were assessed for 1,453 Holstein cows using electronic handheld meters at four time points between 5 and 18 days postpartum. Incidence rates of subclinical (1.2 ≤ maximum BHB ≤ 2.9 mmol/L) and clinical ketosis (maximum BHB ≥ 3.0 mmol/L) were 24.0 and 2.4%, respectively. Variance components, estimated breeding values, and predicted HYK phenotypes were computed on the original, square-root, and binary scales. Heritability estimates for HYK ranged from 0.058 to 0.072 in pedigree-based analyses, as compared to estimates that ranged from 0.071 to 0.093 when pedigrees were augmented with 60,671 single nucleotide polymorphism genotypes of 959 cows and 801 male ancestors. On average, predicted HYK phenotypes from the genome-enhanced analysis ranged from 0.55 mmol/L for first-parity cows in the best contemporary group to 1.40 mmol/L for fourth-parity cows in the worst contemporary group. Genome-enhanced predictions of HYK phenotypes were more closely associated with actual phenotypes than pedigree-based predictions in five-fold cross-validation, and transforming phenotypes to reduce skewness and kurtosis also improved predictive ability. This study demonstrates the feasibility of using repeated cowside measurement of blood BHB concentration in early lactation to construct a reference population that can be used to estimate HYK breeding values for genomic selection programmes and predict HYK phenotypes for genome-guided management decisions. © 2017 Blackwell Verlag GmbH.

Metabolic syndrome, major depression, generalized anxiety disorder, and ten-year all-cause and cardiovascular mortality in middle aged and elderly patients.

PubMed

Butnoriene, Jurate; Bunevicius, Adomas; Saudargiene, Ausra; Nemeroff, Charles B; Norkus, Antanas; Ciceniene, Vile; Bunevicius, Robertas

2015-01-01

Studies investigating specifically whether metabolic syndrome (MetS) and common psychiatric disorders are independently associated with mortality are lacking. In a middle-aged general population, we investigated the association of the MetS, current major depressive episode (MDE), lifetime MDE, and generalized anxiety disorder (GAD) with ten-year all-cause and cardiovascular disease mortality. From February 2003 until January 2004, 1115 individuals aged 45 years and older were randomly selected from a primary care practice and prospectively evaluated for: (1) MetS (The World Health Organization [WHO], National Cholesterol Education Program/Adult Treatment Panel III and International Diabetes Federation [IDF] definitions); (2) current MDE and GAD, and lifetime MDE (Mini International Neuropsychiatric Interview); and (3) conventional cardiovascular risk factors. Follow-up continued through January, 2013. During the 9.32 ± 0.47 years of follow-up, there were 248 deaths, of which 148 deaths were attributed to cardiovascular causes. In women, WHO-MetS and IDF-MetS were associated with greater all-cause (HR-values range from 1.77 to 1.91; p-values ≤ 0.012) and cardiovascular (HR-values range from 1.83 to 2.77; p-values ≤ 0.013) mortality independent of cardiovascular risk factors and MDE/GAD. Current GAD predicted greater cardiovascular mortality (HR-values range from 1.86 to 1.99; p-values ≤ 0.025) independently from MetS and cardiovascular risk factors. In men, the MetS and MDE/GAD were not associated with mortality. In middle aged women, the MetS and GAD predicted greater 10-year cardiovascular mortality independently from each other; 10-year all-cause mortality was independently predicted by the MetS. MetS and GAD should be considered important and independent mortality risk factors in women. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Theory of ultrasonic diffraction by damage developed in thin laminated composites

NASA Technical Reports Server (NTRS)

Hayford, D. T.; Henneke, E. G.

1977-01-01

The apparent attenuation which would result if certain damage states (transverse cracks and delaminations) are introduced into a graphite/epoxy laminate through which an ultrasonic wave passes is investigated. Experimental data for two different laminates are presented which shows changes in the apparent attenuation of about one db. These changes generally occur at loads which correspond to the range predicted for the formation of the damage. The predicted changes in the attenuation for several simple and common damage states are well within the range of experimental values.

Spacecraft Communications System Verification Using On-Axis Near Field Measurement Techniques

NASA Technical Reports Server (NTRS)

Keating, Thomas; Baugh, Mark; Gosselin, R. B.; Lecha, Maria C.; Krebs, Carolyn A. (Technical Monitor)

2000-01-01

Determination of the readiness of a spacecraft for launch is a critical requirement. The final assembly of all subsystems must be verified. Testing of a communications system can mostly be done using closed-circuits (cabling to/from test ports), but the final connections to the antenna require radiation tests. The Tropical Rainfall Measuring Mission (TRMM) Project used a readily available 'near-fleld on-axis' equation to predict the values to be used for comparison with those obtained in a test program. Tests were performed in a 'clean room' environment at both Goddard Space Flight Center (GSFC) and in Japan at the Tanegashima Space Center (TnSC) launch facilities. Most of the measured values agreed with the predicted values to within 0.5 dB. This demonstrates that sometimes you can use relatively simple techniques to make antenna performance measurements when use of the 'far field ranges, anechoic chambers, or precision near-field ranges' are neither available nor practical. Test data and photographs are provided.

Optically Tuned MM-Wave IMPATT Source.

DTIC Science & Technology

1987-07-01

phase of the work has been extended and generalised. Accuracy of the theory in predicting tuning at the higher oscillator voltage swings has been greatly...Accuracy of the theory in predicting tuning at the higher oscillator voltage swings has been greatly improved by reformulating the Bessel function...voltage modulation and a peak optically injected locking current of 100 pA the predicted ftl locking range would be 540MHz, a practicaUy useful value. 4

Comparison of ionospheric F2 peak parameters foF2 and hmF2 with IRI2001 at Hainan

NASA Astrophysics Data System (ADS)

Wang, X.; Shi, J. K.; Wang, G. J.; Gong, Y.

2009-06-01

Monthly median values of foF2, hmF2 and M(3000)F2 parameters, with quarter-hourly time interval resolution for the diurnal variation, obtained with DPS4 digisonde at Hainan (19.5°N, 109.1°E; Geomagnetic coordinates: 178.95°E, 8.1°N) are used to investigate the low-latitude ionospheric variations and comparisons with the International Reference Ionosphere (IRI) model predictions. The data used for the present study covers the period from February 2002 to April 2007, which is characterized by a wide range of solar activity, ranging from high solar activity (2002) to low solar activity (2007). The results show that (1) Generally, IRI predictions follow well the diurnal and seasonal variation patterns of the experimental values of foF2, especially in the summer of 2002. However, there are systematic deviation between experimental values and IRI predictions with either CCIR or URSI coefficients. Generally IRI model greatly underestimate the values of foF2 from about noon to sunrise of next day, especially in the afternoon, and slightly overestimate them from sunrise to about noon. It seems that there are bigger deviations between IRI Model predictions and the experimental observations for the moderate solar activity. (2) Generally the IRI-predicted hmF2 values using CCIR M(3000)F2 option shows a poor agreement with the experimental results, but there is a relatively good agreement in summer at low solar activity. The deviation between the IRI-predicted hmF2 using CCIR M(3000)F2 and observed hmF2 is bigger from noon to sunset and around sunrise especially at high solar activity. The occurrence time of hmF2 peak (about 1200 LT) of the IRI model predictions is earlier than that of observations (around 1500 LT). The agreement between the IRI hmF2 obtained with the measured M(3000)F2 and the observed hmF2 is very good except that IRI overestimates slightly hmF2 in the daytime in summer at high solar activity and underestimates it in the nighttime with lower values near sunrise at low solar activity.

Synthetic Scene Generation of the Stennis V and V Target Range for the Calibration of Remote Sensing Systems

NASA Technical Reports Server (NTRS)

Cao, Chang-Yong; Blonski, Slawomir; Ryan, Robert; Gasser, Jerry; Zanoni, Vicki

1999-01-01

The verification and validation (V&V) target range developed at Stennis Space Center is a useful test site for the calibration of remote sensing systems. In this paper, we present a simple algorithm for generating synthetic radiance scenes or digital models of this target range. The radiation propagation for the target in the solar reflective and thermal infrared spectral regions is modeled using the atmospheric radiative transfer code MODTRAN 4. The at-sensor, in-band radiance and spectral radiance for a given sensor at a given altitude is predicted. Software is developed to generate scenes with different spatial and spectral resolutions using the simulated at-sensor radiance values. The radiometric accuracy of the simulation is evaluated by comparing simulated with AVIRIS acquired radiance values. The results show that in general there is a good match between AVIRIS sensor measured and MODTRAN predicted radiance values for the target despite the fact that some anomalies exist. Synthetic scenes provide a cost-effective way for in-flight validation of the spatial and radiometric accuracy of the data. Other applications include mission planning, sensor simulation, and trade-off analysis in sensor design.

Use of Munsell color charts to measure skin tone objectively in nursing home residents at risk for pressure ulcer development.

PubMed

McCreath, Heather E; Bates-Jensen, Barbara M; Nakagami, Gojiro; Patlan, Anabel; Booth, Howard; Connolly, Dana; Truong, Cyndi; Woldai, Agazi

2016-09-01

To assess the feasibility of classifying skin tone using Munsell color chart values and to compare Munsell-based skin tone categories to ethnicity/race to predict pressure ulcer risk. Pressure ulcer classification uses level of visible tissue damage, including skin discoloration over bony prominences. Prevention begins with early detection of damage. Skin discoloration in those with dark skin tones can be difficult to observe, hindering early detection. Observational cohort of 417 nursing home residents from 19 nursing homes collected between 2009-2014, with weekly skin assessments for up to 16 weeks. Assessment included forearm and buttocks skin tone based on Munsell values (Dark, Medium, Light) at three time points, ethnicity/race medical record documentation, and weekly skin assessment on trunk and heels. Inter-rater reliability was high for forearm and buttock values and skin tone. Mean Munsell buttocks values differed significantly by ethnicity/race. Across ethnicity/race, Munsell value ranges overlapped, with the greatest range among African Americans. Trunk pressure ulcer incidence varied by skin tone, regardless of ethnicity/race. In multinomial regression, skin tone was more predictive of skin damage than ethnicity/race for trunk locations but ethnicity/race was more predictive for heels. Given the overlap of Munsell values across ethnicity/race, color charts provide more objective measurement of skin tone than demographic categories. An objective measure of skin tone can improve pressure ulcer risk assessment among patients for whom current clinical guidelines are less effective. © 2016 John Wiley & Sons Ltd.

[Determination and prediction for vapor pressures of organophosphate flame retardants by gas chromatography].

PubMed

Wang, Qingzhi; Zhao, Hongxia; Wang, Yan; Xie, Qing; Chen, Jingwen; Quan, Xie

2017-09-08

Organophosphate flame retardants (OPFRs) are ubiquitous in the environment. To better understand and predict their environmental transport and fate, well-defined physicochemical properties are required. Vapor pressures ( P ) of 14 OPFRs were estimated as a function of temperature ( T ) by gas chromatography (GC), while 1,1,1-trichioro-2,2-bis (4-chlorophenyl) ethane ( p,p '-DDT) was acted as a reference substance. Their log P GC values and internal energies of phase transfer (△ vap H ) ranged from -6.17 to -1.25 and 74.1 kJ/mol to 122 kJ/mol, respectively. Substitution pattern and molar volume ( V M ) were found to be capable of influencing log P GC values of the OPFRs. The halogenated alkyl-OPFRs had lower log P GC values than aryl-or alkyl-OPFRs. The bigger the molar volume was, the smaller the log P GC value was. In addition, a quantitative structure-property relationship (QSPR) model of log P GC versus different relative retention times (RRTs) was developed with a high cross-validated value ( Q 2 cum ) of 0.946, indicating a good predictive ability and stability. Therefore, the log P GC values of the OPFRs without standard substance can be predicted by using their RRTs on different GC columns.

Determination and prediction of octanol-air partition coefficients for organophosphate flame retardants.

PubMed

Wang, Qingzhi; Zhao, Hongxia; Wang, Yan; Xie, Qing; Chen, Jingwen; Quan, Xie

2017-11-01

Organophosphate flame retardants (OPFRs) have attracted wide concerns due to their toxicities and ubiquitous occurrence in the environment. In this work, Octanol-air partition coefficient (K OA ) for 14 OPFRs including 4 halogenated alkyl-, 5 aryl- and 5 alkyl-OPFRs, were estimated as a function of temperature using a gas chromatographic retention time (GC-RT) method. Their log K OA-GC values and internal energies of phase transfer (Δ OA U/kJmol -1 ) ranged from 8.03 to 13.0 and from 69.7 to 149, respectively. Substitution pattern and molar volume (V M ) were found to be capable of influencing log K OA-GC values of OPFRs. The halogenated alkyl-OPFRs had higher log K OA-GC values than aryl- or alkyl-OPFRs. The bigger the molar volume was, the greater the log K OA-GC values increased. In addition, a predicted model of log K OA-GC versus different relative retention times (RRTs) was developed with a high cross-validated value (Q 2 (cum) ) of 0.951, indicating a good predictive ability and stability. Therefore, the log K OA-GC values of the remaining OPFRs can be predicted by using their RRTs on different GC columns. Copyright © 2017 Elsevier Inc. All rights reserved.

Domestic estimated breeding values and genomic enhanced breeding values of bulls in comparison with their foreign genomic enhanced breeding values.

PubMed

Přibyl, J; Bauer, J; Čermák, V; Pešek, P; Přibylová, J; Šplíchal, J; Vostrá-Vydrová, H; Vostrý, L; Zavadilová, L

2015-10-01

Estimated breeding values (EBVs) and genomic enhanced breeding values (GEBVs) for milk production of young genotyped Holstein bulls were predicted using a conventional BLUP - Animal Model, a method fitting regression coefficients for loci (RRBLUP), a method utilizing the realized genomic relationship matrix (GBLUP), by a single-step procedure (ssGBLUP) and by a one-step blending procedure. Information sources for prediction were the nation-wide database of domestic Czech production records in the first lactation combined with deregressed proofs (DRP) from Interbull files (August 2013) and domestic test-day (TD) records for the first three lactations. Data from 2627 genotyped bulls were used, of which 2189 were already proven under domestic conditions. Analyses were run that used Interbull values for genotyped bulls only or that used Interbull values for all available sires. Resultant predictions were compared with GEBV of 96 young foreign bulls evaluated abroad and whose proofs were from Interbull method GMACE (August 2013) on the Czech scale. Correlations of predictions with GMACE values of foreign bulls ranged from 0.33 to 0.75. Combining domestic data with Interbull EBVs improved prediction of both EBV and GEBV. Predictions by Animal Model (traditional EBV) using only domestic first lactation records and GMACE values were correlated by only 0.33. Combining the nation-wide domestic database with all available DRP for genotyped and un-genotyped sires from Interbull resulted in an EBV correlation of 0.60, compared with 0.47 when only Interbull data were used. In all cases, GEBVs had higher correlations than traditional EBVs, and the highest correlations were for predictions from the ssGBLUP procedure using combined data (0.75), or with all available DRP from Interbull records only (one-step blending approach, 0.69). The ssGBLUP predictions using the first three domestic lactation records in the TD model were correlated with GMACE predictions by 0.69, 0.64 and 0.61 for milk yield, protein yield and fat yield, respectively.

Ultrasound as a screening test for genitourinary anomalies in children with UTI.

PubMed

Nelson, Caleb P; Johnson, Emilie K; Logvinenko, Tanya; Chow, Jeanne S

2014-03-01

The 2011 American Academy of Pediatrics guidelines state that renal and bladder ultrasound (RBUS) should be performed after initial febrile urinary tract infection (UTI) in a young child, with voiding cystourethrogram (VCUG) performed only if RBUS shows abnormalities. We sought to determine test characteristics and predictive values of RBUS for VCUG findings in this setting. We analyzed 3995 clinical encounters from January 1, 2006 to December 31, 2010 during which VCUG and RBUS were performed for history of UTI. Patients who had previous postnatal genitourinary imaging or history of prenatal hydronephrosis were excluded. Sensitivity, specificity, and predictive values of RBUS for VCUG abnormalities were determined. We identified 2259 patients age <60 months who had UTI as the indication for imaging. RBUS was reported as "normal" in 75%. On VCUG, any vesicoureteral reflux (VUR) was identified in 41.7%, VUR grade >II in 20.9%, and VUR grade >III in 2.8%. Sensitivity of RBUS for any abnormal findings on VCUG ranged from 5% (specificity: 97%) to 28% (specificity: 77%). Sensitivity for VUR grade >III ranged from 18% (specificity: 97%) to 55% (specificity: 77%). Among the 1203 children aged 2 to 24 months imaged after a first febrile UTI, positive predictive value of RBUS was 37% to 47% for VUR grade >II (13% to 24% for VUR grade >III); negative predictive value was 72% to 74% for VUR grade >II (95% to 96% for VUR grade >III). RBUS is a poor screening test for genitourinary abnormalities. RBUS and VCUG should be considered complementary as they provide important, but different, information.

Ultrasound as a Screening Test for Genitourinary Anomalies in Children With UTI

PubMed Central

Johnson, Emilie K.; Logvinenko, Tanya; Chow, Jeanne S.

2014-01-01

BACKGROUND: The 2011 American Academy of Pediatrics guidelines state that renal and bladder ultrasound (RBUS) should be performed after initial febrile urinary tract infection (UTI) in a young child, with voiding cystourethrogram (VCUG) performed only if RBUS shows abnormalities. We sought to determine test characteristics and predictive values of RBUS for VCUG findings in this setting. METHODS: We analyzed 3995 clinical encounters from January 1, 2006 to December 31, 2010 during which VCUG and RBUS were performed for history of UTI. Patients who had previous postnatal genitourinary imaging or history of prenatal hydronephrosis were excluded. Sensitivity, specificity, and predictive values of RBUS for VCUG abnormalities were determined. RESULTS: We identified 2259 patients age <60 months who had UTI as the indication for imaging. RBUS was reported as “normal” in 75%. On VCUG, any vesicoureteral reflux (VUR) was identified in 41.7%, VUR grade >II in 20.9%, and VUR grade >III in 2.8%. Sensitivity of RBUS for any abnormal findings on VCUG ranged from 5% (specificity: 97%) to 28% (specificity: 77%). Sensitivity for VUR grade >III ranged from 18% (specificity: 97%) to 55% (specificity: 77%). Among the 1203 children aged 2 to 24 months imaged after a first febrile UTI, positive predictive value of RBUS was 37% to 47% for VUR grade >II (13% to 24% for VUR grade >III); negative predictive value was 72% to 74% for VUR grade >II (95% to 96% for VUR grade >III). CONCLUSIONS: RBUS is a poor screening test for genitourinary abnormalities. RBUS and VCUG should be considered complementary as they provide important, but different, information. PMID:24515519

Comparison of Medicare Claims vs. Physician Adjudication for Identifying Stroke Outcomes in the Women’s Health Initiative

PubMed Central

Lakshminarayan, Kamakshi; Larson, Joseph C.; Virnig, Beth; Fuller, Candace; Allen, Norrina Bai; Limacher, Marian; Winkelmayer, Wolfgang C.; Safford, Monika M.; Burwen, Dale R.

2014-01-01

Background and Purpose Many studies use medical record review for ascertaining outcomes. One large, longitudinal study, the Women’s Health Initiative (WHI) ascertains strokes using participant self-report and subsequent physician review of medical records. This is resource-intensive. Herein, we assess whether Medicare data can reliably assess stroke events in the WHI. Methods Subjects were WHI participants with fee-for-service Medicare. Four stroke definitions were created for Medicare data using discharge diagnoses in hospitalization claims. Definition 1: stroke codes in any position; Definition 2: primary position stroke codes; Definitions 3 & 4: hemorrhagic and ischemic stroke codes respectively. WHI data were randomly split into training (50%) and test sets. A concordance matrix was used to examine agreement between WHI and Medicare stroke diagnosis. A WHI stroke and a Medicare stroke were considered a match if they occurred within +/− 7 days of each other. Refined analyses excluded Medicare events where medical records were unavailable for comparison. Results Training data (n=24,428): There were 577 WHI strokes and 557 Medicare strokes using definition 1. Of these, 478 were a match. Algorithm performance: Specificity 99.7%; Negative Predictive Value 99.7%; Sensitivity 82.8%; Positive Predictive Value 85.8%; kappa 0.84. Performance was similar for test data. While specificity and negative predictive value exceeded 99%, sensitivity ranged from 75 to 88% and positive predictive value ranged from 80 to 90% across stroke definitions. Conclusion Medicare data appear useful for population-based stroke research; however the performance characteristics depend on the definition selected. PMID:24525955

An empirical potential for simulating vacancy clusters in tungsten.

PubMed

Mason, D R; Nguyen-Manh, D; Becquart, C S

2017-12-20

We present an empirical interatomic potential for tungsten, particularly well suited for simulations of vacancy-type defects. We compare energies and structures of vacancy clusters generated with the empirical potential with an extensive new database of values computed using density functional theory, and show that the new potential predicts low-energy defect structures and formation energies with high accuracy. A significant difference to other popular embedded-atom empirical potentials for tungsten is the correct prediction of surface energies. Interstitial properties and short-range pairwise behaviour remain similar to the Ackford-Thetford potential on which it is based, making this potential well-suited to simulations of microstructural evolution following irradiation damage cascades. Using atomistic kinetic Monte Carlo simulations, we predict vacancy cluster dissociation in the range 1100-1300 K, the temperature range generally associated with stage IV recovery.

Highly ionized atoms in cooling gas

NASA Technical Reports Server (NTRS)

Edgar, R. J.; Chevalier, R. A.

1986-01-01

The ionization of low density gas cooling from a high temperature was calculated. The evolution during the cooling is assumed to be isochoric, isobaric, or a combination of these cases. The calculations are used to predict the column densities and ultraviolet line luminosities of highly ionized atoms in cooling gas. In a model for cooling of a hot galactic corona, it is shown that the observed value of N(N V) can be produced in the cooling gas, while the predicted value of N(Si IV) falls short of the observed value by a factor of about 5. The same model predicts fluxes of ultraviolet emission lines that are a factor of 10 lower than the claimed detections of Feldman, Brune, and Henry. Predictions are made for ultraviolet lines in cooling flows in early-type galaxies and clusters of galaxies. It is shown that the column densities of interest vary over a fairly narrow range, while the emission line luminosities are simply proportional to the mass inflow rate.

Highly ionized atoms in cooling gas. [in model for cooling of hot Galactic corona

NASA Technical Reports Server (NTRS)

Edgar, Richard J.; Chevalier, Roger A.

1986-01-01

The ionization of low density gas cooling from a high temperature was calculated. The evolution during the cooling is assumed to be isochoric, isobaric, or a combination of these cases. The calculations are used to predict the column densities and ultraviolet line luminosities of highly ionized atoms in cooling gas. In a model for cooling of a hot galactic corona, it is shown that the observed value of N(N V) can be produced in the cooling gas, while the predicted value of N(Si IV) falls short of the observed value by a factor of about 5. The same model predicts fluxes of ultraviolet emission lines that are a factor of 10 lower than the claimed detections of Feldman, Bruna, and Henry. Predictions are made for ultraviolet lines in cooling flows in early-type galaxies and clusters of galaxies. It is shown that the column densities of interest vary over a fairly narrow range, while the emission line luminosities are simply proportional to the mass inflow rate.

Mercury deposition in snow near an industrial emission source in the western U.S. and comparison to ISC3 model predictions

USGS Publications Warehouse

Abbott, M.L.; Susong, D.D.; Krabbenhoft, D.P.; Rood, A.S.

2002-01-01

Mercury (total and methyl) was evaluated in snow samples collected near a major mercury emission source on the Idaho National Engineering and Environmental Laboratory (INEEL) in southeastern Idaho and 160 km downwind in Teton Range in western Wyoming. The sampling was done to assess near-field (<12 km) deposition rates around the source, compare them to those measured in a relatively remote, pristine downwind location, and to use the measurements to develop improved, site-specific model input parameters for precipitation scavenging coefficient and the fraction of Hg emissions deposited locally. Measured snow water concentrations (ng L-1) were converted to deposition (ug m-2) using the sample location snow water equivalent. The deposition was then compared to that predicted using the ISC3 air dispersion/deposition model which was run with a range of particle and vapor scavenging coefficient input values. Accepted model statistical performance measures (fractional bias and normalized mean square error) were calculated for the different modeling runs, and the best model performance was selected. Measured concentrations close to the source (average = 5.3 ng L-1) were about twice those measured in the Teton Range (average = 2.7 ng L-1) which were within the expected range of values for remote background areas. For most of the sampling locations, the ISC3 model predicted within a factor of two of the observed deposition. The best modeling performance was obtained using a scavenging coefficient value for 0.25 ??m diameter particulate and the assumption that all of the mercury is reactive Hg(II) and subject to local deposition. A 0.1 ??m particle assumption provided conservative overprediction of the data, while a vapor assumption resulted in highly variable predictions. Partitioning a fraction of the Hg emissions to elemental Hg(0) (a U.S. EPA default assumption for combustion facility risk assessments) would have underpredicted the observed fallout.

Is the 15∆ Base in Prism Test Reliable for Detection of Amblyopia in Anisometropic Patients?

PubMed

Burggraaf, F; Verkaik-Rijneveld, M C; Wubbels, R J; de Jongh, E

2017-09-01

The 15∆ base in prism test (15∆BIPT) introduced by Gobin is often used in The Netherlands to detect fixation preference, especially in young and preverbal children in whom a reliable measurement of the visual acuity (VA) is difficult. It is assumed that the fixation preference detected by the 15∆BIPT can be used to predict the presence of amblyopia. The aim of this retrospective case note review was to investigate the accuracy of the 15∆BIPT in detection of amblyopia in anisometropic patients. Four hundred and twelve files of anisometropic patients visiting the orthoptic department of The Rotterdam Eye Hospital were analyzed. Amblyopia was defined as an intraocular difference in VA of 2 or more Snellen lines. The sensitivity, specificity, and positive and negative predictive values of the 15∆BIPT were calculated and the receiver operating characteristic (ROC) curve was plotted. One hundred and fifty-two patients ranging from 3.3-13.1 years of age (median 5.4 years) met the inclusion criteria. One hundred and two patients were diagnosed with amblyopia. Best-corrected median VA of the best eye was 1.0 (range 0.5-1.2) and the worst eye 0.70 (range 0.05-1.2). Sensitivity of the 15∆BIPT (based on detecting amblyopia) was 34.3%. Specificity was 88.0%. The positive predictive value was 85.4% versus a negative predictive value of 39.6%. The area under the ROC curve (AUC) was 0.65 (95% CI 0.56-0.74). The low sensitivity, large number of false negatives and the AUC show that the 15∆BIPT can be considered a poor test for detecting amblyopia in anisometropic patients.

Online physician ratings fail to predict actual performance on measures of quality, value, and peer review.

PubMed

Daskivich, Timothy J; Houman, Justin; Fuller, Garth; Black, Jeanne T; Kim, Hyung L; Spiegel, Brennan

2018-04-01

Patients use online consumer ratings to identify high-performing physicians, but it is unclear if ratings are valid measures of clinical performance. We sought to determine whether online ratings of specialist physicians from 5 platforms predict quality of care, value of care, and peer-assessed physician performance. We conducted an observational study of 78 physicians representing 8 medical and surgical specialties. We assessed the association of consumer ratings with specialty-specific performance scores (metrics including adherence to Choosing Wisely measures, 30-day readmissions, length of stay, and adjusted cost of care), primary care physician peer-review scores, and administrator peer-review scores. Across ratings platforms, multivariable models showed no significant association between mean consumer ratings and specialty-specific performance scores (β-coefficient range, -0.04, 0.04), primary care physician scores (β-coefficient range, -0.01, 0.3), and administrator scores (β-coefficient range, -0.2, 0.1). There was no association between ratings and score subdomains addressing quality or value-based care. Among physicians in the lowest quartile of specialty-specific performance scores, only 5%-32% had consumer ratings in the lowest quartile across platforms. Ratings were consistent across platforms; a physician's score on one platform significantly predicted his/her score on another in 5 of 10 comparisons. Online ratings of specialist physicians do not predict objective measures of quality of care or peer assessment of clinical performance. Scores are consistent across platforms, suggesting that they jointly measure a latent construct that is unrelated to performance. Online consumer ratings should not be used in isolation to select physicians, given their poor association with clinical performance.

Mapping the EORTC QLQ-C30 onto the EQ-5D-3L: assessing the external validity of existing mapping algorithms.

PubMed

Doble, Brett; Lorgelly, Paula

2016-04-01

To determine the external validity of existing mapping algorithms for predicting EQ-5D-3L utility values from EORTC QLQ-C30 responses and to establish their generalizability in different types of cancer. A main analysis (pooled) sample of 3560 observations (1727 patients) and two disease severity patient samples (496 and 93 patients) with repeated observations over time from Cancer 2015 were used to validate the existing algorithms. Errors were calculated between observed and predicted EQ-5D-3L utility values using a single pooled sample and ten pooled tumour type-specific samples. Predictive accuracy was assessed using mean absolute error (MAE) and standardized root-mean-squared error (RMSE). The association between observed and predicted EQ-5D utility values and other covariates across the distribution was tested using quantile regression. Quality-adjusted life years (QALYs) were calculated using observed and predicted values to test responsiveness. Ten 'preferred' mapping algorithms were identified. Two algorithms estimated via response mapping and ordinary least-squares regression using dummy variables performed well on number of validation criteria, including accurate prediction of the best and worst QLQ-C30 health states, predicted values within the EQ-5D tariff range, relatively small MAEs and RMSEs, and minimal differences between estimated QALYs. Comparison of predictive accuracy across ten tumour type-specific samples highlighted that algorithms are relatively insensitive to grouping by tumour type and affected more by differences in disease severity. Two of the 'preferred' mapping algorithms suggest more accurate predictions, but limitations exist. We recommend extensive scenario analyses if mapped utilities are used in cost-utility analyses.

The multidirectional bending properties of the human lumbar intervertebral disc.

PubMed

Spenciner, David; Greene, David; Paiva, James; Palumbo, Mark; Crisco, Joseph

2006-01-01

While the biomechanical properties of the isolated intervertebral disc have been well studied in the three principal anatomic directions of flexion/extension, axial rotation, and lateral bending, there is little data on the properties in the more functional directions that are combinations of these principal anatomic directions. To determine the bending flexibility, range of motion (ROM), and neutral zone (NZ) of the human lumbar disc in multiple directions and to determine if the values about the combined moment axes can be predicted from the values about principal moment axes. Three-dimensional biomechanical analysis of the elastic bending properties of human lumbar discs about principal and combined moment axes. Pure, unconstrained moments were applied about multiple axes. The bending properties (flexibility, ROM, and NZ) of isolated lumbar discs (n=4 for L2/L3 and n=3 for L4/L5) were determined in the six principal directions and in 20 combined directions. The experimental values were compared with those predicted from the linear combination of the six principal moment axes. The maximum and minimum values of the biomechanical properties were found at the principal moment axes. Among combined moment axes, ROM and NZ (but not flexibility) values were predicted from the principal moment axis values. The principal moment axes coincide with the primary mechanical axes of the intervertebral disc and demonstrate significant differences in direction for values of flexibility, ROM, and NZ. Not all combined moment axis values can be predicted from principal moment axis values.

Sensitivity and positive predictive value of CT, MRI and 123I-MIBG scintigraphy in localizing pheochromocytomas: a prospective study.

PubMed

Lumachi, Franco; Tregnaghi, Alberto; Zucchetta, Pietro; Cristina Marzola, Maria; Cecchin, Diego; Grassetto, Gaia; Bui, Franco

2006-07-01

To establish a standardized non-invasive imaging protocol for patients with pheochromocytoma undergoing surgery. A series of 32 consecutive patients (16 men, 16 women; median age 43 years, range 15-71 years) with biochemically confirmed pheochromocytoma underwent computed tomography (CT) scanning, magnetic resonance imaging (MRI) and meta-[I]iodobenzylguanidine (MIBG) whole-body scintigraphy prior to adrenalectomy or excision of extra-adrenal tumour (paraganglioma). At final pathology no malignant pheochromocytomas were found. The tumour was right-sided in 16 (50%) patients, left-sided in 13 (41%), extra-adrenal (sympathetic ganglia, upper abdomen) in two (6%) and bilateral in one (3%) patient. Overall, the median greatest diameter (size) of the tumour was 35 mm (range, 15-90 mm). The sensitivity of CT, MRI and MIBG scintigraphy was 90%, 93% and 91%, and the specificity was 93%, 93% and 100%, respectively. The three patients with false negative scintigraphy had an intra-adrenal tumour, ranging from 20 to 50 mm in size. The presence of necrosis within the mass might justify the lack of significant uptake of radiopharmaceutical in two patients, and the small size (15 mm) of the mass in the other. There were two false positive results with both CT and MRI, and no false positive MIBG scintigraphy, which had the highest (100%) positive predictive value. The combination of MRI+MIBG scintigraphy reached 100% sensitivity and positive predictive value. Our data suggest that this imaging protocol should be used in all patients with biochemically confirmed pheochromocytoma.

Exploring the Predictive Validity of the Susceptibility to Smoking Construct for Tobacco Cigarettes, Alternative Tobacco Products, and E-Cigarettes.

PubMed

Cole, Adam G; Kennedy, Ryan David; Chaurasia, Ashok; Leatherdale, Scott T

2017-12-06

Within tobacco prevention programming, it is useful to identify youth that are at risk for experimenting with various tobacco products and e-cigarettes. The susceptibility to smoking construct is a simple method to identify never-smoking students that are less committed to remaining smoke-free. However, the predictive validity of this construct has not been tested within the Canadian context or for the use of other tobacco products and e-cigarettes. This study used a large, longitudinal sample of secondary school students that reported never using tobacco cigarettes and non-current use of alternative tobacco products or e-cigarettes at baseline in Ontario, Canada. The sensitivity, specificity, and positive and negative predictive values of the susceptibility construct for predicting tobacco cigarette, e-cigarette, cigarillo or little cigar, cigar, hookah, and smokeless tobacco use one and two years after baseline measurement were calculated. At baseline, 29.4% of the sample was susceptible to future tobacco product or e-cigarette use. The sensitivity of the construct ranged from 43.2% (smokeless tobacco) to 59.5% (tobacco cigarettes), the specificity ranged from 70.9% (smokeless tobacco) to 75.9% (tobacco cigarettes), and the positive predictive value ranged from 2.6% (smokeless tobacco) to 32.2% (tobacco cigarettes). Similar values were calculated for each measure of the susceptibility construct. A significant number of youth that did not currently use tobacco products or e-cigarettes at baseline reported using tobacco products and e-cigarettes over a two-year follow-up period. The predictive validity of the susceptibility construct was high and the construct can be used to predict other tobacco product and e-cigarette use among youth. This study presents the predictive validity of the susceptibility construct for the use of tobacco cigarettes among secondary school students in Ontario, Canada. It also presents a novel use of the susceptibility construct for predicting the use of e-cigarettes, cigarillos or little cigars, cigars, hookah, and smokeless tobacco among secondary school students in Ontario, Canada. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Exploring the predictive power of polygenic scores derived from genome-wide association studies: a study of 10 complex traits.

PubMed

So, Hon-Cheong; Sham, Pak C

2017-03-15

It is hoped that advances in our knowledge in disease genomics will contribute to personalized medicine such as individualized preventive strategies or early diagnoses of diseases. With the growth of genome-wide association studies (GWAS) in the past decade, how far have we reached this goal? In this study we explored the predictive ability of polygenic risk scores (PRSs) derived from GWAS for a range of complex disease and traits. We first proposed a new approach to evaluate predictive performances of PRS at arbitrary P -value thresholds. The method was based on corrected estimates of effect sizes, accounting for possible false positives and selection bias. This approach requires no distributional assumptions and only requires summary statistics as input. The validity of the approach was verified in simulations. We explored the predictive power of PRS for ten complex traits, including type 2 diabetes (DM), coronary artery disease (CAD), triglycerides, high- and low-density lipoprotein, total cholesterol, schizophrenia (SCZ), bipolar disorder (BD), major depressive disorder and anxiety disorders. We found that the predictive ability of PRS for CAD and DM were modest (best AUC = 0.608 and 0.607) while for lipid traits the prediction R-squared ranged from 16.1 to 29.8%. For psychiatric disorders, the predictive power for SCZ was estimated to be the highest (best AUC 0.820), followed by BD. Predictive performance of other psychiatric disorders ranged from 0.543 to 0.585. Psychiatric traits tend to have more gradual rise in AUC when significance thresholds increase and achieve the best predictive power at higher P -values than cardiometabolic traits. hcso@cuhk.edu.hk ; pcsham@hku.hk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

DOE PAGES

Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

2015-04-02

The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K 1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO 2 2+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K 1 values are significantly overestimated. Accurate predictions of the absolute log K 1 values (root mean square deviation from experiment < 1.0 for logmore » K 1 values ranging from 0 to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.« less

Universal inverse power-law distribution for temperature and rainfall in the UK region

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2014-06-01

Meteorological parameters, such as temperature, rainfall, pressure, etc., exhibit selfsimilar space-time fractal fluctuations generic to dynamical systems in nature such as fluid flows, spread of forest fires, earthquakes, etc. The power spectra of fractal fluctuations display inverse power-law form signifying long-range correlations. A general systems theory model predicts universal inverse power-law form incorporating the golden mean for the fractal fluctuations. The model predicted distribution was compared with observed distribution of fractal fluctuations of all size scales (small, large and extreme values) in the historic month-wise temperature (maximum and minimum) and total rainfall for the four stations Oxford, Armagh, Durham and Stornoway in the UK region, for data periods ranging from 92 years to 160 years. For each parameter, the two cumulative probability distributions, namely cmax and cmin starting from respectively maximum and minimum data value were used. The results of the study show that (i) temperature distributions (maximum and minimum) follow model predicted distribution except for Stornowy, minimum temperature cmin. (ii) Rainfall distribution for cmin follow model predicted distribution for all the four stations. (iii) Rainfall distribution for cmax follows model predicted distribution for the two stations Armagh and Stornoway. The present study suggests that fractal fluctuations result from the superimposition of eddy continuum fluctuations.

Fatigue crack growth theory and experiment: A comparative analysis

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

Sananda, K.

A number of theoretical models have been proposed in the literature which explain the second or the fourth power dependence of fatigue crack growth rate on ..delta..K, the stress intensity factor range in the Paris-Erdogan relation da/dN = C ..delta..K /SUP m/ . All of these models pertain to the intermediate range of crack growth rates where the m values are relatively low in the range of 2 to 4. The values of m for many metals and alloys can be much larger than 4 at near threshold crack growth rates or at stress intensities close to the fast fracture,more » and in some cases throughout the range of ..delta..K when the faceted mode of crack growth occurs. For such cases, the models appear to have no relevance. In this report predictions of different theoretical models are critically examined in comparison to experimentally determined crack growth rates in a MA 956, oxide dispersion strengthened alloy. Cumulative damage models predict crack growth rates reasonably well except in the range where ductile striations are observed. Lack of agreement with any particular model in this range is related to the fact that at different regions across the specimen thickness different mechanisms, either plastic blunting or cumulative damage, control the crack growth.« less

The PILGRIM study: in silico modeling of a predictive low glucose management system and feasibility in youth with type 1 diabetes during exercise.

PubMed

Danne, Thomas; Tsioli, Christiana; Kordonouri, Olga; Blaesig, Sarah; Remus, Kerstin; Roy, Anirban; Keenan, Barry; Lee, Scott W; Kaufman, Francine R

2014-06-01

Predictive low glucose management (PLGM) may help prevent hypoglycemia by stopping insulin pump delivery based on predicted sensor glucose values. Hypoglycemic challenges were simulated using the Food and Drug Administration-accepted glucose simulator with 100 virtual patients. PLGM was then tested with a system composed of a Paradigm(®) insulin pump (Medtronic, Northridge, CA), an Enlite™ glucose sensor (Medtronic), and a BlackBerry(®) (Waterloo, ON, Canada)-based controller. Subjects (n=22) on continuous subcutaneous insulin infusion (five females, 17 males; median [range] age, 15 [range, 14-20] years; median [range] diabetes duration, 7 [2-14] years; median [range] glycated hemoglobin, 8.0% [6.7-10.4%]) exercised until the PLGM system suspended insulin delivery or until the reference blood glucose value (HemoCue(®); HemoCue GmbH, Großostheim, Germany) reached the predictive suspension threshold setting. PLGM reduced hypoglycemia (<70 mg/dL) in silico by 26.7% compared with no insulin suspension, as opposed to a 5.3% reduction in hypoglycemia with use of low glucose suspend (LGS). The median duration of hypoglycemia (time spent <70 mg/dL) with PLGM was significantly less than with LGS (58 min vs. 101 min, respectively; P<0.001). In the clinical trial the hypoglycemic threshold during exercise was reached in 73% of the patients, and hypoglycemia was prevented in 80% of the successful experiments. The mean (±SD) sensor glucose at predictive suspension was 92±7 mg/dL, resulting in a postsuspension nadir (by HemoCue) of 77±22 mg/dL. The suspension lasted for 90±35 (range, 30-120) min, resulting in a sensor glucose level at insulin resumption of 97±19 mg/dL. In silico modeling and early feasibility data demonstrate that PLGM may further reduce the severity of hypoglycemia beyond that already established for algorithms that use a threshold-based suspension.

[Geographical distribution of the Serum creatinine reference values of healthy adults].

PubMed

Wei, De-Zhi; Ge, Miao; Wang, Cong-Xia; Lin, Qian-Yi; Li, Meng-Jiao; Li, Peng

2016-11-20

To explore the relationship between serum creatinine (Scr) reference values in healthy adults and geographic factors and provide evidence for establishing Scr reference values in different regions. We collected 29 697 Scr reference values from healthy adults measured by 347 medical facilities from 23 provinces, 4 municipalities and 5 autonomous regions. We chose 23 geographical factors and analyzed their correlation with Scr reference values to identify the factors correlated significantly with Scr reference values. According to the Principal component analysis and Ridge regression analysis, two predictive models were constructed and the optimal model was chosen after comparison of the two model's fitting degree of predicted results and measured results. The distribution map of Scr reference values was drawn using the Kriging interpolation method. Seven geographic factors, including latitude, annual sunshine duration, annual average temperature, annual average relative humidity, annual precipitation, annual temperature range and topsoil (silt) cation exchange capacity were found to correlate significantly with Scr reference values. The overall distribution of Scr reference values featured a pattern that the values were high in the south and low in the north, varying consistently with the latitude change. The data of the geographic factors in a given region allows the prediction of the Scr values in healthy adults. Analysis of these geographical factors can facilitate the determination of the reference values specific to a region to improve the accuracy for clinical diagnoses.

Estimating apparent maximum muscle stress of trunk extensor muscles in older adults using subject-specific musculoskeletal models.

PubMed

Burkhart, Katelyn A; Bruno, Alexander G; Bouxsein, Mary L; Bean, Jonathan F; Anderson, Dennis E

2018-01-01

Maximum muscle stress (MMS) is a critical parameter in musculoskeletal modeling, defining the maximum force that a muscle of given size can produce. However, a wide range of MMS values have been reported in literature, and few studies have estimated MMS in trunk muscles. Due to widespread use of musculoskeletal models in studies of the spine and trunk, there is a need to determine reasonable magnitude and range of trunk MMS. We measured trunk extension strength in 49 participants over 65 years of age, surveyed participants about low back pain, and acquired quantitative computed tomography (QCT) scans of their lumbar spines. Trunk muscle morphology was assessed from QCT scans and used to create a subject-specific musculoskeletal model for each participant. Model-predicted extension strength was computed using a trunk muscle MMS of 100 N/cm 2 . The MMS of each subject-specific model was then adjusted until the measured strength matched the model-predicted strength (±20 N). We found that measured trunk extension strength was significantly higher in men. With the initial constant MMS value, the musculoskeletal model generally over-predicted trunk extension strength. By adjusting MMS on a subject-specific basis, we found apparent MMS values ranging from 40 to 130 N/cm 2 , with an average of 75.5 N/cm 2 for both men and women. Subjects with low back pain had lower apparent MMS than subjects with no back pain. This work incorporates a unique approach to estimate subject-specific trunk MMS values via musculoskeletal modeling and provides a useful insight into MMS variation. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:498-505, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Predictive value of painful popping for a posterior root tear of the medial meniscus in middle-aged to older Asian patients.

PubMed

Bae, Ji-Hoon; Paik, Nak Hwan; Park, Gyu-Won; Yoon, Jung-Ro; Chae, Dong-Ju; Kwon, Jae Ho; Kim, Jong In; Nha, Kyung-Wook

2013-03-01

The purpose of this study was to determine the accuracy, sensitivity, specificity, and predictive values of a single event of painful popping in the presence of a posterior root tear of the medial meniscus in middle-aged to older Asian patients. We conducted a retrospective review of medical records of 936 patients who underwent arthroscopic surgeries for an isolated medial meniscus tear between January 2000 and December 2010. There were 332 men and 604 women with a mean age of 41 years (range, 25 to 66 years). The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of a painful popping sensation for a posterior root tear of the medial meniscus were calculated. Arthroscopy confirmed the presence of posterior root tears of the medial menisci in 237 of 936 patients (25.3%). A single event of a painful popping sensation was present in 86 of these 936 patients (9.1%). Of these 86 patients with a painful popping sensation, 83 (96.5%) were categorized as having an isolated posterior root tear of the medial meniscus. The positive predictive value of a painful popping sensation in identifying a posterior root tear of the medial meniscus was 96.5%, the negative predictive value was 81.8%, the sensitivity was 35.0%, the specificity was 99.5%, and the diagnostic accuracy was 77.9%. A single event of painful popping can be a highly predictive clinical sign of a posterior root tear of the medial meniscus in the middle-aged to older Asian population. However, it has low sensitivity for the detection of a posterior root tear of the medial meniscus. Level IV, therapeutic case series. Copyright © 2013 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Dry Heat Inactivation of Bacillus subtilis var. niger Spores as a Function of Relative Humidity

PubMed Central

Brannen, J. P.; Garst, D. M.

1972-01-01

Dry heat sterilization of Bacillus subtilis var. niger spores at 105 C is enhanced in the relative humidity range 0.03 to 0.2%. D-values of 115 and 125 C are predicted by a kinetic model with parameters set from 105 C data. These predictions are compared to observations. Images PMID:4625341

Facial-Attractiveness Choices Are Predicted by Divisive Normalization.

PubMed

Furl, Nicholas

2016-10-01

Do people appear more attractive or less attractive depending on the company they keep? A divisive-normalization account-in which representation of stimulus intensity is normalized (divided) by concurrent stimulus intensities-predicts that choice preferences among options increase with the range of option values. In the first experiment reported here, I manipulated the range of attractiveness of the faces presented on each trial by varying the attractiveness of an undesirable distractor face that was presented simultaneously with two attractive targets, and participants were asked to choose the most attractive face. I used normalization models to predict the context dependence of preferences regarding facial attractiveness. The more unattractive the distractor, the more one of the targets was preferred over the other target, which suggests that divisive normalization (a potential canonical computation in the brain) influences social evaluations. I obtained the same result when I manipulated faces' averageness and participants chose the most average face. This finding suggests that divisive normalization is not restricted to value-based decisions (e.g., attractiveness). This new application to social evaluation of normalization, a classic theory, opens possibilities for predicting social decisions in naturalistic contexts such as advertising or dating.

Dynamic properties of porous B sub 4 C. Interim report

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

Brar, N.S.; Rosenberg, Z.; Bless, S.J.

1990-01-25

The sound speed in porous B4C (Boron Carbide) was measured and predicted on the basis of a spherical void model and a penny crack model. Neither model does well for porosity exceeding 10 percent. Measured values of Hugoniot elastic limit for porous B4C agree well with those predicted by the Steinberg's model. Measured transverse stress in the elastic range of B4C under 1-d strain condition agrees with the predictions.

Adjustment of regional regression models of urban-runoff quality using data for Chattanooga, Knoxville, and Nashville, Tennessee

USGS Publications Warehouse

Hoos, Anne B.; Patel, Anant R.

1996-01-01

Model-adjustment procedures were applied to the combined data bases of storm-runoff quality for Chattanooga, Knoxville, and Nashville, Tennessee, to improve predictive accuracy for storm-runoff quality for urban watersheds in these three cities and throughout Middle and East Tennessee. Data for 45 storms at 15 different sites (five sites in each city) constitute the data base. Comparison of observed values of storm-runoff load and event-mean concentration to the predicted values from the regional regression models for 10 constituents shows prediction errors, as large as 806,000 percent. Model-adjustment procedures, which combine the regional model predictions with local data, are applied to improve predictive accuracy. Standard error of estimate after model adjustment ranges from 67 to 322 percent. Calibration results may be biased due to sampling error in the Tennessee data base. The relatively large values of standard error of estimate for some of the constituent models, although representing significant reduction (at least 50 percent) in prediction error compared to estimation with unadjusted regional models, may be unacceptable for some applications. The user may wish to collect additional local data for these constituents and repeat the analysis, or calibrate an independent local regression model.

Early improvement as a resilience signal predicting later remission to antidepressant treatment in patients with Major Depressive Disorder: Systematic review and meta-analysis.

PubMed

Wagner, Stefanie; Engel, Alice; Engelmann, Jan; Herzog, David; Dreimüller, Nadine; Müller, Marianne B; Tadić, André; Lieb, Klaus

2017-11-01

Early improvement of depressive symptoms during the first two weeks of antidepressant treatment has been discussed to be a resilience signal predicting a later positive treatment outcome in patients with Major Depressive Disorder (MDD). However, the predictive value of early improvement varies between studies, and the use of different antidepressants may explain heterogeneous results. The objective of this review was to assess the predictive value of early improvement on later response and remission and to identify antidepressants with the highest chance of early improvement. We included 17 randomized controlled trials investigating early improvement in 14,779 adult patients with MDD comparing monotherapy with an antidepressant against placebo or another antidepressant drug. 62% (range: 35-85%) of patients treated with an antidepressant and 47% (range: 21-69%) with placebo were early improver, defined as a >20%/25% symptom reduction after two weeks of treatment. Early improvement predicted response and remission after 5-12 weeks of treatment with high sensitivity (85%; 95%-CI: 84.3 to 85.7) and low to moderate specificity (54%; 95%-CI: 53.1 to 54.9). Early improver had a 8.37 fold (6.97-10.05) higher likelihood to become responder and a 6.38 fold (5.07-8.02) higher likelihood to be remitter at endpoint than non-improver. The highest early improver rates were achieved in patients treated with mirtazapine or a tricyclic antidepressant. This finding of a high predictive value of early improvement on treatment outcome may be important for treatment decisions in the early course of antidepressant treatment. Further studies should test the efficacy of such early treatment decisions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Validation of the Five-Phase Method for Simulating Complex Fenestration Systems with Radiance against Field Measurements

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

Geisler-Moroder, David; Lee, Eleanor S.; Ward, Gregory J.

2016-08-29

The Five-Phase Method (5-pm) for simulating complex fenestration systems with Radiance is validated against field measurements. The capability of the method to predict workplane illuminances, vertical sensor illuminances, and glare indices derived from captured and rendered high dynamic range (HDR) images is investigated. To be able to accurately represent the direct sun part of the daylight not only in sensor point simulations, but also in renderings of interior scenes, the 5-pm calculation procedure was extended. The validation shows that the 5-pm is superior to the Three-Phase Method for predicting horizontal and vertical illuminance sensor values as well as glare indicesmore » derived from rendered images. Even with input data from global and diffuse horizontal irradiance measurements only, daylight glare probability (DGP) values can be predicted within 10% error of measured values for most situations.« less

Valuing river characteristics using combined site choice and participation travel cost models.

PubMed

Johnstone, C; Markandya, A

2006-08-01

This paper presents new welfare measures for marginal changes in river quality in selected English rivers. The river quality indicators used include chemical, biological and habitat-level attributes. Economic values for recreational use of three types of river-upland, lowland and chalk-are presented. A survey of anglers was carried out and using these data, two travel cost models were estimated, one to predict the numbers of trips and the other to predict angling site choice. These models were then linked to estimate the welfare associated with marginal changes in river quality using the participation levels as estimated in the trip prediction model. The model results showed that higher flow rates, biological quality and nutrient pollution levels affect site choice and influence the likelihood of a fishing trip. Consumer surplus values per trip for a 10% change in river attributes range from pound 0.04 to pound 3.93 ( pound 2001) depending on the attribute.

Application of Receiver Operating Characteristic Analysis to Refine the Prediction of Potential Digoxin Drug Interactions

PubMed Central

Ellens, Harma; Deng, Shibing; Coleman, JoAnn; Bentz, Joe; Taub, Mitchell E.; Ragueneau-Majlessi, Isabelle; Chung, Sophie P.; Herédi-Szabó, Krisztina; Neuhoff, Sibylle; Palm, Johan; Balimane, Praveen; Zhang, Lei; Jamei, Masoud; Hanna, Imad; O’Connor, Michael; Bednarczyk, Dallas; Forsgard, Malin; Chu, Xiaoyan; Funk, Christoph; Guo, Ailan; Hillgren, Kathleen M.; Li, LiBin; Pak, Anne Y.; Perloff, Elke S.; Rajaraman, Ganesh; Salphati, Laurent; Taur, Jan-Shiang; Weitz, Dietmar; Wortelboer, Heleen M.; Xia, Cindy Q.; Xiao, Guangqing; Yamagata, Tetsuo

2013-01-01

In the 2012 Food and Drug Administration (FDA) draft guidance on drug-drug interactions (DDIs), a new molecular entity that inhibits P-glycoprotein (P-gp) may need a clinical DDI study with a P-gp substrate such as digoxin when the maximum concentration of inhibitor at steady state divided by IC50 ([I1]/IC50) is ≥0.1 or concentration of inhibitor based on highest approved dose dissolved in 250 ml divide by IC50 ([I2]/IC50) is ≥10. In this article, refined criteria are presented, determined by receiver operating characteristic analysis, using IC50 values generated by 23 laboratories. P-gp probe substrates were digoxin for polarized cell-lines and N-methyl quinidine or vinblastine for P-gp overexpressed vesicles. Inhibition of probe substrate transport was evaluated using 15 known P-gp inhibitors. Importantly, the criteria derived in this article take into account variability in IC50 values. Moreover, they are statistically derived based on the highest degree of accuracy in predicting true positive and true negative digoxin DDI results. The refined criteria of [I1]/IC50 ≥ 0.03 and [I2]/IC50 ≥ 45 and FDA criteria were applied to a test set of 101 in vitro-in vivo digoxin DDI pairs collated from the literature. The number of false negatives (none predicted but DDI observed) were similar, 10 and 12%, whereas the number of false positives (DDI predicted but not observed) substantially decreased from 51 to 40%, relative to the FDA criteria. On the basis of estimated overall variability in IC50 values, a theoretical 95% confidence interval calculation was developed for single laboratory IC50 values, translating into a range of [I1]/IC50 and [I2]/IC50 values. The extent by which this range falls above the criteria is a measure of risk associated with the decision, attributable to variability in IC50 values. PMID:23620486

Norcocaine in human hair as a biomarker of heavy cocaine use in a high risk population.

PubMed

Poon, S; Gareri, J; Walasek, P; Koren, G

2014-08-01

In hair analysis, cocaine (COC) and its metabolites have been studied relatively extensively with a consistent focus of distinguishing active drug use and excluding external contamination. Although quantitative cut-offs using major metabolite, benzolecgonine (BE), in hair have been proposed to distinguish likely active use from passive exposure, exogenously formed BE may result in false positive tests. Hence, the presence of less commonly detected COC metabolite, norcocaine (NCOC), may be useful in increasing certainty of illicit COC use and evaluating likelihood of environmental contamination. The objective of the present study was to observe the pattern of NCOC detection in a clinical population of suspected users and evaluate the possible role of NCOC in distinguishing systemic exposure from external contamination to COC and assessing intensity of cocaine use. Hair samples collected between January 2011 and May 2013 from the Motherisk Laboratory were analyzed by GC-MS for the presence of COC, BE, and NCOC. NCOC positivity rates (%) for various COC concentration ranges as well as sensitivity, specificity, positive predictive value, and negative predictive values of NCOC as a biomarker of different COC use profiles was calculated. The rate of NCOC positivity (%) within COC concentration ranges (ng/mg) 0.13-0.4 (above LOD, below LOQ), 0.4-3, 3-6, 6-10, 10-14, >14 were 0.26, 4.15, 29.63, 55.85, 80.37, and 94.02, respectively; p<0.0001 for all positivity comparisons between ranges. These results were used to determine a COC cut-off concentration for differing levels of COC use. The presence of NCOC above the LOD of 0.13 ng/mg predicted COC concentrations exceeding 14.00 ng/mg, with sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 94.0%, 87.9%, 41.5%, and 99.4%, respectively. The presence NCOC above the LOD of 0.13 ng/mg predicted COC concentrations exceeding the 75th percentile, with sensitivity, specificity, PPV, and NPV of 76.6%, 94.7%, 74.7%, and 95.2%, respectively. Despite an inability to definitively rule out external contamination, the presence of NCOC in hair is strongly associated with elevated COC levels and performs as a highly specific surrogate marker for frequent/intensive cocaine use and highly sensitive marker for intensive/daily use of cocaine. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Fusion positron emission/computed tomography underestimates the presence of hilar nodal metastases in patients with resected non-small cell lung cancer.

PubMed

Carrillo, Sergio A; Daniel, Vincent C; Hall, Nathan; Hitchcock, Charles L; Ross, Patrick; Kassis, Edmund S

2012-05-01

The 5-year survival for patients with resected stage II (N1) non-small cell lung cancer ranges from 40% to 55%. No data exist addressing the benefit of neoadjuvant therapy for patients with stage II disease. This is largely in part due to the lack of a reliable, minimally invasive method to assess hilar nodes. This study is aimed at determining the ability of fusion positron emission/computed tomography (PET/CT) to identify hilar metastases in patients with resected non-small cell lung cancer. A retrospective review of surgically resected patients with fusion PET/CT within 30 days of resection was performed. The sensitivity, specificity, positive predictive value, and negative predictive value for PET/CT in detecting hilar nodal metastases was calculated for a range of maximum standardized uptake values (SUVmax). Hilar nodes from patients with falsely positive PET/CT scans were analyzed for the presence of histoplasmosis. Additionally, the impact of hilar node size greater than 1 centimeter on the calculated values was assessed. There were 119 patients evaluated. The number of lymph nodes resected ranged from 1 to 12 (X=2.98). There was decreased sensitivity and increased specificity with higher SUVmax cutoff values. At the standard SUVmax value of 2.5, the sensitivity and specificity were only 48.5% and 80.2%. The addition of size of hilar node by CT led to a modest improvement in sensitivity at all SUVmax cutoff values. Fusion PET/CT lacks sensitivity and specificity in identifying hilar nodal metastasis in patients with resected non-small cell lung cancer. Further prospective studies assessing the utility of PET/CT versus alternative sampling techniques are warranted. Copyright © 2012 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Ground cloud effluent measurements during the May 30, 1974, Titan 3 launch at the Air Force eastern test range

NASA Technical Reports Server (NTRS)

Bendura, R. J.; Crumbly, K. H.

1977-01-01

Surface-level exhaust effluent measurements of HCl, CO, and particulates, ground-cloud behavior, and some comparisons with model predictions for the launch of a Titan 3 rocket are presented along with a limited amount of airborne sampling measurements of other cloud species (O3, NO, NOX). Values above background levels for these effluents were obtained at 20 of the 30 instrument sites; these values were lower than model predictions and did not exceed public health standards. Cloud rise rate, stabilization altitude, and volume are compared with results from previous launches.

Solubility Measurements and Predictions of Gypsum, Anhydrite, and Calcite Over Wide Ranges of Temperature, Pressure, and Ionic Strength with Mixed Electrolytes

NASA Astrophysics Data System (ADS)

Dai, Zhaoyi; Kan, Amy T.; Shi, Wei; Zhang, Nan; Zhang, Fangfu; Yan, Fei; Bhandari, Narayan; Zhang, Zhang; Liu, Ya; Ruan, Gedeng; Tomson, Mason B.

2017-02-01

Today's oil and gas production from deep reservoirs permits exploitation of more oil and gas reserves but increases risks due to conditions of high temperature and high pressure. Predicting mineral solubility under such extreme conditions is critical for mitigating scaling risks, a common and costly problem. Solubility predictions use solubility products and activity coefficients, commonly from Pitzer theory virial coefficients. However, inaccurate activity coefficients and solubility data have limited accurate mineral solubility predictions and applications of the Pitzer theory. This study measured gypsum solubility under its stable phase conditions up to 1400 bar; it also confirmed the anhydrite solubility reported in the literature. Using a novel method, the virial coefficients for Ca2+ and {{SO}}4^{2 - } (i.e., β_{{{{CaSO}}4 }}^{(0)} ,β_{{{{CaSO}}4 }}^{(2)} ,C_{{{{CaSO}}4 }}^{φ }) were calculated over wide ranges of temperature and pressure (0-250 °C and 1-1400 bar). The determination of this set of virial coefficients widely extends the applicable temperature and pressure ranges of the Pitzer theory in Ca2+ and SO 4 2- systems. These coefficients can be applied to improve the prediction of calcite solubility in the presence of high concentrations of Ca2+ and SO 4 2- ions. These new virial coefficients can also be used to predict the solubilities of gypsum and anhydrite accurately. Moreover, based on the derived β_{{{{CaSO}}4 }}^{(2)} values in this study, the association constants of {{CaSO}}4^{( 0 )} at 1 bar and 25 °C can be estimated by K_{{assoc}} = - 2β_{{{{CaSO}}4 }}^{(2)}. These values match very well with those reported in the literature based on other methods.

Effects of feather wear and temperature on prediction of food intake and residual food consumption.

PubMed

Herremans, M; Decuypere, E; Siau, O

1989-03-01

Heat production, which accounts for 0.6 of gross energy intake, is insufficiently represented in predictions of food intake. Especially when heat production is elevated (for example by lower temperature or poor feathering) the classical predictions based on body weight, body-weight change and egg mass are inadequate. Heat production was reliably estimated as [35.5-environmental temperature (degree C)] x [Defeathering (=%IBPW) + 21]. Including this term (PHP: predicted heat production) in equations predicting food intake significantly increased accuracy of prediction, especially under suboptimal conditions. Within the range of body weights tested (from 1.6 kg in brown layers to 2.8 kg in dwarf broiler breeders), body weight as an independent variable contributed little to the prediction of food intake; especially within strains its effect was better included in the intercept. Significantly reduced absolute values of residual food consumption were obtained over a wide range of conditions by using predictions of food intake based on body-weight change, egg mass, predicted heat production (PHP) and an intercept, instead of body weight, body-weight change, egg mass and an intercept.

Artificial Neural Network System to Predict the Postoperative Outcome of Percutaneous Nephrolithotomy.

PubMed

Aminsharifi, Alireza; Irani, Dariush; Pooyesh, Shima; Parvin, Hamid; Dehghani, Sakineh; Yousofi, Khalilolah; Fazel, Ebrahim; Zibaie, Fatemeh

2017-05-01

To construct, train, and apply an artificial neural network (ANN) system for prediction of different outcome variables of percutaneous nephrolithotomy (PCNL). We calculated predictive accuracy, sensitivity, and precision for each outcome variable. During the study period, all adult patients who underwent PCNL at our institute were enrolled in the study. Preoperative and postoperative variables were recorded, and stone-free status was assessed perioperatively with computed tomography scans. MATLAB software was used to design and train the network in a feed forward back-propagation error adjustment scheme. Preoperative and postoperative data from 200 patients (training set) were used to analyze the effect and relative relevance of preoperative values on postoperative parameters. The validated adequately trained ANN was used to predict postoperative outcomes in the subsequent 254 adult patients (test set) whose preoperative values were serially fed into the system. To evaluate system accuracy in predicting each postoperative variable, predicted values were compared with actual outcomes. Two hundred fifty-four patients (155 [61%] males) were considered the test set. Mean stone burden was 6702.86 ± 381.6 mm 3 . Overall stone-free rate was 76.4%. Fifty-four out of 254 patients (21.3%) required ancillary procedures (shockwave lithotripsy 5.9%, transureteral lithotripsy 10.6%, and repeat PCNL 4.7%). The accuracy and sensitivity of the system in predicting different postoperative variables ranged from 81.0% to 98.2%. As a complex nonlinear mathematical model, our ANN system is an interconnected data mining tool, which prospectively analyzes and "learns" the relationships between variables. The accuracy and sensitivity of the system for predicting the stone-free rate, the need for blood transfusion, and post-PCNL ancillary procedures ranged from 81.0% to 98.2%.The stone burden and the stone morphometry were among the most significant preoperative characteristics that affected all postoperative outcome variables and they received the highest relative weight by the ANN system.

Use of risk assessment instruments to predict violence and antisocial behaviour in 73 samples involving 24 827 people: systematic review and meta-analysis.

PubMed

Fazel, Seena; Singh, Jay P; Doll, Helen; Grann, Martin

2012-07-24

To investigate the predictive validity of tools commonly used to assess the risk of violence, sexual, and criminal behaviour. Systematic review and tabular meta-analysis of replication studies following PRISMA guidelines. PsycINFO, Embase, Medline, and United States Criminal Justice Reference Service Abstracts. We included replication studies from 1 January 1995 to 1 January 2011 if they provided contingency data for the offending outcome that the tools were designed to predict. We calculated the diagnostic odds ratio, sensitivity, specificity, area under the curve, positive predictive value, negative predictive value, the number needed to detain to prevent one offence, as well as a novel performance indicator-the number safely discharged. We investigated potential sources of heterogeneity using metaregression and subgroup analyses. Risk assessments were conducted on 73 samples comprising 24,847 participants from 13 countries, of whom 5879 (23.7%) offended over an average of 49.6 months. When used to predict violent offending, risk assessment tools produced low to moderate positive predictive values (median 41%, interquartile range 27-60%) and higher negative predictive values (91%, 81-95%), and a corresponding median number needed to detain of 2 (2-4) and number safely discharged of 10 (4-18). Instruments designed to predict violent offending performed better than those aimed at predicting sexual or general crime. Although risk assessment tools are widely used in clinical and criminal justice settings, their predictive accuracy varies depending on how they are used. They seem to identify low risk individuals with high levels of accuracy, but their use as sole determinants of detention, sentencing, and release is not supported by the current evidence. Further research is needed to examine their contribution to treatment and management.

Evaluation and comparison of statistical methods for early temporal detection of outbreaks: A simulation-based study

PubMed Central

Le Strat, Yann

2017-01-01

The objective of this paper is to evaluate a panel of statistical algorithms for temporal outbreak detection. Based on a large dataset of simulated weekly surveillance time series, we performed a systematic assessment of 21 statistical algorithms, 19 implemented in the R package surveillance and two other methods. We estimated false positive rate (FPR), probability of detection (POD), probability of detection during the first week, sensitivity, specificity, negative and positive predictive values and F1-measure for each detection method. Then, to identify the factors associated with these performance measures, we ran multivariate Poisson regression models adjusted for the characteristics of the simulated time series (trend, seasonality, dispersion, outbreak sizes, etc.). The FPR ranged from 0.7% to 59.9% and the POD from 43.3% to 88.7%. Some methods had a very high specificity, up to 99.4%, but a low sensitivity. Methods with a high sensitivity (up to 79.5%) had a low specificity. All methods had a high negative predictive value, over 94%, while positive predictive values ranged from 6.5% to 68.4%. Multivariate Poisson regression models showed that performance measures were strongly influenced by the characteristics of time series. Past or current outbreak size and duration strongly influenced detection performances. PMID:28715489

Random Predictor Models for Rigorous Uncertainty Quantification: Part 2

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean, the variance, and the range of the model's parameter, thus of the output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, is bounded rigorously.

Estuarine wetland evolution including sea-level rise and infrastructure effects.

NASA Astrophysics Data System (ADS)

Rodriguez, Jose Fernando; Trivisonno, Franco; Rojas, Steven Sandi; Riccardi, Gerardo; Stenta, Hernan; Saco, Patricia Mabel

2015-04-01

Estuarine wetlands are an extremely valuable resource in terms of biotic diversity, flood attenuation, storm surge protection, groundwater recharge, filtering of surface flows and carbon sequestration. On a large scale the survival of these systems depends on the slope of the land and a balance between the rates of accretion and sea-level rise, but local man-made flow disturbances can have comparable effects. Climate change predictions for most of Australia include an accelerated sea level rise, which may challenge the survival of estuarine wetlands. Furthermore, coastal infrastructure poses an additional constraint on the adaptive capacity of these ecosystems. Numerical models are increasingly being used to assess wetland dynamics and to help manage some of these situations. We present results of a wetland evolution model that is based on computed values of hydroperiod and tidal range that drive vegetation preference. Our first application simulates the long term evolution of an Australian wetland heavily constricted by infrastructure that is undergoing the effects of predicted accelerated sea level rise. The wetland presents a vegetation zonation sequence mudflats - mangrove - saltmarsh from the seaward margin and up the topographic gradient but is also affected by compartmentalization due to internal road embankments and culverts that effectively attenuates tidal input to the upstream compartments. For this reason, the evolution model includes a 2D hydrodynamic module which is able to handle man-made flow controls and spatially varying roughness. It continually simulates tidal inputs into the wetland and computes annual values of hydroperiod and tidal range to update vegetation distribution based on preference to hydrodynamic conditions of the different vegetation types. It also computes soil accretion rates and updates roughness coefficient values according to evolving vegetation types. In order to explore in more detail the magnitude of flow attenuation due to roughness and its effects on the computation of tidal range and hydroperiod, we performed numerical experiments simulating floodplain flow on the side of a tidal creek using different roughness values. Even though the values of roughness that produce appreciable changes in hydroperiod and tidal range are relatively high, they are within the range expected for some of the wetland vegetation. Both applications of the model show that flow attenuation can play a major role in wetland hydrodynamics and that its effects must be considered when predicting wetland evolution under climate change scenarios, particularly in situations where existing infrastructure affects the flow.

Prediction models for transfer of arsenic from soil to corn grain (Zea mays L.).

PubMed

Yang, Hua; Li, Zhaojun; Long, Jian; Liang, Yongchao; Xue, Jianming; Davis, Murray; He, Wenxiang

2016-04-01

In this study, the transfer of arsenic (As) from soil to corn grain was investigated in 18 soils collected from throughout China. The soils were treated with three concentrations of As and the transfer characteristics were investigated in the corn grain cultivar Zhengdan 958 in a greenhouse experiment. Through stepwise multiple-linear regression analysis, prediction models were developed combining the As bioconcentration factor (BCF) of Zhengdan 958 and soil pH, organic matter (OM) content, and cation exchange capacity (CEC). The possibility of applying the Zhengdan 958 model to other cultivars was tested through a cross-cultivar extrapolation approach. The results showed that the As concentration in corn grain was positively correlated with soil pH. When the prediction model was applied to non-model cultivars, the ratio ranges between the predicted and measured BCF values were within a twofold interval between predicted and measured values. The ratios were close to a 1:1 relationship between predicted and measured values. It was also found that the prediction model (Log [BCF]=0.064 pH-2.297) could effectively reduce the measured BCF variability for all non-model corn cultivars. The novel model is firstly developed for As concentration in crop grain from soil, which will be very useful for understanding the As risk in soil environment.

Mass scale of vectorlike matter and superpartners from IR fixed point predictions of gauge and top Yukawa couplings

NASA Astrophysics Data System (ADS)

Dermíšek, Radovan; McGinnis, Navin

2018-03-01

We use the IR fixed point predictions for gauge couplings and the top Yukawa coupling in the minimal supersymmetric model (MSSM) extended with vectorlike families to infer the scale of vectorlike matter and superpartners. We quote results for several extensions of the MSSM and present results in detail for the MSSM extended with one complete vectorlike family. We find that for a unified gauge coupling αG>0.3 vectorlike matter or superpartners are expected within 1.7 TeV (2.5 TeV) based on all three gauge couplings being simultaneously within 1.5% (5%) from observed values. This range extends to about 4 TeV for αG>0.2 . We also find that in the scenario with two additional large Yukawa couplings of vectorlike quarks the IR fixed point value of the top Yukawa coupling independently points to a multi-TeV range for vectorlike matter and superpartners. Assuming a universal value for all large Yukawa couplings at the grand unified theory scale, the measured top quark mass can be obtained from the IR fixed point for tan β ≃4 . The range expands to any tan β >3 for significant departures from the universality assumption. Considering that the Higgs boson mass also points to a multi-TeV range for superpartners in the MSSM, adding a complete vectorlike family at the same scale provides a compelling scenario where the values of gauge couplings and the top quark mass are understood as a consequence of the particle content of the model.

Simulation and prediction of the thuringiensin abiotic degradation processes in aqueous solution by a radius basis function neural network model.

PubMed

Zhou, Jingwen; Xu, Zhenghong; Chen, Shouwen

2013-04-01

The thuringiensin abiotic degradation processes in aqueous solution under different conditions, with a pH range of 5.0-9.0 and a temperature range of 10-40°C, were systematically investigated by an exponential decay model and a radius basis function (RBF) neural network model, respectively. The half-lives of thuringiensin calculated by the exponential decay model ranged from 2.72 d to 16.19 d under the different conditions mentioned above. Furthermore, an RBF model with accuracy of 0.1 and SPREAD value 5 was employed to model the degradation processes. The results showed that the model could simulate and predict the degradation processes well. Both the half-lives and the prediction data showed that thuringiensin was an easily degradable antibiotic, which could be an important factor in the evaluation of its safety. Copyright © 2012 Elsevier Ltd. All rights reserved.

The production and measurement of sub-bandage pressure: Laplace's Law revisited.

PubMed

Thomas, S

2014-05-01

The present study was undertaken to demonstrate that the pressures produced by multiple layers of compression bandages applied to artificial limbs of known circumference with predetermined levels of tension can be predicted accurately using the modified Laplace equation. Up to four layers of different bandage types were applied in a carefully controlled fashion to cylinders of known circumference, with tensions ranging from around 200-2000 grams/10cm width. The pressures generated were measured using pneumatic pressure sensors previously shown to possess the required degree of accuracy for this type of experimental system. Good correlation was observed between the mean and standard deviation of each pair of experimental and calculated pressure values for all combinations of bandage type, application tension and cylinder circumference. Over the clinically relevant range of pressures, the difference between data sets was generally less than 1.0mmHg. The results of this experimental study unequivocally prove that provided accurate values for all the relevant variables are known, it is possible to predict the pressure that will be developed by a compression bandage on a limb of known size. However, it is important to recognise that other factors such as the elastomeric properties of the fabric will have a major effect upon the ability of a bandage system to sustain initial compression values. Furthermore, the variation in radius of curvature around a limb will mean that point pressures readings recorded at individual locations around the circumference may vary dramatically from the average value predicted by the modified Laplace equation, calling into question the value of sub-bandage pressure measuring devices for this application.

Effect of bulk modulus on deformation of the brain under rotational accelerations

NASA Astrophysics Data System (ADS)

Ganpule, S.; Daphalapurkar, N. P.; Cetingul, M. P.; Ramesh, K. T.

2018-01-01

Traumatic brain injury such as that developed as a consequence of blast is a complex injury with a broad range of symptoms and disabilities. Computational models of brain biomechanics hold promise for illuminating the mechanics of traumatic brain injury and for developing preventive devices. However, reliable material parameters are needed for models to be predictive. Unfortunately, the properties of human brain tissue are difficult to measure, and the bulk modulus of brain tissue in particular is not well characterized. Thus, a wide range of bulk modulus values are used in computational models of brain biomechanics, spanning up to three orders of magnitude in the differences between values. However, the sensitivity of these variations on computational predictions is not known. In this work, we study the sensitivity of a 3D computational human head model to various bulk modulus values. A subject-specific human head model was constructed from T1-weighted MRI images at 2-mm3 voxel resolution. Diffusion tensor imaging provided data on spatial distribution and orientation of axonal fiber bundles for modeling white matter anisotropy. Non-injurious, full-field brain deformations in a human volunteer were used to assess the simulated predictions. The comparison suggests that a bulk modulus value on the order of GPa gives the best agreement with experimentally measured in vivo deformations in the human brain. Further, simulations of injurious loading suggest that bulk modulus values on the order of GPa provide the closest match with the clinical findings in terms of predicated injured regions and extent of injury.

Basal CD34+ Cell Count Predicts Peripheral Blood Stem Cell Mobilization in Healthy Donors after Administration of Granulocyte Colony-Stimulating Factor: A Longitudinal, Prospective, Observational, Single-Center, Cohort Study.

PubMed

Martino, Massimo; Gori, Mercedes; Pitino, Annalisa; Gentile, Massimo; Dattola, Antonia; Pontari, Antonella; Vigna, Ernesto; Moscato, Tiziana; Recchia, Anna Grazia; Barilla', Santina; Tripepi, Giovanni; Morabito, Fortunato

2017-07-01

A longitudinal, prospective, observational, single-center, cohort study on healthy donors (HDs) was designed to identify predictors of CD34 + cells on day 5 with emphasis on the predictive value of the basal CD34 + cell count. As potential predictors of mobilization, age, sex, body weight, height, blood volume as well as white blood cell count, peripheral blood (PB) mononuclear cells, platelet count, hematocrit, and hemoglobin levels were considered. Two different evaluations of CD34 + cell counts were determined for each donor: baseline (before granulocyte colony-stimulating factor [G-CSF] administration) and in PB after G-CSF administration on the morning of the fifth day (day 5). A total of 128 consecutive HDs (66 males) with a median age of 43 years were enrolled. CD34 + levels on day 5 displayed a non-normal distribution, with a median value of 75.5 cells/µL. To account for the non-normal distribution of the dependent variable, a quantile regression analysis to predict CD34 + on day 5 using the baseline value of CD34 + as the key predictor was performed. On crude analysis, a baseline value of CD34 + ranging from .5 cells/µL to 1 cells/µL predicts a median value of 50 cells/µL on day 5; a value of 2 cells/µL predicts a median value of 70.7 cells/µL; a value of 3 cells/µL to 4 cells/µL predicts a median value of 91.3 cells/µL, and a value ≥ 5 predicts a median value of 112 cells/µL. In conclusion, the baseline PB CD34 + cell count correlates with the effectiveness of allogeneic PB stem cell mobilization and could be useful to plan the collection. Copyright © 2017 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

Determination of the alpha(s) using jet rates at LEP

NASA Astrophysics Data System (ADS)

Donkers, Michael A.

Jets are produced in any high energy collision of particles in which quarks are produced in the final state. Using the OPAL detector to measure particles produced in e+e- collisions at the LEP accelerator, the rate of jet formation has been measured at 91 GeV as well as each of the LEP2 energies, ranging from 161 GeV to 207 GeV. The jet rate observables, in particular the differential 2-jet rate and the average jet rate can be used to determine a value of the strong coupling constant, alphas, by fitting to various theoretical predictions. The value of alphas has been determined using data at 91 GeV and a combined sample comprising all of the LEP2 energies with a luminosity weighted centre-of-mass energy of 195.8 GeV for 10 theoretical predictions and two jet clustering algorithms. A fit of the 91 GeV and LEP2 values of alphas determined using the ln R matching prediction is also performed on the D2 and distributions to the 3-loop alphas prediction to produce 4 values of alphas(MZ 0).

Thermodynamic and mechanical properties of epoxy resin DGEBF crosslinked with DETDA by molecular dynamics.

PubMed

Tack, Jeremy L; Ford, David M

2008-06-01

Fully atomistic molecular dynamics (MD) simulations were used to predict the properties of diglycidyl ether of bisphenol F (DGEBF) crosslinked with curing agent diethyltoluenediamine (DETDA). This polymer is a commercially important epoxy resin and a candidate for applications in nanocomposites. The calculated properties were density and bulk modulus (at near-ambient pressure and temperature) and glass transition temperature (at near-ambient pressure). The molecular topology, degree of curing, and MD force-field were investigated as variables. The models were created by densely packing pre-constructed oligomers of different composition and connectivity into a periodic simulation box. For high degrees of curing (greater than 90%), the density was found to be insensitive to the molecular topology and precise value of degree of curing. Of the two force-fields that were investigated, cff91 and COMPASS, the latter clearly gave more accurate values for the density as compared to experiment. In fact, the density predicted by COMPASS was within 6% of reported experimental values for the highly crosslinked polymer. The predictions of both force-fields for glass transition temperature were within the range of reported experimental values, with the predictions of cff91 being more consistent with a highly cured resin.

Dopamine reward prediction-error signalling: a two-component response

PubMed Central

Schultz, Wolfram

2017-01-01

Environmental stimuli and objects, including rewards, are often processed sequentially in the brain. Recent work suggests that the phasic dopamine reward prediction-error response follows a similar sequential pattern. An initial brief, unselective and highly sensitive increase in activity unspecifically detects a wide range of environmental stimuli, then quickly evolves into the main response component, which reflects subjective reward value and utility. This temporal evolution allows the dopamine reward prediction-error signal to optimally combine speed and accuracy. PMID:26865020

Equation of state for solids with high accuracy and satisfying the limitation condition at high pressure

NASA Astrophysics Data System (ADS)

Jiuxun, Sun; Qiang, Wu; Lingcang, Cai; Fuqian, Jing

2006-01-01

An equation of state (EOS) with high accuracy is proposed to strictly satisfy the Fermi gas limitation condition at high pressure. The EOS (SJX EOS) is a modification of the effective Rydberg (ER2) EOS. Instead of Holzapfel's method to directly modify the ER2 EOS, one modifying term is added to the ER2 EOS to make it not only satisfy the high pressure limitation condition, but also to avoid the disadvantages occurring in the Holzapfel and ‘adapted polynomial expansion of the order 3’ (AP3) EOSs. The two-parameter ER2, Holzapfel, and three-parameter SJX, AP3, Kumari and Dass (KD) EOSs are applied to 50 materials to fit all experimental compression data available. The five EOSs also are applied to 37 of the 50 materials to fit experimental compression data at low-pressure ranges. The results show that for all pressure ranges the AP3 EOS gives the best fitting results; the SJX, ER2, Holzapfel and KD EOSs sequentially give inferior results. Otherwise, it is shown that the values of B0, B0‧ and B0″ are different for different EOSs and also, within one EOS, for high and low-pressure ranges. The SJX EOS gives the best consistency between the values obtained by fitting all experimental data available, and the experimental data at low-pressure ranges, respectively. The AP3 EOS gives the worst results. The differences of the values of B0, B0‧ and B0″ obtained for the ER2, Holzapfel and KD EOSs with those obtained for the SJX EOS are large at high-pressure ranges, but decrease at low-pressure ranges. At present, the newest experimental compression data, within the widest compression range, are available for solid n-H 2. The values of B0, B0‧ and B0″ fitted by using the SJX EOS are almost in agreement with these experimental data. The ER2 EOS gives inferior values, and other EOSs give fairly bad results. For the predicted compression curves and the cohesive energy, the SJX EOS gives the best results; the AP3 EOS gives the worst results, even for many solids the AP3 EOS cannot give physically correct results for the cohesive energy. The analysis shows that for such solids, the variation of pressure and energy versus compression ratio calculated by using the AP3 EOS would oscillate, physically incorrectly. Although the AP3 EOS has the best fitting ability to the pressures, it has the worst predicting ability, and fails to be a universal EOS. The SJX EOS is recommended and can be taken as a candidate of universal EOSs to predict compression curves of solids in a wide pressure range only using the values of B0, B0‧ and B0″ obtained from low-pressure data.

Questionnaire Predictors of Atopy in a US Population Sample: Findings From the National Health and Nutrition Examination Survey, 2005–2006

PubMed Central

Hoppin, Jane A.; Jaramillo, Renee; Salo, Paivi; Sandler, Dale P.; London, Stephanie J.; Zeldin, Darryl C.

2011-01-01

Allergic conditions and biochemical measures are both used to characterize atopy. To assess questionnaires’ ability to predict biochemical measures of atopy, the authors used data on 5 allergic conditions (allergy, hay fever, eczema, rhinitis, and itchy rash) and serum-specific immunoglobulin E (IgE) levels from the 2005–2006 National Health and Nutrition Examination Survey. Atopy was defined as 1 or more positive specific IgEs (≥0.35 kU/L). Questionnaire responses were assessed for sensitivity, specificity, and positive and negative predictive values for atopy. In this population-based US sample, 44% of participants were specific IgE-positive and 53% reported at least 1 allergic condition. Discordance between atopy and allergic conditions was considerable; 37% of persons with atopy reported no allergic condition, and 48% of persons who reported an allergic condition were not atopic. Thus, no combination of self-reported allergic conditions achieved both high sensitivity and high specificity for IgE. The positive predictive value of reported allergic conditions for atopy ranged from 50% for eczema to 72% for hay fever, while the negative predictive value ranged from 57% for eczema to 65% for any condition. Given the high proportion of asymptomatic participants who were specific IgE-positive and persons who reported allergic conditions but were specific IgE-negative, it is unlikely that questionnaires will ever capture the same participants as those found to be atopic by biochemical measures. PMID:21273397

Performance evaluation of objective quality metrics for HDR image compression

NASA Astrophysics Data System (ADS)

Valenzise, Giuseppe; De Simone, Francesca; Lauga, Paul; Dufaux, Frederic

2014-09-01

Due to the much larger luminance and contrast characteristics of high dynamic range (HDR) images, well-known objective quality metrics, widely used for the assessment of low dynamic range (LDR) content, cannot be directly applied to HDR images in order to predict their perceptual fidelity. To overcome this limitation, advanced fidelity metrics, such as the HDR-VDP, have been proposed to accurately predict visually significant differences. However, their complex calibration may make them difficult to use in practice. A simpler approach consists in computing arithmetic or structural fidelity metrics, such as PSNR and SSIM, on perceptually encoded luminance values but the performance of quality prediction in this case has not been clearly studied. In this paper, we aim at providing a better comprehension of the limits and the potentialities of this approach, by means of a subjective study. We compare the performance of HDR-VDP to that of PSNR and SSIM computed on perceptually encoded luminance values, when considering compressed HDR images. Our results show that these simpler metrics can be effectively employed to assess image fidelity for applications such as HDR image compression.

The extrudate swell of HDPE: Rheological effects

NASA Astrophysics Data System (ADS)

Konaganti, Vinod Kumar; Ansari, Mahmoud; Mitsoulis, Evan; Hatzikiriakos, Savvas G.

2017-05-01

The extrudate swell of an industrial grade high molecular weight high-density polyethylene (HDPE) in capillary dies is studied experimentally and numerically using the integral K-BKZ constitutive model. The non-linear viscoelastic flow properties of the polymer resin are studied for a broad range of large step shear strains and high shear rates using the cone partitioned plate (CPP) geometry of the stress/strain controlled rotational rheometer. This allowed the determination of the rheological parameters accurately, in particular the damping function, which is proven to be the most important in simulating transient flows such as extrudate swell. A series of simulations performed using the integral K-BKZ Wagner model with different values of the Wagner exponent n, ranging from n=0.15 to 0.5, demonstrates that the extrudate swell predictions are extremely sensitive to the Wagner damping function exponent. Using the correct n-value resulted in extrudate swell predictions that are in excellent agreement with experimental measurements.

Modeling texture kinetics during thermal processing of potato products.

PubMed

Moyano, P C; Troncoso, E; Pedreschi, F

2007-03-01

A kinetic model based on 2 irreversible serial chemical reactions has been proposed to fit experimental data of texture changes during thermal processing of potato products. The model links dimensionless maximum force F*(MAX) with processing time. Experimental texture changes were obtained during frying of French fries and potato chips at different temperatures, while literature data for blanching/cooking of potato cubes have been considered. A satisfactory agreement between experimental and predicted values was observed, with root mean square values (RMSs) in the range of 4.7% to 16.4% for French fries and 16.7% to 29.3% for potato chips. In the case of blanching/cooking, the proposed model gave RMSs in the range of 1.2% to 17.6%, much better than the 6.2% to 44.0% obtained with the traditional 1st-order kinetics. The model is able to predict likewise the transition from softening to hardening of the tissue during frying.

Height-Diameter Equations for 12 Upland Species in the Missouri Ozark Highlands

Treesearch

J.R. Lootens; David R. Larsen; Stephen R. Shifley

2007-01-01

We calibrated a model predicting total tree height as a function of tree diameter for nine tree species common to the Missouri Ozarks. Model coefficients were derived from nearly 10,000 observed trees. The calibrated model did a good job predicting the mean height-diameter trend for each species (pseudo-R2 values ranged from 0.56 to 0.88), but...

Evaluating the predictive accuracy and the clinical benefit of a nomogram aimed to predict survival in node-positive prostate cancer patients: External validation on a multi-institutional database.

PubMed

Bianchi, Lorenzo; Schiavina, Riccardo; Borghesi, Marco; Bianchi, Federico Mineo; Briganti, Alberto; Carini, Marco; Terrone, Carlo; Mottrie, Alex; Gacci, Mauro; Gontero, Paolo; Imbimbo, Ciro; Marchioro, Giansilvio; Milanese, Giulio; Mirone, Vincenzo; Montorsi, Francesco; Morgia, Giuseppe; Novara, Giacomo; Porreca, Angelo; Volpe, Alessandro; Brunocilla, Eugenio

2018-04-06

To assess the predictive accuracy and the clinical value of a recent nomogram predicting cancer-specific mortality-free survival after surgery in pN1 prostate cancer patients through an external validation. We evaluated 518 prostate cancer patients treated with radical prostatectomy and pelvic lymph node dissection with evidence of nodal metastases at final pathology, at 10 tertiary centers. External validation was carried out using regression coefficients of the previously published nomogram. The performance characteristics of the model were assessed by quantifying predictive accuracy, according to the area under the curve in the receiver operating characteristic curve and model calibration. Furthermore, we systematically analyzed the specificity, sensitivity, positive predictive value and negative predictive value for each nomogram-derived probability cut-off. Finally, we implemented decision curve analysis, in order to quantify the nomogram's clinical value in routine practice. External validation showed inferior predictive accuracy as referred to in the internal validation (65.8% vs 83.3%, respectively). The discrimination (area under the curve) of the multivariable model was 66.7% (95% CI 60.1-73.0%) by testing with receiver operating characteristic curve analysis. The calibration plot showed an overestimation throughout the range of predicted cancer-specific mortality-free survival rates probabilities. However, in decision curve analysis, the nomogram's use showed a net benefit when compared with the scenarios of treating all patients or none. In an external setting, the nomogram showed inferior predictive accuracy and suboptimal calibration characteristics as compared to that reported in the original population. However, decision curve analysis showed a clinical net benefit, suggesting a clinical implication to correctly manage pN1 prostate cancer patients after surgery. © 2018 The Japanese Urological Association.

Correlation of transient elastography with hepatic venous pressure gradient in patients with cirrhotic portal hypertension: A study of 326 patients from India.

PubMed

Kumar, Ashish; Khan, Noor Muhammad; Anikhindi, Shrihari Anil; Sharma, Praveen; Bansal, Naresh; Singla, Vikas; Arora, Anil

2017-01-28

To study the diagnostic accuracy of transient elastography (TE) for detecting clinically significant portal hypertension (CSPH) in Indian patients with cirrhotic portal hypertension. This retrospective study was conducted at the Institute of Liver, Gastroenterology, and Pancreatico-Biliary Sciences, Sir Ganga Ram Hospital, New Delhi, on consecutive patients with cirrhosis greater than 15 years of age who underwent hepatic venous pressure gradient (HVPG) and TE from July 2011 to May 2016. Correlation between HVPG and TE was analyzed using the Spearman's correlation test. Receiver operating characteristic (ROC) curves were prepared for determining the utility of TE in predicting various stages of portal hypertension. The best cut-off value of TE for the diagnosis of CSPH was obtained using the Youden index. The study included 326 patients [median age 52 (range 16-90) years; 81% males]. The most common etiology of cirrhosis was cryptogenic (45%) followed by alcohol (34%). The median HVPG was 16.0 (range 1.5 to 30.5) mmHg. Eighty-five percent of patients had CSPH. A significant positive correlation was noted between TE and HVPG (rho 0.361, P < 0.001). The area under ROC curve for TE in predicting CSPH was 0.740 (95%CI: 0.662-0.818) ( P < 0.01). A cut-off value of TE of 21.6 kPa best predicted CSPH with a positive predictive value (PPV) of 93%. TE has a fair positive correlation with HVPG; thus, TE can be used as a non-invasive modality to assess the degree of portal hypertension. A cut-off TE value of 21.6 kPa identifies CSPH with a PPV of 93%.

Correlation of transient elastography with hepatic venous pressure gradient in patients with cirrhotic portal hypertension: A study of 326 patients from India

PubMed Central

Kumar, Ashish; Khan, Noor Muhammad; Anikhindi, Shrihari Anil; Sharma, Praveen; Bansal, Naresh; Singla, Vikas; Arora, Anil

2017-01-01

AIM To study the diagnostic accuracy of transient elastography (TE) for detecting clinically significant portal hypertension (CSPH) in Indian patients with cirrhotic portal hypertension. METHODS This retrospective study was conducted at the Institute of Liver, Gastroenterology, and Pancreatico-Biliary Sciences, Sir Ganga Ram Hospital, New Delhi, on consecutive patients with cirrhosis greater than 15 years of age who underwent hepatic venous pressure gradient (HVPG) and TE from July 2011 to May 2016. Correlation between HVPG and TE was analyzed using the Spearman’s correlation test. Receiver operating characteristic (ROC) curves were prepared for determining the utility of TE in predicting various stages of portal hypertension. The best cut-off value of TE for the diagnosis of CSPH was obtained using the Youden index. RESULTS The study included 326 patients [median age 52 (range 16-90) years; 81% males]. The most common etiology of cirrhosis was cryptogenic (45%) followed by alcohol (34%). The median HVPG was 16.0 (range 1.5 to 30.5) mmHg. Eighty-five percent of patients had CSPH. A significant positive correlation was noted between TE and HVPG (rho 0.361, P < 0.001). The area under ROC curve for TE in predicting CSPH was 0.740 (95%CI: 0.662-0.818) (P < 0.01). A cut-off value of TE of 21.6 kPa best predicted CSPH with a positive predictive value (PPV) of 93%. CONCLUSION TE has a fair positive correlation with HVPG; thus, TE can be used as a non-invasive modality to assess the degree of portal hypertension. A cut-off TE value of 21.6 kPa identifies CSPH with a PPV of 93%. PMID:28216976

Prediction of area under the curve for a p-glycoprotein, a CYP3A4 and a CYP2C9 substrate using a single time point strategy: assessment using fexofenadine, itraconazole and losartan and metabolites.

PubMed

Srinivas, Nuggehally R

2016-01-01

In the present age of polypharmacy, limited sampling strategy becomes important to verify if drug levels are within the prescribed threshold limits from efficacy and safety considerations. The need to establish reliable single time concentration dependent models to predict exposure becomes important from cost and time perspectives. A simple unweighted linear regression model was developed to describe the relationship between Cmax versus AUC for fexofenadine, losartan, EXP3174, itraconazole and hydroxyitraconazole. The fold difference, defined as the quotient of the observed and predicted AUC values, were evaluated along with statistical comparison of the predicted versus observed values. The correlation between Cmax versus AUC was well established for all the five drugs with a correlation coefficient (r) ranging from 0.9130 to 0.9997. Majority of the predicted values for all the five drugs (77%) were contained within a narrow boundary of 0.75- to 1.5-fold difference. The r values for observed versus predicted AUC were 0.9653 (n = 145), 0.8342 (n = 76), 0.9524 (n = 88), 0.9339 (n = 89) and 0.9452 (n = 66) for fexofenadine, losartan, EXP3174, itraconazole and hydroxyitraconazole, respectively. Cmax versus AUC relationships were established for all drugs and were amenable for limited sampling strategy for AUC prediction. However, fexofenadine, EXP3174 and hydroxyitraconazole may be most relevant for AUC prediction by a single time concentration as judged by the various criteria applied in this study.

Comparison of midlatitude ionospheric F region peak parameters and topside Ne profiles from IRI2012 model prediction with ground-based ionosonde and Alouette II observations

NASA Astrophysics Data System (ADS)

Gordiyenko, G. I.; Yakovets, A. F.

2017-07-01

The ionospheric F2 peak parameters recorded by a ground-based ionosonde at the midlatitude station Alma-Ata [43.25N, 76.92E] were compared with those obtained using the latest version of the IRI model (http://omniweb.gsfc.nasa.gov/vitmo/iri2012_vitmo.html). It was found that for the Alma-Ata (Kazakhstan) location, the IRI2012 model describes well the morphology of seasonal and diurnal variations of the ionospheric critical frequency (foF2) and peak density height (hmF2) monthly medians. The model errors in the median foF2 prediction (percentage deviations between the median foF2 values and their model predictions) were found to vary approximately in the range from about -20% to 34% and showed a stable overestimation in the median foF2 values for daytime in January and July and underestimation for day- and nighttime hours in the equinoctial months. The comparison between the ionosonde hmF2 and IRI results clearly showed that the IRI overestimates the nighttime hmF2 values for March and September months, and the difference is up to 30 km. The daytime Alma-Ata hmF2 data were found to be close to the IRI predictions (deviations are approximately ±10-15 km) in winter and equinoctial months, except in July when the observed hmF2 values were much more (from approximately 50-200 km). The comparison between the Alouette foF2 data and IRI predictions showed mixed results. In particular, the Alouette foF2 data showed a tendency to be overestimated for daytime in winter months similar to the ionosonde data; however, the overestimated foF2 values for nighttime in the autumn equinox were in disagreement with the ionosonde observations. There were large deviations between the observed hmF2 values and their model predictions. The largest deviations were found during winter and summer (up to -90 km). The comparison of the Alouette II electron density profiles with those predicted by the adapted IRI2012 model in the altitude range hmF2 of the satellite position showed a great difference in the shape of the Alouette-, NeQuick-, IRI02-coorr, and IRI2001-derived Ne profiles, with overestimated Ne values at some altitudes and underestimated Ne values at others. The results obtained in the study showed that the observation-model differences were significant especially for the real observed (not median) data. For practical application, it is clearly important for the IRI2012 model to be adapted to the observed F2-layer peak parameters. However, the model does not offer a simple solution to predict the shape of the vertical electron density profile in the topside ionosphere, because of the problem with the topside shape parameters.

Fetal nasal bone length and Down syndrome during the second trimester in a Chinese population.

PubMed

Hung, Jeng-Hsiu; Fu, Chong Yau; Chen, Chih-Yao; Chao, Kuan-Chong; Hung, Jamie

2008-08-01

The purpose of the present study was to build a database of reference ranges of fetal nasal bone length (NBL) in a Chinese population. The accuracy rate of detecting Down syndrome was also analyzed using fetal NBL as a marker. The control group of fetuses included 342 normal singleton pregnancies with no chromosomal or congenital anomalies. The present study was a cross-section study and the control group was used to construct percentile values of NBL from 13 to 29 gestational weeks of age. Two-dimensional ultrasonography was used for the nasal bone studies. Measurements of NBL were collected and each fetus contributed a single value to the reference sample. During the study period, 14 fetuses with Down syndrome were examined. Measurement of fetal NBL was made during amniocentesis, with gestational age ranging from 13 to 19 weeks. From 342 normal fetuses with gestational age ranging from 13 to 29 weeks, reference ranges of NBL were constructed. The reference ranges were constructed from the 100(1 - p)% reference range: Y +/- Zp x square root sigma 2, where Y = 25 - exp(3.58 - 0.044 x t + 0.0006 x t2), with Y being the fitted mean of regression model and t being gestational age (weeks). Using fetal NBL, the regression model was Pr(Down syndrome) = exp(W)/ [1 + exp(W)], where W = 0.62-4.80 x NBL (multiples of the median) in predicting Down syndrome. Fetal NBL was found to have a sensitivity and specificity of 0.78 and 0.78, respectively, in predicting Down syndrome in the second trimester of pregnancy. Fetal NBL measurement can provide a simple and useful algorithm to predict Down syndrome during the second trimester of pregnancy.

Quantification of polyhydroxyalkanoates in mixed and pure cultures biomass by Fourier transform infrared spectroscopy: comparison of different approaches.

PubMed

Isak, I; Patel, M; Riddell, M; West, M; Bowers, T; Wijeyekoon, S; Lloyd, J

2016-08-01

Fourier transform infrared (FTIR) spectroscopy was used in this study for the rapid quantification of polyhydroxyalkanoates (PHA) in mixed and pure culture bacterial biomass. Three different statistical analysis methods (regression, partial least squares (PLS) and nonlinear) were applied to the FTIR data and the results were plotted against the PHA values measured with the reference gas chromatography technique. All methods predicted PHA content in mixed culture biomass with comparable efficiency, indicated by similar residuals values. The PHA in these cultures ranged from low to medium concentration (0-44 wt% of dried biomass content). However, for the analysis of the combined mixed and pure culture biomass with PHA concentration ranging from low to high (0-93% of dried biomass content), the PLS method was most efficient. This paper reports, for the first time, the use of a single calibration model constructed with a combination of mixed and pure cultures covering a wide PHA range, for predicting PHA content in biomass. Currently no one universal method exists for processing FTIR data for polyhydroxyalkanoates (PHA) quantification. This study compares three different methods of analysing FTIR data for quantification of PHAs in biomass. A new data-processing approach was proposed and the results were compared against existing literature methods. Most publications report PHA quantification of medium range in pure culture. However, in our study we encompassed both mixed and pure culture biomass containing a broader range of PHA in the calibration curve. The resulting prediction model is useful for rapid quantification of a wider range of PHA content in biomass. © 2016 The Society for Applied Microbiology.

A rapid analytical method for predicting the oxygen demand of wastewater.

PubMed

Fogelman, Shoshana; Zhao, Huijun; Blumenstein, Michael

2006-11-01

In this study, an investigation was undertaken to determine whether the predictive accuracy of an indirect, multiwavelength spectroscopic technique for rapidly determining oxygen demand (OD) values is affected by the use of unfiltered and turbid samples, as well as by the use of absorbance values measured below 200 nm. The rapid OD technique was developed that uses UV-Vis spectroscopy and artificial neural networks (ANNs) to indirectly determine chemical oxygen demand (COD) levels. It was found that the most accurate results were obtained when a spectral range of 190-350 nm was provided as data input to the ANN, and when using unfiltered samples below a turbidity range of 150 NTU. This is because high correlations of above 0.90 were obtained with the data using the standard COD method. This indicates that samples can be measured directly without the additional need for preprocessing by filtering. Samples with turbidity values higher than 150 NTU were found to produce poor correlations with the standard COD method, which made them unsuitable for accurate, real-time, on-line monitoring of OD levels.

Scaling approach in predicting the seatbelt loading and kinematics of vulnerable occupants: How far can we go?

PubMed

Nie, Bingbing; Forman, Jason L; Joodaki, Hamed; Wu, Taotao; Kent, Richard W

2016-09-01

Occupants with extreme body size and shape, such as the small female or the obese, were reported to sustain high risk of injury in motor vehicle crashes (MVCs). Dimensional scaling approaches are widely used in injury biomechanics research based on the assumption of geometrical similarity. However, its application scope has not been quantified ever since. The objective of this study is to demonstrate the valid range of scaling approaches in predicting the impact response of the occupants with focus on the vulnerable populations. The present analysis was based on a data set consisting of 60 previously reported frontal crash tests in the same sled buck representing a typical mid-size passenger car. The tests included two categories of human surrogates: 9 postmortem human surrogates (PMHS) of different anthropometries (stature range: 147-189 cm; weight range: 27-151 kg) and 5 anthropomorphic test devices (ATDs). The impact response was considered including the restraint loads and the kinematics of multiple body segments. For each category of the human surrogates, a mid-size occupant was selected as a baseline and the impact response was scaled specifically to another subject based on either the body mass (body shape) or stature (the overall body size). To identify the valid range of the scaling approach, the scaled response was compared to the experimental results using assessment scores on the peak value, peak timing (the time when the peak value occurred), and the overall curve shape ranging from 0 (extremely poor) to 1 (perfect match). Scores of 0.7 to 0.8 and 0.8 to 1.0 indicate fair and acceptable prediction. For both ATDs and PMHS, the scaling factor derived from body mass proved an overall good predictor of the peak timing for the shoulder belt (0.868, 0.829) and the lap belt (0.858, 0.774) and for the peak value of the lap belt force (0.796, 0.869). Scaled kinematics based on body stature provided fair or acceptable prediction on the overall head/shoulder kinematics (0.741, 0.822 for the head; 0.817, 0.728 for the shoulder) regardless of the anthropometry. The scaling approach exhibited poor prediction capability on the curve shape for the restraint force (0.494 and 0.546 for the shoulder belt; 0.585 and 0.530 for the lap belt). It also cannot well predict the excursion of the pelvis and the knee. The results revealed that for the peak lap belt force and the forward motion of the head and shoulder, the underlying linear relationship with body size and shape is valid over a wide anthropometric range. The chaotic nature of the dynamic response cannot be fully recovered by the assumption of the whole-body geometrical similarity, especially for the curve shape. The valid range of the scaling approach established in this study can be reasonably referenced in predicting the impact response of a given specific population with expected deviation. Application of this knowledge also includes proposing strategies for restraint configuration and providing reference for ATD and/or human body model (HBM) development for vulnerable occupants.

Prediction of heat capacities of solid inorganic salts from group contributions

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

Mostafa, A.T.M.G.; Eakman, J.M.; Yarbro, S.L.

1997-01-01

A group contribution technique is proposed to predict the coefficients in the heat capacity correlation, C{sub p} = a + bT + c/T{sup 2} + dT{sup 2}, for solid inorganic salts. The results from this work are compared with fits to experimental data from the literature. It is shown to give good predictions for both simple and complex solid inorganic salts. Literature heat capacities for a large number (664) of solid inorganic salts covering a broad range of cations (129), anions (17) and ligands (2) have been used in regressions to obtain group contributions for the parameters in the heatmore » capacity temperature function. A mean error of 3.18% is found when predicted values are compared with literature values for heat capacity at 298{degrees} K. Estimates of the error standard deviation from the regression for each additivity constant are also determined.« less

Cortisol Secretion and Change in Sleep Problems in Early Childhood: Moderation by Maternal Overcontrol

PubMed Central

Kiel, Elizabeth J.; Hummel, Alexandra C.; Luebbe, Aaron M.

2015-01-01

Childhood sleep problems are prevalent and relate to a wide range of negative psychological outcomes. However, it remains unclear how biological processes, such as HPA activity, may predict sleep problems over time in childhood in the context of certain parenting environments. Fifty-one mothers and their 18–20 month-old toddlers participated in a short-term longitudinal study assessing how shared variance among morning levels, diurnal change, and nocturnal change in toddlers’ cortisol secretion predicted change in sleep problems in the context of maternal overprotection and critical control. A composite characterized by low variability in, and, to a lesser extent, high morning values of cortisol, predicted increasing sleep problems from age 2 to age 3 when mothers reported high critical control. Results suggest value in assessing shared variance among different indices of cortisol secretion patterns and the interaction between cortisol and the environment in predicting sleep problems in early childhood. PMID:25766262

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

Apparent diffusion coefficient mapping in medulloblastoma predicts non-infiltrative surgical planes.

PubMed

Marupudi, Neena I; Altinok, Deniz; Goncalves, Luis; Ham, Steven D; Sood, Sandeep

2016-11-01

An appropriate surgical approach for posterior fossa lesions is to start tumor removal from areas with a defined plane to where tumor is infiltrating the brainstem or peduncles. This surgical approach minimizes risk of damage to eloquent areas. Although magnetic resonance imaging (MRI) is the current standard preoperative imaging obtained for diagnosis and surgical planning of pediatric posterior fossa tumors, it offers limited information on the infiltrative planes between tumor and normal structures in patients with medulloblastomas. Because medulloblastomas demonstrate diffusion restriction on apparent diffusion coefficient map (ADC map) sequences, we investigated the role of ADC map in predicting infiltrative and non-infiltrative planes along the brain stem and/or cerebellar peduncles by medulloblastomas prior to surgery. Thirty-four pediatric patients with pathologically confirmed medulloblastomas underwent surgical resection at our facility from 2004 to 2012. An experienced pediatric neuroradiologist reviewed the brain MRIs/ADC map, assessing the planes between the tumor and cerebellar peduncles/brain stem. An independent evaluator documented surgical findings from operative reports for comparison to the radiographic findings. The radiographic findings were statistically compared to the documented intraoperative findings to determine predictive value of the test in identifying tumor infiltration of the brain stem cerebellar peduncles. Twenty-six patients had preoperative ADC mapping completed and thereby, met inclusion criteria. Mean age at time of surgery was 8.3 ± 4.6 years. Positive predictive value of ADC maps to predict tumor invasion of the brain stem and cerebellar peduncles ranged from 69 to 88 %; negative predictive values ranged from 70 to 89 %. Sensitivity approached 93 % while specificity approached 78 %. ADC maps are valuable in predicting the infiltrative and non-infiltrative planes along the tumor and brain stem interface in medulloblastomas. Inclusion and evaluation of ADC maps in preoperative evaluation can assist in surgical resection planning in patients with medulloblastoma.

Interval Predictor Models with a Formal Characterization of Uncertainty and Reliability

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Giesy, Daniel P.; Kenny, Sean P.

2014-01-01

This paper develops techniques for constructing empirical predictor models based on observations. By contrast to standard models, which yield a single predicted output at each value of the model's inputs, Interval Predictors Models (IPM) yield an interval into which the unobserved output is predicted to fall. The IPMs proposed prescribe the output as an interval valued function of the model's inputs, render a formal description of both the uncertainty in the model's parameters and of the spread in the predicted output. Uncertainty is prescribed as a hyper-rectangular set in the space of model's parameters. The propagation of this set through the empirical model yields a range of outputs of minimal spread containing all (or, depending on the formulation, most) of the observations. Optimization-based strategies for calculating IPMs and eliminating the effects of outliers are proposed. Outliers are identified by evaluating the extent by which they degrade the tightness of the prediction. This evaluation can be carried out while the IPM is calculated. When the data satisfies mild stochastic assumptions, and the optimization program used for calculating the IPM is convex (or, when its solution coincides with the solution to an auxiliary convex program), the model's reliability (that is, the probability that a future observation would be within the predicted range of outputs) can be bounded rigorously by a non-asymptotic formula.

The discriminatory capability of existing scores to predict advanced colorectal neoplasia: a prospective colonoscopy study of 5,899 screening participants.

PubMed

Wong, Martin C S; Ching, Jessica Y L; Ng, Simpson; Lam, Thomas Y T; Luk, Arthur K C; Wong, Sunny H; Ng, Siew C; Ng, Simon S M; Wu, Justin C Y; Chan, Francis K L; Sung, Joseph J Y

2016-02-03

We evaluated the performance of seven existing risk scoring systems in predicting advanced colorectal neoplasia in an asymptomatic Chinese cohort. We prospectively recruited 5,899 Chinese subjects aged 50-70 years in a colonoscopy screening programme(2008-2014). Scoring systems under evaluation included two scoring tools from the US; one each from Spain, Germany, and Poland; the Korean Colorectal Screening(KCS) scores; and the modified Asia Pacific Colorectal Screening(APCS) scores. The c-statistics, sensitivity, specificity, positive predictive values(PPVs), and negative predictive values(NPVs) of these systems were evaluated. The resources required were estimated based on the Number Needed to Screen(NNS) and the Number Needed to Refer for colonoscopy(NNR). Advanced neoplasia was detected in 364 (6.2%) subjects. The German system referred the least proportion of subjects (11.2%) for colonoscopy, whilst the KCS scoring system referred the highest (27.4%). The c-statistics of all systems ranged from 0.56-0.65, with sensitivities ranging from 0.04-0.44 and specificities from 0.74-0.99. The modified APCS scoring system had the highest c-statistics (0.65, 95% C.I. 0.58-0.72). The NNS (12-19) and NNR (5-10) were similar among the scoring systems. The existing scoring systems have variable capability to predict advanced neoplasia among asymptomatic Chinese subjects, and further external validation should be performed.

Parameterizing the Spatial Markov Model from Breakthrough Curve Data Alone

NASA Astrophysics Data System (ADS)

Sherman, T.; Bolster, D.; Fakhari, A.; Miller, S.; Singha, K.

2017-12-01

The spatial Markov model (SMM) uses a correlated random walk and has been shown to effectively capture anomalous transport in porous media systems; in the SMM, particles' future trajectories are correlated to their current velocity. It is common practice to use a priori Lagrangian velocity statistics obtained from high resolution simulations to determine a distribution of transition probabilities (correlation) between velocity classes that govern predicted transport behavior; however, this approach is computationally cumbersome. Here, we introduce a methodology to quantify velocity correlation from Breakthrough (BTC) curve data alone; discretizing two measured BTCs into a set of arrival times and reverse engineering the rules of the SMM allows for prediction of velocity correlation, thereby enabling parameterization of the SMM in studies where Lagrangian velocity statistics are not available. The introduced methodology is applied to estimate velocity correlation from BTCs measured in high resolution simulations, thus allowing for a comparison of estimated parameters with known simulated values. Results show 1) estimated transition probabilities agree with simulated values and 2) using the SMM with estimated parameterization accurately predicts BTCs downstream. Additionally, we include uncertainty measurements by calculating lower and upper estimates of velocity correlation, which allow for prediction of a range of BTCs. The simulated BTCs fall in the range of predicted BTCs. This research proposes a novel method to parameterize the SMM from BTC data alone, thereby reducing the SMM's computational costs and widening its applicability.

Study on elevated-temperature flow behavior of Ni-Cr-Mo-B ultra-heavy-plate steel via experiment and modelling

NASA Astrophysics Data System (ADS)

Gao, Zhi-yu; Kang, Yu; Li, Yan-shuai; Meng, Chao; Pan, Tao

2018-04-01

Elevated-temperature flow behavior of a novel Ni-Cr-Mo-B ultra-heavy-plate steel was investigated by conducting hot compressive deformation tests on a Gleeble-3800 thermo-mechanical simulator at a temperature range of 1123 K–1423 K with a strain rate range from 0.01 s‑1 to10 s‑1 and a height reduction of 70%. Based on the experimental results, classic strain-compensated Arrhenius-type, a new revised strain-compensated Arrhenius-type and classic modified Johnson-Cook constitutive models were developed for predicting the high-temperature deformation behavior of the steel. The predictability of these models were comparatively evaluated in terms of statistical parameters including correlation coefficient (R), average absolute relative error (AARE), average root mean square error (RMSE), normalized mean bias error (NMBE) and relative error. The statistical results indicate that the new revised strain-compensated Arrhenius-type model could give prediction of elevated-temperature flow stress for the steel accurately under the entire process conditions. However, the predicted values by the classic modified Johnson-Cook model could not agree well with the experimental values, and the classic strain-compensated Arrhenius-type model could track the deformation behavior more accurately compared with the modified Johnson-Cook model, but less accurately with the new revised strain-compensated Arrhenius-type model. In addition, reasons of differences in predictability of these models were discussed in detail.

Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers.

PubMed

Crossa, José; Campos, Gustavo de Los; Pérez, Paulino; Gianola, Daniel; Burgueño, Juan; Araus, José Luis; Makumbi, Dan; Singh, Ravi P; Dreisigacker, Susanne; Yan, Jianbing; Arief, Vivi; Banziger, Marianne; Braun, Hans-Joachim

2010-10-01

The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.

Accuracy and Predictability of PANC-3 Scoring System over APACHE II in Acute Pancreatitis: A Prospective Study.

PubMed

Rathnakar, Surag Kajoor; Vishnu, Vikram Hubbanageri; Muniyappa, Shridhar; Prasath, Arun

2017-02-01

Acute Pancreatitis (AP) is one of the common conditions encountered in the emergency room. The course of the disease ranges from mild form to severe acute form. Most of these episodes are mild and spontaneously subsiding within 3 to 5 days. In contrast, Severe Acute Pancreatitis (SAP) occurring in around 15-20% of all cases, mortality can range between 10 to 85% across various centres and countries. In such a situation we need an indicator which can predict the outcome of an attack, as severe or mild, as early as possible and such an indicator should be sensitive and specific enough to trust upon. PANC-3 scoring is such a scoring system in predicting the outcome of an attack of AP. To assess the accuracy and predictability of PANC-3 scoring system over APACHE II in predicting severity in an attack of AP. This prospective study was conducted on 82 patients admitted with the diagnosis of pancreatitis. Investigations to evaluate PANC-3 and APACHE II were done on all the patients and the PANC-3 and APACHE II score was calculated. PANC-3 score has a sensitivity of 82.6% and specificity of 77.9%, the test had a Positive Predictive Value (PPV) of 0.59 and Negative Predictive Value (NPV) of 0.92. Sensitivity of APACHE II in predicting SAP was 91.3% and specificity was 96.6% with PPV of 0.91, NPV was 0.96. Our study shows that PANC-3 can be used to predict the severity of pancreatitis as efficiently as APACHE II. The interpretation of PANC-3 does not need expertise and can be applied at the time of admission which is an advantage when compared to classical scoring systems.

Investigation of Universal Behavior in Symmetric Diblock Copolymer Melts

NASA Astrophysics Data System (ADS)

Medapuram, Pavani

Coarse-grained theories of dense polymer liquids such as block copolymer melts predict a universal dependence of equilibrium properties on a few dimensionless parameters. For symmetric diblock copolymer melts, such theories predict a universal dependence on only chieN and N¯, where chie is an effective interaction parameter, N is the degree of polymerization, and N¯ is a measure of overlap. This thesis focuses on testing the universal behavior hypothesis by comparing results for various properties obtained from different coarse-grained simulation models to each other. Specifically, results from pairs of simulations of different models that have been designed to have matched values of N¯ are compared over a range of values of chiN. The use of vastly different simulation models allows us to cover a vast range of chi eN ≃ 200 - 8000 that includes most of the experimentally relevant range. Properties studied here include collective and single-chain correlations in the disordered phase, block and chain radii of gyration in the disordered phase, the value of chieN at the order-disorder transition (ODT), the free energy per chain, the latent heat of transition, the layer spacing, the composition profile, and compression modulus in the ordered phase. All results strongly support the universal scaling hypothesis, even for rather short chains, confirming that it is indeed possible to give an accurate universal description of simulation models that differ in many details. The underlying universality becomes apparent, however, only if data are analyzed using an adequate estimate of chie, which we obtained by fitting the structure factor S( q) in the disordered state to predictions of the recently developed renormalized one-loop (ROL) theory. The ROL theory is shown to provide an excellent description of the dependence of S(q on chain length and thermodynamic conditions for all models, even for very short chains, if we allow for the existence of a nonlinear dependence of the effective interaction parameter chie upon the strength of the AB repulsion. The results show that behavior near the ODT exhibits a different character at moderate and high values of N¯, with a crossover near N¯ ≃ 104. Within the range N¯ ≤sssim 104 studied in this work, the ordered and disordered phases near the ODT both contain strongly segregated domains of nearly pure A and B, in contrast to the assumption of weak segregation underlying the Fredrickson-Helfand (FH) theory. In this regime, the FH theory is inaccurate and substantially underestimates the value of chieN at the ODT. Results for the highest values of N¯ studied here agree reasonably well with FH predictions, suggesting that the theory may be accurate for N¯ gtrsim 104. Self-consistent field theory (SCFT) grossly underestimates (chieN)ODT for modest N¯ because it cannot describe strong correlations in the disordered phase. SCFT is found, however, to yield accurate predictions for several properties of the ordered lamellar phase. A detailed quantitative comparison of experimental results to theoretical predictions and obtained simulations results is also presented. Experimental results for structure factor obtained from small-angle neutron and X-ray scattering (SANS and SAXS) measurements are analyzed using methods closely analogous to those used to analyze simulation results. Peak scattering intensity results of different chain lengths of a AB pair are fitted to the ROL theory predictions in order to estimate the effective interaction parameter chi e(T) of the chemical system. The resulting chi e(T) estimates are used to obtain ODT values (chieN)ODT of different experimental systems, which we compare to the scaling law obtained from simulation results and to theoretical predictions. The results are largely consistent with the expected systematic decrease with increasing N¯ and lie closer to the simulations scaling law than to any theoretical prediction. These results confirm the overwhelming importance of fluctuation effects in systems with modest values of N¯ = 102 - 103, and the usefulness of coarse-grained simulations as a starting point for quantitative modeling.

External Validation of Risk Prediction Scores for Invasive Candidiasis in a Medical/Surgical Intensive Care Unit: An Observational Study

PubMed Central

Ahmed, Armin; Baronia, Arvind Kumar; Azim, Afzal; Marak, Rungmei S. K.; Yadav, Reema; Sharma, Preeti; Gurjar, Mohan; Poddar, Banani; Singh, Ratender Kumar

2017-01-01

Background: The aim of this study was to conduct external validation of risk prediction scores for invasive candidiasis. Methods: We conducted a prospective observational study in a 12-bedded adult medical/surgical Intensive Care Unit (ICU) to evaluate Candida score >3, colonization index (CI) >0.5, corrected CI >0.4 (CCI), and Ostrosky's clinical prediction rule (CPR). Patients' characteristics and risk factors for invasive candidiasis were noted. Patients were divided into two groups; invasive candidiasis and no-invasive candidiasis. Results: Of 198 patients, 17 developed invasive candidiasis. Discriminatory power (area under receiver operator curve [AUROC]) for Candida score, CI, CCI, and CPR were 0.66, 0.67, 0.63, and 0.62, respectively. A large number of patients in the no-invasive candidiasis group (114 out of 181) were exposed to antifungal agents during their stay in ICU. Subgroup analysis was carried out after excluding such patients from no-invasive candidiasis group. AUROC of Candida score, CI, CCI, and CPR were 0.7, 0.7, 0.65, and 0.72, respectively, and positive predictive values (PPVs) were in the range of 25%–47%, along with negative predictive values (NPVs) in the range of 84%–96% in the subgroup analysis. Conclusion: Currently available risk prediction scores have good NPV but poor PPV. They are useful for selecting patients who are not likely to benefit from antifungal therapy. PMID:28904481

Hemoglobin A1c can be helpful in predicting progression to diabetes after Whipple procedure.

PubMed

Hamilton, Lisa; Jeyarajah, D Rohan

2007-01-01

Normoglycemic patients undergoing pancreaticoduodenectomy (Whipple procedure) often inquire whether they will be diabetic postoperatively. There is limited information on this issue. We therefore looked at a more subtle measurement of long-term glycemic control, hemoglobin A1c (HgbA1c), as a prognostic tool in predicting progression to diabetes post Whipple. A retrospective review over a 6-year period of all patients undergoing Whipple procedures at a single institution was conducted. In all, 27 patients had no prior history of diabetes, complete follow-up, and measured preoperative HgbA1c values. Postoperative diabetes was defined as the need for oral hypoglycemic agents or insulin. These charts were analyzed for progression to diabetes after Whipple. Of the 27 patients, 10 were considered to have postoperative diabetes. The average preoperative HgbA1c value for these patients was 6.3+/-0.66. This was statistically different from the 17 patients without postoperative diabetes (average HgbA1c 5.2+/-0.39, p<0.001). The positive predictive value, negative predictive value, sensitivity, and specificity were 82%, 94%, 90%, and 88%, respectively. This study demonstrates that progression to diabetes is very unlikely after Whipple operation if the preoperative HgbA1c value is in the normal range. The apparent utility of HgbA1c in predicting postoperative diabetes in this small study suggests that this laboratory test may be very helpful in counseling patients for Whipple operation.

Model-based prediction of myelosuppression and recovery based on frequent neutrophil monitoring.

PubMed

Netterberg, Ida; Nielsen, Elisabet I; Friberg, Lena E; Karlsson, Mats O

2017-08-01

To investigate whether a more frequent monitoring of the absolute neutrophil counts (ANC) during myelosuppressive chemotherapy, together with model-based predictions, can improve therapy management, compared to the limited clinical monitoring typically applied today. Daily ANC in chemotherapy-treated cancer patients were simulated from a previously published population model describing docetaxel-induced myelosuppression. The simulated values were used to generate predictions of the individual ANC time-courses, given the myelosuppression model. The accuracy of the predicted ANC was evaluated under a range of conditions with reduced amount of ANC measurements. The predictions were most accurate when more data were available for generating the predictions and when making short forecasts. The inaccuracy of ANC predictions was highest around nadir, although a high sensitivity (≥90%) was demonstrated to forecast Grade 4 neutropenia before it occurred. The time for a patient to recover to baseline could be well forecasted 6 days (±1 day) before the typical value occurred on day 17. Daily monitoring of the ANC, together with model-based predictions, could improve anticancer drug treatment by identifying patients at risk for severe neutropenia and predicting when the next cycle could be initiated.

Development and evaluation of a bioenergetics model for bull trout

USGS Publications Warehouse

Mesa, Matthew G.; Welland, Lisa K.; Christiansen, Helena E.; Sauter, Sally T.; Beauchamp, David A.

2013-01-01

We conducted laboratory experiments to parameterize a bioenergetics model for wild Bull Trout Salvelinus confluentus, estimating the effects of body mass (12–1,117 g) and temperature (3–20°C) on maximum consumption (C max) and standard metabolic rates. The temperature associated with the highest C max was 16°C, and C max showed the characteristic dome-shaped temperature-dependent response. Mass-dependent values of C max (N = 28) at 16°C ranged from 0.03 to 0.13 g·g−1·d−1. The standard metabolic rates of fish (N = 110) ranged from 0.0005 to 0.003 g·O2·g−1·d−1 and increased with increasing temperature but declined with increasing body mass. In two separate evaluation experiments, which were conducted at only one ration level (40% of estimated C max), the model predicted final weights that were, on average, within 1.2 ± 2.5% (mean ± SD) of observed values for fish ranging from 119 to 573 g and within 3.5 ± 4.9% of values for 31–65 g fish. Model-predicted consumption was within 5.5 ± 10.9% of observed values for larger fish and within 12.4 ± 16.0% for smaller fish. Our model should be useful to those dealing with issues currently faced by Bull Trout, such as climate change or alterations in prey availability.

CoMFA and CoMSIA 3D-QSAR studies on S(6)-(4-nitrobenzyl)mercaptopurine riboside (NBMPR) analogs as inhibitors of human equilibrative nucleoside transporter 1 (hENT1).

PubMed

Gupte, Amol; Buolamwini, John K

2009-01-15

3D-QSAR (CoMFA and CoMSIA) studies were performed on human equlibrative nucleoside transporter (hENT1) inhibitors displaying K(i) values ranging from 10,000 to 0.7nM. Both CoMFA and CoMSIA analysis gave reliable models with q2 values >0.50 and r2 values >0.92. The models have been validated for their stability and robustness using group validation and bootstrapping techniques and for their predictive abilities using an external test set of nine compounds. The high predictive r2 values of the test set (0.72 for CoMFA model and 0.74 for CoMSIA model) reveals that the models can prove to be a useful tool for activity prediction of newly designed nucleoside transporter inhibitors. The CoMFA and CoMSIA contour maps identify features important for exhibiting good binding affinities at the transporter, and can thus serve as a useful guide for the design of potential equilibrative nucleoside transporter inhibitors.

Integrating GLL-Weibull Distribution Within a Bayesian Framework for Life Prediction of Shape Memory Alloy Spring Undergoing Thermo-mechanical Fatigue

NASA Astrophysics Data System (ADS)

Kundu, Pradeep; Nath, Tameshwer; Palani, I. A.; Lad, Bhupesh K.

2018-06-01

The present paper tackles an important but unmapped problem of the reliability estimations of smart materials. First, an experimental setup is developed for accelerated life testing of the shape memory alloy (SMA) springs. Generalized log-linear Weibull (GLL-Weibull) distribution-based novel approach is then developed for SMA spring life estimation. Applied stimulus (voltage), elongation and cycles of operation are used as inputs for the life prediction model. The values of the parameter coefficients of the model provide better interpretability compared to artificial intelligence based life prediction approaches. In addition, the model also considers the effect of operating conditions, making it generic for a range of the operating conditions. Moreover, a Bayesian framework is used to continuously update the prediction with the actual degradation value of the springs, thereby reducing the uncertainty in the data and improving the prediction accuracy. In addition, the deterioration of material with number of cycles is also investigated using thermogravimetric analysis and scanning electron microscopy.

Use of the Biotic Ligand Model to predict metal toxicity to aquatic biota in areas of differing geology

USGS Publications Warehouse

Smith, Kathleen S.

2005-01-01

This work evaluates the use of the biotic ligand model (BLM), an aquatic toxicity model, to predict toxic effects of metals on aquatic biota in areas underlain by different rock types. The chemical composition of water, soil, and sediment is largely derived from the composition of the underlying rock. Geologic source materials control key attributes of water chemistry that affect metal toxicity to aquatic biota, including: 1) potentially toxic elements, 2) alkalinity, 3) total dissolved solids, and 4) soluble major elements, such as Ca and Mg, which contribute to water hardness. Miller (2002) compiled chemical data for water samples collected in watersheds underlain by ten different rock types, and in a mineralized area in western Colorado. He found that each rock type has a unique range of water chemistry. In this study, the ten rock types were grouped into two general categories, igneous and sedimentary. Water collected in watersheds underlain by sedimentary rock has higher mean pH, alkalinity, and calcium concentrations than water collected in watersheds underlain by igneous rock. Water collected in the mineralized area had elevated concentrations of calcium and sulfate in addition to other chemical constituents. Miller's water-chemistry data were used in the BLM (computer program) to determine copper and zinc toxicity to Daphnia magna. Modeling results show that waters from watersheds underlain by different rock types have characteristic ranges of predicted LC 50 values (a measurement of aquatic toxicity) for copper and zinc, with watersheds underlain by igneous rock having lower predicted LC 50 values than watersheds underlain by sedimentary rock. Lower predicted LC 50 values suggest that aquatic biota in watersheds underlain by igneous rock may be more vulnerable to copper and zinc inputs than aquatic biota in watersheds underlain by sedimentary rock. For both copper and zinc, there is a trend of increasing predicted LC 50 values with increasing dissolved organic carbon (DOC) concentrations. Predicted copper LC 50 values are extremely sensitive to DOC concentrations, whereas alkalinity appears to have an influence on zinc toxicity at alkalinities in excess of about 100 mg/L CaCO 3 . These findings show promise for coupling the BLM (computer program) with measured water-chemistry data to predict metal toxicity to aquatic biota in different geologic settings and under different scenarios. This approach may ultimately be a useful tool for mine-site planning, mitigation and remediation strategies, and ecological risk assessment.

Use of the partial farm budget technique to predict the economic impact of the flock management decision to use B-mode ultrasonographic pregnancy diagnosis.

PubMed

Sprecher, D J; Ley, W B; Whittier, W D; Bowen, J M; Thatcher, C D; Pelzer, K D; Moore, J M

1989-07-15

A computer spreadsheet was developed to predict the economic impact of a management decision to use B-mode ultrasonographic ovine pregnancy diagnosis. The spreadsheet design and spreadsheet cell formulas are provided. The program used the partial farm budget technique to calculate net return (NR) or cash flow changes that resulted from the decision to use ultrasonography. Using the program, either simple pregnancy diagnosis or pregnancy diagnosis with the ability to determine singleton or multiple pregnancies may be compared with no flock ultrasonographic pregnancy diagnosis. A wide range of user-selected regional variables are used to calculate the cash flow changes associated with the ultrasonography decisions. A variable may be altered through a range of values to conduct a sensitivity analysis of predicted NR. Example sensitivity analyses are included for flock conception rate, veterinary ultrasound fee, and the price of corn. Variables that influence the number of cull animals and the cost of ultrasonography have the greatest impact on predicted NR. Because the determination of singleton or multiple pregnancies is more time consuming, its economic practicality in comparison with simple pregnancy diagnosis is questionable. The value of feed saved by identifying and separately feeding ewes with singleton pregnancies is not offset by the increased ultrasonography cost.

Synthesis, structure, theoretical and experimental in vitro antioxidant/pharmacological properties of α-aryl, N-alkyl nitrones, as potential agents for the treatment of cerebral ischemia.

PubMed

Samadi, Abdelouahid; Soriano, Elena; Revuelta, Julia; Valderas, Carolina; Chioua, Mourad; Garrido, Ignacio; Bartolomé, Begoña; Tomassolli, Isabelle; Ismaili, Lhassane; González-Lafuente, Laura; Villarroya, Mercedes; García, Antonio G; Oset-Gasque, María J; Marco-Contelles, José

2011-01-15

The synthesis, structure, theoretical and experimental in vitro antioxidant properties using the DPPH, ORAC, and benzoic acid, as well as preliminary in vitro pharmacological activities of (Z)-α-aryl and heteroaryl N-alkyl-nitrones 6-15, 18, 19, 21, and 23, is reported. In the in vitro antioxidant activity, for the DPPH radical test, only nitrones bearing free phenol groups gave the best RSA (%) values, nitrones 13 and 14 showing the highest values in this assay. In the ORAC analysis, the most potent radical scavenger was nitrone indole 21, followed by the N-benzyl benzene-type nitrones 10 and 15. Interestingly enough, the archetypal nitrone 7 (PBN) gave a low RSA value (1.4%) in the DPPH test, or was inactive in the ORAC assay. Concerning the ability to scavenge the hydroxyl radical, all the nitrones studied proved active in this experiment, showing high values in the 94-97% range, the most potent being nitrone 14. The theoretical calculations for the prediction of the antioxidant power, and the potential of ionization confirm that nitrones 9 and 10 are among the best compounds in electron transfer processes, a result that is also in good agreement with the experimental values in the DPPH assay. The calculated energy values for the reaction of ROS (hydroxyl, peroxyl) with the nitrones predict that the most favourable adduct-spin will take place between nitrones 9, 10, and 21, a fact that would be in agreement with their experimentally observed scavenger ability. The in vitro pharmacological analysis showed that the neuroprotective profile of the target molecules was in general low, with values ranging from 0% to 18.7%, in human neuroblastoma cells stressed with a mixture of rotenone/oligomycin-A, being nitrones 18, and 6-8 the most potent, as they show values in the range 24-18.4%. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

A prediction model for early death in non-small cell lung cancer patients following curative-intent chemoradiotherapy.

PubMed

Jochems, Arthur; El-Naqa, Issam; Kessler, Marc; Mayo, Charles S; Jolly, Shruti; Matuszak, Martha; Faivre-Finn, Corinne; Price, Gareth; Holloway, Lois; Vinod, Shalini; Field, Matthew; Barakat, Mohamed Samir; Thwaites, David; de Ruysscher, Dirk; Dekker, Andre; Lambin, Philippe

2018-02-01

Early death after a treatment can be seen as a therapeutic failure. Accurate prediction of patients at risk for early mortality is crucial to avoid unnecessary harm and reducing costs. The goal of our work is two-fold: first, to evaluate the performance of a previously published model for early death in our cohorts. Second, to develop a prognostic model for early death prediction following radiotherapy. Patients with NSCLC treated with chemoradiotherapy or radiotherapy alone were included in this study. Four different cohorts from different countries were available for this work (N = 1540). The previous model used age, gender, performance status, tumor stage, income deprivation, no previous treatment given (yes/no) and body mass index to make predictions. A random forest model was developed by learning on the Maastro cohort (N = 698). The new model used performance status, age, gender, T and N stage, total tumor volume (cc), total tumor dose (Gy) and chemotherapy timing (none, sequential, concurrent) to make predictions. Death within 4 months of receiving the first radiotherapy fraction was used as the outcome. Early death rates ranged from 6 to 11% within the four cohorts. The previous model performed with AUC values ranging from 0.54 to 0.64 on the validation cohorts. Our newly developed model had improved AUC values ranging from 0.62 to 0.71 on the validation cohorts. Using advanced machine learning methods and informative variables, prognostic models for early mortality can be developed. Development of accurate prognostic tools for early mortality is important to inform patients about treatment options and optimize care.

Experimental evaluation of heat transfer on a 1030:1 area ratio rocket nozzle

NASA Technical Reports Server (NTRS)

Kacynski, Kenneth J.; Pavli, Albert J.; Smith, Tamara A.

1987-01-01

A 1030:1 carbon steel, heat-sink nozzle was tested. The test conditions included a nominal chamber pressure of 2413 kN/sq m and a mixture ratio range of 2.78 to 5.49. The propellants were gaseous oxygen and gaseous hydrogen. Outer wall temperature measurements were used to calculate the inner wall temperature and the heat flux and heat rate to the nozzle at specified axial locations. The experimental heat fluxes were compared to those predicted by the Two-Dimensional Kinetics (TDK) computer model analysis program. When laminar boundary layer flow was assumed in the analysis, the predicted values were within 15 percent of the experimental values for the area ratios of 20 to 975. However, when turbulent boundary layer conditions were assumed, the predicted values were approximately 120 percent higher than the experimental values. A study was performed to determine if the conditions within the nozzle could sustain a laminar boundary layer. Using the flow properties predicted by TDK, the momentum-thickness Reynolds number was calculated, and the point of transition to turbulent flow was predicted. The predicted transition point was within 0.5 inches of the nozzle throat. Calculations of the acceleration parameter were then made to determine if the flow conditions could produce relaminarization of the boundary layer. It was determined that if the boundary layer flow was inclined to transition to turbulent, the acceleration conditions within the nozzle would tend to suppress turbulence and keep the flow laminar-like.

Experimental evaluation of heat transfer on a 1030:1 area ratio rocket nozzle

NASA Technical Reports Server (NTRS)

Kacynski, Kenneth J.; Pavli, Albert J.; Smith, Tamara A.

1987-01-01

A 1030:1 carbon steel, heat-sink nozzle was tested. The test conditions included a nominal chamber pressure of 2413 kN/sq m and a mixture ratio range of 2.78 to 5.49. The propellants were gaseous oxygen and gaseous hydrogen. Outer wall temperature measurements were used to calculate the inner wall temperature and the heat flux and heat rate to the nozzle at specified axial locations. The experimental heat fluxes were compared to those predicted by the Two-Dimensional Kinetics (TDK) computer model analysis program. When laminar boundary layer flow was assumed in the analysis, the predicted values were within 15% of the experimental values for the area ratios of 20 to 975. However, when turbulent boundary layer conditions were assumed, the predicted values were approximately 120% higher than the experimental values. A study was performed to determine if the conditions within the nozzle could sustain a laminar boundary layer. Using the flow properties predicted by TDK, the momentum-thickness Reynolds number was calculated, and the point of transition to turbulent flow was predicted. The predicted transition point was within 0.5 inches of the nozzle throat. Calculations of the acceleration parameter were then made to determine if the flow conditions could produce relaminarization of the boundary layer. It was determined that if the boundary layer flow was inclined to transition to turbulent, the acceleration conditions within the nozzle would tend to suppress turbulence and keep the flow laminar-like.

Attributing Predictable Signals at Subseasonal Timescales

NASA Astrophysics Data System (ADS)

Shelly, A.; Norton, W.; Rowlands, D.; Beech-Brandt, J.

2016-12-01

Subseasonal forecasts offer significant economic value in the management of energy infrastructure and through the associated financial markets. Models are now accurate enough to provide, for some occasions, good forecasts in the subseasonal range. However, it is often not clear what the drivers of these subseasonal signals are and if the forecasts could be more accurate with better representation of physical processes. Also what are the limits of predictability in the subseasonal range? To address these questions, we have run the ECMWF monthly forecast system over the 2015/16 winter with a set of 6 week ensemble integrations initialised every week over the period. In these experiments, we have relaxed the band 15N to 15S to reanalysis fields. Hence, we have a set of forecasts where the tropics is constrained to actual events and we can analyse the changes in predictability in middle latitudes - in particular in regions of high energy consumption like North America and Europe. Not surprisingly, the forecast of some periods are significantly improved while others show no improvement. We discuss events/patterns that have extended range predictability and also the tropical forecast errors which prevent the potential predictability in middle latitudes from being realised.

From points to forecasts: Predicting invasive species habitat suitability in the near term

USGS Publications Warehouse

Holcombe, Tracy R.; Stohlgren, Thomas J.; Jarnevich, Catherine S.

2010-01-01

We used near-term climate scenarios for the continental United States, to model 12 invasive plants species. We created three potential habitat suitability models for each species using maximum entropy modeling: (1) current; (2) 2020; and (3) 2035. Area under the curve values for the models ranged from 0.92 to 0.70, with 10 of the 12 being above 0.83 suggesting strong and predictable species-environment matching. Change in area between the current potential habitat and 2035 ranged from a potential habitat loss of about 217,000 km2, to a potential habitat gain of about 133,000 km2.

Narcotic Independence After Pancreatic Duct Stenting Predicts Narcotic Independence After Lateral Pancreaticojejunostomy for Chronic Pancreatitis.

PubMed

Kwon, Richard S; Young, Benjamin E; Marsteller, William F; Lawrence, Christopher; Wu, Bechien U; Lee, Linda S; Mullady, Daniel; Klibansky, David A; Gardner, Timothy B; Simeone, Diane M

2016-09-01

This study aimed to determine if the improved pain response to endoscopic retrograde cholangiopancreatogrphy (ERCP) and pancreatic stent placement (EPS) predicts pain response in patients with chronic pancreatitis after modified lateral pancreaticojejunostomy (LPJ). A multi-institutional, retrospective review of patients who underwent successful EPS before LPJ between 2001 and 2010 was performed. The primary outcome was narcotic independence (NI) within 2 months after ERCP or LPJ. A total of 31 narcotic-dependent patients with chronic pancreatitis underwent successful EPS before LPJ. Ten (32%) achieved post-LPJ NI (median follow-up, 8.5 months; interquartile range [IQR], 2-38 months). Eight (80%) of 10 patients with NI post-ERCP achieved NI post-LPJ. Two (10%) without NI post-ERCP achieved NI post-LPJ. Narcotic independence post-EPS was associated strongly with NI post-LPJ with an odds ratio of 38 (P = 0.0025) and predicted post-LPJ NI with a sensitivity, specificity, positive predictive value, and negative predictive value of 80%, 90.5%, 80%, and 90.5%, respectively. Narcotic independence after EPS is associated with NI after LPJ. Failure to achieve NI post-ERCP predicts failure to achieve NI post-LPJ. These results support the need for larger studies to confirm the predictive value of pancreatic duct stenting for better selection of chronic pancreatitis patients who will benefit from LPJ.

Prediction of acute mammalian toxicity using QSAR methods: a case study of sulfur mustard and its breakdown products.

PubMed

Ruiz, Patricia; Begluitti, Gino; Tincher, Terry; Wheeler, John; Mumtaz, Moiz

2012-07-27

Predicting toxicity quantitatively, using Quantitative Structure Activity Relationships (QSAR), has matured over recent years to the point that the predictions can be used to help identify missing comparison values in a substance's database. In this manuscript we investigate using the lethal dose that kills fifty percent of a test population (LD₅₀) for determining relative toxicity of a number of substances. In general, the smaller the LD₅₀ value, the more toxic the chemical, and the larger the LD₅₀ value, the lower the toxicity. When systemic toxicity and other specific toxicity data are unavailable for the chemical(s) of interest, during emergency responses, LD₅₀ values may be employed to determine the relative toxicity of a series of chemicals. In the present study, a group of chemical warfare agents and their breakdown products have been evaluated using four available rat oral QSAR LD₅₀ models. The QSAR analysis shows that the breakdown products of Sulfur Mustard (HD) are predicted to be less toxic than the parent compound as well as other known breakdown products that have known toxicities. The QSAR estimated break down products LD₅₀ values ranged from 299 mg/kg to 5,764 mg/kg. This evaluation allows for the ranking and toxicity estimation of compounds for which little toxicity information existed; thus leading to better risk decision making in the field.

Assessing explicit error reporting in the narrative electronic medical record using keyword searching.

PubMed

Cao, Hui; Stetson, Peter; Hripcsak, George

2003-01-01

Many types of medical errors occur in and outside of hospitals, some of which have very serious consequences and increase cost. Identifying errors is a critical step for managing and preventing them. In this study, we assessed the explicit reporting of medical errors in the electronic record. We used five search terms "mistake," "error," "incorrect," "inadvertent," and "iatrogenic" to survey several sets of narrative reports including discharge summaries, sign-out notes, and outpatient notes from 1991 to 2000. We manually reviewed all the positive cases and identified them based on the reporting of physicians. We identified 222 explicitly reported medical errors. The positive predictive value varied with different keywords. In general, the positive predictive value for each keyword was low, ranging from 3.4 to 24.4%. Therapeutic-related errors were the most common reported errors and these reported therapeutic-related errors were mainly medication errors. Keyword searches combined with manual review indicated some medical errors that were reported in medical records. It had a low sensitivity and a moderate positive predictive value, which varied by search term. Physicians were most likely to record errors in the Hospital Course and History of Present Illness sections of discharge summaries. The reported errors in medical records covered a broad range and were related to several types of care providers as well as non-health care professionals.

Forecasting Kp from solar wind data: input parameter study using 3-hour averages and 3-hour range values

NASA Astrophysics Data System (ADS)

Wintoft, Peter; Wik, Magnus; Matzka, Jürgen; Shprits, Yuri

2017-11-01

We have developed neural network models that predict Kp from upstream solar wind data. We study the importance of various input parameters, starting with the magnetic component Bz, particle density n, and velocity V and then adding total field B and the By component. As we also notice a seasonal and UT variation in average Kp we include functions of day-of-year and UT. Finally, as Kp is a global representation of the maximum range of geomagnetic variation over 3-hour UT intervals we conclude that sudden changes in the solar wind can have a big effect on Kp, even though it is a 3-hour value. Therefore, 3-hour solar wind averages will not always appropriately represent the solar wind condition, and we introduce 3-hour maxima and minima values to some degree address this problem. We find that introducing total field B and 3-hour maxima and minima, derived from 1-minute solar wind data, have a great influence on the performance. Due to the low number of samples for high Kp values there can be considerable variation in predicted Kp for different networks with similar validation errors. We address this issue by using an ensemble of networks from which we use the median predicted Kp. The models (ensemble of networks) provide prediction lead times in the range 20-90 min given by the time it takes a solar wind structure to travel from L1 to Earth. Two models are implemented that can be run with real time data: (1) IRF-Kp-2017-h3 uses the 3-hour averages of the solar wind data and (2) IRF-Kp-2017 uses in addition to the averages, also the minima and maxima values. The IRF-Kp-2017 model has RMS error of 0.55 and linear correlation of 0.92 based on an independent test set with final Kp covering 2 years using ACE Level 2 data. The IRF-Kp-2017-h3 model has RMSE = 0.63 and correlation = 0.89. We also explore the errors when tested on another two-year period with real-time ACE data which gives RMSE = 0.59 for IRF-Kp-2017 and RMSE = 0.73 for IRF-Kp-2017-h3. The errors as function of Kp and for different years are also studied.

Prediction of the Thermal Conductivity of Refrigerants by Computational Methods and Artificial Neural Network.

PubMed

Ghaderi, Forouzan; Ghaderi, Amir H; Ghaderi, Noushin; Najafi, Bijan

2017-01-01

Background: The thermal conductivity of fluids can be calculated by several computational methods. However, these methods are reliable only at the confined levels of density, and there is no specific computational method for calculating thermal conductivity in the wide ranges of density. Methods: In this paper, two methods, an Artificial Neural Network (ANN) approach and a computational method established upon the Rainwater-Friend theory, were used to predict the value of thermal conductivity in all ranges of density. The thermal conductivity of six refrigerants, R12, R14, R32, R115, R143, and R152 was predicted by these methods and the effectiveness of models was specified and compared. Results: The results show that the computational method is a usable method for predicting thermal conductivity at low levels of density. However, the efficiency of this model is considerably reduced in the mid-range of density. It means that this model cannot be used at density levels which are higher than 6. On the other hand, the ANN approach is a reliable method for thermal conductivity prediction in all ranges of density. The best accuracy of ANN is achieved when the number of units is increased in the hidden layer. Conclusion: The results of the computational method indicate that the regular dependence between thermal conductivity and density at higher densities is eliminated. It can develop a nonlinear problem. Therefore, analytical approaches are not able to predict thermal conductivity in wide ranges of density. Instead, a nonlinear approach such as, ANN is a valuable method for this purpose.

Prediction of the Thermal Conductivity of Refrigerants by Computational Methods and Artificial Neural Network

PubMed Central

Ghaderi, Forouzan; Ghaderi, Amir H.; Ghaderi, Noushin; Najafi, Bijan

2017-01-01

Background: The thermal conductivity of fluids can be calculated by several computational methods. However, these methods are reliable only at the confined levels of density, and there is no specific computational method for calculating thermal conductivity in the wide ranges of density. Methods: In this paper, two methods, an Artificial Neural Network (ANN) approach and a computational method established upon the Rainwater-Friend theory, were used to predict the value of thermal conductivity in all ranges of density. The thermal conductivity of six refrigerants, R12, R14, R32, R115, R143, and R152 was predicted by these methods and the effectiveness of models was specified and compared. Results: The results show that the computational method is a usable method for predicting thermal conductivity at low levels of density. However, the efficiency of this model is considerably reduced in the mid-range of density. It means that this model cannot be used at density levels which are higher than 6. On the other hand, the ANN approach is a reliable method for thermal conductivity prediction in all ranges of density. The best accuracy of ANN is achieved when the number of units is increased in the hidden layer. Conclusion: The results of the computational method indicate that the regular dependence between thermal conductivity and density at higher densities is eliminated. It can develop a nonlinear problem. Therefore, analytical approaches are not able to predict thermal conductivity in wide ranges of density. Instead, a nonlinear approach such as, ANN is a valuable method for this purpose. PMID:29188217

Developing and validating a predictive model for stroke progression.

PubMed

Craig, L E; Wu, O; Gilmour, H; Barber, M; Langhorne, P

2011-01-01

Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Two patient cohorts were used for this study - the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p < 0.1) on univariate analysis were included in the multivariate model. Logistic regression was the technique employed using backward stepwise regression to drop the least significant variables (p > 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72-0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50-0.92)]. The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and calibration of the predictive model appear sufficiently high to provide accurate predictions. This study also offers some discussion around the validation of predictive models for wider use in clinical practice.

Diagnostic value of 18F-FDG-PET/CT for the follow-up and restaging of soft tissue sarcomas in adults.

PubMed

Kassem, T W; Abdelaziz, O; Emad-Eldin, S

2017-10-01

The purpose of this study was to evaluate the clinical utility of 2-[ 18 F] fluoro-2-deoxy-D-glucose ( 18 FDG) positron emission tomography (PET)/computed tomography (CT) ( 18 F-FDG-PET/CT) in the follow-up of adult patients with soft tissue sarcomas. We prospectively evaluated 37 consecutive patients with known soft tissue sarcoma with 18 F-FDG-PET/CT examination for suspected recurrence of disease. They were 21 men and 16 women with a mean age of 49.6±10.6 (SD) years (range, 34-75years). The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of 18 F-FDG-PET/CT examination were calculated on a per patient basis. 18 F-FDG-PET/CT showed an overall diagnostic accuracy of 91.8%, sensitivity of 90% and a specificity of 100%. The positive predictive value and negative predictive value were 100 and 70%, respectively. The 18 F-FDG-PET/CT interpretations were correct in 34/37 patients (91.8%). Incorrect interpretations occurred in three patients (8.1%). Reasons for false negative findings were low 18 F-FDG uptake of local recurrence in one patient and low 18 F-FDG uptake of subcentimetric inguinal lymph node metastases. 18 F-FDG-PET/CT has a high diagnostic value in the follow-up of patients with soft tissue sarcoma. Copyright © 2017 Editions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

A unifying Bayesian account of contextual effects in value-based choice

PubMed Central

Friston, Karl J.; Dolan, Raymond J.

2017-01-01

Empirical evidence suggests the incentive value of an option is affected by other options available during choice and by options presented in the past. These contextual effects are hard to reconcile with classical theories and have inspired accounts where contextual influences play a crucial role. However, each account only addresses one or the other of the empirical findings and a unifying perspective has been elusive. Here, we offer a unifying theory of context effects on incentive value attribution and choice based on normative Bayesian principles. This formulation assumes that incentive value corresponds to a precision-weighted prediction error, where predictions are based upon expectations about reward. We show that this scheme explains a wide range of contextual effects, such as those elicited by other options available during choice (or within-choice context effects). These include both conditions in which choice requires an integration of multiple attributes and conditions where a multi-attribute integration is not necessary. Moreover, the same scheme explains context effects elicited by options presented in the past or between-choice context effects. Our formulation encompasses a wide range of contextual influences (comprising both within- and between-choice effects) by calling on Bayesian principles, without invoking ad-hoc assumptions. This helps clarify the contextual nature of incentive value and choice behaviour and may offer insights into psychopathologies characterized by dysfunctional decision-making, such as addiction and pathological gambling. PMID:28981514

Predictive model for the growth kinetics of Staphylococcus aureus in raw pork developed using Integrated Pathogen Modeling Program (IPMP) 2013.

PubMed

Lee, Yong Ju; Jung, Byeong Su; Kim, Kee-Tae; Paik, Hyun-Dong

2015-09-01

A predictive model was performed to describe the growth of Staphylococcus aureus in raw pork by using Integrated Pathogen Modeling Program 2013 and a polynomial model as a secondary predictive model. S. aureus requires approximately 180 h to reach 5-6 log CFU/g at 10 °C. At 15 °C and 25 °C, approximately 48 and 20 h, respectively, are required to cause food poisoning. Predicted data using the Gompertz model was the most accurate in this study. For lag time (LT) model, bias factor (Bf) and accuracy factor (Af) values were both 1.014, showing that the predictions were within a reliable range. For specific growth rate (SGR) model, Bf and Af were 1.188 and 1.190, respectively. Additionally, both Bf and Af values of the LT and SGR models were close to 1, indicating that IPMP Gompertz model is more adequate for predicting the growth of S. aureus on raw pork than other models. Copyright © 2015 Elsevier Ltd. All rights reserved.

Kinetic modeling of α-hydrogen abstractions from unsaturated and saturated oxygenate compounds by carbon-centered radicals.

PubMed

Paraskevas, Paschalis D; Sabbe, Maarten K; Reyniers, Marie-Françoise; Papayannakos, Nikos; Marin, Guy B

2014-06-23

Hydrogen abstractions are important elementary reactions in a variety of reacting media at high temperatures in which oxygenates and hydrocarbon radicals are present. Accurate kinetic data are obtained from CBS-QB3 ab initio (AI) calculations by using conventional transition-state theory within the high-pressure limit, including corrections for hindered rotation and tunneling. From the obtained results, a group-additive (GA) model is developed that allows the Arrhenius parameters and rate coefficients for abstraction of the α-hydrogen from a wide range of oxygenate compounds to be predicted at temperatures ranging from 300 to 1500 K. From a training set of 60 hydrogen abstractions from oxygenates by carbon-centered radicals, 15 GA values (ΔGAV°s) are obtained for both the forward and reverse reactions. Among them, four ΔGAV°s refer to primary contributions, and the remaining 11 ΔGAV°s refer to secondary ones. The accuracy of the model is further improved by introducing seven corrections for cross-resonance stabilization of the transition state from an additional set of 43 reactions. The determined ΔGAV°s are validated upon a test set of AI data for 17 reactions. The mean absolute deviation of the pre-exponential factors (log A) and activation energies (E(a)) for the forward reaction at 300 K are 0.238 log(m(3)  mol(-1)  s(-1)) and 1.5 kJ mol(-1), respectively, whereas the mean factor of deviation <ρ> between the GA-predicted and the AI-calculated rate coefficients is 1.6. In comparison with a compilation of 33 experimental rate coefficients, the <ρ> between the GA-predicted values and these experimental values is only 2.2. Hence, the constructed GA model can be reliably used in the prediction of the kinetics of α-hydrogen-abstraction reactions between a broad range of oxygenates and oxygenate radicals. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Liver Stiffness Reflecting Right-Sided Filling Pressure Can Predict Adverse Outcomes in Patients With Heart Failure.

PubMed

Taniguchi, Tatsunori; Ohtani, Tomohito; Kioka, Hidetaka; Tsukamoto, Yasumasa; Onishi, Toshinari; Nakamoto, Kei; Katsimichas, Themistoklis; Sengoku, Kaoruko; Chimura, Misato; Hashimoto, Haruko; Yamaguchi, Osamu; Sawa, Yoshiki; Sakata, Yasushi

2018-01-12

This study sought to investigate whether elevated liver stiffness (LS) values at discharge reflect residual liver congestion and are associated with worse outcomes in patients with heart failure (HF). Transient elastography is a newly developed, noninvasive method for assessing LS, which can be highly reflective of right-sided filling pressure associated with passive liver congestion in patients with HF. LS values were determined for 171 hospitalized patients with HF before discharge using a Fibroscan device. The median LS value was 5.6 kPa (interquartile range: 4.4 to 8.1; range 2.4 to 39.7) and that of right-sided filling pressure, which was estimated based on LS, was 5.7 mm Hg (interquartile range: 4.1 to 8.2 mm Hg; range 0.1 to 18.9 mm Hg). The patients in the highest LS tertile (>6.9 kPa, corresponding to an estimated right-sided filling pressure of >7.1 mm Hg) had advanced New York Heart Association functional class, high prevalence of jugular venous distention and moderate/severe tricuspid regurgitation, large inferior vena cava (IVC) diameter, low hemoglobin and hematocrit levels, high serum direct bilirubin level, and a similar left ventricular ejection fraction compared with the lower tertiles. During follow-up periods (median: 203 days), 8 (5%) deaths and 33 (19%) hospitalizations for HF were observed. The patients in the highest LS group had a significantly higher mortality rate and HF rehospitalization (hazard ratio: 3.57; 95% confidence interval: 1.93 to 6.83; p < 0.001) compared with the other tertiles. Although LS correlated with IVC diameter and serum direct bilirubin and brain natriuretic peptide levels, LS values were predictive of worse outcomes, even after adjustment for these indices. These data suggest that LS is a useful index for assessing systemic volume status and predicting the severity of HF, and that the presence of liver congestion at discharge is associated with worse outcomes in patients with HF. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Otoliths - Accelerometer and seismometer; Implications in Vestibular Evoked Myogenic Potential (VEMP).

PubMed

Grant, Wally; Curthoys, Ian

2017-09-01

Vestibular otolithic organs are recognized as transducers of head acceleration and they function as such up to their corner frequency or undamped natural frequency. It is well recognized that these organs respond to frequencies above their corner frequency up to the 2-3 kHz range (Curthoys et al., 2016). A mechanics model for the transduction of these organs is developed that predicts the response below the undamped natural frequency as an accelerometer and above that frequency as a seismometer. The model is converted to a transfer function using hair cell bundle deflection. Measured threshold acceleration stimuli are used along with threshold deflections for threshold transfer function values. These are compared to model predicted values, both below and above their undamped natural frequency. Threshold deflection values are adjusted to match the model transfer function. The resulting threshold deflection values were well within in measure threshold bundle deflection ranges. Vestibular Evoked Myogenic Potentials (VEMPs) today routinely uses stimulus frequencies of 500 and 1000 Hz, and otoliths have been established incontrovertibly by clinical and neural evidence as the stimulus source. The mechanism for stimulus at these frequencies above the undamped natural frequency of otoliths is presented where otoliths are utilizing a seismometer mode of response for VEMP transduction. Copyright © 2017 Elsevier B.V. All rights reserved.

Reliability of the mangled extremity severity score in combat-related upper and lower extremity injuries.

PubMed

Ege, Tolga; Unlu, Aytekin; Tas, Huseyin; Bek, Dogan; Turkan, Selim; Cetinkaya, Aytac

2015-01-01

Decision of limb salvage or amputation is generally aided with several trauma scoring systems such as the mangled extremity severity score (MESS). However, the reliability of the injury scores in the settling of open fractures due to explosives and missiles is challenging. Mortality and morbidity of the extremity trauma due to firearms are generally associated with time delay in revascularization, injury mechanism, anatomy of the injured site, associated injuries, age and the environmental circumstance. The purpose of the retrospective study was to evaluate the extent of extremity injuries due to ballistic missiles and to detect the reliability of mangled extremity severity score (MESS) in both upper and lower extremities. Between 2004 and 2014, 139 Gustillo Anderson Type III open fractures of both the upper and lower extremities were enrolled in the study. Data for patient age, fire arm type, transporting time from the field to the hospital (and the method), injury severity scores, MESS scores, fracture types, amputation levels, bone fixation methods and postoperative infections and complications retrieved from the two level-2 trauma center's data base. Sensitivity, specificity, positive and negative predictive values of the MESS were calculated to detect the ability in deciding amputation in the mangled limb. Amputation was performed in 39 extremities and limb salvage attempted in 100 extremities. The mean followup time was 14.6 months (range 6-32 months). In the amputated group, the mean MESS scores for upper and lower extremity were 8.8 (range 6-11) and 9.24 (range 6-11), respectively. In the limb salvage group, the mean MESS scores for upper and lower extremities were 5.29 (range 4-7) and 5.19 (range 3-8), respectively. Sensitivity of MESS in upper and lower extremities were calculated as 80% and 79.4% and positive predictive values detected as 55.55% and 83.3%, respectively. Specificity of MESS score for upper and lower extremities was 84% and 86.6%; negative predictive values were calculated as 95.45% and 90.2%, respectively. MESS is not predictive in combat related extremity injuries especially if between a score of 6-8. Limb ischemia and presence or absence of shock can be used in initial decision-making for amputation.

Reliability of the mangled extremity severity score in combat-related upper and lower extremity injuries

PubMed Central

Ege, Tolga; Unlu, Aytekin; Tas, Huseyin; Bek, Dogan; Turkan, Selim; Cetinkaya, Aytac

2015-01-01

Background: Decision of limb salvage or amputation is generally aided with several trauma scoring systems such as the mangled extremity severity score (MESS). However, the reliability of the injury scores in the settling of open fractures due to explosives and missiles is challenging. Mortality and morbidity of the extremity trauma due to firearms are generally associated with time delay in revascularization, injury mechanism, anatomy of the injured site, associated injuries, age and the environmental circumstance. The purpose of the retrospective study was to evaluate the extent of extremity injuries due to ballistic missiles and to detect the reliability of mangled extremity severity score (MESS) in both upper and lower extremities. Materials and Methods: Between 2004 and 2014, 139 Gustillo Anderson Type III open fractures of both the upper and lower extremities were enrolled in the study. Data for patient age, fire arm type, transporting time from the field to the hospital (and the method), injury severity scores, MESS scores, fracture types, amputation levels, bone fixation methods and postoperative infections and complications retrieved from the two level-2 trauma center's data base. Sensitivity, specificity, positive and negative predictive values of the MESS were calculated to detect the ability in deciding amputation in the mangled limb. Results: Amputation was performed in 39 extremities and limb salvage attempted in 100 extremities. The mean followup time was 14.6 months (range 6–32 months). In the amputated group, the mean MESS scores for upper and lower extremity were 8.8 (range 6–11) and 9.24 (range 6–11), respectively. In the limb salvage group, the mean MESS scores for upper and lower extremities were 5.29 (range 4–7) and 5.19 (range 3–8), respectively. Sensitivity of MESS in upper and lower extremities were calculated as 80% and 79.4% and positive predictive values detected as 55.55% and 83.3%, respectively. Specificity of MESS score for upper and lower extremities was 84% and 86.6%; negative predictive values were calculated as 95.45% and 90.2%, respectively. Conclusion: MESS is not predictive in combat related extremity injuries especially if between a score of 6–8. Limb ischemia and presence or absence of shock can be used in initial decision-making for amputation. PMID:26806974

Genomic prediction using different estimation methodology, blending and cross-validation techniques for growth traits and visual scores in Hereford and Braford cattle.

PubMed

Campos, G S; Reimann, F A; Cardoso, L L; Ferreira, C E R; Junqueira, V S; Schmidt, P I; Braccini Neto, J; Yokoo, M J I; Sollero, B P; Boligon, A A; Cardoso, F F

2018-05-07

The objective of the present study was to evaluate the accuracy and bias of direct and blended genomic predictions using different methods and cross-validation techniques for growth traits (weight and weight gains) and visual scores (conformation, precocity, muscling and size) obtained at weaning and at yearling in Hereford and Braford breeds. Phenotypic data contained 126,290 animals belonging to the Delta G Connection genetic improvement program, and a set of 3,545 animals genotyped with the 50K chip and 131 sires with the 777K. After quality control, 41,045 markers remained for all animals. An animal model was used to estimate (co)variances components and to predict breeding values, which were later used to calculate the deregressed estimated breeding values (DEBV). Animals with genotype and phenotype for the traits studied were divided into four or five groups by random and k-means clustering cross-validation strategies. The values of accuracy of the direct genomic values (DGV) were moderate to high magnitude for at weaning and at yearling traits, ranging from 0.19 to 0.45 for the k-means and 0.23 to 0.78 for random clustering among all traits. The greatest gain in relation to the pedigree BLUP (PBLUP) was 9.5% with the BayesB method with both the k-means and the random clustering. Blended genomic value accuracies ranged from 0.19 to 0.56 for k-means and from 0.21 to 0.82 for random clustering. The analyzes using the historical pedigree and phenotypes contributed additional information to calculate the GEBV and in general, the largest gains were for the single-step (ssGBLUP) method in bivariate analyses with a mean increase of 43.00% among all traits measured at weaning and of 46.27% for those evaluated at yearling. The accuracy values for the marker effects estimation methods were lower for k-means clustering, indicating that the training set relationship to the selection candidates is a major factor affecting accuracy of genomic predictions. The gains in accuracy obtained with genomic blending methods, mainly ssGBLUP in bivariate analyses, indicate that genomic predictions should be used as a tool to improve genetic gains in relation to the traditional PBLUP selection.

Refinement of detecting atrial fibrillation in stroke patients: results from the TRACK-AF Study.

PubMed

Reinke, F; Bettin, M; Ross, L S; Kochhäuser, S; Kleffner, I; Ritter, M; Minnerup, J; Dechering, D; Eckardt, L; Dittrich, R

2018-04-01

Detection of occult atrial fibrillation (AF) is crucial for optimal secondary prevention in stroke patients. The AF detection rate was determined by implantable cardiac monitor (ICM) and compared to the prediction rate of the probability of incident AF by software based analysis of a continuously monitored electrocardiogram at follow-up (stroke risk analysis, SRA); an optimized AF detection algorithm is proposed by combining both tools. In a monocentric prospective study 105 out of 389 patients with cryptogenic stroke despite extensive diagnostic workup were investigated with two additional cardiac monitoring tools: (a) 20 months' monitoring by ICM and (b) SRA during hospitalization at the stroke unit. The detection rate of occult AF was 18% by ICM (n = 19) (range 6-575 days) and 62% (n = 65) had an increased risk for AF predicted by SRA. When comparing the predictive accuracy of SRA to ICM, the sensitivity was 95%, specificity 35%, positive predictive value 27% and negative predictive value 96%. In 18 patients with AF detected by ICM, SRA also showed a medium risk for AF. Only one patient with a very low risk predicted by SRA developed AF revealed by ICM after 417 days. A combination of SRA and ICM is a promising strategy to detect occult AF. SRA is reliable in predicting incident AF with a high negative predictive value. Thus, SRA may serve as a cost-effective pre-selection tool identifying patients at risk for AF who may benefit from further cardiac monitoring by ICM. © 2017 EAN.

Theoretical predictions for α -decay chains of 118 290 -298Og isotopes using a finite-range nucleon-nucleon interaction

NASA Astrophysics Data System (ADS)

Ismail, M.; Adel, A.

2018-04-01

The α -decay half-lives of the recently synthesized superheavy nuclei (SHN) are investigated by employing the density dependent cluster model. A realistic nucleon-nucleon (NN ) interaction with a finite-range exchange part is used to calculate the microscopic α -nucleus potential in the well-established double-folding model. The calculated potential is then implemented to find both the assault frequency and the penetration probability of the α particle by means of the Wentzel-Kramers-Brillouin (WKB) approximation in combination with the Bohr-Sommerfeld quantization condition. The calculated values of α -decay half-lives of the recently synthesized Og isotopes and its decay products are in good agreement with the experimental data. Moreover, the calculated values of α -decay half-lives have been compared with those values evaluated using other theoretical models, and it was found that our theoretical values match well with their counterparts. The competition between α decay and spontaneous fission is investigated and predictions for possible decay modes for the unknown nuclei 118 290 -298Og are presented. We studied the behavior of the α -decay half-lives of Og isotopes and their decay products as a function of the mass number of the parent nuclei. We found that the behavior of the curves is governed by proton and neutron magic numbers found from previous studies. The proton numbers Z =114 , 116, 108, 106 and the neutron numbers N =172 , 164, 162, 158 show some magic character. We hope that the theoretical prediction of α -decay chains provides a new perspective to experimentalists.

Aberrant GSTP1 promoter methylation predicts short-term prognosis in acute-on-chronic hepatitis B liver failure.

PubMed

Gao, S; Sun, F-K; Fan, Y-C; Shi, C-H; Zhang, Z-H; Wang, L-Y; Wang, K

2015-08-01

Glutathione-S-transferase P1 (GSTP1) methylation has been demonstrated to be associated with oxidative stress induced liver damage in acute-on-chronic hepatitis B liver failure (ACHBLF). To evaluate the methylation level of GSTP1 promoter in acute-on-chronic hepatitis B liver failure and determine its predictive value for prognosis. One hundred and five patients with acute-on-chronic hepatitis B liver failure, 86 with chronic hepatitis B (CHB) and 30 healthy controls (HC) were retrospectively enrolled. GSTP1 methylation level in peripheral mononuclear cells (PBMC) was detected by MethyLight. Clinical and laboratory parameters were obtained. GSTP1 methylation levels were significantly higher in patients with acute-on-chronic hepatitis B liver failure (median 16.84%, interquartile range 1.83-59.05%) than those with CHB (median 1.25%, interquartile range 0.48-2.47%; P < 0.01) and HC (median 0.80%, interquartile range 0.67-1.27%; P < 0.01). In acute-on-chronic hepatitis B liver failure group, nonsurvivors showed significantly higher GSTP1 methylation levels (P < 0.05) than survivors. GSTP1 methylation level was significantly correlated with total bilirubin (r = 0.29, P < 0.01), prothrombin time activity (r = -0.24, P = 0.01) and model for end-stage liver disease (MELD) score (r = 0.26, P = 0.01). When used to predict 1- or 2-month mortality of acute-on-chronic hepatitis B liver failure, GSTP1 methylation showed significantly better predictive value than MELD score [area under the receiver operating characteristic curve (AUC) 0.89 vs. 0.72, P < 0.01; AUC 0.83 vs. 0.70, P < 0.05 respectively]. Meanwhile, patients with GSTP1 methylation levels above the cut-off points showed significantly poorer survival than those below (P < 0.05). Aberrant GSTP1 promoter methylation exists in acute-on-chronic hepatitis B liver failure and shows high predictive value for short-term mortality. It might serve as a potential prognostic marker for acute-on-chronic hepatitis B liver failure. © 2015 John Wiley & Sons Ltd.

Prediction of Airfoil Characteristics With Higher Order Turbulence Models

NASA Technical Reports Server (NTRS)

Gatski, Thomas B.

1996-01-01

This study focuses on the prediction of airfoil characteristics, including lift and drag over a range of Reynolds numbers. Two different turbulence models, which represent two different types of models, are tested. The first is a standard isotropic eddy-viscosity two-equation model, and the second is an explicit algebraic stress model (EASM). The turbulent flow field over a general-aviation airfoil (GA(W)-2) at three Reynolds numbers is studied. At each Reynolds number, predicted lift and drag values at different angles of attack are compared with experimental results, and predicted variations of stall locations with Reynolds number are compared with experimental data. Finally, the size of the separation zone predicted by each model is analyzed, and correlated with the behavior of the lift coefficient near stall. In summary, the EASM model is able to predict the lift and drag coefficients over a wider range of angles of attack than the two-equation model for the three Reynolds numbers studied. However, both models are unable to predict the correct lift and drag behavior near the stall angle, and for the lowest Reynolds number case, the two-equation model did not predict separation on the airfoil near stall.

Reference Values and Utility of Serum Total Immunoglobulin E for Predicting Atopy and Allergic Diseases in Korean Schoolchildren

PubMed Central

2017-01-01

The present study aimed to investigate the distribution of total serum immunoglobulin E (IgE) levels in Korean schoolchildren and to evaluate its utility in the prediction of atopy and allergic diseases. A nationwide, cross-sectional survey was conducted in first grade students from randomly selected elementary and middle schools. Total IgE levels were measured by ImmunoCAP. Skin prick tests were performed for 18 common inhalant allergens to determine the presence of atopy. Children aged 12–13 years and parents of children aged 6–7 years were asked to complete questionnaire assessing allergic diseases. The cut-off levels of total IgE were determined by analyzing receiver operating characteristic curves. The median total IgE level was 86.7 kU/L (range: 1.5–4,523.1) in 3,753 children aged 6–7 years and 94.7 kU/L (range: 1.5–3,000.0) in 3,930 children aged 12–13 years. Total IgE concentrations were higher in children with atopy or allergic diseases than in those without (all P < 0.001). At the cut-off value of 127.7 kU/L, sensitivity, specificity, and positive and negative predictive values (PPV and NPV) were 67.1%, 75.4%, 65.4%, and 76.7%, respectively, in elementary schoolchildren. At the cut-off value of 63.0 kU/L, sensitivity, specificity, PPV, and NPV were 81.9%, 66.6%, 75.0%, and 75.1%, respectively, in middle schoolchildren. PPV and NPV were ≥ 70% when cut-offs of 258.8 kU/L and 38.4 kU/L were used for the diagnosis of atopy in 6–7 year-olds and 12–13 year-olds, respectively. This nationwide population-based study provided the first normal reference ranges of total IgE in Korean schoolchildren. PMID:28378554

Use of risk assessment instruments to predict violence and antisocial behaviour in 73 samples involving 24 827 people: systematic review and meta-analysis

PubMed Central

Singh, Jay P; Doll, Helen; Grann, Martin

2012-01-01

Objective To investigate the predictive validity of tools commonly used to assess the risk of violence, sexual, and criminal behaviour. Design Systematic review and tabular meta-analysis of replication studies following PRISMA guidelines. Data sources PsycINFO, Embase, Medline, and United States Criminal Justice Reference Service Abstracts. Review methods We included replication studies from 1 January 1995 to 1 January 2011 if they provided contingency data for the offending outcome that the tools were designed to predict. We calculated the diagnostic odds ratio, sensitivity, specificity, area under the curve, positive predictive value, negative predictive value, the number needed to detain to prevent one offence, as well as a novel performance indicator—the number safely discharged. We investigated potential sources of heterogeneity using metaregression and subgroup analyses. Results Risk assessments were conducted on 73 samples comprising 24 847 participants from 13 countries, of whom 5879 (23.7%) offended over an average of 49.6 months. When used to predict violent offending, risk assessment tools produced low to moderate positive predictive values (median 41%, interquartile range 27-60%) and higher negative predictive values (91%, 81-95%), and a corresponding median number needed to detain of 2 (2-4) and number safely discharged of 10 (4-18). Instruments designed to predict violent offending performed better than those aimed at predicting sexual or general crime. Conclusions Although risk assessment tools are widely used in clinical and criminal justice settings, their predictive accuracy varies depending on how they are used. They seem to identify low risk individuals with high levels of accuracy, but their use as sole determinants of detention, sentencing, and release is not supported by the current evidence. Further research is needed to examine their contribution to treatment and management. PMID:22833604

Laser Signature Prediction Using The VALUE Computer Program

NASA Astrophysics Data System (ADS)

Akerman, Alexander; Hoffman, George A.; Patton, Ronald

1989-09-01

A variety of enhancements are being made to the 1976-vintage LASERX computer code. These include: - Surface characterization with BDRF tabular data - Specular reflection from transparent surfaces - Generation of glint direction maps - Generation of relative range imagery - Interface to the LOWTRAN atmospheric transmission code - Interface to the LEOPS laser sensor code - User friendly menu prompting for easy setup Versions of VALUE have been written for both VAX/VMS and PC/DOS computer environments. Outputs have also been revised to be user friendly and include tables, plots, and images for (1) intensity, (2) cross section,(3) reflectance, (4) relative range, (5) region type, and (6) silhouette.

Molecular and biochemical characterization of natural and recombinant phosphoglycerate kinase B from Trypanosoma rangeli.

PubMed

Villafraz, O; Rondón-Mercado, R; Cáceres, A J; Concepción, J L; Quiñones, W

2018-04-01

T. rangeli epimastigotes contain only a single detectable phosphoglycerate kinase (PGK) enzyme in their cytosol. Analysis of this parasite's recently sequenced genome showed a gene predicted to code for a PGK with the same molecular mass as the natural enzyme, and with a cytosolic localization as well. In this work, we have partially purified the natural PGK from T. rangeli epimastigotes. Furthermore, we cloned the predicted PGK gene and expressed it as a recombinant active enzyme. Both purified enzymes were kinetically characterized and displayed similar substrate affinities, with Km ATP values of 0.13 mM and 0.5 mM, and Km 3PGA values of 0.28 mM and 0.71 mM, for the natural and recombinant enzyme, respectively. The optimal pH for activity of both enzymes was in the range of 8-10. Like other PGKs, TrPGK is monomeric with a molecular mass of approximately 44 kDa. The enzyme's kinetic characteristics are comparable with those of cytosolic PGK isoforms from related trypanosomatid species, indicating that, most likely, this enzyme is equivalent with the PGKB that is responsible for generating ATP in the cytosol of other trypanosomatids. This is the first report of a glycolytic enzyme characterization from T. rangeli. Copyright © 2018 Elsevier Inc. All rights reserved.

Ductal carcinoma of breast: nuclear grade as a predictor of S-phase fraction.

PubMed

Dabbs, D J

1993-06-01

Nuclear grade (NG) and S-phase fraction (SPF) are established independent prognostic variables for ductal breast carcinomas. Nuclear grade can be assigned by a pathologist in a simple fashion during histopathologic evaluation of the tumor, while SPF requires flow cytometric evaluation of tumor samples. This prospective study was undertaken to determine whether elevated SPF could be predicted from NG alone and how NG and SPF correlate with c-erbB-2 expression. Eighty-two breast carcinomas of ductal type were assigned an NG of low (grade 1 or grade 2) or high (grade 3). S-phase fraction was recorded initially from fresh-frozen tissue samples and was designated as either low SPF (below the value designated as the cutoff for elevated SPF) or high SPF (a value at or greater than the cutoff value). On fresh tissue the NG predicted the range of SPF (low or high) in 89% of cases. Four percent of the cases that did not correlate could definitely be attributed to sample error. The remaining 7% that did not correlate could have been due to sample error, specimen quality, or tumor heterogeneity, as demonstrated by reversal of SPF range as performed on paraffin blocks of tumor. Eighty-eight percent of the tumors positive for c-erbB-2 were NG 3 and 12% were NG 2. All c-erbB-2 tumors were aneuploid. This study demonstrates the importance of carefully assigning NGs on tissue and indicates the importance of reviewing flow cytometric data side by side with histopathologic parameters to detect discrepancies between these two modalities. Careful nuclear grading assignment can accurately predict the range of SPF.

Electro-oculography-based detection of sleep-wake in sleep apnea patients.

PubMed

Virkkala, Jussi; Toppila, Jussi; Maasilta, Paula; Bachour, Adel

2015-09-01

Recently, we have developed a simple method that uses two electro-oculography (EOG) electrodes for the automatic scoring of sleep-wake in normal subjects. In this study, we investigated the usefulness of this method on 284 consecutive patients referred for a suspicion of sleep apnea who underwent a polysomnography (PSG). We applied the AASM 2007 scoring rules. A simple automatic sleep-wake classification algorithm based on 18-45 Hz beta power was applied to the calculated bipolar EOG channel and was compared to standard polysomnography. Epoch by epoch agreement was evaluated. Eighteen patients were excluded due to poor EOG quality. One hundred fifty-eight males and 108 females were studied, their mean age was 48 (range 17-89) years, apnea-hypopnea index 13 (range 0-96) /h, BMI 29 (range 17-52) kg/m(2), and sleep efficiency 78 (range 0-98) %. The mean agreement in sleep-wake states between EOG and PSG was 85% and the Cohen's kappa was 0.56. Overall epoch-by-epoch agreement was 85%, and the Cohen's kappa was 0.57 with positive predictive value of 91% and negative predictive value of 65%. The EOG method can be applied to patients referred for suspicion of sleep apnea to indicate the sleep-wake state.

On the look-up tables for the critical heat flux in tubes (history and problems)

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

Kirillov, P.L.; Smogalev, I.P.

1995-09-01

The complication of critical heat flux (CHF) problem for boiling in channels is caused by the large number of variable factors and the variety of two-phase flows. The existence of several hundreds of correlations for the prediction of CHF demonstrates the unsatisfactory state of this problem. The phenomenological CHF models can provide only the qualitative predictions of CHF primarily in annular-dispersed flow. The CHF look-up tables covered the results of numerous experiments received more recognition in the last 15 years. These tables are based on the statistical averaging of CHF values for each range of pressure, mass flux and quality.more » The CHF values for regions, where no experimental data is available, are obtained by extrapolation. The correction of these tables to account for the diameter effect is a complicated problem. There are ranges of conditions where the simple correlations cannot produce the reliable results. Therefore, diameter effect on CHF needs additional study. The modification of look-up table data for CHF in tubes to predict CHF in rod bundles must include a method which to take into account the nonuniformity of quality in a rod bundle cross section.« less

Improving discrimination in antepartum depression screening using the Edinburgh Postnatal Depression Scale.

PubMed

Venkatesh, Kartik K; Kaimal, Anjali J; Castro, Victor M; Perlis, Roy H

2017-05-01

Universal screening of pregnant women for postpartum depression has recently been recommended; however, optimal application of depression screening tools in stratifying risk has not been defined. The current study examines new approaches to improve the ability of the Edinburgh Postnatal Depression Scale (EPDS) to stratify risk for postpartum depression, including alternate cut points, use of a continuous measure, and incorporation of other putative risk factors. An observational cohort study of 4939 women screened both antepartum and postpartum with a negative EPDS screen antepartum(i.e. EPDS<10). The primary outcome was a probable postpartum major depressive episode(EPDS cut-off ≥10). Area under the receiver operating characteristics curve(AUC), sensitivity, specificity, and predictive values were calculated. 287 women(5.8%) screened positive for postpartum depression. An antepartum EPDS cut-off<5 optimally identified women with a low risk of postpartum depression with a negative predictive value of 97.6%; however, overall discrimination was modest(AUC 0.66, 95%CI: 0.64-0.69); sensitivity was 78.7%, and specificity was 53.8%, and the positive predictive value was low at 9.5%. The negative predictive values were similar(>95%) at all antepartum EPDS cut-off values from 4 to 8. Discrimination was improved(AUC ranging from 0.70 to 0.73) when the antepartum EPDS was combined with a prior history of major depressive disorder before pregnancy. An inability to assess EPDS subscales and a relatively low prevalence of depression in this cohort. Though an antepartum EPDS cut-off score <5 yielded the greatest discrimination identifying women at low risk for postpartum depression, the negative predictive value was insufficient to substitute for postpartum screening. Copyright © 2017. Published by Elsevier B.V.

Investigation of guided wave propagation and attenuation in pipe buried in sand

NASA Astrophysics Data System (ADS)

Leinov, Eli; Lowe, Michael J. S.; Cawley, Peter

2015-07-01

Long-range guided wave testing is a well-established method for detection of corrosion defects in pipelines. The method is currently used routinely for above ground pipelines in a variety of industries, e.g. petrochemical and energy. When the method is applied to pipes buried in soil, test ranges tend to be significantly compromised and unpredictable due to attenuation of the guided wave resulting from energy leakage into the embedding soil. The attenuation characteristics of guided wave propagation in an 8 in. pipe buried in sand are investigated using a laboratory full-scale experimental rig and model predictions. We report measurements of attenuation of the T(0,1) and L(0,2) guided wave modes over a range of sand conditions, including loose, compacted, mechanically compacted, water saturated and drained. Attenuation values are found to be in the range of 1.65-5.5 dB/m and 0.98-3.2 dB/m for the torsional and longitudinal modes, respectively, over the frequency of 11-34 kHz. The application of overburden pressure modifies the compaction of the sand and increases the attenuation. Mechanical compaction of the sand yields similar attenuation values to those obtained with applied overburden pressure. The attenuation decreases in the fully water-saturated sand, and increases in drained sand to values comparable with those obtained for compacted sand. Attenuation measurements are compared with Disperse software model predictions and confirm that the attenuation phenomenon in buried pipes is essentially governed by the bulk shear velocity in the sand. The attenuation behaviour of the torsional guided wave mode is found not to be captured by a uniform soil model; comparison with predictions obtained with the Disperse software suggest that this is likely to be due to a layer of sand adhering to the surface of the pipe.

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

Lan, Chune; Xue, Jianming; Zhang, Yanwen

The determination of stopping powers for slow heavy ions in targets containing light elements is important to accurately describe ion-solid interactions, evaluate ion irradiation effects and predict ion ranges for device fabrication and nuclear applications. Recently, discrepancies of up to 40% between the experimental results and SRIM (Stopping and Range of Ions in Matter) predictions of ion ranges for heavy ions with medium and low energies (< {approx} 25 keV/nucleon) in light elemental targets have been reported. The longer experimental ion ranges indicate that the stopping powers used in the SRIM code are overestimated. Here, a molecular dynamics simulation schememore » is developed to calculate the ion ranges of heavy ions in light elemental targets. Electronic stopping powers generated from both a reciprocity approach and the SRIM code are used to investigate the influence of electronic stopping on ion range profiles. The ion range profiles for Au and Pb ions in SiC and Er ions in Si, with energies between 20 and 5250 keV, are simulated. The simulation results show that the depth profiles of implanted ions are deeper and in better agreement with the experiments when using the electronic stopping power values derived from the reciprocity approach. These results indicate that the origin of the discrepancy in ion ranges between experimental results and SRIM predictions in the low energy region may be an overestimation of the electronic stopping powers used in SRIM.« less

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

Lan, Chune; Xue, Jianming; Zhang, Yanwen

The determination of stopping powers for slow heavy ions in targets containing light elements is important to accurately describe ion-solid interactions, evaluate ion irradiation effects and predict ion ranges for device fabrication and nuclear applications. Recently, discrepancies of up to 40% between the experimental results and SRIM (Stopping and Range of Ions in Matter) predictions of ion ranges for heavy ions with medium and low energies (<25 keV/nucleon) in light elemental targets have been reported. The longer experimental ion ranges indicate that the stopping powers used in the SRIM code are overestimated. Here, a molecular dynamics simulation scheme is developedmore » to calculate the ion ranges of heavy ions in light elemental targets. Electronic stopping powers generated from both a reciprocity approach and the SRIM code are used to investigate the influence of electronic stopping on ion range profiles. The ion range profiles for Au and Pb ions in SiC and Er ions in Si, with energies between 20 and 5250 keV, are simulated. The simulation results show that the depth profiles of implanted ions are deeper and in better agreement with the experiments when using the electronic stopping power values derived from the reciprocity approach. These results indicate that the origin of the discrepancy in ion ranges between experimental results and SRIM predictions in the low energy region may be an overestimation of the electronic stopping powers used in SRIM.« less

Comparisons of AEROX computer program predictions of lift and induced drag with flight test data

NASA Technical Reports Server (NTRS)

Axelson, J.; Hill, G. C.

1981-01-01

The AEROX aerodynamic computer program which provides accurate predictions of induced drag and trim drag for the full angle of attack range and for Mach numbers from 0.4 to 3.0 is described. This capability is demonstrated comparing flight test data and AEROX predictions for 17 different tactical aircraft. Values of minimum (skin friction, pressure, and zero lift wave) drag coefficients and lift coefficient offset due to camber (when required) were input from the flight test data to produce total lift and drag curves. The comparisons of trimmed lift drag polars show excellent agreement between the AEROX predictions and the in flight measurements.

An improved method for predicting the effects of flight on jet mixing noise

NASA Technical Reports Server (NTRS)

Stone, J. R.

1979-01-01

A method for predicting the effects of flight on jet mixing noise has been developed on the basis of the jet noise theory of Ffowcs-Williams (1963) and data derived from model-jet/free-jet simulated flight tests. Predicted and experimental values are compared for the J85 turbojet engine on the Bertin Aerotrain, the low-bypass refanned JT8D engine on a DC-9, and the high-bypass JT9D engine on a DC-10. Over the jet velocity range from 280 to 680 m/sec, the predictions show a standard deviation of 1.5 dB.

Predictive Modeling of Response to Pregabalin for the Treatment of Neuropathic Pain Using 6-Week Observational Data: A Spectrum of Modern Analytics Applications.

PubMed

Emir, Birol; Johnson, Kjell; Kuhn, Max; Parsons, Bruce

2017-01-01

This post hoc analysis used 11 predictive models of data from a large observational study in Germany to evaluate potential predictors of achieving at least 50% pain reduction by week 6 after treatment initiation (50% pain response) with pregabalin (150-600 mg/d) in patients with neuropathic pain (NeP). The potential predictors evaluated included baseline demographic and clinical characteristics, such as patient-reported pain severity (0 [no pain] to 10 [worst possible pain]) and pain-related sleep disturbance scores (0 [sleep not impaired] to 10 [severely impaired sleep]) that were collected during clinic visits (baseline and weeks 1, 3, and 6). Baseline characteristics were also evaluated combined with pain change at week 1 or weeks 1 and 3 as potential predictors of end-of-treatment 50% pain response. The 11 predictive models were linear, nonlinear, and tree based, and all predictors in the training dataset were ranked according to their variable importance and normalized to 100%. The training dataset comprised 9187 patients, and the testing dataset had 6114 patients. To adjust for the high imbalance in the responder distribution (75% of patients were 50% responders), which can skew the parameter tuning process, the training set was balanced into sets of 1000 responders and 1000 nonresponders. The predictive modeling approaches that were used produced consistent results. Baseline characteristics alone had fair predictive value (accuracy range, 0.61-0.72; κ range, 0.17-0.30). Baseline predictors combined with pain change at week 1 had moderate predictive value (accuracy, 0.73-0.81; κ range, 0.37-0.49). Baseline predictors with pain change at weeks 1 and 3 had substantial predictive value (accuracy, 0.83-0.89; κ range, 0.54-0.71). When variable importance across the models was estimated, the best predictor of 50% responder status was pain change at week 3 (average importance 100.0%), followed by pain change at week 1 (48.1%), baseline pain score (14.1%), baseline depression (13.9%), and using pregabalin as a monotherapy (11.7%). The finding that pain changes by week 1 or weeks 1 and 3 are the best predictors of pregabalin response at 6 weeks suggests that adhering to a pregabalin medication regimen is important for an optimal end-of-treatment outcome. Regarding baseline predictors alone, considerable published evidence supports the importance of high baseline pain score and presence of depression as factors that can affect treatment response. Future research would be required to elucidate why using pregabalin as a monotherapy also had more than a 10% variable importance as a potential predictor. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A comparison of empirical and experimental O7+, O8+, and O/H values, with applications to terrestrial solar wind charge exchange

NASA Astrophysics Data System (ADS)

Whittaker, Ian C.; Sembay, Steve

2016-07-01

Solar wind charge exchange occurs at Earth between the neutral planetary exosphere and highly charged ions of the solar wind. The main challenge in predicting the resultant photon flux in the X-ray energy bands is due to the interaction efficiency, known as the α value. This study produces experimental α values at the Earth, for oxygen emission in the range of 0.5-0.7 keV. Thirteen years of data from the Advanced Composition Explorer are examined, comparing O7+ and O8+ abundances, as well as O/H to other solar wind parameters allowing all parameters in the αO7,8+ calculation to be estimated based on solar wind velocity. Finally, a table is produced for a range of solar wind speeds giving average O7+ and O8+ abundances, O/H, and αO7,8+ values.

Regression Analysis of Stage Variability for West-Central Florida Lakes

USGS Publications Warehouse

Sacks, Laura A.; Ellison, Donald L.; Swancar, Amy

2008-01-01

The variability in a lake's stage depends upon many factors, including surface-water flows, meteorological conditions, and hydrogeologic characteristics near the lake. An understanding of the factors controlling lake-stage variability for a population of lakes may be helpful to water managers who set regulatory levels for lakes. The goal of this study is to determine whether lake-stage variability can be predicted using multiple linear regression and readily available lake and basin characteristics defined for each lake. Regressions were evaluated for a recent 10-year period (1996-2005) and for a historical 10-year period (1954-63). Ground-water pumping is considered to have affected stage at many of the 98 lakes included in the recent period analysis, and not to have affected stage at the 20 lakes included in the historical period analysis. For the recent period, regression models had coefficients of determination (R2) values ranging from 0.60 to 0.74, and up to five explanatory variables. Standard errors ranged from 21 to 37 percent of the average stage variability. Net leakage was the most important explanatory variable in regressions describing the full range and low range in stage variability for the recent period. The most important explanatory variable in the model predicting the high range in stage variability was the height over median lake stage at which surface-water outflow would occur. Other explanatory variables in final regression models for the recent period included the range in annual rainfall for the period and several variables related to local and regional hydrogeology: (1) ground-water pumping within 1 mile of each lake, (2) the amount of ground-water inflow (by category), (3) the head gradient between the lake and the Upper Floridan aquifer, and (4) the thickness of the intermediate confining unit. Many of the variables in final regression models are related to hydrogeologic characteristics, underscoring the importance of ground-water exchange in controlling the stage of karst lakes in Florida. Regression equations were used to predict lake-stage variability for the recent period for 12 additional lakes, and the median difference between predicted and observed values ranged from 11 to 23 percent. Coefficients of determination for the historical period were considerably lower (maximum R2 of 0.28) than for the recent period. Reasons for these low R2 values are probably related to the small number of lakes (20) with stage data for an equivalent time period that were unaffected by ground-water pumping, the similarity of many of the lake types (large surface-water drainage lakes), and the greater uncertainty in defining historical basin characteristics. The lack of lake-stage data unaffected by ground-water pumping and the poor regression results obtained for that group of lakes limit the ability to predict natural lake-stage variability using this method in west-central Florida.

Microwave spectroscopy of carbonyl sulfide isotopologues solvated with 2-5 para-hydrogen molecules

NASA Astrophysics Data System (ADS)

Raston, Paul L.; Knapp, Chrissy J.; Jäger, Wolfgang

2017-11-01

We report high resolution Fourier transform microwave spectra of (pH2)N-OC32S and (pH2)N-OC34S clusters in the size range from N = 2 to 5. Observation of the J = 1-0 and J = 2-1 transitions allowed for determination of the rotational (B) and quartic distortion (D) constants for each N. Comparison with theory (Paesani et al., 2003) reveals that the predicted B values are of good quality (all within 100 MHz of the actual values), while the predicted D values are an order of magnitude too high. Results from linear molecule Kraitchman analyses for clusters with N ≤ 5 are consistent with theoretical calculations which suggest that the initial pH2 density accumulates in a donut ring about the carbon-oxygen bond.

Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS

USGS Publications Warehouse

Chelgani, S.C.; Hart, B.; Grady, W.C.; Hower, J.C.

2011-01-01

The relationship between maceral content plus mineral matter and gross calorific value (GCV) for a wide range of West Virginia coal samples (from 6518 to 15330 BTU/lb; 15.16 to 35.66MJ/kg) has been investigated by multivariable regression and adaptive neuro-fuzzy inference system (ANFIS). The stepwise least square mathematical method comparison between liptinite, vitrinite, plus mineral matter as input data sets with measured GCV reported a nonlinear correlation coefficient (R2) of 0.83. Using the same data set the correlation between the predicted GCV from the ANFIS model and the actual GCV reported a R2 value of 0.96. It was determined that the GCV-based prediction methods, as used in this article, can provide a reasonable estimation of GCV. Copyright ?? Taylor & Francis Group, LLC.

Estimation of sensitivity and specificity of pregnancy diagnosis using transrectal ultrasonography and ELISA for pregnancy-associated glycoprotein in dairy cows using a Bayesian latent class model.

PubMed

Shephard, R W; Morton, J M

2018-01-01

To determine the sensitivity (Se) and specificity (Sp) of pregnancy diagnosis using transrectal ultrasonography and an ELISA for pregnancy-associated glycoprotein (PAG) in milk, in lactating dairy cows in seasonally calving herds approximately 85-100 days after the start of the herd's breeding period. Paired results were used from pregnancy diagnosis using transrectal ultrasonography and ELISA for PAG in milk carried out approximately 85 and 100 days after the start of the breeding period, respectively, from 879 cows from four herds in Victoria, Australia. A Bayesian latent class model was used to estimate the proportion of cows pregnant, the Se and Sp of each test, and covariances between test results in pregnant and non-pregnant cows. Prior probability estimates were defined using beta distributions for the expected proportion of cows pregnant, Se and Sp for each test, and covariances between tests. Markov Chain Monte Carlo iterations identified posterior distributions for each of the unknown variables. Posterior distributions for each parameter were described using medians and 95% probability (i.e. credible) intervals (PrI). The posterior median estimates for Se and Sp for each test were used to estimate positive predictive and negative predictive values across a range of pregnancy proportions. The estimate for proportion pregnant was 0.524 (95% PrI = 0.485-0.562). For pregnancy diagnosis using transrectal ultrasonography, Se and Sp were 0.939 (95% PrI = 0.890-0.974) and 0.943 (95% PrI = 0.885-0.984), respectively; for ELISA, Se and Sp were 0.963 (95% PrI = 0.919-0.990) and 0.870 (95% PrI = 0.806-0.931), respectively. The estimated covariance between test results was 0.033 (95% PrI = 0.008-0.046) and 0.035 (95% PrI = 0.018-0.078) for pregnant and non-pregnant cows, respectively. Pregnancy diagnosis results using transrectal ultrasonography had a higher positive predictive value but lower negative predictive value than results from the ELISA across the range of pregnancy proportions assessed. Pregnancy diagnosis using transrectal ultrasonography and ELISA for PAG in milk had similar Se but differed in predictive values. Pregnancy diagnosis in seasonally calving herds around 85-100 days after the start of the breeding period using the ELISA is expected to result in a higher negative predictive value but lower positive predictive value than pregnancy diagnosis using transrectal ultrasonography. Thus, with the ELISA, a higher proportion of the cows with negative results will be non-pregnant, relative to results from transrectal ultrasonography, but a lower proportion of cows with positive results will be pregnant.

Preoperative Molecular Markers in Thyroid Nodules.

PubMed

Sahli, Zeyad T; Smith, Philip W; Umbricht, Christopher B; Zeiger, Martha A

2018-01-01

The need for distinguishing benign from malignant thyroid nodules has led to the pursuit of differentiating molecular markers. The most common molecular tests in clinical use are Afirma ® Gene Expression Classifier (GEC) and Thyroseq ® V2. Despite the rapidly developing field of molecular markers, several limitations exist. These challenges include the recent introduction of the histopathological diagnosis "Non-Invasive Follicular Thyroid neoplasm with Papillary-like nuclear features", the correlation of genetic mutations within both benign and malignant pathologic diagnoses, the lack of follow-up of molecular marker negative nodules, and the cost-effectiveness of molecular markers. In this manuscript, we review the current published literature surrounding the diagnostic value of Afirma ® GEC and Thyroseq ® V2. Among Afirma ® GEC studies, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) ranged from 75 to 100%, 5 to 53%, 13 to 100%, and 20 to 100%, respectively. Among Thyroseq ® V2 studies, Se, Sp, PPV, and NPV ranged from 40 to 100%, 56 to 93%, 13 to 90%, and 48 to 97%, respectively. We also discuss current challenges to Afirma ® GEC and Thyroseq ® V2 utility and clinical application, and preview the future directions of these rapidly developing technologies.

Gas-liquid nucleation at large metastability: unusual features and a new formalism

NASA Astrophysics Data System (ADS)

Santra, Mantu; Singh, Rakesh S.; Bagchi, Biman

2011-03-01

Nucleation at large metastability is still largely an unsolved problem, even though it is a problem of tremendous current interest, with wide-ranging practical value, from atmospheric research to materials science. It is now well accepted that the classical nucleation theory (CNT) fails to provide a qualitative picture and gives incorrect quantitative values for such quantities as activation-free energy barrier and supersaturation dependence of nucleation rate, especially at large metastability. In this paper, we present an alternative formalism to treat nucleation at large supersaturation by introducing an extended set of order parameters in terms of the kth largest liquid-like clusters, where k = 1 is the largest cluster in the system, k = 2 is the second largest cluster and so on. At low supersaturation, the size of the largest liquid-like cluster acts as a suitable order parameter. At large supersaturation, the free energy barrier for the largest liquid-like cluster disappears. We identify this supersaturation as the one at the onset of kinetic spinodal. The kinetic spinodal is system-size-dependent. Beyond kinetic spinodal many clusters grow simultaneously and competitively and hence the nucleation and growth become collective. In order to describe collective growth, we need to consider the full set of order parameters. We derive an analytic expression for the free energy of formation of the kth largest cluster. The expression predicts that, at large metastability (beyond kinetic spinodal), the barrier of growth for several largest liquid-like clusters disappears, and all these clusters grow simultaneously. The approach to the critical size occurs by barrierless diffusion in the cluster size space. The expression for the rate of barrier crossing predicts weaker supersaturation dependence than what is predicted by CNT at large metastability. Such a crossover behavior has indeed been observed in recent experiments (but eluded an explanation till now). In order to understand the large numerical discrepancy between simulation predictions and experimental results, we carried out a study of the dependence on the range of intermolecular interactions of both the surface tension of an equilibrium planar gas-liquid interface and the free energy barrier of nucleation. Both are found to depend significantly on the range of interaction for the Lennard-Jones potential, both in two and three dimensions. The value of surface tension and also the free energy difference between the gas and the liquid phase increase significantly and converge only when the range of interaction is extended beyond 6-7 molecular diameters. We find, with the full range of interaction potential, that the surface tension shows only a weak dependence on supersaturation, so the reason for the breakdown of CNT (with simulated values of surface tension and free energy gap) cannot be attributed to the supersaturation dependence of surface tension. This remains an unsettled issue at present because of the use of the value of surface tension obtained at coexistence.

THINGS about MOND

NASA Astrophysics Data System (ADS)

Gentile, G.; Famaey, B.; de Blok, W. J. G.

2011-03-01

We present an analysis of 12 high-resolution galactic rotation curves from The HI Nearby Galaxy Survey (THINGS) in the context of modified Newtonian dynamics (MOND). These rotation curves were selected to be the most reliable for mass modelling, and they are the highest quality rotation curves currently available for a sample of galaxies spanning a wide range of luminosities. We fit the rotation curves with the "simple" and "standard" interpolating functions of MOND, and we find that the "simple" function yields better results. We also redetermine the value of a0, and find a median value very close to the one determined in previous studies, a0 = (1.22 ± 0.33) × 10-8 cm s-2. Leaving the distance as a free parameter within the uncertainty of its best independently determined value leads to excellent quality fits for 75% of the sample. Among the three exceptions, two are also known to give relatively poor fits in Newtonian dynamics plus dark matter. The remaining case (NGC 3198) presents some tension between the observations and the MOND fit, which might, however, be explained by the presence of non-circular motions, by a small distance, or by a value of a0 at the lower end of our best-fit interval, 0.9 × 10-8 cm s-2. The best-fit stellar M/L ratios are generally in remarkable agreement with the predictions of stellar population synthesis models. We also show that the narrow range of gravitational accelerations found to be generated by dark matter in galaxies is consistent with the narrow range of additional gravity predicted by MOND.

Rapid and non-destructive determination of rancidity levels in butter cookies by multi-spectral imaging.

PubMed

Xia, Qing; Liu, Changhong; Liu, Jinxia; Pan, Wenjuan; Lu, Xuzhong; Yang, Jianbo; Chen, Wei; Zheng, Lei

2016-03-30

Rancidity is an important attribute for quality assessment of butter cookies, while traditional methods for rancidity measurement are usually laborious, destructive and prone to operational error. In the present paper, the potential of applying multi-spectral imaging (MSI) technology with 19 wavelengths in the range of 405-970 nm to evaluate the rancidity in butter cookies was investigated. Moisture content, acid value and peroxide value were determined by traditional methods and then related with the spectral information by partial least squares regression (PLSR) and back-propagation artificial neural network (BP-ANN). The optimal models for predicting moisture content, acid value and peroxide value were obtained by PLSR. The correlation coefficient (r) obtained by PLSR models revealed that MSI had a perfect ability to predict moisture content (r = 0.909), acid value (r = 0.944) and peroxide value (r = 0.971). The study demonstrated that the rancidity level of butter cookies can be continuously monitored and evaluated in real-time by the multi-spectral imaging, which is of great significance for developing online food safety monitoring solutions. © 2015 Society of Chemical Industry.

Estimation of shelf life of natural rubber latex exam-gloves based on creep behavior.

PubMed

Das, Srilekha Sarkar; Schroeder, Leroy W

2008-05-01

Samples of full-length glove-fingers cut from chlorinated and nonchlorinated latex medical examination gloves were aged for various times at several fixed temperatures and 25% relative humidity. Creep testing was performed using an applied stress of 50 kPa on rectangular specimens (10 mm x 8 mm) of aged and unaged glove fingers as an assessment of glove loosening during usage. Variations in creep curves obtained were compared to determine the threshold aging time when the amount of creep became larger than the initial value. These times were then used in various models to estimate shelf lives at lower temperatures. Several different methods of extrapolation were used for shelf-life estimation and comparison. Neither Q-factor nor Arrhenius activation energies, as calculated from 10 degrees C interval shift factors, were constant over the temperature range; in fact, both decreased at lower temperatures. Values of Q-factor and activation energies predicted up to 5 years of shelf life. Predictions are more sensitive to values of activation energy as the storage temperature departs from the experimental aging data. Averaging techniques for prediction of average activation energy predicted the longest shelf life as the curvature is reduced. Copyright 2007 Wiley Periodicals, Inc.

Point Spectroscopy System for Noncontact and Noninvasive Prediction of Transcutaneous Bilirubin Concentration

NASA Astrophysics Data System (ADS)

Ong, P. E.; K. C Huong, Audrey

2017-08-01

This paper presents the use of a point spectroscopy system to determine one’s transcutaneous bilirubin level using Modified Lambert Beer model and the developed fitting routine. This technique required a priori knowledge of extinction coefficient of bilirubin and hemoglobin components in the wavelength range of 440-500 nm for the prediction of the required parameter value. This work was conducted on different skin sites of six healthy Asians namely on the thenar region of the palm of their hand, back of the hand, posterior and anterior forearm. The obtained results revealed the lowest mean transcutaneous bilirubin concentration of 0.44±0.3 g/l predicted for palm site while the highest bilirubin level of 0.98±0.2 g/l was estimated for posterior forearm. These values were also compared with that presented in the literature. This study found considerably good consistency in the value predicted for different subjects especially at the thenar region of the palm. This work concluded that the proposed system and technique may be suitably served as an alternative means to noncontact and noninvasive measurement of one’s transcutaneous bilirubin level at palm site.

Modelling and simulation of the intervertebral movements of the lumbar spine using an inverse kinematic algorithm.

PubMed

Sun, L W; Lee, R Y W; Lu, W; Luk, K D K

2004-11-01

An inverse kinematic model is presented that was employed to determine the optimum intervertebral joint configuration for a given forward-bending posture of the human trunk. The lumbar spine was modelled as an open-end, kinematic chain of five links that represented the five vertebrae (L 1-L5). An optimisation equation with physiological constraints was employed to determine the intervertebral joint configuration. Intervertebral movements were measured from sagittal X-ray films of 22 subjects. The mean difference between the X-ray measurements of intervertebral rotations in the sagittal plane and the values predicted by the kinematic model was less than 1.6 degrees. Pearson product-moment correlation R was used to measure the relationship between the measured and predicted values. The R-values were found to be high, ranging from 0.83 to 0.97, for prediction of intervertebral rotation, but poor for intervertebral translation (R= 0.08-0.67). It is concluded that the inverse kinematic model will be clinically useful for predicting intervertebral rotation when X-ray or invasive measurements are undesirable. It will also be useful to biomechanical modelling, which requires accurate kinematic information as model input data.

Predicting terrestrial gamma dose rate based on geological and soil information: case study of Perak state, Malaysia.

PubMed

Ramli, A T; Apriantoro, N H; Heryansyah, A; Basri, N A; Sanusi, M S M; Abu Hanifah, N Z H

2016-03-01

An extensive terrestrial gamma radiation dose (TGRD) rate survey has been conducted in Perak State, Peninsular Malaysia. The survey has been carried out taking into account geological and soil information, involving 2930 in situ surveys. Based on geological and soil information collected during TGRD rate measurements, TGRD rates have been predicted in Perak State using a statistical regression analysis which would be helpful to focus surveys in areas that are difficult to access. An equation was formulated according to a linear relationship between TGRD rates, geological contexts and soil types. The comparison of in situ measurements and predicted TGRD dose rates was tabulated and showed good agreement with the linear regression equation. The TGRD rates in the study area ranged from 38 nGy h(-1) to 1039 nGy h(-1) with a mean value of 224  ±  138 nGy h(-1). This value is higher than the world average as reported in UNSCEAR 2000. The TGRD rates contribute an average dose rate of 1.37 mSv per year. An isodose map for the study area was developed using a Kriging method based on predicted and in situ TGRD rate values.

Capturing anharmonicity in a lattice thermal conductivity model for high-throughput predictions

DOE PAGES

Miller, Samuel A.; Gorai, Prashun; Ortiz, Brenden R.; ...

2017-01-06

High-throughput, low-cost, and accurate predictions of thermal properties of new materials would be beneficial in fields ranging from thermal barrier coatings and thermoelectrics to integrated circuits. To date, computational efforts for predicting lattice thermal conductivity (κ L) have been hampered by the complexity associated with computing multiple phonon interactions. In this work, we develop and validate a semiempirical model for κ L by fitting density functional theory calculations to experimental data. Experimental values for κ L come from new measurements on SrIn 2O 4, Ba 2SnO 4, Cu 2ZnSiTe 4, MoTe 2, Ba 3In 2O 6, Cu 3TaTe 4, SnO,more » and InI as well as 55 compounds from across the published literature. Here, to capture the anharmonicity in phonon interactions, we incorporate a structural parameter that allows the model to predict κ L within a factor of 1.5 of the experimental value across 4 orders of magnitude in κ L values and over a diverse chemical and structural phase space, with accuracy similar to or better than that of computationally more expensive models.« less

Water quality characterization and mathematical modeling of dissolved oxygen in the East and West Ponds, Jamaica Bay Wildlife Refuge.

PubMed

Maillacheruvu, Krishnanand; Roy, D; Tanacredi, J

2003-09-01

The current study was undertaken to characterize the East and West Ponds and develop a mathematical model of the effects of nutrient and BOD loading on dissolved oxygen (DO) concentrations in these ponds. The model predicted that both ponds will recover adequately given the average expected range of nutrient and BOD loading due to waste from surface runoff and migratory birds. The predicted dissolved oxygen levels in both ponds were greater than 5.0 mg/L, and were supported by DO levels in the field which were typically above 5.0 mg/L during the period of this study. The model predicted a steady-state NBOD concentration of 12.0-14.0 mg/L in the East Pond, compared to an average measured value of 3.73 mg/L in 1994 and an average measured value of 12.51 mg/L in a 1996-97 study. The model predicted that the NBOD concentration in the West Pond would be under 3.0 mg/L compared to the average measured values of 7.50 mg/L in 1997, and 8.51 mg/L in 1994. The model predicted that phosphorus (as PO4(3-)) concentration in the East Pond will approach 4.2 mg/L in 4 months, compared to measured average value of 2.01 mg/L in a 1994 study. The model predicted that phosphorus concentration in the West Pond will approach 1.00 mg/L, compared to a measured average phosphorus (as PO4(3-)) concentration of 1.57 mg/L in a 1994 study.

Simulation of nutrient and sediment concentrations and loads in the Delaware inland bays watershed: Extension of the hydrologic and water-quality model to ungaged segments

USGS Publications Warehouse

Gutierrez-Magness, Angelica L.

2006-01-01

Rapid population increases, agriculture, and industrial practices have been identified as important sources of excessive nutrients and sediments in the Delaware Inland Bays watershed. The amount and effect of excessive nutrients and sediments in the Inland Bays watershed have been well documented by the Delaware Geological Survey, the Delaware Department of Natural Resources and Environmental Control, the U.S. Environmental Protection Agency's National Estuary Program, the Delaware Center for Inland Bays, the University of Delaware, and other agencies. This documentation and data previously were used to develop a hydrologic and water-quality model of the Delaware Inland Bays watershed to simulate nutrients and sediment concentrations and loads, and to calibrate the model by comparing concentrations and streamflow data at six stations in the watershed over a limited period of time (October 1998 through April 2000). Although the model predictions of nutrient and sediment concentrations for the calibrated segments were fairly accurate, the predictions for the 28 ungaged segments located near tidal areas, where stream data were not available, were above the range of values measured in the area. The cooperative study established in 2000 by the Delaware Department of Natural Resources and Environmental Control, the Delaware Geological Survey, and the U.S. Geological Survey was extended to evaluate the model predictions in ungaged segments and to ensure that the model, developed as a planning and management tool, could accurately predict nutrient and sediment concentrations within the measured range of values in the area. The evaluation of the predictions was limited to the period of calibration (1999) of the 2003 model. To develop estimates on ungaged watersheds, parameter values from calibrated segments are transferred to the ungaged segments; however, accurate predictions are unlikely where parameter transference is subject to error. The unexpected nutrient and sediment concentrations simulated with the 2003 model were likely the result of inappropriate criteria for the transference of parameter values. From a model-simulation perspective, it is a common practice to transfer parameter values based on the similarity of soils or the similarity of land-use proportions between segments. For the Inland Bays model, the similarity of soils between segments was used as the basis to transfer parameter values. An alternative approach, which is documented in this report, is based on the similarity of the spatial distribution of the land use between segments and the similarity of land-use proportions, as these can be important factors for the transference of parameter values in lumped models. Previous work determined that the difference in the variation of runoff due to various spatial distributions of land use within a watershed can cause substantialloss of accuracy in the model predictions. The incorporation of the spatial distribution of land use to transfer parameter values from calibrated to uncalibrated segments provided more consistent and rational predictions of flow, especially during the summer, and consequently, predictions of lower nutrient concentrations during the same period. For the segments where the similarity of spatial distribution of land use was not clearly established with a calibrated segment, the similarity of the location of the most impervious areas was also used as a criterion for the transference of parameter values. The model predictions from the 28 ungaged segments were verified through comparison with measured in-stream concentrations from local and nearby streams provided by the Delaware Department of Natural Resources and Environmental Control. Model results indicated that the predicted edge-of-stream total suspended solids loads in the Inland Bays watershed were low in comparison to loads reported for the Eastern Shore of Maryland from the Chesapeake Bay watershed model. The flatness of the ter

[A Retrospective Study of Mean Computed Tomography Value to Predict 
the Tumor Invasiveness in AAH and Clinical Stage Ia Lung Cancer].

PubMed

Wu, Hanran; Liu, Changqing; Xu, Meiqing; Xiong, Ran; Xu, Guangwen; Li, Caiwei; Xie, Mingran

2018-03-20

Recently, the detectable rate of ground-glass opacity (GGO ) was significantly increased, a appropriate diagnosis before clinic treatment tends to be important for patients with GGO lesions. The aim of this study is to validate the ability of the mean computed tomography (m-CT) value to predict tumor invasiveness, and compared with other measurements such as Max CT value, GGO size, solid size of GGO and C/T ratio (consolid/tumor ratio, C/T) to find out the best measurement to predict tumor invasiveness. A retrospective study was conducted of 129 patients who recieved lobectomy and were pathological confirmed as atypical adenomatous pyperplasia (AAH) or clinical stage Ia lung cance in our center between January 2012 and December 2013. Of those 129 patients, the number of patients of AAH, AIS, AIS and invasive adenocarcinoma were 43, 26, 17 and 43, respectively. We defined AAH and AIS as noninvasive cancer (NC), MIA and invasive adenocarcinoma were categorized as invasive cancer(IC). We used receiver operating characteristic (ROC) curve analysis to compare the ability to predict tumor invasiveness between m-CT value, consolidation/tumor ratio, tumor size and solid size of tumor. Multiple logistic regression analyses were performed to determine the independent variables for prediction of pathologic more invasive lung cancer. 129 patients were enrolled in our study (59 male and 70 female), the patients were a median age of (62.0±8.6) years (range, 44 to 82 years). The two groups were similar in terms of age, sex, differentiation (P>0.05). ROC curve analysis was performed to determine the appropriate cutoff value and area under the cure (AUC). The cutoff value of solid tumor size, tumor size, C/T ratio, m-CT value and Max CT value were 9.4 mm, 15.3 mm, 47.5%, -469.0 HU and -35.0 HU, respectively. The AUC of those variate were 0.89, 0.79, 0.82, 0.90, 0.85, respectively. When compared the clinical and radiologic data between two groups, we found the IC group was strongly associated with a high m-CT value, high Max CT value, high C/T ratio and large tumor size. Gender, solid tumor size, tumor size, C/T ratio, m-CT value and MaxCT value were selected factor for multivariate analysis, when using the preoperatively determined variables to predict the tumor invasiveness, revealed that tumor size, C/T ratio, m-CT value and Max CT value were independent predictive factors of IC. The musurements of Max CT value, GGO size, solid size of GGO and C/T ratio were significantly correlated with tumor invasiveness, and the evaluation of m-CT value is most useful musurement in predicting more invasive lung cancer.

Applications of subseasonal-to-seasonal (S2S) predictions

NASA Astrophysics Data System (ADS)

White, Christopher; Lamb, Rob; Carlsen, Henrik; Robertson, Andrew; Klein, Richard; Lazo, Jeffrey; Kumar, Arun; Vitart, Frederic; Coughlan de Perez, Erin; Ray, Andrea; Murray, Virginia; Graham, Richard; Buontempo, Carlo

2017-04-01

While long-range seasonal outlooks have been operational for many years, until recently the extended-range timescale - referred to as 'subseasonal-to-seasonal' (S2S) and which sits between the medium- to long-range forecasting timescales - has received relatively little attention. The S2S timescale has long been seen as a 'predictability desert', yet a new generation of S2S predictions are starting to bridge the gap between weather forecasts and longer-range prediction. Decisions in a range of sectors are made in this extended-range lead time, therefore there is a strong demand for this new generation of predictions. At least ten international weather centres now have some capability for issuing experimental or operational S2S predictions, including the European Centre for Medium-Range Weather Forecasting (ECMWF) and the National Oceanic and Atmospheric Administration (NOAA) that now have operational S2S outputs. International efforts are now underway to identify key sources of predictability, improve forecast skill and operationalise aspects of S2S forecasts, however challenges remain in advancing this new frontier. If S2S predictions are to be utilised effectively, it is important that along with science advances, we learn how to develop, communicate and apply these forecasts appropriately. In this study, we present the potential of the emerging operational S2S forecasts to the wider weather and climate applications community by undertaking the first comprehensive review of sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. We explore the value of applications-relevant S2S predictions, and highlight the opportunities and challenges facing their uptake. We show how social sciences can be integrated with S2S development - from communication to decision-making and valuation of forecasts - to enhance the benefits of 'climate services' approaches for extended-range forecasting. We highlight the availability of data repositories of near real-time S2S forecasts and hindcasts, including the WWRP-WCRP (http://apps.ecmwf.int/datasets/data/s2s) and North American Multimodel Ensemble (NMME; http://www.cpc.ncep.noaa.gov/products/NMME/data.html) repositories, and discuss how they are promoting the use (and aiding the development) of S2S predictions. While S2S forecasting is at a relatively early stage of development, we conclude that it presents a significant new window of opportunity that can be explored for application-ready capabilities that could allow many sectors the opportunity to systematically plan on a new time horizon.

Developing a computer-controlled simulated digestion system to predict the concentration of metabolizable energy of feedstuffs for rooster.

PubMed

Zhao, F; Ren, L Q; Mi, B M; Tan, H Z; Zhao, J T; Li, H; Zhang, H F; Zhang, Z Y

2014-04-01

Four experiments were conducted to evaluate the effectiveness of a computer-controlled simulated digestion system (CCSDS) for predicting apparent metabolizable energy (AME) and true metabolizable energy (TME) using in vitro digestible energy (IVDE) content of feeds for roosters. In Exp. 1, the repeatability of the IVDE assay was tested in corn, wheat, rapeseed meal, and cottonseed meal with 3 assays of each sample and each with 5 replicates of the same sample. In Exp. 2, the additivity of IVDE concentration in corn, soybean meal, and cottonseed meal was tested by comparing determined IVDE values of the complete diet with values predicted from measurements on individual ingredients. In Exp. 3, linear models to predict AME and TME based on IVDE were developed with 16 calibration samples. In Exp. 4, the accuracy of prediction models was tested by the differences between predicted and determined values for AME or TME of 6 ingredients and 4 diets. In Exp. 1, the mean CV of IVDE was 0.88% (range = 0.20 to 2.14%) for corn, wheat, rapeseed meal, and cottonseed meal. No difference in IVDE was observed between 3 assays of an ingredient, indicating that the IVDE assay is repeatable under these conditions. In Exp. 2, minimal differences (<21 kcal/kg) were observed between determined and calculated IVDE of 3 complete diets formulated with corn, soybean meal, and cottonseed meal, demonstrating that the IVDE values are additive in a complete diet. In Exp. 3, linear relationships between AME and IVDE and between TME and IVDE were observed in 16 calibration samples: AME = 1.062 × IVDE - 530 (R(2) = 0.97, residual standard deviation [RSD] = 146 kcal/kg, P < 0.001) and TME = 1.050 × IVDE - 16 (R(2) = 0.97, RSD = 148 kcal/kg, P < 0.001). Differences of less than 100 kcal/kg were observed between determined and predicted values in 10 and 9 of the 16 calibration samples for AME and TME, respectively. In Exp. 4, differences of less than 100 kcal/kg between determined and predicted values were observed in 3 and 4 of the 6 ingredient samples for AME and TME, respectively, and all 4 diets showed the differences of less than 25 kcal/kg between determined and predicted AME or TME. Our results indicate that the CCSDS is repeatable and additive. This system accurately predicted AME or TME on 17 of the 26 samples and may be a promising method to predict the energetic values of feed for poultry.

Fractional Flow Reserve: Does a Cut-off Value add Value?

PubMed Central

Mohdnazri, Shah R; Keeble, Thomas R

2016-01-01

Fractional flow reserve (FFR) has been shown to improve outcomes when used to guide percutaneous coronary intervention (PCI). There have been two proposed cut-off points for FFR. The first was derived by comparing FFR against a series of non-invasive tests, with a value of ≤0.75 shown to predict a positive ischaemia test. It was then shown in the DEFER study that a vessel FFR value of ≥0.75 was associated with safe deferral of PCI. During the validation phase, a ‘grey zone’ for FFR values of between 0.76 and 0.80 was demonstrated, where a positive non-invasive test may still occur, but sensitivity and specificity were sub-optimal. Clinical judgement was therefore advised for values in this range. The FAME studies then moved the FFR cut-off point to ≤0.80, with a view to predicting outcomes. The ≤0.80 cut-off point has been adopted into clinical practice guidelines, whereas the lower value of ≤0.75 is no longer widely used. Here, the authors discuss the data underpinning these cut-off values and the practical implications for their use when using FFR guidance in PCI. PMID:29588700

Measurements of (60)Co in massive steel samples exposed to the Hiroshima atomic bomb explosion.

PubMed

Gasparro, Joël; Hult, Mikael; Marissens, Gerd; Hoshi, Masaharu; Tanaka, Kenichi; Endo, Satoru; Laubenstein, Matthias; Dombrowski, Harald; Arnold, Dirk

2012-04-01

To study discrepancies in retrospective Hiroshima dosimetry, the specific activity of (60)Co in 16 steel samples from Hiroshima was measured using gamma-ray spectrometry in underground laboratories. There is general agreement between these new activity measurements and the specific activities derived from previously calculated dose values on the one hand and former measurements of samples gathered at distances less than 1,000 m from the center of the explosion (< 1,000 m slant range) on the other. It was found that activities at long range (> 1,300 m slant range) were mainly cosmogenically induced. Furthermore, at long range, these results are in disagreement with older measurements whose specific activity values were 10 to 100 times higher than predicted by computer model calculations in DS86 and DS02. As a consequence, the previously reported discrepancy is not confirmed.

Isopycnal mixing by mesoscale eddies significantly impacts oceanic anthropogenic carbon uptake

NASA Astrophysics Data System (ADS)

Gnanadesikan, Anand; Pradal, Marie-Aude; Abernathey, Ryan

2015-06-01

Anthropogenic carbon dioxide uptake varies across Earth System Models for reasons that have remained obscure. When varied within a single model, the lateral eddy mixing coefficient ARedi produces a range of uptake similar to the modeled range. The highest uptake, resulting from a simulation with a constant ARedi of 2400 m2/s, simulates 15% more historical carbon uptake than a model with ARedi = 400 m2/s. A sudden doubling in carbon dioxide produces a 21% range in carbon uptake across the models. Two spatially dependent representations of ARedi produce uptake that lies in the middle of the range of constant values despite predicting very large values in the subtropical gyres. One-dimensional diffusive models of the type used for integrated assessments can be fit to the simulations, with ARedi accounting for a substantial fraction of the effective vertical diffusion. Such models, however, mask significant regional changes in stratification and biological carbon storage.

The galaxy-dark matter halo connection: which galaxy properties are correlated with the host halo mass?

NASA Astrophysics Data System (ADS)

Contreras, S.; Baugh, C. M.; Norberg, P.; Padilla, N.

2015-09-01

We demonstrate how the properties of a galaxy depend on the mass of its host dark matter subhalo, using two independent models of galaxy formation. For the cases of stellar mass and black hole mass, the median property value displays a monotonic dependence on subhalo mass. The slope of the relation changes for subhalo masses for which heating by active galactic nuclei becomes important. The median property values are predicted to be remarkably similar for central and satellite galaxies. The two models predict considerable scatter around the median property value, though the size of the scatter is model dependent. There is only modest evolution with redshift in the median galaxy property at a fixed subhalo mass. Properties such as cold gas mass and star formation rate, however, are predicted to have a complex dependence on subhalo mass. In these cases, subhalo mass is not a good indicator of the value of the galaxy property. We illustrate how the predictions in the galaxy property-subhalo mass plane differ from the assumptions made in some empirical models of galaxy clustering by reconstructing the model output using a basic subhalo abundance matching scheme. In its simplest form, abundance matching generally does not reproduce the clustering predicted by the models, typically resulting in an overprediction of the clustering signal. Using the predictions of the galaxy formation model for the correlations between pairs of galaxy properties, the basic abundance matching scheme can be extended to reproduce the model predictions more faithfully for a wider range of galaxy properties. Our results have implications for the analysis of galaxy clustering, particularly for low abundance samples.

Graphical assessment of incremental value of novel markers in prediction models: From statistical to decision analytical perspectives.

PubMed

Steyerberg, Ewout W; Vedder, Moniek M; Leening, Maarten J G; Postmus, Douwe; D'Agostino, Ralph B; Van Calster, Ben; Pencina, Michael J

2015-07-01

New markers may improve prediction of diagnostic and prognostic outcomes. We aimed to review options for graphical display and summary measures to assess the predictive value of markers over standard, readily available predictors. We illustrated various approaches using previously published data on 3264 participants from the Framingham Heart Study, where 183 developed coronary heart disease (10-year risk 5.6%). We considered performance measures for the incremental value of adding HDL cholesterol to a prediction model. An initial assessment may consider statistical significance (HR = 0.65, 95% confidence interval 0.53 to 0.80; likelihood ratio p < 0.001), and distributions of predicted risks (densities or box plots) with various summary measures. A range of decision thresholds is considered in predictiveness and receiver operating characteristic curves, where the area under the curve (AUC) increased from 0.762 to 0.774 by adding HDL. We can furthermore focus on reclassification of participants with and without an event in a reclassification graph, with the continuous net reclassification improvement (NRI) as a summary measure. When we focus on one particular decision threshold, the changes in sensitivity and specificity are central. We propose a net reclassification risk graph, which allows us to focus on the number of reclassified persons and their event rates. Summary measures include the binary AUC, the two-category NRI, and decision analytic variants such as the net benefit (NB). Various graphs and summary measures can be used to assess the incremental predictive value of a marker. Important insights for impact on decision making are provided by a simple graph for the net reclassification risk. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predictive value of pulse pressure variation for fluid responsiveness in septic patients using lung-protective ventilation strategies.

PubMed

Freitas, F G R; Bafi, A T; Nascente, A P M; Assunção, M; Mazza, B; Azevedo, L C P; Machado, F R

2013-03-01

The applicability of pulse pressure variation (ΔPP) to predict fluid responsiveness using lung-protective ventilation strategies is uncertain in clinical practice. We designed this study to evaluate the accuracy of this parameter in predicting the fluid responsiveness of septic patients ventilated with low tidal volumes (TV) (6 ml kg(-1)). Forty patients after the resuscitation phase of severe sepsis and septic shock who were mechanically ventilated with 6 ml kg(-1) were included. The ΔPP was obtained automatically at baseline and after a standardized fluid challenge (7 ml kg(-1)). Patients whose cardiac output increased by more than 15% were considered fluid responders. The predictive values of ΔPP and static variables [right atrial pressure (RAP) and pulmonary artery occlusion pressure (PAOP)] were evaluated through a receiver operating characteristic (ROC) curve analysis. Thirty-four patients had characteristics consistent with acute lung injury or acute respiratory distress syndrome and were ventilated with high levels of PEEP [median (inter-quartile range) 10.0 (10.0-13.5)]. Nineteen patients were considered fluid responders. The RAP and PAOP significantly increased, and ΔPP significantly decreased after volume expansion. The ΔPP performance [ROC curve area: 0.91 (0.82-1.0)] was better than that of the RAP [ROC curve area: 0.73 (0.59-0.90)] and pulmonary artery occlusion pressure [ROC curve area: 0.58 (0.40-0.76)]. The ROC curve analysis revealed that the best cut-off for ΔPP was 6.5%, with a sensitivity of 0.89, specificity of 0.90, positive predictive value of 0.89, and negative predictive value of 0.90. Automatized ΔPP accurately predicted fluid responsiveness in septic patients ventilated with low TV.

Among-Individual Variation in Desert Iguanas (Squamata: Dipsosaurus dorsalis): Endurance Capacity Is Positively Related to Home Range Size.

PubMed

Singleton, Jennifer M; Garland, Theodore

Among species of lizards, endurance capacity measured on a motorized treadmill is positively related to daily movement distance and time spent moving, but few studies have addressed such relationships at the level of individual variation within a sex and age category in a single population. Both endurance capacity and home range size show substantial individual variation in lizards, rendering them suitable for such studies. We predicted that these traits would be positively related because endurance capacity is one of the factors that has the potential to limit home range size. We measured the endurance capacity and home range size of adult male desert iguanas (Dipsosaurus dorsalis). Lizards were field captured for measurements of endurance, and home range data were gathered using visual identification of previously marked individuals. Endurance was significantly repeatable between replicate trials, conducted 1-17 d apart ([Formula: see text] for log-transformed values, [Formula: see text], [Formula: see text]). The log of the higher of two endurance trials was positively but not significantly related to log body mass. The log of home range area was positively but not significantly related to log body mass, the number of sightings, or the time span from first to last sighting. As predicted, log endurance was positively correlated with log home range area ([Formula: see text], [Formula: see text], one-tailed [Formula: see text]; for body-mass residual endurance values: [Formula: see text], one-tailed [Formula: see text]). These results suggest that endurance capacity may have a permissive effect on home range size. Alternatively, individuals with larger home ranges may experience training effects (phenotypic plasticity) that increase their endurance.

Prediction of Chemoresistance in Women Undergoing Neo-Adjuvant Chemotherapy for Locally Advanced Breast Cancer: Volumetric Analysis of First-Order Textural Features Extracted from Multiparametric MRI

PubMed Central

Losio, C.; Della Corte, A.; Venturini, E.; Ambrosi, A.; Panizza, P.; De Cobelli, F.

2018-01-01

Purpose To assess correlations between volumetric first-order texture parameters on baseline MRI and pathological response after neoadjuvant chemotherapy (NAC) for locally advanced breast cancer (BC). Materials and Methods 69 patients with locally advanced BC candidate to neoadjuvant chemotherapy underwent MRI within 4 weeks from the start of therapeutic regimen. T2, DWI, and DCE sequences were analyzed and maps were generated for Apparent Diffusion Coefficient (ADC), T2 signal intensity, and the following dynamic parameters: k-trans, peak enhancement, area under curve (AUC), time to maximal enhancement (TME), wash-in rate, and washout rate. Volumetric analysis of these parameters was performed, yielding a histogram analysis including first-order texture kinetics (percentiles, maximum value, minimum value, range, standard deviation, mean, median, mode, skewness, and kurtosis). Finally, correlations between these values and response to NAC (evaluated on the surgical specimen according to RECIST 1.1 criteria) were assessed. Results Out of 69 tumors, 33 (47.8%) achieved complete pathological response, 26 (37.7%) partial response, and 10 (14.5%) no response. Higher levels of AUCmax (p value = 0.0338), AUCrange (p value = 0.0311), and TME75 (p value = 0.0452) and lower levels of washout10 (p value = 0.0417), washout20 (p value = 0.0138), washout25 (p value = 0.0114), and washout30 (p value = 0.05) were predictive of noncomplete response. Conclusion Histogram-derived texture analysis of MRI images allows finding quantitative parameters predictive of nonresponse to NAC in women affected by locally advanced BC. PMID:29853811

Prediction of Chemoresistance in Women Undergoing Neo-Adjuvant Chemotherapy for Locally Advanced Breast Cancer: Volumetric Analysis of First-Order Textural Features Extracted from Multiparametric MRI.

PubMed

Panzeri, M M; Losio, C; Della Corte, A; Venturini, E; Ambrosi, A; Panizza, P; De Cobelli, F

2018-01-01

To assess correlations between volumetric first-order texture parameters on baseline MRI and pathological response after neoadjuvant chemotherapy (NAC) for locally advanced breast cancer (BC). 69 patients with locally advanced BC candidate to neoadjuvant chemotherapy underwent MRI within 4 weeks from the start of therapeutic regimen. T2, DWI, and DCE sequences were analyzed and maps were generated for Apparent Diffusion Coefficient (ADC), T2 signal intensity, and the following dynamic parameters: k -trans, peak enhancement, area under curve (AUC), time to maximal enhancement (TME), wash-in rate, and washout rate. Volumetric analysis of these parameters was performed, yielding a histogram analysis including first-order texture kinetics (percentiles, maximum value, minimum value, range, standard deviation, mean, median, mode, skewness, and kurtosis). Finally, correlations between these values and response to NAC (evaluated on the surgical specimen according to RECIST 1.1 criteria) were assessed. Out of 69 tumors, 33 (47.8%) achieved complete pathological response, 26 (37.7%) partial response, and 10 (14.5%) no response. Higher levels of AUCmax ( p value = 0.0338), AUCrange ( p value = 0.0311), and TME 75 ( p value = 0.0452) and lower levels of washout 10 ( p value = 0.0417), washout 20 ( p value = 0.0138), washout 25 ( p value = 0.0114), and washout 30 ( p value = 0.05) were predictive of noncomplete response. Histogram-derived texture analysis of MRI images allows finding quantitative parameters predictive of nonresponse to NAC in women affected by locally advanced BC.

Thirteenth Annual Acquisition Research Symposium. Acquisition Research: Creating Synergy for Informed Change. Volume 1

DTIC Science & Technology

2016-04-30

renewable energy projects with a focus on novel onshore/offshore and small/large scale wind turbine designs for expanding their operational range and...ROA to estimate the values of maintenance options created by the implementation of PHM in wind turbines . When an RUL is predicted for a subsystem...predicted for the system. The section titled Example— Wind Turbine With an Outcome-Based Contract presents a case study for a PHM enabled wind

Prediction of hot deformation behavior of high phosphorus steel using artificial neural network

NASA Astrophysics Data System (ADS)

Singh, Kanchan; Rajput, S. K.; Soota, T.; Verma, Vijay; Singh, Dharmendra

2018-03-01

To predict the hot deformation behavior of high phosphorus steel, the hot compression experiments were performed with the help of thermo-mechanical simulator Gleeble® 3800 in the temperatures ranging from 750 °C to 1050 °C and strain rates of 0.001 s-1, 0.01 s-1, 0.1 s-1, 0.5 s-1, 1.0 s-1 and 10 s-1. The experimental stress-strain data are employed to develop artificial neural network (ANN) model and their predictability. Using different combination of temperature, strain and strain rate as a input parameter and obtained experimental stress as a target, a multi-layer ANN model based on feed-forward back-propagation algorithm is trained, to predict the flow stress for a given processing condition. The relative error between predicted and experimental stress are in the range of ±3.5%, whereas the correlation coefficient (R2) of training and testing data are 0.99986 and 0.99999 respectively. This shows that a well-trained ANN model has excellent capability to predict the hot deformation behavior of materials. Comparative study shows quite good agreement of predicted and experimental values.

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

PubMed Central

Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM. PMID:29391864

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

PubMed

Yang, Haimin; Pan, Zhisong; Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

Thermal expansion coefficient prediction of fuel-cell seal materials from silica sand

NASA Astrophysics Data System (ADS)

Hidayat, Nurul; Triwikantoro, Baqiya, Malik A.; Pratapa, Suminar

2013-09-01

This study is focused on the prediction of coefficient of thermal expansion (CTE) of silica-sand-based fuel-cell seal materials (FcSMs) which in principle require a CTE value in the range of 9.5-12 ppm/°C. A semi-quantitative theoretical method to predict the CTE value is proposed by applying the analyzed phase compositions from XRD data and characterized density-porosity behavior. A typical silica sand was milled at 150 rpm for 1 hour followed by heating at 1000 °C for another hour. The sand and heated samples were characterized by means of XRD to perceive the phase composition correlation between them. Rietveld refinement was executed to investigate the weight fraction of the phase contained in the samples, and then converted to volume fraction for composite CTE calculations. The result was applied to predict their potential physical properties for FcSM. Porosity was taken into account in the calculation after which it was directly measured by the Archimedes method.

Differences in SEM-AVS and ERM-ERL predictions of sediment impacts from metals in two US Virgin Islands marinas.

PubMed

Hinkey, Lynne M; Zaidi, Baqar R

2007-02-01

Two US Virgin Islands marinas were examined for potential metal impacts by comparing sediment chemistry data with two sediment quality guideline (SQG) values: the ratio of simultaneously extractable metals to acid volatile sulfides (SEM-AVS), and effects range-low and -mean (ERL-ERM) values. ERL-ERMs predicted the marina/boatyard complex (IBY: 2118 microg/g dry weight total metals, two exceeded ERMs) would have greater impacts than the marina with no boatyard (CBM: 231 microg/g dry weight total metals, no ERMs exceeded). The AVS-SEM method predicted IBY would have fewer effects due to high AVS-forming metal sulfide complexes, reducing trace metal bioavailability. These contradictory predictions demonstrate the importance of validating the results of either of these methods with other toxicity measures before making any management or regulatory decisions regarding boating and marina impacts. This is especially important in non-temperate areas where sediment quality guidelines have not been validated.

Numerical Simulation and Artificial Neural Network Modeling for Predicting Welding-Induced Distortion in Butt-Welded 304L Stainless Steel Plates

NASA Astrophysics Data System (ADS)

Narayanareddy, V. V.; Chandrasekhar, N.; Vasudevan, M.; Muthukumaran, S.; Vasantharaja, P.

2016-02-01

In the present study, artificial neural network modeling has been employed for predicting welding-induced angular distortions in autogenous butt-welded 304L stainless steel plates. The input data for the neural network have been obtained from a series of three-dimensional finite element simulations of TIG welding for a wide range of plate dimensions. Thermo-elasto-plastic analysis was carried out for 304L stainless steel plates during autogenous TIG welding employing double ellipsoidal heat source. The simulated thermal cycles were validated by measuring thermal cycles using thermocouples at predetermined positions, and the simulated distortion values were validated by measuring distortion using vertical height gauge for three cases. There was a good agreement between the model predictions and the measured values. Then, a multilayer feed-forward back propagation neural network has been developed using the numerically simulated data. Artificial neural network model developed in the present study predicted the angular distortion accurately.

Fuzzy logic modeling of the resistivity parameter and topography features for aquifer assessment in hydrogeological investigation of a crystalline basement complex

NASA Astrophysics Data System (ADS)

Adabanija, M. A.; Omidiora, E. O.; Olayinka, A. I.

2008-05-01

A linguistic fuzzy logic system (LFLS)-based expert system model has been developed for the assessment of aquifers for the location of productive water boreholes in a crystalline basement complex. The model design employed a multiple input/single output (MISO) approach with geoelectrical parameters and topographic features as input variables and control crisp value as the output. The application of the method to the data acquired in Khondalitic terrain, a basement complex in Vizianagaram District, south India, shows that potential groundwater resource zones that have control output values in the range 0.3295-0.3484 have a yield greater than 6,000 liters per hour (LPH). The range 0.3174-0.3226 gives a yield less than 4,000 LPH. The validation of the control crisp value using data acquired from Oban Massif, a basement complex in southeastern Nigeria, indicates a yield less than 3,000 LPH for control output values in the range 0.2938-0.3065. This validation corroborates the ability of control output values to predict a yield, thereby vindicating the applicability of linguistic fuzzy logic system in siting productive water boreholes in a basement complex.

NT-proBNP Predicts All-Cause Mortality in a Population of Insurance Applicants, Follow-up Analysis and Further Observations.

PubMed

Fulks, Michael; Kaufman, Valerie; Clark, Michael; Stout, Robert L

2017-01-01

- Further refine the independent value of NT-proBNP, accounting for the impact of other test results, in predicting all-cause mortality for individual life insurance applicants with and without heart disease. - Using the Social Security Death Master File and multivariate analysis, relative mortality was determined for 245,322 life insurance applicants ages 50 to 89 tested for NT-proBNP (almost all based on age and policy amount) along with other laboratory tests and measurement of blood pressure and BMI. - NT-proBNP values ≤75 pg/mL included the majority of applicants denying heart disease and had the lowest risk, while values >500 pg/mL for females and >300 pg/mL for males had very high relative risk. Those admitting to heart disease had a higher mortality risk for each band of NT-proBNP relative to those denying heart disease but had a similar and equally predictive risk curve. - NT-proBNP is a strong independent predictor of all-cause mortality in the absence or presence of known heart disease but the range of values associated with increased risk varies by sex.

Sweat loss prediction using a multi-model approach

NASA Astrophysics Data System (ADS)

Xu, Xiaojiang; Santee, William R.

2011-07-01

A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.

Labor Supply and Consumption of Food in a Closed Economy under a Range of Fixed- and Random-Ratio Schedules: Tests of Unit Price

ERIC Educational Resources Information Center

Madden, Gregory J.; Dake, Jamie M.; Mauel, Ellie C.; Rowe, Ryan R.

2005-01-01

The behavioral economic concept of unit price predicts that consumption and response output (labor supply) are determined by the unit price at which a good is available regardless of the value of the cost and benefit components of the unit price ratio. Experiment 1 assessed 4 pigeons' consumption and response output at a range of unit prices. In…

Creatinine measurement on dry blood spot sample for chronic kidney disease screening.

PubMed

Silva, Alan Castro Azevedo E; Gómez, Juan Fidel Bencomo; Lugon, Jocemir Ronaldo; Graciano, Miguel Luis

2016-03-01

Chronic kidney disease (CKD) screening is advisable due to its high morbidity and mortality and is usually performed by sampling blood and urine. Here we present an innovative and simpler method, by measuring creatinine on a dry blood spot on filter paper. One-hundred and six individuals at high risk for CKD were enrolled. The creatinine values obtained using both tests and the demographic data of each participant allowed us to determinate the eGFR. The adopted cutoff for CKD was an eGFR < 60 ml/min. Mean age was 57 ± 12 years, 74% were female, 40% white, and 60% non-white. Seventy-six percent were hypertensive, 30% diabetic, 37% had family history of CKD, and 22% of smoking. The BMI was 29.5 ± 6.9 kg/m2, median systolic blood pressure was 125 mmHg (IQR 120-140 mmHg) and median diastolic blood pressure was 80 mmHg (IQR 70-80 mmHg). According to MDRD equation, sensitivity was 96%, specificity 55%, predictive positive value 96%, predictive negative value 55% and accuracy 92%. By the CKD-EPI equation the sensitivity was 94%, specificity 55%, predictive positive value 94%, predictive negative value 55% and accuracy 90%. A Bland and Altman analysis showed a relatively narrow range of creatinine values differences (+ 0.68mg/dl to -0.55mg/dl) inside the ± 1.96 SD, without systematic differences. Measurement of creatinine on dry blood sample is an easily feasible non-invasive diagnostic test with good accuracy that may be useful to screen chronic kidney disease.

Differentiation of benign from malignant liver masses with Acoustic Radiation Force Impulse technique.

PubMed

Yu, Hojun; Wilson, Stephanie R

2011-12-01

The objective of the study was to determine the performance of Acoustic Radiation Force Impulse (ARFI) imaging to differentiate benign from malignant liver masses, both of hepatocellular origin and metastases, by quantification of their stiffness. This study has institutional review board approval and informed consent. Eighty-nine patients (42 female and 47 male patients) with 105 liver masses had ARFI evaluation on ultrasound, S2000 (Siemens, Mountain View, Calif). Mean age of the patients was 53.67 years (range, 27-83 years). Mean diameter of the masses was 2.77 cm (range, 1.0-13.0 cm). Final diagnoses, confirmed by imaging on contrast-enhanced computed tomography, magnetic resonance, or ultrasound or biopsy, include hepatocellular carcinoma (n = 28), metastasis (n = 13), hemangioma (n = 35), focal nodular hyperplasia (n = 15), focal fat sparing (n = 8), focal fat deposit (n = 4), and adenoma (n = 2). Receiver operating characteristic analysis was performed to evaluate the diagnostic accuracy of the ARFI measurement and to extract the optimal cutoff values in the differentiation of benign from malignant disease. Acoustic Radiation Force Impulse values showed a statistically significant difference between benign (1.73 [SD, 0.8] m/sec) and malignant masses (2.57 [SD, 1.01] m/sec) (P < 0.001). However, the area under the receiver operating characteristic curve was 0.744, suggesting only fair accuracy. For differentiation of malignant from benign masses, the sensitivity, specificity, positive predictive value, and negative predictive value were 68% (28/41), 69% (44/64), 58% (28/48), and 77% (44/57), respectively, when 1.9 m/sec was chosen as a cutoff value, reflective of a wide variation of ARFI values in each diagnosis. For differentiation of metastasis from benign masses, sensitivity, specificity, positive predictive value, and NPV were 69% (9/13), 89% (57/64), 56% (9/16), and 93% (57/61), respectively, when 2.72 m/sec was chosen as a cutoff value. Acoustic Radiation Force Impulse measurement may be helpful to differentiate benign masses from metastases, in particular. Otherwise, ARFI measurements alone do not differentiate benign and malignant masses because of variations in stiffness of all types of masses.

CO32- concentration and pCO2 thresholds for calcification and dissolution on the Molokai reef flat, Hawaii

USGS Publications Warehouse

Yates, K.K.; Halley, R.B.

2006-01-01

The severity of the impact of elevated atmospheric pCO2 to coral reef ecosystems depends, in part, on how sea-water pCO2 affects the balance between calcification and dissolution of carbonate sediments. Presently, there are insufficient published data that relate concentrations of pCO 2 and CO32- to in situ rates of reef calcification in natural settings to accurately predict the impact of elevated atmospheric pCO2 on calcification and dissolution processes. Rates of net calcification and dissolution, CO32- concentrations, and pCO2 were measured, in situ, on patch reefs, bare sand, and coral rubble on the Molokai reef flat in Hawaii. Rates of calcification ranged from 0.03 to 2.30 mmol CaCO3 m-2 h-1 and dissolution ranged from -0.05 to -3.3 mmol CaCO3 m-2 h-1. Calcification and dissolution varied diurnally with net calcification primarily occurring during the day and net dissolution occurring at night. These data were used to calculate threshold values for pCO2 and CO32- at which rates of calcification and dissolution are equivalent. Results indicate that calcification and dissolution are linearly correlated with both CO32- and pCO2. Threshold pCO2 and CO32- values for individual substrate types showed considerable variation. The average pCO2 threshold value for all substrate types was 654??195 ??atm and ranged from 467 to 1003 ??atm. The average CO32- threshold value was 152??24 ??mol kg-1, ranging from 113 to 184 ??mol kg-1. Ambient seawater measurements of pCO2 and CO32- indicate that CO32- and pCO2 threshold values for all substrate types were both exceeded, simultaneously, 13% of the time at present day atmospheric pCO2 concentrations. It is predicted that atmospheric pCO2 will exceed the average pCO2 threshold value for calcification and dissolution on the Molokai reef flat by the year 2100.

Predictions of H-mode performance in ITER

NASA Astrophysics Data System (ADS)

Budny, Robert

2008-11-01

Time-dependent integrated predictions of performance metrics such as the fusion power PDT, QDT≡ PDT/Pext, and alpha profiles are presented. The PTRANSP [1] code is used, along with GLF23 to predict plasma profiles, NUBEAM for NNBI and alpha heating, TORIC for ICRH, and TORAY for ECRH. Effects of sawteeth mixing, beam steering, beam shine-through, radiation loss, ash accumulation, and toroidal rotation are included. A total heating of Pext=73MW is assumed to achieve H-mode during the density and current ramp-up phase. Various mixes of NNBI, ICRH, and ECRH heating schemes are compared. After steady state conditions are achieved, Pext is stepped down to lower values to explore high QDT. Physics and computation uncertainties lead to ranges in predictions for PDT and QDT. Physics uncertainties include the L->H and H->L threshold powers, pedestal height, impurity and ash transport, and recycling. There are considerably more uncertainties predicting the peak value for QDT than for PDT. [0pt] [1] R.V. Budny, R. Andre, G. Bateman, F. Halpern, C.E. Kessel, A. Kritz, and D. McCune, Nuclear Fusion 48 (2008) 075005.

A computer-based matrix for rapid calculation of pulmonary hemodynamic parameters in congenital heart disease

PubMed Central

Lopes, Antonio Augusto; dos Anjos Miranda, Rogério; Gonçalves, Rilvani Cavalcante; Thomaz, Ana Maria

2009-01-01

BACKGROUND: In patients with congenital heart disease undergoing cardiac catheterization for hemodynamic purposes, parameter estimation by the indirect Fick method using a single predicted value of oxygen consumption has been a matter of criticism. OBJECTIVE: We developed a computer-based routine for rapid estimation of replicate hemodynamic parameters using multiple predicted values of oxygen consumption. MATERIALS AND METHODS: Using Microsoft® Excel facilities, we constructed a matrix containing 5 models (equations) for prediction of oxygen consumption, and all additional formulas needed to obtain replicate estimates of hemodynamic parameters. RESULTS: By entering data from 65 patients with ventricular septal defects, aged 1 month to 8 years, it was possible to obtain multiple predictions for oxygen consumption, with clear between-age groups (P <.001) and between-methods (P <.001) differences. Using these predictions in the individual patient, it was possible to obtain the upper and lower limits of a likely range for any given parameter, which made estimation more realistic. CONCLUSION: The organized matrix allows for rapid obtainment of replicate parameter estimates, without error due to exhaustive calculations. PMID:19641642

Statistical physics in foreign exchange currency and stock markets

NASA Astrophysics Data System (ADS)

Ausloos, M.

2000-09-01

Problems in economy and finance have attracted the interest of statistical physicists all over the world. Fundamental problems pertain to the existence or not of long-, medium- or/and short-range power-law correlations in various economic systems, to the presence of financial cycles and on economic considerations, including economic policy. A method like the detrended fluctuation analysis is recalled emphasizing its value in sorting out correlation ranges, thereby leading to predictability at short horizon. The ( m, k)-Zipf method is presented for sorting out short-range correlations in the sign and amplitude of the fluctuations. A well-known financial analysis technique, the so-called moving average, is shown to raise questions to physicists about fractional Brownian motion properties. Among spectacular results, the possibility of crash predictions has been demonstrated through the log-periodicity of financial index oscillations.

Prediction of the fertility of stallion frozen-thawed semen using a combination of computer-assisted motility analysis, microscopical observation and flow cytometry.

PubMed

Battut, I Barrier; Kempfer, A; Lemasson, N; Chevrier, L; Camugli, S

2017-07-15

Spermatozoa from some stallions do not maintain an acceptable fertility after freezing and thawing. The selection of frozen ejaculates that would be suitable for insemination is mainly based on post-thaw motility, but the prediction of fertility remains limited. A recent study in our laboratory has enabled the determination of a new protocol for the evaluation of fresh stallion semen, combining microscopical observation, computer-assisted motility analysis and flow cytometry, and providing a high level of fertility prediction. The purpose of the present experiment was to perform similar investigations on frozen semen. A panel of tests evaluating a large number of compartments or functions of the spermatozoa was applied to a population of 42 stallions, 33 of which showing widely differing fertilities (17-67% pregnancy rate per cycle [PRC]). Variability was evaluated by calculating the coefficient of variation (CV=SD/mean) and the intra-class correlation or "repeatability" for each variable. For paired variables, mean within-stallion CV% was significantly lower than between-stallion CV%, which was significantly lower than total CV%. Within-ejaculate repeatability, determined by analysing 6 straws for each of 10 ejaculates, ranged from 0.60 to 0.97. Within-stallion repeatability, determined by analysing at least 5 ejaculates for each of 38 stallions, ranged from 0.12 to 0.95. Principal component regression using a combination of 25 variables, including motility, morphology, viability, oxidation level, acrosome integrity, DNA integrity and hypoosmotic resistance, accounted for 94.5% of the variability regarding fertility, and was used to calculate a prediction of the PRC with a mean standard deviation of 2.2. The difference between the observed PRC and the calculated value ranged from -3.4 to 4.2. The 90% confidence interval (90CI) for the prediction of the PRC for the stallions of unknown fertility ranged from 8 to 30 (mean = 17). The best-fit model using only motility variables, evaluated after 10 min at 36 °C and 2 h at 36 °C or room temperature, accounted for only 74.2% of the variability. The difference between the observed PRC and the calculated value ranged from -7.2 to 14. The 90CI for the prediction of the PRC for the stallions of unknown fertility ranged from 23 to 48 (mean = 33). In conclusion, this study demonstrated that an appropriate combination of computer-assisted motility analysis, microscopical observation and flow cytometry can provide a higher prediction of fertility than motility analysis alone. Copyright © 2017 Elsevier Inc. All rights reserved.

Prediction of transmission loss through an aircraft sidewall using statistical energy analysis

NASA Astrophysics Data System (ADS)

Ming, Ruisen; Sun, Jincai

1989-06-01

The transmission loss of randomly incident sound through an aircraft sidewall is investigated using statistical energy analysis. Formulas are also obtained for the simple calculation of sound transmission loss through single- and double-leaf panels. Both resonant and nonresonant sound transmissions can be easily calculated using the formulas. The formulas are used to predict sound transmission losses through a Y-7 propeller airplane panel. The panel measures 2.56 m x 1.38 m and has two windows. The agreement between predicted and measured values through most of the frequency ranges tested is quite good.

Prognostic Value of the Thrombolysis in Myocardial Infarction Risk Score in ST-Elevation Myocardial Infarction Patients With Left Ventricular Dysfunction (from the EPHESUS Trial).

PubMed

Popovic, Batric; Girerd, Nicolas; Rossignol, Patrick; Agrinier, Nelly; Camenzind, Edoardo; Fay, Renaud; Pitt, Bertram; Zannad, Faiez

2016-11-15

The Thrombolysis in Myocardial Infarction (TIMI) risk score remains a robust prediction tool for short-term and midterm outcome in the patients with ST-elevation myocardial infarction (STEMI). However, the validity of this risk score in patients with STEMI with reduced left ventricular ejection fraction (LVEF) remains unclear. A total of 2,854 patients with STEMI with early coronary revascularization participating in the randomized EPHESUS (Epleronone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study) trial were analyzed. TIMI risk score was calculated at baseline, and its predictive value was evaluated using C-indexes from Cox models. The increase in reclassification of other variables in addition to TIMI score was assessed using the net reclassification index. TIMI risk score had a poor predictive accuracy for all-cause mortality (C-index values at 30 days and 1 year ≤0.67) and recurrent myocardial infarction (MI; C-index values ≤0.60). Among TIMI score items, diabetes/hypertension/angina, heart rate >100 beats/min, and systolic blood pressure <100 mm Hg were inconsistently associated with survival, whereas none of the TIMI score items, aside from age, were significantly associated with MI recurrence. Using a constructed predictive model, lower LVEF, lower estimated glomerular filtration rate (eGFR), and previous MI were significantly associated with all-cause mortality. The predictive accuracy of this model, which included LVEF and eGFR, was fair for both 30-day and 1-year all-cause mortality (C-index values ranging from 0.71 to 0.75). In conclusion, TIMI risk score demonstrates poor discrimination in predicting mortality or recurrent MI in patients with STEMI with reduced LVEF. LVEF and eGFR are major factors that should not be ignored by predictive risk scores in this population. Copyright © 2016 Elsevier Inc. All rights reserved.

Automated chart review utilizing natural language processing algorithm for asthma predictive index.

PubMed

Kaur, Harsheen; Sohn, Sunghwan; Wi, Chung-Il; Ryu, Euijung; Park, Miguel A; Bachman, Kay; Kita, Hirohito; Croghan, Ivana; Castro-Rodriguez, Jose A; Voge, Gretchen A; Liu, Hongfang; Juhn, Young J

2018-02-13

Thus far, no algorithms have been developed to automatically extract patients who meet Asthma Predictive Index (API) criteria from the Electronic health records (EHR) yet. Our objective is to develop and validate a natural language processing (NLP) algorithm to identify patients that meet API criteria. This is a cross-sectional study nested in a birth cohort study in Olmsted County, MN. Asthma status ascertained by manual chart review based on API criteria served as gold standard. NLP-API was developed on a training cohort (n = 87) and validated on a test cohort (n = 427). Criterion validity was measured by sensitivity, specificity, positive predictive value and negative predictive value of the NLP algorithm against manual chart review for asthma status. Construct validity was determined by associations of asthma status defined by NLP-API with known risk factors for asthma. Among the eligible 427 subjects of the test cohort, 48% were males and 74% were White. Median age was 5.3 years (interquartile range 3.6-6.8). 35 (8%) had a history of asthma by NLP-API vs. 36 (8%) by abstractor with 31 by both approaches. NLP-API predicted asthma status with sensitivity 86%, specificity 98%, positive predictive value 88%, negative predictive value 98%. Asthma status by both NLP and manual chart review were significantly associated with the known asthma risk factors, such as history of allergic rhinitis, eczema, family history of asthma, and maternal history of smoking during pregnancy (p value < 0.05). Maternal smoking [odds ratio: 4.4, 95% confidence interval 1.8-10.7] was associated with asthma status determined by NLP-API and abstractor, and the effect sizes were similar between the reviews with 4.4 vs 4.2 respectively. NLP-API was able to ascertain asthma status in children mining from EHR and has a potential to enhance asthma care and research through population management and large-scale studies when identifying children who meet API criteria.

Application of reflectance colorimeter measurements and infrared spectroscopy methods to rapid and nondestructive evaluation of carotenoids content in apricot (Prunus armeniaca L.).

PubMed

Ruiz, David; Reich, Maryse; Bureau, Sylvie; Renard, Catherine M G C; Audergon, Jean-Marc

2008-07-09

The importance of carotenoid content in apricot (Prunus armeniaca L.) is recognized not only because of the color that they impart but also because of their protective activity against human diseases. Current methods to assess carotenoid content are time-consuming, expensive, and destructive. In this work, the application of rapid and nondestructive methods such as colorimeter measurements and infrared spectroscopy has been evaluated for carotenoid determination in apricot. Forty apricot genotypes covering a wide range of peel and flesh colors have been analyzed. Color measurements on the skin and flesh ( L*, a*, b*, hue, chroma, and a*/ b* ratio) as well as Fourier transform near-infrared spectroscopy (FT-NIR) on intact fruits and Fourier transform mid-infrared spectroscopy (FT-MIR) on ground flesh were correlated with the carotenoid content measured by high-performance liquid chromatography. A high variability in color values and carotenoid content was observed. Partial least squares regression analyses between beta-carotene content and provitamin A activity and color measurements showed a high fit in peel, flesh, and edible apricot portion (R(2) ranged from 0.81 to 0.91) and low prediction error. Regression equations were developed for predicting carotenoid content by using color values, which appeared as a simple, rapid, reliable, and nondestructive method. However, FT-NIR and FT-MIR models showed very low R(2) values and very high prediction errors for carotenoid content.

Parameterizing the binding properties of dissolved organic matter with default values skews the prediction of copper solution speciation and ecotoxicity in soil.

PubMed

Djae, Tanalou; Bravin, Matthieu N; Garnier, Cédric; Doelsch, Emmanuel

2017-04-01

Parameterizing speciation models by setting the percentage of dissolved organic matter (DOM) that is reactive (% r-DOM) toward metal cations at a single 65% default value is very common in predictive ecotoxicology. The authors tested this practice by comparing the free copper activity (pCu 2+  = -log 10 [Cu 2+ ]) measured in 55 soil sample solutions with pCu 2+ predicted with the Windermere humic aqueous model (WHAM) parameterized by default. Predictions of Cu toxicity to soil organisms based on measured or predicted pCu 2+ were also compared. Default WHAM parameterization substantially skewed the prediction of measured pCu 2+ by up to 2.7 pCu 2+ units (root mean square residual = 0.75-1.3) and subsequently the prediction of Cu toxicity for microbial functions, invertebrates, and plants by up to 36%, 45%, and 59% (root mean square residuals ≤9 %, 11%, and 17%), respectively. Reparametrizing WHAM by optimizing the 2 DOM binding properties (i.e., % r-DOM and the Cu complexation constant) within a physically realistic value range much improved the prediction of measured pCu 2+ (root mean square residual = 0.14-0.25). Accordingly, this WHAM parameterization successfully predicted Cu toxicity for microbial functions, invertebrates, and plants (root mean square residual ≤3.4%, 4.4%, and 5.8%, respectively). Thus, it is essential to account for the real heterogeneity in DOM binding properties for relatively accurate prediction of Cu speciation in soil solution and Cu toxic effects on soil organisms. Environ Toxicol Chem 2017;36:898-905. © 2016 SETAC. © 2016 SETAC.

Predicting the effect of cytochrome P450 inhibitors on substrate drugs: analysis of physiologically based pharmacokinetic modeling submissions to the US Food and Drug Administration.

PubMed

Wagner, Christian; Pan, Yuzhuo; Hsu, Vicky; Grillo, Joseph A; Zhang, Lei; Reynolds, Kellie S; Sinha, Vikram; Zhao, Ping

2015-01-01

The US Food and Drug Administration (FDA) has seen a recent increase in the application of physiologically based pharmacokinetic (PBPK) modeling towards assessing the potential of drug-drug interactions (DDI) in clinically relevant scenarios. To continue our assessment of such approaches, we evaluated the predictive performance of PBPK modeling in predicting cytochrome P450 (CYP)-mediated DDI. This evaluation was based on 15 substrate PBPK models submitted by nine sponsors between 2009 and 2013. For these 15 models, a total of 26 DDI studies (cases) with various CYP inhibitors were available. Sponsors developed the PBPK models, reportedly without considering clinical DDI data. Inhibitor models were either developed by sponsors or provided by PBPK software developers and applied with minimal or no modification. The metric for assessing predictive performance of the sponsors' PBPK approach was the R predicted/observed value (R predicted/observed = [predicted mean exposure ratio]/[observed mean exposure ratio], with the exposure ratio defined as [C max (maximum plasma concentration) or AUC (area under the plasma concentration-time curve) in the presence of CYP inhibition]/[C max or AUC in the absence of CYP inhibition]). In 81 % (21/26) and 77 % (20/26) of cases, respectively, the R predicted/observed values for AUC and C max ratios were within a pre-defined threshold of 1.25-fold of the observed data. For all cases, the R predicted/observed values for AUC and C max were within a 2-fold range. These results suggest that, based on the submissions to the FDA to date, there is a high degree of concordance between PBPK-predicted and observed effects of CYP inhibition, especially CYP3A-based, on the exposure of drug substrates.

Computational alloy design of (Co1-xNix)88Zr7B4Cu1 nanocomposite soft magnets

NASA Astrophysics Data System (ADS)

Dong, B.; Healy, J.; Lan, S.; Daniil, M.; Willard, M. A.

2018-05-01

The dependence of coercivity on composition is an important factor for establishing optimized soft magnetic properties. In this study, we have used the random anisotropy and coherent rotation models to estimate the variation of coercivity with composition in (Co1-xNix)88Zr7B4Cu1 nanocomposite alloys. Our calculations that the magnetoelastic anisotropy contribution to coercivity dominates for Ni rich compositions (x > 0.5). A small range of compositions (0.65 < x < 0.75) is predicted to result in low values of coercivity (<10 A/m). To validate this prediction, (Co1-xNix)88Zr7B4Cu1 nanocomposites in this range were prepared by melt spinning followed by 3600 s isothermal annealing at the primary crystallization peak temperature (˜673 K). Hysteresis loops were measured using vibrating sample magnetometry at room temperature and saturation magnetostriction was measured using a strain gage based magnetostrictometer. Moderately small coercivities (30-40 A/m) and magnetostrictions (3-4 ppm) were measured at for samples with 0.685 < x < 0.725. Our measured coercivity had a minimum value of 32 A/m at x = 0.725, a shift in composition of about 5 at% in the direction of higher Ni content and without the anticipated low value of coercivity. Several reasons for the inaccuracy of this approach are described, including: ignored contributions from amorphous phase (especially in magnetoealstic anisotropy), composition segregation during crystallization leading to unpredictable compositional shifts in prediction, and the general observation that the predictability of minimum coercivity from minimal combined anisotropies has unexplained deviation even in far less complicated materials.

Bare soil respiration in a temperate climate: multiyear evaluation of a coupled CO2 transport and carbon turnover model

NASA Astrophysics Data System (ADS)

Herbst, M.; Hellebrand, H. J.; Bauer, J.; Vanderborght, J.; Vereecken, H.

2006-12-01

The modelling of soil respiration plays an important role in the prediction of climate change. Soil respiration is usually divided in autotrophic and heterotrophic fractions orginating from root respiration and microbial decomposition of soil organic carbon, respectively. We report on the coupling of a one dimensional water, heat and CO2 flux model (SOILCO2) with a model of carbon turnover (RothC) for the prediction of soil heterotrophic respiration. The coupled model was tested using soil temperature, soil moisture, and CO2 flux measurements in a bare soil experimental plot located in Bornim, Germany. A seven year record of soil and CO2 measurements covering a broad range of atmospheric and soil conditions was availabe to evaluate the model performance. After calibrating the decomposition rate constant of the humic fraction pool, the overall model performance on CO2 efflux prediction was acceptable. The root mean square error for the CO2 efflux prediction was 0.12 cm ³/cm ²/d. During the severe summer draught of 2003 very high CO2 efluxes were measured, which could not be explained by the model. Those high fluxes were attributed to a pressure pumping effect. The soil temperature dependency of CO2 production was well described by th e model, whereas the biggest opportunity for improvement is seen in a better description of the soil moisture dependency of CO2 production. The calibration of the humus decomposition rate constant revealed a value of 0.09 1/d, which is higher than the original value suggested by the RothC model developers but within the range of literature values.

Nanofluidic Digital PCR and Extended Genotyping of RAS and BRAF for Improved Selection of Metastatic Colorectal Cancer Patients for Anti-EGFR Therapies.

PubMed

Azuara, Daniel; Santos, Cristina; Lopez-Doriga, Adriana; Grasselli, Julieta; Nadal, Marga; Sanjuan, Xavier; Marin, Fátima; Vidal, Joana; Montal, Robert; Moreno, Victor; Bellosillo, Beatriz; Argiles, Guillem; Elez, Elena; Dienstmann, Rodrigo; Montagut, Clara; Tabernero, Josep; Capellá, Gabriel; Salazar, Ramon

2016-05-01

The clinical significance of low-frequent RAS pathway-mutated alleles and the optimal sensitivity cutoff value in the prediction of response to anti-EGFR therapy in metastatic colorectal cancer (mCRC) patients remains controversial. We aimed to evaluate the added value of genotyping an extended RAS panel using a robust nanofluidic digital PCR (dPCR) approach. A panel of 34 hotspots, including RAS (KRAS and NRAS exons 2/3/4) and BRAF (V600E), was analyzed in tumor FFPE samples from 102 mCRC patients treated with anti-EGFR therapy. dPCR was compared with conventional quantitative PCR (qPCR). Response rates, progression-free survival (PFS), and overall survival (OS) were correlated to the mutational status and the mutated allele fraction. Tumor response evaluations were not available in 9 patients and were excluded for response rate analysis. Twenty-two percent of patients were positive for one mutation with qPCR (mutated alleles ranged from 2.1% to 66.6%). Analysis by dPCR increased the number of positive patients to 47%. Mutated alleles for patients only detected by dPCR ranged from 0.04% to 10.8%. An inverse correlation between the fraction of mutated alleles and radiologic response was observed. ROC analysis showed that a fraction of 1% or higher of any mutated alleles offered the best predictive value for all combinations of RAS and BRAF analysis. In addition, this threshold also optimized prediction both PFS and OS. We conclude that mutation testing using an extended gene panel, including RAS and BRAF with a threshold of 1% improved prediction of response to anti-EGFR therapy. Mol Cancer Ther; 15(5); 1106-12. ©2016 AACR. ©2016 American Association for Cancer Research.

A prediction of the minke whale (Balaenoptera acutorostrata) middle-ear transfer function.

PubMed

Tubelli, Andrew A; Zosuls, Aleks; Ketten, Darlene R; Yamato, Maya; Mountain, David C

2012-11-01

The lack of baleen whale (Cetacea Mysticeti) audiograms impedes the assessment of the impacts of anthropogenic noise on these animals. Estimates of audiograms, which are difficult to obtain behaviorally or electrophysiologically for baleen whales, can be made by simulating the audiogram as a series of components representing the outer, middle, and inner ear (Rosowski, 1991; Ruggero and Temchin, 2002). The middle-ear portion of the system can be represented by the middle-ear transfer function (METF), a measure of the transmission of acoustic energy from the external ear to the cochlea. An anatomically accurate finite element model of the minke whale (Balaenoptera acutorostrata) middle ear was developed to predict the METF for a mysticete species. The elastic moduli of the auditory ossicles were measured by using nanoindentation. Other mechanical properties were estimated from experimental stiffness measurements or from published values. The METF predicted a best frequency range between approximately 30 Hz and 7.5 kHz or between 100 Hz and 25 kHz depending on stimulation location. Parametric analysis found that the most sensitive parameters are the elastic moduli of the glove finger and joints and the Rayleigh damping stiffness coefficient β. The predicted hearing range matches well with the vocalization range.

Predictability of short-range forecasting: a multimodel approach

NASA Astrophysics Data System (ADS)

García-Moya, Jose-Antonio; Callado, Alfons; Escribà, Pau; Santos, Carlos; Santos-Muñoz, Daniel; Simarro, Juan

2011-05-01

Numerical weather prediction (NWP) models (including mesoscale) have limitations when it comes to dealing with severe weather events because extreme weather is highly unpredictable, even in the short range. A probabilistic forecast based on an ensemble of slightly different model runs may help to address this issue. Among other ensemble techniques, Multimodel ensemble prediction systems (EPSs) are proving to be useful for adding probabilistic value to mesoscale deterministic models. A Multimodel Short Range Ensemble Prediction System (SREPS) focused on forecasting the weather up to 72 h has been developed at the Spanish Meteorological Service (AEMET). The system uses five different limited area models (LAMs), namely HIRLAM (HIRLAM Consortium), HRM (DWD), the UM (UKMO), MM5 (PSU/NCAR) and COSMO (COSMO Consortium). These models run with initial and boundary conditions provided by five different global deterministic models, namely IFS (ECMWF), UM (UKMO), GME (DWD), GFS (NCEP) and CMC (MSC). AEMET-SREPS (AE) validation on the large-scale flow, using ECMWF analysis, shows a consistent and slightly underdispersive system. For surface parameters, the system shows high skill forecasting binary events. 24-h precipitation probabilistic forecasts are verified using an up-scaling grid of observations from European high-resolution precipitation networks, and compared with ECMWF-EPS (EC).

Evaluation of an artificial intelligence program for estimating occupational exposures.

PubMed

Johnston, Karen L; Phillips, Margaret L; Esmen, Nurtan A; Hall, Thomas A

2005-03-01

Estimation and Assessment of Substance Exposure (EASE) is an artificial intelligence program developed by UK's Health and Safety Executive to assess exposure. EASE computes estimated airborne concentrations based on a substance's vapor pressure and the types of controls in the work area. Though EASE is intended only to make broad predictions of exposure from occupational environments, some occupational hygienists might attempt to use EASE for individual exposure characterizations. This study investigated whether EASE would accurately predict actual sampling results from a chemical manufacturing process. Personal breathing zone time-weighted average (TWA) monitoring data for two volatile organic chemicals--a common solvent (toluene) and a specialty monomer (chloroprene)--present in this manufacturing process were compared to EASE-generated estimates. EASE-estimated concentrations for specific tasks were weighted by task durations reported in the monitoring record to yield TWA estimates from EASE that could be directly compared to the measured TWA data. Two hundred and six chloroprene and toluene full-shift personal samples were selected from eight areas of this manufacturing process. The Spearman correlation between EASE TWA estimates and measured TWA values was 0.55 for chloroprene and 0.44 for toluene, indicating moderate predictive values for both compounds. For toluene, the interquartile range of EASE estimates at least partially overlapped the interquartile range of the measured data distributions in all process areas. The interquartile range of EASE estimates for chloroprene fell above the interquartile range of the measured data distributions in one process area, partially overlapped the third quartile of the measured data in five process areas and fell within the interquartile range in two process areas. EASE is not a substitute for actual exposure monitoring. However, EASE can be used in conditions that cannot otherwise be sampled and in preliminary exposure assessment if it is recognized that the actual interquartile range could be much wider and/or offset by a factor of 10 or more.

Evolution of Mobil`s methods to evaluate exploration and producing opportunities

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

Gaynor, C.B.; Cook, D.M. Jr.

1996-08-01

Over the past decade, Mobil has changed significantly in size, structure and focus to improve profitability. Concurrently, work processes and methodologies have been modified to improve resource utilization and opportunity selection. The key imperative has been recognition of the full range of hydrocarbon volume uncertainty, its risk and value. Exploration has focussed on increasing success through improved geotechnical estimates and demonstrating value addition. For Producing, the important tasks: (1) A centralized Exploration and Producing team was formed to help ensure an integrated, consistent worldwide approach to prospect and field assessments. Monte Carlo simulation was instituted to recognize probability-weighted ranges ofmore » possible outcomes for prospects and fields, and hydrocarbon volume category definitions were standardized. (2) Exploration instituted a global Prospect Inventory, tracking wildcat predictions vs. results. Performance analyses led to initiatives to improve the quality and consistency of assessments. Process improvement efforts included the use of multidisciplinary teams and peer reviews. Continued overestimates of hydrocarbon volumes prompted methodology changes such as the use of {open_quotes}reality checks{close_quotes} and log-normal distributions. The communication of value predictions and additions became paramount. (3) Producing now recognizes the need for Exploration`s commercial discoveries and new Producing ventures, notwithstanding the associated risk. Multi-disciplinary teams of engineers and geoscientists work on post-discovery assessments to optimize field development and maximize the value of opportunities. Mobil now integrates volume and risk assessment with correlative future capital investment programs to make proactive strategic choices to maximize shareholder value.« less

Shear wave elastography of placenta: in vivo quantitation of placental elasticity in preeclampsia

PubMed Central

Kılıç, Fahrettin; Kayadibi, Yasemin; Yüksel, Mehmet Aytaç; Adaletli, İbrahim; Ustabaşıoğlu, Fethi Emre; Öncül, Mahmut; Madazlı, Rıza; Yılmaz, Mehmet Halit; Mihmanlı, İsmail; Kantarcı, Fatih

2015-01-01

PURPOSE We aimed to evaluate the utility of shear wave elastography (SWE) for assessing the placenta in preeclampsia disease. METHODS A total of 50 pregnant women in the second or third trimester (23 preeclampsia patients and 27 healthy control subjects) were enrolled in the study. Obstetrical grayscale and Doppler ultrasonography, SWE findings of placenta, and prenatal/postnatal clinical data were analyzed and the best SWE cutoff value which represents the diagnosis of preeclampsia was determined. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy of preeclampsia were calculated based on SWE measurements. RESULTS Mean stiffness values were much higher in preeclamptic placentas in all regions and layers than in normal controls. The most significant difference was observed in the central placental area facing the fetus where the umbilical cord inserts, with a median of 21 kPa (range, 3–71 kPa) for preeclampsia and 4 kPa (range, 1.5–14 kPa) for the control group (P < 0.01). The SWE data showed a moderate correlation with the uterine artery resistivity and pulsatility indices. The cutoff value maximizing the accuracy of diagnosis was 7.35 kPa (area under curve, 0.895; 95% confidence interval, 0.791–0.998); sensitivity, specificity, PPV, NPV, and accuracy were 90%, 86%, 82%, 92%, and 88%, respectively. CONCLUSION Stiffness of the placenta is significantly higher in patients with preeclampsia. SWE appears to be an assistive diagnostic technique for placenta evaluation in preeclampsia. PMID:25858523

[Validation of the Eating Attitudes Test as a screening instrument for eating disorders in general population].

PubMed

Peláez-Fernández, María Angeles; Ruiz-Lázaro, Pedro Manuel; Labrador, Francisco Javier; Raich, Rosa María

2014-02-20

To validate the best cut-off point of the Eating Attitudes Test (EAT-40), Spanish version, for the screening of eating disorders (ED) in the general population. This was a transversal cross-sectional study. The EAT-40 Spanish version was administered to a representative sample of 1.543 students, age range 12 to 21 years, in the Region of Madrid. Six hundred and two participants (probable cases and a random sample of controls) were interviewed. The best diagnostic prediction was obtained with a cut-off point of 21, with sensitivity: 88.2%; specificity: 62.1%; positive predictive value: 17.7%; negative predictive value: 62.1%. Use of a cut-off point of 21 is recommended in epidemiological studies of eating disorders in the Spanish general population. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Reference values for clinical laboratory parameters in young adults in Maputo, Mozambique.

PubMed

Tembe, Nelson; Joaquim, Orvalho; Alfai, Eunice; Sitoe, Nádia; Viegas, Edna; Macovela, Eulalia; Gonçalves, Emilia; Osman, Nafissa; Andersson, Sören; Jani, Ilesh; Nilsson, Charlotta

2014-01-01

Clinical laboratory reference values from North American and European populations are currently used in most Africans countries due to the absence of locally derived reference ranges, despite previous studies reporting significant differences between populations. Our aim was to define reference ranges for both genders in 18 to 24 year-old Mozambicans in preparation for clinical vaccine trials. A cross-sectional study including 257 volunteers (102 males and 155 females) between 18 and 24 years was performedat a youth clinic in Maputo, Mozambique. All volunteers were clinically healthy and human immunodeficiency virus, Hepatitis B virus and syphilis negative.Median and 95% reference ranges were calculated for immunological, hematological and chemistry parameters. Ranges were compared with those reported based on populations in other African countries and the US. The impact of applying US NIH Division of AIDS (DAIDS) toxicity tables was assessed. The immunology ranges were comparable to those reported for the US and western Kenya.There were significant gender differences in CD4+ T cell values 713 cells/µL in males versus 824 cells/µL in females (p<0.0001). Hematologic values differed from the US values but were similar to reports of populations in western Kenya and Uganda. The lower and upper limits of the ranges for hemoglobin, hematocrit, red blood cells, white blood cells and lymphocytes were somewhat lower than those from these African countries. The chemistry values were comparable to US values, with few exceptions. The upper limits for ALT, AST, bilirubin, cholesterol and triglycerides were higher than those from the US. DAIDStables for adverse events predicted 297 adverse events and 159 (62%) of the volunteers would have been excluded. This study is the first to determine normal laboratory parameters in Mozambique. Our results underscore the necessity of establishing region-specific clinical reference ranges for proper patient management and safe conduct of clinical trials.

Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients.

PubMed

Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

2016-01-01

Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30-70% range, with no significant difference among models ( P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others ( P > 0.05). This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others.

A fluctuating plume dispersion model for the prediction of odour-impact frequencies from continuous stationary sources

NASA Astrophysics Data System (ADS)

Mussio, P.; Gnyp, A. W.; Henshaw, P. F.

A fluctuating plume dispersion model has been developed to facilitate the prediction of odour-impact frequencies in the communities surrounding elevated point sources. The model was used to predict the frequencies of occurrence of odours of various magnitudes for 1 h periods. In addition, the model predicted the maximum odour level. The model was tested with an extensive set of data collected in the residential areas surrounding the paint shop of an automotive assembly plant. Most of the perceived odours in the vicinity of the 64, 46 m high stacks ranged between 2 and 7 odour units and generally persisted for less than 30 s. Ninety-eight different field determinations of odour impact frequencies within 1 km of the plant were conducted during the course of the study. To simplify evaluation, the frequencies of occurrence of different odour levels were summed to give the total frequency of occurrence of all readily detectable (>2 OU) odours. The model provided excellent simulation of the total frequencies of occurrence where the odour was frequent (i.e . readily detectable more than 30% of the time). At lower frequencies of occurrence the model prediction was poor. The stability class did not seem to affect the model's ability to predict field frequency values. However, the model provided excellent predictions of the maximum odour levels without being sensitive to either stability class or distance from the source. Ninety-five percent of the predicted maximum values were within a factor of two of the measured field maximum values.

Relation of electrochemical potentials and iron content to ground-water flow patterns

USGS Publications Warehouse

Back, William; Barnes, Ivan

1965-01-01

This study was undertaken to develop means of measuring oxidation potentials in aquifer systems and to use the measured values in interpreting the behavior of iron in ground water. Anne Arundel County, Md., was selected as the area of study because of the wide range of concentration of iron-nearly zero to about 35 ppm-in the ground water and the rather complete information on the geology and hydrology. The regional geology consists of coastal plain sediments ranging in age from Early Cretaceous through the Recent. Most of the pH and oxidation-potential measurements were made in nonmarine Cretaceous deposits, only a few in the marine Eocene. Iron-bearing minerals in the area are primarily hematite or limonite and glauconite with a small amount of pyrite. Equipment was developed that permits the measurement of oxidation potentials by use of saturated calomel and platinum electrodes in ground-water samples uncontaminated by oxygen of the atmosphere. Measured Eh values range from about +700 mv to -40 mv. Approximately 2 to 3 hours are required to measure a stable or nearly stable oxidation potential. The mineralogy and organic content of the deposits and the ground-water flow pattern are the primary controls on the oxidation potential and pH of the water. A correlation exists between the oxidation potential and the concentration of iron in ground water; the higher concentrations occur in waters with the lowest values of Eh. The concentration of iron in the water tested shows little correlation with the pH of the water. The highest oxidation potentials were measured in water produced from shallow wells and those wells in recharge areas. The lowest potentials were measured farthest downgradient in water associated with gray and green sediments. The Eh values measured in the field are between values predicted from the solubility of Fe(OH)2(c) and values predicted from the solubility of hematite.

Reality Check Algorithm for Complex Sources in Early Warning

NASA Astrophysics Data System (ADS)

Karakus, G.; Heaton, T. H.

2013-12-01

In almost all currently operating earthquake early warning (EEW) systems, presently available seismic data are used to predict future shaking. In most cases, location and magnitude are estimated. We are developing an algorithm to test the goodness of that prediction in real time. We monitor envelopes of acceleration, velocity, and displacement; if they deviate significantly from the envelope predicted by Cua's envelope gmpe's then we declare an overfit (perhaps false alarm) or an underfit (possibly a larger event has just occurred). This algorithm is designed to provide a robust measure and to work as quickly as possible in real-time. We monitor the logarithm of the ratio between the envelopes of the ongoing observed event and the envelopes derived from the predicted envelopes of channels of ground motion of the Virtual Seismologist (VS) (Cua, G. and Heaton, T.). Then, we recursively filter this result with a simple running median (de-spiking operator) to minimize the effect of one single high value. Depending on the result of the filtered value we make a decision such as if this value is large enough (e.g., >1), then we would declare, 'that a larger event is in progress', or similarly if this value is small enough (e.g., <-1), then we would declare a false alarm. We design the algorithm to work at a wide range of amplitude scales; that is, it should work for both small and large events.

Predictive value of the korean academy of family medicine in-training examination for certifying examination.

PubMed

Cho, Jung-Jin; Kim, Ji-Yong

2011-09-01

In-training examination (ITE) is a cognitive examination similar to the written test, but it is different from the Clinical Practice Examination of the Korean Academy of Family Medicine (KAFM) Certification Examination (CE). The objective of this is to estimate the positive predictive value of the KAFM-ITE for identifying residents at risk for poor performance on the three types of KAFM-CE. 372 residents who completed the KAFM-CE in 2011 were included. We compared the mean KAFM-CE scores with ITE experience. We evaluated the correlation and the positive predictive value (PPV) of ITE for the multiple choice question (MCQ) scores of 1st written test & 2nd slide examination, the total clinical practice examination scores, and the total sum of 2nd test. 275 out of 372 residents completed ITE. Those who completed ITE had significantly higher MCQ scores of 1st written test than those who did not. The correlation of ITE scores with 1st written MCQ (0.627) was found to be the highest among the other kinds of CE. The PPV of the ITE score for 1st written MCQ scores was 0.672. The PPV of the ITE score ranged from 0.376 to 0.502. The score of the KAFM ITE has acceptable positive predictive value that could be used as a part of comprehensive evaluation system for residents in cognitive field.

Predicting Bacillus coagulans spores inactivation in tomato pulp under nonisothermal heat treatments.

PubMed

Zimmermann, Morgana; Longhi, Daniel A; Schaffner, Donald W; Aragão, Gláucia M F

2014-05-01

The knowledge and understanding of Bacillus coagulans inactivation during a thermal treatment in tomato pulp, as well as the influence of temperature variation during thermal processes are essential for design, calculation, and optimization of the process. The aims of this work were to predict B. coagulans spores inactivation in tomato pulp under varying time-temperature profiles with Gompertz-inspired inactivation model and to validate the model's predictions by comparing the predicted values with experimental data. B. coagulans spores in pH 4.3 tomato pulp at 4 °Brix were sealed in capillary glass tubes and heated in thermostatically controlled circulating oil baths. Seven different nonisothermal profiles in the range from 95 to 105 °C were studied. Predicted inactivation kinetics showed similar behavior to experimentally observed inactivation curves when the samples were exposed to temperatures in the upper range of this study (99 to 105 °C). Profiles that resulted in less accurate predictions were those where the range of temperatures analyzed were comparatively lower (inactivation profiles starting at 95 °C). The link between fail prediction and both lower starting temperature and magnitude of the temperature shift suggests some chemical or biological mechanism at work. Statistical analysis showed that overall model predictions were acceptable, with bias factors from 0.781 to 1.012, and accuracy factors from 1.049 to 1.351, and confirm that the models used were adequate to estimate B. coagulans spores inactivation under fluctuating temperature conditions in the range from 95 to 105 °C. How can we estimate Bacillus coagulans inactivation during sudden temperature shifts in heat processing? This article provides a validated model that can be used to predict B. coagulans under changing temperature conditions. B. coagulans is a spore-forming bacillus that spoils acidified food products. The mathematical model developed here can be used to predict the spoilage risk following thermal process deviations for tomato products. © 2014 Institute of Food Technologists®

Parameterizing the Spatial Markov Model From Breakthrough Curve Data Alone

NASA Astrophysics Data System (ADS)

Sherman, Thomas; Fakhari, Abbas; Miller, Savannah; Singha, Kamini; Bolster, Diogo

2017-12-01

The spatial Markov model (SMM) is an upscaled Lagrangian model that effectively captures anomalous transport across a diverse range of hydrologic systems. The distinct feature of the SMM relative to other random walk models is that successive steps are correlated. To date, with some notable exceptions, the model has primarily been applied to data from high-resolution numerical simulations and correlation effects have been measured from simulated particle trajectories. In real systems such knowledge is practically unattainable and the best one might hope for is breakthrough curves (BTCs) at successive downstream locations. We introduce a novel methodology to quantify velocity correlation from BTC data alone. By discretizing two measured BTCs into a set of arrival times and developing an inverse model, we estimate velocity correlation, thereby enabling parameterization of the SMM in studies where detailed Lagrangian velocity statistics are unavailable. The proposed methodology is applied to two synthetic numerical problems, where we measure all details and thus test the veracity of the approach by comparison of estimated parameters with known simulated values. Our results suggest that our estimated transition probabilities agree with simulated values and using the SMM with this estimated parameterization accurately predicts BTCs downstream. Our methodology naturally allows for estimates of uncertainty by calculating lower and upper bounds of velocity correlation, enabling prediction of a range of BTCs. The measured BTCs fall within the range of predicted BTCs. This novel method to parameterize the SMM from BTC data alone is quite parsimonious, thereby widening the SMM's practical applicability.

Using the Bayesian Improved Surname Geocoding Method (BISG) to create a working classification of race and ethnicity in a diverse managed care population: a validation study.

PubMed

Adjaye-Gbewonyo, Dzifa; Bednarczyk, Robert A; Davis, Robert L; Omer, Saad B

2014-02-01

To validate classification of race/ethnicity based on the Bayesian Improved Surname Geocoding method (BISG) and assess variations in validity by gender and age. Secondary data on members of Kaiser Permanente Georgia, an integrated managed care organization, through 2010. For 191,494 members with self-reported race/ethnicity, probabilities for belonging to each of six race/ethnicity categories predicted from the BISG algorithm were used to assign individuals to a race/ethnicity category over a range of cutoffs greater than a probability of 0.50. Overall as well as gender- and age-stratified sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Receiver operating characteristic (ROC) curves were generated and used to identify optimal cutoffs for race/ethnicity assignment. The overall cutoffs for assignment that optimized sensitivity and specificity ranged from 0.50 to 0.57 for the four main racial/ethnic categories (White, Black, Asian/Pacific Islander, Hispanic). Corresponding sensitivity, specificity, PPV, and NPV ranged from 64.4 to 81.4 percent, 80.8 to 99.7 percent, 75.0 to 91.6 percent, and 79.4 to 98.0 percent, respectively. Accuracy of assignment was better among males and individuals of 65 years or older. BISG may be useful for classifying race/ethnicity of health plan members when needed for health care studies. © Health Research and Educational Trust.

Listening In on the Past: What Can Otolith δ18O Values Really Tell Us about the Environmental History of Fishes?

PubMed Central

Darnaude, Audrey M.; Sturrock, Anna; Trueman, Clive N.; Mouillot, David; EIMF; Campana, Steven E.; Hunter, Ewan

2014-01-01

Oxygen isotope ratios from fish otoliths are used to discriminate marine stocks and reconstruct past climate, assuming that variations in otolith δ18O values closely reflect differences in temperature history of fish when accounting for salinity induced variability in water δ18O. To investigate this, we exploited the environmental and migratory data gathered from a decade using archival tags to study the behaviour of adult plaice (Pleuronectes platessa L.) in the North Sea. Based on the tag-derived monthly distributions of the fish and corresponding temperature and salinity estimates modelled across three consecutive years, we first predicted annual otolith δ18O values for three geographically discrete offshore sub-stocks, using three alternative plausible scenarios for otolith growth. Comparison of predicted vs. measured annual δ18O values demonstrated >96% correct prediction of sub-stock membership, irrespective of the otolith growth scenario. Pronounced inter-stock differences in δ18O values, notably in summer, provide a robust marker for reconstructing broad-scale plaice distribution in the North Sea. However, although largely congruent, measured and predicted annual δ18O values of did not fully match. Small, but consistent, offsets were also observed between individual high-resolution otolith δ18O values measured during tag recording time and corresponding δ18O predictions using concomitant tag-recorded temperatures and location-specific salinity estimates. The nature of the shifts differed among sub-stocks, suggesting specific vital effects linked to variation in physiological response to temperature. Therefore, although otolith δ18O in free-ranging fish largely reflects environmental temperature and salinity, we counsel prudence when interpreting otolith δ18O data for stock discrimination or temperature reconstruction until the mechanisms underpinning otolith δ18O signature acquisition, and associated variation, are clarified. PMID:25279667

Jaw-opening force test to screen for Dysphagia: preliminary results.

PubMed

Hara, Koji; Tohara, Haruka; Wada, Satoko; Iida, Takatoshi; Ueda, Koichiro; Ansai, Toshihiro

2014-05-01

To assess the jaw-opening force test (JOFT) for dysphagia screening. Criterion standard. University dental hospital. Patients complaining of dysphagia (N=95) and with symptoms of dysphagia with chronic underlying causes (mean age ± SD, 79.3±9.61y; range, 50-94y; men: n=49; mean age ± SD, 77.03±9.81y; range, 50-94y; women: n=46; mean age ± SD, 75.42±9.73y; range, 51-93y) admitted for treatment between May 2011 and December 2012 were included. None. All patients were administered the JOFT and underwent fiberoptic endoscopic evaluation of swallowing (FEES). The mean jaw-opening strength was compared with aspiration (ASP) and pharyngeal residue observations of the FEES, which was used as the criterion standard. A receiver operating characteristic (ROC) curve analysis was performed. Forces of ≤3.2kg for men and ≤4kg for women were appropriate cutoff values for predicting ASP with a sensitivity and specificity of .57 and .79 for men and .93 and .52 for women, respectively. Based on the ROC analyses for predicting pharyngeal residue, forces of ≤5.3kg in men and ≤3.9kg in women were appropriate cutoff values, with a sensitivity and specificity of .80 and .88 for men and .83 and .81 for women, respectively. The JOFT could be a useful screening tool for predicting pharyngeal residue and could provide useful information to aid in the referral of patients for further diagnostic imaging testing. However, given its low sensitivity to ASP the JOFT should be paired with other screening tests that predict ASP. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Modeling the dynamic equilibrium between oligomers of (AlOCH3)n in methylaluminoxane (MAO). A theoretical study based on a combined quantum mechanical and statistical mechanical approach.

PubMed

Zurek, E; Woo, T K; Firman, T K; Ziegler, T

2001-01-15

Density functional theory (DFT) has been used to calculate the energies of 36 different methylaluminoxane (MAO) cage structures with the general formula (MeAlO)n, where n ranges from 4 to 16. A least-squares fit has been used to devise a formula which predicts the total energies of the MAO with different n's giving an rms deviation of 4.70 kcal/mol. These energies in conjunction with frequency calculations based on molecular mechanics have been used to estimate the finite temperature enthalpies, entropies, and free energies for these MAO structures. Furthermore, formulas have been devised which predict finite temperature enthalpies and entropies for MAO structures of any n for a temperature range of 198.15-598.15 K. Using these formulas, the free energies at different temperatures have been predicted for MAO structures where n ranges from 17 to 30. The free energy values were then used to predict the percentage of each n found at a given temperature. Our calculations give an average n value of 18.41, 17.23, 16.89, and 15.72 at 198.15, 298.15, 398.15, and 598.15 K, respectively. Topological arguments have also been used to show that the MAO cage structure contains a limited amount of square faces as compared to octagonal and hexagonal ones. It is also suggested that the limited number of square faces with their strained Al-O bonds explain the high molar Al:catalyst ratio required for activation. Moreover, in this study we outline a general methodology which may be used to calculate the percent abundance of an equilibrium mixture of oligomers with the general formula (X)n.

A digital prediction algorithm for a single-phase boost PFC

NASA Astrophysics Data System (ADS)

Qing, Wang; Ning, Chen; Weifeng, Sun; Shengli, Lu; Longxing, Shi

2012-12-01

A novel digital control algorithm for digital control power factor correction is presented, which is called the prediction algorithm and has a feature of a higher PF (power factor) with lower total harmonic distortion, and a faster dynamic response with the change of the input voltage or load current. For a certain system, based on the current system state parameters, the prediction algorithm can estimate the track of the output voltage and the inductor current at the next switching cycle and get a set of optimized control sequences to perfectly track the trajectory of input voltage. The proposed prediction algorithm is verified at different conditions, and computer simulation and experimental results under multi-situations confirm the effectiveness of the prediction algorithm. Under the circumstances that the input voltage is in the range of 90-265 V and the load current in the range of 20%-100%, the PF value is larger than 0.998. The startup and the recovery times respectively are about 0.1 s and 0.02 s without overshoot. The experimental results also verify the validity of the proposed method.

The Predictive Validity of the Short-Term Assessment of Risk and Treatability (START) for Multiple Adverse Outcomes in a Secure Psychiatric Inpatient Setting.

PubMed

O'Shea, Laura E; Picchioni, Marco M; Dickens, Geoffrey L

2016-04-01

The Short-Term Assessment of Risk and Treatability (START) aims to assist mental health practitioners to estimate an individual's short-term risk for a range of adverse outcomes via structured consideration of their risk ("Vulnerabilities") and protective factors ("Strengths") in 20 areas. It has demonstrated predictive validity for aggression but this is less established for other outcomes. We collated START assessments for N = 200 adults in a secure mental health hospital and ascertained 3-month risk event incidence using the START Outcomes Scale. The specific risk estimates, which are the tool developers' suggested method of overall assessment, predicted aggression, self-harm/suicidality, and victimization, and had incremental validity over the Strength and Vulnerability scales for these outcomes. The Strength scale had incremental validity over the Vulnerability scale for aggressive outcomes; therefore, consideration of protective factors had demonstrable value in their prediction. Further evidence is required to support use of the START for the full range of outcomes it aims to predict. © The Author(s) 2015.

Testing the relativistic precession model using low-frequency and kHz quasi-periodic oscillations in neutron star low-mass X-ray binaries with known spin

NASA Astrophysics Data System (ADS)

van Doesburgh, Marieke; van der Klis, Michiel

2017-03-01

We analyse all available RXTE data on a sample of 13 low-mass X-ray binaries with known neutron star spin that are not persistent pulsars. We carefully measure the correlations between the centroid frequencies of the quasi-periodic oscillations (QPOs). We compare these correlations to the prediction of the relativistic precession model that, due to frame dragging, a QPO will occur at the Lense-Thirring precession frequency νLT of a test-particle orbit whose orbital frequency is the upper kHz QPO frequency νu. Contrary to the most prominent previous studies, we find two different oscillations in the range predicted for νLT that are simultaneously present over a wide range of νu. Additionally, one of the low-frequency noise components evolves into a (third) QPO in the νLT range when νu exceeds 600 Hz. The frequencies of these QPOs all correlate to νu following power laws with indices between 0.4 and 3.3, significantly exceeding the predicted value of 2.0 in 80 per cent of the cases (at 3 to >20σ). Also, there is no evidence that the neutron star spin frequency affects any of these three QPO frequencies, as would be expected for frame dragging. Finally, the observed QPO frequencies tend to be higher than the νLT predicted for reasonable neutron star specific moment of inertia. In the light of recent successes of precession models in black holes, we briefly discuss ways in which such precession can occur in neutron stars at frequencies different from test-particle values and consistent with those observed. A precessing torus geometry and other torques than frame dragging may allow precession to produce the observed frequency correlations, but can only explain one of the three QPOs in the νLT range.

Assessment of the forecast skill of spring onset in the NMME experiment

NASA Astrophysics Data System (ADS)

Carrillo, C. M.; Ault, T.

2017-12-01

This study assesses the predictability of spring onset using an index of its interannual variability. We use the North American Multi-Model Ensemble (NMME) experiment to assess this predictability. The input dataset to compute spring onset index, SI-x, were treated with a daily joint bias correction (JBC) approach, and the SI-x outputs were post-processed using three ensemble model output statistic (EMOS) approaches—logistic regression, Gaussian Ensemble Dressing, and non-homogeneous Gaussian regression. These EMOS approaches quantify the effect of training period length and ensemble size on forecast skill. The highest range of predictability for the timing spring onset is from 10 to 60 days, and it is located along a narrow band between 35° to 45°N in the US. Using rank probability scores based on quantiles (q), a forecast threshold (q) of 0.5 provides a range of predictability that falls into two categories 10-40 and 40-60 days, which seems to represent the effect of the intra-seasonal scale. Using higher thresholds (q=0.6 and 0.7) predictability shows lower range with values around 10-30 days. The post-processing work using JBC improves the predictability skill by 13% from uncorrected results. Using EMOS, a significant positive change in the skill score is noted in regions where the skill with JBC shows evidence of improvement. The consensus of these techniques shows that regions of better predictability can be expanded.

Evaluation of non-animal methods for assessing skin sensitisation hazard: A Bayesian Value-of-Information analysis.

PubMed

Leontaridou, Maria; Gabbert, Silke; Van Ierland, Ekko C; Worth, Andrew P; Landsiedel, Robert

2016-07-01

This paper offers a Bayesian Value-of-Information (VOI) analysis for guiding the development of non-animal testing strategies, balancing information gains from testing with the expected social gains and costs from the adoption of regulatory decisions. Testing is assumed to have value, if, and only if, the information revealed from testing triggers a welfare-improving decision on the use (or non-use) of a substance. As an illustration, our VOI model is applied to a set of five individual non-animal prediction methods used for skin sensitisation hazard assessment, seven battery combinations of these methods, and 236 sequential 2-test and 3-test strategies. Their expected values are quantified and compared to the expected value of the local lymph node assay (LLNA) as the animal method. We find that battery and sequential combinations of non-animal prediction methods reveal a significantly higher expected value than the LLNA. This holds for the entire range of prior beliefs. Furthermore, our results illustrate that the testing strategy with the highest expected value does not necessarily have to follow the order of key events in the sensitisation adverse outcome pathway (AOP). 2016 FRAME.

Clinical application of the basic definition of malnutrition proposed by the European Society for Clinical Nutrition and Metabolism (ESPEN): Comparison with classical tools in geriatric care.

PubMed

Sánchez-Rodríguez, Dolores; Annweiler, Cédric; Ronquillo-Moreno, Natalia; Tortosa-Rodríguez, Andrea; Guillén-Solà, Anna; Vázquez-Ibar, Olga; Escalada, Ferran; Muniesa, Josep M; Marco, Ester

Malnutrition is a prevalent condition related to adverse outcomes in older people. Our aim was to compare the diagnostic capacity of the malnutrition criteria of the European Society of Parenteral and Enteral Nutrition (ESPEN) with other classical diagnostic tools. Cohort study of 102 consecutive in-patients ≥70 years admitted for postacute rehabilitation. Patients were considered malnourished if their Mini-Nutritional Assessment-Short Form (MNA-SF) score was ≤11 and serum albumin <3 mg/dL or MNA-SF ≤ 11, serum albumin <3 mg/dL, and usual clinical signs and symptoms of malnutrition. Sensitivity, specificity, positive and negative predictive values, accuracy likelihood ratios, and kappa values were calculated for both methods: and compared with ESPEN consensus. Of 102 eligible in-patients, 88 fulfilled inclusion criteria and were identified as "at risk" by MNA-SF. Malnutrition diagnosis was confirmed in 11.6% and 10.5% of the patients using classical methods,whereas 19.3% were malnourished according to the ESPEN criteria. Combined with low albumin levels, the diagnosis showed 57.9% sensitivity, 64.5% specificity, 85.9% negative predictive value,0.63 accuracy (fair validity, low range), and kappa index of 0.163 (poor ESPEN agreement). The combination of MNA-SF, low albumin, and clinical malnutrition showed 52.6% sensitivity, 88.3% specificity, 88.3%negative predictive value, and 0.82 accuracy (fair validity, low range), and kappa index of 0.43 (fair ESPEN agreement). Malnutrition was almost twice as prevalent when diagnosed by the ESPEN consensus, compared to classical assessment methods: Classical methods: showed fair validity and poor agreement with the ESPEN consensus in assessing malnutrition in geriatric postacute care. Copyright © 2018 Elsevier B.V. All rights reserved.

Toward a consistent model for strain accrual and release for the New Madrid Seismic Zone, central United States

USGS Publications Warehouse

Hough, S.E.; Page, M.

2011-01-01

At the heart of the conundrum of seismogenesis in the New Madrid Seismic Zone is the apparently substantial discrepancy between low strain rate and high recent seismic moment release. In this study we revisit the magnitudes of the four principal 1811–1812 earthquakes using intensity values determined from individual assessments from four experts. Using these values and the grid search method of Bakun and Wentworth (1997), we estimate magnitudes around 7.0 for all four events, values that are significantly lower than previously published magnitude estimates based on macroseismic intensities. We further show that the strain rate predicted from postglacial rebound is sufficient to produce a sequence with the moment release of one Mmax6.8 every 500 years, a rate that is much lower than previous estimates of late Holocene moment release. However, Mw6.8 is at the low end of the uncertainty range inferred from analysis of intensities for the largest 1811–1812 event. We show that Mw6.8 is also a reasonable value for the largest main shock given a plausible rupture scenario. One can also construct a range of consistent models that permit a somewhat higher Mmax, with a longer average recurrence rate. It is thus possible to reconcile predicted strain and seismic moment release rates with alternative models: one in which 1811–1812 sequences occur every 500 years, with the largest events being Mmax∼6.8, or one in which sequences occur, on average, less frequently, with Mmax of ∼7.0. Both models predict that the late Holocene rate of activity will continue for the next few to 10 thousand years.

Limitations of experiments performed in artificially made OECD standard soils for predicting cadmium, lead and zinc toxicity towards organisms living in natural soils.

PubMed

Sydow, Mateusz; Chrzanowski, Łukasz; Cedergreen, Nina; Owsianiak, Mikołaj

2017-08-01

Development of comparative toxicity potentials of cationic metals in soils for applications in hazard ranking and toxic impact assessment is currently jeopardized by the availability of experimental effect data. To compensate for this deficiency, data retrieved from experiments carried out in standardized artificial soils, like OECD soils, could potentially be tapped as a source of effect data. It is, however, unknown whether such data are applicable to natural soils where the variability in pore water concentrations of dissolved base cations is large, and where mass transfer limitations of metal uptake can occur. Here, free ion activity models (FIAM) and empirical regression models (ERM, with pH as a predictor) were derived from total metal EC50 values (concentration with effects in 50% of individuals) using speciation for experiments performed in artificial OECD soils measuring ecotoxicological endpoints for terrestrial earthworms, potworms, and springtails. The models were validated by predicting total metal based EC50 values using backward speciation employing an independent set of natural soils with missing information about ionic composition of pore water, as retrieved from a literature review. ERMs performed better than FIAMs. Pearson's r for log 10 -transformed total metal based EC50s values (ERM) ranged from 0.25 to 0.74, suggesting a general correlation between predicted and measured values. Yet, root-mean-square-error (RMSE) ranged from 0.16 to 0.87 and was either smaller or comparable with the variability of measured EC50 values, suggesting modest performance. This modest performance was mainly due to the omission of pore water concentrations of base cations during model development and their validation, as verified by comparisons with predictions of published terrestrial biotic ligand models. Thus, the usefulness of data from artificial OECD soils for global-scale assessment of terrestrial ecotoxic impacts of Cd, Pb and Zn in soils is limited due to relatively small variability of pore water concentrations of dissolved base cations in OECD soils, preventing their inclusion in development of predictive models. Our findings stress the importance of considering differences in ionic composition of soil pore water when characterizing terrestrial ecotoxicity of cationic metals in natural soils. Copyright © 2017 Elsevier Ltd. All rights reserved.

Edge safety factor at the onset of plasma disruption during VDEs in JT-60U

NASA Astrophysics Data System (ADS)

Sugihara, Masayoshi; Lukash, Victor; Khayrutdinov, Rustam; Neyatani, Yuzuru

2004-10-01

Detailed examinations of the value of the edge safety factor (qa) at the onset of thermal quench (TQ) during intentional vertical displacement event (VDE) experiments in JT-60U are carried out using two different reconstruction methods, FBI/FBEQU and DINA. The results from the two methods are very similar and show that the TQ occurs when the qa value is in the range between 1.5 and 2. This result suggests that the predictive simulations for VDEs should be performed within this range of q to examine the subsequent differences in the halo currents, plasma movement and other plasma behaviour during the current quench.

Application of a continuous distribution model for proton binding by humic acids extracted from acidic lake sediments

NASA Astrophysics Data System (ADS)

Rhea, James R.; Young, Thomas C.

1987-10-01

The proton binding characteristics of humic acids extracted from the sediments of Cranberry Pond, an acidic water body located in the Adirondack Mountain region of New York State, were explored by the application of a multiligand distribution model. The model characterizes a class of proton binding sites by mean log K values and the standard deviations of log K values about the mean. Mean log K values and their relative abundances were determined directly from experimental titration data. The model accurately predicts the binding of protons by the humic acids for pH values in the range 3.5 to 10.0.

Application of a continuous distribution model for proton binding by humic acids extracted from acidic lake sediments

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

Rhea, J.R.; Young, T.C.

1987-01-01

The proton binding characteristics of humic acids extracted from the sediments of Cranberry Pond, an acidic water body located in the Adirondack Mountain region of New York State, were explored by the application of a nultiligand distribution model. The model characterizes a class of proton binding sites by mean log K values and the standard deviations of log K values and the mean. Mean log K values and their relative abundances were determined directly from experimental titration data. The model accurately predicts the binding of protons by the humic acids for pH values in the range 3.5 to 10.0.

Effect of analgesia on the changes in respiratory parameters in blunt chest injury with multiple rib fractures.

PubMed

Ekpe, Eyo Effiong; Eyo, Catherine

2017-01-01

Blunt chest injury with multiple rib fractures can result in such complications as pneumonia, atelectasis, bronchiectasis, empyema thoracis, acute respiratory distress syndrome, and prolonged Intensive Care Unit and hospital stay, with its concomitant mortality. These may be prevented or reduced by good analgesic therapy which is the subject of this study. This was a prospective study of effects of analgesia on changes in pulmonary functions of patients with traumatic multiple rib fractures resulting from blunt chest injury. There were 64 adult patients who were studied with multiple rib fractures caused by blunt chest trauma. Of these patients, 54 (84.4%) were male and 10 (15.6%) were female. Motorcycle (popularly known as "okada") and tricycle (popularly known as keke napep) accidents significantly accounted for the majority of the multiple rib fractures, that is, in 50 (78.1%) of the patients. Before analgesic administration, no patient had a normal respiratory rate, but at 1 h following the administration of analgesic, 21 (32.8%) of patients recorded normal respiratory rates and there was a significant reduction in the number (10.9% vs. 39.1%) of patients with respiratory rates> 30 breaths/min. Before commencement of analgesic, no patient recorded up to 99% of oxygen saturation (SpO2) as measured by pulse oximeter, while 43.8% recorded SpO2of 96%. This improved after 1 h of administration of analgesics to SpO2of 100% in 18.8% of patients and 99% in 31.3% of patients and none recording SpO2of < 97% (P = 0.006). Before analgesia, no patient was able to achieve peak expiratory flow rate (PEFR) value> 100% of predicted while only 9 (14.1%) patients were able to achieve a PEFR value in the range of 91%-100% of predicted value. One hour after analgesia, a total of 6 (9.4%) patients were able to achieve PEFR values> 100% predicted, while 35 (54.7%) patients achieved PEFR values in the range of 91%-100% predicted. Adequate analgesia is capable of reversing the negative effects of chest pain of traumatic multiple rib fractures on pulmonary function parameters through improvement in respiratory mechanics.

A GIS modeling method applied to predicting forest songbird habitat

USGS Publications Warehouse

Dettmers, Randy; Bart, Jonathan

1999-01-01

We have developed an approach for using a??presencea?? data to construct habitat models. Presence data are those that indicate locations where the target organism is observed to occur, but that cannot be used to define locations where the organism does not occur. Surveys of highly mobile vertebrates often yield these kinds of data. Models developed through our approach yield predictions of the amount and the spatial distribution of good-quality habitat for the target species. This approach was developed primarily for use in a GIS context; thus, the models are spatially explicit and have the potential to be applied over large areas. Our method consists of two primary steps. In the first step, we identify an optimal range of values for each habitat variable to be used as a predictor in the model. To find these ranges, we employ the concept of maximizing the difference between cumulative distribution functions of (1) the values of a habitat variable at the observed presence locations of the target organism, and (2) the values of that habitat variable for all locations across a study area. In the second step, multivariate models of good habitat are constructed by combining these ranges of values, using the Boolean operators a??anda?? and a??or.a?? We use an approach similar to forward stepwise regression to select the best overall model. We demonstrate the use of this method by developing species-specific habitat models for nine forest-breeding songbirds (e.g., Cerulean Warbler, Scarlet Tanager, Wood Thrush) studied in southern Ohio. These models are based on speciesa?? microhabitat preferences for moisture and vegetation characteristics that can be predicted primarily through the use of abiotic variables. We use slope, land surface morphology, land surface curvature, water flow accumulation downhill, and an integrated moisture index, in conjunction with a land-cover classification that identifies forest/nonforest, to develop these models. The performance of these models was evaluated with an independent data set. Our tests showed that the models performed better than random at identifying where the birds occurred and provided useful information for predicting the amount and spatial distribution of good habitat for the birds we studied. In addition, we generally found positive correlations between the amount of habitat, as predicted by the models, and the number of territories within a given area. This added component provides the possibility, ultimately, of being able to estimate population sizes. Our models represent useful tools for resource managers who are interested in assessing the impacts of alternative management plans that could alter or remove habitat for these birds.

Psychopathology in African Unaccompanied Refugee Minors in Austria

ERIC Educational Resources Information Center

Huemer, Julia; Karnik, Niranjan; Voelkl-Kernstock, Sabine; Granditsch, Elisabeth; Plattner, Belinda; Friedrich, Max; Steiner, Hans

2011-01-01

We assessed the prevalence of a range of psychopathology among African unaccompanied refugee minors (URMs) in Austria. Additionally, the predictive value of war exposure on PTSD symptoms was examined. Forty-one URMs were assessed with the Mini-International Neuropsychiatric Interview for children and adolescents, the Youth Self-Report, the UCLA…

Development of a predictive program for Vibrio parahaemolyticus growth under various environmental conditions.

PubMed

Fujikawa, Hiroshi; Kimura, Bon; Fujii, Tateo

2009-09-01

In this study, we developed a predictive program for Vibrio parahaemolyticus growth under various environmental conditions. Raw growth data was obtained with a V. parahaemolyticus O3:K6 strain cultured at a variety of broth temperatures, pH, and salt concentrations. Data were analyzed with our logistic model and the parameter values of the model were analyzed with polynomial equations. A prediction program consisting of the growth model and the polynomial equations was then developed. After the range of the growth environments was modified, the program successfully predicted the growth for all environments tested. The program could be a useful tool to ensure the bacteriological safety of seafood.

Fitting stress relaxation experiments with fractional Zener model to predict high frequency moduli of polymeric acoustic foams

NASA Astrophysics Data System (ADS)

Guo, Xinxin; Yan, Guqi; Benyahia, Lazhar; Sahraoui, Sohbi

2016-11-01

This paper presents a time domain method to determine viscoelastic properties of open-cell foams on a wide frequency range. This method is based on the adjustment of the stress-time relationship, obtained from relaxation tests on polymeric foams' samples under static compression, with the four fractional derivatives Zener model. The experimental relaxation function, well described by the Mittag-Leffler function, allows for straightforward prediction of the frequency-dependence of complex modulus of polyurethane foams. To show the feasibility of this approach, complex shear moduli of the same foams were measured in the frequency range between 0.1 and 16 Hz and at different temperatures between -20 °C and 20 °C. A curve was reconstructed on the reduced frequency range (0.1 Hz-1 MHz) using the time-temperature superposition principle. Very good agreement was obtained between experimental complex moduli values and the fractional Zener model predictions. The proposed time domain method may constitute an improved alternative to resonant and non-resonant techniques often used for dynamic characterization of polymers for the determination of viscoelastic moduli on a broad frequency range.

Duration of untreated psychosis: Impact of the definition of treatment onset on its predictive value over three years of treatment.

PubMed

Golay, Philippe; Alameda, Luis; Baumann, Philipp; Elowe, Julien; Progin, Pierre; Polari, Andrea; Conus, Philippe

2016-06-01

While reduction of DUP (Duration of Untreated Psychosis) is a key goal in early intervention strategies, the predictive value of DUP on outcome has been questioned. We planned this study in order to explore the impact of three different definition of "treatment initiation" on the predictive value of DUP on outcome in an early psychosis sample. 221 early psychosis patients aged 18-35 were followed-up prospectively over 36 months. DUP was measured using three definitions for treatment onset: Initiation of antipsychotic medication (DUP1); engagement in a specialized programme (DUP2) and combination of engagement in a specialized programme and adherence to medication (DUP3). 10% of patients never reached criteria for DUP3 and therefore were never adequately treated over the 36-month period of care. While DUP1 and DUP2 had a limited predictive value on outcome, DUP3, based on a more restrictive definition for treatment onset, was a better predictor of positive and negative symptoms, as well as functional outcome at 12, 24 and 36 months. Globally, DUP3 explained 2 to 5 times more of the variance than DUP1 and DUP2, with effect sizes falling in the medium range according to Cohen. The limited predictive value of DUP on outcome in previous studies may be linked to problems of definitions that do not take adherence to treatment into account. While they need replication, our results suggest effort to reduce DUP should continue and aim both at early detection and development of engagement strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interobserver variability of sonography for prediction of placenta accreta.

PubMed

Bowman, Zachary S; Eller, Alexandra G; Kennedy, Anne M; Richards, Douglas S; Winter, Thomas C; Woodward, Paula J; Silver, Robert M

2014-12-01

The sensitivity of sonography to predict accreta has been reported as higher than 90%. However, most studies are from single expert investigators. Our objective was to analyze interobserver variability of sonography for prediction of placenta accreta. Patients with previa with and without accreta were ascertained, and images with placental views were collected, deidentified, and placed in random sequence. Three radiologists and 3 maternal-fetal medicine specialists interpreted each study for the presence of accreta and specific findings reported to be associated with its diagnosis. Investigator-specific sensitivity, specificity, and accuracy were calculated. κ statistics were used to assess variability between individuals and types of investigators. A total of 229 sonographic studies from 55 patients with accreta and 56 control patients were examined. Accuracy ranged from 55.9% to 76.4%. Of imaging studies yielding diagnoses, sensitivity ranged from 53.4% to 74.4%, and specificity ranged from 70.8% to 94.8%. Overall interobserver agreement was moderate (mean κ ± SD = 0.47 ± 0.12). κ values between pairs of investigators ranged from 0.32 (fair agreement) to 0.73 (substantial agreement). Average individual agreement ranged from fair (κ = 0.35) to moderate (κ = 0.53). Blinded from clinical data, sonography has significant interobserver variability for the diagnosis of placenta accreta. © 2013 by the American Institute of Ultrasound in Medicine.

Prediction of Classroom Reverberation Time using Neural Network

NASA Astrophysics Data System (ADS)

Liyana Zainudin, Fathin; Kadir Mahamad, Abd; Saon, Sharifah; Nizam Yahya, Musli

2018-04-01

In this paper, an alternative method for predicting the reverberation time (RT) using neural network (NN) for classroom was designed and explored. Classroom models were created using Google SketchUp software. The NN applied training dataset from the classroom models with RT values that were computed from ODEON 12.10 software. The NN was conducted separately for 500Hz, 1000Hz, and 2000Hz as absorption coefficient that is one of the prominent input variable is frequency dependent. Mean squared error (MSE) and regression (R) values were obtained to examine the NN efficiency. Overall, the NN shows a good result with MSE < 0.005 and R > 0.9. The NN also managed to achieve a percentage of accuracy of 92.53% for 500Hz, 93.66% for 1000Hz, and 93.18% for 2000Hz and thus displays a good and efficient performance. Nevertheless, the optimum RT value is range between 0.75 – 0.9 seconds.

Young's Modulus of Wurtzite and Zinc Blende InP Nanowires.

PubMed

Dunaevskiy, Mikhail; Geydt, Pavel; Lähderanta, Erkki; Alekseev, Prokhor; Haggrén, Tuomas; Kakko, Joona-Pekko; Jiang, Hua; Lipsanen, Harri

2017-06-14

The Young's modulus of thin conical InP nanowires with either wurtzite or mixed "zinc blende/wurtzite" structures was measured. It has been shown that the value of Young's modulus obtained for wurtzite InP nanowires (E [0001] = 130 ± 30 GPa) was similar to the theoretically predicted value for the wurtzite InP material (E [0001] = 120 ± 10 GPa). The Young's modulus of mixed "zinc blende/wurtzite" InP nanowires (E [111] = 65 ± 10 GPa) appeared to be 40% less than the theoretically predicted value for the zinc blende InP material (E [111] = 110 GPa). An advanced method for measuring the Young's modulus of thin and flexible nanostructures is proposed. It consists of measuring the flexibility (the inverse of stiffness) profiles 1/k(x) by the scanning probe microscopy with precise control of loading force in nanonewton range followed by simulations.

Rapeseed-straw enzymatic digestibility enhancement by sodium hydroxide treatment under ultrasound irradiation.

PubMed

Kang, Kyeong Eop; Jeong, Gwi-Taek; Park, Don-Hee

2013-08-01

In this study, we carried out sodium hydroxide and sonication pretreatments of rapeseed straw (Brassica napus) to obtain monosugar suitable for production of biofuels. To optimize the pretreatment conditions, we applied a statistical response-surface methodology. The optimal pretreatment conditions using sodium hydroxide under sonication irradiation were determined to be 75.0 °C, 7.0 % sodium hydroxide, and 6.8 h. For these conditions, we predicted 97.3 % enzymatic digestibility. In repeated experiments to validate the predicted value, 98.9 ± 0.3 % enzymatic digestibility was obtained, which was well within the range of the predicted model. Moreover, sonication irradiation was found to have a good effect on pretreatment in the lower temperature range and at all concentrations of sodium hydroxide. According to scanning electron microscopy images, the surface area and pore size of the pretreated rapeseed straw were modified by the sodium hydroxide pretreatment under sonication irradiation.

Timebias corrections to predictions

NASA Technical Reports Server (NTRS)

Wood, Roger; Gibbs, Philip

1993-01-01

The importance of an accurate knowledge of the time bias corrections to predicted orbits to a satellite laser ranging (SLR) observer, especially for low satellites, is highlighted. Sources of time bias values and the optimum strategy for extrapolation are discussed from the viewpoint of the observer wishing to maximize the chances of getting returns from the next pass. What is said may be seen as a commercial encouraging wider and speedier use of existing data centers for mutually beneficial exchange of time bias data.

Quasi-particle properties from tunneling in the v = 5/2 fractional quantum Hall state.

PubMed

Radu, Iuliana P; Miller, J B; Marcus, C M; Kastner, M A; Pfeiffer, L N; West, K W

2008-05-16

Quasi-particles with fractional charge and statistics, as well as modified Coulomb interactions, exist in a two-dimensional electron system in the fractional quantum Hall (FQH) regime. Theoretical models of the FQH state at filling fraction v = 5/2 make the further prediction that the wave function can encode the interchange of two quasi-particles, making this state relevant for topological quantum computing. We show that bias-dependent tunneling across a narrow constriction at v = 5/2 exhibits temperature scaling and, from fits to the theoretical scaling form, extract values for the effective charge and the interaction parameter of the quasi-particles. Ranges of values obtained are consistent with those predicted by certain models of the 5/2 state.

Effective heating of magnetic nanoparticle aggregates for in vivo nano-theranostic hyperthermia.

PubMed

Wang, Chencai; Hsu, Chao-Hsiung; Li, Zhao; Hwang, Lian-Pin; Lin, Ying-Chih; Chou, Pi-Tai; Lin, Yung-Ya

2017-01-01

Magnetic resonance (MR) nano-theranostic hyperthermia uses magnetic nanoparticles to target and accumulate at the lesions and generate heat to kill lesion cells directly through hyperthermia or indirectly through thermal activation and control releasing of drugs. Preclinical and translational applications of MR nano-theranostic hyperthermia are currently limited by a few major theoretical difficulties and experimental challenges in in vivo conditions. For example, conventional models for estimating the heat generated and the optimal magnetic nanoparticle sizes for hyperthermia do not accurately reproduce reported in vivo experimental results. In this work, a revised cluster-based model was proposed to predict the specific loss power (SLP) by explicitly considering magnetic nanoparticle aggregation in in vivo conditions. By comparing with the reported experimental results of magnetite Fe 3 O 4 and cobalt ferrite CoFe 2 O 4 magnetic nanoparticles, it is shown that the revised cluster-based model provides a more accurate prediction of the experimental values than the conventional models that assume magnetic nanoparticles act as single units. It also provides a clear physical picture: the aggregation of magnetic nanoparticles increases the cluster magnetic anisotropy while reducing both the cluster domain magnetization and the average magnetic moment, which, in turn, shift the predicted SLP toward a smaller magnetic nanoparticle diameter with lower peak values. As a result, the heating efficiency and the SLP values are decreased. The improvement in the prediction accuracy in in vivo conditions is particularly pronounced when the magnetic nanoparticle diameter is in the range of ~10-20 nm. This happens to be an important size range for MR cancer nano-theranostics, as it exhibits the highest efficacy against both primary and metastatic tumors in vivo. Our studies show that a relatively 20%-25% smaller magnetic nanoparticle diameter should be chosen to reach the maximal heating efficiency in comparison with the optimal size predicted by previous models.

Effective heating of magnetic nanoparticle aggregates for in vivo nano-theranostic hyperthermia

PubMed Central

Wang, Chencai; Hsu, Chao-Hsiung; Li, Zhao; Hwang, Lian-Pin; Lin, Ying-Chih; Chou, Pi-Tai; Lin, Yung-Ya

2017-01-01

Magnetic resonance (MR) nano-theranostic hyperthermia uses magnetic nanoparticles to target and accumulate at the lesions and generate heat to kill lesion cells directly through hyperthermia or indirectly through thermal activation and control releasing of drugs. Preclinical and translational applications of MR nano-theranostic hyperthermia are currently limited by a few major theoretical difficulties and experimental challenges in in vivo conditions. For example, conventional models for estimating the heat generated and the optimal magnetic nanoparticle sizes for hyperthermia do not accurately reproduce reported in vivo experimental results. In this work, a revised cluster-based model was proposed to predict the specific loss power (SLP) by explicitly considering magnetic nanoparticle aggregation in in vivo conditions. By comparing with the reported experimental results of magnetite Fe3O4 and cobalt ferrite CoFe2O4 magnetic nanoparticles, it is shown that the revised cluster-based model provides a more accurate prediction of the experimental values than the conventional models that assume magnetic nanoparticles act as single units. It also provides a clear physical picture: the aggregation of magnetic nanoparticles increases the cluster magnetic anisotropy while reducing both the cluster domain magnetization and the average magnetic moment, which, in turn, shift the predicted SLP toward a smaller magnetic nanoparticle diameter with lower peak values. As a result, the heating efficiency and the SLP values are decreased. The improvement in the prediction accuracy in in vivo conditions is particularly pronounced when the magnetic nanoparticle diameter is in the range of ~10–20 nm. This happens to be an important size range for MR cancer nano-theranostics, as it exhibits the highest efficacy against both primary and metastatic tumors in vivo. Our studies show that a relatively 20%–25% smaller magnetic nanoparticle diameter should be chosen to reach the maximal heating efficiency in comparison with the optimal size predicted by previous models. PMID:28894366

PREDICTION OF RELAPSE FROM HYPERTHYROIDISM FOLLOWING ANTITHYROID MEDICATION WITHDRAWAL USING TECHNETIUM THYROID UPTAKE SCANNING.

PubMed

Nakhjavani, Manouchehr; Abdollahi, Soraya; Farzanefar, Saeed; Abousaidi, Mohammadtagi; Esteghamati, Alireza; Naseri, Maryam; Eftekhari, Mohamad; Abbasi, Mehrshad

2017-04-02

Technetium thyroid uptake (TTU) is not inhibited by antithyroid drugs (ATD) and reflects the degree of thyroid stimulation. We intended to predict the relapse rate from hyperthyroidism based on TTU measurement. Out of 44 initially enrolled subjects, 38 patients aged 41.6 ± 14.6 with Graves disease (duration: 84 ± 78 months) completed the study. TTU was performed with 40-second imaging of the neck and mediastinum 20 minutes after injection of 1 mCi technetium-99m pertechnetate. TTU was measured as the percentage of the count of activity accumulated in the thyroidal region minus the mediastinal background uptake to the count of 1 mCi technetium-99m under the same acquisition conditions. Then methimazole was stopped and patients were followed. The optimal TTU cutoff value for Graves relapse prediction was calculated using Youden's J statistic. Hyperthyroidism relapsed in 11 (28.9%) patients 122 ± 96 (range: 15-290) days post-ATD withdrawal. The subjects in remission were followed for 209 ± 81 days (range: 88-390). TTU was significantly higher in patients with forthcoming relapse (12.0 ± 8.0 vs. 3.9 ± 2.0, P = .007). The difference was significant after adjustment for age, sex, history of previous relapse, disease duration, and thyroid-stimulating hormone (TSH) levels before withdrawal. The area under the receiver operative characteristic (ROC) curve was 0.87. The optimal TTU cutoff value for classification of subjects with relapse and remission was 8.7 with sensitivity, specificity, and positive and negative predictive value of 73%, 100%, 100%, and 90%, respectively (odds ratio [OR] = 10.0; 95% confidence interval [CI]: 3.4-29.3). TTU evaluation in hyperthyroid patients receiving antithyroid medication is an accurate and practical method for predicting relapse after ATD withdrawal. ATD = antithyroid drugs RIU = radio-iodine uptake TSH = thyroid-stimulating hormone TSI = thyroid-stimulating immunoglobulin TTU = technetium thyroid uptake.

Genomic selection using beef commercial carcass phenotypes.

PubMed

Todd, D L; Roughsedge, T; Woolliams, J A

2014-03-01

In this study, an industry terminal breeding goal was used in a deterministic simulation, using selection index methodology, to predict genetic gain in a beef population modelled on the UK pedigree Limousin, when using genomic selection (GS) and incorporating phenotype information from novel commercial carcass traits. The effect of genotype-environment interaction was investigated by including the model variations of the genetic correlation between purebred and commercial cross-bred performance (ρX). Three genomic scenarios were considered: (1) genomic breeding values (GBV)+estimated breeding values (EBV) for existing selection traits; (2) GBV for three novel commercial carcass traits+EBV in existing traits; and (3) GBV for novel and existing traits plus EBV for existing traits. Each of the three scenarios was simulated for a range of training population (TP) sizes and with three values of ρX. Scenarios 2 and 3 predicted substantially higher percentage increases over current selection than Scenario 1. A TP of 2000 sires, each with 20 commercial progeny with carcass phenotypes, and assuming a ρX of 0.7, is predicted to increase gain by 40% over current selection in Scenario 3. The percentage increase in gain over current selection increased with decreasing ρX; however, the effect of varying ρX was reduced at high TP sizes for Scenarios 2 and 3. A further non-genomic scenario (4) was considered simulating a conventional population-wide progeny test using EBV only. With 20 commercial cross-bred progenies per sire, similar gain was predicted to Scenario 3 with TP=5000 and ρX=1.0. The range of increases in genetic gain predicted for terminal traits when using GS are of similar magnitude to those observed after the implementation of BLUP technology in the United Kingdom. It is concluded that implementation of GS in a terminal sire breeding goal, using purebred phenotypes alone, will be sub-optimal compared with the inclusion of novel commercial carcass phenotypes in genomic evaluations.

The value of mainstreaming human rights into health impact assessment.

PubMed

MacNaughton, Gillian; Forman, Lisa

2014-09-26

Health impact assessment (HIA) is increasingly being used to predict the health and social impacts of domestic and global laws, policies and programs. In a comprehensive review of HIA practice in 2012, the authors indicated that, given the diverse range of HIA practice, there is an immediate need to reconsider the governing values and standards for HIA implementation [1]. This article responds to this call for governing values and standards for HIA. It proposes that international human rights standards be integrated into HIA to provide a universal value system backed up by international and domestic laws and mechanisms of accountability. The idea of mainstreaming human rights into HIA is illustrated with the example of impact assessments that have been carried out to predict the potential effects of intellectual property rights in international trade agreements on the availability and affordability of medicines. The article concludes by recommending international human rights standards as a legal and ethical framework for HIA that will enhance the universal values of nondiscrimination, participation, transparency and accountability and bring legitimacy and coherence to HIA practice as well.

The Value of Mainstreaming Human Rights into Health Impact Assessment

PubMed Central

MacNaughton, Gillian; Forman, Lisa

2014-01-01

Health impact assessment (HIA) is increasingly being used to predict the health and social impacts of domestic and global laws, policies and programs. In a comprehensive review of HIA practice in 2012, the authors indicated that, given the diverse range of HIA practice, there is an immediate need to reconsider the governing values and standards for HIA implementation [1]. This article responds to this call for governing values and standards for HIA. It proposes that international human rights standards be integrated into HIA to provide a universal value system backed up by international and domestic laws and mechanisms of accountability. The idea of mainstreaming human rights into HIA is illustrated with the example of impact assessments that have been carried out to predict the potential effects of intellectual property rights in international trade agreements on the availability and affordability of medicines. The article concludes by recommending international human rights standards as a legal and ethical framework for HIA that will enhance the universal values of nondiscrimination, participation, transparency and accountability and bring legitimacy and coherence to HIA practice as well. PMID:25264683

Validity and reliability of clinical prediction rules used to screen for cervical spine injury in alert low-risk patients with blunt trauma to the neck: part 2. A systematic review from the Cervical Assessment and Diagnosis Research Evaluation (CADRE) Collaboration.

PubMed

Moser, N; Lemeunier, N; Southerst, D; Shearer, H; Murnaghan, K; Sutton, D; Côté, P

2018-06-01

To update findings of the 2000-2010 Bone and Joint Decade Task Force on Neck Pain and its Associated Disorders (Neck Pain Task Force) on the validity and reliability of clinical prediction rules used to screen for cervical spine injury in alert low-risk adult patients with blunt trauma to the neck. We searched four databases from 2005 to 2015. Pairs of independent reviewers critically appraised eligible studies using the modified QUADAS-2 and QAREL criteria. We synthesized low risk of bias studies following best evidence synthesis principles. We screened 679 citations; five had a low risk of bias and were included in our synthesis. The sensitivity of the Canadian C-spine rule ranged from 0.90 to 1.00 with negative predictive values ranging from 99 to 100%. Inter-rater reliability of the Canadian C-spine rule varied from k = 0.60 between nurses and physicians to k = 0.93 among paramedics. The inter-rater reliability of the Nexus Low-Risk Criteria was k = 0.53 between resident physicians and faculty physicians. Our review adds new evidence to the Neck Pain Task Force and supports the use of clinical prediction rules in emergency care settings to screen for cervical spine injury in alert low-risk adult patients with blunt trauma to the neck. The Canadian C-spine rule consistently demonstrated excellent sensitivity and negative predictive values. Our review, however, suggests that the reproducibility of the clinical predictions rules varies depending on the examiners level of training and experience.

Assessment of langatate material constants and temperature coefficients using SAW delay line measurements.

PubMed

Sturtevant, Blake T; Pereira da Cunha, Mauricio

2010-03-01

This paper reports on the assessment of langatate (LGT) acoustic material constants and temperature coefficients by surface acoustic wave (SAW) delay line measurements up to 130 degrees C. Based upon a full set of material constants recently reported by the authors, 7 orientations in the LGT plane with Euler angles (90 degrees, 23 degrees, Psi) were identified for testing. Each of the 7 selected orientations exhibited calculated coupling coefficients (K(2)) between 0.2% and 0.75% and also showed a large range of predicted temperature coefficient of delay (TCD) values around room temperature. Additionally, methods for estimating the uncertainty in predicted SAW propagation properties were developed and applied to SAW phase velocity and temperature coefficient of delay calculations. Starting from a purchased LGT boule, the SAW wafers used in this work were aligned, cut, ground, and polished at University of Maine facilities, followed by device fabrication and testing. Using repeated measurements of 2 devices on separate wafers for each of the 7 orientations, the room temperature SAW phase velocities were extracted with a precision of 0.1% and found to be in agreement with the predicted values. The normalized frequency change and the temperature coefficient of delay for all 7 orientations agreed with predictions within the uncertainty of the measurement and the predictions over the entire 120 degrees C temperature range measured. Two orientations, with Euler angles (90 degrees, 23 degrees, 123 degrees) and (90 degrees, 23 degrees, 119 degrees), were found to have high predicted coupling for LGT (K(2) > 0.5%) and were shown experimentally to exhibit temperature compensation in the vicinity of room temperature, with turnover temperatures at 50 and 60 degrees C, respectively.

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms.

PubMed

Morote, Juan; Del Amo, Jokin; Borque, Angel; Ars, Elisabet; Hernández, Carlos; Herranz, Felipe; Arruza, Antonio; Llarena, Roberto; Planas, Jacques; Viso, María J; Palou, Joan; Raventós, Carles X; Tejedor, Diego; Artieda, Marta; Simón, Laureano; Martínez, Antonio; Rioja, Luis A

2010-08-01

Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy. We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index. The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities. Predicting biochemical recurrence after radical prostatectomy based on clinicopathological data can be significantly improved by including patient genetic information. Copyright (c) 2010 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Developing and Validating a Predictive Model for Stroke Progression

PubMed Central

Craig, L.E.; Wu, O.; Gilmour, H.; Barber, M.; Langhorne, P.

2011-01-01

Background Progression is believed to be a common and important complication in acute stroke, and has been associated with increased mortality and morbidity. Reliable identification of predictors of early neurological deterioration could potentially benefit routine clinical care. The aim of this study was to identify predictors of early stroke progression using two independent patient cohorts. Methods Two patient cohorts were used for this study – the first cohort formed the training data set, which included consecutive patients admitted to an urban teaching hospital between 2000 and 2002, and the second cohort formed the test data set, which included patients admitted to the same hospital between 2003 and 2004. A standard definition of stroke progression was used. The first cohort (n = 863) was used to develop the model. Variables that were statistically significant (p < 0.1) on univariate analysis were included in the multivariate model. Logistic regression was the technique employed using backward stepwise regression to drop the least significant variables (p > 0.1) in turn. The second cohort (n = 216) was used to test the performance of the model. The performance of the predictive model was assessed in terms of both calibration and discrimination. Multiple imputation methods were used for dealing with the missing values. Results Variables shown to be significant predictors of stroke progression were conscious level, history of coronary heart disease, presence of hyperosmolarity, CT lesion, living alone on admission, Oxfordshire Community Stroke Project classification, presence of pyrexia and smoking status. The model appears to have reasonable discriminative properties [the median receiver-operating characteristic curve value was 0.72 (range 0.72–0.73)] and to fit well with the observed data, which is indicated by the high goodness-of-fit p value [the median p value from the Hosmer-Lemeshow test was 0.90 (range 0.50–0.92)]. Conclusion The predictive model developed in this study contains variables that can be easily collected in practice therefore increasing its usability in clinical practice. Using this analysis approach, the discrimination and calibration of the predictive model appear sufficiently high to provide accurate predictions. This study also offers some discussion around the validation of predictive models for wider use in clinical practice. PMID:22566988

A deep learning framework for improving long-range residue-residue contact prediction using a hierarchical strategy.

PubMed

Xiong, Dapeng; Zeng, Jianyang; Gong, Haipeng

2017-09-01

Residue-residue contacts are of great value for protein structure prediction, since contact information, especially from those long-range residue pairs, can significantly reduce the complexity of conformational sampling for protein structure prediction in practice. Despite progresses in the past decade on protein targets with abundant homologous sequences, accurate contact prediction for proteins with limited sequence information is still far from satisfaction. Methodologies for these hard targets still need further improvement. We presented a computational program DeepConPred, which includes a pipeline of two novel deep-learning-based methods (DeepCCon and DeepRCon) as well as a contact refinement step, to improve the prediction of long-range residue contacts from primary sequences. When compared with previous prediction approaches, our framework employed an effective scheme to identify optimal and important features for contact prediction, and was only trained with coevolutionary information derived from a limited number of homologous sequences to ensure robustness and usefulness for hard targets. Independent tests showed that 59.33%/49.97%, 64.39%/54.01% and 70.00%/59.81% of the top L/5, top L/10 and top 5 predictions were correct for CASP10/CASP11 proteins, respectively. In general, our algorithm ranked as one of the best methods for CASP targets. All source data and codes are available at http://166.111.152.91/Downloads.html . hgong@tsinghua.edu.cn or zengjy321@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Modeling sorption of divalent metal cations on hydrous manganese oxide using the diffuse double layer model

USGS Publications Warehouse

Tonkin, J.W.; Balistrieri, L.S.; Murray, J.W.

2004-01-01

Manganese oxides are important scavengers of trace metals and other contaminants in the environment. The inclusion of Mn oxides in predictive models, however, has been difficult due to the lack of a comprehensive set of sorption reactions consistent with a given surface complexation model (SCM), and the discrepancies between published sorption data and predictions using the available models. The authors have compiled a set of surface complexation reactions for synthetic hydrous Mn oxide (HMO) using a two surface site model and the diffuse double layer SCM which complements databases developed for hydrous Fe (III) oxide, goethite and crystalline Al oxide. This compilation encompasses a range of data observed in the literature for the complex HMO surface and provides an error envelope for predictions not well defined by fitting parameters for single or limited data sets. Data describing surface characteristics and cation sorption were compiled from the literature for the synthetic HMO phases birnessite, vernadite and ??-MnO2. A specific surface area of 746 m2g-1 and a surface site density of 2.1 mmol g-1 were determined from crystallographic data and considered fixed parameters in the model. Potentiometric titration data sets were adjusted to a pH1EP value of 2.2. Two site types (???XOH and ???YOH) were used. The fraction of total sites attributed to ???XOH (??) and pKa2 were optimized for each of 7 published potentiometric titration data sets using the computer program FITEQL3.2. pKa2 values of 2.35??0.077 (???XOH) and 6.06??0.040 (???YOH) were determined at the 95% confidence level. The calculated average ?? value was 0.64, with high and low values ranging from 1.0 to 0.24, respectively. pKa2 and ?? values and published cation sorption data were used subsequently to determine equilibrium surface complexation constants for Ba2+, Ca2+, Cd 2+, Co2+, Cu2+, Mg2+, Mn 2+, Ni2+, Pb2+, Sr2+ and Zn 2+. In addition, average model parameters were used to predict additional sorption data for which complementary titration data were not available. The two-site model accounts for variability in the titration data and most metal sorption data are fit well using the pKa2 and ?? values reported above. A linear free energy relationship (LFER) appears to exist for some of the metals; however, redox and cation exchange reactions may limit the prediction of surface complexation constants for additional metals using the LFER. ?? 2003 Elsevier Ltd. All rights reserved.

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

NASA Technical Reports Server (NTRS)

Epperson, David L.; Davis, Jerry M.; Bloomfield, Peter; Karl, Thomas R.; Mcnab, Alan L.; Gallo, Kevin P.

1995-01-01

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal problems for global application once global NDVI and DMSP data become available.

Modern modeling techniques had limited external validity in predicting mortality from traumatic brain injury.

PubMed

van der Ploeg, Tjeerd; Nieboer, Daan; Steyerberg, Ewout W

2016-10-01

Prediction of medical outcomes may potentially benefit from using modern statistical modeling techniques. We aimed to externally validate modeling strategies for prediction of 6-month mortality of patients suffering from traumatic brain injury (TBI) with predictor sets of increasing complexity. We analyzed individual patient data from 15 different studies including 11,026 TBI patients. We consecutively considered a core set of predictors (age, motor score, and pupillary reactivity), an extended set with computed tomography scan characteristics, and a further extension with two laboratory measurements (glucose and hemoglobin). With each of these sets, we predicted 6-month mortality using default settings with five statistical modeling techniques: logistic regression (LR), classification and regression trees, random forests (RFs), support vector machines (SVM) and neural nets. For external validation, a model developed on one of the 15 data sets was applied to each of the 14 remaining sets. This process was repeated 15 times for a total of 630 validations. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminative ability of the models. For the most complex predictor set, the LR models performed best (median validated AUC value, 0.757), followed by RF and support vector machine models (median validated AUC value, 0.735 and 0.732, respectively). With each predictor set, the classification and regression trees models showed poor performance (median validated AUC value, <0.7). The variability in performance across the studies was smallest for the RF- and LR-based models (inter quartile range for validated AUC values from 0.07 to 0.10). In the area of predicting mortality from TBI, nonlinear and nonadditive effects are not pronounced enough to make modern prediction methods beneficial. Copyright © 2016 Elsevier Inc. All rights reserved.

Validating models of target acquisition performance in the dismounted soldier context

NASA Astrophysics Data System (ADS)

Glaholt, Mackenzie G.; Wong, Rachel K.; Hollands, Justin G.

2018-04-01

The problem of predicting real-world operator performance with digital imaging devices is of great interest within the military and commercial domains. There are several approaches to this problem, including: field trials with imaging devices, laboratory experiments using imagery captured from these devices, and models that predict human performance based on imaging device parameters. The modeling approach is desirable, as both field trials and laboratory experiments are costly and time-consuming. However, the data from these experiments is required for model validation. Here we considered this problem in the context of dismounted soldiering, for which detection and identification of human targets are essential tasks. Human performance data were obtained for two-alternative detection and identification decisions in a laboratory experiment in which photographs of human targets were presented on a computer monitor and the images were digitally magnified to simulate range-to-target. We then compared the predictions of different performance models within the NV-IPM software package: Targeting Task Performance (TTP) metric model and the Johnson model. We also introduced a modification to the TTP metric computation that incorporates an additional correction for target angular size. We examined model predictions using NV-IPM default values for a critical model constant, V50, and we also considered predictions when this value was optimized to fit the behavioral data. When using default values, certain model versions produced a reasonably close fit to the human performance data in the detection task, while for the identification task all models substantially overestimated performance. When using fitted V50 values the models produced improved predictions, though the slopes of the performance functions were still shallow compared to the behavioral data. These findings are discussed in relation to the models' designs and parameters, and the characteristics of the behavioral paradigm.

Kinetic modeling of α-hydrogen abstractions from unsaturated and saturated oxygenate compounds by hydrogen atoms.

PubMed

Paraskevas, Paschalis D; Sabbe, Maarten K; Reyniers, Marie-Françoise; Papayannakos, Nikos G; Marin, Guy B

2014-10-09

Hydrogen-abstraction reactions play a significant role in thermal biomass conversion processes, as well as regular gasification, pyrolysis, or combustion. In this work, a group additivity model is constructed that allows prediction of reaction rates and Arrhenius parameters of hydrogen abstractions by hydrogen atoms from alcohols, ethers, esters, peroxides, ketones, aldehydes, acids, and diketones in a broad temperature range (300-2000 K). A training set of 60 reactions was developed with rate coefficients and Arrhenius parameters calculated by the CBS-QB3 method in the high-pressure limit with tunneling corrections using Eckart tunneling coefficients. From this set of reactions, 15 group additive values were derived for the forward and the reverse reaction, 4 referring to primary and 11 to secondary contributions. The accuracy of the model is validated upon an ab initio and an experimental validation set of 19 and 21 reaction rates, respectively, showing that reaction rates can be predicted with a mean factor of deviation of 2 for the ab initio and 3 for the experimental values. Hence, this work illustrates that the developed group additive model can be reliably applied for the accurate prediction of kinetics of α-hydrogen abstractions by hydrogen atoms from a broad range of oxygenates.

Protein Solvent-Accessibility Prediction by a Stacked Deep Bidirectional Recurrent Neural Network.

PubMed

Zhang, Buzhong; Li, Linqing; Lü, Qiang

2018-05-25

Residue solvent accessibility is closely related to the spatial arrangement and packing of residues. Predicting the solvent accessibility of a protein is an important step to understand its structure and function. In this work, we present a deep learning method to predict residue solvent accessibility, which is based on a stacked deep bidirectional recurrent neural network applied to sequence profiles. To capture more long-range sequence information, a merging operator was proposed when bidirectional information from hidden nodes was merged for outputs. Three types of merging operators were used in our improved model, with a long short-term memory network performing as a hidden computing node. The trained database was constructed from 7361 proteins extracted from the PISCES server using a cut-off of 25% sequence identity. Sequence-derived features including position-specific scoring matrix, physical properties, physicochemical characteristics, conservation score and protein coding were used to represent a residue. Using this method, predictive values of continuous relative solvent-accessible area were obtained, and then, these values were transformed into binary states with predefined thresholds. Our experimental results showed that our deep learning method improved prediction quality relative to current methods, with mean absolute error and Pearson's correlation coefficient values of 8.8% and 74.8%, respectively, on the CB502 dataset and 8.2% and 78%, respectively, on the Manesh215 dataset.

A Comparison of EAST Shock-Tube Radiation Measurements with a New Air Radiation Model

NASA Technical Reports Server (NTRS)

Johnston, Christopher O.

2008-01-01

This paper presents a comparison between the recent EAST shock tube radiation measurements (Grinstead et al., AIAA 2008-1244) and the HARA radiation model. The equilibrium and nonequilibrium radiation measurements are studied for conditions relevant to lunar-return shock-layers; specifically shock velocities ranging from 9 to 11 kilometers per second at initial pressures of 0.1 and 0.3 Torr. The simulated shock-tube flow is assumed one-dimensional and is calculated using the LAURA code, while a detailed nonequilibrium radiation prediction is obtained in an uncoupled manner from the HARA code. The measured and predicted intensities are separated into several spectral ranges to isolate significant spectral features, mainly strong atomic line multiplets. The equations and physical data required for the prediction of these strong atomic lines are reviewed and their uncertainties identified. The 700-1020 nm wavelength range, which accounts for roughly 30% of the radiative flux to a peak-heating lunar return shock-layer, is studied in detail and the measurements and predictions are shown to agree within 15% in equilibrium. The plus or minus 1.5% uncertainty on the measured shock velocity is shown to cause up to a plus or minus 30% difference in the predicted radiation. This band of predictions contains the measured values in almost all cases. For the highly nonequilibrium 0.1 Torr cases, the nonequilibrium radiation peaks are under-predicted by about half. This under-prediction is considered acceptable when compared to the order-of-magnitude over-prediction obtained using a Boltzmann population of electronic states. The reasonable comparison in the nonequilibrium regions provides validation for both the non-Boltzmann modeling in HARA and the thermochemical nonequilibrium modeling in LAURA. The N2 (+)(1-) and N2(2+) molecular band systems are studied in the 290 480 nm wavelength range for both equilibrium and nonequilibrium regimes. The non-Boltzmann rate models for these systems, which have significant uncertainties, are tuned to improve the comparison with measurements.

Predictive displays for a process-control schematic interface.

PubMed

Yin, Shanqing; Wickens, Christopher D; Helander, Martin; Laberge, Jason C

2015-02-01

Our objective was to examine the extent to which increasing precision of predictive (rate of change) information in process control will improve performance on a simulated process-control task. Predictive displays have been found to be useful in process control (as well as aviation and maritime industries). However, authors of prior research have not examined the extent to which predictive value is increased by increasing predictor resolution, nor has such research tied potential improvements to changes in process control strategy. Fifty nonprofessional participants each controlled a simulated chemical mixture process (honey mixer simulation) that simulated the operations found in process control. Participants in each of five groups controlled with either no predictor or a predictor ranging in the resolution of prediction of the process. Increasing detail resolution generally increased the benefit of prediction over the control condition although not monotonically so. The best overall performance, combining quality and predictive ability, was obtained by the display of intermediate resolution. The two displays with the lowest resolution were clearly inferior. Predictors with higher resolution are of value but may trade off enhanced sensitivity to variable change (lower-resolution discrete state predictor) with smoother control action (higher-resolution continuous predictors). The research provides guidelines to the process-control industry regarding displays that can most improve operator performance.

Collective behaviour in vertebrates: a sensory perspective

PubMed Central

Collignon, Bertrand; Fernández-Juricic, Esteban

2016-01-01

Collective behaviour models can predict behaviours of schools, flocks, and herds. However, in many cases, these models make biologically unrealistic assumptions in terms of the sensory capabilities of the organism, which are applied across different species. We explored how sensitive collective behaviour models are to these sensory assumptions. Specifically, we used parameters reflecting the visual coverage and visual acuity that determine the spatial range over which an individual can detect and interact with conspecifics. Using metric and topological collective behaviour models, we compared the classic sensory parameters, typically used to model birds and fish, with a set of realistic sensory parameters obtained through physiological measurements. Compared with the classic sensory assumptions, the realistic assumptions increased perceptual ranges, which led to fewer groups and larger group sizes in all species, and higher polarity values and slightly shorter neighbour distances in the fish species. Overall, classic visual sensory assumptions are not representative of many species showing collective behaviour and constrain unrealistically their perceptual ranges. More importantly, caution must be exercised when empirically testing the predictions of these models in terms of choosing the model species, making realistic predictions, and interpreting the results. PMID:28018616

Range prediction for tissue mixtures based on dual-energy CT

NASA Astrophysics Data System (ADS)

Möhler, Christian; Wohlfahrt, Patrick; Richter, Christian; Greilich, Steffen

2016-06-01

The use of dual-energy CT (DECT) potentially decreases range uncertainties in proton and ion therapy treatment planning via determination of the involved physical target quantities. For eventual clinical application, the correct treatment of tissue mixtures and heterogeneities is an essential feature, as they naturally occur within a patient’s CT. Here, we present how existing methods for DECT-based ion-range prediction can be modified in order to incorporate proper mixing behavior on several structural levels. Our approach is based on the factorization of the stopping-power ratio into the relative electron density and the relative stopping number. The latter is confined for tissue between about 0.95 and 1.02 at a therapeutic beam energy of 200 MeV u-1 and depends on the I-value. We show that convenient mixing and averaging properties arise by relating the relative stopping number to the relative cross section obtained by DECT. From this, a maximum uncertainty of the stopping-power ratio prediction below 1% is suggested for arbitrary mixtures of human body tissues.

SU-E-T-98: An Analysis of TG-51 Electron Beam Calibration Correction Factor Uncertainty

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

Lee, P; Alvarez, P; Taylor, P

Purpose: To analyze the uncertainty of the TG-51 electron beam calibration correction factors for farmer type ion chambers currently used by institutions visited by IROC Houston. Methods: TG-51 calibration data were collected from 181 institutions visited by IROC Houston physicists for 1174 and 197 distinct electron beams from modern Varian and Elekta accelerators, respectively. Data collected and analyzed included ion chamber make and model, nominal energy, N{sub D,w}, I{sub 50}, R{sub 50}, k’R{sub 50}, d{sub ref}, P{sub gr} and pdd(d{sub ref}). k’R{sub 50} data for parallel plate chambers were excluded from the analysis. Results: Unlike photon beams, electron nominal energymore » is a poor indicator of the actual energy as evidenced by the range of R{sub 50} values for each electron beam energy (6–22MeV). The large range in R{sub 50} values resulted k’R{sub 50} values with a small standard deviation but large range between maximum value used and minimum value (0.001–0.029) used for a specific Varian nominal energy. Varian data showed more variability in k’R{sub 50} values than the Elekta data (0.001–0.014). Using the observed range of R{sub 50} values, the maximum spread in k’R{sub 50} values was determined by IROC Houston and compared to the spread of k’R{sub 50} values used in the community. For Elekta linacs the spreads were equivalent, but for Varian energies of 6 to 16MeV, the community spread was 2 to 6 times larger. Community P{sub gr} values had a much larger range of values for 6 and 9 MeV values than predicted. The range in Varian pdd(d{sub ref} ) used by the community for low energies was large, (1.4–4.9 percent), when it should have been very close to unity. Exradin, PTW Roos and PTW farmer chambers N{sub D,w} values showed the largest spread, ≥11 percent. Conclusion: While the vast majority of electron beam calibration correction factors used are accurate, there is a surprising spread in some of the values used.« less

A physiologically based pharmacokinetic model to predict disposition of CYP2D6 and CYP1A2 metabolized drugs in pregnant women.

PubMed

Ke, Alice Ban; Nallani, Srikanth C; Zhao, Ping; Rostami-Hodjegan, Amin; Isoherranen, Nina; Unadkat, Jashvant D

2013-04-01

Conducting pharmacokinetic (PK) studies in pregnant women is challenging. Therefore, we asked if a physiologically based pharmacokinetic (PBPK) model could be used to evaluate different dosing regimens for pregnant women. We refined and verified our previously published pregnancy PBPK model by incorporating cytochrome P450 CYP1A2 suppression (based on caffeine PK) and CYP2D6 induction (based on metoprolol PK) into the model. This model accounts for gestational age-dependent changes in maternal physiology and hepatic CYP3A activity. For verification, the disposition of CYP1A2-metabolized drug theophylline (THEO) and CYP2D6-metabolized drugs paroxetine (PAR), dextromethorphan (DEX), and clonidine (CLO) during pregnancy was predicted. Our PBPK model successfully predicted THEO disposition during the third trimester (T3). Predicted mean postpartum to third trimester (PP:T3) ratios of THEO area under the curve (AUC), maximum plasma concentration, and minimum plasma concentration were 0.76, 0.95, and 0.66 versus observed values 0.75, 0.89, and 0.72, respectively. The predicted mean PAR steady-state plasma concentration (Css) ratio (PP:T3) was 7.1 versus the observed value 3.7. Predicted mean DEX urinary ratio (UR) (PP:T3) was 2.9 versus the observed value 1.9. Predicted mean CLO AUC ratio (PP:T3) was 2.2 versus the observed value 1.7. Sensitivity analysis suggested that a 100% induction of CYP2D6 during T3 was required to recover the observed PP:T3 ratios of PAR Css, DEX UR, and CLO AUC. Based on these data, it is prudent to conclude that the magnitude of hepatic CYP2D6 induction during T3 ranges from 100 to 200%. Our PBPK model can predict the disposition of CYP1A2, 2D6, and 3A drugs during pregnancy.

A Physiologically Based Pharmacokinetic Model to Predict Disposition of CYP2D6 and CYP1A2 Metabolized Drugs in Pregnant Women

PubMed Central

Ke, Alice Ban; Nallani, Srikanth C.; Zhao, Ping; Rostami-Hodjegan, Amin; Isoherranen, Nina

2013-01-01

Conducting pharmacokinetic (PK) studies in pregnant women is challenging. Therefore, we asked if a physiologically based pharmacokinetic (PBPK) model could be used to evaluate different dosing regimens for pregnant women. We refined and verified our previously published pregnancy PBPK model by incorporating cytochrome P450 CYP1A2 suppression (based on caffeine PK) and CYP2D6 induction (based on metoprolol PK) into the model. This model accounts for gestational age–dependent changes in maternal physiology and hepatic CYP3A activity. For verification, the disposition of CYP1A2–metabolized drug theophylline (THEO) and CYP2D6–metabolized drugs paroxetine (PAR), dextromethorphan (DEX), and clonidine (CLO) during pregnancy was predicted. Our PBPK model successfully predicted THEO disposition during the third trimester (T3). Predicted mean postpartum to third trimester (PP:T3) ratios of THEO area under the curve (AUC), maximum plasma concentration, and minimum plasma concentration were 0.76, 0.95, and 0.66 versus observed values 0.75, 0.89, and 0.72, respectively. The predicted mean PAR steady-state plasma concentration (Css) ratio (PP:T3) was 7.1 versus the observed value 3.7. Predicted mean DEX urinary ratio (UR) (PP:T3) was 2.9 versus the observed value 1.9. Predicted mean CLO AUC ratio (PP:T3) was 2.2 versus the observed value 1.7. Sensitivity analysis suggested that a 100% induction of CYP2D6 during T3 was required to recover the observed PP:T3 ratios of PAR Css, DEX UR, and CLO AUC. Based on these data, it is prudent to conclude that the magnitude of hepatic CYP2D6 induction during T3 ranges from 100 to 200%. Our PBPK model can predict the disposition of CYP1A2, 2D6, and 3A drugs during pregnancy. PMID:23355638

3He(α, γ)7Be cross section in a wide energy range

NASA Astrophysics Data System (ADS)

Szücs, Tamás; Gyürky, György; Halász, Zoltán; Kiss, Gábor Gy.; Fülöp, Zsolt

2018-01-01

The reaction rate of the 3He(α,γ)7 Be reaction is important both in the Big Bang Nucleosynthesis (BBN) and in the Solar hydrogen burning. There have been a lot of experimental and theoretical efforts to determine this reaction rate with high precision. Some long standing issues have been solved by the more precise investigations, like the different S(0) values predicted by the activation and in-beam measurement. However, the recent, more detailed astrophysical model predictions require the reaction rate with even higher precision to unravel new issues like the Solar composition. One way to increase the precision is to provide a comprehensive dataset in a wide energy range, extending the experimental cross section database of this reaction. This paper presents a new cross section measurement between Ecm = 2.5 - 4.4 MeV, in an energy range which extends above the 7Be proton separation threshold.

Falls Risk Prediction for Older Inpatients in Acute Care Medical Wards: Is There an Interest to Combine an Early Nurse Assessment and the Artificial Neural Network Analysis?

PubMed

Beauchet, O; Noublanche, F; Simon, R; Sekhon, H; Chabot, J; Levinoff, E J; Kabeshova, A; Launay, C P

2018-01-01

Identification of the risk of falls is important among older inpatients. This study aims to examine performance criteria (i.e.; sensitivity, specificity, positive predictive value, negative predictive value and accuracy) for fall prediction resulting from a nurse assessment and an artificial neural networks (ANNs) analysis in older inpatients hospitalized in acute care medical wards. A total of 848 older inpatients (mean age, 83.0±7.2 years; 41.8% female) admitted to acute care medical wards in Angers University hospital (France) were included in this study using an observational prospective cohort design. Within 24 hours after admission of older inpatients, nurses performed a bedside clinical assessment. Participants were separated into non-fallers and fallers (i.e.; ≥1 fall during hospitalization stay). The analysis was conducted using three feed forward ANNs (multilayer perceptron [MLP], averaged neural network, and neuroevolution of augmenting topologies [NEAT]). Seventy-three (8.6%) participants fell at least once during their hospital stay. ANNs showed a high specificity, regardless of which ANN was used, and the highest value reported was with MLP (99.8%). In contrast, sensitivity was lower, with values ranging between 98.4 to 14.8%. MLP had the highest accuracy (99.7). Performance criteria for fall prediction resulting from a bedside nursing assessment and an ANNs analysis was associated with a high specificity but a low sensitivity, suggesting that this combined approach should be used more as a diagnostic test than a screening test when considering older inpatients in acute care medical ward.

Nutritional evaluation of commercial dry dog foods by near infrared reflectance spectroscopy.

PubMed

Alomar, D; Hodgkinson, S; Abarzúa, D; Fuchslocher, R; Alvarado, C; Rosales, E

2006-06-01

Near infrared reflectance spectroscopy (NIRS) was used to predict the nutritional value of dog foods sold in Chile. Fifty-nine dry foods for adult and growing dogs were collected, ground and scanned across the visible/NIR range and subsequently analysed for dry matter (DM), crude protein (CP), crude fibre (CF), total fat, linoleic acid, gross energy (GE), estimated metabolizable energy (ME) and several amino acids and minerals. Calibration equations were developed by modified partial least squares regression, and tested by cross-validation. Standard error of cross validation (SE(CV)) and coefficient of determination of cross validation (SE(CV)) were used to select best equations. Equations with good predicting accuracy were obtained for DM, CF, CP, GE and fat. Corresponding values for and SE(CV) were 0.96 and 1.7 g/kg, 0.91 and 3.1 g/kg, 0.99 and 5.0 g/kg, 0.93 and 0.26 MJ/kg, 0.89 and 12.4 g/kg. Several amino acids were also well predicted, such as arginine, leucine, isoleucine, phenylalanine-tyrosine (combined), threonine and valine, with values for and SE(CV) (g/kg) of 0.89 and 0.9, 0.94 and 1.3, 0.91 and 0.5, 0.95 and 0.9, 0.91 and 0.5, 0.93 and 0.5. Intermediate values, appropriate for ranking purposes, were obtained for ME, histidine, lysine and methionine-cysteine. Tryptophan, minerals or linoleic acid were not acceptably predicted, irrespective of the mathematical treatment applied. It is concluded that NIR can be successfully used to predict important nutritional characteristics of commercial dog foods.

Progression of coronary artery calcification seems to be inevitable, but predictable - results of the Heinz Nixdorf Recall (HNR) study.

PubMed

Erbel, Raimund; Lehmann, Nils; Churzidse, Sofia; Rauwolf, Michael; Mahabadi, Amir A; Möhlenkamp, Stefan; Moebus, Susanne; Bauer, Marcus; Kälsch, Hagen; Budde, Thomas; Montag, Michael; Schmermund, Axel; Stang, Andreas; Führer-Sakel, Dagmar; Weimar, Christian; Roggenbuck, Ulla; Dragano, Nico; Jöckel, Karl-Heinz

2014-11-07

Coronary artery calcification (CAC), as a sign of atherosclerosis, can be detected and progression quantified using computed tomography (CT). We develop a tool for predicting CAC progression. In 3481 participants (45-74 years, 53.1% women) CAC percentiles at baseline (CACb) and after five years (CAC₅y) were evaluated, demonstrating progression along gender-specific percentiles, which showed exponentially shaped age-dependence. Using quantile regression on the log-scale (log(CACb+1)) we developed a tool to individually predict CAC₅y, and compared to observed CAC₅y. The difference between observed and predicted CAC₅y (log-scale, mean±SD) was 0.08±1.11 and 0.06±1.29 in men and women. Agreement reached a kappa-value of 0.746 (95% confidence interval: 0.732-0.760) and concordance correlation (log-scale) of 0.886 (0.879-0.893). Explained variance of observed by predicted log(CAC₅y+1) was 80.1% and 72.0% in men and women, and 81.0 and 73.6% including baseline risk factors. Evaluating the tool in 1940 individuals with CACb>0 and CACb<400 at baseline, of whom 242 (12.5%) developed CAC₅y>400, yielded a sensitivity of 59.5%, specificity 96.1%, (+) and (-) predictive values of 68.3% and 94.3%. A pre-defined acceptance range around predicted CAC₅y contained 68.1% of observed CAC₅y; only 20% were expected by chance. Age, blood pressure, lipid-lowering medication, diabetes, and smoking contributed to progression above the acceptance range in men and, excepting age, in women. CAC nearly inevitably progresses with limited influence of cardiovascular risk factors. This allowed the development of a mathematical tool for prediction of individual CAC progression, enabling anticipation of the age when CAC thresholds of high risk are reached. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Cardiology.

Glycated hemoglobin measurement and prediction of cardiovascular disease.

PubMed

Di Angelantonio, Emanuele; Gao, Pei; Khan, Hassan; Butterworth, Adam S; Wormser, David; Kaptoge, Stephen; Kondapally Seshasai, Sreenivasa Rao; Thompson, Alex; Sarwar, Nadeem; Willeit, Peter; Ridker, Paul M; Barr, Elizabeth L M; Khaw, Kay-Tee; Psaty, Bruce M; Brenner, Hermann; Balkau, Beverley; Dekker, Jacqueline M; Lawlor, Debbie A; Daimon, Makoto; Willeit, Johann; Njølstad, Inger; Nissinen, Aulikki; Brunner, Eric J; Kuller, Lewis H; Price, Jackie F; Sundström, Johan; Knuiman, Matthew W; Feskens, Edith J M; Verschuren, W M M; Wald, Nicholas; Bakker, Stephan J L; Whincup, Peter H; Ford, Ian; Goldbourt, Uri; Gómez-de-la-Cámara, Agustín; Gallacher, John; Simons, Leon A; Rosengren, Annika; Sutherland, Susan E; Björkelund, Cecilia; Blazer, Dan G; Wassertheil-Smoller, Sylvia; Onat, Altan; Marín Ibañez, Alejandro; Casiglia, Edoardo; Jukema, J Wouter; Simpson, Lara M; Giampaoli, Simona; Nordestgaard, Børge G; Selmer, Randi; Wennberg, Patrik; Kauhanen, Jussi; Salonen, Jukka T; Dankner, Rachel; Barrett-Connor, Elizabeth; Kavousi, Maryam; Gudnason, Vilmundur; Evans, Denis; Wallace, Robert B; Cushman, Mary; D'Agostino, Ralph B; Umans, Jason G; Kiyohara, Yutaka; Nakagawa, Hidaeki; Sato, Shinichi; Gillum, Richard F; Folsom, Aaron R; van der Schouw, Yvonne T; Moons, Karel G; Griffin, Simon J; Sattar, Naveed; Wareham, Nicholas J; Selvin, Elizabeth; Thompson, Simon G; Danesh, John

2014-03-26

The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. Analysis of individual-participant data available from 73 prospective studies involving 294,998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥ 7.5%) risk. During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20,840 incident fatal and nonfatal CVD outcomes (13,237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.

Assessing the predictive value of means-end-chain theory: an application to meat product choice by Australian middle-aged women.

PubMed

Le Page, Aurore; Cox, David N; Georgie Russell, C; Leppard, Phillip I

2005-04-01

Means-end-chain theory seeks to understand how consumers make links between products and self-relevant consequences and values. To date, means-end-chain theory has remained a descriptive process and has not been applied to predicting product choice. Within the context of cooking meat, the main objective of this research was to assess the predictive value of the means-end-chain theory. In a two part study, we first undertook a laddering study (n=58 middle-aged women) focusing on cooking three different meat products, using small group administration and paper-and-pencil responses to elicit mean-end-chains (MEC). In the second part, we considered all the MEC independently and incorporated them into a questionnaire, which was also comprised of psycho-social predictors from a range of behavioural models. Responses were elicited from a sample of middle-aged women (n=247). Although MEC explained little of the variance in self-reported behaviour, they were shown to be an important predictor of attitude. Contrary to expectations, the least abstract levels of the MEC appeared to be the most predictive. A critical examination of the data suggested a need to reconsider the means-end-chain theory since it appears to take the respondents beyond their own awareness of their behaviours.

Structure-Activity Relationship Models for Rat Carcinogenesis and Assessing the Role Mutagens Play in Model Predictivity

PubMed Central

Carrasquer, C. Alex; Batey, Kaylind; Qamar, Shahid; Cunningham, Albert R.; Cunningham, Suzanne L.

2016-01-01

We previously demonstrated that fragment based cat-SAR carcinogenesis models consisting solely of mutagenic or non-mutagenic carcinogens varied greatly in terms of their predictive accuracy. This led us to investigate how well the rat cancer cat-SAR model predicted mutagens and non-mutagens in their learning set. Four rat cancer cat-SAR models were developed: Complete Rat, Transgender Rat, Male Rat, and Female Rat, with leave-one-out (LOO) validation concordance values of 69%, 74%, 67%, and 73%, respectively. The mutagenic carcinogens produced concordance values in the range of 69–76% as compared to only 47–53% for non-mutagenic carcinogens. As a surrogate for mutagenicity comparisons between single site and multiple site carcinogen SAR models was analyzed. The LOO concordance values for models consisting of 1-site, 2-site, and 4+-site carcinogens were 66%, 71%, and 79%, respectively. As expected, the proportion of mutagens to non-mutagens also increased, rising from 54% for 1-site to 80% for 4+-site carcinogens. This study demonstrates that mutagenic chemicals, in both SAR learning sets and test sets, are influential in assessing model accuracy. This suggests that SAR models for carcinogens may require a two-step process in which mutagenicity is first determined before carcinogenicity can be accurately predicted. PMID:24697549

Predictive value of ventilatory inflection points determined under field conditions.

PubMed

Heyde, Christian; Mahler, Hubert; Roecker, Kai; Gollhofer, Albert

2016-01-01

The aim of this study was to evaluate the predictive potential provided by two ventilatory inflection points (VIP1 and VIP2) examined in field without using gas analysis systems and uncomfortable facemasks. A calibrated respiratory inductance plethysmograph (RIP) and a computerised routine were utilised, respectively, to derive ventilation and to detect VIP1 and VIP2 during a standardised field ramp test on a 400 m running track on 81 participants. In addition, average running speed of a competitive 1000 m run (S1k) was observed as criterion. The predictive value of running speed at VIP1 (SVIP1) and the speed range between VIP1 and VIP2 in relation to VIP2 (VIPSPAN) was analysed via regression analysis. VIPSPAN rather than running speed at VIP2 (SVIP2) was operationalised as a predictor to consider the covariance between SVIP1 and SVIP2. SVIP1 and VIPSPAN, respectively, provided 58.9% and 22.9% of explained variance in regard to S1k. Considering covariance, the timing of two ventilatory inflection points provides predictive value in regard to a competitive 1000 m run. This is the first study to apply computerised detection of ventilatory inflection points in a field setting independent on measurements of the respiratory gas exchange and without using any facemasks.

External validation of the NUn score for predicting anastomotic leakage after oesophageal resection.

PubMed

Paireder, Matthias; Jomrich, Gerd; Asari, Reza; Kristo, Ivan; Gleiss, Andreas; Preusser, Matthias; Schoppmann, Sebastian F

2017-08-29

Early detection of anastomotic leakage (AL) after oesophageal resection for malignancy is crucial. This retrospective study validates a risk score, predicting AL, which includes C-reactive protein, albumin and white cell count in patients undergoing oesophageal resection between 2003 and 2014. For validation of the NUn score a receiver operating characteristic (ROC) curve is estimated. Area under the ROC curve (AUC) is reported with 95% confidence interval (CI). Among 258 patients (79.5% male) 32 patients showed signs of anastomotic leakage (12.4%). NUn score in our data has a median of 9.3 (range 6.2-17.6). The odds ratio for AL was 1.31 (CI 1.03-1.67; p = 0.028). AUC for AL was 0.59 (CI 0.47-0.72). Using the original cutoff value of 10, the sensitivity was 45.2% an the specificity was 73.8%. This results in a positive predictive value of 19.4% and a negative predictive value of 90.6%. The proportion of variation in AL occurrence, which is explained by the NUn score, was 2.5% (PEV = 0.025). This study provides evidence for an external validation of a simple risk score for AL after oesophageal resection. In this cohort, the NUn score is not useful due to its poor discrimination.

Random Predictor Models for Rigorous Uncertainty Quantification: Part 1

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean and the variance of the model's parameters, thus of the predicted output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, can be bounded tightly and rigorously.

Influence of high magnetic field on access to stationary H-modes and pedestal characteristics in Alcator C-Mod

NASA Astrophysics Data System (ADS)

Tolman, E. A.; Hughes, J. W.; Wolfe, S. M.; Wukitch, S. J.; LaBombard, B.; Hubbard, A. E.; Marmar, E. S.; Snyder, P. B.; Schmidtmayr, M.

2018-04-01

Recent Alcator C-Mod experiments have explored access to and characteristics of H-modes at magnetic fields approaching 8 T, the highest field achieved to date in a diverted tokamak. The H-modes originated from L-mode densities ranging from 1.1 × 1020~m-3 to 2.8 × 1020~m-3 , allowing insight into the density dependence of the H-mode power threshold at high magnetic field. This dependence is compared to predictions from the ITPA scaling law ([1]), finding that the law is approximately accurate at 7.8 T. However, the law underpredicted the high density H-mode threshold at lower magnetic field in previous C-Mod experiments ([2]), suggesting that the overall dependence of the threshold on magnetic field is weaker than predicted by the scaling law. The threshold data at 7.8 T also indicates that the onset of a low density branch at this magnetic field on C-Mod occurs below 1.4 × 1020~m-3 , which is lower than predicted by an existing model for low density branch onset. The H-modes achieved steady-state densities ranging from 2.3 × 1020 ~m-3 to 4.4 × 1020 ~m-3 , and higher transient densities, and had values of q 95 from 3.3 to 6.0. This parameter range allowed the achievement of all three types of H-mode routinely observed at lower magnetic field on C-Mod: the stationary, ELM-suppressed Enhanced D α (EDA) regime, seen at high densities and high values of q 95; the nonstationary ELM-free regime, seen at lower densities and values of q 95; and the ELMy regime, seen at low density, moderate q 95, and specialized plasma shape. The parameter space in which these regimes occur at 7.8 T is consistent with lower magnetic field experience. Pressure pedestal height at 7.8 T is compared to EPED [3, 4] predictions, and a scaling law for EDA density pedestal height developed between 4.5 T and 6.0 T is updated to include fields from 2.7 T to 7.8 T. Overall, this analysis increases confidence in the use of low magnetic field experience to predict some elements of high magnetic field tokamak behavior.

The cost of being valuable: predictors of extinction risk in marine invertebrates exploited as luxury seafood

PubMed Central

Purcell, Steven W.; Polidoro, Beth A.; Hamel, Jean-François; Gamboa, Ruth U.; Mercier, Annie

2014-01-01

Extinction risk has been linked to biological and anthropogenic variables. Prediction of extinction risk in valuable fauna may not follow mainstream drivers when species are exploited for international markets. We use results from an International Union for Conservation of Nature Red List assessment of extinction risk in all 377 known species of sea cucumber within the order Aspidochirotida, many of which are exploited worldwide as luxury seafood for Asian markets. Extinction risk was primarily driven by high market value, compounded by accessibility and familiarity (well known) in the marketplace. Extinction risk in marine animals often relates closely to body size and small geographical range but our study shows a clear exception. Conservation must not lose sight of common species, especially those of high value. Greater human population density and poorer economies in the geographical ranges of endangered species illustrate that anthropogenic variables can also predict extinction risks in marine animals. Local-level regulatory measures must prevent opportunistic exploitation of high-value species. Trade agreements, for example CITES, may aid conservation but will depend on international technical support to low-income tropical countries. The high proportion of data deficient species also stresses a need for research on the ecology and population demographics of unglamorous invertebrates. PMID:24598425

Enhanced power factor via the control of structural phase transition in SnSe

PubMed Central

Yu, Hulei; Dai, Shuai; Chen, Yue

2016-01-01

Tin selenide has attracted much research interest due to its unprecedentedly high thermoelectric figure of merit (ZT). For real applications, it is desirable to increase the ZT value in the lower-temperature range, as the peak ZT value currently exists near the melting point. It is shown in this paper that the structural phase transition plays an important role in boosting the ZT value of SnSe in the lower-temperature range, as the Cmcm phase is found to have a much higher power factor than the Pnma phase. Furthermore, hydrostatic pressure is predicted to be extremely effective in tuning the phase transition temperature based on ab-initio molecular dynamic simulations; a remarkable decrease in the phase transition temperature is found when a hydrostatic pressure is applied. Dynamical stabilities are investigated based on phonon calculations, providing deeper insight into the pressure effects. Accurate band structures are obtained using the modified Becke-Johnson correction, allowing reliable prediction of the electrical transport properties. The effects of hydrostatic pressure on the thermal transport properties are also discussed. Hydrostatic pressure is shown to be efficient in manipulating the transport properties via the control of phase transition temperature in SnSe, paving a new path for enhancing its thermoelectric efficiency. PMID:27193260

The cost of being valuable: predictors of extinction risk in marine invertebrates exploited as luxury seafood.

PubMed

Purcell, Steven W; Polidoro, Beth A; Hamel, Jean-François; Gamboa, Ruth U; Mercier, Annie

2014-04-22

Extinction risk has been linked to biological and anthropogenic variables. Prediction of extinction risk in valuable fauna may not follow mainstream drivers when species are exploited for international markets. We use results from an International Union for Conservation of Nature Red List assessment of extinction risk in all 377 known species of sea cucumber within the order Aspidochirotida, many of which are exploited worldwide as luxury seafood for Asian markets. Extinction risk was primarily driven by high market value, compounded by accessibility and familiarity (well known) in the marketplace. Extinction risk in marine animals often relates closely to body size and small geographical range but our study shows a clear exception. Conservation must not lose sight of common species, especially those of high value. Greater human population density and poorer economies in the geographical ranges of endangered species illustrate that anthropogenic variables can also predict extinction risks in marine animals. Local-level regulatory measures must prevent opportunistic exploitation of high-value species. Trade agreements, for example CITES, may aid conservation but will depend on international technical support to low-income tropical countries. The high proportion of data deficient species also stresses a need for research on the ecology and population demographics of unglamorous invertebrates.

Using liver enzymes as screening tests to predict mortality risk.

PubMed

Fulks, Michael; Stout, Robert L; Dolan, Vera F

2008-01-01

Determine the relationship between liver function test results (GGT, alkaline phosphatase, AST, and ALT) and all-cause mortality in life insurance applicants. By use of the Social Security Master Death File, mortality was examined in 1,905,664 insurance applicants for whom blood samples were submitted to the Clinical Reference Laboratory. There were 50,174 deaths observed in this study population. Results were stratified by 3 age/sex groups: females, age <60; males, age <60; and all, age 60+. Liver function test values were grouped using percentiles of their distribution in these 3 age/sex groups, as well as ranges of actual values. Using the risk of the middle 50% of the population by distribution as a reference, relative mortality observed for GGT and alkaline phosphatase was linear with a steep slope from very low to relatively high values. Relative mortality was increased at lower values for both AST and ALT. ALT did not predict mortality for values above the middle 50% of its distribution. GGT and alkaline phosphatase are significant predictors of mortality risk for all values. ALT is still useful for triggering further testing for hepatitis, but AST should be used instead to assess mortality risk linked with transaminases.

Predicting maximal strength of quadriceps from submaximal performance in individuals with knee joint osteoarthritis.

PubMed

McNair, Peter J; Colvin, Matt; Reid, Duncan

2011-02-01

To compare the accuracy of 12 maximal strength (1-repetition maximum [1-RM]) equations for predicting quadriceps strength in people with osteoarthritis (OA) of the knee joint. Eighteen subjects with OA of the knee joint attended a rehabilitation gymnasium on 3 occasions: 1) a familiarization session, 2) a session where the 1-RM of the quadriceps was established using a weights machine for an open-chain knee extension exercise and a leg press exercise, and 3) a session where the subjects performed with a load at which they could lift for approximately 10 repetitions only. The data were used in 12 prediction equations to calculate 1-RM strength and compared to the actual 1-RM data. Data were examined using Bland and Altman graphs and statistics, intraclass correlation coefficients (ICCs), and typical error values between the actual 1-RM and the respective 1-RM prediction equation data. Difference scores (predicted 1-RM--actual 1-RM) across the injured and control legs were also compared. For the knee extension exercise, the Brown, Brzycki, Epley, Lander, Mayhew et al, Poliquin, and Wathen prediction equations demonstrated the greatest levels of predictive accuracy. All of the ICCs were high (range 0.96–0.99), and typical errors were between 3% and 4%. For the knee press exercise, the Adams, Berger, Kemmler et al, and O'Conner et al equations demonstrated the greatest levels of predictive accuracy. All of the ICCs were high (range 0.95-0.98), and the typical errors ranged from 5.9-6.3%. This study provided evidence supporting the use of prediction equations to assess maximal strength in individuals with a knee joint with OA.

Geographical distribution of reference value of aging people's left ventricular end systolic diameter based on the support vector regression.

PubMed

Han, Xiao; Ge, Miao; Dong, Jie; Xue, Ranying; Wang, Zixuan; He, Jinwei

2014-09-01

The aim of this paper is to analyze the geographical distribution of reference value of aging people's left ventricular end systolic diameter (LVDs), and to provide a scientific basis for clinical examination. The study is focus on the relationship between reference value of left ventricular end systolic diameter of aging people and 14 geographical factors, selecting 2495 samples of left ventricular end systolic diameter (LVDs) of aging people in 71 units of China, in which including 1620 men and 875 women. By using the Moran's I index to make sure the relationship between the reference values and spatial geographical factors, extracting 5 geographical factors which have significant correlation with left ventricular end systolic diameter for building the support vector regression, detecting by the method of paired sample t test to make sure the consistency between predicted and measured values, finally, makes the distribution map through the disjunctive kriging interpolation method and fits the three-dimensional trend of normal reference value. It is found that the correlation between the extracted geographical factors and the reference value of left ventricular end systolic diameter is quite significant, the 5 indexes respectively are latitude, annual mean air temperature, annual mean relative humidity, annual precipitation amount, annual range of air temperature, the predicted values and the observed ones are in good conformity, there is no significant difference at 95% degree of confidence. The overall trend of predicted values increases from west to east, increases first and then decreases from north to south. If geographical values are obtained in one region, the reference value of left ventricular end systolic diameter of aging people in this region can be obtained by using the support vector regression model. It could be more scientific to formulate the different distributions on the basis of synthesizing the physiological and the geographical factors. -Use Moran's index to analyze the spatial correlation. -Choose support vector machine to build model that overcome complexity of variables. -Test normal distribution of predicted data to guarantee the interpolation results. -Through trend analysis to explain the changes of reference value clearly. Copyright © 2014 Elsevier Inc. All rights reserved.

Nonlinear times series analysis of epileptic human electroencephalogram (EEG)

NASA Astrophysics Data System (ADS)

Li, Dingzhou

The problem of seizure anticipation in patients with epilepsy has attracted significant attention in the past few years. In this paper we discuss two approaches, using methods of nonlinear time series analysis applied to scalp electrode recordings, which is able to distinguish between epochs temporally distant from and just prior to, the onset of a seizure in patients with temporal lobe epilepsy. First we describe a method involving a comparison of recordings taken from electrodes adjacent to and remote from the site of the seizure focus. In particular, we define a nonlinear quantity which we call marginal predictability. This quantity is computed using data from remote and from adjacent electrodes. We find that the difference between the marginal predictabilities computed for the remote and adjacent electrodes decreases several tens of minutes prior to seizure onset, compared to its value interictally. We also show that these difl'crcnc es of marginal predictability intervals are independent of the behavior state of the patient. Next we examine the please coherence between different electrodes both in the long-range and the short-range. When time is distant from seizure onsets ("interictally"), epileptic patients have lower long-range phase coherence in the delta (1-4Hz) and beta (18-30Hz) frequency band compared to nonepileptic subjects. When seizures approach (''preictally"), we observe an increase in phase coherence in the beta band. However, interictally there is no difference in short-range phase coherence between this cohort of patients and non-epileptic subjects. Preictally short-range phase coherence also increases in the alpha (10-13Hz) and the beta band. Next we apply the quantity marginal predictability on the phase difference time series. Such marginal predictabilities are lower in the patients than in the non-epileptic subjects. However, when seizure approaches, the former moves asymptotically towards the latter.

Accelerated Discovery of High-Refractive-Index Polymers Using First-Principles Modeling, Virtual High-Throughput Screening, and Data Mining

NASA Astrophysics Data System (ADS)

Afzal, Mohammad Atif Faiz; Cheng, Chong; Hachmann, Johannes

Organic materials with refractive index (RI) values higher than 1.7 have attracted considerable interest in recent years due to the tremendous potential for their application in optical, optometric, and optoelectronic devices, and thus for shaping technological innovation in numerous related areas. Our work is concerned with creating predictive models for the optical properties of organic polymers, which will guide our experimentalist partners and allow them to target the most promising candidates. The RI model is developed based on a synergistic combination of first-principles electronic structure theory and machine learning techniques. The RI values predicted for common polymers using this model are in very good agreement with the experimental values. We also benchmark different DFT approximations along with various basis sets for their predictive performance in this model. We demonstrate that this combination of first-principles and data modeling is both successful and highly economical in determining the RI values of a wide range of organic polymers. To accelerate the development process, we cast this modeling approach into the high-throughput screening, materials informatics, and rational design framework that is developed in the group. This framework is a powerful tool and has shown to be highly promising for rapidly identifying polymer candidates with exceptional RI values as well as discovering design rules for advanced materials.

[Application of ARIMA model on prediction of malaria incidence].

PubMed

Jing, Xia; Hua-Xun, Zhang; Wen, Lin; Su-Jian, Pei; Ling-Cong, Sun; Xiao-Rong, Dong; Mu-Min, Cao; Dong-Ni, Wu; Shunxiang, Cai

2016-01-29

To predict the incidence of local malaria of Hubei Province applying the Autoregressive Integrated Moving Average model (ARIMA). SPSS 13.0 software was applied to construct the ARIMA model based on the monthly local malaria incidence in Hubei Province from 2004 to 2009. The local malaria incidence data of 2010 were used for model validation and evaluation. The model of ARIMA (1, 1, 1) (1, 1, 0) 12 was tested as relatively the best optimal with the AIC of 76.085 and SBC of 84.395. All the actual incidence data were in the range of 95% CI of predicted value of the model. The prediction effect of the model was acceptable. The ARIMA model could effectively fit and predict the incidence of local malaria of Hubei Province.

Age-related DNA methylation changes for forensic age-prediction.

PubMed

Yi, Shao Hua; Jia, Yun Shu; Mei, Kun; Yang, Rong Zhi; Huang, Dai Xin

2015-03-01

There is no available method of age-prediction for biological samples. The accumulating evidences indicate that DNA methylation patterns change with age. Aging resembles a developmentally regulated process that is tightly controlled by specific epigenetic modifications and age-associated methylation changes exist in human genome. In this study, three age-related methylation fragments were isolated and identified in blood of 40 donors. Age-related methylation changes with each fragment was validated and replicated in a general population sample of 65 donors over a wide age range (11-72 years). Methylation of these fragments is linearly correlated with age over a range of six decades (r = 0.80-0.88). Using average methylation of CpG sites of three fragments, a regression model that explained 95 % of the variance in age was built and is able to predict an individual's age with great accuracy (R (2 )= 0.93). The predicted value is highly correlated with the observed age in the sample (r = 0.96) and has great accuracy of average 4 years difference between predicted age and true age. This study implicates that DNA methylation can be an available biological marker of age-prediction. Further measurement of relevant markers in the genome could be a tool in routine screening to predict age of forensic biological samples.

Predicting top-of-atmosphere radiance for arbitrary viewing geometries from the visible to thermal infrared: generalization to arbitrary average scene temperatures

NASA Astrophysics Data System (ADS)

Florio, Christopher J.; Cota, Steve A.; Gaffney, Stephanie K.

2010-08-01

In a companion paper presented at this conference we described how The Aerospace Corporation's Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) may be used in conjunction with a limited number of runs of AFRL's MODTRAN4 radiative transfer code, to quickly predict the top-of-atmosphere (TOA) radiance received in the visible through midwave IR (MWIR) by an earth viewing sensor, for any arbitrary combination of solar and sensor elevation angles. The method is particularly useful for large-scale scene simulations where each pixel could have a unique value of reflectance/emissivity and temperature, making the run-time required for direct prediction via MODTRAN4 prohibitive. In order to be self-consistent, the method described requires an atmospheric model (defined, at a minimum, as a set of vertical temperature, pressure and water vapor profiles) that is consistent with the average scene temperature. MODTRAN4 provides only six model atmospheres, ranging from sub-arctic winter to tropical conditions - too few to cover with sufficient temperature resolution the full range of average scene temperatures that might be of interest. Model atmospheres consistent with intermediate temperature values can be difficult to come by, and in any event, their use would be too cumbersome for use in trade studies involving a large number of average scene temperatures. In this paper we describe and assess a method for predicting TOA radiance for any arbitrary average scene temperature, starting from only a limited number of model atmospheres.

Shelf-life dating of shelf-stable strawberry juice based on survival analysis of consumer acceptance information.

PubMed

Buvé, Carolien; Van Bedts, Tine; Haenen, Annelien; Kebede, Biniam; Braekers, Roel; Hendrickx, Marc; Van Loey, Ann; Grauwet, Tara

2018-07-01

Accurate shelf-life dating of food products is crucial for consumers and industries. Therefore, in this study we applied a science-based approach for shelf-life assessment, including accelerated shelf-life testing (ASLT), acceptability testing and the screening of analytical attributes for fast shelf-life predictions. Shelf-stable strawberry juice was selected as a case study. Ambient storage (20 °C) had no effect on the aroma-based acceptance of strawberry juice. The colour-based acceptability decreased during storage under ambient and accelerated (28-42 °C) conditions. The application of survival analysis showed that the colour-based shelf-life was reached in the early stages of storage (≤11 weeks) and that the shelf-life was shortened at higher temperatures. None of the selected attributes (a * and ΔE * value, anthocyanin and ascorbic acid content) is an ideal analytical marker for shelf-life predictions in the investigated temperature range (20-42 °C). Nevertheless, an overall analytical cut-off value over the whole temperature range can be selected. Colour changes of strawberry juice during storage are shelf-life limiting. Combining ASLT with acceptability testing allowed to gain faster insight into the change in colour-based acceptability and to perform shelf-life predictions relying on scientific data. An analytical marker is a convenient tool for shelf-life predictions in the context of ASLT. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

The value of non-echo planar HASTE diffusion-weighted MR imaging in the detection, localisation and prediction of extent of postoperative cholesteatoma.

PubMed

Khemani, S; Lingam, R K; Kalan, A; Singh, A

2011-08-01

To evaluate the diagnostic performance of half-Fourier-acquisition single-shot turbo-spin-echo (HASTE) diffusion-weighted magnetic resonance imaging in the detection, localisation and prediction of extent of cholesteatoma following canal wall up mastoid surgery. Prospective blinded observational study. University affiliated teaching hospital. Forty-eight patients undergoing second-look surgery after previous canal wall up mastoid surgery for primary acquired cholesteatoma. All patients underwent non-echo planar HASTE diffusion-weighted imaging prior to being offered 'second-look' surgery. Radiological findings were correlated with second-look intra-operative findings in 38 cases with regard to presence, location and maximum dimensions of cholesteatoma. Half-Fourier-acquisition single-shot turbo-spin-echo diffusion-weighted imaging accurately predicted the presence of cholesteatoma in 23 of 28 cases, and it correctly excluded in nine of 10 cases. Five false negatives were caused by keratin pearls of <2 mm and in one case 5 mm. Overall sensitivity and specificity for detection of cholesteatoma were 82% (95% confidence interval [CI] 62-94%) and 90% (CI 55-100%), respectively. Positive predictive value and negative predictive value were 96% (CI 79-100%) and 64% (CI 35-87%), respectively. Overall accuracy for detection of cholesteatoma was 84% (CI 69-94%). Half-Fourier-acquisition single-shot turbo-spin-echo diffusion-weighted imaging has good performance in localising cholesteatoma to a number of anatomical sub-sites within the middle ear and mastoid (sensitivity ranging from 75% to 88% and specificity ranging from 94% to 100%). There was no statistically significant difference in the size of cholesteatoma detected radiologically and that found during surgery (paired t-test, P = 0.16). However, analysis of size agreement suggests possible radiological underestimation of size when using HASTE diffusion-weighted imaging (mean difference -0.6 mm, CI -5.3 to 4.6 mm). Half-Fourier-acquisition single-shot turbo-spin-echo diffusion-weighted imaging performs reasonably well in predicting the presence and location of postoperative cholesteatoma but may miss small foci of disease and may underestimate the true size of cholesteatoma. © 2011 Blackwell Publishing Ltd.

Can We Weight Satisfaction Score with Importance Ranks across Life Domains?

ERIC Educational Resources Information Center

Wu, Chia-Huei

2008-01-01

The main purpose of this study was to investigate the utility of importance weighting when importance ranks were considered as the weighting values by (1) examining the range-of-affect hypothesis in the within-subject context and (2) comparing performances of weighted and unweighted satisfaction scores in predicting overall judgment of subjective…

Star formation in the multiverse

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

Bousso, Raphael; Leichenauer, Stefan

2009-03-15

We develop a simple semianalytic model of the star formation rate as a function of time. We estimate the star formation rate for a wide range of values of the cosmological constant, spatial curvature, and primordial density contrast. Our model can predict such parameters in the multiverse, if the underlying theory landscape and the cosmological measure are known.

On the Dielectric Constant for Acetanilide: Experimental Measurements and Effect on Energy Transport

NASA Astrophysics Data System (ADS)

Careri, G.; Compatangelo, E.; Christiansen, P. L.; Halding, J.; Skovgaard, O.

1987-01-01

Experimental measurements of the dielectric constant for crystalline acetanilide powder for temperatures ranging from - 140°C to 20°C and for different hydration levels are presented. A Davydov-soliton computer model predicts dramatic changes in the energy transport and storage for typically increased values of the dielectric constant.

Usefulness of plasma B-type natriuretic peptide to identify ventricular dysfunction in pediatric and adult patients with congenital heart disease.

PubMed

Law, Yuk M; Keller, Bradley B; Feingold, Brian M; Boyle, Gerard J

2005-02-15

The usefulness of B-type natriuretic peptide (BNP) levels to assess ventricular dysfunction in children and the congenital heart disease population remains largely unknown. We retrospectively analyzed 62 patients with or without known heart disease who had plasma BNP measured for the investigation of new or severity grading of known ventricular dysfunction. BNP levels were significantly higher in patients with ventricular dysfunction (mean 623 +/- 146 pg/ml, range 5 to 5,000) than in patients without ventricular dysfunction (mean 22 +/- 5 pg/ml, range 5 to 63; p <0.01). Using a cutoff of 40 pg/ml, BNP levels detected heart disease associated with ventricular dysfunction at a sensitivity of 85%, specificity of 81%, positive predictive value of 92%, and negative predictive value of 68%. The degree of BNP elevation was also associated with the severity of heart failure and high ventricular filling pressures. Plasma BNP elevation can be a reliable test in children and young adults with various kinds of congenital heart disease resulting in ventricular dysfunction.

On Geomagnetism and Paleomagnetism I

NASA Technical Reports Server (NTRS)

Voorhies, Coerte V.

2000-01-01

A partial description of Earth's broad scale, core-source magnetic field has been developed and tested three ways. The description features an expected, or mean, spatial magnetic power spectrum that is approximately inversely proportional to horizontal wavenumber atop Earth's core. This multipole spectrum describes a magnetic energy range; it is not steep enough for Gubbins' magnetic dissipation range. Temporal variations of core multipole powers about mean values are to be expected and are described statistically, via trial probability distribution functions, instead of deterministically, via trial solution of closed transport equations. The distributions considered here are closed and neither require nor prohibit magnetic isotropy. The description is therefore applicable to, and tested against, both dipole and low degree non-dipole fields. In Part 1, a physical basis for an expectation spectrum is developed and checked. The description is then combined with main field models of twentieth century satellite and surface geomagnetic field measurements to make testable predictions of the radius of Earth's core. The predicted core radius is 0.7% above the 3480 km seismological value. Partial descriptions of other planetary dipole fields are noted.

A new model of cavern diameter based on a validated CFD study on stirring of a highly shear-thinning fluid.

PubMed

Story, Anna; Jaworski, Zdzisław

2017-01-01

Results of numerical simulations of momentum transfer for a highly shear-thinning fluid (0.2% Carbopol) in a stirred tank equipped with a Prochem Maxflo T type impeller are presented. The simulation results were validated using LDA data and both tangential and axial force measurements in the laminar and early transitional flow range. A good agreement between the predicted and experimental results of the local fluid velocity components was found. From the predicted and experimental values of both tangential and axial forces, the power number, Po , and thrust number, Th , were also calculated. Values of the absolute relative deviations were below 4.0 and 10.5%, respectively, for Po and Th , which confirms a satisfactory agreement with experiments. An intensive mixing zone, known as cavern, was observed near the impeller. In this zone, the local values of fluid velocity, strain rate, Metzner-Otto coefficient, shear stress and intensity of energy dissipation were all characterized by strong variability. Based on the results of experimental study a new model using non-dimensional impeller force number was proposed to predict the cavern diameter. Comparative numerical simulations were also carried out for a Newtonian fluid (water) and their results were similarly well verified using LDA measurements, as well as experimental power number values.

Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients

PubMed Central

Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

2016-01-01

Background: Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. Materials and Methods: The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. Results: A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30–70% range, with no significant difference among models (P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others (P > 0.05). Conclusion: This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others. PMID:27904602

External Evaluation of Two Fluconazole Infant Population Pharmacokinetic Models

PubMed Central

Hwang, Michael F.; Beechinor, Ryan J.; Wade, Kelly C.; Benjamin, Daniel K.; Smith, P. Brian; Hornik, Christoph P.; Capparelli, Edmund V.; Duara, Shahnaz; Kennedy, Kathleen A.; Cohen-Wolkowiez, Michael

2017-01-01

ABSTRACT Fluconazole is an antifungal agent used for the treatment of invasive candidiasis, a leading cause of morbidity and mortality in premature infants. Population pharmacokinetic (PK) models of fluconazole in infants have been previously published by Wade et al. (Antimicrob Agents Chemother 52:4043–4049, 2008, https://doi.org/10.1128/AAC.00569-08) and Momper et al. (Antimicrob Agents Chemother 60:5539–5545, 2016, https://doi.org/10.1128/AAC.00963-16). Here we report the results of the first external evaluation of the predictive performance of both models. We used patient-level data from both studies to externally evaluate both PK models. The predictive performance of each model was evaluated using the model prediction error (PE), mean prediction error (MPE), mean absolute prediction error (MAPE), prediction-corrected visual predictive check (pcVPC), and normalized prediction distribution errors (NPDE). The values of the parameters of each model were reestimated using both the external and merged data sets. When evaluated with the external data set, the model proposed by Wade et al. showed lower median PE, MPE, and MAPE (0.429 μg/ml, 41.9%, and 57.6%, respectively) than the model proposed by Momper et al. (2.45 μg/ml, 188%, and 195%, respectively). The values of the majority of reestimated parameters were within 20% of their respective original parameter values for all model evaluations. Our analysis determined that though both models are robust, the model proposed by Wade et al. had greater accuracy and precision than the model proposed by Momper et al., likely because it was derived from a patient population with a wider age range. This study highlights the importance of the external evaluation of infant population PK models. PMID:28893774

A Predictive Model to Identify Patients With Fecal Incontinence Based on High-Definition Anorectal Manometry.

PubMed

Zifan, Ali; Ledgerwood-Lee, Melissa; Mittal, Ravinder K

2016-12-01

Three-dimensional high-definition anorectal manometry (3D-HDAM) is used to assess anal sphincter function; it determines profiles of regional pressure distribution along the length and circumference of the anal canal. There is no consensus, however, on the best way to analyze data from 3D-HDAM to distinguish healthy individuals from persons with sphincter dysfunction. We developed a computer analysis system to analyze 3D-HDAM data and to aid in the diagnosis and assessment of patients with fecal incontinence (FI). In a prospective study, we performed 3D-HDAM analysis of 24 asymptomatic healthy subjects (control subjects; all women; mean age, 39 ± 10 years) and 24 patients with symptoms of FI (all women; mean age, 58 ± 13 years). Patients completed a standardized questionnaire (FI severity index) to score the severity of FI symptoms. We developed and evaluated a robust prediction model to distinguish patients with FI from control subjects using linear discriminant, quadratic discriminant, and logistic regression analyses. In addition to collecting pressure information from the HDAM data, we assessed regional features based on shape characteristics and the anal sphincter pressure symmetry index. The combination of pressure values, anal sphincter area, and reflective symmetry values was identified in patients with FI versus control subjects with an area under the curve value of 1.0. In logistic regression analyses using different predictors, the model identified patients with FI with an area under the curve value of 0.96 (interquartile range, 0.22). In discriminant analysis, results were classified with a minimum error of 0.02, calculated using 10-fold cross-validation; different combinations of predictors produced median classification errors of 0.16 in linear discriminant analysis (interquartile range, 0.25) and 0.08 in quadratic discriminant analysis (interquartile range, 0.25). We developed and validated a novel prediction model to analyze 3D-HDAM data. This system can accurately distinguish patients with FI from control subjects. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.

Increased odds and predictive rates of MMPI-2-RF scale elevations in patients with psychogenic non-epileptic seizures and observed sex differences.

PubMed

Del Bene, Victor A; Arce Rentería, Miguel; Maiman, Moshe; Slugh, Mitch; Gazzola, Deana M; Nadkarni, Siddhartha S; Barr, William B

2017-07-01

The Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) is a self-report instrument, previously shown to differentiate patients with epileptic seizures (ES) and psychogenic non-epileptic seizures (PNES). At present, the odds of MMPI-2-RF scale elevations in PNES patients, as well as the diagnostic predictive value of such scale elevations, remain largely unexplored. This can be of clinical utility, particularly when a diagnosis is uncertain. After looking at mean group differences, we applied contingency table derived odds ratios to a sample of ES (n=92) and PNES (n=77) patients from a video EEG (vEEG) monitoring unit. We also looked at the positive and negative predictive values (PPV, NPV), as well as the false discovery rate (FDR) and false omission rate (FOR) for scales found to have increased odds of elevation in PNES patients. This was completed for the overall sample, as well as the sample stratified by sex. The odds of elevations related to somatic concerns, negative mood, and suicidal ideation in the PNES sample ranged from 2 to 5 times more likely. Female PNES patients had 3-6 times greater odds of such scale elevations, while male PNES patients had odds of 5-15 times more likely. PPV rates ranged from 53.66% to 84.62%, while NPV rates ranged from 47.52% to 90.91%. FDR across scales ranged from 15.38% to 50%, while the FOR ranged from 9.09% to 52.47%. Consistent with prior research, PNES patients have greater odds of MMPI-2-RF scale elevations, particularly related to somatic concerns and mood disturbance. Female PNES patients endorsed greater emotional distress, including endorsement of suicide related items. Elevations of these scales could aid in differentiating PNES from ES patients, although caution is warranted due to the possibility of both false positives and the incorrect omissions of PNES cases. Copyright © 2017 Elsevier Inc. All rights reserved.

Total and Bioaccessible Soil Arsenic and Lead Levels and Plant Uptake in Three Urban Community Gardens in Puerto Rico.

PubMed

Misenheimer, John; Nelson, Clay; Huertas, Evelyn; Medina-Vera, Myriam; Prevatte, Alex; Bradham, Karen

2018-01-01

Arsenic (As) and lead (Pb) are two contaminants of concern associated with urban gardening. In Puerto Rico, data currently is limited on As and Pb levels in urban garden soils, soil metal (loid) bioaccessibility, and uptake of As and Pb in soil by edible plants grown in the region. This study examined total and bioaccessible soil As and Pb concentrations and accumulation in 10 commonly grown garden plants collected from three urban community gardens in Puerto Rico. Bioavailability values were predicted using bioaccessibility data to compare site-specific bioavailability estimates to commonly used default exposure assumptions. Total and bioaccessible As levels in study soils ranged from 2 to 55 mg/kg and 1 to 18 mg/kg, respectively. Total and bioaccessible Pb levels ranged from 19 to 172 mg/kg and 17 to 97 mg/kg, respectively. Measured bioaccessibility values corresponded to 19 to 42% bioaccessible As and 61 to 100% bioaccessible Pb when expressed as a percent of total As and Pb respectively. Predicted relative percent bioavailability of soil As and Pb based on measured bioaccessibility values ranged from 18 to 36% and 51 to 85% for As and Pb respectively. Transfer factors (TFs) measuring uptake of As in plants from soil ranged from 0 to 0.073 in the edible flesh (fruit or vegetable) of plant tissues analyzed and 0.073 to 0.444 in edible leaves. Pb TFs ranged from 0.002 to 0.012 in flesh and 0.023 to 0.204 in leaves. Consistent with TF values, leaves accumulated higher concentrations of As and Pb than the flesh, with the highest tissue concentrations observed in the culantro leaf (3.2 mg/kg dw of As and 8.9 mg/kg dw of Pb). Leaves showed a general but not statistically-significant (α = 0.05) trend of increased As and Pb concentration with increased soil levels, while no trend was observed for flesh tissues. These findings provide critical data that can improve accuracy and reduce uncertainty when conducting site-specific risk determination of potential As and Pb exposure while gardening or consuming garden produce in the understudied region of Puerto Rico.

The application of SEAT values for predicting how compliant seats with backrests influence vibration discomfort.

PubMed

Basri, Bazil; Griffin, Michael J

2014-11-01

The extent to which a seat can provide useful attenuation of vehicle vibration depends on three factors: the characteristics of the vehicle motion, the vibration transmissibility of the seat, and the sensitivity of the body to vibration. The 'seat effective amplitude transmissibility' (i.e., SEAT value) reflects how these three factors vary with the frequency and the direction of vibration so as to predict the vibration isolation efficiency of a seat. The SEAT value is mostly used to select seat cushions or seat suspensions based on the transmission of vertical vibration to the principal supporting surface of a seat. This study investigated the accuracy of SEAT values in predicting how seats with backrests influence the discomfort caused by multiple-input vibration. Twelve male subjects participated in a four-part experiment to determine equivalent comfort contours, the relative discomfort, the location of discomfort, and seat transmissibility with three foam seats and a rigid reference seat at 14 frequencies of vibration in the range 1-20 Hz at magnitudes of vibration from 0.2 to 1.6 ms(-2) r.m.s. The 'measured seat dynamic discomfort' (MSDD) was calculated for each foam seat from the ratio of the vibration acceleration required to cause similar discomfort with the foam seat and with the rigid reference seat. Using the frequency weightings in current standards, the SEAT values of each seat were calculated from the ratio of overall ride values with the foam seat to the overall ride values with the rigid reference seat, and compared to the corresponding MSDD at each frequency. The SEAT values provided good predictions of how the foam seats increased vibration discomfort at frequencies around the 4-Hz resonance but reduced vibration discomfort at frequencies greater than about 6.3 Hz, with discrepancies explained by a known limitation of the frequency weightings. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows.

PubMed

Visentin, G; McDermott, A; McParland, S; Berry, D P; Kenny, O A; Brodkorb, A; Fenelon, M A; De Marchi, M

2015-09-01

Rapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n=713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000cm(-1) were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability

USGS Publications Warehouse

Montgomery, D.R.; Schmidt, K.M.; Dietrich, W.E.; McKean, J.

2009-01-01

The middle of a hillslope hollow in the Oregon Coast Range failed and mobilized as a debris flow during heavy rainfall in November 1996. Automated pressure transducers recorded high spatial variability of pore water pressure within the area that mobilized as a debris flow, which initiated where local upward flow from bedrock developed into overlying colluvium. Postfailure observations of the bedrock surface exposed in the debris flow scar reveal a strong spatial correspondence between elevated piezometric response and water discharging from bedrock fractures. Measurements of apparent root cohesion on the basal (Cb) and lateral (Cl) scarp demonstrate substantial local variability, with areally weighted values of Cb = 0.1 and Cl = 4.6 kPa. Using measured soil properties and basal root strength, the widely used infinite slope model, employed assuming slope parallel groundwater flow, provides a poor prediction of hydrologie conditions at failure. In contrast, a model including lateral root strength (but neglecting lateral frictional strength) gave a predicted critical value of relative soil saturation that fell within the range defined by the arithmetic and geometric mean values at the time of failure. The 3-D slope stability model CLARA-W, used with locally observed pore water pressure, predicted small areas with lower factors of safety within the overall slide mass at sites consistent with field observations of where the failure initiated. This highly variable and localized nature of small areas of high pore pressure that can trigger slope failure means, however, that substantial uncertainty appears inevitable for estimating hydrologie conditions within incipient debris flows under natural conditions. Copyright 2009 by the American Geophysical Union.

Hepatitis C treatment among racial and ethnic groups in the IDEAL trial.

PubMed

Muir, A J; Hu, K-Q; Gordon, S C; Koury, K; Boparai, N; Noviello, S; Albrecht, J K; Sulkowski, M S; McCone, J

2011-04-01

Previous studies of chronic hepatitis C virus (HCV) treatment have demonstrated variations in response among racial and ethnic groups including poorer efficacy rates among African American and Hispanic patients. The individualized dosing efficacy vs flat dosing to assess optimaL pegylated interferon therapy (IDEAL) trial enrolled 3070 patients from 118 United States centres to compare treatment with peginterferon (PEG-IFN) alfa-2a and ribavirin (RBV) and two doses of PEG-IFN alfa-2b and RBV. This analysis examines treatment response among the major racial and ethnic groups in the trial. Overall, sustained virologic response (SVR) rates were 44% for white, 22% for African American, 38% for Hispanic and 59% for Asian American patients. For patients with undetectable HCV RNA at treatment week 4, the positive predictive value of SVR was 86% for white, 92% for African American, 83% for Hispanic and 89% for Asian American patients. The positive predictive values of SVR in those with undetectable HCV RNA at treatment week 12 ranged from 72% to 81%. Multivariate regression analysis using baseline characteristics demonstrated that treatment regimen was not a predictor of SVR. Despite wide-ranging SVR rates among the different racial and ethnic groups, white and Hispanic patients had similar SVR rates. In all groups, treatment response was largely determined by antiviral activity in the first 12 weeks of treatment. Therefore, decisions regarding HCV treatment should consider the predictive value of the early on-treatment response, not just baseline characteristics, such as race and ethnicity. © 2010 Blackwell Publishing Ltd.

Continuously Variable Rating: a new, simple and logical procedure to evaluate original scientific publications

PubMed Central

Silva, Mauricio Rocha e

2011-01-01

OBJECTIVE: Impact Factors (IF) are widely used surrogates to evaluate single articles, in spite of known shortcomings imposed by cite distribution skewness. We quantify this asymmetry and propose a simple computer-based procedure for evaluating individual articles. METHOD: (a) Analysis of symmetry. Journals clustered around nine Impact Factor points were selected from the medical “Subject Categories” in Journal Citation Reports 2010. Citable items published in 2008 were retrieved and ranked by granted citations over the Jan/2008 - Jun/2011 period. Frequency distribution of cites, normalized cumulative cites and absolute cites/decile were determined for each journal cluster. (b) Positive Predictive Value. Three arbitrarily established evaluation classes were generated: LOW (1.3≤IF<2.6); MID: (2.6≤IF<3.9); HIGH: (IF≥3.9). Positive Predictive Value for journal clusters within each class range was estimated. (c) Continuously Variable Rating. An alternative evaluation procedure is proposed to allow the rating of individually published articles in comparison to all articles published in the same journal within the same year of publication. The general guiding lines for the construction of a totally dedicated software program are delineated. RESULTS AND CONCLUSIONS: Skewness followed the Pareto Distribution for (1

Improvement of gel strength and melting point of fish gelatin by addition of coenhancers using response surface methodology.

PubMed

Koli, Jayappa M; Basu, Subrata; Nayak, Binay B; Kannuchamy, Nagalakshmi; Gudipati, Venkateshwarlu

2011-08-01

Fish gelatin is a potential alternative to mammalian gelatin. However, poor gel strength and low melting point limit its applications. The study was aimed at improving these properties by adding coenhancers in the range obtained from response surface methodology (RSM) by using Box-Behnken design. Three different coenhancers, MgSO₄, sucrose, and transglutaminase were used as the independent variables for improving the gel strength and melting point of gelatin extracted from Tiger-toothed croaker (Otolithes ruber). Addition of coenhancers at different combinations resulted gel strength and melting point in the range of 150.5 to 240.5 g and 19.5 to 22.5 °C, respectively. The optimal concentrations of coenhancers for predicted maximum gel strength (242.8 g) obtained by RSM were 0.23 M MgSO₄, 12.60% sucrose (w/v), and 5.92 mg/g transglutaminase and for predicted maximum melting point (22.57 °C), the values were 0.24 M MgSO₄, 10.44% sucrose (w/v), and 5.72 mg/g transglutaminase. By addition of coenhancers at these optimal concentrations in verification experiments, the gel strength and melting point were improved from 170 to 240.89 g and 20.3 to 22.7 °C, respectively. These experimental values agreed well with the predicted values demonstrating the fitness of the models. Results from the present study clearly revealed that the addition of coenhancers at a particular combination can improve the gel strength and melting point of fish gelatin to enhance its range of applications. There is a growing interest in the use of fish gelatin as an alternative to mammalian gelatin. However, poor gel strength and low melting point of fish gelatin have limited its commercial applications. The gel strength and melting point of fish gelatin can be increased by incorporation of coenhancers such as magnesium sulphate, sucrose, and transglutaminase. Results of this work help to produce the fish gelatin suitable for wide range of applications in the food industry. © 2011 Institute of Food Technologists®

Relevance of genetic relationship in GWAS and genomic prediction.

PubMed

Pereira, Helcio Duarte; Soriano Viana, José Marcelo; Andrade, Andréa Carla Bastos; Fonseca E Silva, Fabyano; Paes, Geísa Pinheiro

2018-02-01

The objective of this study was to analyze the relevance of relationship information on the identification of low heritability quantitative trait loci (QTLs) from a genome-wide association study (GWAS) and on the genomic prediction of complex traits in human, animal and cross-pollinating populations. The simulation-based data sets included 50 samples of 1000 individuals of seven populations derived from a common population with linkage disequilibrium. The populations had non-inbred and inbred progeny structure (50 to 200) with varying number of members (5 to 20). The individuals were genotyped for 10,000 single nucleotide polymorphisms (SNPs) and phenotyped for a quantitative trait controlled by 10 QTLs and 90 minor genes showing dominance. The SNP density was 0.1 cM and the narrow sense heritability was 25%. The QTL heritabilities ranged from 1.1 to 2.9%. We applied mixed model approaches for both GWAS and genomic prediction using pedigree-based and genomic relationship matrices. For GWAS, the observed false discovery rate was kept below the significance level of 5%, the power of detection for the low heritability QTLs ranged from 14 to 50%, and the average bias between significant SNPs and a QTL ranged from less than 0.01 to 0.23 cM. The QTL detection power was consistently higher using genomic relationship matrix. Regardless of population and training set size, genomic prediction provided higher prediction accuracy of complex trait when compared to pedigree-based prediction. The accuracy of genomic prediction when there is relatedness between individuals in the training set and the reference population is much higher than the value for unrelated individuals.

Development of NIRS models to predict protein and amylose content of brown rice and proximate compositions of rice bran.

PubMed

Bagchi, Torit Baran; Sharma, Srigopal; Chattopadhyay, Krishnendu

2016-01-15

With the escalating persuasion of economic and nutritional importance of rice grain protein and nutritional components of rice bran (RB), NIRS can be an effective tool for high throughput screening in rice breeding programme. Optimization of NIRS is prerequisite for accurate prediction of grain quality parameters. In the present study, 173 brown rice (BR) and 86 RB samples with a wide range of values were used to compare the calibration models generated by different chemometrics for grain protein (GPC) and amylose content (AC) of BR and proximate compositions (protein, crude oil, moisture, ash and fiber content) of RB. Various modified partial least square (mPLSs) models corresponding with the best mathematical treatments were identified for all components. Another set of 29 genotypes derived from the breeding programme were employed for the external validation of these calibration models. High accuracy of all these calibration and prediction models was ensured through pair t-test and correlation regression analysis between reference and predicted values. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predictions of high QDT in ITER H-mode plasmas

NASA Astrophysics Data System (ADS)

Budny, Robert

2009-05-01

Time-dependent integrated predictions of performance metrics such as the fusion power PDT, QDT≡ PDT/Pext, and alpha profiles are presented. The PTRANSP code (see R.V. Budny, R. Andre, G. Bateman, F. Halpern, C.E. Kessel, A. Kritz, and D. McCune, Nuclear Fusion 48 075005, and F. Halpern, A. Kritz, G. Bateman, R.V. Budny, and D. McCune, Phys. Plasmas 15 062505) is used, along with GLF23 to predict plasma profiles, NUBEAM for NNBI and alpha heating, TORIC for ICRH, and TORAY for ECRH. Effects of sawteeth mixing, beam steering, beam shine-through, radiation loss, ash accumulation, and toroidal rotation are included. A total heating of Pext=73MW is assumed to achieve H-mode during the density and current ramp-up phase. Various mixes of NNBI, ICRH, and ECRH heating schemes are compared. After steady state conditions are achieved, Pext is stepped down to lower values to explore high QDT. Physics and computation uncertainties lead to ranges in predictions for PDT and QDT. Physics uncertainties include the L->H and H->L threshold powers, pedestal height, impurity and ash transport, and recycling. There are considerably more uncertainties predicting the peak value for QDT than for PDT.

Traveller Information System for Heterogeneous Traffic Condition: A Case Study in Thiruvananthapuram City, India

NASA Astrophysics Data System (ADS)

Satyakumar, M.; Anil, R.; Sreeja, G. S.

2017-12-01

Traffic in Kerala has been growing at a rate of 10-11% every year, resulting severe congestion especially in urban areas. Because of the limitation of spaces it is not always possible to construct new roads. Road users rely on travel time information for journey planning and route choice decisions, while road system managers are increasingly viewing travel time as an important network performance indicator. More recently Advanced Traveler Information Systems (ATIS) are being developed to provide real-time information to roadway users. For ATIS various methodologies have been developed for dynamic travel time prediction. For this work the Kalman Filter Algorithm was selected for dynamic travel time prediction of different modes. The travel time data collected using handheld GPS device were used for prediction. Congestion Index were calculated and Range of CI values were determined according to the percentage speed drop. After prediction using Kalman Filter, the predicted values along with the GPS data was integrated to GIS and using Network Analysis of ArcGIS the offline route navigation guide was prepared. Using this database a program for route navigation based on travel time was developed. This system will help the travelers with pre-trip information.

[Predictive value of Ages & Stages Questionnaires for cognitive performance at early years of schooling].

PubMed

Schonhaut B, Luisa; Pérez R, Marcela; Castilla F, Ana María; Castro M, Sonia; Salinas A, Patricia; Armijo R, Iván

2017-02-01

The Ages and Stages questionnaires (ASQ) has been recently validated in our country for developmental screening. The objective of this study is evaluate the validity of ASQ to predict low cognitive performance in the early years of schooling. Diagnostic test studies conducted on a sample of children of medium-high socioeconomic level were evaluated using ASQ at least once at 8, 18 and/or 30 months old, and later, between 6 and 9 years old, reevaluated using the Wechsler Intelligence Scale for Children-third edition (WISC-III). Each ASQ evaluation was recorded independently. WISC-III was standardized, considering underperformance when the total score were under -1 standard deviation. 123 children, corresponding to 174 ASQ assessments (42 of them were 8 months old, 55 were 18 months and 77 were 30 months of age) were included. An area under the ROC curve of 80.7% was obtained, showing higher values at 8 months (98.0%) compared to 18 and 30 months old (78.1 and 79.3%, respectively). Considering different ASQ scoring criteria, a low sensitivity (27.8 to 50.0%), but a high specificity (78.8 to 96.2%) were obtained; the positive predictive value ranged between 21 and 46%, while the negative value was 92.0-93.2%. Conclusion ASQ has low sensitivity but excellent specificity to predict a low cognitive performance during the first years of schooling, being a good alternative to monitor psychomotor development in children who attend the private sector healthcare in our country.

Predictive Value of the Korean Academy of Family Medicine In-Training Examination for Certifying Examination

PubMed Central

Kim, Ji-Yong

2011-01-01

Background In-training examination (ITE) is a cognitive examination similar to the written test, but it is different from the Clinical Practice Examination of the Korean Academy of Family Medicine (KAFM) Certification Examination (CE). The objective of this is to estimate the positive predictive value of the KAFM-ITE for identifying residents at risk for poor performance on the three types of KAFM-CE. Methods 372 residents who completed the KAFM-CE in 2011 were included. We compared the mean KAFM-CE scores with ITE experience. We evaluated the correlation and the positive predictive value (PPV) of ITE for the multiple choice question (MCQ) scores of 1st written test & 2nd slide examination, the total clinical practice examination scores, and the total sum of 2nd test. Results 275 out of 372 residents completed ITE. Those who completed ITE had significantly higher MCQ scores of 1st written test than those who did not. The correlation of ITE scores with 1st written MCQ (0.627) was found to be the highest among the other kinds of CE. The PPV of the ITE score for 1st written MCQ scores was 0.672. The PPV of the ITE score ranged from 0.376 to 0.502. Conclusion The score of the KAFM ITE has acceptable positive predictive value that could be used as a part of comprehensive evaluation system for residents in cognitive field. PMID:22745873

Long-Range Solar Activity Predictions: A Reprieve from Cycle #24's Activity

NASA Technical Reports Server (NTRS)

Richon, K.; Schatten, K.

2003-01-01

We discuss the field of long-range solar activity predictions and provide an outlook into future solar activity. Orbital predictions for satellites in Low Earth Orbit (LEO) depend strongly on exospheric densities. Solar activity forecasting is important in this regard, as the solar ultra-violet (UV) and extreme ultraviolet (EUV) radiations inflate the upper atmospheric layers of the Earth, forming the exosphere in which satellites orbit. Rather than concentrate on statistical, or numerical methods, we utilize a class of techniques (precursor methods) which is founded in physical theory. The geomagnetic precursor method was originally developed by the Russian geophysicist, Ohl, using geomagnetic observations to predict future solar activity. It was later extended to solar observations, and placed within the context of physical theory, namely the workings of the Sun s Babcock dynamo. We later expanded the prediction methods with a SOlar Dynamo Amplitude (SODA) index. The SODA index is a measure of the buried solar magnetic flux, using toroidal and poloidal field components. It allows one to predict future solar activity during any phase of the solar cycle, whereas previously, one was restricted to making predictions only at solar minimum. We are encouraged that solar cycle #23's behavior fell closely along our predicted curve, peaking near 192, comparable to the Schatten, Myers and Sofia (1996) forecast of 182+/-30. Cycle #23 extends from 1996 through approximately 2006 or 2007, with cycle #24 starting thereafter. We discuss the current forecast of solar cycle #24, (2006-2016), with a predicted smoothed F10.7 radio flux of 142+/-28 (1-sigma errors). This, we believe, represents a reprieve, in terms of reduced fuel costs, etc., for new satellites to be launched or old satellites (requiring reboosting) which have been placed in LEO. By monitoring the Sun s most deeply rooted magnetic fields; long-range solar activity can be predicted. Although a degree of uncertainty in the long-range predictions remains, requiring future monitoring, we do not expect the next cycle's + 2-sigma value will rise significantly above solar cycle #23's activity level.

Predicting emergency department volume using forecasting methods to create a "surge response" for noncrisis events.

PubMed

Chase, Valerie J; Cohn, Amy E M; Peterson, Timothy A; Lavieri, Mariel S

2012-05-01

This study investigated whether emergency department (ED) variables could be used in mathematical models to predict a future surge in ED volume based on recent levels of use of physician capacity. The models may be used to guide decisions related to on-call staffing in non-crisis-related surges of patient volume. A retrospective analysis was conducted using information spanning July 2009 through June 2010 from a large urban teaching hospital with a Level I trauma center. A comparison of significance was used to assess the impact of multiple patient-specific variables on the state of the ED. Physician capacity was modeled based on historical physician treatment capacity and productivity. Binary logistic regression analysis was used to determine the probability that the available physician capacity would be sufficient to treat all patients forecasted to arrive in the next time period. The prediction horizons used were 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 8 hours, and 12 hours. Five consecutive months of patient data from July 2010 through November 2010, similar to the data used to generate the models, was used to validate the models. Positive predictive values, Type I and Type II errors, and real-time accuracy in predicting noncrisis surge events were used to evaluate the forecast accuracy of the models. The ratio of new patients requiring treatment over total physician capacity (termed the care utilization ratio [CUR]) was deemed a robust predictor of the state of the ED (with a CUR greater than 1 indicating that the physician capacity would not be sufficient to treat all patients forecasted to arrive). Prediction intervals of 30 minutes, 8 hours, and 12 hours performed best of all models analyzed, with deviances of 1.000, 0.951, and 0.864, respectively. A 95% significance was used to validate the models against the July 2010 through November 2010 data set. Positive predictive values ranged from 0.738 to 0.872, true positives ranged from 74% to 94%, and true negatives ranged from 70% to 90% depending on the threshold used to determine the state of the ED with the 30-minute prediction model. The CUR is a new and robust indicator of an ED system's performance. The study was able to model the tradeoff of longer time to response versus shorter but more accurate predictions, by investigating different prediction intervals. Current practice would have been improved by using the proposed models and would have identified the surge in patient volume earlier on noncrisis days. © 2012 by the Society for Academic Emergency Medicine.

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction

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

Pöhlker, Mira L.; Pöhlker, Christopher; Ditas, Florian

Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). Our measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.The CCN measurements were continuously cycled through 10 levels of supersaturation ( S=0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172more » nm at S = 0.11 %. Furthermore, the particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode ( κ Ait = 0.14 ± 0.03), higher values for the accumulation mode ( κ Acc = 0.22 ± 0.05), and an overall mean value of κ mean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. Here, we find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.« less

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction

DOE PAGES

Pöhlker, Mira L.; Pöhlker, Christopher; Ditas, Florian; ...

2016-12-20

Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). Our measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.The CCN measurements were continuously cycled through 10 levels of supersaturation ( S=0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172more » nm at S = 0.11 %. Furthermore, the particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode ( κ Ait = 0.14 ± 0.03), higher values for the accumulation mode ( κ Acc = 0.22 ± 0.05), and an overall mean value of κ mean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. Here, we find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.« less

A prediction of the minke whale (Balaenoptera acutorostrata) middle-ear transfer functiona)

PubMed Central

Tubelli, Andrew A.; Zosuls, Aleks; Ketten, Darlene R.; Yamato, Maya; Mountain, David C.

2012-01-01

The lack of baleen whale (Cetacea Mysticeti) audiograms impedes the assessment of the impacts of anthropogenic noise on these animals. Estimates of audiograms, which are difficult to obtain behaviorally or electrophysiologically for baleen whales, can be made by simulating the audiogram as a series of components representing the outer, middle, and inner ear (Rosowski, 1991; Ruggero and Temchin, 2002). The middle-ear portion of the system can be represented by the middle-ear transfer function (METF), a measure of the transmission of acoustic energy from the external ear to the cochlea. An anatomically accurate finite element model of the minke whale (Balaenoptera acutorostrata) middle ear was developed to predict the METF for a mysticete species. The elastic moduli of the auditory ossicles were measured by using nanoindentation. Other mechanical properties were estimated from experimental stiffness measurements or from published values. The METF predicted a best frequency range between approximately 30 Hz and 7.5 kHz or between 100 Hz and 25 kHz depending on stimulation location. Parametric analysis found that the most sensitive parameters are the elastic moduli of the glove finger and joints and the Rayleigh damping stiffness coefficient β. The predicted hearing range matches well with the vocalization range. PMID:23145610

Imposing constraints on parameter values of a conceptual hydrological model using baseflow response

NASA Astrophysics Data System (ADS)

Dunn, S. M.

Calibration of conceptual hydrological models is frequently limited by a lack of data about the area that is being studied. The result is that a broad range of parameter values can be identified that will give an equally good calibration to the available observations, usually of stream flow. The use of total stream flow can bias analyses towards interpretation of rapid runoff, whereas water quality issues are more frequently associated with low flow condition. This paper demonstrates how model distinctions between surface an sub-surface runoff can be used to define a likelihood measure based on the sub-surface (or baseflow) response. This helps to provide more information about the model behaviour, constrain the acceptable parameter sets and reduce uncertainty in streamflow prediction. A conceptual model, DIY, is applied to two contrasting catchments in Scotland, the Ythan and the Carron Valley. Parameter ranges and envelopes of prediction are identified using criteria based on total flow efficiency, baseflow efficiency and combined efficiencies. The individual parameter ranges derived using the combined efficiency measures still cover relatively wide bands, but are better constrained for the Carron than the Ythan. This reflects the fact that hydrological behaviour in the Carron is dominated by a much flashier surface response than in the Ythan. Hence, the total flow efficiency is more strongly controlled by surface runoff in the Carron and there is a greater contrast with the baseflow efficiency. Comparisons of the predictions using different efficiency measures for the Ythan also suggest that there is a danger of confusing parameter uncertainties with data and model error, if inadequate likelihood measures are defined.

Novel opportunities for computational biology and sociology in drug discovery☆

PubMed Central

Yao, Lixia; Evans, James A.; Rzhetsky, Andrey

2013-01-01

Current drug discovery is impossible without sophisticated modeling and computation. In this review we outline previous advances in computational biology and, by tracing the steps involved in pharmaceutical development, explore a range of novel, high-value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy–industry links for scientific and human benefit. Attention to these opportunities could promise punctuated advance and will complement the well-established computational work on which drug discovery currently relies. PMID:20349528

Genomic prediction of reproduction traits for Merino sheep.

PubMed

Bolormaa, S; Brown, D J; Swan, A A; van der Werf, J H J; Hayes, B J; Daetwyler, H D

2017-06-01

Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross-validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross-validations. The accuracies of GEBVs from random cross-validations (range 0.17-0.61) were higher than were those from sire family cross-validations (range 0.00-0.51). The GEBV accuracies of 0.41-0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy, it identified several candidate genes which are known to be associated with NLB and LSIZE. The approach provides a way to make use of all data available in genomic prediction for traits that have limited recording. © 2017 Stichting International Foundation for Animal Genetics.

Aboveground biomass mapping in French Guiana by combining remote sensing, forest inventories and environmental data

NASA Astrophysics Data System (ADS)

Fayad, Ibrahim; Baghdadi, Nicolas; Guitet, Stéphane; Bailly, Jean-Stéphane; Hérault, Bruno; Gond, Valéry; El Hajj, Mahmoud; Tong Minh, Dinh Ho

2016-10-01

Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain ;wall-to-wall; AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS footprints are not a problem for regional and global calibrated regression models because field data aim to predict large and deep tendencies in AGB variations from environmental gradients and do not aim to represent high but stochastic and temporally limited variations from forest dynamics. Thus, we advocate including a greater variety of data, even if less precise and shifted, to better represent high AGB values in global models and to improve the fitting of these models for high values.

Soil erosion assessment on hillslope of GCE using RUSLE model

NASA Astrophysics Data System (ADS)

Islam, Md. Rabiul; Jaafar, Wan Zurina Wan; Hin, Lai Sai; Osman, Normaniza; Din, Moktar Aziz Mohd; Zuki, Fathiah Mohamed; Srivastava, Prashant; Islam, Tanvir; Adham, Md. Ibrahim

2018-06-01

A new method for obtaining the C factor (i.e., vegetation cover and management factor) of the RUSLE model is proposed. The method focuses on the derivation of the C factor based on the vegetation density to obtain a more reliable erosion prediction. Soil erosion that occurs on the hillslope along the highway is one of the major problems in Malaysia, which is exposed to a relatively high amount of annual rainfall due to the two different monsoon seasons. As vegetation cover is one of the important factors in the RUSLE model, a new method that accounts for a vegetation density is proposed in this study. A hillslope near the Guthrie Corridor Expressway (GCE), Malaysia, is chosen as an experimental site whereby eight square plots with the size of 8× 8 and 5× 5 m are set up. A vegetation density available on these plots is measured by analyzing the taken image followed by linking the C factor with the measured vegetation density using several established formulas. Finally, erosion prediction is computed based on the RUSLE model in the Geographical Information System (GIS) platform. The C factor obtained by the proposed method is compared with that of the soil erosion guideline Malaysia, thereby predicted erosion is determined by both the C values. Result shows that the C value from the proposed method varies from 0.0162 to 0.125, which is lower compared to the C value from the soil erosion guideline, i.e., 0.8. Meanwhile predicted erosion computed from the proposed C value is between 0.410 and 3.925 t ha^{-1 } yr^{-1} compared to 9.367 to 34.496 t ha^{-1} yr^{-1 } range based on the C value of 0.8. It can be concluded that the proposed method of obtaining a reasonable C value is acceptable as the computed predicted erosion is found to be classified as a very low zone, i.e. less than 10 t ha^{-1 } yr^{-1} whereas the predicted erosion based on the guideline has classified the study area as a low zone of erosion, i.e., between 10 and 50 t ha^{-1 } yr^{-1}.

Microwave pretreatment of switchgrass for bioethanol production

NASA Astrophysics Data System (ADS)

Keshwani, Deepak Radhakrishin

Lignocellulosic materials are promising alternative feedstocks for bioethanol production. These materials include agricultural residues, cellulosic waste such as newsprint and office paper, logging residues, and herbaceous and woody crops. However, the recalcitrant nature of lignocellulosic biomass necessitates a pretreatment step to improve the yield of fermentable sugars. The overall goal of this dissertation is to expand the current state of knowledge on microwave-based pretreatment of lignocellulosic biomass. Existing research on bioenergy and value-added applications of switchgrass is reviewed in Chapter 2. Switchgrass is an herbaceous energy crop native to North America and has high biomass productivity, potentially low requirements for agricultural inputs and positive environmental impacts. Based on results from test plots, yields in excess of 20 Mg/ha have been reported. Environmental benefits associated with switchgrass include the potential for carbon sequestration, nutrient recovery from run-off, soil remediation and provision of habitats for grassland birds. Published research on pretreatment of switchgrass reported glucose yields ranging from 70-90% and xylose yields ranging from 70-100% after hydrolysis and ethanol yields ranging from 72-92% after fermentation. Other potential value-added uses of switchgrass include gasification, bio-oil production, newsprint production and fiber reinforcement in thermoplastic composites. Research on microwave-based pretreatment of switchgrass and coastal bermudagrass is presented in Chapter 3. Pretreatments were carried out by immersing the biomass in dilute chemical reagents and exposing the slurry to microwave radiation at 250 watts for residence times ranging from 5 to 20 minutes. Preliminary experiments identified alkalis as suitable chemical reagents for microwave-based pretreatment. An evaluation of different alkalis identified sodium hydroxide as the most effective alkali reagent. Under optimum pretreatment conditions, 82% glucose and 63% xylose yields were achieved for switchgrass, and 87% glucose and 59% xylose yields were achieved for coastal bermudagrass following enzymatic hydrolysis of the pretreated biomass. The optimum enzyme loadings were 15 FPU/g and 20 CBU/g for switchgrass and 10 FPU/g and 20 CBU/g for coastal bermudagrass. Dielectric properties for dilute sodium hydroxide solutions were measured and compared to solid loss, lignin reduction and reducing sugar levels in hydrolyzates. Results indicate that the dielectric loss tangent of alkali solutions is a potential indicator of the severity of microwave-based pretreatments. Modeling of pretreatment processes can be a valuable tool in process simulations of bioethanol production from lignocellulosic biomass. Chapter 4 discusses three different approaches that were used to model delignification and carbohydrate loss during microwave-based pretreatment of switchgrass: statistical linear regression modeling, kinetic modeling using a time-dependent rate coefficient, and a Mamdani-type fuzzy inference system. The dielectric loss tangent of the alkali reagent and pretreatment time were used as predictors in all models. The statistical linear regression model for delignification gave comparable root mean square error (RMSE) values for training and testing data and predictions were approximately within 1% of experimental values. The kinetic model for delignification and xylan loss gave comparable RMSE values for training and testing data sets and predictions were approximately within 2% of experimental values. The kinetic model for cellulose loss was not as effective and predictions were only within 5-7% of experimental values. The time-dependent rate coefficients of the kinetic models calculated from experimental data were consistent with the heterogeneity (or lack thereof) of individual biomass components. The Mamdani-type fuzzy inference system was shown to be an effective means to model pretreatment processes and gave the most accurate predictions (<3%) for cellulose loss.

Systematic review of validated case definitions for diabetes in ICD-9-coded and ICD-10-coded data in adult populations.

PubMed

Khokhar, Bushra; Jette, Nathalie; Metcalfe, Amy; Cunningham, Ceara Tess; Quan, Hude; Kaplan, Gilaad G; Butalia, Sonia; Rabi, Doreen

2016-08-05

With steady increases in 'big data' and data analytics over the past two decades, administrative health databases have become more accessible and are now used regularly for diabetes surveillance. The objective of this study is to systematically review validated International Classification of Diseases (ICD)-based case definitions for diabetes in the adult population. Electronic databases, MEDLINE and Embase, were searched for validation studies where an administrative case definition (using ICD codes) for diabetes in adults was validated against a reference and statistical measures of the performance reported. The search yielded 2895 abstracts, and of the 193 potentially relevant studies, 16 met criteria. Diabetes definition for adults varied by data source, including physician claims (sensitivity ranged from 26.9% to 97%, specificity ranged from 94.3% to 99.4%, positive predictive value (PPV) ranged from 71.4% to 96.2%, negative predictive value (NPV) ranged from 95% to 99.6% and κ ranged from 0.8 to 0.9), hospital discharge data (sensitivity ranged from 59.1% to 92.6%, specificity ranged from 95.5% to 99%, PPV ranged from 62.5% to 96%, NPV ranged from 90.8% to 99% and κ ranged from 0.6 to 0.9) and a combination of both (sensitivity ranged from 57% to 95.6%, specificity ranged from 88% to 98.5%, PPV ranged from 54% to 80%, NPV ranged from 98% to 99.6% and κ ranged from 0.7 to 0.8). Overall, administrative health databases are useful for undertaking diabetes surveillance, but an awareness of the variation in performance being affected by case definition is essential. The performance characteristics of these case definitions depend on the variations in the definition of primary diagnosis in ICD-coded discharge data and/or the methodology adopted by the healthcare facility to extract information from patient records. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

[A site index model for Larix principis-rupprechtii plantation in Saihanba, north China].

PubMed

Wang, Dong-zhi; Zhang, Dong-yan; Jiang, Feng-ling; Bai, Ye; Zhang, Zhi-dong; Huang, Xuan-rui

2015-11-01

It is often difficult to estimate site indices for different types of plantation by using an ordinary site index model. The objective of this paper was to establish a site index model for plantations in varied site conditions, and assess the site qualities. In this study, a nonlinear mixed site index model was constructed based on data from the second class forest resources inventory and 173 temporary sample plots. The results showed that the main limiting factors for height growth of Larix principis-rupprechtii were elevation, slope, soil thickness and soil type. A linear regression model was constructed for the main constraining site factors and dominant tree height, with the coefficient of determination being 0.912, and the baseline age of Larix principis-rupprechtii determined as 20 years. The nonlinear mixed site index model parameters for the main site types were estimated (R2 > 0.85, the error between the predicted value and the actual value was in the range of -0.43 to 0.45, with an average root mean squared error (RMSE) in the range of 0.907 to 1.148). The estimation error between the predicted value and the actual value of dominant tree height for the main site types was in the confidence interval of [-0.95, 0.95]. The site quality of the high altitude-shady-sandy loam-medium soil layer was the highest and that of low altitude-sunny-sandy loam-medium soil layer was the lowest, while the other two sites were moderate.

Ecology and geography of avian influenza (HPAI H5N1) transmission in the Middle East and northeastern Africa

PubMed Central

Williams, Richard AJ; Peterson, A Townsend

2009-01-01

Background The emerging highly pathogenic avian influenza strain H5N1 ("HPAI-H5N1") has spread broadly in the past decade, and is now the focus of considerable concern. We tested the hypothesis that spatial distributions of HPAI-H5N1 cases are related consistently and predictably to coarse-scale environmental features in the Middle East and northeastern Africa. We used ecological niche models to relate virus occurrences to 8 km resolution digital data layers summarizing parameters of monthly surface reflectance and landform. Predictive challenges included a variety of spatial stratification schemes in which models were challenged to predict case distributions in broadly unsampled areas. Results In almost all tests, HPAI-H5N1 cases were indeed occurring under predictable sets of environmental conditions, generally predicted absent from areas with low NDVI values and minimal seasonal variation, and present in areas with a broad range of and appreciable seasonal variation in NDVI values. Although we documented significant predictive ability of our models, even between our study region and West Africa, case occurrences in the Arabian Peninsula appear to follow a distinct environmental regime. Conclusion Overall, we documented a variable environmental "fingerprint" for areas suitable for HPAI-H5N1 transmission. PMID:19619336

Multiplier method may be unreliable to predict the timing of temporary hemiepiphysiodesis for coronal angular deformity.

PubMed

Wu, Zhenkai; Ding, Jing; Zhao, Dahang; Zhao, Li; Li, Hai; Liu, Jianlin

2017-07-10

The multiplier method was introduced by Paley to calculate the timing for temporary hemiepiphysiodesis. However, this method has not been verified in terms of clinical outcome measure. We aimed to (1) predict the rate of angular correction per year (ACPY) at the various corresponding ages by means of multiplier method and verify the reliability based on the data from the published studies and (2) screen out risk factors for deviation of prediction. A comprehensive search was performed in the following electronic databases: Cochrane, PubMed, and EMBASE™. A total of 22 studies met the inclusion criteria. If the actual value of ACPY from the collected date was located out of the range of the predicted value based on the multiplier method, it was considered as the deviation of prediction (DOP). The associations of patient characteristics with DOP were assessed with the use of univariate logistic regression. Only one article was evaluated as moderate evidence; the remaining articles were evaluated as poor quality. The rate of DOP was 31.82%. In the detailed individual data of included studies, the rate of DOP was 55.44%. The multiplier method is not reliable in predicting the timing for temporary hemiepiphysiodesis, even though it is prone to be more reliable for the younger patients with idiopathic genu coronal deformity.

Predictive performance of three practical approaches for grapefruit juice-induced 2-fold or greater increases in AUC of concomitantly administered drugs.

PubMed

Takahashi, M; Onozawa, S; Ogawa, R; Uesawa, Y; Echizen, H

2015-02-01

Clinical pharmacists have a challenging task when answering patients' question about whether they can take specific drugs with grapefruit juice (GFJ) without risk of drug interaction. To identify the most practicable method for predicting clinically relevant changes in plasma concentrations of orally administered drugs caused by the ingestion of GFJ, we compared the predictive performance of three methods using data obtained from the literature. We undertook a systematic search of drug interactions associated with GFJ using MEDLINE and the Metabolism & Transport Drug Interaction Database (DIDB version 4.0). We considered an elevation of the area under the plasma concentration-time curve (AUC) of 2 or greater relative to the control value [AUC ratio (AUCR) ≥ 2.0] as a clinically significant interaction. The data from 74 drugs (194 data sets) were analysed. When the reported information of CYP3A involvement in the metabolism of a drug of interest was adopted as a predictive criterion for GFJ-drug interaction, the performance assessed by positive predictive value (PPV) was low (0.26), but that assessed by negative predictive value (NPV) and sensitivity was high (1.00 for both). When the reported oral bioavailability of ≤ 0.1 was used as a criterion, the PPV improved to 0.50 with an acceptable NPV of 0.81, but sensitivity was reduced to 0.21. When the reported AUCR was ≥ 10 after co-administration of a typical CYP3A inhibitor, the corresponding values were 0.64, 0.79 and 0.19, respectively. We consider that an oral bioavailability of ≤ 0.1 or an AUCR of ≥ 10 caused by a CYP3A inhibitor of a drug of interest may be a practical prediction criterion for avoiding significant interactions with GFJ. Information about the involvement of CYP3A in their metabolism should also be taken into account for drugs with narrow therapeutic ranges. © 2014 John Wiley & Sons Ltd.

Characterization of oxygen transfer in miniature and lab-scale bubble column bioreactors and comparison of microbial growth performance based on constant k(L)a.

PubMed

Doig, Steven D; Ortiz-Ochoa, Kenny; Ward, John M; Baganz, Frank

2005-01-01

This work describes the engineering characterization of miniature (2 mL) and laboratory-scale (100 mL) bubble column bioreactors useful for the cultivation of microbial cells. These bioreactors were constructed of glass and used a range of sintered glass gas diffusers with differently sized pores to disperse humidified air within the liquid biomedium. The effect of the pressure of this supplied air on the breakthrough point for gas diffusers with different pore sizes was examined and could be predicted using the Laplace-Young equation. The influence of the superficial gas velocity (u(g)) on the volumetric mass transfer coefficient (k(L)a) was determined, and values of up to 0.09 s(-1) were observed in this work. Two modeling approaches were considered in order to predict and provide comparison criteria. The first related the volumetric power consumption (P/V) to the k(L)a and a good correlation was obtained for differently sized reactors with a given pore size, but this correlation was not satisfactory for bubble columns with different gas diffusers. Values for P/V ranged from about 10 to 400 W.m(-3). Second, a model was developed predicting bubble size (d(b)), bubble rising velocity (u(b)), gas hold-up (phi), liquid side mass transfer coefficient (k(L)), and thus the k(L)a using established theory and empirical correlations. Good agreement was found with our experimental data at different scales and pore sizes. Values for d(b) varied from 0.1 to 0.6 mm, and k(L) values between 1.7 and 9.8 x 10(-4) m.s(-1) were determined. Several E. coli cultivations were performed in the miniature bubble column at low and high k(L)a values, and the results were compared to those from a conventional stirred tank operated under identical k(L)a values. Results from the two systems were similar in terms of biomass growth rate and carbon source utilization.

Optical absorption of carbon and hydrocarbon species from shock heated acetylene and methane in the 135-220 nm wavelength range

NASA Technical Reports Server (NTRS)

Shinn, J. L.

1981-01-01

Absorption spectroscopy of carbon and hydrocarbon species has been performed in a shock tube at an incident shock condition for a wavelength range of 135-220 nm, in order to obtain information needed for calculating radiation blockage ahead of a planetary probe. Instrumentation consisted of high frequency response pressure transducers, thin-film heat transfer gages, or photomultipliers coupled by light pipes. Two test-gas mixtures, one with acetylene and the other with methane, both diluted with argon, were used to provide a reliable variation of C3 and C2H concentration ratio. Comparison of tests results of the two mixtures, in the temperature range of 3750 + or - 100 K, showed the main absorbing species to be C3. The wavelength for maximum absorption agrees well with the theoretical values of 7.68 eV and 8.03 eV for the vertical excitation energy, and a value of 0.90 for the electronic oscillator strength, obtained from the measured absorption band, is also in good agreement with the predicted value of 0.92.

A modification of Murray's law for shear-thinning rheology.

PubMed

McGah, Patrick M; Capobianchi, Massimo

2015-05-01

This study reformulates Murray's well-known principle of minimum work as applied to the cardiovascular system to include the effects of the shear-thinning rheology of blood. The viscous behavior is described using the extended modified power law (EMPL), which is a time-independent, but shear-thinning rheological constitutive equation. The resulting minimization problem is solved numerically for typical parameter ranges. The non-Newtonian analysis still predicts the classical cubic diameter dependence of the volume flow rate and the cubic branching law. The current analysis also predicts a constant wall shear stress throughout the vascular tree, albeit with a numerical value about 15-25% higher than the Newtonian analysis. Thus, experimentally observed deviations from the cubic branching law or the predicted constant wall shear stress in the vasculature cannot likely be attributed to blood's shear-thinning behavior. Further differences between the predictions of the non-Newtonian and the Newtonian analyses are highlighted, and the limitations of the Newtonian analysis are discussed. Finally, the range and limits of applicability of the current results as applied to the human arterial tree are also discussed.

Prediction of the Creep-Fatigue Lifetime of Alloy 617: An Application of Non-destructive Evaluation and Information Integration

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

Vivek Agarwal; Richard Wright; Timothy Roney

A relatively simple method using the nominal constant average stress information and the creep rupture model is developed to predict the creep-fatigue lifetime of Alloy 617, in terms of time to rupture. The nominal constant average stress is computed using the stress relaxation curve. The predicted time to rupture can be converted to number of cycles to failure using the strain range, the strain rate during each cycle, and the hold time information. The predicted creep-fatigue lifetime is validated against the experimental measurements of the creep-fatigue lifetime collected using conventional laboratory creep-fatigue tests. High temperature creep-fatigue tests of Alloy 617more » were conducted in air at 950°C with a tensile hold period of up to 1800s in a cycle at total strain ranges of 0.3% and 0.6%. It was observed that the proposed method is conservative in that the predicted lifetime is less than the experimentally determined values. The approach would be relevant to calculate the remaining useful life to a component like a steam generator that might fail by the creep-fatigue mechanism.« less

Real-time demonstration and evaluation of over-the-loop short to medium-range ensemble streamflow forecasting

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, E.; Newman, A. J.; Nijssen, B.; Clark, M. P.; Gangopadhyay, S.; Arnold, J. R.

2015-12-01

The US National Weather Service River Forecasting Centers are beginning to operationalize short range to medium range ensemble predictions that have been in development for several years. This practice contrasts with the traditional single-value forecast practice at these lead times not only because the ensemble forecasts offer a basis for quantifying forecast uncertainty, but also because the use of ensembles requires a greater degree of automation in the forecast workflow than is currently used. For instance, individual ensemble member forcings cannot (practically) be manually adjusted, a step not uncommon with the current single-value paradigm, thus the forecaster is required to adopt a more 'over-the-loop' role than before. The relative lack of experience among operational forecasters and forecast users (eg, water managers) in the US with over-the-loop approaches motivates the creation of a real-time demonstration and evaluation platform for exploring the potential of over-the-loop workflows to produce usable ensemble short-to-medium range forecasts, as well as long range predictions. We describe the development and early results of such an effort by a collaboration between NCAR and the two water agencies, the US Army Corps of Engineers and the US Bureau of Reclamation. Focusing on small to medium sized headwater basins around the US, and using multi-decade series of ensemble streamflow hindcasts, we also describe early results, assessing the skill of daily-updating, over-the-loop forecasts driven by a set of ensemble atmospheric outputs from the NCEP GEFS for lead times from 1-15 days.

Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models.

PubMed

Yock, Adam D; Rao, Arvind; Dong, Lei; Beadle, Beth M; Garden, Adam S; Kudchadker, Rajat J; Court, Laurence E

2014-05-01

The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: -11.6%-23.8%) and 14.6% (range: -7.3%-27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: -6.8%-40.3%) and 13.1% (range: -1.5%-52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: -11.1%-20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.

Applying the Expectancy-Value Model to understand health values.

PubMed

Zhang, Xu-Hao; Xie, Feng; Wee, Hwee-Lin; Thumboo, Julian; Li, Shu-Chuen

2008-03-01

Expectancy-Value Model (EVM) is the most structured model in psychology to predict attitudes by measuring attitudinal attributes (AAs) and relevant external variables. Because health value could be categorized as attitude, we aimed to apply EVM to explore its usefulness in explaining variances in health values and investigate underlying factors. Focus group discussion was carried out to identify the most common and significant AAs toward 5 different health states (coded as 11111, 11121, 21221, 32323, and 33333 in EuroQol Five-Dimension (EQ-5D) descriptive system). AAs were measured in a sum of multiplications of subjective probability (expectancy) and perceived value of attributes with 7-point Likert scales. Health values were measured using visual analog scales (VAS, range 0-1). External variables (age, sex, ethnicity, education, housing, marital status, and concurrent chronic diseases) were also incorporated into survey questionnaire distributed by convenience sampling among eligible respondents. Univariate analyses were used to identify external variables causing significant differences in VAS. Multiple linear regression model (MLR) and hierarchical regression model were used to investigate the explanatory power of AAs and possible significant external variable(s) separately or in combination, for each individual health state and a mixed scenario of five states, respectively. Four AAs were identified, namely, "worsening your quality of life in terms of health" (WQoL), "adding a burden to your family" (BTF), "making you less independent" (MLI) and "unable to work or study" (UWS). Data were analyzed based on 232 respondents (mean [SD] age: 27.7 [15.07] years, 49.1% female). Health values varied significantly across 5 health states, ranging from 0.12 (33333) to 0.97 (11111). With no significant external variables identified, EVM explained up to 62% of the variances in health values across 5 health states. The explanatory power of 4 AAs were found to be between 13% and 28% in separate MLR models (P < 0.05). When data were analyzed for each health state, variances in health values became small and explanatory power of EVM was reduced to a range between 8% and 23%. EVM was useful in explaining variances of health values and predicting important factors. Its power to explain small variances might be restricted due to limitations of 7-point Likert scale to measure AAs accurately. With further improvement and validation of a compatible continuous scale for more accurate measurement, EVM is expected to explain health values to a larger extent.

Linking CDOM spectral absorption to dissolved organic carbon concentrations and loadings in boreal estuaries

NASA Astrophysics Data System (ADS)

Asmala, Eero; Stedmon, Colin A.; Thomas, David N.

2012-10-01

The quantity of chromophoric dissolved organic matter (CDOM) and dissolved organic carbon (DOC) in three Finnish estuaries (Karjaanjoki, Kyrönjoki and Kiiminkijoki) was investigated, with respect to predicting DOC concentrations and loadings from spectral CDOM absorption measurements. Altogether 87 samples were collected from three estuarine transects which were studied in three seasons, covering a salinity range between 0 and 6.8, and DOC concentrations from 1572 μmol l-1 in freshwater to 222 μmol l-1 in coastal waters. CDOM absorption coefficient, aCDOM(375) values followed the trend in DOC concentrations across the salinity gradient and ranged from 1.67 to 33.4 m-1. The link between DOC and CDOM was studied using a range of wavelengths and algorithms. Wavelengths between 250 and 270 nm gave the best predictions with single linear regression. Total dissolved iron was found to influence the prediction in wavelengths above 520 nm. Despite significant seasonal and spatial differences in DOC-CDOM models, a universal relationship was tested with an independent data set and found to be robust. DOC and CDOM yields (loading/catchment area) from the catchments ranged from 1.98 to 5.44 g C m-2 yr-1, and 1.67 to 11.5 aCDOM(375) yr-1, respectively.

High-Area-Ratio Rocket Nozzle at High Combustion Chamber Pressure: Experimental and Analytical Validation

NASA Technical Reports Server (NTRS)

Jankovsky, Robert S.; Smith, Timothy D.; Pavli, Albert J.

1999-01-01

Experimental data were obtained on an optimally contoured nozzle with an area ratio of 1025:1 and on a truncated version of this nozzle with an area ratio of 440:1. The nozzles were tested with gaseous hydrogen and liquid oxygen propellants at combustion chamber pressures of 1800 to 2400 psia and mixture ratios of 3.89 to 6.15. This report compares the experimental performance, heat transfer, and boundary layer total pressure measurements with theoretical predictions of the current Joint Army, Navy, NASA, Air Force (JANNAF) developed methodology. This methodology makes use of the Two-Dimensional Kinetics (TDK) nozzle performance code. Comparisons of the TDK-predicted performance to experimentally attained thrust performance indicated that both the vacuum thrust coefficient and the vacuum specific impulse values were approximately 2.0-percent higher than the turbulent prediction for the 1025:1 configurations, and approximately 0.25-percent higher than the turbulent prediction for the 440:1 configuration. Nozzle wall temperatures were measured on the outside of a thin-walled heat sink nozzle during the test fittings. Nozzle heat fluxes were calculated front the time histories of these temperatures and compared with predictions made with the TDK code. The heat flux values were overpredicted for all cases. The results range from nearly 100 percent at an area ratio of 50 to only approximately 3 percent at an area ratio of 975. Values of the integral of the heat flux as a function of nozzle surface area were also calculated. Comparisons of the experiment with analyses of the heat flux and the heat rate per axial length also show that the experimental values were lower than the predicted value. Three boundary layer rakes mounted on the nozzle exit were used for boundary layer measurements. This arrangement allowed total pressure measurements to be obtained at 14 different distances from the nozzle wall. A comparison of boundary layer total pressure profiles and analytical predictions show good agreement for the first 0.5 in. from the nozzle wall; but the further into the core flow that measurements were taken, the more that TDK overpredicted the boundary layer thickness.

The microwave propagation and backscattering characteristics of vegetation. [wheat, sorghum, soybeans and corn fields in Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Wilson, E. A.

1984-01-01

A semi-empirical model for microwave backscatter from vegetation was developed and a complete set of canope attenuation measurements as a function of frequency, incidence angle and polarization was acquired. The semi-empirical model was tested on corn and sorghum data over the 8 to 35 GHz range. The model generally provided an excellent fit to the data as measured by the correlation and rms error between observed and predicted data. The model also predicted reasonable values of canopy attenuation. The attenuation data was acquired over the 1.6 to 10.2 GHz range for the linear polarizations at approximately 20 deg and 50 deg incidence angles for wheat and soybeans. An attenuation model is proposed which provides reasonable agreement with the measured data.

Positive predictive value estimates for cell-free noninvasive prenatal screening from data of a large referral genetic diagnostic laboratory.

PubMed

Petersen, Andrea K; Cheung, Sau Wai; Smith, Janice L; Bi, Weimin; Ward, Patricia A; Peacock, Sandra; Braxton, Alicia; Van Den Veyver, Ignatia B; Breman, Amy M

2017-12-01

Since its debut in 2011, cell-free fetal DNA screening has undergone rapid expansion with respect to both utilization and coverage. However, conclusive data regarding the clinical validity and utility of this screening tool, both for the originally included common autosomal and sex-chromosomal aneuploidies as well as the more recently added chromosomal microdeletion syndromes, have lagged behind. Thus, there is a continued need to educate clinicians and patients about the current benefits and limitations of this screening tool to inform pre- and posttest counseling, pre/perinatal decision making, and medical risk assessment/management. The objective of this study was to determine the positive predictive value and false-positive rates for different chromosomal abnormalities identified by cell-free fetal DNA screening using a large data set of diagnostic testing results on invasive samples submitted to the laboratory for confirmatory studies. We tested 712 patient samples sent to our laboratory to confirm a cell-free fetal DNA screening result, indicating high risk for a chromosome abnormality. We compiled data from all cases in which the indication for confirmatory testing was a positive cell-free fetal DNA screen, including the common trisomies, sex chromosomal aneuploidies, microdeletion syndromes, and other large genome-wide copy number abnormalities. Testing modalities included fluorescence in situ hybridization, G-banded karyotype, and/or chromosomal microarray analysis performed on chorionic villus samples, amniotic fluid, or postnatally obtained blood samples. Positive predictive values and false-positive rates were calculated from tabulated data. The positive predictive values for trisomy 13, 18, and 21 were consistent with previous reports at 45%, 76%, and 84%, respectively. For the microdeletion syndrome regions, positive predictive values ranged from 0% for detection of Cri-du-Chat syndrome and Prader-Willi/Angelman syndrome to 14% for 1p36 deletion syndrome and 21% for 22q11.2 deletion syndrome. Detection of sex chromosomal aneuploidies had positive predictive values of 26% for monosomy X, 50% for 47,XXX, and 86% for 47,XXY. The positive predictive values for detection of common autosomal and sex chromosomal aneuploidies by cell-free fetal DNA screening were comparable with other studies. Identification of microdeletions was associated with lower positive predictive values and higher false-positive rates, likely because of the low prevalence of the individual targeted microdeletion syndromes in the general population. Although the obtained positive predictive values compare favorably with those seen in traditional screening approaches for common aneuploidies, they highlight the importance of educating clinicians and patients on the limitations of cell-free fetal DNA screening tests. Improvement of the cell-free fetal DNA screening technology and continued monitoring of its performance after introduction into clinical practice will be important to fully establish its clinical utility. Nonetheless, our data provide valuable information that may aid result interpretation, patient counseling, and clinical decision making/management. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Health fair screening: the clinical utility of the comprehensive metabolic profile.

PubMed

Alpert, Jeffrey P; Greiner, Allen; Hall, Sandra

2004-01-01

Health fairs are a common method used by providers and health care organizations to provide screening tests, including comprehensive metabolic profiles (CMPs), to asymptomatic individuals. No national organizations currently recommend the complete CMP as a screening test for asymptomatic individuals in primary care settings. This study evaluated the value of CMPs in a health fair setting by measuring the ability of a health fair CMP to predict new medical diagnoses among residents of a sparsely populated rural county. Volunteer participants submitted fasting blood samples at a health fair conducted by a county health center in a county with 2,531 total residents. CMP values were determined to be "normal" or "abnormal" based on laboratory reference ranges and clinical judgment of the health center physicians. Medical records were reviewed 4 months later to determine if participants with abnormal CMP values had been diagnosed with new medical conditions as a result of the screening tests. Analysis was conducted to evaluate CMP test characteristics and determine whether demographic factors or specific CMP values predicted new medical diagnoses in the participants. Out of 478 health fair participants, 73 individuals had at least one abnormal CMP value. The most frequently occurring abnormal value was an elevated glucose level, with Hispanic participants significantly more likely to have this abnormality than whites. After all evaluation was completed, only about 1% of tested subjects had a new diagnosis as a result of the screening CMP test; most abnormal CMP tests did not result in a new diagnosis. The positive predictive value for an abnormal test resulting in a new medical diagnosis was 0.356. Comprehensive metabolic profiles have limited value as a screening tool in asymptomatic populations at health fairs.

Comparison of in situ uranium KD values with a laboratory determined surface complexation model

USGS Publications Warehouse

Curtis, G.P.; Fox, P.; Kohler, M.; Davis, J.A.

2004-01-01

Reactive solute transport simulations in groundwater require a large number of parameters to describe hydrologic and chemical reaction processes. Appropriate methods for determining chemical reaction parameters required for reactive solute transport simulations are still under investigation. This work compares U(VI) distribution coefficients (i.e. KD values) measured under field conditions with KD values calculated from a surface complexation model developed in the laboratory. Field studies were conducted in an alluvial aquifer at a former U mill tailings site near the town of Naturita, CO, USA, by suspending approximately 10 g samples of Naturita aquifer background sediments (NABS) in 17-5.1-cm diameter wells for periods of 3 to 15 months. Adsorbed U(VI) on these samples was determined by extraction with a pH 9.45 NaHCO3/Na2CO3 solution. In wells where the chemical conditions in groundwater were nearly constant, adsorbed U concentrations for samples taken after 3 months of exposure to groundwater were indistinguishable from samples taken after 15 months. Measured in situ K D values calculated from the measurements of adsorbed and dissolved U(VI) ranged from 0.50 to 10.6 mL/g and the KD values decreased with increasing groundwater alkalinity, consistent with increased formation of soluble U(VI)-carbonate complexes at higher alkalinities. The in situ K D values were compared with KD values predicted from a surface complexation model (SCM) developed under laboratory conditions in a separate study. A good agreement between the predicted and measured in situ KD values was observed. The demonstration that the laboratory derived SCM can predict U(VI) adsorption in the field provides a critical independent test of a submodel used in a reactive transport model. ?? 2004 Elsevier Ltd. All rights reserved.

Differential diagnosis of benign and malignant breast masses using diffusion-weighted magnetic resonance imaging.

PubMed

Min, Qinghua; Shao, Kangwei; Zhai, Lulan; Liu, Wei; Zhu, Caisong; Yuan, Lixin; Yang, Jun

2015-02-07

Diffusion-weighted magnetic resonance imaging (DW-MRI) is different from conventional diagnostic methods and has the potential to delineate the microscopic anatomy of a target tissue or organ. The purpose of our study was to evaluate the value of DW-MRI in the diagnosis of benign and malignant breast masses, which would help the clinical surgeon to decide the scope and pattern of operation. A total of 52 female patients with palpable solid breast masses received breast MRI scans using routine sequences, dynamic contrast-enhanced imaging, and diffusion-weighted echo-planar imaging at b values of 400, 600, and 800 s/mm(2), respectively. Two regions of interest (ROIs) were plotted, with a smaller ROI for the highest signal and a larger ROI for the overall lesion. Apparent diffusion coefficient (ADC) values were calculated at three different b values for all detectable lesions and from two different ROIs. The sensitivity, specificity, positive predictive value, and positive likelihood ratio of DW-MRI were determined for comparison with histological results. A total of 49 (49/52, 94.2%) lesions were detected using DW-MRI, including 20 benign lesions (two lesions detected in the same patient) and 29 malignant lesions. Benign lesion had a higher mean ADC value than their malignant counterparts, regardless of b value. According to the receiver operating characteristic (ROC) curve, the smaller-range ROI was more effective in differentiation between benign and malignant lesions. The area under the ROC curve was the largest at a b value of 800 s/mm(2). With a threshold ADC value at 1.23 × 10(-3) mm(2)/s, DW-MRI achieved a sensitivity of 82.8%, specificity of 90.0%, positive predictive value of 92.3%, and positive likelihood ratio of 8.3 for differentiating benign and malignant lesions. DW-MRI is an accurate diagnostic tool for differentiation between benign and malignant breast lesions, with an optimal b value of 800 s/mm(2). A smaller-range ROI focusing on the highest signal has a better differential value.

Radiative PQ breaking and the Higgs boson mass

NASA Astrophysics Data System (ADS)

D'Eramo, Francesco; Hall, Lawrence J.; Pappadopulo, Duccio

2015-06-01

The small and negative value of the Standard Model Higgs quartic coupling at high scales can be understood in terms of anthropic selection on a landscape where large and negative values are favored: most universes have a very short-lived electroweak vacuum and typical observers are in universes close to the corresponding metastability boundary. We provide a simple example of such a landscape with a Peccei-Quinn symmetry breaking scale generated through dimensional transmutation and supersymmetry softly broken at an intermediate scale. Large and negative contributions to the Higgs quartic are typically generated on integrating out the saxion field. Cancellations among these contributions are forced by the anthropic requirement of a sufficiently long-lived electroweak vacuum, determining the multiverse distribution for the Higgs quartic in a similar way to that of the cosmological constant. This leads to a statistical prediction of the Higgs boson mass that, for a wide range of parameters, yields the observed value within the 1σ statistical uncertainty of ˜ 5 GeV originating from the multiverse distribution. The strong CP problem is solved and single-component axion dark matter is predicted, with an abundance that can be understood from environmental selection. A more general setting for the Higgs mass prediction is discussed.

A stepwise model to predict monthly streamflow

NASA Astrophysics Data System (ADS)

Mahmood Al-Juboori, Anas; Guven, Aytac

2016-12-01

In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

3-D residual eddy current field characterisation: applied to diffusion weighted magnetic resonance imaging.

PubMed

O'Brien, Kieran; Daducci, Alessandro; Kickler, Nils; Lazeyras, Francois; Gruetter, Rolf; Feiweier, Thorsten; Krueger, Gunnar

2013-08-01

Clinical use of the Stejskal-Tanner diffusion weighted images is hampered by the geometric distortions that result from the large residual 3-D eddy current field induced. In this work, we aimed to predict, using linear response theory, the residual 3-D eddy current field required for geometric distortion correction based on phantom eddy current field measurements. The predicted 3-D eddy current field induced by the diffusion-weighting gradients was able to reduce the root mean square error of the residual eddy current field to ~1 Hz. The model's performance was tested on diffusion weighted images of four normal volunteers, following distortion correction, the quality of the Stejskal-Tanner diffusion-weighted images was found to have comparable quality to image registration based corrections (FSL) at low b-values. Unlike registration techniques the correction was not hindered by low SNR at high b-values, and results in improved image quality relative to FSL. Characterization of the 3-D eddy current field with linear response theory enables the prediction of the 3-D eddy current field required to correct eddy current induced geometric distortions for a wide range of clinical and high b-value protocols.

Validation study of the SCREENIVF: an instrument to screen women or men on risk for emotional maladjustment before the start of a fertility treatment.

PubMed

Ockhuijsen, Henrietta D L; van Smeden, Maarten; van den Hoogen, Agnes; Boivin, Jacky

2017-06-01

To examine construct and criterion validity of the Dutch SCREENIVF among women and men undergoing a fertility treatment. A prospective longitudinal study nested in a randomized controlled trial. University hospital. Couples, 468 women and 383 men, undergoing an IVF/intracytoplasmic sperm injection (ICSI) treatment in a fertility clinic, completed the SCREENIVF. Construct and criteria validity of the SCREENIVF. The comparative fit index and root mean square error of approximation for women and men show a good fit of the factor model. Across time, the sensitivity for Hospital Anxiety and Depression Scale subscale in women ranged from 61%-98%, specificity 53%-65%, predictive value of a positive test (PVP) 13%-56%, predictive value of a negative test (PVN) 70%-99%. The sensitivity scores for men ranged from 38%-100%, specificity 71%-75%, PVP 9%-27%, PVN 92%-100%. A prediction model revealed that for women 68.7% of the variance in the Hospital Anxiety and Depression Scale on time 1 and 42.5% at time 2 and 38.9% at time 3 was explained by the predictors, the sum score scales of the SCREENIVF. For men, 58.1% of the variance in the Hospital Anxiety and Depression Scale on time 1 and 46.5% at time 2 and 37.3% at time 3 was explained by the predictors, the sum score scales of the SCREENIVF. The SCREENIVF has good construct validity but the concurrent validity is better than the predictive validity. SCREENIVF will be most effectively used in fertility clinics at the start of treatment and should not be used as a predictive tool. Copyright © 2017 American Society for Reproductive Medicine. All rights reserved.

Predictive value of low tube voltage and dual-energy CT for successful shock wave lithotripsy: an in vitro study.

PubMed

Largo, Remo; Stolzmann, Paul; Fankhauser, Christian D; Poyet, Cédric; Wolfsgruber, Pirmin; Sulser, Tullio; Alkadhi, Hatem; Winklhofer, Sebastian

2016-06-01

This study investigates the capabilities of low tube voltage computed tomography (CT) and dual-energy CT (DECT) for predicting successful shock wave lithotripsy (SWL) of urinary stones in vitro. A total of 33 urinary calculi (six different chemical compositions; mean size 6 ± 3 mm) were scanned using a dual-source CT machine with single- (120 kVp) and dual-energy settings (80/150, 100/150 Sn kVp) resulting in six different datasets. The attenuation (Hounsfield Units) of calculi was measured on single-energy CT images and the dual-energy indices (DEIs) were calculated from DECT acquisitions. Calculi underwent SWL and the number of shock waves for successful disintegration was recorded. The prediction of required shock waves regarding stone attenuation/DEI was calculated using regression analysis (adjusted for stone size and composition) and the correlation between CT attenuation/DEI and the number of shock waves was assessed for all datasets. The median number of shock waves for successful stone disintegration was 72 (interquartile range 30-361). CT attenuation/DEI of stones was a significant, independent predictor (P < 0.01) for the number of required shock waves with the best prediction at 80 kVp (β estimate 0.576) (P < 0.05). Correlation coefficients between attenuation/DEI and the number of required shock waves ranged between ρ = 0.31 and 0.68 showing the best correlation at 80 kVp (P < 0.001). The attenuation of urinary stones at low tube voltage CT is the best predictor for successful stone disintegration, being independent of stone composition and size. DECT shows no added value for predicting the success of SWL.

Ventricular Cycle Length Characteristics Estimative of Prolonged RR Interval during Atrial Fibrillation

PubMed Central

CIACCIO, EDWARD J.; BIVIANO, ANGELO B.; GAMBHIR, ALOK; EINSTEIN, ANDREW J.; GARAN, HASAN

2014-01-01

Background When atrial fibrillation (AF) is incessant, imaging during a prolonged ventricular RR interval may improve image quality. It was hypothesized that long RR intervals could be predicted from preceding RR values. Methods From the PhysioNet database, electrocardiogram RR intervals were obtained from 74 persistent AF patients. An RR interval lengthened by at least 250 ms beyond the immediately preceding RR interval (termed T0 and T1, respectively) was considered prolonged. A two-parameter scatterplot was used to predict the occurrence of a prolonged interval T0. The scatterplot parameters were: (1) RR variability (RRv) estimated as the average second derivative from 10 previous pairs of RR differences, T13–T2, and (2) Tm–T1, the difference between Tm, the mean from T13 to T2, and T1. For each patient, scatterplots were constructed using preliminary data from the first hour. The ranges of parameters 1 and 2 were adjusted to maximize the proportion of prolonged RR intervals within range. These constraints were used for prediction of prolonged RR in test data collected during the second hour. Results The mean prolonged event was 1.0 seconds in duration. Actual prolonged events were identified with a mean positive predictive value (PPV) of 80% in the test set. PPV was >80% in 36 of 74 patients. An average of 10.8 prolonged RR intervals per 60 minutes was correctly identified. Conclusions A method was developed to predict prolonged RR intervals using two parameters and prior statistical sampling for each patient. This or similar methodology may help improve cardiac imaging in many longstanding persistent AF patients. PMID:23998759

Prediction of Rate Constant for Supramolecular Systems with Multiconfigurations.

PubMed

Guo, Tao; Li, Haiyan; Wu, Li; Guo, Zhen; Yin, Xianzhen; Wang, Caifen; Sun, Lixin; Shao, Qun; Gu, Jingkai; York, Peter; Zhang, Jiwen

2016-02-25

The control of supramolecular systems requires a thorough understanding of their dynamics, especially on a molecular level. It is extremely difficult to determine the thermokinetic parameters of supramolecular systems, such as drug-cyclodextrin complexes with fast association/dissociation processes by experimental techniques. In this paper, molecular modeling combined with novel mathematical relationships integrating the thermodynamic/thermokinetic parameters of a series of isomeric multiconfigurations to predict the overall parameters in a range of pH values have been employed to study supramolecular dynamics at the molecular level. A suitable form of Eyring's equation was derived and a two-stage model was introduced. The new approach enabled accurate prediction of the apparent dissociation/association (k(off)/k(on)) and unbinding/binding (k-r/kr) rate constants of the ubiquitous multiconfiguration complexes of the supramolecular system. The pyronine Y (PY) was used as a model system for the validation of the presented method. Interestingly, the predicted k(off) value ((40 ± 1) × 10(5) s(-1), 298 K) of PY is largely in agreement with that previously determined by fluorescence correlation spectroscopy ((5 ± 3) × 10(5) s(-1), 298 K). Moreover, the k(off)/k(on) and k-r/kr for flurbiprofen-β-cylcodextrin and ibuprofen-β-cyclodextrin systems were also predicted and suggested that the association processes are diffusion-controlled. The methodology is considered to be especially useful in the design and selection of excipients for a supramolecular system with preferred association and dissociation rate constants and understanding their mechanisms. It is believed that this new approach could be applicable to a wide range of ligand-receptor supramolecular systems and will surely help in understanding their complex mechanism.

Predicting the Size of Sunspot Cycle 24 on the Basis of Single- and Bi-Variate Geomagnetic Precursor Methods

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2009-01-01

Examined are single- and bi-variate geomagnetic precursors for predicting the maximum amplitude (RM) of a sunspot cycle several years in advance. The best single-variate fit is one based on the average of the ap index 36 mo prior to cycle minimum occurrence (E(Rm)), having a coefficient of correlation (r) equal to 0.97 and a standard error of estimate (se) equal to 9.3. Presuming cycle 24 not to be a statistical outlier and its minimum in March 2008, the fit suggests cycle 24 s RM to be about 69 +/- 20 (the 90% prediction interval). The weighted mean prediction of 11 statistically important single-variate fits is 116 +/- 34. The best bi-variate fit is one based on the maximum and minimum values of the 12-mma of the ap index; i.e., APM# and APm*, where # means the value post-E(RM) for the preceding cycle and * means the value in the vicinity of cycle minimum, having r = 0.98 and se = 8.2. It predicts cycle 24 s RM to be about 92 +/- 27. The weighted mean prediction of 22 statistically important bi-variate fits is 112 32. Thus, cycle 24's RM is expected to lie somewhere within the range of about 82 to 144. Also examined are the late-cycle 23 behaviors of geomagnetic indices and solar wind velocity in comparison to the mean behaviors of cycles 2023 and the geomagnetic indices of cycle 14 (RM = 64.2), the weakest sunspot cycle of the modern era.

Measurement and Modeling of Acoustic Fields in a Gel Phantom at High Intensities

NASA Astrophysics Data System (ADS)

Canney, Michael S.; Bailey, Michael R.; Khokhlova, Vera A.; Crum, Lawrence A.

2006-05-01

The goal of this work was to compare measured and numerically predicted HIFU pressure waveforms in water and a tissue-mimicking phantom. Waveforms were measured at the focus of a 2-MHz HIFU transducer with a fiber optic hydrophone. The transducer was operated with acoustic powers ranging from 2W to 300W. A KZK-type equation was used for modeling the experimental conditions. Strongly asymmetric nonlinear waves with peak positive pressure up to 80 MPa and peak negative pressure up to 20 MPa were measured in water, while waves up to 50 MPa peak positive pressure and 15 MPa peak negative pressure were measured in tissue phantoms. The values of peak negative pressure corresponded well with numerical simulations and were significantly smaller than predicted by linear extrapolation from low-level measurements. The values of peak positive pressures differed only at high levels of excitation where bandwidth limitations of the hydrophone failed to fully capture the predicted sharp shock fronts.

EUPORIAS: plans and preliminary results

NASA Astrophysics Data System (ADS)

Buontempo, C.

2013-12-01

Recent advances in our understanding and ability to forecast climate variability have meant that skilful predictions are beginning to be routinely made on seasonal to decadal (s2d) timescales. Such forecasts have the potential to be of great value to a wide range of decision-making, where outcomes are strongly influenced by variations in the climate. In 2012 the European Commission funded EUPORIAS, a four year long project to develop prototype end-to-end climate impact prediction services operating on a seasonal to decadal timescale, and assess their value in informing decision-making. EUPORIAS commenced on 1 November 2012, coordinated by the UK Met Office leading a consortium of 24 organisations representing world-class European climate research and climate service centres, expertise in impacts assessments and seasonal predictions, two United Nations agencies, specialists in new media, and commercial companies in climate-vulnerable sectors such as energy, water and tourism. The poster describes the setup of the project, its main outcome and some of the very preliminary results.

Predicting health-related quality of life (EQ-5D-5 L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP.

PubMed

Peak, Jasmine; Goranitis, Ilias; Day, Ed; Copello, Alex; Freemantle, Nick; Frew, Emma

2018-05-30

Economic evaluation normally requires information to be collected on outcome improvement using utility values. This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult. One potential solution is the use of mapping to generate utility values from clinical measures. This study develops and evaluates mapping algorithms that could be used to predict the EuroQol-5D (EQ-5D-5 L) and the ICEpop CAPability measure for Adults (ICECAP-A) from the three commonly used clinical measures; the CORE-OM, the LDQ and the TOP measures. Models were estimated using pilot trial data of heroin users in opiate substitution treatment. In the trial the EQ-5D-5 L, ICECAP-A, CORE-OM, LDQ and TOP were administered at baseline, three and twelve month time intervals. Mapping was conducted using estimation and validation datasets. The normal estimation dataset, which comprised of baseline sample data, used ordinary least squares (OLS) and tobit regression methods. Data from the baseline and three month time periods were combined to create a pooled estimation dataset. Cluster and mixed regression methods were used to map from this dataset. Predictive accuracy of the models was assessed using the root mean square error (RMSE) and the mean absolute error (MAE). Algorithms were validated using sample data from the follow-up time periods. Mapping algorithms can be used to predict the ICECAP-A and the EQ-5D-5 L in the context of opiate dependence. Although both measures can be predicted, the ICECAP-A was better predicted by the clinical measures. There were no advantages of pooling the data. There were 6 chosen mapping algorithms, which had MAE scores ranging from 0.100 to 0.138 and RMSE scores ranging from 0.134 to 0.178. It is possible to predict the scores of the ICECAP-A and the EQ-5D-5 L with the use of mapping. In the context of opiate dependence, these algorithms provide the possibility of generating utility values from clinical measures and thus enabling economic evaluation of alternative therapy options. ISRCTN22608399 . Date of registration: 27/04/2012. Date of first randomisation: 14/08/2012.

Estimating Time-Varying PCB Exposures Using Person-Specific Predictions to Supplement Measured Values: A Comparison of Observed and Predicted Values in Two Cohorts of Norwegian Women

PubMed Central

Nøst, Therese Haugdahl; Breivik, Knut; Wania, Frank; Rylander, Charlotta; Odland, Jon Øyvind; Sandanger, Torkjel Manning

2015-01-01

Background Studies on the health effects of polychlorinated biphenyls (PCBs) call for an understanding of past and present human exposure. Time-resolved mechanistic models may supplement information on concentrations in individuals obtained from measurements and/or statistical approaches if they can be shown to reproduce empirical data. Objectives Here, we evaluated the capability of one such mechanistic model to reproduce measured PCB concentrations in individual Norwegian women. We also assessed individual life-course concentrations. Methods Concentrations of four PCB congeners in pregnant (n = 310, sampled in 2007–2009) and postmenopausal (n = 244, 2005) women were compared with person-specific predictions obtained using CoZMoMAN, an emission-based environmental fate and human food-chain bioaccumulation model. Person-specific predictions were also made using statistical regression models including dietary and lifestyle variables and concentrations. Results CoZMoMAN accurately reproduced medians and ranges of measured concentrations in the two study groups. Furthermore, rank correlations between measurements and predictions from both CoZMoMAN and regression analyses were strong (Spearman’s r > 0.67). Precision in quartile assignments from predictions was strong overall as evaluated by weighted Cohen’s kappa (> 0.6). Simulations indicated large inter-individual differences in concentrations experienced in the past. Conclusions The mechanistic model reproduced all measurements of PCB concentrations within a factor of 10, and subject ranking and quartile assignments were overall largely consistent, although they were weak within each study group. Contamination histories for individuals predicted by CoZMoMAN revealed variation between study subjects, particularly in the timing of peak concentrations. Mechanistic models can provide individual PCB exposure metrics that could serve as valuable supplements to measurements. Citation Nøst TH, Breivik K, Wania F, Rylander C, Odland JØ, Sandanger TM. 2016. Estimating time-varying PCB exposures using person-specific predictions to supplement measured values: a comparison of observed and predicted values in two cohorts of Norwegian women. Environ Health Perspect 124:299–305; http://dx.doi.org/10.1289/ehp.1409191 PMID:26186800

Diffusion of isolated DNA molecules: dependence on length and topology.

PubMed

Robertson, Rae M; Laib, Stephan; Smith, Douglas E

2006-05-09

The conformation and dynamics of circular polymers is a subject of considerable theoretical and experimental interest. DNA is an important example because it occurs naturally in different topological states, including linear, relaxed circular, and supercoiled circular forms. A fundamental question is how the diffusion coefficients of isolated polymers scale with molecular length and how they vary for different topologies. Here, diffusion coefficients D for relaxed circular, supercoiled, and linear DNA molecules of length L ranging from approximately 6 to 290 kbp were measured by tracking the Brownian motion of single molecules. A topology-independent scaling law D approximately L(-nu) was observed with nu(L) = 0.571 +/- 0.014, nu(C) = 0.589 +/- 0.018, and nu(S) = 0.571 +/- 0.057 for linear, relaxed circular, and supercoiled DNA, respectively, in good agreement with the scaling exponent of nu congruent with 0.588 predicted by renormalization group theory for polymers with significant excluded volume interactions. Our findings thus provide evidence in support of several theories that predict an effective diameter of DNA much greater than the Debye screening length. In addition, the measured ratio D(Circular)/D(Linear) = 1.32 +/- 0.014 was closer to the value of 1.45 predicted by using renormalization group theory than the value of 1.18 predicted by classical Kirkwood hydrodynamic theory and agreed well with a value of 1.31 predicted when incorporating a recently proposed expression for the radius of gyration of circular polymers into the Zimm model.

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

Lafontaine Rivera, Jimmy G.; Theisen, Matthew K.; Chen, Po-Wei

The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here in this paper we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realisticmore » quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.« less

Classifying environmental pollutants: Part 3. External validation of the classification system.

PubMed

Verhaar, H J; Solbé, J; Speksnijder, J; van Leeuwen, C J; Hermens, J L

2000-04-01

In order to validate a classification system for the prediction of the toxic effect concentrations of organic environmental pollutants to fish, all available fish acute toxicity data were retrieved from the ECETOC database, a database of quality-evaluated aquatic toxicity measurements created and maintained by the European Centre for the Ecotoxicology and Toxicology of Chemicals. The individual chemicals for which these data were available were classified according to the rulebase under consideration and predictions of effect concentrations or ranges of possible effect concentrations were generated. These predictions were compared to the actual toxicity data retrieved from the database. The results of this comparison show that generally, the classification system provides adequate predictions of either the aquatic toxicity (class 1) or the possible range of toxicity (other classes) of organic compounds. A slight underestimation of effect concentrations occurs for some highly water soluble, reactive chemicals with low log K(ow) values. On the other end of the scale, some compounds that are classified as belonging to a relatively toxic class appear to belong to the so-called baseline toxicity compounds. For some of these, additional classification rules are proposed. Furthermore, some groups of compounds cannot be classified, although they should be amenable to predictions. For these compounds additional research as to class membership and associated prediction rules is proposed.

Random Forests for Global and Regional Crop Yield Predictions.

PubMed

Jeong, Jig Han; Resop, Jonathan P; Mueller, Nathaniel D; Fleisher, David H; Yun, Kyungdahm; Butler, Ethan E; Timlin, Dennis J; Shim, Kyo-Moon; Gerber, James S; Reddy, Vangimalla R; Kim, Soo-Hyung

2016-01-01

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.

Metabolic Tumor Volume and Total Lesion Glycolysis in Oropharyngeal Cancer Treated With Definitive Radiotherapy: Which Threshold Is the Best Predictor of Local Control?

PubMed

Castelli, Joël; Depeursinge, Adrien; de Bari, Berardino; Devillers, Anne; de Crevoisier, Renaud; Bourhis, Jean; Prior, John O

2017-06-01

In the context of oropharyngeal cancer treated with definitive radiotherapy, the aim of this retrospective study was to identify the best threshold value to compute metabolic tumor volume (MTV) and/or total lesion glycolysis to predict local-regional control (LRC) and disease-free survival. One hundred twenty patients with a locally advanced oropharyngeal cancer from 2 different institutions treated with definitive radiotherapy underwent FDG PET/CT before treatment. Various MTVs and total lesion glycolysis were defined based on 2 segmentation methods: (i) an absolute threshold of SUV (0-20 g/mL) or (ii) a relative threshold for SUVmax (0%-100%). The parameters' predictive capabilities for disease-free survival and LRC were assessed using the Harrell C-index and Cox regression model. Relative thresholds between 40% and 68% and absolute threshold between 5.5 and 7 had a similar predictive value for LRC (C-index = 0.65 and 0.64, respectively). Metabolic tumor volume had a higher predictive value than gross tumor volume (C-index = 0.61) and SUVmax (C-index = 0.54). Metabolic tumor volume computed with a relative threshold of 51% of SUVmax was the best predictor of disease-free survival (hazard ratio, 1.23 [per 10 mL], P = 0.009) and LRC (hazard ratio: 1.22 [per 10 mL], P = 0.02). The use of different thresholds within a reasonable range (between 5.5 and 7 for an absolute threshold and between 40% and 68% for a relative threshold) seems to have no major impact on the predictive value of MTV. This parameter may be used to identify patient with a high risk of recurrence and who may benefit from treatment intensification.

Hypoglycemia prediction with subject-specific recursive time-series models.

PubMed

Eren-Oruklu, Meriyan; Cinar, Ali; Quinn, Lauretta

2010-01-01

Avoiding hypoglycemia while keeping glucose within the narrow normoglycemic range (70-120 mg/dl) is a major challenge for patients with type 1 diabetes. Continuous glucose monitors can provide hypoglycemic alarms when the measured glucose decreases below a threshold. However, a better approach is to provide an early alarm that predicts a hypoglycemic episode before it occurs, allowing enough time for the patient to take the necessary precaution to avoid hypoglycemia. We have previously proposed subject-specific recursive models for the prediction of future glucose concentrations and evaluated their prediction performance. In this work, our objective was to evaluate this algorithm further to predict hypoglycemia and provide early hypoglycemic alarms. Three different methods were proposed for alarm decision, where (A) absolute predicted glucose values, (B) cumulative-sum (CUSUM) control chart, and (C) exponentially weighted moving-average (EWMA) control chart were used. Each method was validated using data from the Diabetes Research in Children Network, which consist of measurements from a continuous glucose sensor during an insulin-induced hypoglycemia. Reference serum glucose measurements were used to determine the sensitivity to predict hypoglycemia and the false alarm rate. With the hypoglycemic threshold set to 60 mg/dl, sensitivity of 89, 87.5, and 89% and specificity of 67, 74, and 78% were reported for methods A, B, and C, respectively. Mean values for time to detection were 30 +/- 5.51 (A), 25.8 +/- 6.46 (B), and 27.7 +/- 5.32 (C) minutes. Compared to the absolute value method, both CUSUM and EWMA methods behaved more conservatively before raising an alarm (reduced time to detection), which significantly decreased the false alarm rate and increased the specificity. 2010 Diabetes Technology Society.

Passenger Flow Forecasting Research for Airport Terminal Based on SARIMA Time Series Model

NASA Astrophysics Data System (ADS)

Li, Ziyu; Bi, Jun; Li, Zhiyin

2017-12-01

Based on the data of practical operating of Kunming Changshui International Airport during2016, this paper proposes Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the passenger flow. This article not only considers the non-stationary and autocorrelation of the sequence, but also considers the daily periodicity of the sequence. The prediction results can accurately describe the change trend of airport passenger flow and provide scientific decision support for the optimal allocation of airport resources and optimization of departure process. The result shows that this model is applicable to the short-term prediction of airport terminal departure passenger traffic and the average error ranges from 1% to 3%. The difference between the predicted and the true values of passenger traffic flow is quite small, which indicates that the model has fairly good passenger traffic flow prediction ability.

More than Content: The Persistent Cross-Subject Effects of English Language Arts Teachers' Instruction

ERIC Educational Resources Information Center

Master, Benjamin; Loeb, Susanna; Wyckoff, James

2017-01-01

Evidence that teachers' short-term instructional effects persist over time and predict substantial long-run impacts on students' lives provides much of the impetus for a wide range of educational reforms focused on identifying and responding to differences in teachers' value-added to student learning. However, relatively little research has…

Mental Health and Functional Outcomes of Maternal and Adolescent Reports of Adolescent Depressive Symptoms

ERIC Educational Resources Information Center

Rice, Frances; Lifford, Kate J.; Thomas, Hollie V.; Thapar, Anita

2007-01-01

Objective: To assess the value of maternal and self-ratings of adolescent depression by investigating the extent to which these reports predicted a range of mental health and functional outcomes 4 years later. The potential influence of mother's own depressed mood on her ratings of adolescent depression and suicidal ideation on adolescent outcome…

Blood glucose control for patients with acute coronary syndromes in Qatar.

PubMed

Wilby, Kyle John; Elmekaty, Eman; Abdallah, Ibtihal; Habra, Masa; Al-Siyabi, Khalid

2016-01-01

Blood glucose is known to be elevated in patients presenting with acute coronary syndromes. However a gap in knowledge exists regarding effective management strategies once admitted to acute care units. It is also unknown what factors (if any) predict elevated glucose values during initial presentation. OBJECTIVES of the study were to characterize blood glucose control in patients admitted to the cardiac care unit (CCU) in Qatar and to determine predictive factors associated with high glucose levels (>10 mmol/l) on admission to the CCU. All data for this study were obtained from the CCU at Heart Hospital in Doha, Qatar. A retrospective chart review was completed for patients admitted to the CCU in Qatar from October 1st, 2012 to March 31st, 2013, of which 283 were included. Baseline characteristics (age, gender, nationality, medical history, smoking status, type of acute coronary syndrome), capillary and lab blood glucose measurements, and use of insulin were extracted. Time spent in glucose ranges of <4, 4 to <8, 8 to <10, and >10 mmol/1 was calculated manually. Univariate and multivariate logistic regression were performed to assess factors associated with high glucose on admission. The primary analysis was completed with capillary data and a sensitivity analysis was completed using laboratory data. Blood glucose values measured on admission and throughout length of stay in the CCU. Capillary blood glucose data showed majority of time was spent in the range of >10 mmol/l (41.95%), followed by 4-8 mmol/l (35.44%), then 8-10 mmol/l (21.45%), and finally <4 mmol/l (1.16%). As a sensitivity analysis, laboratory data showed very similar findings. Diabetes, hypertension, and non-smoker status predicted glucose values >10 mmol/l on admission (p < 0.05) in a univariate analysis but only diabetes remained significant in a multivariate model (OR 23.3; 95% CI, 11.5-47.3). Diabetes predicts high glucose values on hospital admission for patients with ACS and patients are not being adequately controlled throughout CCU stay.

CGM-measured glucose values have a strong correlation with C-peptide, HbA1c and IDAAC, but do poorly in predicting C-peptide levels in the two years following onset of diabetes.

PubMed

Buckingham, Bruce; Cheng, Peiyao; Beck, Roy W; Kollman, Craig; Ruedy, Katrina J; Weinzimer, Stuart A; Slover, Robert; Bremer, Andrew A; Fuqua, John; Tamborlane, William

2015-06-01

The aim of this work was to assess the association between continuous glucose monitoring (CGM) data, HbA1c, insulin-dose-adjusted HbA1c (IDAA1c) and C-peptide responses during the first 2 years following diagnosis of type 1 diabetes. A secondary analysis was conducted of data collected from a randomised trial assessing the effect of intensive management initiated within 1 week of diagnosis of type 1 diabetes, in which mixed-meal tolerance tests were performed at baseline and at eight additional time points through 24 months. CGM data were collected at each visit. Among 67 study participants (mean age [± SD] 13.3 ± 5.7 years), HbA1c was inversely correlated with C-peptide at each time point (p < 0.001), as were changes in each measure between time points (p < 0.001). However, C-peptide at one visit did not predict the change in HbA1c at the next visit and vice versa. Higher C-peptide levels correlated with increased proportion of CGM glucose values between 3.9 and 7.8 mmol/l and lower CV (p = 0.001 and p = 0.02, respectively) but not with CGM glucose levels <3.9 mmol/l. Virtually all participants with IDAA1c < 9 retained substantial insulin secretion but when evaluated together with CGM, time in the range of 3.9-7.8 mmol/l and CV did not provide additional value in predicting C-peptide levels. In the first 2 years after diagnosis of type 1 diabetes, higher C-peptide levels are associated with increased sensor glucose levels in the target range and with lower glucose variability but not hypoglycaemia. CGM metrics do not provide added value over the IDAA1c in predicting C-peptide levels.

Stable isotope signatures and trophic-step fractionation factors of fish tissues collected as non-lethal surrogates of dorsal muscle.

PubMed

Busst, Georgina M A; Bašić, Tea; Britton, J Robert

2015-08-30

Dorsal white muscle is the standard tissue analysed in fish trophic studies using stable isotope analyses. As muscle is usually collected destructively, fin tissues and scales are often used as non-lethal surrogates; we examined the utility of scales and fin tissue as muscle surrogates. The muscle, fin and scale δ(15) N and δ(13) C values from 10 cyprinid fish species determined with an elemental analyser coupled with an isotope ratio mass spectrometer were compared. The fish comprised (1) samples from the wild, and (2) samples from tank aquaria, using six species held for 120 days and fed a single food resource. Relationships between muscle, fin and scale isotope ratios were examined for each species and for the entire dataset, with the efficacy of four methods of predicting muscle isotope ratios from fin and scale values being tested. The fractionation factors between the three tissues of the laboratory fishes and their food resource were then calculated and applied to Bayesian mixing models to assess their effect on fish diet predictions. The isotopic data of the three tissues per species were distinct, but were significantly related, enabling estimations of muscle values from the two surrogates. Species-specific equations provided the least erroneous corrections of scale and fin isotope ratios (errors < 0.6‰). The fractionation factors for δ(15) N values were in the range obtained for other species, but were often higher for δ(13) C values. Their application to data from two fish populations in the mixing models resulted in significant alterations in diet predictions. Scales and fin tissue are strong surrogates of dorsal muscle in food web studies as they can provide estimates of muscle values within an acceptable level of error when species-specific methods are used. Their derived fractionation factors can also be applied to models predicting fish diet composition from δ(15) N and δ(13) C values. Copyright © 2015 John Wiley & Sons, Ltd.

Galaxy Formation Efficiency and the Multiverse Explanation of the Cosmological Constant with EAGLE Simulations

NASA Astrophysics Data System (ADS)

Barnes, Luke A.; Elahi, Pascal J.; Salcido, Jaime; Bower, Richard G.; Lewis, Geraint F.; Theuns, Tom; Schaller, Matthieu; Crain, Robert A.; Schaye, Joop

2018-04-01

Models of the very early universe, including inflationary models, are argued to produce varying universe domains with different values of fundamental constants and cosmic parameters. Using the cosmological hydrodynamical simulation code from the EAGLE collaboration, we investigate the effect of the cosmological constant on the formation of galaxies and stars. We simulate universes with values of the cosmological constant ranging from Λ = 0 to Λ0 × 300, where Λ0 is the value of the cosmological constant in our Universe. Because the global star formation rate in our Universe peaks at t = 3.5 Gyr, before the onset of accelerating expansion, increases in Λ of even an order of magnitude have only a small effect on the star formation history and efficiency of the universe. We use our simulations to predict the observed value of the cosmological constant, given a measure of the multiverse. Whether the cosmological constant is successfully predicted depends crucially on the measure. The impact of the cosmological constant on the formation of structure in the universe does not seem to be a sharp enough function of Λ to explain its observed value alone.

Galaxy formation efficiency and the multiverse explanation of the cosmological constant with EAGLE simulations

NASA Astrophysics Data System (ADS)

Barnes, Luke A.; Elahi, Pascal J.; Salcido, Jaime; Bower, Richard G.; Lewis, Geraint F.; Theuns, Tom; Schaller, Matthieu; Crain, Robert A.; Schaye, Joop

2018-07-01

Models of the very early Universe, including inflationary models, are argued to produce varying universe domains with different values of fundamental constants and cosmic parameters. Using the cosmological hydrodynamical simulation code from the EAGLE collaboration, we investigate the effect of the cosmological constant on the formation of galaxies and stars. We simulate universes with values of the cosmological constant ranging from Λ = 0 to Λ0 × 300, where Λ0 is the value of the cosmological constant in our Universe. Because the global star formation rate in our Universe peaks at t = 3.5 Gyr, before the onset of accelerating expansion, increases in Λ of even an order of magnitude have only a small effect on the star formation history and efficiency of the universe. We use our simulations to predict the observed value of the cosmological constant, given a measure of the multiverse. Whether the cosmological constant is successfully predicted depends crucially on the measure. The impact of the cosmological constant on the formation of structure in the universe does not seem to be a sharp enough function of Λ to explain its observed value alone.

The Value of Geriatric Assessments in Predicting Treatment Tolerance and All-Cause Mortality in Older Patients With Cancer

PubMed Central

Vos, Alinda G.; Smorenburg, Carolien H.; de Rooij, Sophia E.; van Munster, Barbara C.

2012-01-01

Background. Awareness of the use of geriatric assessments for older patients with cancer is increasing. The aim of this review is to summarize all available evidence on the association between geriatric assessments and relevant oncologic outcomes. Method. A systematic search was conducted in Medline and Embase of studies on geriatric assessment in oncology, focusing on the association between baseline assessment and outcome. Results. The literature search identified 2008 reports; 51 publications from 37 studies were selected for inclusion in the review. The quality of studies was heterogeneous and generally poor. A median of five geriatric conditions were assessed per study (interquartile range: 4–8). Little consistency was found in the results of the studies. Furthermore, different tools appear to be predictive depending on the outcome measure: frailty, nutritional status, and comorbidity assessed by the Cumulative Illness Rating Scale for Geriatrics were predictive for all-cause mortality; frailty was predictive for toxicity of chemotherapy; cognitive impairment and activities of daily living impairment were predictive for chemotherapy completion; and instrumental activities of daily living impairment was predictive for perioperative complications. Conclusion. Although various geriatric conditions appear to be of some value in predicting outcome in elderly patients with cancer, the results are too inconsistent to guide treatment decisions. Further research is needed to elucidate the role of geriatric assessments in the oncologic decision-making process for these patients. PMID:22941970

Do intensive care data on respiratory infections reflect influenza epidemics?

PubMed

Koetsier, Antonie; van Asten, Liselotte; Dijkstra, Frederika; van der Hoek, Wim; Snijders, Bianca E; van den Wijngaard, Cees C; Boshuizen, Hendriek C; Donker, Gé A; de Lange, Dylan W; de Keizer, Nicolette F; Peek, Niels

2013-01-01

Severe influenza can lead to Intensive Care Unit (ICU) admission. We explored whether ICU data reflect influenza like illness (ILI) activity in the general population, and whether ICU respiratory infections can predict influenza epidemics. We calculated the time lag and correlation between ILI incidence (from ILI sentinel surveillance, based on general practitioners (GP) consultations) and percentages of ICU admissions with a respiratory infection (from the Dutch National Intensive Care Registry) over the years 2003-2011. In addition, ICU data of the first three years was used to build three regression models to predict the start and end of influenza epidemics in the years thereafter, one to three weeks ahead. The predicted start and end of influenza epidemics were compared with observed start and end of such epidemics according to the incidence of ILI. Peaks in respiratory ICU admissions lasted longer than peaks in ILI incidence rates. Increases in ICU admissions occurred on average two days earlier compared to ILI. Predicting influenza epidemics one, two, or three weeks ahead yielded positive predictive values ranging from 0.52 to 0.78, and sensitivities from 0.34 to 0.51. ICU data was associated with ILI activity, with increases in ICU data often occurring earlier and for a longer time period. However, in the Netherlands, predicting influenza epidemics in the general population using ICU data was imprecise, with low positive predictive values and sensitivities.

Investigating the Energetic Ordering of Stable and Metastable TiO 2 Polymorphs Using DFT+ U and Hybrid Functionals

DOE PAGES

Curnan, Matthew T.; Kitchin, John R.

2015-08-12

Prediction of transition metal oxide BO 2 (B = Ti, V, etc.) polymorph energetic properties is critical to tunable material design and identifying thermodynamically accessible structures. Determining procedures capable of synthesizing particular polymorphs minimally requires prior knowledge of their relative energetic favorability. Information concerning TiO 2 polymorph relative energetic favorability has been ascertained from experimental research. In this study, the consistency of first-principles predictions and experimental results involving the relative energetic ordering of stable (rutile), metastable (anatase and brookite), and unstable (columbite) TiO 2 polymorphs is assessed via density functional theory (DFT). Considering the issues involving electron–electron interaction and chargemore » delocalization in TiO 2 calculations, relative energetic ordering predictions are evaluated over trends varying Ti Hubbard U 3d or exact exchange fraction parameter values. Energetic trends formed from varying U 3d predict experimentally consistent energetic ordering over U 3d intervals when using GGA-based functionals, regardless of pseudopotential selection. Given pertinent linear response calculated Hubbard U values, these results enable TiO 2 polymorph energetic ordering prediction. Here, the hybrid functional calculations involving rutile–anatase relative energetics, though demonstrating experimentally consistent energetic ordering over exact exchange fraction ranges, are not accompanied by predicted fractions, for a first-principles methodology capable of calculating exact exchange fractions precisely predicting TiO 2 polymorph energetic ordering is not available.« less

The value of geriatric assessments in predicting treatment tolerance and all-cause mortality in older patients with cancer.

PubMed

Hamaker, Marije E; Vos, Alinda G; Smorenburg, Carolien H; de Rooij, Sophia E; van Munster, Barbara C

2012-01-01

Awareness of the use of geriatric assessments for older patients with cancer is increasing. The aim of this review is to summarize all available evidence on the association between geriatric assessments and relevant oncologic outcomes. A systematic search was conducted in Medline and Embase of studies on geriatric assessment in oncology, focusing on the association between baseline assessment and outcome. The literature search identified 2008 reports; 51 publications from 37 studies were selected for inclusion in the review. The quality of studies was heterogeneous and generally poor. A median of five geriatric conditions were assessed per study (interquartile range: 4-8). Little consistency was found in the results of the studies. Furthermore, different tools appear to be predictive depending on the outcome measure: frailty, nutritional status, and comorbidity assessed by the Cumulative Illness Rating Scale for Geriatrics were predictive for all-cause mortality; frailty was predictive for toxicity of chemotherapy; cognitive impairment and activities of daily living impairment were predictive for chemotherapy completion; and instrumental activities of daily living impairment was predictive for perioperative complications. Although various geriatric conditions appear to be of some value in predicting outcome in elderly patients with cancer, the results are too inconsistent to guide treatment decisions. Further research is needed to elucidate the role of geriatric assessments in the oncologic decision-making process for these patients.

Clinical prediction models for young febrile infants at the emergency department: an international validation study.

PubMed

Vos-Kerkhof, Evelien de; Gomez, Borja; Milcent, Karen; Steyerberg, Ewout W; Nijman, Ruud Gerard; Smit, Frank J; Mintegi, Santiago; Moll, Henriette A; Gajdos, Vincent; Oostenbrink, Rianne

2018-05-24

To assess the diagnostic value of existing clinical prediction models (CPM; ie, statistically derived) in febrile young infants at risk for serious bacterial infections. A systematic literature review identified eight CPMs for predicting serious bacterial infections in febrile children. We validated these CPMs on four validation cohorts of febrile children in Spain (age <3 months), France (age <3 months) and two cohorts in the Netherlands (age 1-3 months and >3-12 months). We evaluated the performance of the CPMs by sensitivity/specificity, area under the receiver operating characteristic curve (AUC) and calibration studies. The original cohorts in which the prediction rules were developed (derivation cohorts) ranged from 381 to 15 781 children, with a prevalence of serious bacterial infections varying from 0.8% to 27% and spanned an age range of 0-16 years. All CPMs originally performed moderately to very well (AUC 0.60-0.93). The four validation cohorts included 159-2204 febrile children, with a median age range of 1.8 (1.2-2.4) months for the three cohorts <3 months and 8.4 (6.0-9.6) months for the cohort >3-12 months of age. The prevalence of serious bacterial infections varied between 15.1% and 17.2% in the three cohorts <3 months and was 9.8% for the cohort >3-12 months of age. Although discriminative values varied greatly, best performance was observed for four CPMs including clinical signs and symptoms, urine dipstick analyses and laboratory markers with AUC ranging from 0.68 to 0.94 in the three cohorts <3 months (ranges sensitivity: 0.48-0.94 and specificity: 0.71-0.97). For the >3-12 months' cohort AUC ranges from 0.80 to 0.89 (ranges sensitivity: 0.70-0.82 and specificity: 0.78-0.90). In general, the specificities exceeded sensitivities in our cohorts, in contrast to derivation cohorts with high sensitivities, although this effect was stronger in infants <3 months than in infants >3-12 months. We identified four CPMs, including clinical signs and symptoms, urine dipstick analysis and laboratory markers, which can aid clinicians in identifying serious bacterial infections. We suggest clinicians should use CPMs as an adjunctive clinical tool when assessing the risk of serious bacterial infections in febrile young infants. © 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.

Phase Behavior in Blends of Asymmetrical Polyolefins

NASA Astrophysics Data System (ADS)

Nedoma, Alisyn Jenise

This dissertation presents the most comprehensive study of chi to date for a single pair of homopolymers. Polyisobutylene (component B) and deuterated polybutadiene with 63 % 1,2 addition (component C) were selected for this study because they exhibit a large window of miscibility and may be tailored to cross the spinodal at experimentally accessible temperatures. Binary blends were designed across a range of values for NB/ NC and the composition of the blend, φB, to study the effect of these parameters on the measured value, chi sc. In addition to the strict temperature dependence presumed for chi, this study documented a composition and molecular weight dependence. The empirical expression for chisc, measured using small angle neutron scattering, was three times more dependent on composition then the expression for chi used to predict thermodynamic behavior. Despite this three-fold diminished dependence on φB, the composition-dependent chi profoundly affected the phase behavior of binary blends. A range of values was studied for NB/ NC ≤ 1, and in all cases φB,cirt was found to be < 0.5, in stark contrast to the expectation of Flory-Huggins Theory that φB,crit ≥ 0.5. This effect was shown to result from the combined effects of a composition-dependent chi and N B/NC removed from values of 1. Remarkable agreement was obtained between the predicted phase diagrams and measured phase transitions, over a range of values for NB/ NC and φB, by accounting for the composition and molecular weight dependence of chi. The miscibility of binary B/C blends was used as the basis for designing a diblock copolymer (component A-C) to order immiscible binary blends of polyisobutylene and deuterated polybutadiene with 89 % 1,2 addition (component A). The copolymer comprised one block chemically identical to component C (miscible in component B) and one block chemically identical to component A. This is in contrast to the majority of ternary blend studies which comprise A/B/A-B polymer systems with neutral interactions between each homopolymer and the corresponding block of the diblock copolymer. Ternary A/B/A-C blends exhibit a favorable interaction between the B homopolymer and C block, demonstrated by the miscibility of B/C blends. The A-C diblock copolymer surfactant can produce microstructures when added to A/B blends at much lower concentrations of copolymer than for an analagous A-B copolymer. This dissertation introduces the use of lamellar structure factor that fits scattering profiles unsuitable for the microemulsion fit. In addition, the lamellar fits include as adjustable parameters the size of each microdomain and corresponding interfacial width. These fit values agree quantitatively with independently generated predictions using self-consistent field theory, indicating a broad understanding of the physical parameters that affect thermodynamic behavior in the A/B/A-C system studied. This dissertation presents a study for which the concentration of diblock copolymer was fixed and the composition of the A and B homopolymers was systematically varied across a range of compositions including φA,crit. The experiment corresponded to tracing the copolymer isopleth on a ternary phase prism. Theoretical groups have predicted a rich phase behavior along the isopleth for similar ternary systems, however, the observed phase behavior was quantitatively identical for all blends studied. Self-consistent field theory predictions agreed with fit values of the domain spacing and microdomain widths. There was no discernible correlation between φA and phase behavior. This finding, and that of the study with critical A/B/A-C blends, together suggest that NA/NB correlates strongly with the phase behavior of a blend, while φ A does not. This relationship, captured by mean-field theory, provides a simple method for tuning the phase behavior of polymer nanocomposites without using additional surfactant. (Abstract shortened by UMI.)

Rapid and Cost-Effective Quantification of Glucosinolates and Total Phenolic Content in Rocket Leaves by Visible/Near-Infrared Spectroscopy.

PubMed

Toledo-Martín, Eva María; Font, Rafael; Obregón-Cano, Sara; De Haro-Bailón, Antonio; Villatoro-Pulido, Myriam; Del Río-Celestino, Mercedes

2017-05-20

The potential of visible-near infrared spectroscopy to predict glucosinolates and total phenolic content in rocket ( Eruca vesicaria ) leaves has been evaluated. Accessions of the E. vesicaria species were scanned by NIRS as ground leaf, and their reference values regressed against different spectral transformations by modified partial least squares (MPLS) regression. The coefficients of determination in the external validation (R²VAL) for the different quality components analyzed in rocket ranged from 0.59 to 0.84, which characterize those equations as having from good to excellent quantitative information. These results show that the total glucosinolates, glucosativin and glucoerucin equations obtained, can be used to identify those samples with low and high contents. The glucoraphanin equation obtained can be used for rough predictions of samples and in case of total phenolic content, the equation showed good correlation. The standard deviation (SD) to standard error of prediction ratio (RPD) and SD to range (RER) were variable for the different quality compounds and showed values that were characteristic of equations suitable for screening purposes or to perform accurate analyses. From the study of the MPLS loadings of the first three terms of the different equations, it can be concluded that some major cell components such as protein and cellulose, highly participated in modelling the equations for glucosinolates.

Comparison of Two Predictive Models for Short-Term Mortality in Patients after Severe Traumatic Brain Injury.

PubMed

Kesmarky, Klara; Delhumeau, Cecile; Zenobi, Marie; Walder, Bernhard

2017-07-15

The Glasgow Coma Scale (GCS) and the Abbreviated Injury Score of the head region (HAIS) are validated prognostic factors in traumatic brain injury (TBI). The aim of this study was to compare the prognostic performance of an alternative predictive model including motor GCS, pupillary reactivity, age, HAIS, and presence of multi-trauma for short-term mortality with a reference predictive model including motor GCS, pupil reaction, and age (IMPACT core model). A secondary analysis of a prospective epidemiological cohort study in Switzerland including patients after severe TBI (HAIS >3) with the outcome death at 14 days was performed. Performance of prediction, accuracy of discrimination (area under the receiver operating characteristic curve [AUROC]), calibration, and validity of the two predictive models were investigated. The cohort included 808 patients (median age, 56; interquartile range, 33-71), median GCS at hospital admission 3 (3-14), abnormal pupil reaction 29%, with a death rate of 29.7% at 14 days. The alternative predictive model had a higher accuracy of discrimination to predict death at 14 days than the reference predictive model (AUROC 0.852, 95% confidence interval [CI] 0.824-0.880 vs. AUROC 0.826, 95% CI 0.795-0.857; p < 0.0001). The alternative predictive model had an equivalent calibration, compared with the reference predictive model Hosmer-Lemeshow p values (Chi2 8.52, Hosmer-Lemeshow p = 0.345 vs. Chi2 8.66, Hosmer-Lemeshow p = 0.372). The optimism-corrected value of AUROC for the alternative predictive model was 0.845. After severe TBI, a higher performance of prediction for short-term mortality was observed with the alternative predictive model, compared with the reference predictive model.

Area and volume ratios for prediction of visual outcome in idiopathic macular hole.

PubMed

Geng, Xing-Yun; Wu, Hui-Qun; Jiang, Jie-Hui; Jiang, Kui; Zhu, Jun; Xu, Yi; Dong, Jian-Cheng; Yan, Zhuang-Zhi

2017-01-01

To predict the visual outcome in patients undergoing macular hole surgery by two novel three-dimensional morphological parameters on optical coherence tomography (OCT): area ratio factor (ARF) and volume ratio factor (VRF). A clinical case series was conducted, including 54 eyes of 54 patients with an idiopathic macular hole (IMH). Each patient had an OCT examination before and after surgery. Morphological parameters of the macular hole, such as minimum diameter, base diameter, and height were measured. Then, the macular hole index (MHI), tractional hole index (THI), and hole form factor (HFF) were calculated. Meanwhile, novel postoperative macular hole (MH) factors, ARF and VRF were calculated by three-dimensional morphology. Bivariate correlations were performed to acquire asymptotic significance values between the steady best corrected visual acuity (BCVA) after surgery and 2D/3D arguments of MH by the Pearson method with two-tailed test. All significant factors were analyzed by the receiver operating characteristic (ROC) curve analysis of SPSS software which were responsible for vision recovery. ROC curves analyses were performed to further discuss the different parameters on the prediction of visual outcome. The mean and standard deviation values of patients' age, symptoms duration, and follow-up time were 64.8±8.9y (range: 28-81), 18.6±11.5d (range: 2-60), and 11.4±0.4mo (range: 6-24), respectively. Steady-post-BCVA analyzed with bivariate correlations was found to be significantly correlated with base diameter ( r =0.521, P <0.001), minimum diameter ( r =0.514, P <0.001), MHI ( r =-0.531, P <0.001), THI ( r =-0.386, P =0.004), HFF ( r =-0.508, P <0.001), and ARF ( r =-0.532, P <0.001). Other characteristic parameters such as age, duration of surgery, height, diameter hole index, and VRF were not statistically significant with steady-post-BCVA. According to area under the curve (AUC) values, values of ARF, MHI, HFF, minimum diameter, THI, and base diameter are 0.806, 0.772, 0.750, 0.705, 0.690, and 0.686, respectively. However, Steady-post-BCVA analysis with bivariate correlations for VRF was no statistical significance. Results of ROC curve analysis indicated that the MHI value, HFF, and ARF was greater than 0.427, 1.027 and 1.558 respectively which could correlate with better visual acuity. Compared with MHI and HFF, ARF could effectively express three-dimensional characteristics of macular hole and achieve better sensitivity and specificity. Thus, ARF could be the most effective parameter to predict the visual outcome in macular hole surgery.

[Prediction of soil adsorption coefficients of organic compounds in a wide range of soil types by soil column liquid chromatography].

PubMed

Guo, Rongbo; Chen, Jiping; Zhang, Qing; Wu, Wenzhong; Liang, Xinmiao

2004-01-01

Using the methanol-water mixtures as mobile phases of soil column liquid chromatography (SCLC), prediction of soil adsorption coefficients (K(d)) by SCLC was validated in a wide range of soil types. The correlations between the retention factors measured by SCLC and soil adsorption coefficients measured by batch experiments were studied for five soils with different properties, i.e., Eurosoil 1#, 2#, 3#, 4# and 5#. The results show that good correlations existed between the retention factors and soil adsorption coefficients for Eurosoil 1#, 2#, 3# and 4#. For Eurosoil 5# which has a pH value of near 3, the correlation between retention factors and soil adsorption coefficients was unsatisfactory using methanol-water as mobile phase of SCLC. However, a good correlation was obtained using a methanol-buffer mixture with pH 3 as the mobile phase. This study proved that the SCLC is suitable for the prediction of soil adsorption coefficients.

Prediction of Ductile Fracture Behaviors for 42CrMo Steel at Elevated Temperatures

NASA Astrophysics Data System (ADS)

Lin, Y. C.; Liu, Yan-Xing; Liu, Ge; Chen, Ming-Song; Huang, Yuan-Chun

2015-01-01

The ductile fracture behaviors of 42CrMo steel are studied by hot tensile tests with the deformation temperature range of 1123-1373 K and strain rate range of 0.0001-0.1 s-1. Effects of deformation temperature and strain rate on the flow stress and fracture strain of the studied steel are discussed in detail. Based on the experimental results, a ductile damage model is established to describe the combined effects of deformation temperature and strain rate on the ductile fracture behaviors of 42CrMo steel. It is found that the flow stress first increases to a peak value and then decreases, showing an obvious dynamic softening. This is mainly attributed to the dynamic recrystallization and material intrinsic damage during the hot tensile deformation. The established damage model is verified by hot forging experiments and finite element simulations. Comparisons between the predicted and experimental results indicate that the established ductile damage model is capable of predicting the fracture behaviors of 42CrMo steel during hot forging.

The dynamic-response characteristics of a 35 degree swept-wing airplane as determined from flight measurements

NASA Technical Reports Server (NTRS)

Triplett, William C; Brown, Stuart C; Smith, G Allan

1955-01-01

The longitudinal and lateral-directional dynamic-response characteristics of a 35 degree swept-wing fighter-type airplane determined from flight measurements are presented and compared with predictions based on theoretical studies and wind-tunnel data. Flights were made at an altitude of 35,000 feet covering the Mach number range of 0.50 to 1.04. A limited amount of lateral-directional data were also obtained at 10,000 feet. The flight consisted essentially of recording transient responses to pilot-applied pulsed motions of each of the three primary control surfaces. These transient data were converted into frequency-response form by means of the Fourier transformation and compared with predicted responses calculated from the basic equations. Experimentally determined transfer functions were used for the evaluation of the stability derivatives that have the greatest effect on the dynamic response of the airplane. The values of these derivatives, in most cases, agreed favorably with predictions over the Mach number range of the test.

Can the multiple mini-interview predict academic achievement in medical school?

PubMed

Kim, Ja Kyoung; Kang, Seok Hoon; Lee, Hee Jae; Yang, JeongHee

2014-09-01

The purpose of this study was to determine whether the multiple mini-interview (MMI) predicts academic achievement for subjects in a medical school curriculum. Of 49 students who were admitted in 2008, 46 students finished the entire medical education curriculum within 4 years. We calculated the Pearson correlation coefficients between the total MMI score of the 46 graduates and their academic achievements in all subjects of the curriculum. The correlation coefficients between total MMI score and academic achievement in Medical Interview and History Taking, Problem-Based Learning, Doctoring I, and Clinical Practice of Surgery ranged from 0.4 to 0.7, indicating that they were moderately related. The values between total MMI score and achievement in Research Overview, Technical and Procedural Skills, Clinical Performance Examinations 1 and 3, Clinical Practice of Laboratory Medicine and Psychiatry, Neurology, and Orthopedics ranged from 0.2 to 0.4, which meant that they were weakly related. MMI score can predict medical student' academic achievement in subjects in the medical humanities and clinical practice.

Maximum a posteriori Bayesian estimation of mycophenolic Acid area under the concentration-time curve: is this clinically useful for dosage prediction yet?

PubMed

Staatz, Christine E; Tett, Susan E

2011-12-01

This review seeks to summarize the available data about Bayesian estimation of area under the plasma concentration-time curve (AUC) and dosage prediction for mycophenolic acid (MPA) and evaluate whether sufficient evidence is available for routine use of Bayesian dosage prediction in clinical practice. A literature search identified 14 studies that assessed the predictive performance of maximum a posteriori Bayesian estimation of MPA AUC and one report that retrospectively evaluated how closely dosage recommendations based on Bayesian forecasting achieved targeted MPA exposure. Studies to date have mostly been undertaken in renal transplant recipients, with limited investigation in patients treated with MPA for autoimmune disease or haematopoietic stem cell transplantation. All of these studies have involved use of the mycophenolate mofetil (MMF) formulation of MPA, rather than the enteric-coated mycophenolate sodium (EC-MPS) formulation. Bias associated with estimation of MPA AUC using Bayesian forecasting was generally less than 10%. However some difficulties with imprecision was evident, with values ranging from 4% to 34% (based on estimation involving two or more concentration measurements). Evaluation of whether MPA dosing decisions based on Bayesian forecasting (by the free website service https://pharmaco.chu-limoges.fr) achieved target drug exposure has only been undertaken once. When MMF dosage recommendations were applied by clinicians, a higher proportion (72-80%) of subsequent estimated MPA AUC values were within the 30-60 mg · h/L target range, compared with when dosage recommendations were not followed (only 39-57% within target range). Such findings provide evidence that Bayesian dosage prediction is clinically useful for achieving target MPA AUC. This study, however, was retrospective and focussed only on adult renal transplant recipients. Furthermore, in this study, Bayesian-generated AUC estimations and dosage predictions were not compared with a later full measured AUC but rather with a further AUC estimate based on a second Bayesian analysis. This study also provided some evidence that a useful monitoring schedule for MPA AUC following adult renal transplant would be every 2 weeks during the first month post-transplant, every 1-3 months between months 1 and 12, and each year thereafter. It will be interesting to see further validations in different patient groups using the free website service. In summary, the predictive performance of Bayesian estimation of MPA, comparing estimated with measured AUC values, has been reported in several studies. However, the next step of predicting dosages based on these Bayesian-estimated AUCs, and prospectively determining how closely these predicted dosages give drug exposure matching targeted AUCs, remains largely unaddressed. Further prospective studies are required, particularly in non-renal transplant patients and with the EC-MPS formulation. Other important questions remain to be answered, such as: do Bayesian forecasting methods devised to date use the best population pharmacokinetic models or most accurate algorithms; are the methods simple to use for routine clinical practice; do the algorithms actually improve dosage estimations beyond empirical recommendations in all groups that receive MPA therapy; and, importantly, do the dosage predictions, when followed, improve patient health outcomes?

Modeling of venturi scrubber efficiency

NASA Astrophysics Data System (ADS)

Crowder, Jerry W.; Noll, Kenneth E.; Davis, Wayne T.

The parameters affecting venturi scrubber performance have been rationally examined and modifications to the current modeling theory have been developed. The modified model has been validated with available experimental data for a range of throat gas velocities, liquid-to-gas ratios and particle diameters and is used to study the effect of some design parameters on collection efficiency. Most striking among the observations is the prediction of a new design parameter termed the minimum contactor length. Also noted is the prediction of little effect on collection efficiency with increasing liquid-to-gas ratio above about 2ℓ m-3. Indeed, for some cases a decrease in collection efficiency is predicted for liquid rates above this value.

Statistically Based Approach to Broadband Liner Design and Assessment

NASA Technical Reports Server (NTRS)

Jones, Michael G. (Inventor); Nark, Douglas M. (Inventor)

2016-01-01

A broadband liner design optimization includes utilizing in-duct attenuation predictions with a statistical fan source model to obtain optimum impedance spectra over a number of flow conditions for one or more liner locations in a bypass duct. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners having impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increasing weighting to specific frequencies and/or operating conditions. One or more broadband design approaches are utilized to produce a broadband liner that targets a full range of frequencies and operating conditions.

Milgromian dynamics and dwarf galaxies in galactic voids

NASA Astrophysics Data System (ADS)

Khadem, Mahdi; Haghi, Hosein

2018-05-01

We use kinematic data of 103 dwarf galaxies, obtained from the Sloan Digital Sky Survey catalog, to test the Milgromian dynamics (MOND) inside a galactic void. From this data, we compute the line-of-sight velocity dispersions of the dwarf galaxies in the frameworks of MOND and Newtonian dynamics without invoking any dark matter. The prediction for the line-of-sight velocity dispersions from MOND of 53 selected dwarf galaxies is compared with their measured values. For appropriate mass-to-light ratios in the range 1 to 5 for each individual dwarf galaxy, our results for the line-of-sight velocity dispersions predicted by MOND are more compatible with observations than those predicted by Newtonian dynamics.

[Application of decision curve on evaluation of MRI predictive model for early assessing pathological complete response to neoadjuvant therapy in breast cancer].

PubMed

He, Y J; Li, X T; Fan, Z Q; Li, Y L; Cao, K; Sun, Y S; Ouyang, T

2018-01-23

Objective: To construct a dynamic enhanced MR based predictive model for early assessing pathological complete response (pCR) to neoadjuvant therapy in breast cancer, and to evaluate the clinical benefit of the model by using decision curve. Methods: From December 2005 to December 2007, 170 patients with breast cancer treated with neoadjuvant therapy were identified and their MR images before neoadjuvant therapy and at the end of the first cycle of neoadjuvant therapy were collected. Logistic regression model was used to detect independent factors for predicting pCR and construct the predictive model accordingly, then receiver operating characteristic (ROC) curve and decision curve were used to evaluate the predictive model. Results: ΔArea(max) and Δslope(max) were independent predictive factors for pCR, OR =0.942 (95% CI : 0.918-0.967) and 0.961 (95% CI : 0.940-0.987), respectively. The area under ROC curve (AUC) for the constructed model was 0.886 (95% CI : 0.820-0.951). Decision curve showed that in the range of the threshold probability above 0.4, the predictive model presented increased net benefit as the threshold probability increased. Conclusions: The constructed predictive model for pCR is of potential clinical value, with an AUC>0.85. Meanwhile, decision curve analysis indicates the constructed predictive model has net benefit from 3 to 8 percent in the likely range of probability threshold from 80% to 90%.

Thermal inactivation of infectious pancreatic necrosis virus in a peptone-salt medium mimicking the water-soluble phase of hydrolyzed fish by-products.

PubMed

Nygaard, Halvor; Modahl, Ingebjørg; Myrmel, Mette

2012-04-01

Infectious pancreatic necrosis virus (IPNV) (serotype Sp) was exposed to temperatures between 60 and 90°C in a medium mimicking the water-soluble phase of hydrolyzed fish by-products. D values ranged from 290 to 0.5 min, and the z value was approximately 9.8°C. Addition of formic acid to create a pH 4 medium did not enhance heat inactivation. Predicted inactivation effects at different temperature-time combinations are provided.

Volatility in financial markets: stochastic models and empirical results

NASA Astrophysics Data System (ADS)

Miccichè, Salvatore; Bonanno, Giovanni; Lillo, Fabrizio; Mantegna, Rosario N.

2002-11-01

We investigate the historical volatility of the 100 most capitalized stocks traded in US equity markets. An empirical probability density function (pdf) of volatility is obtained and compared with the theoretical predictions of a lognormal model and of the Hull and White model. The lognormal model well describes the pdf in the region of low values of volatility whereas the Hull and White model better approximates the empirical pdf for large values of volatility. Both models fail in describing the empirical pdf over a moderately large volatility range.

Molecular absorption by atmospheric gases in the 100-1000 GHz region

NASA Astrophysics Data System (ADS)

Llewellyn-Jones, D. T.; Knight, R. J.

The two principal atmospheric absorbers in the near-mm wavelength region are oxygen and water vapor. In order to measure the degree of water vapor absorption with the required precision, a large untuned resonator was constructed, consisting of a copper cylindrical structure with a Q-value close to one million at 100 GHz. A comparison of observed absorption values with theoretical predictions show a marked discrepancy. Without laboratory measurements such as the present, existing atmospheric attenuation models are likely to be inaccurate and misleading, especially at the lower range of tropospheric temperatures.

Feasibility of dual-energy computed tomography in radiation therapy planning

NASA Astrophysics Data System (ADS)

Sheen, Heesoon; Shin, Han-Back; Cho, Sungkoo; Cho, Junsang; Han, Youngyih

2017-12-01

In this study, the noise level, effective atomic number ( Z eff), accuracy of the computed tomography (CT) number, and the CT number to the relative electron density EDconversion curve were estimated for virtual monochromatic energy and polychromatic energy. These values were compared to the theoretically predicted values to investigate the feasibility of the use of dual-energy CT in routine radiation therapy planning. The accuracies of the parameters were within the range of acceptability. These results can serve as a stepping stone toward the routine use of dual-energy CT in radiotherapy planning.

Ternary isocratic mobile phase optimization utilizing resolution Design Space based on retention time and peak width modeling.

PubMed

Kawabe, Takefumi; Tomitsuka, Toshiaki; Kajiro, Toshi; Kishi, Naoyuki; Toyo'oka, Toshimasa

2013-01-18

An optimization procedure of ternary isocratic mobile phase composition in the HPLC method using a statistical prediction model and visualization technique is described. In this report, two prediction models were first evaluated to obtain reliable prediction results. The retention time prediction model was constructed by modification from past respectable knowledge of retention modeling against ternary solvent strength changes. An excellent correlation between observed and predicted retention time was given in various kinds of pharmaceutical compounds by the multiple regression modeling of solvent strength parameters. The peak width of half height prediction model employed polynomial fitting of the retention time, because a linear relationship between the peak width of half height and the retention time was not obtained even after taking into account the contribution of the extra-column effect based on a moment method. Accurate prediction results were able to be obtained by such model, showing mostly over 0.99 value of correlation coefficient between observed and predicted peak width of half height. Then, a procedure to visualize a resolution Design Space was tried as the secondary challenge. An artificial neural network method was performed to link directly between ternary solvent strength parameters and predicted resolution, which were determined by accurate prediction results of retention time and a peak width of half height, and to visualize appropriate ternary mobile phase compositions as a range of resolution over 1.5 on the contour profile. By using mixtures of similar pharmaceutical compounds in case studies, we verified a possibility of prediction to find the optimal range of condition. Observed chromatographic results on the optimal condition mostly matched with the prediction and the average of difference between observed and predicted resolution were approximately 0.3. This means that enough accuracy for prediction could be achieved by the proposed procedure. Consequently, the procedure to search the optimal range of ternary solvent strength achieving an appropriate separation is provided by using the resolution Design Space based on accurate prediction. Copyright © 2012 Elsevier B.V. All rights reserved.

Computer modeling of obesity links theoretical energetic measures with experimental measures of fuel use for lean and obese men.

PubMed

Rossow, Heidi A; Calvert, C Chris

2014-10-01

The goal of this research was to use a computational model of human metabolism to predict energy metabolism for lean and obese men. The model is composed of 6 state variables representing amino acids, muscle protein, visceral protein, glucose, triglycerides, and fatty acids (FAs). Differential equations represent carbohydrate, amino acid, and FA uptake and output by tissues based on ATP creation and use for both lean and obese men. Model parameterization is based on data from previous studies. Results from sensitivity analyses indicate that model predictions of resting energy expenditure (REE) and respiratory quotient (RQ) are dependent on FA and glucose oxidation rates with the highest sensitivity coefficients (0.6, 0.8 and 0.43, 0.15, respectively, for lean and obese models). Metabolizable energy (ME) is influenced by ingested energy intake with a sensitivity coefficient of 0.98, and a phosphate-to-oxygen ratio by FA oxidation rate and amino acid oxidation rate (0.32, 0.24 and 0.55, 0.65 for lean and obese models, respectively). Simulations of previously published studies showed that the model is able to predict ME ranging from 6.6 to 9.3 with 0% differences between published and model values, and RQ ranging from 0.79 to 0.86 with 1% differences between published and model values. REEs >7 MJ/d are predicted with 6% differences between published and model values. Glucose oxidation increases by ∼0.59 mol/d, RQ increases by 0.03, REE increases by 2 MJ/d, and heat production increases by 1.8 MJ/d in the obese model compared with lean model simulations. Increased FA oxidation results in higher changes in RQ and lower relative changes in REE. These results suggest that because fat mass is directly related to REE and rate of FA oxidation, body fat content could be used as a predictor of RQ. © 2014 American Society for Nutrition.

Building beef cow nutritional programs with the 1996 NRC beef cattle requirements model.

PubMed

Lardy, G P; Adams, D C; Klopfenstein, T J; Patterson, H H

2004-01-01

Designing a sound cow-calf nutritional program requires knowledge of nutrient requirements, diet quality, and intake. Effectively using the NRC (1996) beef cattle requirements model (1996NRC) also requires knowledge of dietary degradable intake protein (DIP) and microbial efficiency. Objectives of this paper are to 1) describe a framework in which 1996NRC-applicable data can be generated, 2) describe seasonal changes in nutrients on native range, 3) use the 1996NRC to predict nutrient balance for cattle grazing these forages, and 4) make recommendations for using the 1996NRC for forage-fed cattle. Extrusa samples were collected over 2 yr on native upland range and subirrigated meadow in the Nebraska Sandhills. Samples were analyzed for CP, in vitro OM digestibility (IVOMD), and DIP. Regression equations to predict nutrients were developed from these data. The 1996NRC was used to predict nutrient balances based on the dietary nutrient analyses. Recommendations for model users were also developed. On subirrigated meadow, CP and IVOMD increased rapidly during March and April. On native range, CP and IVOMD increased from April through June but decreased rapidly from August through September. Degradable intake protein (DM basis) followed trends similar to CP for both native range and subirrigated meadow. Predicted nutrient balances for spring- and summer-calving cows agreed with reported values in the literature, provided that IVOMD values were converted to DE before use in the model (1.07 x IVOMD - 8.13). When the IVOMD-to-DE conversion was not used, the model gave unrealistically high NE(m) balances. To effectively use the 1996NRC to estimate protein requirements, users should focus on three key estimates: DIP, microbial efficiency, and TDN intake. Consequently, efforts should be focused on adequately describing seasonal changes in forage nutrient content. In order to increase use of the 1996NRC, research is needed in the following areas: 1) cost-effective and accurate commercial laboratory procedures to estimate DIP, 2) reliable estimates or indicators of microbial efficiency for various forage types and qualities, 3) improved estimates of dietary TDN for forage-based diets, 4) validation work to improve estimates of DIP and MP requirements, and 5) incorporation of nitrogen recycling estimates.

Integrating spatial modeling, climate change scenarios, invasive species risk, and public perceptions to inform sustainable management in mixed hemlock-hardwood forests in Maine

NASA Astrophysics Data System (ADS)

Dunckel, Kathleen Lois

Introduced invasive pests and climate change are perhaps the most important and persistent catalyst for changes in forest composition. Infestation and outbreak of the hemlock woolly adelgid (HWA, Adelges tsugae) along the eastern coast of the USA, has led to widespread loss of hemlock (Tsuga canadensis (L.) Carr.), and a shift in tree species composition towards hardwood stands. Maine's forest dominated landscape and position at the leading edge of the HWA invasion provides an excellent opportunity to inform sustainable forest management (SFM) practices by using spatially explicit models to predict current tree species distribution, future range shifts, and solicit broad based feedback from Maine residents about forest management goals and preferences. This paper describes an interdisciplinary study of the ecological and social implications of changes in mixed northern hardwood forests due to disturbance. A two stage mapping approach was used where presence/absence of eastern hemlock is predicted with an overall accuracy of 85% and the continuous distribution (% basal area) was predicted with an accuracy of 83%. Given the importance of climate variables in predicting eastern hemlock, forecasts of future range shifts are possible using data generated through climate scenarios. The NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset was used to model future shifts in the geographic range of eastern hemlock throughout the state of Maine. The results clearly describe a significant shift in eastern hemlock range with gains in total geographic area that is suitable habitat. Sustaining forest systems across the landscape requires not only ecological knowledge, but also the integration of multiple socio-economic criteria as well, including data obtained through broad-based public participation approaches. Here, 3000 Maine residents were surveyed and asked how they: (1) value local forests; (2) view forest management goals and threats to forest ecosystems; and (3) evaluate alternative treatment options for the control of invasive species - in this case, HWA. Results suggest that despite Maine's historic dependence on forest products, resident values regarding forests are complex and display agreement with both psycho-spiritual and anthropocentric motivations.

Measurement of photoemission and secondary emission from laboratory dust grains

NASA Technical Reports Server (NTRS)

Hazelton, Robert C.; Yadlowsky, Edward J.; Settersten, Thomas B.; Spanjers, Gregory G.; Moschella, John J.

1995-01-01

The overall goal of this project is experimentally determine the emission properties of dust grains in order to provide theorists and modelers with an accurate data base to use in codes that predict the charging of grains in various plasma environments encountered in the magnetospheres of the planets. In general these modelers use values which have been measured on planar, bulk samples of the materials in question. The large enhancements expected due to the small size of grains can have a dramatic impact upon the predictions and the ultimate utility of these predictions. The first experimental measurement of energy resolved profiles of the secondary electron emission coefficient, 6, of sub-micron diameter particles has been accomplished. Bismuth particles in the size range of .022 to .165 micrometers were generated in a moderate pressure vacuum oven (average size is a function of oven temperature and pressure) and introduced into a high vacuum chamber where they interacted with a high energy electron beam (0.4 to 20 keV). Large enhancements in emission were observed with a peak value, delta(sub max) = 4. 5 measured for the ensemble of particles with a mean size of .022 micrometers. This is in contrast to the published value, delta(sub max) = 1.2, for bulk bismuth. The observed profiles are in general agreement with recent theoretical predictions made by Chow et al. at UCSD.

A transient dopamine signal encodes subjective value and causally influences demand in an economic context

PubMed Central

Schelp, Scott A.; Pultorak, Katherine J.; Rakowski, Dylan R.; Gomez, Devan M.; Krzystyniak, Gregory; Das, Raibatak; Oleson, Erik B.

2017-01-01

The mesolimbic dopamine system is strongly implicated in motivational processes. Currently accepted theories suggest that transient mesolimbic dopamine release events energize reward seeking and encode reward value. During the pursuit of reward, critical associations are formed between the reward and cues that predict its availability. Conditioned by these experiences, dopamine neurons begin to fire upon the earliest presentation of a cue, and again at the receipt of reward. The resulting dopamine concentration scales proportionally to the value of the reward. In this study, we used a behavioral economics approach to quantify how transient dopamine release events scale with price and causally alter price sensitivity. We presented sucrose to rats across a range of prices and modeled the resulting demand curves to estimate price sensitivity. Using fast-scan cyclic voltammetry, we determined that the concentration of accumbal dopamine time-locked to cue presentation decreased with price. These data confirm and extend the notion that dopamine release events originating in the ventral tegmental area encode subjective value. Using optogenetics to augment dopamine concentration, we found that enhancing dopamine release at cue made demand more sensitive to price and decreased dopamine concentration at reward delivery. From these observations, we infer that value is decreased because of a negative reward prediction error (i.e., the animal receives less than expected). Conversely, enhancing dopamine at reward made demand less sensitive to price. We attribute this finding to a positive reward prediction error, whereby the animal perceives they received a better value than anticipated. PMID:29109253

An Improved Method of Predicting Extinction Coefficients for the Determination of Protein Concentration.

PubMed

Hilario, Eric C; Stern, Alan; Wang, Charlie H; Vargas, Yenny W; Morgan, Charles J; Swartz, Trevor E; Patapoff, Thomas W

2017-01-01

Concentration determination is an important method of protein characterization required in the development of protein therapeutics. There are many known methods for determining the concentration of a protein solution, but the easiest to implement in a manufacturing setting is absorption spectroscopy in the ultraviolet region. For typical proteins composed of the standard amino acids, absorption at wavelengths near 280 nm is due to the three amino acid chromophores tryptophan, tyrosine, and phenylalanine in addition to a contribution from disulfide bonds. According to the Beer-Lambert law, absorbance is proportional to concentration and path length, with the proportionality constant being the extinction coefficient. Typically the extinction coefficient of proteins is experimentally determined by measuring a solution absorbance then experimentally determining the concentration, a measurement with some inherent variability depending on the method used. In this study, extinction coefficients were calculated based on the measured absorbance of model compounds of the four amino acid chromophores. These calculated values for an unfolded protein were then compared with an experimental concentration determination based on enzymatic digestion of proteins. The experimentally determined extinction coefficient for the native proteins was consistently found to be 1.05 times the calculated value for the unfolded proteins for a wide range of proteins with good accuracy and precision under well-controlled experimental conditions. The value of 1.05 times the calculated value was termed the predicted extinction coefficient. Statistical analysis shows that the differences between predicted and experimentally determined coefficients are scattered randomly, indicating no systematic bias between the values among the proteins measured. The predicted extinction coefficient was found to be accurate and not subject to the inherent variability of experimental methods. We propose the use of a predicted extinction coefficient for determining the protein concentration of therapeutic proteins starting from early development through the lifecycle of the product. LAY ABSTRACT: Knowing the concentration of a protein in a pharmaceutical solution is important to the drug's development and posology. There are many ways to determine the concentration, but the easiest one to use in a testing lab employs absorption spectroscopy. Absorbance of ultraviolet light by a protein solution is proportional to its concentration and path length; the proportionality constant is the extinction coefficient. The extinction coefficient of a protein therapeutic is usually determined experimentally during early product development and has some inherent method variability. In this study, extinction coefficients of several proteins were calculated based on the measured absorbance of model compounds. These calculated values for an unfolded protein were then compared with experimental concentration determinations based on enzymatic digestion of the proteins. The experimentally determined extinction coefficient for the native protein was 1.05 times the calculated value for the unfolded protein with good accuracy and precision under controlled experimental conditions, so the value of 1.05 times the calculated coefficient was called the predicted extinction coefficient. Comparison of predicted and measured extinction coefficients indicated that the predicted value was very close to the experimentally determined values for the proteins. The predicted extinction coefficient was accurate and removed the variability inherent in experimental methods. © PDA, Inc. 2017.

Using vegetation cover type to predict and scale peatland methane dynamics.

NASA Astrophysics Data System (ADS)

McArthur, K. J.; McCalley, C. K.; Palace, M. W.; Varner, R. K.; Herrick, C.; DelGreco, J. L.

2015-12-01

Permafrost ecosystems contain about 50% of the global soil carbon. As these northern ecosystems experience warmer temperature, permafrost thaws and may result in an increase in atmospheric methane. We examined a thawing and discontinuous permafrost boundary at Stordalen Mire, in Northern Sweden, in an effort to better understand methane emissions. Stable isotope analysis of methane in peatland porewater can give insights into the pathway of methane production. By measuring δ13CH4 we can predict whether a system is dominated by either hydrogenotrophic or acetaclastic methane production. Currently, it is a challenge to scale these isotopic patterns, thus, atmospheric inversion models simply assume that acetoclastic production dominates. We analyzed porewater samples collected across a range of vegetation cover types for δ13CH4 using a QCL (Quantum Cascade Laser Spectrometer) in conjunction with highly accurate GPS (3-10cm) measurements and high-resolution UAV imaging. We found δ13CH4 values ranging from -88‰ to -41‰, with averages based on cover type and other vegetation features showing differences of up to -15‰. We then used a computer neural network to predict cover types across Stordalen Mire from UAV imagery based on field-based plot measurements and training samples.. This prediction map was used to scale methane flux and isotope measurements. Our results suggest that the current values used in atmospheric inversion studies may oversimplify the relationship between plant and microbial communities in complex permafrost landscapes. As we gain a deeper understanding of how vegetation relates to methanogenic communities, understanding the spatial component of ecosystem methane metabolism and distribution will be increasingly valuable.

Rapid determination of biogenic amines in cooked beef using hyperspectral imaging with sparse representation algorithm

NASA Astrophysics Data System (ADS)

Yang, Dong; Lu, Anxiang; Ren, Dong; Wang, Jihua

2017-11-01

This study explored the feasibility of rapid detection of biogenic amines (BAs) in cooked beef during the storage process using hyperspectral imaging technique combined with sparse representation (SR) algorithm. The hyperspectral images of samples were collected in the two spectral ranges of 400-1000 nm and 1000-1800 nm, separately. The spectral data were reduced dimensionality by SR and principal component analysis (PCA) algorithms, and then integrated the least square support vector machine (LS-SVM) to build the SR-LS-SVM and PC-LS-SVM models for the prediction of BAs values in cooked beef. The results showed that the SR-LS-SVM model exhibited the best predictive ability with determination coefficients (RP2) of 0.943 and root mean square errors (RMSEP) of 1.206 in the range of 400-1000 nm of prediction set. The SR and PCA algorithms were further combined to establish the best SR-PC-LS-SVM model for BAs prediction, which had high RP2of 0.969 and low RMSEP of 1.039 in the region of 400-1000 nm. The visual map of the BAs was generated using the best SR-PC-LS-SVM model with imaging process algorithms, which could be used to observe the changes of BAs in cooked beef more intuitively. The study demonstrated that hyperspectral imaging technique combined with sparse representation were able to detect effectively the BAs values in cooked beef during storage and the built SR-PC-LS-SVM model had a potential for rapid and accurate determination of freshness indexes in other meat and meat products.

Suitability of parametric models to describe the hydraulic properties of an unsaturated coarse sand and gravel

USGS Publications Warehouse

Mace, Andy; Rudolph, David L.; Kachanoski , R. Gary

1998-01-01

The performance of parametric models used to describe soil water retention (SWR) properties and predict unsaturated hydraulic conductivity (K) as a function of volumetric water content (θ) is examined using SWR and K(θ) data for coarse sand and gravel sediments. Six 70 cm long, 10 cm diameter cores of glacial outwash were instrumented at eight depths with porous cup ten-siometers and time domain reflectometry probes to measure soil water pressure head (h) and θ, respectively, for seven unsaturated and one saturated steady-state flow conditions. Forty-two θ(h) and K(θ) relationships were measured from the infiltration tests on the cores. Of the four SWR models compared in the analysis, the van Genuchten (1980) equation with parameters m and n restricted according to the Mualem (m = 1 - 1/n) criterion is best suited to describe the θ(h) relationships. The accuracy of two models that predict K(θ) using parameter values derived from the SWR models was also evaluated. The model developed by van Genuchten (1980) based on the theoretical expression of Mualem (1976) predicted K(θ) more accurately than the van Genuchten (1980) model based on the theory of Burdine (1953). A sensitivity analysis shows that more accurate predictions of K(θ) are achieved using SWR model parameters derived with residual water content (θr) specified according to independent measurements of θ at values of h where θ/h ∼ 0 rather than model-fit θr values. The accuracy of the model K(θ) function improves markedly when at least one value of unsaturated K is used to scale the K(θ) function predicted using the saturated K. The results of this investigation indicate that the hydraulic properties of coarse-grained sediments can be accurately described using the parametric models. In addition, data collection efforts should focus on measuring at least one value of unsaturated hydraulic conductivity and as complete a set of SWR data as possible, particularly in the dry range.

Arthroscopic and magnetic resonance imaging evaluation of meniscus lesions in the chronic anterior cruciate ligament-deficient knee.

PubMed

Naranje, Sameer; Mittal, Ravi; Nag, Hiralal; Sharma, Raju

2008-09-01

We performed this prospective study to evaluate the incidence of meniscus tears arthroscopically and the effectiveness of magnetic resonance imaging (MRI) in detecting these lesions in patients with chronic anterior cruciate ligament (ACL)-deficient knees. We reviewed 50 patients (46 male and 4 female) with a mean age of 27 years (range, 18 to 48 years) who underwent ACL reconstruction for chronic ACL tears. Injuries were classified as chronic because arthroscopy was performed after more than 6 weeks of injury. All 50 patients had clinical and MRI evaluation followed by knee arthroscopy. The MRI and arthroscopic findings were then analyzed by a single independent reviewer. The presence of meniscus tears and their morphologic types and locations were analyzed. The sensitivity, specificity, positive predictive value, and negative predictive value of MRI were calculated. On arthroscopy, a medial meniscus tear was found in 18 patients (36%), a lateral meniscus tear was found in 11 patients (22%), both menisci were torn in 8 patients (16%), and no meniscus lesion was found in 13 patients (26%). The most common morphologic type of tear seen in the medial meniscus was "complex" (n = 11 [42%]), and that in the lateral meniscus was "longitudinal" (n = 10 [53%]). The posterior horn of the meniscus was the most common tear site. The overall sensitivity, specificity, positive predictive value, and negative predictive value for detecting meniscus tears in chronic ACL-deficient knees on MRI were 90%, 89%, 87%, 93%, respectively. We conclude from our study that in chronic ACL-deficient patients, the prevalence of posterior horn medial meniscus tears seems to be high. Anterior horn tears and radial and horizontal patterns of meniscus tears seem to be rare in chronic ACL deficiency. MRI correlates well with arthroscopy and has high negative predictive values. Level I, prognostic prospective study.

Frailty Screening Tools for Elderly Patients Incident to Dialysis.

PubMed

van Loon, Ismay N; Goto, Namiko A; Boereboom, Franciscus T J; Bots, Michiel L; Verhaar, Marianne C; Hamaker, Marije E

2017-09-07

A geriatric assessment is an appropriate method for identifying frail elderly patients. In CKD, it may contribute to optimize personalized care. However, a geriatric assessment is time consuming. The purpose of our study was to compare easy to apply frailty screening tools with the geriatric assessment in patients eligible for dialysis. A total of 123 patients on incident dialysis ≥65 years old were included <3 weeks before to ≤2 weeks after dialysis initiation, and all underwent a geriatric assessment. Patients with impairment in two or more geriatric domains on the geriatric assessment were considered frail. The diagnostic abilities of six frailty screening tools were compared with the geriatric assessment: the Fried Frailty Index, the Groningen Frailty Indicator, Geriatric8, the Identification of Seniors at Risk, the Hospital Safety Program, and the clinical judgment of the nephrologist. Outcome measures were sensitivity, specificity, positive predictive value, and negative predictive value. In total, 75% of patients were frail according to the geriatric assessment. Sensitivity of frailty screening tools ranged from 48% (Fried Frailty Index) to 88% (Geriatric8). The discriminating features of the clinical judgment were comparable with the other screening tools. The Identification of Seniors at Risk screening tool had the best discriminating abilities, with a sensitivity of 74%, a specificity of 80%, a positive predictive value of 91%, and a negative predictive value of 52%. The negative predictive value was poor for all tools, which means that almost one half of the patients screened as fit (nonfrail) had two or more geriatric impairments on the geriatric assessment. All frailty screening tools are able to detect geriatric impairment in elderly patients eligible for dialysis. However, all applied screening tools, including the judgment of the nephrologist, lack the discriminating abilities to adequately rule out frailty compared with a geriatric assessment. Copyright © 2017 by the American Society of Nephrology.

Modeling of temperature-induced near-infrared and low-field time-domain nuclear magnetic resonance spectral variation: chemometric prediction of limonene and water content in spray-dried delivery systems.

PubMed

Andrade, Letícia; Farhat, Imad A; Aeberhardt, Kasia; Bro, Rasmus; Engelsen, Søren Balling

2009-02-01

The influence of temperature on near-infrared (NIR) and nuclear magnetic resonance (NMR) spectroscopy complicates the industrial applications of both spectroscopic methods. The focus of this study is to analyze and model the effect of temperature variation on NIR spectra and NMR relaxation data. Different multivariate methods were tested for constructing robust prediction models based on NIR and NMR data acquired at various temperatures. Data were acquired on model spray-dried limonene systems at five temperatures in the range from 20 degrees C to 60 degrees C and partial least squares (PLS) regression models were computed for limonene and water predictions. The predictive ability of the models computed on the NIR spectra (acquired at various temperatures) improved significantly when data were preprocessed using extended inverted signal correction (EISC). The average PLS regression prediction error was reduced to 0.2%, corresponding to 1.9% and 3.4% of the full range of limonene and water reference values, respectively. The removal of variation induced by temperature prior to calibration, by direct orthogonalization (DO), slightly enhanced the predictive ability of the models based on NMR data. Bilinear PLS models, with implicit inclusion of the temperature, enabled limonene and water predictions by NMR with an error of 0.3% (corresponding to 2.8% and 7.0% of the full range of limonene and water). For NMR, and in contrast to the NIR results, modeling the data using multi-way N-PLS improved the models' performance. N-PLS models, in which temperature was included as an extra variable, enabled more accurate prediction, especially for limonene (prediction error was reduced to 0.2%). Overall, this study proved that it is possible to develop models for limonene and water content prediction based on NIR and NMR data, independent of the measurement temperature.

Orbital Signature Analyzer (OSA): A spacecraft health/safety monitoring and analysis tool

NASA Technical Reports Server (NTRS)

Weaver, Steven; Degeorges, Charles; Bush, Joy; Shendock, Robert; Mandl, Daniel

1993-01-01

Fixed or static limit sensing is employed in control centers to ensure that spacecraft parameters remain within a nominal range. However, many critical parameters, such as power system telemetry, are time-varying and, as such, their 'nominal' range is necessarily time-varying as well. Predicted data, manual limits checking, and widened limit-checking ranges are often employed in an attempt to monitor these parameters without generating excessive limits violations. Generating predicted data and manual limits checking are both resource intensive, while broadening limit ranges for time-varying parameters is clearly inadequate to detect all but catastrophic problems. OSA provides a low-cost solution by using analytically selected data as a reference upon which to base its limits. These limits are always defined relative to the time-varying reference data, rather than as fixed upper and lower limits. In effect, OSA provides individual limits tailored to each value throughout all the data. A side benefit of using relative limits is that they automatically adjust to new reference data. In addition, OSA provides a wealth of analytical by-products in its execution.

Stretched size of atrial septal defect predicted by intracardiac echocardiography.

PubMed

Lin, Ming-Chih; Fu, Yun-Ching; Jan, Sheng-Ling; Ho, Chi-Lin; Hwang, Betau

2010-01-01

The stretched size of an atrial septal defect (ASD) is important for device selection during transcatheter closure. However, balloon sizing carries potential risks such as hypotension, bradycardia, or laceration of the atrial septum. The aim of the present study was to investigate the accuracy of the predicted stretched size of ASD by intracardiac echocardiography (ICE). From December 2004 to November 2007, 136 consecutive patients with single secundum type ASD undergoing transcatheter closure of their defect using the Amplatzer septal occluder under ICE guidance were enrolled for analysis. There were 43 males and 93 females. The age ranged from 2.2 to 79.1 years with a median age of 13.4 years. The body weight ranged from 12.1 to 93.2 kg with a median body weight of 45.8 kg. The stretched size of ASD measured by a sizing plate was considered as the standard. ASD sizes measured by ICE in bicaval and short-axis views predicted the stretched size by formulae derived from linear regressions. The predicted stretched sizes obtained using 2 formulae, 1.34 x radicalbicaval xshort axis (formula 1) and 1.22 x larger diameter (formula 2), exhibited good agreement with the standard stretched size with Kappa values of 0.91 and 0.90, respectively. The accuracy rate of predicted stretched sizes within 2 mm, 3 mm, and 4 mm range of the standard size were 32.8%, 45.4%, and 57.7% (formula 1) and 33.1%, 50%, and 63.2% (formula 2). The stretched size of ASD predicted by ICE exhibited good agreement with the standard stretched size. This prediction provides helpful information, especially if balloon sizing cannot be adequately performed.

CYP3A4 substrate selection and substitution in the prediction of potential drug-drug interactions.

PubMed

Galetin, Aleksandra; Ito, Kiyomi; Hallifax, David; Houston, J Brian

2005-07-01

The complexity of in vitro kinetic phenomena observed for CYP3A4 substrates (homo- or heterotropic cooperativity) confounds the prediction of drug-drug interactions, and an evaluation of alternative and/or pragmatic approaches and substrates is needed. The current study focused on the utility of the three most commonly used CYP3A4 in vitro probes for the prediction of 26 reported in vivo interactions with azole inhibitors (increase in area under the curve ranged from 1.2 to 24, 50% in the range of potent inhibition). In addition to midazolam, testosterone, and nifedipine, quinidine was explored as a more "pragmatic" substrate due to its kinetic properties and specificity toward CYP3A4 in comparison with CYP3A5. Ki estimates obtained in human liver microsomes under standardized in vitro conditions for each of the four probes were used to determine the validity of substrate substitution in CYP3A4 drug-drug interaction prediction. Detailed inhibitor-related (microsomal binding, depletion over incubation time) and substrate-related factors (cooperativity, contribution of other metabolic pathways, or renal excretion) were incorporated in the assessment of the interaction potential. All four CYP3A4 probes predicted 69 to 81% of the interactions with azoles within 2-fold of the mean in vivo value. Comparison of simple and multisite mechanistic models and interaction prediction accuracy for each of the in vitro probes indicated that midazolam and quinidine in vitro data provided the best assessment of a potential interaction, with the lowest bias and the highest precision of the prediction. Further investigations with a wider range of inhibitors are required to substantiate these findings.

Predictive accuracy of risk scales following self-harm: multicentre, prospective cohort study†

PubMed Central

Quinlivan, Leah; Cooper, Jayne; Meehan, Declan; Longson, Damien; Potokar, John; Hulme, Tom; Marsden, Jennifer; Brand, Fiona; Lange, Kezia; Riseborough, Elena; Page, Lisa; Metcalfe, Chris; Davies, Linda; O'Connor, Rory; Hawton, Keith; Gunnell, David; Kapur, Nav

2017-01-01

Background Scales are widely used in psychiatric assessments following self-harm. Robust evidence for their diagnostic use is lacking. Aims To evaluate the performance of risk scales (Manchester Self-Harm Rule, ReACT Self-Harm Rule, SAD PERSONS scale, Modified SAD PERSONS scale, Barratt Impulsiveness Scale); and patient and clinician estimates of risk in identifying patients who repeat self-harm within 6 months. Method A multisite prospective cohort study was conducted of adults aged 18 years and over referred to liaison psychiatry services following self-harm. Scale a priori cut-offs were evaluated using diagnostic accuracy statistics. The area under the curve (AUC) was used to determine optimal cut-offs and compare global accuracy. Results In total, 483 episodes of self-harm were included in the study. The episode-based 6-month repetition rate was 30% (n = 145). Sensitivity ranged from 1% (95% CI 0–5) for the SAD PERSONS scale, to 97% (95% CI 93–99) for the Manchester Self-Harm Rule. Positive predictive values ranged from 13% (95% CI 2–47) for the Modified SAD PERSONS Scale to 47% (95% CI 41–53) for the clinician assessment of risk. The AUC ranged from 0.55 (95% CI 0.50–0.61) for the SAD PERSONS scale to 0.74 (95% CI 0.69–0.79) for the clinician global scale. The remaining scales performed significantly worse than clinician and patient estimates of risk (P<0.001). Conclusions Risk scales following self-harm have limited clinical utility and may waste valuable resources. Most scales performed no better than clinician or patient ratings of risk. Some performed considerably worse. Positive predictive values were modest. In line with national guidelines, risk scales should not be used to determine patient management or predict self-harm. PMID:28302702

Predictive accuracy of risk scales following self-harm: multicentre, prospective cohort study.

PubMed

Quinlivan, Leah; Cooper, Jayne; Meehan, Declan; Longson, Damien; Potokar, John; Hulme, Tom; Marsden, Jennifer; Brand, Fiona; Lange, Kezia; Riseborough, Elena; Page, Lisa; Metcalfe, Chris; Davies, Linda; O'Connor, Rory; Hawton, Keith; Gunnell, David; Kapur, Nav

2017-06-01

Background Scales are widely used in psychiatric assessments following self-harm. Robust evidence for their diagnostic use is lacking. Aims To evaluate the performance of risk scales (Manchester Self-Harm Rule, ReACT Self-Harm Rule, SAD PERSONS scale, Modified SAD PERSONS scale, Barratt Impulsiveness Scale); and patient and clinician estimates of risk in identifying patients who repeat self-harm within 6 months. Method A multisite prospective cohort study was conducted of adults aged 18 years and over referred to liaison psychiatry services following self-harm. Scale a priori cut-offs were evaluated using diagnostic accuracy statistics. The area under the curve (AUC) was used to determine optimal cut-offs and compare global accuracy. Results In total, 483 episodes of self-harm were included in the study. The episode-based 6-month repetition rate was 30% ( n = 145). Sensitivity ranged from 1% (95% CI 0-5) for the SAD PERSONS scale, to 97% (95% CI 93-99) for the Manchester Self-Harm Rule. Positive predictive values ranged from 13% (95% CI 2-47) for the Modified SAD PERSONS Scale to 47% (95% CI 41-53) for the clinician assessment of risk. The AUC ranged from 0.55 (95% CI 0.50-0.61) for the SAD PERSONS scale to 0.74 (95% CI 0.69-0.79) for the clinician global scale. The remaining scales performed significantly worse than clinician and patient estimates of risk ( P <0.001). Conclusions Risk scales following self-harm have limited clinical utility and may waste valuable resources. Most scales performed no better than clinician or patient ratings of risk. Some performed considerably worse. Positive predictive values were modest. In line with national guidelines, risk scales should not be used to determine patient management or predict self-harm. © The Royal College of Psychiatrists 2017.

Novel opportunities for computational biology and sociology in drug discovery

PubMed Central

Yao, Lixia

2009-01-01

Drug discovery today is impossible without sophisticated modeling and computation. In this review we touch on previous advances in computational biology and by tracing the steps involved in pharmaceutical development, we explore a range of novel, high value opportunities for computational innovation in modeling the biological process of disease and the social process of drug discovery. These opportunities include text mining for new drug leads, modeling molecular pathways and predicting the efficacy of drug cocktails, analyzing genetic overlap between diseases and predicting alternative drug use. Computation can also be used to model research teams and innovative regions and to estimate the value of academy-industry ties for scientific and human benefit. Attention to these opportunities could promise punctuated advance, and will complement the well-established computational work on which drug discovery currently relies. PMID:19674801

Prediction of pH-dependent properties of DNA triple helices.

PubMed

Hüsler, P L; Klump, H H

1995-02-20

The thermodynamic properties of two triple helices were investigated by uv thermal denaturation, differential scanning calorimetry, and pH titrations. Starting from the grand partition function and using matrix methods we present a formalism that describes pH effects on the thermal stability of triple helices. The formalism can be used over a wide pH range and is not restricted to the limiting case where the pH is larger or smaller than the pK alpha of cytosine. Furthermore, it covers nearest neighbor electrostatic effects of closely spaced cytosines in the Hoogsteen strand which can shift the pK alpha of cytosine to lower pH values. A procedure is employed to predict enthalpy and entropy changes for triplex formation. These values are in accordance with the results obtained by differential scanning calorimetry.

Wind tunnel wall effects in a linear oscillating cascade

NASA Technical Reports Server (NTRS)

Buffum, Daniel H.; Fleeter, Sanford

1991-01-01

Experiments in a linear oscillating cascade reveal that the wind tunnel walls enclosing the airfoils have, in some cases, a detrimental effect on the oscillating cascade aerodynamics. In a subsonic flow field, biconvex airfoils are driven simultaneously in harmonic, torsion-mode oscillations for a range of interblade phase angle values. It is found that the cascade dynamic periodicity - the airfoil to airfoil variation in unsteady surface pressure - is good for some values of interblade phase angle but poor for others. Correlation of the unsteady pressure data with oscillating flat plate cascade predictions is generally good for conditions where the periodicity is good and poor where the periodicity is poor. Calculations based upon linearized unsteady aerodynamic theory indicate that pressure waves reflected from the wind tunnel walls are responsible for the cases where there is poor periodicity and poor correlation with the predictions.

Application of fecal near-infrared spectroscopy and nutritional balance software to monitor diet quality and body condition in beef cows grazing Arizona rangeland.

PubMed

Tolleson, D R; Schafer, D W

2014-01-01

Monitoring the nutritional status of range cows is difficult. Near-infrared spectroscopy (NIRS) of feces has been used to predict diet quality in cattle. When fecal NIRS is coupled with decision support software such as the Nutritional Balance Analyzer (NUTBAL PRO), nutritional status and animal performance can be monitored. Approximately 120 Hereford and 90 CGC composite (50% Red Angus, 25% Tarentaise, and 25% Charolais) cows grazing in a single herd were used in a study to determine the ability of fecal NIRS and NutbalPro to project BCS (1 = thin and 9 = fat) under commercial scale rangeland conditions in central Arizona. Cattle were rotated across the 31,000 ha allotment at 10 to 20 d intervals. Cattle BCS and fecal samples (approximately 500 g) composited from 5 to 10 cows were collected in the pasture approximately monthly at the midpoint of each grazing period. Samples were frozen and later analyzed by NIRS for prediction of diet crude protein (CP) and digestible organic matter (DOM). Along with fecal NIRS predicted diet quality, animal breed type, reproductive status, and environmental conditions were input to the software for each fecal sampling and BCS date. Three different evaluations were performed. First, fecal NIRS and NutbalPro derived BCS was projected forward from each sampling as if it were a "one-time only" measurement. Second, BCS was derived from the average predicted weight change between 2 sampling dates for a given period. Third, inputs to the model were adjusted to better represent local animals and conditions. Fecal NIRS predicted diet quality varied from a minimum of approximately 5% CP and 57% DOM in winter to a maximum of approximately 11% CP and 60% DOM in summer. Diet quality correlated with observed seasonal changes and precipitation events. In evaluation 1, differences in observed versus projected BCS were not different (P > 0.1) between breed types but these values ranged from 0.1 to 1.1 BCS in Herefords and 0.0 to 0.9 in CGC. In evaluation 2, differences in observed versus projected BCS were not different (P > 0.1) between breed types but these values ranged from 0.00 to 0.46 in Hereford and 0.00 to 0.67 in CGC. In evaluation 3, the range of differences between observed and projected BCS was 0.04 to 0.28. The greatest difference in projected versus observed BCS occurred during periods of lowest diet quality. Body condition was predicted accurately enough to be useful in monitoring the nutrition of range beef cows under the conditions of this study.

Symbolic Numerical Distance Effect Does Not Reflect the Difference between Numbers.

PubMed

Krajcsi, Attila; Kojouharova, Petia

2017-01-01

In a comparison task, the larger the distance between the two numbers to be compared, the better the performance-a phenomenon termed as the numerical distance effect. According to the dominant explanation, the distance effect is rooted in a noisy representation, and performance is proportional to the size of the overlap between the noisy representations of the two values. According to alternative explanations, the distance effect may be rooted in the association between the numbers and the small-large categories, and performance is better when the numbers show relatively high differences in their strength of association with the small-large properties. In everyday number use, the value of the numbers and the association between the numbers and the small-large categories strongly correlate; thus, the two explanations have the same predictions for the distance effect. To dissociate the two potential sources of the distance effect, in the present study, participants learned new artificial number digits only for the values between 1 and 3, and between 7 and 9, thus, leaving out the numbers between 4 and 6. It was found that the omitted number range (the distance between 3 and 7) was considered in the distance effect as 1, and not as 4, suggesting that the distance effect does not follow the values of the numbers predicted by the dominant explanation, but it follows the small-large property association predicted by the alternative explanations.

On the Distribution of Protein Refractive Index Increments

PubMed Central

Zhao, Huaying; Brown, Patrick H.; Schuck, Peter

2011-01-01

The protein refractive index increment, dn/dc, is an important parameter underlying the concentration determination and the biophysical characterization of proteins and protein complexes in many techniques. In this study, we examine the widely used assumption that most proteins have dn/dc values in a very narrow range, and reappraise the prediction of dn/dc of unmodified proteins based on their amino acid composition. Applying this approach in large scale to the entire set of known and predicted human proteins, we obtain, for the first time, to our knowledge, an estimate of the full distribution of protein dn/dc values. The distribution is close to Gaussian with a mean of 0.190 ml/g (for unmodified proteins at 589 nm) and a standard deviation of 0.003 ml/g. However, small proteins <10 kDa exhibit a larger spread, and almost 3000 proteins have values deviating by more than two standard deviations from the mean. Due to the widespread availability of protein sequences and the potential for outliers, the compositional prediction should be convenient and provide greater accuracy than an average consensus value for all proteins. We discuss how this approach should be particularly valuable for certain protein classes where a high dn/dc is coincidental to structural features, or may be functionally relevant such as in proteins of the eye. PMID:21539801

An assessment of two-step linear regression and a multifactor probit analysis as alternatives to acute to chronic ratios in the estimation of chronic response from acute toxicity data to derive water quality guidelines.

PubMed

Slaughter, Andrew R; Palmer, Carolyn G; Muller, Wilhelmine J

2007-04-01

In aquatic ecotoxicology, acute to chronic ratios (ACRs) are often used to predict chronic responses from available acute data to derive water quality guidelines, despite many problems associated with this method. This paper explores the comparative protectiveness and accuracy of predicted guideline values derived from the ACR, linear regression analysis (LRA), and multifactor probit analysis (MPA) extrapolation methods applied to acute toxicity data for aquatic macroinvertebrates. Although the authors of the LRA and MPA methods advocate the use of extrapolated lethal effects in the 0.01% to 10% lethal concentration (LC0.01-LC10) range to predict safe chronic exposure levels to toxicants, the use of an extrapolated LC50 value divided by a safety factor of 5 was in addition explored here because of higher statistical confidence surrounding the LC50 value. The LRA LC50/5 method was found to compare most favorably with available experimental chronic toxicity data and was therefore most likely to be sufficiently protective, although further validation with the use of additional species is needed. Values derived by the ACR method were the least protective. It is suggested that there is an argument for the replacement of ACRs in developing water quality guidelines by the LRA LC50/5 method.